mobiledetnet object detection model removed as this is not the latest configuration

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/deploy.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/deploy.prototxt
deleted file mode 100755 (executable)
index 941284d..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/deploy.prototxt
+++ /dev/null
@@ -1,2373 +0,0 @@
-name: "mobiledetnet-0.5_deploy"
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 256
-  dim: 512
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
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-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
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-  top: "conv4_2/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
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-  type: "Convolution"
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-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
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-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/dw/scale"
-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
-  name: "conv6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
-  name: "conv6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
-  name: "ctx_output2/1x1"
-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/relu"
-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
-  name: "ctx_output3/1x1"
-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
-  name: "ctx_output3"
-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/relu"
-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19.0
-    max_size: 88.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output2"
-  bottom: "data"
-  top: "ctx_output2/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 88.0
-    max_size: 157.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_loc"
-  top: "ctx_output3/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_loc_perm"
-  top: "ctx_output3/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_conf"
-  top: "ctx_output3/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_conf_perm"
-  top: "ctx_output3/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output3"
-  bottom: "data"
-  top: "ctx_output3/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 157.0
-    max_size: 226.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_loc"
-  top: "ctx_output4/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_loc_perm"
-  top: "ctx_output4/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_conf"
-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_conf_perm"
-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output4"
-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 226.0
-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_reshape"
-  type: "Reshape"
-  bottom: "mbox_conf"
-  top: "mbox_conf_reshape"
-  reshape_param {
-    shape {
-      dim: 0
-      dim: -1
-      dim: 21
-    }
-  }
-}
-layer {
-  name: "mbox_conf_softmax"
-  type: "Softmax"
-  bottom: "mbox_conf_reshape"
-  top: "mbox_conf_softmax"
-  softmax_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_flatten"
-  type: "Flatten"
-  bottom: "mbox_conf_softmax"
-  top: "mbox_conf_flatten"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "detection_out"
-  type: "DetectionOutput"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf_flatten"
-  bottom: "mbox_priorbox"
-  top: "detection_out"
-  include {
-    phase: TEST
-  }
-  detection_output_param {
-    num_classes: 21
-    share_location: true
-    background_label_id: 0
-    nms_param {
-      nms_threshold: 0.45
-      top_k: 400
-    }
-    save_output_param {
-      output_directory: ""
-      output_name_prefix: "comp4_det_test_"
-      output_format: "VOC"
-      label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-      name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-      num_test_image: 4952
-    }
-    code_type: CENTER_SIZE
-    keep_top_k: 200
-    confidence_threshold: 0.01
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/image_object_detection.py b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/image_object_detection.py
deleted file mode 100755 (executable)
index 88b0dae..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/image_object_detection.py
+++ /dev/null
@@ -1,986 +0,0 @@
-from __future__ import print_function
-import caffe
-from google.protobuf import text_format
-import ast
-from models.model_libs import *
-import models.jacintonet_v2
-import models.mobilenet
-import numpy as np
-import math
-import os
-import shutil
-import stat
-import subprocess
-import sys
-import argparse
-from collections import OrderedDict
-
-
-def set_min_max_sizes(config_param):
-  # in percent %
-  min_ratio = 15
-  if config_param.ssd_size == '512x512':
-    min_ratio = 15
-  elif (config_param.ssd_size == '300x300') or(config_param.ssd_size == '256x256'):
-    min_ratio = 20
-  
-  if config_param.small_objs: 
-    min_ratio = min_ratio - 5
-   
-  max_ratio = 90
-  step = int(math.floor((max_ratio - min_ratio) / (config_param.num_steps - 2)))
-
-  min_sizes = []
-  max_sizes = []
-
-  for ratio in xrange(min_ratio, max_ratio + 1, step):
-    min_sizes.append(config_param.min_dim * ratio / 100.)
-    max_sizes.append(config_param.min_dim * (ratio + step) / 100.)
-
-  print('ratio_step_size:', step)   
-  
-  min_size_mul = 7
-  max_size_mul = 15
-  if config_param.ssd_size == '512x512':
-    if config_param.small_objs:
-      min_size_mul = 4 
-      max_size_mul = 10
-    else:  
-      min_size_mul = 7
-      max_size_mul = 15 
-  elif (config_param.ssd_size == '300x300') or (config_param.ssd_size == '256x256'):
-    if config_param.small_objs:
-      min_size_mul = 7
-      max_size_mul = 15 
-    else:
-      min_size_mul = 10
-      max_size_mul = 20
-  
-  min_sizes = [config_param.min_dim * min_size_mul / 100.] + min_sizes
-  max_sizes = [config_param.min_dim * max_size_mul / 100.] + max_sizes
-  
-  #print('min_sizes:', min_sizes)   
-  #print('max_sizes:', max_sizes)  
-
-  return min_sizes, max_sizes  
-
-def CreateAnnotatedDataLayer(source, batch_size=32, backend=P.Data.LMDB,
-        output_label=True, train=True, label_map_file='', anno_type=None,
-        transform_param={}, batch_sampler=[{}], threads=1):
-    if train:
-        kwargs = {
-                'include': dict(phase=caffe_pb2.Phase.Value('TRAIN')),
-                'transform_param': transform_param,
-                }
-    else:
-        kwargs = {
-                'include': dict(phase=caffe_pb2.Phase.Value('TEST')),
-                'transform_param': transform_param,
-                }
-    ntop = 1
-    if output_label:
-        ntop = 2
-    annotated_data_param = {
-        'label_map_file': label_map_file,
-        'batch_sampler': batch_sampler,
-        }
-    if anno_type is not None:
-        annotated_data_param.update({'anno_type': anno_type})
-    return L.AnnotatedData(name="data", annotated_data_param=annotated_data_param,
-        data_param=dict(batch_size=batch_size, backend=backend, source=source, parser_threads=threads, threads=threads),
-        ntop=ntop, **kwargs)
-        
-def CreateMultiBoxHead(net, data_layer="data", num_classes=[], from_layers=[],
-        use_objectness=False, normalizations=[], use_batchnorm=True, lr_mult=1,
-        use_scale=True, min_sizes=[], max_sizes=[], prior_variance = [0.1],
-        aspect_ratios=[], steps=[], img_height=0, img_width=0, share_location=True,
-        flip=True, clip=True, offset=0.5, inter_layer_depth=[], kernel_size=1, pad=0,
-        conf_postfix='', loc_postfix='', **bn_param):
-    assert num_classes, "must provide num_classes"
-    assert num_classes > 0, "num_classes must be positive number"
-    if normalizations:
-        assert len(from_layers) == len(normalizations), "from_layers and normalizations should have same length"
-    assert len(from_layers) == len(min_sizes), "from_layers and min_sizes should have same length"
-    if max_sizes:
-        assert len(from_layers) == len(max_sizes), "from_layers and max_sizes should have same length"
-    if aspect_ratios:
-        assert len(from_layers) == len(aspect_ratios), "from_layers and aspect_ratios should have same length"
-    if steps:
-        assert len(from_layers) == len(steps), "from_layers and steps should have same length"
-    net_layers = net.keys()
-    assert data_layer in net_layers, "data_layer is not in net's layers"
-    if inter_layer_depth:
-        assert len(from_layers) == len(inter_layer_depth), "from_layers and inter_layer_depth should have same length"
-
-    num = len(from_layers)
-    priorbox_layers = []
-    loc_layers = []
-    conf_layers = []
-    objectness_layers = []
-    for i in range(0, num):
-        from_layer = from_layers[i]
-
-        # Get the normalize value.
-        if normalizations:
-            if normalizations[i] != -1:
-                norm_name = "{}_norm".format(from_layer)
-                net[norm_name] = L.Normalize(net[from_layer], scale_filler=dict(type="constant", value=normalizations[i]),
-                    across_spatial=False, channel_shared=False)
-                from_layer = norm_name
-
-        # Add intermediate layers.
-        if inter_layer_depth:
-            if inter_layer_depth[i] > 0:
-                inter_name = "{}_inter".format(from_layer)
-                ConvBNLayerSSD(net, from_layer, inter_name, use_bn=use_batchnorm, use_relu=True, lr_mult=lr_mult,
-                      num_output=inter_layer_depth[i], kernel_size=3, pad=1, stride=1, use_scale=use_scale, **bn_param)
-                from_layer = inter_name
-
-        # Estimate number of priors per location given provided parameters.
-        min_size = min_sizes[i]
-        if type(min_size) is not list:
-            min_size = [min_size]
-        aspect_ratio = []
-        if len(aspect_ratios) > i:
-            aspect_ratio = aspect_ratios[i]
-            if type(aspect_ratio) is not list:
-                aspect_ratio = [aspect_ratio]
-        max_size = []
-        if len(max_sizes) > i:
-            max_size = max_sizes[i]
-            if type(max_size) is not list:
-                max_size = [max_size]
-            if max_size:
-                assert len(max_size) == len(min_size), "max_size and min_size should have same length."
-        if max_size:
-            num_priors_per_location = (2 + len(aspect_ratio)) * len(min_size)
-        else:
-            num_priors_per_location = (1 + len(aspect_ratio)) * len(min_size)
-        if flip:
-            num_priors_per_location += len(aspect_ratio) * len(min_size)
-        step = []
-        if len(steps) > i:
-            step = steps[i]
-
-        # Create location prediction layer.
-        name = "{}_mbox_loc{}".format(from_layer, loc_postfix)
-        num_loc_output = num_priors_per_location * 4;
-        if not share_location:
-            num_loc_output *= num_classes
-       
-        dilation=1
-        pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-        ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-            num_output=num_loc_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-        permute_name = "{}_perm".format(name)
-        net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-        flatten_name = "{}_flat".format(name)
-        net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-        loc_layers.append(net[flatten_name])
-
-        # Create confidence prediction layer.
-        name = "{}_mbox_conf{}".format(from_layer, conf_postfix)
-        num_conf_output = num_priors_per_location * num_classes;
-
-        dilation=1
-        pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-        ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-            num_output=num_conf_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-        permute_name = "{}_perm".format(name)
-        net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-        flatten_name = "{}_flat".format(name)
-        net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-        conf_layers.append(net[flatten_name])
-
-        # Create prior generation layer.
-        name = "{}_mbox_priorbox".format(from_layer)
-        net[name] = L.PriorBox(net[from_layer], net[data_layer], min_size=min_size,
-                clip=clip, variance=prior_variance, offset=offset)
-        if max_size:
-            net.update(name, {'max_size': max_size})
-        if aspect_ratio:
-            net.update(name, {'aspect_ratio': aspect_ratio, 'flip': flip})
-        if step:
-            net.update(name, {'step': step})
-        if img_height != 0 and img_width != 0:
-            if img_height == img_width:
-                net.update(name, {'img_size': img_height})
-            else:
-                net.update(name, {'img_h': img_height, 'img_w': img_width})
-        priorbox_layers.append(net[name])
-
-        # Create objectness prediction layer.
-        if use_objectness:
-            name = "{}_mbox_objectness".format(from_layer)
-            num_obj_output = num_priors_per_location * 2;
-            dilation=1
-            pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-            ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-                num_output=num_obj_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-            permute_name = "{}_perm".format(name)
-            net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-            flatten_name = "{}_flat".format(name)
-            net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-            objectness_layers.append(net[flatten_name])
-
-    # Concatenate priorbox, loc, and conf layers.
-    mbox_layers = []
-    name = "mbox_loc"
-    net[name] = L.Concat(*loc_layers, axis=1)
-    mbox_layers.append(net[name])
-    name = "mbox_conf"
-    net[name] = L.Concat(*conf_layers, axis=1)
-    mbox_layers.append(net[name])
-    name = "mbox_priorbox"
-    net[name] = L.Concat(*priorbox_layers, axis=2)
-    mbox_layers.append(net[name])
-    if use_objectness:
-        name = "mbox_objectness"
-        net[name] = L.Concat(*objectness_layers, axis=1)
-        mbox_layers.append(net[name])
-
-    return mbox_layers
-
-
-def CoreNetwork(config_param, net, from_layer):
-    if config_param.model_name == 'jdetnet21v2':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)
-    elif config_param.model_name == 'jdetnet21v2-s8':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21_s8(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)              
-    elif config_param.model_name == 'jdetnet21v2-fpn':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21_fpn(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)
-    elif config_param.model_name == 'ssdJacintoNetV2':
-        out_layer, out_layer_names = models.jacintonet_v2.ssdJacintoNetV2(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,\
-          dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride,\
-          ds_type=config_param.ds_type, use_batchnorm_mbox=config_param.use_batchnorm_mbox,fully_conv_at_end=config_param.fully_conv_at_end, 
-          reg_head_at_ds8=config_param.reg_head_at_ds8, concat_reg_head=config_param.concat_reg_head,
-          base_nw_3_head=config_param.base_nw_3_head, first_hd_same_op_ch=config_param.first_hd_same_op_ch,
-          num_intermediate=config_param.num_intermediate, rhead_name_non_linear=config_param.rhead_name_non_linear,
-          chop_num_heads=config_param.chop_num_heads)
-    elif 'mobiledetnet' in config_param.model_name:
-        #out_layer = models.mobilenet.mobiledetnet(net, from_layer=from_layer,\
-        #  num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-        #  freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride, wide_factor=wide_factor)
-        wide_factor = float(config_param.model_name.split('-')[1])
-        out_layer, out_layer_names = models.mobilenet.mobiledetnet(net, from_layer=from_layer, wide_factor=wide_factor, num_intermediate=config_param.num_intermediate)
-    else:
-        ValueError("Invalid model name")
-
-    return net, out_layer, out_layer_names
-
-
-def get_arguments():
-    parser = argparse.ArgumentParser()   
-    parser.add_argument('--config_param', type=str, default=None, help='Extra config parameters')      
-    parser.add_argument('--solver_param', type=str, default=None, help='Extra solver parameters')        
-    return parser.parse_args()
-      
-def main(): 
-    args = get_arguments()
-   
-    if args.solver_param != None:
-      print(args.solver_param)
-      args.solver_param = ast.literal_eval(args.solver_param) 
-            
-    if args.config_param != None:
-      print(args.config_param)
-      args.config_param = ast.literal_eval(args.config_param) 
-            
-    #Start populating config_param
-    config_param = OrderedDict()
-  
-    #Names
-    config_param.config_name = 'image-objdet'
-    config_param.model_name = "jacintonet11"
-    config_param.dataset = "nodataset"       
-    config_param.pretrain_model = None
-                          
-    ### Modify the following parameters accordingly ###
-    # The directory which contains the caffe code.
-    # We assume you are running the script at the CAFFE_ROOT.
-    config_param.caffe_root = os.environ['CAFFE_ROOT'] if 'CAFFE_ROOT' in os.environ else None
-    if config_param.caffe_root == None:
-      config_param.caffe_root = os.environ['CAFFE_HOME'] if 'CAFFE_HOME' in os.environ else None
-    if config_param.caffe_root != None:
-      config_param.caffe_root = config_param.caffe_root + '/build/tools/caffe.bin'
-    config_param.caffe_cmd = 'train'
-
-    print("caffe_root = : ",  config_param.caffe_root)
-
-    # Set true if you want to start training right after generating all files.
-    config_param.run_soon = False
-    # Set true if you want to load from most recently saved snapshot.
-    # Otherwise, we will load from the pretrain_model defined below.
-    config_param.resume_training = True
-    # If true, Remove old model files.
-    config_param.remove_old_models = False
-    config_param.display_sparsity = False
-    
-    # Specify the batch sampler.
-    config_param.resize_width = 512
-    config_param.resize_height = 512
-    config_param.crop_width = config_param.resize_width
-    config_param.crop_height = config_param.resize_height
-
-    #feature stride can be 16, 32. 32 provides the best radeoff
-    config_param.feature_stride = 32
-    config_param.num_feature = 512 #number of feature channels
-    config_param.threads = 4
-    # The database file for training data. Created by data/VOC0712/create_data.sh
-    config_param.train_data = "/data/hdd/datasets/object-detect/other/pascal-voc/VOCdevkit/VOC0712/lmdb/VOC0712_trainval_lmdb"
-    # The database file for testing data. Created by data/VOC0712/create_data.sh
-    config_param.test_data = "/data/hdd/datasets/object-detect/other/pascal-voc/VOCdevkit/VOC0712/lmdb/VOC0712_test_lmdb"
-
-    config_param.stride_list = None
-    config_param.dilation_list = None
-
-    config_param.mean_value = 128 #used in a bias layer in the net.
-
-    
-    # If true, use batch norm for all newly added layers.
-    # Currently only the non batch norm version has been tested.
-    config_param.use_batchnorm = False
-    config_param.use_scale = False
-    
-    config_param.lr_mult = 1
-
-    # Which layers to freeze (no backward) during training.
-    config_param.freeze_layers = []
-    # Defining which GPUs to use.
-    config_param.gpus = "0,1" #gpus = "0"  
-
-    config_param.batch_size = 32
-    config_param.accum_batch_size = 32
-
-    # Evaluate on whole test set.
-    config_param.num_test_image = 4952
-    config_param.test_batch_size = 8
-    
-    # Stores the test image names and sizes. Created by data/VOC0712/create_list.sh
-    config_param.name_size_file = "/user/a0393608/files/work/code/vision/github/weiliu89_ssd/caffe/data/VOC0712/test_name_size.txt"
-    # Stores LabelMapItem.
-    config_param.label_map_file = "/user/a0393608/files/work/code/vision/github/weiliu89_ssd/caffe/data/VOC0712/labelmap_voc.prototxt"
-
-    # minimum dimension of input image
-    config_param.log_space_steps = False #True
-    config_param.min_ratio = 10 #5 #20     # in percent %
-    config_param.max_ratio = 90            # in percent %
-    config_param.num_classes = 21
-    
-    # MultiBoxLoss parameters initialization.
-    config_param.share_location = True
-    config_param.background_label_id=0
-    config_param.use_difficult_gt = True
-    config_param.ignore_difficult_gt = False
-    config_param.evaluate_difficult_gt = False
-    config_param.normalization_mode = P.Loss.VALID
-    config_param.code_type = P.PriorBox.CENTER_SIZE
-    config_param.ignore_cross_boundary_bbox = False
-    config_param.mining_type = P.MultiBoxLoss.MAX_NEGATIVE
-    config_param.neg_pos_ratio = 3.
-    config_param.loc_weight = (config_param.neg_pos_ratio + 1.) / 4.
-    config_param.min_dim = -1
-    config_param.aspect_ratios_type=0
-    #need it for COCO which may have gray scale image
-    config_param.force_color = 0 
-
-    #Update from params given from outside
-    #if args.config_param != None:
-    #  config_param.update(args.config_param)   
-    if args.config_param != None: 
-      for k in args.config_param.keys():
-        config_param.__setattr__(k,args.config_param[k])
-        config_param.__setitem__(k,args.config_param[k])
-
-    if config_param.min_dim == -1:
-      config_param.min_dim = int((config_param.crop_width + config_param.crop_height)/2)
-
-    if config_param.ds_fac == 16: 
-      config_param.stride_list = [2,2,2,2,1]
-      config_param.dilation_list = [1,1,1,1,2]
-      config_param.feature_stride = 16
-    elif config_param.ds_fac == 32: 
-      config_param.stride_list = [2,2,2,2,2]
-      config_param.dilation_list = [1,1,1,1,1]
-      config_param.feature_stride = 32
-   
-    print("config_param.ds_fac :", config_param.ds_fac)
-    print("config_param.stride_list :", config_param.stride_list)
-    resize = "{}x{}".format(config_param.resize_width, config_param.resize_height)
-    config_param.batch_sampler = [
-            {
-                    'sampler': {
-                            },
-                    'max_trials': 1,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.1,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.3,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.5,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.7,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.9,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'max_jaccard_overlap': 1.0,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            ]
-    config_param.train_transform_param = {
-            'mirror': True,
-            'mean_value': [0, 0, 0],
-            'force_color':config_param.force_color,
-            'resize_param': {
-                    'prob': 1,
-                    'resize_mode': P.Resize.WARP,
-                    'height': config_param.resize_height,
-                    'width': config_param.resize_width,
-                    'interp_mode': [
-                            P.Resize.LINEAR,
-                            P.Resize.AREA,
-                            P.Resize.NEAREST,
-                            P.Resize.CUBIC,
-                            P.Resize.LANCZOS4,
-                            ],
-                    },
-            'distort_param': {
-                    'brightness_prob': 0.5,
-                    'brightness_delta': 32,
-                    'contrast_prob': 0.5,
-                    'contrast_lower': 0.5,
-                    'contrast_upper': 1.5,
-                    'hue_prob': 0.5,
-                    'hue_delta': 18,
-                    'saturation_prob': 0.5,
-                    'saturation_lower': 0.5,
-                    'saturation_upper': 1.5,
-                    'random_order_prob': 0.0,
-                    },
-            'expand_param': {
-                    'prob': 0.5,
-                    'max_expand_ratio': 4.0,
-                    },
-            'emit_constraint': {
-                'emit_type': caffe_pb2.EmitConstraint.CENTER,
-                },
-      'crop_h': config_param.crop_height,
-      'crop_w': config_param.crop_width
-            }
-    config_param.test_transform_param = {
-            'mean_value': [0, 0, 0],
-            'force_color':config_param.force_color,
-            'resize_param': {
-                    'prob': 1,
-                    'resize_mode': P.Resize.WARP,
-                    'height': config_param.resize_height,
-                    'width': config_param.resize_width,
-                    'interp_mode': [P.Resize.LINEAR],
-                    },
-      'crop_h': config_param.crop_height,
-      'crop_w': config_param.crop_width          
-            }
-
-        
-    # Modify the job name if you want.
-    #print("config_name is {}".format(config_param.config_name))
-    config_param.base_name = config_param.config_name
-    config_param.job_name = config_param.base_name
-
-    # Base dir
-    config_param.base_dir = config_param.job_name
-    # Directory which stores the model .prototxt file.
-    config_param.save_dir = config_param.job_name
-    # Directory which stores the snapshot of models.
-    config_param.snapshot_dir = config_param.job_name
-    # Directory which stores the job script and log file.
-    config_param.job_dir = config_param.job_name
-    # Directory which stores the detection results.
-    config_param.output_result_dir = "" #"{}/results".format(config_param.job_name)
-        
-    # model definition files.
-    config_param.train_net_file = "{}/train.prototxt".format(config_param.save_dir)
-    config_param.test_net_file = "{}/test.prototxt".format(config_param.save_dir)
-    config_param.deploy_net_file = "{}/deploy.prototxt".format(config_param.save_dir)
-    config_param.solver_file = "{}/solver.prototxt".format(config_param.save_dir)
-    # snapshot prefix.
-    config_param.snapshot_prefix = "{}/{}_{}".format(config_param.snapshot_dir, config_param.dataset, config_param.model_name)
-    # job script path.
-    job_file_base_name = 'run' 
-    config_param.job_file_base = "{}/{}".format(config_param.job_dir, job_file_base_name)
-    config_param.log_file = "{}.log".format(config_param.job_file_base)    
-    config_param.job_file = "{}.sh".format(config_param.job_file_base)
-   
-    # MultiBoxLoss parameters.
-    multibox_loss_param = {
-        'loc_loss_type': P.MultiBoxLoss.SMOOTH_L1,
-        'conf_loss_type': P.MultiBoxLoss.SOFTMAX,
-        'loc_weight': config_param.loc_weight,
-        'num_classes': config_param.num_classes,
-        'share_location': config_param.share_location,
-        'match_type': P.MultiBoxLoss.PER_PREDICTION,
-        'overlap_threshold': 0.5,
-        'use_prior_for_matching': True,
-        'background_label_id': config_param.background_label_id,
-        'use_difficult_gt': config_param.use_difficult_gt,
-        'ignore_difficult_gt': config_param.ignore_difficult_gt,
-        'mining_type': config_param.mining_type,
-        'neg_pos_ratio': config_param.neg_pos_ratio,
-        'neg_overlap': 0.5,
-        'code_type': config_param.code_type,
-        'ignore_cross_boundary_bbox': config_param.ignore_cross_boundary_bbox,
-        }
-    loss_param = {
-        'normalization': config_param.normalization_mode,
-        }
-
-    if config_param.feature_stride != 16 and config_param.feature_stride != 32:
-        ValueError("config_param.feature_stride {} is incorrect".format(config_param.feature_stride))
-    
-
-    config_param.flip = True
-    config_param.clip = False
-
-    # Solver parameters.
-    # Defining which GPUs to use.
-    config_param.gpulist = config_param.gpus.split(",")
-    config_param.num_gpus = len(config_param.gpulist)
-   
-    # Divide the mini-batch to different GPUs.
-    iter_size = int(math.ceil(config_param.accum_batch_size/config_param.batch_size))
-    solver_mode = P.Solver.CPU
-    device_id = 0
-    batch_size_per_device = config_param.batch_size
-    if config_param.num_gpus > 0:
-      batch_size_per_device = int(math.ceil(float(config_param.batch_size) / config_param.num_gpus))
-      iter_size = int(math.ceil(float(config_param.accum_batch_size) / (batch_size_per_device * config_param.num_gpus)))
-      solver_mode = P.Solver.GPU
-      device_id = int(config_param.gpulist[0])
-
-    # Ideally test_batch_size should be divisible by num_test_image,
-    # otherwise mAP will be slightly off the true value.
-    test_iter = int(math.ceil(float(config_param.num_test_image) / config_param.test_batch_size))
-
-    solver_param = {
-        # Train parameters
-        'type': "SGD",
-        'base_lr': 1e-3,
-        'max_iter': 32000, 
-        'weight_decay': 0.0005,
-        'lr_policy': "multistep",
-        'power': 1.0,
-        'stepvalue': [24000, 30000, 32000],
-        'gamma': 0.1,
-        'momentum': 0.9,
-        'iter_size': iter_size,
-        'snapshot': 2000,
-        'display': 100,
-        'average_loss': 10,
-        'type': "SGD",
-        'solver_mode': solver_mode,
-        'device_id': device_id,
-        'debug_info': False,
-        'snapshot_after_train': True,
-        # Test parameters
-        'test_iter': [test_iter],
-        'test_interval': 2000,
-        'eval_type': "detection",
-        'ap_version': "11point",
-        'test_initialization': True,
-        'random_seed': 33,
-        'show_per_class_result': True,
-        }
-
-    #if args.solver_param != None:
-    #  solver_param.update(args.solver_param)       
-    if args.solver_param != None: 
-      for k in args.solver_param.keys():
-        solver_param.__setitem__(k,args.solver_param[k])    
-        #solver_param.__setattr__(k,args.solver_param[k])
-    
-    # parameters for generating detection output.
-    det_out_param = {
-        'num_classes': config_param.num_classes,
-        'share_location': config_param.share_location,
-        'background_label_id': config_param.background_label_id,
-        'nms_param': {'nms_threshold': 0.45, 'top_k': 400},
-        'save_output_param': {
-            'output_directory': config_param.output_result_dir,
-            'output_name_prefix': "comp4_det_test_",
-            'output_format': "VOC",
-            'label_map_file': config_param.label_map_file,
-            'name_size_file': config_param.name_size_file,
-            'num_test_image': config_param.num_test_image,
-            },
-        'keep_top_k': 200,
-        'confidence_threshold': 0.01,
-        'code_type': config_param.code_type,
-        }
-
-    # parameters for evaluating detection results.
-    det_eval_param = {
-        'num_classes': config_param.num_classes,
-        'background_label_id': config_param.background_label_id,
-        'overlap_threshold': 0.5,
-        'evaluate_difficult_gt': config_param.evaluate_difficult_gt,
-        'name_size_file': config_param.name_size_file,
-        }
-
-    ### Hopefully you don't need to change the following ###
-    # Check file.
-    check_if_exist(config_param.train_data)
-    check_if_exist(config_param.test_data)
-    check_if_exist(config_param.label_map_file)
-    if config_param.pretrain_model != None:    
-      check_if_exist(config_param.pretrain_model)
-    make_if_not_exist(config_param.base_dir)  
-    make_if_not_exist(config_param.save_dir)
-    make_if_not_exist(config_param.job_dir)
-    make_if_not_exist(config_param.snapshot_dir)
-
-    # Create train net.
-    net = caffe.NetSpec()
-    net.data, net.label = CreateAnnotatedDataLayer(config_param.train_data, batch_size=config_param.batch_size,
-            train=True, output_label=True, label_map_file=config_param.label_map_file,
-            transform_param=config_param.train_transform_param, batch_sampler=config_param.batch_sampler, 
-            threads=config_param.threads)
-
-    out_layer = 'data'
-    bias_kwargs = { #fixed value with lr_mult=0
-        'param': [dict(lr_mult=0, decay_mult=0)],
-        'filler': dict(type='constant', value=(-config_param.mean_value)),
-        }       
-    net['data/bias'] = L.Bias(net[out_layer], in_place=False, **bias_kwargs)
-    out_layer = 'data/bias'           
-
-    net, out_layer, out_layer_names = CoreNetwork(config_param, net, out_layer)
-
-    if (config_param.model_name == 'jdetnet21v2'):
-        config_param.steps = [] #[16, 32, 64, 128]
-        config_param.mbox_source_layers = out_layer_names
-    elif (config_param.model_name == 'jdetnet21v2-s8'):
-        config_param.steps = [] #[8, 16, 32, 64, 128, 256]
-        config_param.mbox_source_layers = out_layer_names
-    elif (config_param.model_name == 'jdetnet21v2-fpn'):
-        config_param.steps = [] #[16, 16, 32, 64, 128, 256]
-        config_param.mbox_source_layers = out_layer_names
-    if (config_param.model_name == 'ssdJacintoNetV2'):
-      config_param.mbox_source_layers = out_layer_names
-      config_param.steps = []
-      if config_param.ds_type == 'DFLT':
-        #config_param.mbox_source_layers = ['res3a_branch2b/relu', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2', 'conv10_2']
-        config_param.mbox_source_layers = out_layer_names
-        if config_param.base_nw_3_head:
-          config_param.mbox_source_layers.append('ctx_output{}/relu'.format(len(config_param.mbox_source_layers)+1))
-    elif config_param.model_name == 'vgg16':
-        # conv4_3 ==> 38 x 38
-        # fc7 ==> 19 x 19
-        # conv6_2 ==> 10 x 10
-        # conv7_2 ==> 5 x 5
-        # conv8_2 ==> 3 x 3
-        # conv9_2 ==> 1 x 1
-        config_param.mbox_source_layers = ['conv4_3', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2']
-        config_param.steps = [8, 16, 32, 64, 100, 300]
-    elif 'mobiledetnet' in config_param.model_name:
-        config_param.mbox_source_layers = out_layer_names
-        config_param.steps = [] #[16, 32, 64, 128, 256] #[8, 16, 32, 64, 128, 256]
-    else:
-        print("Unknown detection network. Assuming default step sizes")
-        config_param.steps = []
-        config_param.mbox_source_layers = out_layer_names
-    
-    #-------------------------------------------------------------------
-    # parameters for generating priors.
-    config_param.num_steps = len(config_param.mbox_source_layers)  
-    config_param.step = int(math.floor((config_param.max_ratio - config_param.min_ratio) / config_param.num_steps))
-    config_param.min_sizes = []
-    config_param.max_sizes = []
-      
-    print("min_dim = {}".format(config_param.min_dim))
-    min_dim_to_use = config_param.min_ratio*config_param.min_dim/100
-    max_dim_to_use = config_param.max_ratio*config_param.min_dim/100
-    if config_param.log_space_steps == 1:
-      #log
-      min_max_sizes = np.logspace(np.log2(min_dim_to_use), np.log2(max_dim_to_use), num=config_param.num_steps+1, base=2)
-      config_param.min_sizes = list(min_max_sizes[0:config_param.num_steps])
-      config_param.max_sizes = list(min_max_sizes[1:config_param.num_steps+1])
-    elif config_param.log_space_steps == 0:
-      #linear
-      min_max_sizes = np.linspace(min_dim_to_use, max_dim_to_use, num=config_param.num_steps+1)
-      config_param.min_sizes = list(min_max_sizes[0:config_param.num_steps])
-      config_param.max_sizes = list(min_max_sizes[1:config_param.num_steps+1])
-    else:
-      #like original SSD
-      config_param.min_sizes, config_param.max_sizes = set_min_max_sizes(config_param)
-  
-    print("minsizes = {}".format(config_param.min_sizes))
-    print("maxsizes = {}".format(config_param.max_sizes))
-   
-    if config_param.aspect_ratios_type == 0:
-      config_param.aspect_ratios = [[2]]*config_param.num_steps 
-    else:
-      #like original SSD
-      config_param.aspect_ratios = [[2,3]]*config_param.num_steps
-      config_param.aspect_ratios[0] = [2]
-      config_param.aspect_ratios[-1] = [2]
-      config_param.aspect_ratios[-2] = [2]
-           
-    print("ARs:",config_param.aspect_ratios)
-    # L2 normalize conv4_3.
-    config_param.normalizations = [-1]*config_param.num_steps #[20, -1, -1, -1, -1, -1]
-    # variance used to encode/decode prior bboxes.
-    if config_param.code_type == P.PriorBox.CENTER_SIZE:
-      config_param.prior_variance = [0.1, 0.1, 0.2, 0.2]
-    else:
-      config_param.prior_variance = [0.1]
-
-    if config_param.chop_num_heads > 0:
-      print("Chopping heads")
-      del config_param.min_sizes[-config_param.chop_num_heads:]
-      del config_param.max_sizes[-config_param.chop_num_heads:]
-      del config_param.aspect_ratios[-config_param.chop_num_heads:]
-      del config_param.normalizations[-config_param.chop_num_heads:]
-      del config_param.mbox_source_layers[-config_param.chop_num_heads:]
-
-      print("minsizes = {}".format(config_param.min_sizes))
-      print("maxsizes = {}".format(config_param.max_sizes))
-      print("aspect_ratios = {}".format(config_param.aspect_ratios))
-      print(config_param.mbox_source_layers)
-    
-    
-    mbox_layers = CreateMultiBoxHead(net, data_layer='data', from_layers=config_param.mbox_source_layers,
-            use_batchnorm=config_param.use_batchnorm, use_scale=config_param.use_scale, min_sizes=config_param.min_sizes, max_sizes=config_param.max_sizes,
-            aspect_ratios=config_param.aspect_ratios, steps=config_param.steps, normalizations=config_param.normalizations,
-            num_classes=config_param.num_classes, share_location=config_param.share_location, flip=config_param.flip, clip=config_param.clip,
-            prior_variance=config_param.prior_variance, kernel_size=config_param.ker_mbox_loc_conf, pad=1, lr_mult=config_param.lr_mult)
-
-    # Create the MultiBoxLossLayer.
-    name = "mbox_loss"
-    mbox_layers.append(net.label)
-    net[name] = L.MultiBoxLoss(*mbox_layers, multibox_loss_param=multibox_loss_param,
-            loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')),
-            propagate_down=[True, True, False, False])
-
-    with open(config_param.train_net_file, 'w') as f:
-        print(config_param.train_net_file)
-        print('name: "{}"'.format(config_param.model_name), file=f)
-        print(net.to_proto(), file=f)
-    #shutil.copy(train_net_file, job_dir)
-
-
-    #-------------------------------------------------------------------
-    # Create test net.
-    net = caffe.NetSpec()
-    net.data, net.label = CreateAnnotatedDataLayer(config_param.test_data, batch_size=config_param.test_batch_size,
-            train=False, output_label=True, label_map_file=config_param.label_map_file,
-            transform_param=config_param.test_transform_param, threads=config_param.threads)
-
-    out_layer = 'data'
-    bias_kwargs = { #fixed value with lr_mult=0
-        'param': [dict(lr_mult=0, decay_mult=0)],
-        'filler': dict(type='constant', value=(-config_param.mean_value)),
-        }       
-    net['data/bias'] = L.Bias(net[out_layer], in_place=False, **bias_kwargs)
-    out_layer = 'data/bias'    
-    
-    net, out_layer, out_layer_names = CoreNetwork(config_param, net, out_layer)
-    
-    mbox_layers = CreateMultiBoxHead(net, data_layer='data', from_layers=config_param.mbox_source_layers,
-            use_batchnorm=config_param.use_batchnorm, use_scale=config_param.use_scale, min_sizes=config_param.min_sizes, max_sizes=config_param.max_sizes,
-            aspect_ratios=config_param.aspect_ratios, steps=config_param.steps, normalizations=config_param.normalizations,
-            num_classes=config_param.num_classes, share_location=config_param.share_location, flip=config_param.flip, clip=config_param.clip,
-            prior_variance=config_param.prior_variance, kernel_size=config_param.ker_mbox_loc_conf, pad=1, lr_mult=config_param.lr_mult)
-
-    conf_name = "mbox_conf"
-    if multibox_loss_param["conf_loss_type"] == P.MultiBoxLoss.SOFTMAX:
-      reshape_name = "{}_reshape".format(conf_name)
-      net[reshape_name] = L.Reshape(net[conf_name], shape=dict(dim=[0, -1, config_param.num_classes]))
-      softmax_name = "{}_softmax".format(conf_name)
-      net[softmax_name] = L.Softmax(net[reshape_name], axis=2)
-      flatten_name = "{}_flatten".format(conf_name)
-      net[flatten_name] = L.Flatten(net[softmax_name], axis=1)
-      mbox_layers[1] = net[flatten_name]
-    elif multibox_loss_param["conf_loss_type"] == P.MultiBoxLoss.LOGISTIC:
-      sigmoid_name = "{}_sigmoid".format(conf_name)
-      net[sigmoid_name] = L.Sigmoid(net[conf_name])
-      mbox_layers[1] = net[sigmoid_name]
-
-    net.detection_out = L.DetectionOutput(*mbox_layers,
-        detection_output_param=det_out_param,
-        include=dict(phase=caffe_pb2.Phase.Value('TEST')))
-    net.detection_eval = L.DetectionEvaluate(net.detection_out, net.label,
-        detection_evaluate_param=det_eval_param,
-        include=dict(phase=caffe_pb2.Phase.Value('TEST')))
-
-    with open(config_param.test_net_file, 'w') as f:
-        print('name: "{}_test"'.format(config_param.model_name), file=f)
-        print(net.to_proto(verbose=False), file=f)
-    if config_param.save_dir!=config_param.job_dir:
-      shutil.copy(config_param.test_net_file, config_param.job_dir)
-
-    # Create deploy net.
-    # Remove the first and last layer from test net.
-    deploy_net = net
-    with open(config_param.deploy_net_file, 'w') as f:
-        net_param = deploy_net.to_proto()
-        # Remove the first (AnnotatedData) and last (DetectionEvaluate) layer from test net.
-        del net_param.layer[0]
-        del net_param.layer[-1]
-        net_param.name = '{}_deploy'.format(config_param.model_name)
-        net_param.input.extend(['data'])
-        net_param.input_shape.extend([
-            caffe_pb2.BlobShape(dim=[1, 3, config_param.resize_height, config_param.resize_width])])
-        print(net_param, file=f)
-    if config_param.save_dir!=config_param.job_dir:        
-      shutil.copy(config_param.deploy_net_file, config_param.job_dir)
-
-    # Create solver.
-    solver = caffe_pb2.SolverParameter(
-            train_net=config_param.train_net_file,
-            test_net=[config_param.test_net_file],
-            snapshot_prefix=config_param.snapshot_prefix,
-            **solver_param)
-            
-    with open(config_param.solver_file, 'w') as f:
-        print(solver, file=f)
-    if config_param.save_dir!=config_param.job_dir:        
-      shutil.copy(solver_file, job_dir)
-
-    max_iter = 0
-    # Find most recent snapshot.
-    for file in os.listdir(config_param.snapshot_dir):
-      if file.endswith(".solverstate"):
-        basename = os.path.splitext(file)[0]
-        iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-        if iter > max_iter:
-          max_iter = iter
-
-    train_src_param = None
-    if config_param.pretrain_model != None:
-      train_src_param = '--weights="{}" \\\n'.format(config_param.pretrain_model)
-    if config_param.resume_training:
-      if max_iter > 0:
-        train_src_param = '--snapshot="{}_iter_{}.solverstate" \\\n'.format(config_param.snapshot_prefix, max_iter)
-
-    if config_param.remove_old_models:
-      # Remove any snapshots smaller than max_iter.
-      for file in os.listdir(config_param.snapshot_dir):
-        if file.endswith(".solverstate"):
-          basename = os.path.splitext(file)[0]
-          iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-          if max_iter > iter:
-            os.remove("{}/{}".format(config_param.snapshot_dir, file))
-        if file.endswith(".caffemodel"):
-          basename = os.path.splitext(file)[0]
-          iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-          if max_iter > iter:
-            os.remove("{}/{}".format(config_param.snapshot_dir, file))
-
-    # Create job file.
-    with open(config_param.job_file, 'w') as f:
-      #f.write('cd {}\n'.format(config_param.caffe_root))
-      f.write('{} {} \\\n'.format(config_param.caffe_root, config_param.caffe_cmd))    
-      if(config_param.caffe_cmd == 'test' or config_param.caffe_cmd == 'test_detection'):
-        f.write('--model="{}" \\\n'.format(config_param.test_net_file))
-        f.write('--iterations="{}" \\\n'.format(solver_param['test_iter'][0]))       
-        if config_param.display_sparsity:
-          f.write('--display_sparsity=1 \\\n')
-      else:
-        f.write('--solver="{}" \\\n'.format(config_param.solver_file))      
-      if train_src_param != None:
-        f.write(train_src_param)
-      if solver_param['solver_mode'] == P.Solver.GPU:
-        f.write('--gpu "{}" 2>&1 | tee {}\n'.format(config_param.gpus, config_param.log_file))
-      else:
-        f.write('2>&1 | tee {}\n'.format(config_param.log_file))
-
-    # Copy the python script to job_dir.
-    py_file = os.path.abspath(__file__)
-    shutil.copy(py_file, config_param.job_dir)
-    
-    #copy some other utils scripts
-    shutil.copy(os.getcwd() + '/train_image_object_detection.sh', config_param.job_dir)
-    shutil.copy(os.getcwd() + '/models/jacintonet_v2.py', config_param.job_dir)
-
-    # Run the job.
-    os.chmod(config_param.job_file, stat.S_IRWXU)
-    if config_param.run_soon:
-      subprocess.call(config_param.job_file, shell=True)
-  
-  
-if __name__ == "__main__":
-  main()  

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/jacintonet_v2.py b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/jacintonet_v2.py
deleted file mode 100755 (executable)
index a19b4d4..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/jacintonet_v2.py
+++ /dev/null
@@ -1,703 +0,0 @@
-from __future__ import print_function
-import caffe
-from models.model_libs import *
-
-def jacintonet11_base(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=1000, stride_list=None, dilation_list=None, freeze_layers=None, in_place=True):  
-   #Top and Bottom blobs must be different for NVCaffe BN caffe-0.15 (in_place=False), but no such constraint for caffe-0.16
-   
-   #--     
-   stage=0
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]   
-   
-   out_layer = 'conv1a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=32, kernel_size=[5,5], pad=2*dilation, stride=stride, group=1, dilation=dilation, in_place=in_place)  
-   
-   from_layer = out_layer
-   out_layer = 'conv1b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=32, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)       
-   
-   #--     
-   stage=1
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]   
-        
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool1'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)       
-      
-   from_layer = out_layer
-   out_layer = 'res2a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res2a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)     
-     
-   #--     
-   stage=2
-   stride=stride_list[stage]
-   dilation=dilation_list[stage] 
-        
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}       
-   from_layer = out_layer
-   out_layer = 'pool2'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)     
-         
-   from_layer = out_layer
-   out_layer = 'res3a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=128, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res3a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=128, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)    
-   
-   #--       
-   stage=3
-   stride=stride_list[stage]
-   dilation=dilation_list[stage] 
-      
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool3'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)         
-         
-   from_layer = out_layer
-   out_layer = 'res4a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer 
-   out_layer = 'res4a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)        
-      
-   #--      
-   stage=4
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]         
-   
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool4'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)     
-
-   from_layer = out_layer
-   out_layer = 'res5a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=512, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res5a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=512, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place) 
-   
-   return out_layer
-  
-  
-def jacintonet11(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=1000, stride_list=None, dilation_list=None, freeze_layers=None):  
-   if stride_list == None:
-     stride_list = [2,2,2,2,2]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1]
-   
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #--   
-   # Add global pooling layer.
-   from_layer = out_layer
-   out_layer = 'pool5'
-   net[out_layer] = L.Pooling(net[from_layer], pool=P.Pooling.AVE, global_pooling=True)
-       
-   from_layer = out_layer 
-   out_layer = 'fc'+str(num_output)
-   kwargs = { 'num_output': num_output, 
-     'param': [{'lr_mult': 1, 'decay_mult': 1}, {'lr_mult': 2, 'decay_mult': 0}], 
-     'inner_product_param': { 
-         'weight_filler': { 'type': 'msra' }, 
-         'bias_filler': { 'type': 'constant', 'value': 0 }   
-     },
-   }
-   net[out_layer] = L.InnerProduct(net[from_layer], **kwargs)    
-   
-   return out_layer
-   
-   
-def jsegnet21(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=True): 
-   in_place = True
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #--   
-   from_layer = out_layer
-   out_layer = 'out5a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=2, dilation=4) 
-   
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'out5a_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 64, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 64, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)    
-   
-   from_layer = 'res3a_branch2b' if in_place else 'res3a_branch2b/bn'
-   out_layer = 'out3a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=1, stride=1, group=2, dilation=1) 
-   
-   from_layer = out_layer   
-   out_layer = 'out3_out5_combined'
-   net[out_layer] = L.Eltwise(net['out5a_up2'], net[from_layer])
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv1'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1) 
-      
-   from_layer = out_layer
-   out_layer = 'ctx_conv2'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv3'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv4'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-       
-   from_layer = out_layer
-   out_layer = 'ctx_final'
-   conv_kwargs = {
-        'param': [dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)],
-        'weight_filler': dict(type='msra'),
-        'bias_term': True, 
-        'bias_filler': dict(type='constant', value=0) }   
-   net[out_layer] = L.Convolution(net[from_layer], num_output=num_output, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, **conv_kwargs) 
-         
-   from_layer = out_layer
-   out_layer = 'ctx_final/relu'
-   net[out_layer] = L.ReLU(net[from_layer], in_place=True) 
-               
-   #frozen upsampling layer   
-   if upsample:      
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up2'   
-       deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-           'convolution_param': { 'num_output': num_output, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': num_output, 'stride': 2, 
-           'weight_filler': { 'type': 'bilinear' } } }       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-               
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up4'       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs) 
-       
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up8'       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)     
-                            
-   return out_layer    
-
-
-def jdetnet21(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-      
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   
-   #---------------------------        
-   out_layer_names = []
-  
-   from_layer = 'res5a_branch2b/relu'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7'
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-
-def jdetnet21_s8(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,2] #[2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1] #[1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-
-   from_layer = 'res5a_branch2b/relu'
-   out_layer = 'conv6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=1024, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1)
-      
-   from_layer = out_layer
-   out_layer = 'conv7'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=1024, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)
-
-   #---------------------------       
-   out_layer = 'res3a_branch2b/concat'    
-   net[out_layer] = L.Concat(net['res3a_branch2a/relu'], net['res3a_branch2b/relu'])  
-         
-   out_layer = 'res4a_branch2b/concat'    
-   net[out_layer] = L.Concat(net['res4a_branch2a/relu'], net['res4a_branch2b/relu'])  
-            
-   #out_layer = 'res5a_branch2b/concat'    
-   #net[out_layer] = L.Concat(net['res5a_branch2a/relu'], net['res5a_branch2b/relu'])  
-               
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = 'conv7/relu' #'res5a_branch2b/concat' #
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':1, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   #---------------------------       
-   out_layer_names = []
-   
-   from_layer = 'res3a_branch2b/concat'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)  
-   out_layer_names += [out_layer]
-   
-   from_layer = 'res4a_branch2b/concat'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1) 
-   out_layer_names += [out_layer]
-   
-   from_layer = 'conv7/relu' #'res5a_branch2b/concat' #
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7'
-   out_layer = 'ctx_output5'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-
-#To match configuration used by original SSD script
-def ssdJacintoNetV2(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32, use_batchnorm_mbox=True, ds_type='PSP', fully_conv_at_end=True, reg_head_at_ds8=True, 
-   concat_reg_head=False, base_nw_3_head=False, first_hd_same_op_ch=False,
-   rhead_name_non_linear=False, chop_num_heads=0): 
-   
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-
-   last_base_layer_name = out_layer
-
-   if concat_reg_head:
-     out_layer = 'res4a_branch2b/concat'    
-     net[out_layer] = L.Concat(net['res4a_branch2a/relu'], net['res4a_branch2b/relu']) 
-                           
-     out_layer = 'res5a_branch2b/concat'    
-     net[out_layer] = L.Concat(net['res5a_branch2a/relu'], net['res5a_branch2b/relu'])  
-     last_base_layer_name = out_layer
-
-   if fully_conv_at_end:
-     from_layer = last_base_layer_name 
-     out_layer = 'fc6'
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=1024, kernel_size=[3,3], pad=6, stride=1, group=1, dilation=6)
-        
-     from_layer = out_layer
-     out_layer = 'fc7'
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=1024, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)
-     last_base_layer_name = out_layer
-      
-   #---------------------------     
-   out_layer_names = []
-  
-   #PSP style pool down
-   if ds_type == 'PSP':
-     if chop_num_heads < 4:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool6'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-     
-     #--
-     if chop_num_heads < 3:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool7'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if chop_num_heads < 2:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool8'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if chop_num_heads < 1:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool9'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if stride_list[4] == 1:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':1, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool10'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   
-     #mbox_source_layers = ['res3a_branch2b_relu', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2','conv10_2']
-     if rhead_name_non_linear:
-       reg_head_idx=6
-     else:
-       reg_head_idx=1
-
-     if reg_head_at_ds8:
-       from_layer = 'res3a_branch2b/relu'
-     else: 
-       if concat_reg_head:
-         from_layer = 'res4a_branch2b/concat'
-       else:  
-         from_layer = 'res4a_branch2b/relu'
-
-     out_layer = 'ctx_output{}'.format(reg_head_idx)
-
-     if rhead_name_non_linear:
-       reg_head_idx=0
-
-     reg_head_idx += 1
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>first_hd_same_op_ch, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-     out_layer_names += [out_layer]
-     
-     from_layer = last_base_layer_name 
-     out_layer = 'ctx_output{}'.format(reg_head_idx)
-     reg_head_idx += 1
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-     out_layer_names += [out_layer]
-    
-     if chop_num_heads < 4:
-       from_layer = 'pool6'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 3:
-       from_layer = 'pool7'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 2:
-       from_layer = 'pool8'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 1:
-       from_layer = 'pool9'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if stride_list[4] == 1:
-       from_layer = 'pool10'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if base_nw_3_head:
-       #by default 2 heads are connected in base n/w are at res3a and res5a (at the end of base n/w)
-       from_layer = 'res4a_branch2b/relu'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     return out_layer, out_layer_names
-   else:
-     out_layer_names += ['res3a_branch2b/relu']
-     if fully_conv_at_end:
-       out_layer_names += ['fc7']
-     
-     ssd_size = '512x512'
-     training_type = 'SSD'
-     if (ssd_size == '512x512') and (training_type == 'SSD'):
-                       #32x32    #16x16    #8x8      #4x4      #2x2
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,   1,   4,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,   1,   1,]
-     elif (ssd_size == '300x300') and (training_type == 'SSD'):
-                      #19x19     #10x10    #5x5      #3x3
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   0,   0,   0,]
-       strides=       [  1,   2,   1,   2,   1,   1,   1,   1,]
-     elif (ssd_size == '256x256') and (training_type == 'SSD'):
-                      #16x16     #8x8    #8x8      #4x4
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   0,   0,   0,]
-       strides=       [  1,   2,   1,   1,   1,   1,   1,   1,]
-     elif (ssd_size == '512x512') and (training_type == 'IMGNET'):
-                       #16x16    #8x8      #4x4      #2x2
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,]
-     elif (ssd_size == '300x300') and (training_type == 'IMGNET'):
-                       #10x10    #5x5      #3x3       #2x2   
-       num_outputs =  [256, 512, 128, 256, 128, 256,  64, 128,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,]
-
-     # index of first additional layer after base network
-     first_idx = 6
-     from_layer = net.keys()[-1]
-     blk_idx = first_idx
-     lr_mult = 1 
-     bn_postfix='/bn'
-     scale_postfix='/scale'
-     print("num_outputs: ", num_outputs) 
-     for idx in range (0, len(num_outputs)):
-       print("blk_index: ", blk_idx)
-       # TODO(weiliu89): Construct the name using the last layer to avoid duplication.
-       one_or_two = (idx%2) + 1
-       out_layer = "conv{}_{}".format(blk_idx, one_or_two)
-       ConvBNLayer(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_outputs[idx],
-           kernel_sizes[idx], pads[idx], strides[idx], lr_mult=lr_mult, bn_postfix=bn_postfix,
-           scale_postfix=scale_postfix)
-       out_layer_names += [out_layer]
-       from_layer = out_layer
-       if one_or_two == 2:
-         blk_idx = blk_idx + 1
-
-     return out_layer, out_layer_names
-   #---------------------------       
-
-   
-   
-def jdetnet21_fpn(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   in_place = True   
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,2]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-   from_layer = out_layer
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':1, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   #---------------------------   
-   #FPN layers start here  
-   #---------------------------  512->256  
-   from_layer = out_layer
-   out_layer = 'pool8_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-   
-   out_layer_1x1 = 'pool7_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'pool7', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)    
-            
-   from_layer = out_layer   
-   out_layer = 'pool7_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-              
-   #---------------------------  512->256  
-   from_layer = out_layer
-   out_layer = 'pool7_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'pool7_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-            
-   out_layer_1x1 = 'pool6_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'pool6', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)     
-            
-   from_layer = out_layer   
-   out_layer = 'pool6_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-          
-   #---------------------------  512->256   
-   from_layer = out_layer
-   out_layer = 'pool6_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'pool6_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-            
-   out_layer_1x1 = 'res5a_branch2b_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res5a_branch2b/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)         
-        
-   from_layer = out_layer   
-   out_layer = 'res5a_branch2b_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-              
-   #---------------------------   256->256 
-   from_layer = out_layer
-   out_layer = 'res5a_branch2b_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'res5a_branch2a_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-       
-   out_layer_1x1 = 'res4a_branch2b_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res4a_branch2b/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)  
-                         
-   from_layer = out_layer   
-   out_layer = 'res4a_branch2b_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-          
-   #---------------------------   256->256 
-   from_layer = out_layer
-   out_layer = 'res4a_branch2b_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place)    
-       
-   out_layer_1x1 = 'res4a_branch2a_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res4a_branch2a/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)   
-                      
-   from_layer = out_layer   
-   out_layer = 'res4a_branch2a_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-                              
-   #---------------------------  
-   out_layer_names = []
-   
-   #SSD heads start here
-   from_layer = 'res4a_branch2a_plus'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)   
-   out_layer_names += [out_layer]
-
-   from_layer = 'res4a_branch2b_plus'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)          
-   out_layer_names += [out_layer]
-   
-   from_layer = 'res5a_branch2b_plus'
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6_plus'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7_plus'
-   out_layer = 'ctx_output5'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/run.log b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/run.log
deleted file mode 100755 (executable)
index c7d5ce0..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/run.log
+++ /dev/null
@@ -1,12957 +0,0 @@
-I0510 14:48:29.573801  5307 caffe.cpp:902] This is NVCaffe 0.17.0 started at Thu May 10 14:48:29 2018
-I0510 14:48:29.573921  5307 caffe.cpp:904] CuDNN version: 7003
-I0510 14:48:29.573925  5307 caffe.cpp:905] CuBLAS version: 9000
-I0510 14:48:29.573927  5307 caffe.cpp:906] CUDA version: 9000
-I0510 14:48:29.573930  5307 caffe.cpp:907] CUDA driver version: 9000
-I0510 14:48:29.573932  5307 caffe.cpp:908] Arguments: 
-[0]: /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-[1]: train
-[2]: --solver=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/solver.prototxt
-[3]: --weights=../trained/image_classification/imagenet_mobilenet-0.5/initial/imagenet_mobilenet-0.5_iter_320000.caffemodel
-[4]: --gpu
-[5]: 0
-I0510 14:48:29.596494  5307 gpu_memory.cpp:105] GPUMemory::Manager initialized
-I0510 14:48:29.597261  5307 gpu_memory.cpp:107] Total memory: 11713708032, Free: 11223957504, dev_info[0]: total=11713708032 free=11223957504
-I0510 14:48:29.597268  5307 caffe.cpp:226] Using GPUs 0
-I0510 14:48:29.597745  5307 caffe.cpp:230] GPU 0: GeForce GTX 1080 Ti
-I0510 14:48:29.597784  5307 solver.cpp:41] Solver data type: FLOAT
-I0510 14:48:29.605398  5307 solver.cpp:44] Initializing solver from parameters: 
-train_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/train.prototxt"
-test_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/test.prototxt"
-test_iter: 619
-test_interval: 2000
-base_lr: 0.01
-display: 100
-max_iter: 120000
-lr_policy: "multistep"
-gamma: 0.1
-power: 1
-momentum: 0.9
-weight_decay: 0.0001
-snapshot: 2000
-snapshot_prefix: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5"
-solver_mode: GPU
-device_id: 0
-random_seed: 33
-debug_info: false
-train_state {
-  level: 0
-  stage: ""
-}
-snapshot_after_train: true
-test_initialization: true
-average_loss: 10
-stepvalue: 60000
-stepvalue: 90000
-stepvalue: 300000
-iter_size: 2
-type: "SGD"
-eval_type: "detection"
-ap_version: "11point"
-show_per_class_result: true
-I0510 14:48:29.605489  5307 solver.cpp:76] Creating training net from train_net file: training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/train.prototxt
-I0510 14:48:29.607403  5307 net.cpp:80] Initializing net from parameters: 
-name: "mobiledetnet-0.5"
-state {
-  phase: TRAIN
-  level: 0
-  stage: ""
-}
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TRAIN
-  }
-  transform_param {
-    mirror: true
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-      interp_mode: AREA
-      interp_mode: NEAREST
-      interp_mode: CUBIC
-      interp_mode: LANCZOS4
-    }
-    emit_constraint {
-      emit_type: CENTER
-    }
-    crop_h: 256
-    crop_w: 512
-    distort_param {
-      brightness_prob: 0.5
-      brightness_delta: 32
-      contrast_prob: 0.5
-      contrast_lower: 0.5
-      contrast_upper: 1.5
-      hue_prob: 0.5
-      hue_delta: 18
-      saturation_prob: 0.5
-      saturation_lower: 0.5
-      saturation_upper: 1.5
-      random_order_prob: 0
-    }
-    expand_param {
-      prob: 0.5
-      max_expand_ratio: 4
-    }
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb"
-    batch_size: 16
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-      max_sample: 1
-      max_trials: 1
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.1
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.3
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.5
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.7
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.9
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        max_jaccard_overlap: 1
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
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-}
-layer {
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-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    pad: 1
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-    stride: 2
-    weight_filler {
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
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-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
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-    decay_mult: 1
-  }
-  convolution_param {
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-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
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-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
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-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
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-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
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-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
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-  }
-}
-layer {
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-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
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-  type: "Scale"
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-  top: "conv5_2/dw"
-  scale_param {
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-layer {
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-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
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-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
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-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
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-layer {
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-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
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-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
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-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
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-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
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-  }
-}
-layer {
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-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
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-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
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-  }
-}
-layer {
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-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
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-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
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-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-layer {
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-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
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-  }
-}
-layer {
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-  top: "conv5_4/sep"
-}
-layer {
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-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
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-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
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-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
-  name: "ctx_output1"
-  type: "Convolution"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
-  name: "ctx_output2/1x1"
-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
-  name: "ctx_output2"
-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/relu"
-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
-  name: "ctx_output3/1x1"
-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
-  name: "ctx_output3"
-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/relu"
-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-I0510 14:48:29.607969  5307 net.cpp:110] Using FLOAT as default forward math type
-I0510 14:48:29.607976  5307 net.cpp:116] Using FLOAT as default backward math type
-I0510 14:48:29.607981  5307 layer_factory.hpp:172] Creating layer 'data' of type 'AnnotatedData'
-I0510 14:48:29.607986  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:29.608055  5307 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0510 14:48:29.608973  5322 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0510 14:48:29.609016  5307 net.cpp:200] Created Layer data (0)
-I0510 14:48:29.609035  5307 net.cpp:542] data -> data
-I0510 14:48:29.609045  5307 net.cpp:542] data -> label
-I0510 14:48:29.609061  5307 data_reader.cpp:58] Data Reader threads: 4, out queues: 16, depth: 16
-I0510 14:48:29.609109  5307 internal_thread.cpp:19] Starting 4 internal thread(s) on device 0
-I0510 14:48:29.609990  5323 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb
-I0510 14:48:29.610841  5324 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb
-I0510 14:48:29.612040  5307 annotated_data_layer.cpp:105] output data size: 16,3,256,512
-I0510 14:48:29.612288  5307 annotated_data_layer.cpp:150] [0] Output data size: 16, 3, 256, 512
-I0510 14:48:29.612665  5325 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb
-I0510 14:48:29.613466  5326 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb
-I0510 14:48:29.613507  5307 internal_thread.cpp:19] Starting 4 internal thread(s) on device 0
-I0510 14:48:29.614493  5328 data_layer.cpp:105] [0] Parser threads: 4
-I0510 14:48:29.614506  5328 data_layer.cpp:107] [0] Transformer threads: 4
-I0510 14:48:29.615298  5307 net.cpp:260] Setting up data
-I0510 14:48:29.624570  5307 net.cpp:267] TRAIN Top shape for layer 0 'data' 16 3 256 512 (6291456)
-I0510 14:48:29.624604  5307 net.cpp:267] TRAIN Top shape for layer 0 'data' 1 1 2 8 (16)
-I0510 14:48:29.624614  5307 layer_factory.hpp:172] Creating layer 'data_data_0_split' of type 'Split'
-I0510 14:48:29.624619  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:29.624629  5307 net.cpp:200] Created Layer data_data_0_split (1)
-I0510 14:48:29.624634  5307 net.cpp:572] data_data_0_split <- data
-I0510 14:48:29.624646  5307 net.cpp:542] data_data_0_split -> data_data_0_split_0
-I0510 14:48:29.624662  5307 net.cpp:542] data_data_0_split -> data_data_0_split_1
-I0510 14:48:29.624671  5307 net.cpp:542] data_data_0_split -> data_data_0_split_2
-I0510 14:48:29.624678  5307 net.cpp:542] data_data_0_split -> data_data_0_split_3
-I0510 14:48:29.624685  5307 net.cpp:542] data_data_0_split -> data_data_0_split_4
-I0510 14:48:29.624688  5307 net.cpp:542] data_data_0_split -> data_data_0_split_5
-I0510 14:48:29.624884  5307 net.cpp:260] Setting up data_data_0_split
-I0510 14:48:29.624892  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624897  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624902  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624907  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624910  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624915  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624933  5307 layer_factory.hpp:172] Creating layer 'data/bias' of type 'Bias'
-I0510 14:48:29.624944  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:29.624961  5307 net.cpp:200] Created Layer data/bias (2)
-I0510 14:48:29.624971  5307 net.cpp:572] data/bias <- data_data_0_split_0
-I0510 14:48:29.624981  5307 net.cpp:542] data/bias -> data/bias
-I0510 14:48:29.637835  5307 net.cpp:260] Setting up data/bias
-I0510 14:48:29.637859  5307 net.cpp:267] TRAIN Top shape for layer 2 'data/bias' 16 3 256 512 (6291456)
-I0510 14:48:29.637876  5307 layer_factory.hpp:172] Creating layer 'conv1' of type 'Convolution'
-I0510 14:48:29.637883  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:29.637907  5307 net.cpp:200] Created Layer conv1 (3)
-I0510 14:48:29.637912  5307 net.cpp:572] conv1 <- data/bias
-I0510 14:48:29.637917  5307 net.cpp:542] conv1 -> conv1
-I0510 14:48:30.098809  5307 net.cpp:260] Setting up conv1
-I0510 14:48:30.098845  5307 net.cpp:267] TRAIN Top shape for layer 3 'conv1' 16 16 128 256 (8388608)
-I0510 14:48:30.098858  5307 layer_factory.hpp:172] Creating layer 'conv1/bn' of type 'BatchNorm'
-I0510 14:48:30.098865  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.098881  5307 net.cpp:200] Created Layer conv1/bn (4)
-I0510 14:48:30.098886  5307 net.cpp:572] conv1/bn <- conv1
-I0510 14:48:30.098891  5307 net.cpp:527] conv1/bn -> conv1 (in-place)
-I0510 14:48:30.099910  5307 net.cpp:260] Setting up conv1/bn
-I0510 14:48:30.099922  5307 net.cpp:267] TRAIN Top shape for layer 4 'conv1/bn' 16 16 128 256 (8388608)
-I0510 14:48:30.099934  5307 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Scale'
-I0510 14:48:30.099942  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.099951  5307 net.cpp:200] Created Layer conv1/scale (5)
-I0510 14:48:30.099956  5307 net.cpp:572] conv1/scale <- conv1
-I0510 14:48:30.099961  5307 net.cpp:527] conv1/scale -> conv1 (in-place)
-I0510 14:48:30.100003  5307 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Bias'
-I0510 14:48:30.100008  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.100152  5307 net.cpp:260] Setting up conv1/scale
-I0510 14:48:30.100162  5307 net.cpp:267] TRAIN Top shape for layer 5 'conv1/scale' 16 16 128 256 (8388608)
-I0510 14:48:30.100169  5307 layer_factory.hpp:172] Creating layer 'relu1' of type 'ReLU'
-I0510 14:48:30.100173  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.100180  5307 net.cpp:200] Created Layer relu1 (6)
-I0510 14:48:30.100184  5307 net.cpp:572] relu1 <- conv1
-I0510 14:48:30.100188  5307 net.cpp:527] relu1 -> conv1 (in-place)
-I0510 14:48:30.100204  5307 net.cpp:260] Setting up relu1
-I0510 14:48:30.100209  5307 net.cpp:267] TRAIN Top shape for layer 6 'relu1' 16 16 128 256 (8388608)
-I0510 14:48:30.100214  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw' of type 'Convolution'
-I0510 14:48:30.100217  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.100227  5307 net.cpp:200] Created Layer conv2_1/dw (7)
-I0510 14:48:30.100232  5307 net.cpp:572] conv2_1/dw <- conv1
-I0510 14:48:30.100236  5307 net.cpp:542] conv2_1/dw -> conv2_1/dw
-I0510 14:48:30.101371  5307 net.cpp:260] Setting up conv2_1/dw
-I0510 14:48:30.101382  5307 net.cpp:267] TRAIN Top shape for layer 7 'conv2_1/dw' 16 16 128 256 (8388608)
-I0510 14:48:30.101388  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.101394  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.101402  5307 net.cpp:200] Created Layer conv2_1/dw/bn (8)
-I0510 14:48:30.101408  5307 net.cpp:572] conv2_1/dw/bn <- conv2_1/dw
-I0510 14:48:30.101411  5307 net.cpp:527] conv2_1/dw/bn -> conv2_1/dw (in-place)
-I0510 14:48:30.101748  5307 net.cpp:260] Setting up conv2_1/dw/bn
-I0510 14:48:30.101757  5307 net.cpp:267] TRAIN Top shape for layer 8 'conv2_1/dw/bn' 16 16 128 256 (8388608)
-I0510 14:48:30.101766  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Scale'
-I0510 14:48:30.101773  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.101778  5307 net.cpp:200] Created Layer conv2_1/dw/scale (9)
-I0510 14:48:30.101783  5307 net.cpp:572] conv2_1/dw/scale <- conv2_1/dw
-I0510 14:48:30.101788  5307 net.cpp:527] conv2_1/dw/scale -> conv2_1/dw (in-place)
-I0510 14:48:30.101821  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Bias'
-I0510 14:48:30.101827  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.101965  5307 net.cpp:260] Setting up conv2_1/dw/scale
-I0510 14:48:30.101975  5307 net.cpp:267] TRAIN Top shape for layer 9 'conv2_1/dw/scale' 16 16 128 256 (8388608)
-I0510 14:48:30.101981  5307 layer_factory.hpp:172] Creating layer 'relu2_1/dw' of type 'ReLU'
-I0510 14:48:30.101995  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102000  5307 net.cpp:200] Created Layer relu2_1/dw (10)
-I0510 14:48:30.102005  5307 net.cpp:572] relu2_1/dw <- conv2_1/dw
-I0510 14:48:30.102008  5307 net.cpp:527] relu2_1/dw -> conv2_1/dw (in-place)
-I0510 14:48:30.102013  5307 net.cpp:260] Setting up relu2_1/dw
-I0510 14:48:30.102018  5307 net.cpp:267] TRAIN Top shape for layer 10 'relu2_1/dw' 16 16 128 256 (8388608)
-I0510 14:48:30.102022  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep' of type 'Convolution'
-I0510 14:48:30.102026  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102035  5307 net.cpp:200] Created Layer conv2_1/sep (11)
-I0510 14:48:30.102038  5307 net.cpp:572] conv2_1/sep <- conv2_1/dw
-I0510 14:48:30.102042  5307 net.cpp:542] conv2_1/sep -> conv2_1/sep
-I0510 14:48:30.102200  5307 net.cpp:260] Setting up conv2_1/sep
-I0510 14:48:30.102208  5307 net.cpp:267] TRAIN Top shape for layer 11 'conv2_1/sep' 16 32 128 256 (16777216)
-I0510 14:48:30.102216  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.102219  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102226  5307 net.cpp:200] Created Layer conv2_1/sep/bn (12)
-I0510 14:48:30.102229  5307 net.cpp:572] conv2_1/sep/bn <- conv2_1/sep
-I0510 14:48:30.102234  5307 net.cpp:527] conv2_1/sep/bn -> conv2_1/sep (in-place)
-I0510 14:48:30.102529  5307 net.cpp:260] Setting up conv2_1/sep/bn
-I0510 14:48:30.102545  5307 net.cpp:267] TRAIN Top shape for layer 12 'conv2_1/sep/bn' 16 32 128 256 (16777216)
-I0510 14:48:30.102557  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Scale'
-I0510 14:48:30.102566  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102576  5307 net.cpp:200] Created Layer conv2_1/sep/scale (13)
-I0510 14:48:30.102583  5307 net.cpp:572] conv2_1/sep/scale <- conv2_1/sep
-I0510 14:48:30.102591  5307 net.cpp:527] conv2_1/sep/scale -> conv2_1/sep (in-place)
-I0510 14:48:30.102627  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Bias'
-I0510 14:48:30.102636  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102756  5307 net.cpp:260] Setting up conv2_1/sep/scale
-I0510 14:48:30.102767  5307 net.cpp:267] TRAIN Top shape for layer 13 'conv2_1/sep/scale' 16 32 128 256 (16777216)
-I0510 14:48:30.102778  5307 layer_factory.hpp:172] Creating layer 'relu2_1/sep' of type 'ReLU'
-I0510 14:48:30.102787  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102794  5307 net.cpp:200] Created Layer relu2_1/sep (14)
-I0510 14:48:30.102802  5307 net.cpp:572] relu2_1/sep <- conv2_1/sep
-I0510 14:48:30.102810  5307 net.cpp:527] relu2_1/sep -> conv2_1/sep (in-place)
-I0510 14:48:30.102820  5307 net.cpp:260] Setting up relu2_1/sep
-I0510 14:48:30.102829  5307 net.cpp:267] TRAIN Top shape for layer 14 'relu2_1/sep' 16 32 128 256 (16777216)
-I0510 14:48:30.102838  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw' of type 'Convolution'
-I0510 14:48:30.102845  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102857  5307 net.cpp:200] Created Layer conv2_2/dw (15)
-I0510 14:48:30.102865  5307 net.cpp:572] conv2_2/dw <- conv2_1/sep
-I0510 14:48:30.102874  5307 net.cpp:542] conv2_2/dw -> conv2_2/dw
-I0510 14:48:30.103037  5307 net.cpp:260] Setting up conv2_2/dw
-I0510 14:48:30.103050  5307 net.cpp:267] TRAIN Top shape for layer 15 'conv2_2/dw' 16 32 64 128 (4194304)
-I0510 14:48:30.103060  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.103068  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.103081  5307 net.cpp:200] Created Layer conv2_2/dw/bn (16)
-I0510 14:48:30.103094  5307 net.cpp:572] conv2_2/dw/bn <- conv2_2/dw
-I0510 14:48:30.103102  5307 net.cpp:527] conv2_2/dw/bn -> conv2_2/dw (in-place)
-I0510 14:48:30.104127  5307 net.cpp:260] Setting up conv2_2/dw/bn
-I0510 14:48:30.104146  5307 net.cpp:267] TRAIN Top shape for layer 16 'conv2_2/dw/bn' 16 32 64 128 (4194304)
-I0510 14:48:30.104158  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Scale'
-I0510 14:48:30.104167  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.104180  5307 net.cpp:200] Created Layer conv2_2/dw/scale (17)
-I0510 14:48:30.104188  5307 net.cpp:572] conv2_2/dw/scale <- conv2_2/dw
-I0510 14:48:30.104197  5307 net.cpp:527] conv2_2/dw/scale -> conv2_2/dw (in-place)
-I0510 14:48:30.104234  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Bias'
-I0510 14:48:30.104244  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.104336  5307 net.cpp:260] Setting up conv2_2/dw/scale
-I0510 14:48:30.104347  5307 net.cpp:267] TRAIN Top shape for layer 17 'conv2_2/dw/scale' 16 32 64 128 (4194304)
-I0510 14:48:30.104357  5307 layer_factory.hpp:172] Creating layer 'relu2_2/dw' of type 'ReLU'
-I0510 14:48:30.104365  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.104374  5307 net.cpp:200] Created Layer relu2_2/dw (18)
-I0510 14:48:30.104382  5307 net.cpp:572] relu2_2/dw <- conv2_2/dw
-I0510 14:48:30.104390  5307 net.cpp:527] relu2_2/dw -> conv2_2/dw (in-place)
-I0510 14:48:30.104400  5307 net.cpp:260] Setting up relu2_2/dw
-I0510 14:48:30.104409  5307 net.cpp:267] TRAIN Top shape for layer 18 'relu2_2/dw' 16 32 64 128 (4194304)
-I0510 14:48:30.104418  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep' of type 'Convolution'
-I0510 14:48:30.104425  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.104436  5307 net.cpp:200] Created Layer conv2_2/sep (19)
-I0510 14:48:30.104445  5307 net.cpp:572] conv2_2/sep <- conv2_2/dw
-I0510 14:48:30.104454  5307 net.cpp:542] conv2_2/sep -> conv2_2/sep
-I0510 14:48:30.105271  5307 net.cpp:260] Setting up conv2_2/sep
-I0510 14:48:30.105281  5307 net.cpp:267] TRAIN Top shape for layer 19 'conv2_2/sep' 16 64 64 128 (8388608)
-I0510 14:48:30.105289  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.105294  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105303  5307 net.cpp:200] Created Layer conv2_2/sep/bn (20)
-I0510 14:48:30.105306  5307 net.cpp:572] conv2_2/sep/bn <- conv2_2/sep
-I0510 14:48:30.105311  5307 net.cpp:527] conv2_2/sep/bn -> conv2_2/sep (in-place)
-I0510 14:48:30.105557  5307 net.cpp:260] Setting up conv2_2/sep/bn
-I0510 14:48:30.105564  5307 net.cpp:267] TRAIN Top shape for layer 20 'conv2_2/sep/bn' 16 64 64 128 (8388608)
-I0510 14:48:30.105572  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Scale'
-I0510 14:48:30.105576  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105582  5307 net.cpp:200] Created Layer conv2_2/sep/scale (21)
-I0510 14:48:30.105587  5307 net.cpp:572] conv2_2/sep/scale <- conv2_2/sep
-I0510 14:48:30.105590  5307 net.cpp:527] conv2_2/sep/scale -> conv2_2/sep (in-place)
-I0510 14:48:30.105618  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Bias'
-I0510 14:48:30.105623  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105701  5307 net.cpp:260] Setting up conv2_2/sep/scale
-I0510 14:48:30.105707  5307 net.cpp:267] TRAIN Top shape for layer 21 'conv2_2/sep/scale' 16 64 64 128 (8388608)
-I0510 14:48:30.105715  5307 layer_factory.hpp:172] Creating layer 'relu2_2/sep' of type 'ReLU'
-I0510 14:48:30.105718  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105731  5307 net.cpp:200] Created Layer relu2_2/sep (22)
-I0510 14:48:30.105736  5307 net.cpp:572] relu2_2/sep <- conv2_2/sep
-I0510 14:48:30.105741  5307 net.cpp:527] relu2_2/sep -> conv2_2/sep (in-place)
-I0510 14:48:30.105746  5307 net.cpp:260] Setting up relu2_2/sep
-I0510 14:48:30.105751  5307 net.cpp:267] TRAIN Top shape for layer 22 'relu2_2/sep' 16 64 64 128 (8388608)
-I0510 14:48:30.105756  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw' of type 'Convolution'
-I0510 14:48:30.105760  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105770  5307 net.cpp:200] Created Layer conv3_1/dw (23)
-I0510 14:48:30.105774  5307 net.cpp:572] conv3_1/dw <- conv2_2/sep
-I0510 14:48:30.105778  5307 net.cpp:542] conv3_1/dw -> conv3_1/dw
-I0510 14:48:30.106595  5307 net.cpp:260] Setting up conv3_1/dw
-I0510 14:48:30.106611  5307 net.cpp:267] TRAIN Top shape for layer 23 'conv3_1/dw' 16 64 64 128 (8388608)
-I0510 14:48:30.106621  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.106629  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.106639  5307 net.cpp:200] Created Layer conv3_1/dw/bn (24)
-I0510 14:48:30.106647  5307 net.cpp:572] conv3_1/dw/bn <- conv3_1/dw
-I0510 14:48:30.106657  5307 net.cpp:527] conv3_1/dw/bn -> conv3_1/dw (in-place)
-I0510 14:48:30.106976  5307 net.cpp:260] Setting up conv3_1/dw/bn
-I0510 14:48:30.106989  5307 net.cpp:267] TRAIN Top shape for layer 24 'conv3_1/dw/bn' 16 64 64 128 (8388608)
-I0510 14:48:30.107003  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Scale'
-I0510 14:48:30.107012  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107023  5307 net.cpp:200] Created Layer conv3_1/dw/scale (25)
-I0510 14:48:30.107030  5307 net.cpp:572] conv3_1/dw/scale <- conv3_1/dw
-I0510 14:48:30.107039  5307 net.cpp:527] conv3_1/dw/scale -> conv3_1/dw (in-place)
-I0510 14:48:30.107076  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Bias'
-I0510 14:48:30.107087  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107194  5307 net.cpp:260] Setting up conv3_1/dw/scale
-I0510 14:48:30.107206  5307 net.cpp:267] TRAIN Top shape for layer 25 'conv3_1/dw/scale' 16 64 64 128 (8388608)
-I0510 14:48:30.107218  5307 layer_factory.hpp:172] Creating layer 'relu3_1/dw' of type 'ReLU'
-I0510 14:48:30.107226  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107235  5307 net.cpp:200] Created Layer relu3_1/dw (26)
-I0510 14:48:30.107244  5307 net.cpp:572] relu3_1/dw <- conv3_1/dw
-I0510 14:48:30.107251  5307 net.cpp:527] relu3_1/dw -> conv3_1/dw (in-place)
-I0510 14:48:30.107260  5307 net.cpp:260] Setting up relu3_1/dw
-I0510 14:48:30.107270  5307 net.cpp:267] TRAIN Top shape for layer 26 'relu3_1/dw' 16 64 64 128 (8388608)
-I0510 14:48:30.107278  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep' of type 'Convolution'
-I0510 14:48:30.107286  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107298  5307 net.cpp:200] Created Layer conv3_1/sep (27)
-I0510 14:48:30.107306  5307 net.cpp:572] conv3_1/sep <- conv3_1/dw
-I0510 14:48:30.107314  5307 net.cpp:542] conv3_1/sep -> conv3_1/sep
-I0510 14:48:30.107592  5307 net.cpp:260] Setting up conv3_1/sep
-I0510 14:48:30.107605  5307 net.cpp:267] TRAIN Top shape for layer 27 'conv3_1/sep' 16 64 64 128 (8388608)
-I0510 14:48:30.107615  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.107623  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107633  5307 net.cpp:200] Created Layer conv3_1/sep/bn (28)
-I0510 14:48:30.107637  5307 net.cpp:572] conv3_1/sep/bn <- conv3_1/sep
-I0510 14:48:30.107642  5307 net.cpp:527] conv3_1/sep/bn -> conv3_1/sep (in-place)
-I0510 14:48:30.107893  5307 net.cpp:260] Setting up conv3_1/sep/bn
-I0510 14:48:30.107900  5307 net.cpp:267] TRAIN Top shape for layer 28 'conv3_1/sep/bn' 16 64 64 128 (8388608)
-I0510 14:48:30.107908  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Scale'
-I0510 14:48:30.107913  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107919  5307 net.cpp:200] Created Layer conv3_1/sep/scale (29)
-I0510 14:48:30.107923  5307 net.cpp:572] conv3_1/sep/scale <- conv3_1/sep
-I0510 14:48:30.107928  5307 net.cpp:527] conv3_1/sep/scale -> conv3_1/sep (in-place)
-I0510 14:48:30.107954  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Bias'
-I0510 14:48:30.107959  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108036  5307 net.cpp:260] Setting up conv3_1/sep/scale
-I0510 14:48:30.108042  5307 net.cpp:267] TRAIN Top shape for layer 29 'conv3_1/sep/scale' 16 64 64 128 (8388608)
-I0510 14:48:30.108048  5307 layer_factory.hpp:172] Creating layer 'relu3_1/sep' of type 'ReLU'
-I0510 14:48:30.108052  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108057  5307 net.cpp:200] Created Layer relu3_1/sep (30)
-I0510 14:48:30.108062  5307 net.cpp:572] relu3_1/sep <- conv3_1/sep
-I0510 14:48:30.108065  5307 net.cpp:527] relu3_1/sep -> conv3_1/sep (in-place)
-I0510 14:48:30.108072  5307 net.cpp:260] Setting up relu3_1/sep
-I0510 14:48:30.108078  5307 net.cpp:267] TRAIN Top shape for layer 30 'relu3_1/sep' 16 64 64 128 (8388608)
-I0510 14:48:30.108081  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw' of type 'Convolution'
-I0510 14:48:30.108086  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108093  5307 net.cpp:200] Created Layer conv3_2/dw (31)
-I0510 14:48:30.108098  5307 net.cpp:572] conv3_2/dw <- conv3_1/sep
-I0510 14:48:30.108103  5307 net.cpp:542] conv3_2/dw -> conv3_2/dw
-I0510 14:48:30.108237  5307 net.cpp:260] Setting up conv3_2/dw
-I0510 14:48:30.108245  5307 net.cpp:267] TRAIN Top shape for layer 31 'conv3_2/dw' 16 64 32 64 (2097152)
-I0510 14:48:30.108252  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.108255  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108263  5307 net.cpp:200] Created Layer conv3_2/dw/bn (32)
-I0510 14:48:30.108266  5307 net.cpp:572] conv3_2/dw/bn <- conv3_2/dw
-I0510 14:48:30.108271  5307 net.cpp:527] conv3_2/dw/bn -> conv3_2/dw (in-place)
-I0510 14:48:30.108546  5307 net.cpp:260] Setting up conv3_2/dw/bn
-I0510 14:48:30.108561  5307 net.cpp:267] TRAIN Top shape for layer 32 'conv3_2/dw/bn' 16 64 32 64 (2097152)
-I0510 14:48:30.108573  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Scale'
-I0510 14:48:30.108582  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108592  5307 net.cpp:200] Created Layer conv3_2/dw/scale (33)
-I0510 14:48:30.108598  5307 net.cpp:572] conv3_2/dw/scale <- conv3_2/dw
-I0510 14:48:30.108606  5307 net.cpp:527] conv3_2/dw/scale -> conv3_2/dw (in-place)
-I0510 14:48:30.108641  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Bias'
-I0510 14:48:30.108650  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108736  5307 net.cpp:260] Setting up conv3_2/dw/scale
-I0510 14:48:30.108747  5307 net.cpp:267] TRAIN Top shape for layer 33 'conv3_2/dw/scale' 16 64 32 64 (2097152)
-I0510 14:48:30.108757  5307 layer_factory.hpp:172] Creating layer 'relu3_2/dw' of type 'ReLU'
-I0510 14:48:30.108765  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108773  5307 net.cpp:200] Created Layer relu3_2/dw (34)
-I0510 14:48:30.108781  5307 net.cpp:572] relu3_2/dw <- conv3_2/dw
-I0510 14:48:30.108793  5307 net.cpp:527] relu3_2/dw -> conv3_2/dw (in-place)
-I0510 14:48:30.108806  5307 net.cpp:260] Setting up relu3_2/dw
-I0510 14:48:30.108815  5307 net.cpp:267] TRAIN Top shape for layer 34 'relu3_2/dw' 16 64 32 64 (2097152)
-I0510 14:48:30.108824  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep' of type 'Convolution'
-I0510 14:48:30.108830  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108842  5307 net.cpp:200] Created Layer conv3_2/sep (35)
-I0510 14:48:30.108850  5307 net.cpp:572] conv3_2/sep <- conv3_2/dw
-I0510 14:48:30.108857  5307 net.cpp:542] conv3_2/sep -> conv3_2/sep
-I0510 14:48:30.109174  5307 net.cpp:260] Setting up conv3_2/sep
-I0510 14:48:30.109182  5307 net.cpp:267] TRAIN Top shape for layer 35 'conv3_2/sep' 16 128 32 64 (4194304)
-I0510 14:48:30.109189  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.109192  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109200  5307 net.cpp:200] Created Layer conv3_2/sep/bn (36)
-I0510 14:48:30.109203  5307 net.cpp:572] conv3_2/sep/bn <- conv3_2/sep
-I0510 14:48:30.109207  5307 net.cpp:527] conv3_2/sep/bn -> conv3_2/sep (in-place)
-I0510 14:48:30.109417  5307 net.cpp:260] Setting up conv3_2/sep/bn
-I0510 14:48:30.109424  5307 net.cpp:267] TRAIN Top shape for layer 36 'conv3_2/sep/bn' 16 128 32 64 (4194304)
-I0510 14:48:30.109431  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Scale'
-I0510 14:48:30.109436  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109441  5307 net.cpp:200] Created Layer conv3_2/sep/scale (37)
-I0510 14:48:30.109446  5307 net.cpp:572] conv3_2/sep/scale <- conv3_2/sep
-I0510 14:48:30.109449  5307 net.cpp:527] conv3_2/sep/scale -> conv3_2/sep (in-place)
-I0510 14:48:30.109475  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Bias'
-I0510 14:48:30.109480  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109545  5307 net.cpp:260] Setting up conv3_2/sep/scale
-I0510 14:48:30.109552  5307 net.cpp:267] TRAIN Top shape for layer 37 'conv3_2/sep/scale' 16 128 32 64 (4194304)
-I0510 14:48:30.109558  5307 layer_factory.hpp:172] Creating layer 'relu3_2/sep' of type 'ReLU'
-I0510 14:48:30.109563  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109568  5307 net.cpp:200] Created Layer relu3_2/sep (38)
-I0510 14:48:30.109572  5307 net.cpp:572] relu3_2/sep <- conv3_2/sep
-I0510 14:48:30.109576  5307 net.cpp:527] relu3_2/sep -> conv3_2/sep (in-place)
-I0510 14:48:30.109582  5307 net.cpp:260] Setting up relu3_2/sep
-I0510 14:48:30.109586  5307 net.cpp:267] TRAIN Top shape for layer 38 'relu3_2/sep' 16 128 32 64 (4194304)
-I0510 14:48:30.109591  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw' of type 'Convolution'
-I0510 14:48:30.109596  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109604  5307 net.cpp:200] Created Layer conv4_1/dw (39)
-I0510 14:48:30.109607  5307 net.cpp:572] conv4_1/dw <- conv3_2/sep
-I0510 14:48:30.109612  5307 net.cpp:542] conv4_1/dw -> conv4_1/dw
-I0510 14:48:30.109755  5307 net.cpp:260] Setting up conv4_1/dw
-I0510 14:48:30.109761  5307 net.cpp:267] TRAIN Top shape for layer 39 'conv4_1/dw' 16 128 32 64 (4194304)
-I0510 14:48:30.109767  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.109771  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109777  5307 net.cpp:200] Created Layer conv4_1/dw/bn (40)
-I0510 14:48:30.109781  5307 net.cpp:572] conv4_1/dw/bn <- conv4_1/dw
-I0510 14:48:30.109786  5307 net.cpp:527] conv4_1/dw/bn -> conv4_1/dw (in-place)
-I0510 14:48:30.110059  5307 net.cpp:260] Setting up conv4_1/dw/bn
-I0510 14:48:30.110075  5307 net.cpp:267] TRAIN Top shape for layer 40 'conv4_1/dw/bn' 16 128 32 64 (4194304)
-I0510 14:48:30.110090  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Scale'
-I0510 14:48:30.110102  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.110112  5307 net.cpp:200] Created Layer conv4_1/dw/scale (41)
-I0510 14:48:30.110121  5307 net.cpp:572] conv4_1/dw/scale <- conv4_1/dw
-I0510 14:48:30.110129  5307 net.cpp:527] conv4_1/dw/scale -> conv4_1/dw (in-place)
-I0510 14:48:30.110170  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Bias'
-I0510 14:48:30.110905  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.111003  5307 net.cpp:260] Setting up conv4_1/dw/scale
-I0510 14:48:30.111017  5307 net.cpp:267] TRAIN Top shape for layer 41 'conv4_1/dw/scale' 16 128 32 64 (4194304)
-I0510 14:48:30.111029  5307 layer_factory.hpp:172] Creating layer 'relu4_1/dw' of type 'ReLU'
-I0510 14:48:30.111037  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.111047  5307 net.cpp:200] Created Layer relu4_1/dw (42)
-I0510 14:48:30.111055  5307 net.cpp:572] relu4_1/dw <- conv4_1/dw
-I0510 14:48:30.111064  5307 net.cpp:527] relu4_1/dw -> conv4_1/dw (in-place)
-I0510 14:48:30.111074  5307 net.cpp:260] Setting up relu4_1/dw
-I0510 14:48:30.111084  5307 net.cpp:267] TRAIN Top shape for layer 42 'relu4_1/dw' 16 128 32 64 (4194304)
-I0510 14:48:30.111093  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep' of type 'Convolution'
-I0510 14:48:30.111100  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.111114  5307 net.cpp:200] Created Layer conv4_1/sep (43)
-I0510 14:48:30.111122  5307 net.cpp:572] conv4_1/sep <- conv4_1/dw
-I0510 14:48:30.111131  5307 net.cpp:542] conv4_1/sep -> conv4_1/sep
-I0510 14:48:30.111766  5307 net.cpp:260] Setting up conv4_1/sep
-I0510 14:48:30.111775  5307 net.cpp:267] TRAIN Top shape for layer 43 'conv4_1/sep' 16 128 32 64 (4194304)
-I0510 14:48:30.111783  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.111786  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.111793  5307 net.cpp:200] Created Layer conv4_1/sep/bn (44)
-I0510 14:48:30.111798  5307 net.cpp:572] conv4_1/sep/bn <- conv4_1/sep
-I0510 14:48:30.111802  5307 net.cpp:527] conv4_1/sep/bn -> conv4_1/sep (in-place)
-I0510 14:48:30.112027  5307 net.cpp:260] Setting up conv4_1/sep/bn
-I0510 14:48:30.112035  5307 net.cpp:267] TRAIN Top shape for layer 44 'conv4_1/sep/bn' 16 128 32 64 (4194304)
-I0510 14:48:30.112045  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Scale'
-I0510 14:48:30.112049  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112056  5307 net.cpp:200] Created Layer conv4_1/sep/scale (45)
-I0510 14:48:30.112059  5307 net.cpp:572] conv4_1/sep/scale <- conv4_1/sep
-I0510 14:48:30.112063  5307 net.cpp:527] conv4_1/sep/scale -> conv4_1/sep (in-place)
-I0510 14:48:30.112092  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Bias'
-I0510 14:48:30.112097  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112161  5307 net.cpp:260] Setting up conv4_1/sep/scale
-I0510 14:48:30.112167  5307 net.cpp:267] TRAIN Top shape for layer 45 'conv4_1/sep/scale' 16 128 32 64 (4194304)
-I0510 14:48:30.112174  5307 layer_factory.hpp:172] Creating layer 'relu4_1/sep' of type 'ReLU'
-I0510 14:48:30.112179  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112184  5307 net.cpp:200] Created Layer relu4_1/sep (46)
-I0510 14:48:30.112187  5307 net.cpp:572] relu4_1/sep <- conv4_1/sep
-I0510 14:48:30.112191  5307 net.cpp:527] relu4_1/sep -> conv4_1/sep (in-place)
-I0510 14:48:30.112197  5307 net.cpp:260] Setting up relu4_1/sep
-I0510 14:48:30.112202  5307 net.cpp:267] TRAIN Top shape for layer 46 'relu4_1/sep' 16 128 32 64 (4194304)
-I0510 14:48:30.112215  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw' of type 'Convolution'
-I0510 14:48:30.112220  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112228  5307 net.cpp:200] Created Layer conv4_2/dw (47)
-I0510 14:48:30.112232  5307 net.cpp:572] conv4_2/dw <- conv4_1/sep
-I0510 14:48:30.112237  5307 net.cpp:542] conv4_2/dw -> conv4_2/dw
-I0510 14:48:30.112385  5307 net.cpp:260] Setting up conv4_2/dw
-I0510 14:48:30.112392  5307 net.cpp:267] TRAIN Top shape for layer 47 'conv4_2/dw' 16 128 16 32 (1048576)
-I0510 14:48:30.112399  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.112403  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112409  5307 net.cpp:200] Created Layer conv4_2/dw/bn (48)
-I0510 14:48:30.112413  5307 net.cpp:572] conv4_2/dw/bn <- conv4_2/dw
-I0510 14:48:30.112418  5307 net.cpp:527] conv4_2/dw/bn -> conv4_2/dw (in-place)
-I0510 14:48:30.112669  5307 net.cpp:260] Setting up conv4_2/dw/bn
-I0510 14:48:30.112685  5307 net.cpp:267] TRAIN Top shape for layer 48 'conv4_2/dw/bn' 16 128 16 32 (1048576)
-I0510 14:48:30.112696  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Scale'
-I0510 14:48:30.112705  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112715  5307 net.cpp:200] Created Layer conv4_2/dw/scale (49)
-I0510 14:48:30.112722  5307 net.cpp:572] conv4_2/dw/scale <- conv4_2/dw
-I0510 14:48:30.112730  5307 net.cpp:527] conv4_2/dw/scale -> conv4_2/dw (in-place)
-I0510 14:48:30.112766  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Bias'
-I0510 14:48:30.112776  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112857  5307 net.cpp:260] Setting up conv4_2/dw/scale
-I0510 14:48:30.112869  5307 net.cpp:267] TRAIN Top shape for layer 49 'conv4_2/dw/scale' 16 128 16 32 (1048576)
-I0510 14:48:30.112879  5307 layer_factory.hpp:172] Creating layer 'relu4_2/dw' of type 'ReLU'
-I0510 14:48:30.112887  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112896  5307 net.cpp:200] Created Layer relu4_2/dw (50)
-I0510 14:48:30.112905  5307 net.cpp:572] relu4_2/dw <- conv4_2/dw
-I0510 14:48:30.112912  5307 net.cpp:527] relu4_2/dw -> conv4_2/dw (in-place)
-I0510 14:48:30.112923  5307 net.cpp:260] Setting up relu4_2/dw
-I0510 14:48:30.112928  5307 net.cpp:267] TRAIN Top shape for layer 50 'relu4_2/dw' 16 128 16 32 (1048576)
-I0510 14:48:30.112934  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep' of type 'Convolution'
-I0510 14:48:30.112938  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112948  5307 net.cpp:200] Created Layer conv4_2/sep (51)
-I0510 14:48:30.112952  5307 net.cpp:572] conv4_2/sep <- conv4_2/dw
-I0510 14:48:30.112957  5307 net.cpp:542] conv4_2/sep -> conv4_2/sep
-I0510 14:48:30.113800  5307 net.cpp:260] Setting up conv4_2/sep
-I0510 14:48:30.113813  5307 net.cpp:267] TRAIN Top shape for layer 51 'conv4_2/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.113823  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.113831  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.113842  5307 net.cpp:200] Created Layer conv4_2/sep/bn (52)
-I0510 14:48:30.113849  5307 net.cpp:572] conv4_2/sep/bn <- conv4_2/sep
-I0510 14:48:30.113857  5307 net.cpp:527] conv4_2/sep/bn -> conv4_2/sep (in-place)
-I0510 14:48:30.114123  5307 net.cpp:260] Setting up conv4_2/sep/bn
-I0510 14:48:30.114135  5307 net.cpp:267] TRAIN Top shape for layer 52 'conv4_2/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.114147  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Scale'
-I0510 14:48:30.114156  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114173  5307 net.cpp:200] Created Layer conv4_2/sep/scale (53)
-I0510 14:48:30.114181  5307 net.cpp:572] conv4_2/sep/scale <- conv4_2/sep
-I0510 14:48:30.114189  5307 net.cpp:527] conv4_2/sep/scale -> conv4_2/sep (in-place)
-I0510 14:48:30.114230  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Bias'
-I0510 14:48:30.114235  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114305  5307 net.cpp:260] Setting up conv4_2/sep/scale
-I0510 14:48:30.114310  5307 net.cpp:267] TRAIN Top shape for layer 53 'conv4_2/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.114317  5307 layer_factory.hpp:172] Creating layer 'relu4_2/sep' of type 'ReLU'
-I0510 14:48:30.114321  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114326  5307 net.cpp:200] Created Layer relu4_2/sep (54)
-I0510 14:48:30.114331  5307 net.cpp:572] relu4_2/sep <- conv4_2/sep
-I0510 14:48:30.114336  5307 net.cpp:527] relu4_2/sep -> conv4_2/sep (in-place)
-I0510 14:48:30.114341  5307 net.cpp:260] Setting up relu4_2/sep
-I0510 14:48:30.114346  5307 net.cpp:267] TRAIN Top shape for layer 54 'relu4_2/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.114349  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw' of type 'Convolution'
-I0510 14:48:30.114354  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114362  5307 net.cpp:200] Created Layer conv5_1/dw (55)
-I0510 14:48:30.114365  5307 net.cpp:572] conv5_1/dw <- conv4_2/sep
-I0510 14:48:30.114370  5307 net.cpp:542] conv5_1/dw -> conv5_1/dw
-I0510 14:48:30.114540  5307 net.cpp:260] Setting up conv5_1/dw
-I0510 14:48:30.114547  5307 net.cpp:267] TRAIN Top shape for layer 55 'conv5_1/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.114553  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.114557  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114563  5307 net.cpp:200] Created Layer conv5_1/dw/bn (56)
-I0510 14:48:30.114567  5307 net.cpp:572] conv5_1/dw/bn <- conv5_1/dw
-I0510 14:48:30.114573  5307 net.cpp:527] conv5_1/dw/bn -> conv5_1/dw (in-place)
-I0510 14:48:30.114795  5307 net.cpp:260] Setting up conv5_1/dw/bn
-I0510 14:48:30.114802  5307 net.cpp:267] TRAIN Top shape for layer 56 'conv5_1/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.114810  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Scale'
-I0510 14:48:30.114820  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114830  5307 net.cpp:200] Created Layer conv5_1/dw/scale (57)
-I0510 14:48:30.114838  5307 net.cpp:572] conv5_1/dw/scale <- conv5_1/dw
-I0510 14:48:30.114845  5307 net.cpp:527] conv5_1/dw/scale -> conv5_1/dw (in-place)
-I0510 14:48:30.114882  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Bias'
-I0510 14:48:30.114892  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114976  5307 net.cpp:260] Setting up conv5_1/dw/scale
-I0510 14:48:30.114989  5307 net.cpp:267] TRAIN Top shape for layer 57 'conv5_1/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.114998  5307 layer_factory.hpp:172] Creating layer 'relu5_1/dw' of type 'ReLU'
-I0510 14:48:30.115006  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.115015  5307 net.cpp:200] Created Layer relu5_1/dw (58)
-I0510 14:48:30.115022  5307 net.cpp:572] relu5_1/dw <- conv5_1/dw
-I0510 14:48:30.115031  5307 net.cpp:527] relu5_1/dw -> conv5_1/dw (in-place)
-I0510 14:48:30.115041  5307 net.cpp:260] Setting up relu5_1/dw
-I0510 14:48:30.115049  5307 net.cpp:267] TRAIN Top shape for layer 58 'relu5_1/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.115057  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep' of type 'Convolution'
-I0510 14:48:30.115067  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.115084  5307 net.cpp:200] Created Layer conv5_1/sep (59)
-I0510 14:48:30.115093  5307 net.cpp:572] conv5_1/sep <- conv5_1/dw
-I0510 14:48:30.115101  5307 net.cpp:542] conv5_1/sep -> conv5_1/sep
-I0510 14:48:30.117199  5307 net.cpp:260] Setting up conv5_1/sep
-I0510 14:48:30.117218  5307 net.cpp:267] TRAIN Top shape for layer 59 'conv5_1/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.117230  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.117240  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117251  5307 net.cpp:200] Created Layer conv5_1/sep/bn (60)
-I0510 14:48:30.117260  5307 net.cpp:572] conv5_1/sep/bn <- conv5_1/sep
-I0510 14:48:30.117270  5307 net.cpp:527] conv5_1/sep/bn -> conv5_1/sep (in-place)
-I0510 14:48:30.117601  5307 net.cpp:260] Setting up conv5_1/sep/bn
-I0510 14:48:30.117615  5307 net.cpp:267] TRAIN Top shape for layer 60 'conv5_1/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.117628  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Scale'
-I0510 14:48:30.117640  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117650  5307 net.cpp:200] Created Layer conv5_1/sep/scale (61)
-I0510 14:48:30.117660  5307 net.cpp:572] conv5_1/sep/scale <- conv5_1/sep
-I0510 14:48:30.117669  5307 net.cpp:527] conv5_1/sep/scale -> conv5_1/sep (in-place)
-I0510 14:48:30.117710  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Bias'
-I0510 14:48:30.117722  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117818  5307 net.cpp:260] Setting up conv5_1/sep/scale
-I0510 14:48:30.117835  5307 net.cpp:267] TRAIN Top shape for layer 61 'conv5_1/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.117847  5307 layer_factory.hpp:172] Creating layer 'relu5_1/sep' of type 'ReLU'
-I0510 14:48:30.117853  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117861  5307 net.cpp:200] Created Layer relu5_1/sep (62)
-I0510 14:48:30.117866  5307 net.cpp:572] relu5_1/sep <- conv5_1/sep
-I0510 14:48:30.117871  5307 net.cpp:527] relu5_1/sep -> conv5_1/sep (in-place)
-I0510 14:48:30.117877  5307 net.cpp:260] Setting up relu5_1/sep
-I0510 14:48:30.117883  5307 net.cpp:267] TRAIN Top shape for layer 62 'relu5_1/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.117887  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw' of type 'Convolution'
-I0510 14:48:30.117892  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117900  5307 net.cpp:200] Created Layer conv5_2/dw (63)
-I0510 14:48:30.117903  5307 net.cpp:572] conv5_2/dw <- conv5_1/sep
-I0510 14:48:30.117908  5307 net.cpp:542] conv5_2/dw -> conv5_2/dw
-I0510 14:48:30.118083  5307 net.cpp:260] Setting up conv5_2/dw
-I0510 14:48:30.118090  5307 net.cpp:267] TRAIN Top shape for layer 63 'conv5_2/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.118096  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.118100  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118109  5307 net.cpp:200] Created Layer conv5_2/dw/bn (64)
-I0510 14:48:30.118113  5307 net.cpp:572] conv5_2/dw/bn <- conv5_2/dw
-I0510 14:48:30.118119  5307 net.cpp:527] conv5_2/dw/bn -> conv5_2/dw (in-place)
-I0510 14:48:30.118343  5307 net.cpp:260] Setting up conv5_2/dw/bn
-I0510 14:48:30.118350  5307 net.cpp:267] TRAIN Top shape for layer 64 'conv5_2/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.118357  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Scale'
-I0510 14:48:30.118361  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118367  5307 net.cpp:200] Created Layer conv5_2/dw/scale (65)
-I0510 14:48:30.118371  5307 net.cpp:572] conv5_2/dw/scale <- conv5_2/dw
-I0510 14:48:30.118376  5307 net.cpp:527] conv5_2/dw/scale -> conv5_2/dw (in-place)
-I0510 14:48:30.118410  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Bias'
-I0510 14:48:30.118415  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118484  5307 net.cpp:260] Setting up conv5_2/dw/scale
-I0510 14:48:30.118489  5307 net.cpp:267] TRAIN Top shape for layer 65 'conv5_2/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.118496  5307 layer_factory.hpp:172] Creating layer 'relu5_2/dw' of type 'ReLU'
-I0510 14:48:30.118500  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118505  5307 net.cpp:200] Created Layer relu5_2/dw (66)
-I0510 14:48:30.118510  5307 net.cpp:572] relu5_2/dw <- conv5_2/dw
-I0510 14:48:30.118515  5307 net.cpp:527] relu5_2/dw -> conv5_2/dw (in-place)
-I0510 14:48:30.118520  5307 net.cpp:260] Setting up relu5_2/dw
-I0510 14:48:30.118525  5307 net.cpp:267] TRAIN Top shape for layer 66 'relu5_2/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.118528  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep' of type 'Convolution'
-I0510 14:48:30.118533  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118542  5307 net.cpp:200] Created Layer conv5_2/sep (67)
-I0510 14:48:30.118546  5307 net.cpp:572] conv5_2/sep <- conv5_2/dw
-I0510 14:48:30.118551  5307 net.cpp:542] conv5_2/sep -> conv5_2/sep
-I0510 14:48:30.120138  5307 net.cpp:260] Setting up conv5_2/sep
-I0510 14:48:30.120154  5307 net.cpp:267] TRAIN Top shape for layer 67 'conv5_2/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.120165  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.120174  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120184  5307 net.cpp:200] Created Layer conv5_2/sep/bn (68)
-I0510 14:48:30.120193  5307 net.cpp:572] conv5_2/sep/bn <- conv5_2/sep
-I0510 14:48:30.120203  5307 net.cpp:527] conv5_2/sep/bn -> conv5_2/sep (in-place)
-I0510 14:48:30.120518  5307 net.cpp:260] Setting up conv5_2/sep/bn
-I0510 14:48:30.120535  5307 net.cpp:267] TRAIN Top shape for layer 68 'conv5_2/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.120548  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Scale'
-I0510 14:48:30.120555  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120565  5307 net.cpp:200] Created Layer conv5_2/sep/scale (69)
-I0510 14:48:30.120573  5307 net.cpp:572] conv5_2/sep/scale <- conv5_2/sep
-I0510 14:48:30.120581  5307 net.cpp:527] conv5_2/sep/scale -> conv5_2/sep (in-place)
-I0510 14:48:30.120617  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Bias'
-I0510 14:48:30.120626  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120719  5307 net.cpp:260] Setting up conv5_2/sep/scale
-I0510 14:48:30.120730  5307 net.cpp:267] TRAIN Top shape for layer 69 'conv5_2/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.120740  5307 layer_factory.hpp:172] Creating layer 'relu5_2/sep' of type 'ReLU'
-I0510 14:48:30.120748  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120757  5307 net.cpp:200] Created Layer relu5_2/sep (70)
-I0510 14:48:30.120764  5307 net.cpp:572] relu5_2/sep <- conv5_2/sep
-I0510 14:48:30.120772  5307 net.cpp:527] relu5_2/sep -> conv5_2/sep (in-place)
-I0510 14:48:30.120782  5307 net.cpp:260] Setting up relu5_2/sep
-I0510 14:48:30.120791  5307 net.cpp:267] TRAIN Top shape for layer 70 'relu5_2/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.120800  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw' of type 'Convolution'
-I0510 14:48:30.120807  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120818  5307 net.cpp:200] Created Layer conv5_3/dw (71)
-I0510 14:48:30.120829  5307 net.cpp:572] conv5_3/dw <- conv5_2/sep
-I0510 14:48:30.120838  5307 net.cpp:542] conv5_3/dw -> conv5_3/dw
-I0510 14:48:30.121068  5307 net.cpp:260] Setting up conv5_3/dw
-I0510 14:48:30.121081  5307 net.cpp:267] TRAIN Top shape for layer 71 'conv5_3/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.121091  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.121099  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121109  5307 net.cpp:200] Created Layer conv5_3/dw/bn (72)
-I0510 14:48:30.121116  5307 net.cpp:572] conv5_3/dw/bn <- conv5_3/dw
-I0510 14:48:30.121125  5307 net.cpp:527] conv5_3/dw/bn -> conv5_3/dw (in-place)
-I0510 14:48:30.121392  5307 net.cpp:260] Setting up conv5_3/dw/bn
-I0510 14:48:30.121398  5307 net.cpp:267] TRAIN Top shape for layer 72 'conv5_3/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.121407  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Scale'
-I0510 14:48:30.121410  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121417  5307 net.cpp:200] Created Layer conv5_3/dw/scale (73)
-I0510 14:48:30.121420  5307 net.cpp:572] conv5_3/dw/scale <- conv5_3/dw
-I0510 14:48:30.121425  5307 net.cpp:527] conv5_3/dw/scale -> conv5_3/dw (in-place)
-I0510 14:48:30.121454  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Bias'
-I0510 14:48:30.121459  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121527  5307 net.cpp:260] Setting up conv5_3/dw/scale
-I0510 14:48:30.121533  5307 net.cpp:267] TRAIN Top shape for layer 73 'conv5_3/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.121541  5307 layer_factory.hpp:172] Creating layer 'relu5_3/dw' of type 'ReLU'
-I0510 14:48:30.121544  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121549  5307 net.cpp:200] Created Layer relu5_3/dw (74)
-I0510 14:48:30.121553  5307 net.cpp:572] relu5_3/dw <- conv5_3/dw
-I0510 14:48:30.121558  5307 net.cpp:527] relu5_3/dw -> conv5_3/dw (in-place)
-I0510 14:48:30.121565  5307 net.cpp:260] Setting up relu5_3/dw
-I0510 14:48:30.121570  5307 net.cpp:267] TRAIN Top shape for layer 74 'relu5_3/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.121574  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep' of type 'Convolution'
-I0510 14:48:30.121578  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121587  5307 net.cpp:200] Created Layer conv5_3/sep (75)
-I0510 14:48:30.121589  5307 net.cpp:572] conv5_3/sep <- conv5_3/dw
-I0510 14:48:30.121594  5307 net.cpp:542] conv5_3/sep -> conv5_3/sep
-I0510 14:48:30.123428  5307 net.cpp:260] Setting up conv5_3/sep
-I0510 14:48:30.123436  5307 net.cpp:267] TRAIN Top shape for layer 75 'conv5_3/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.123442  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.123446  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123452  5307 net.cpp:200] Created Layer conv5_3/sep/bn (76)
-I0510 14:48:30.123456  5307 net.cpp:572] conv5_3/sep/bn <- conv5_3/sep
-I0510 14:48:30.123461  5307 net.cpp:527] conv5_3/sep/bn -> conv5_3/sep (in-place)
-I0510 14:48:30.123687  5307 net.cpp:260] Setting up conv5_3/sep/bn
-I0510 14:48:30.123692  5307 net.cpp:267] TRAIN Top shape for layer 76 'conv5_3/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.123700  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Scale'
-I0510 14:48:30.123703  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123711  5307 net.cpp:200] Created Layer conv5_3/sep/scale (77)
-I0510 14:48:30.123715  5307 net.cpp:572] conv5_3/sep/scale <- conv5_3/sep
-I0510 14:48:30.123720  5307 net.cpp:527] conv5_3/sep/scale -> conv5_3/sep (in-place)
-I0510 14:48:30.123749  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Bias'
-I0510 14:48:30.123754  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123829  5307 net.cpp:260] Setting up conv5_3/sep/scale
-I0510 14:48:30.123836  5307 net.cpp:267] TRAIN Top shape for layer 77 'conv5_3/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.123842  5307 layer_factory.hpp:172] Creating layer 'relu5_3/sep' of type 'ReLU'
-I0510 14:48:30.123847  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123852  5307 net.cpp:200] Created Layer relu5_3/sep (78)
-I0510 14:48:30.123855  5307 net.cpp:572] relu5_3/sep <- conv5_3/sep
-I0510 14:48:30.123859  5307 net.cpp:527] relu5_3/sep -> conv5_3/sep (in-place)
-I0510 14:48:30.123865  5307 net.cpp:260] Setting up relu5_3/sep
-I0510 14:48:30.123870  5307 net.cpp:267] TRAIN Top shape for layer 78 'relu5_3/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.123874  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw' of type 'Convolution'
-I0510 14:48:30.123878  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123886  5307 net.cpp:200] Created Layer conv5_4/dw (79)
-I0510 14:48:30.123890  5307 net.cpp:572] conv5_4/dw <- conv5_3/sep
-I0510 14:48:30.123894  5307 net.cpp:542] conv5_4/dw -> conv5_4/dw
-I0510 14:48:30.124126  5307 net.cpp:260] Setting up conv5_4/dw
-I0510 14:48:30.124142  5307 net.cpp:267] TRAIN Top shape for layer 79 'conv5_4/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.124152  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.124161  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124172  5307 net.cpp:200] Created Layer conv5_4/dw/bn (80)
-I0510 14:48:30.124181  5307 net.cpp:572] conv5_4/dw/bn <- conv5_4/dw
-I0510 14:48:30.124189  5307 net.cpp:527] conv5_4/dw/bn -> conv5_4/dw (in-place)
-I0510 14:48:30.124495  5307 net.cpp:260] Setting up conv5_4/dw/bn
-I0510 14:48:30.124506  5307 net.cpp:267] TRAIN Top shape for layer 80 'conv5_4/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.124517  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Scale'
-I0510 14:48:30.124533  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124545  5307 net.cpp:200] Created Layer conv5_4/dw/scale (81)
-I0510 14:48:30.124554  5307 net.cpp:572] conv5_4/dw/scale <- conv5_4/dw
-I0510 14:48:30.124563  5307 net.cpp:527] conv5_4/dw/scale -> conv5_4/dw (in-place)
-I0510 14:48:30.124601  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Bias'
-I0510 14:48:30.124611  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124696  5307 net.cpp:260] Setting up conv5_4/dw/scale
-I0510 14:48:30.124706  5307 net.cpp:267] TRAIN Top shape for layer 81 'conv5_4/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.124716  5307 layer_factory.hpp:172] Creating layer 'relu5_4/dw' of type 'ReLU'
-I0510 14:48:30.124724  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124732  5307 net.cpp:200] Created Layer relu5_4/dw (82)
-I0510 14:48:30.124740  5307 net.cpp:572] relu5_4/dw <- conv5_4/dw
-I0510 14:48:30.124748  5307 net.cpp:527] relu5_4/dw -> conv5_4/dw (in-place)
-I0510 14:48:30.124758  5307 net.cpp:260] Setting up relu5_4/dw
-I0510 14:48:30.124766  5307 net.cpp:267] TRAIN Top shape for layer 82 'relu5_4/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.124774  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep' of type 'Convolution'
-I0510 14:48:30.124783  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124794  5307 net.cpp:200] Created Layer conv5_4/sep (83)
-I0510 14:48:30.124802  5307 net.cpp:572] conv5_4/sep <- conv5_4/dw
-I0510 14:48:30.124810  5307 net.cpp:542] conv5_4/sep -> conv5_4/sep
-I0510 14:48:30.128613  5307 net.cpp:260] Setting up conv5_4/sep
-I0510 14:48:30.128695  5307 net.cpp:267] TRAIN Top shape for layer 83 'conv5_4/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.128736  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.128757  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.128780  5307 net.cpp:200] Created Layer conv5_4/sep/bn (84)
-I0510 14:48:30.128794  5307 net.cpp:572] conv5_4/sep/bn <- conv5_4/sep
-I0510 14:48:30.128809  5307 net.cpp:527] conv5_4/sep/bn -> conv5_4/sep (in-place)
-I0510 14:48:30.129273  5307 net.cpp:260] Setting up conv5_4/sep/bn
-I0510 14:48:30.129310  5307 net.cpp:267] TRAIN Top shape for layer 84 'conv5_4/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.129335  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Scale'
-I0510 14:48:30.129354  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.129376  5307 net.cpp:200] Created Layer conv5_4/sep/scale (85)
-I0510 14:48:30.129393  5307 net.cpp:572] conv5_4/sep/scale <- conv5_4/sep
-I0510 14:48:30.129410  5307 net.cpp:527] conv5_4/sep/scale -> conv5_4/sep (in-place)
-I0510 14:48:30.129469  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Bias'
-I0510 14:48:30.129492  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.129631  5307 net.cpp:260] Setting up conv5_4/sep/scale
-I0510 14:48:30.129653  5307 net.cpp:267] TRAIN Top shape for layer 85 'conv5_4/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.129673  5307 layer_factory.hpp:172] Creating layer 'relu5_4/sep' of type 'ReLU'
-I0510 14:48:30.129693  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.129714  5307 net.cpp:200] Created Layer relu5_4/sep (86)
-I0510 14:48:30.129737  5307 net.cpp:572] relu5_4/sep <- conv5_4/sep
-I0510 14:48:30.129758  5307 net.cpp:527] relu5_4/sep -> conv5_4/sep (in-place)
-I0510 14:48:30.129781  5307 net.cpp:260] Setting up relu5_4/sep
-I0510 14:48:30.129801  5307 net.cpp:267] TRAIN Top shape for layer 86 'relu5_4/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.129820  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw' of type 'Convolution'
-I0510 14:48:30.129839  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.129868  5307 net.cpp:200] Created Layer conv5_5/dw (87)
-I0510 14:48:30.129887  5307 net.cpp:572] conv5_5/dw <- conv5_4/sep
-I0510 14:48:30.129905  5307 net.cpp:542] conv5_5/dw -> conv5_5/dw
-I0510 14:48:30.130306  5307 net.cpp:260] Setting up conv5_5/dw
-I0510 14:48:30.130342  5307 net.cpp:267] TRAIN Top shape for layer 87 'conv5_5/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.130373  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.130393  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.130414  5307 net.cpp:200] Created Layer conv5_5/dw/bn (88)
-I0510 14:48:30.130434  5307 net.cpp:572] conv5_5/dw/bn <- conv5_5/dw
-I0510 14:48:30.130450  5307 net.cpp:527] conv5_5/dw/bn -> conv5_5/dw (in-place)
-I0510 14:48:30.130820  5307 net.cpp:260] Setting up conv5_5/dw/bn
-I0510 14:48:30.130844  5307 net.cpp:267] TRAIN Top shape for layer 88 'conv5_5/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.130873  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Scale'
-I0510 14:48:30.130889  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.130909  5307 net.cpp:200] Created Layer conv5_5/dw/scale (89)
-I0510 14:48:30.130926  5307 net.cpp:572] conv5_5/dw/scale <- conv5_5/dw
-I0510 14:48:30.130942  5307 net.cpp:527] conv5_5/dw/scale -> conv5_5/dw (in-place)
-I0510 14:48:30.130995  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Bias'
-I0510 14:48:30.131014  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.131129  5307 net.cpp:260] Setting up conv5_5/dw/scale
-I0510 14:48:30.131156  5307 net.cpp:267] TRAIN Top shape for layer 89 'conv5_5/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.131183  5307 layer_factory.hpp:172] Creating layer 'relu5_5/dw' of type 'ReLU'
-I0510 14:48:30.131199  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.131216  5307 net.cpp:200] Created Layer relu5_5/dw (90)
-I0510 14:48:30.131229  5307 net.cpp:572] relu5_5/dw <- conv5_5/dw
-I0510 14:48:30.131244  5307 net.cpp:527] relu5_5/dw -> conv5_5/dw (in-place)
-I0510 14:48:30.131261  5307 net.cpp:260] Setting up relu5_5/dw
-I0510 14:48:30.131278  5307 net.cpp:267] TRAIN Top shape for layer 90 'relu5_5/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.131291  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep' of type 'Convolution'
-I0510 14:48:30.131305  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.131325  5307 net.cpp:200] Created Layer conv5_5/sep (91)
-I0510 14:48:30.131340  5307 net.cpp:572] conv5_5/sep <- conv5_5/dw
-I0510 14:48:30.131356  5307 net.cpp:542] conv5_5/sep -> conv5_5/sep
-I0510 14:48:30.133545  5307 net.cpp:260] Setting up conv5_5/sep
-I0510 14:48:30.133577  5307 net.cpp:267] TRAIN Top shape for layer 91 'conv5_5/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.133596  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.133611  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.133628  5307 net.cpp:200] Created Layer conv5_5/sep/bn (92)
-I0510 14:48:30.133644  5307 net.cpp:572] conv5_5/sep/bn <- conv5_5/sep
-I0510 14:48:30.133661  5307 net.cpp:527] conv5_5/sep/bn -> conv5_5/sep (in-place)
-I0510 14:48:30.134043  5307 net.cpp:260] Setting up conv5_5/sep/bn
-I0510 14:48:30.134069  5307 net.cpp:267] TRAIN Top shape for layer 92 'conv5_5/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.134088  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Scale'
-I0510 14:48:30.134104  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134121  5307 net.cpp:200] Created Layer conv5_5/sep/scale (93)
-I0510 14:48:30.134137  5307 net.cpp:572] conv5_5/sep/scale <- conv5_5/sep
-I0510 14:48:30.134155  5307 net.cpp:527] conv5_5/sep/scale -> conv5_5/sep (in-place)
-I0510 14:48:30.134205  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Bias'
-I0510 14:48:30.134222  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134336  5307 net.cpp:260] Setting up conv5_5/sep/scale
-I0510 14:48:30.134356  5307 net.cpp:267] TRAIN Top shape for layer 93 'conv5_5/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.134379  5307 layer_factory.hpp:172] Creating layer 'relu5_5/sep' of type 'ReLU'
-I0510 14:48:30.134397  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134414  5307 net.cpp:200] Created Layer relu5_5/sep (94)
-I0510 14:48:30.134429  5307 net.cpp:572] relu5_5/sep <- conv5_5/sep
-I0510 14:48:30.134443  5307 net.cpp:527] relu5_5/sep -> conv5_5/sep (in-place)
-I0510 14:48:30.134460  5307 net.cpp:260] Setting up relu5_5/sep
-I0510 14:48:30.134475  5307 net.cpp:267] TRAIN Top shape for layer 94 'relu5_5/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.134490  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep_relu5_5/sep_0_split' of type 'Split'
-I0510 14:48:30.134505  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134519  5307 net.cpp:200] Created Layer conv5_5/sep_relu5_5/sep_0_split (95)
-I0510 14:48:30.134533  5307 net.cpp:572] conv5_5/sep_relu5_5/sep_0_split <- conv5_5/sep
-I0510 14:48:30.134548  5307 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_0
-I0510 14:48:30.134565  5307 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_1
-I0510 14:48:30.134613  5307 net.cpp:260] Setting up conv5_5/sep_relu5_5/sep_0_split
-I0510 14:48:30.134639  5307 net.cpp:267] TRAIN Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 16 256 16 32 (2097152)
-I0510 14:48:30.134663  5307 net.cpp:267] TRAIN Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 16 256 16 32 (2097152)
-I0510 14:48:30.134680  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw' of type 'Convolution'
-I0510 14:48:30.134696  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134718  5307 net.cpp:200] Created Layer conv5_6/dw (96)
-I0510 14:48:30.134734  5307 net.cpp:572] conv5_6/dw <- conv5_5/sep_relu5_5/sep_0_split_0
-I0510 14:48:30.134749  5307 net.cpp:542] conv5_6/dw -> conv5_6/dw
-I0510 14:48:30.135025  5307 net.cpp:260] Setting up conv5_6/dw
-I0510 14:48:30.135047  5307 net.cpp:267] TRAIN Top shape for layer 96 'conv5_6/dw' 16 256 8 16 (524288)
-I0510 14:48:30.135064  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.135078  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135095  5307 net.cpp:200] Created Layer conv5_6/dw/bn (97)
-I0510 14:48:30.135114  5307 net.cpp:572] conv5_6/dw/bn <- conv5_6/dw
-I0510 14:48:30.135130  5307 net.cpp:527] conv5_6/dw/bn -> conv5_6/dw (in-place)
-I0510 14:48:30.135478  5307 net.cpp:260] Setting up conv5_6/dw/bn
-I0510 14:48:30.135500  5307 net.cpp:267] TRAIN Top shape for layer 97 'conv5_6/dw/bn' 16 256 8 16 (524288)
-I0510 14:48:30.135519  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Scale'
-I0510 14:48:30.135534  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135550  5307 net.cpp:200] Created Layer conv5_6/dw/scale (98)
-I0510 14:48:30.135568  5307 net.cpp:572] conv5_6/dw/scale <- conv5_6/dw
-I0510 14:48:30.135586  5307 net.cpp:527] conv5_6/dw/scale -> conv5_6/dw (in-place)
-I0510 14:48:30.135637  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Bias'
-I0510 14:48:30.135654  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135759  5307 net.cpp:260] Setting up conv5_6/dw/scale
-I0510 14:48:30.135778  5307 net.cpp:267] TRAIN Top shape for layer 98 'conv5_6/dw/scale' 16 256 8 16 (524288)
-I0510 14:48:30.135797  5307 layer_factory.hpp:172] Creating layer 'relu5_6/dw' of type 'ReLU'
-I0510 14:48:30.135814  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135830  5307 net.cpp:200] Created Layer relu5_6/dw (99)
-I0510 14:48:30.135845  5307 net.cpp:572] relu5_6/dw <- conv5_6/dw
-I0510 14:48:30.135860  5307 net.cpp:527] relu5_6/dw -> conv5_6/dw (in-place)
-I0510 14:48:30.135876  5307 net.cpp:260] Setting up relu5_6/dw
-I0510 14:48:30.135891  5307 net.cpp:267] TRAIN Top shape for layer 99 'relu5_6/dw' 16 256 8 16 (524288)
-I0510 14:48:30.135906  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep' of type 'Convolution'
-I0510 14:48:30.135921  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135939  5307 net.cpp:200] Created Layer conv5_6/sep (100)
-I0510 14:48:30.135953  5307 net.cpp:572] conv5_6/sep <- conv5_6/dw
-I0510 14:48:30.135967  5307 net.cpp:542] conv5_6/sep -> conv5_6/sep
-I0510 14:48:30.140096  5307 net.cpp:260] Setting up conv5_6/sep
-I0510 14:48:30.140142  5307 net.cpp:267] TRAIN Top shape for layer 100 'conv5_6/sep' 16 512 8 16 (1048576)
-I0510 14:48:30.140163  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.140183  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.140204  5307 net.cpp:200] Created Layer conv5_6/sep/bn (101)
-I0510 14:48:30.140221  5307 net.cpp:572] conv5_6/sep/bn <- conv5_6/sep
-I0510 14:48:30.140239  5307 net.cpp:527] conv5_6/sep/bn -> conv5_6/sep (in-place)
-I0510 14:48:30.140622  5307 net.cpp:260] Setting up conv5_6/sep/bn
-I0510 14:48:30.140650  5307 net.cpp:267] TRAIN Top shape for layer 101 'conv5_6/sep/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.140676  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Scale'
-I0510 14:48:30.140700  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.140722  5307 net.cpp:200] Created Layer conv5_6/sep/scale (102)
-I0510 14:48:30.140741  5307 net.cpp:572] conv5_6/sep/scale <- conv5_6/sep
-I0510 14:48:30.140758  5307 net.cpp:527] conv5_6/sep/scale -> conv5_6/sep (in-place)
-I0510 14:48:30.140813  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Bias'
-I0510 14:48:30.140830  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.140949  5307 net.cpp:260] Setting up conv5_6/sep/scale
-I0510 14:48:30.140969  5307 net.cpp:267] TRAIN Top shape for layer 102 'conv5_6/sep/scale' 16 512 8 16 (1048576)
-I0510 14:48:30.140987  5307 layer_factory.hpp:172] Creating layer 'relu5_6/sep' of type 'ReLU'
-I0510 14:48:30.141003  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.141021  5307 net.cpp:200] Created Layer relu5_6/sep (103)
-I0510 14:48:30.141036  5307 net.cpp:572] relu5_6/sep <- conv5_6/sep
-I0510 14:48:30.141052  5307 net.cpp:527] relu5_6/sep -> conv5_6/sep (in-place)
-I0510 14:48:30.141070  5307 net.cpp:260] Setting up relu5_6/sep
-I0510 14:48:30.141088  5307 net.cpp:267] TRAIN Top shape for layer 103 'relu5_6/sep' 16 512 8 16 (1048576)
-I0510 14:48:30.141103  5307 layer_factory.hpp:172] Creating layer 'conv6/dw' of type 'Convolution'
-I0510 14:48:30.141118  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.141139  5307 net.cpp:200] Created Layer conv6/dw (104)
-I0510 14:48:30.141163  5307 net.cpp:572] conv6/dw <- conv5_6/sep
-I0510 14:48:30.141181  5307 net.cpp:542] conv6/dw -> conv6/dw
-I0510 14:48:30.141530  5307 net.cpp:260] Setting up conv6/dw
-I0510 14:48:30.141553  5307 net.cpp:267] TRAIN Top shape for layer 104 'conv6/dw' 16 512 8 16 (1048576)
-I0510 14:48:30.141571  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.141587  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.141602  5307 net.cpp:200] Created Layer conv6/dw/bn (105)
-I0510 14:48:30.141618  5307 net.cpp:572] conv6/dw/bn <- conv6/dw
-I0510 14:48:30.141631  5307 net.cpp:527] conv6/dw/bn -> conv6/dw (in-place)
-I0510 14:48:30.141988  5307 net.cpp:260] Setting up conv6/dw/bn
-I0510 14:48:30.142010  5307 net.cpp:267] TRAIN Top shape for layer 105 'conv6/dw/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.142029  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Scale'
-I0510 14:48:30.142045  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.142060  5307 net.cpp:200] Created Layer conv6/dw/scale (106)
-I0510 14:48:30.142076  5307 net.cpp:572] conv6/dw/scale <- conv6/dw
-I0510 14:48:30.142089  5307 net.cpp:527] conv6/dw/scale -> conv6/dw (in-place)
-I0510 14:48:30.142138  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Bias'
-I0510 14:48:30.142154  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.142272  5307 net.cpp:260] Setting up conv6/dw/scale
-I0510 14:48:30.142292  5307 net.cpp:267] TRAIN Top shape for layer 106 'conv6/dw/scale' 16 512 8 16 (1048576)
-I0510 14:48:30.142313  5307 layer_factory.hpp:172] Creating layer 'relu6/dw' of type 'ReLU'
-I0510 14:48:30.142328  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.142344  5307 net.cpp:200] Created Layer relu6/dw (107)
-I0510 14:48:30.142359  5307 net.cpp:572] relu6/dw <- conv6/dw
-I0510 14:48:30.142375  5307 net.cpp:527] relu6/dw -> conv6/dw (in-place)
-I0510 14:48:30.142392  5307 net.cpp:260] Setting up relu6/dw
-I0510 14:48:30.142410  5307 net.cpp:267] TRAIN Top shape for layer 107 'relu6/dw' 16 512 8 16 (1048576)
-I0510 14:48:30.142429  5307 layer_factory.hpp:172] Creating layer 'conv6/sep' of type 'Convolution'
-I0510 14:48:30.142452  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.142474  5307 net.cpp:200] Created Layer conv6/sep (108)
-I0510 14:48:30.142490  5307 net.cpp:572] conv6/sep <- conv6/dw
-I0510 14:48:30.142504  5307 net.cpp:542] conv6/sep -> conv6/sep
-I0510 14:48:30.148224  5307 net.cpp:260] Setting up conv6/sep
-I0510 14:48:30.148257  5307 net.cpp:267] TRAIN Top shape for layer 108 'conv6/sep' 16 512 8 16 (1048576)
-I0510 14:48:30.148267  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.148273  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148284  5307 net.cpp:200] Created Layer conv6/sep/bn (109)
-I0510 14:48:30.148300  5307 net.cpp:572] conv6/sep/bn <- conv6/sep
-I0510 14:48:30.148313  5307 net.cpp:527] conv6/sep/bn -> conv6/sep (in-place)
-I0510 14:48:30.148607  5307 net.cpp:260] Setting up conv6/sep/bn
-I0510 14:48:30.148614  5307 net.cpp:267] TRAIN Top shape for layer 109 'conv6/sep/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.148622  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Scale'
-I0510 14:48:30.148633  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148646  5307 net.cpp:200] Created Layer conv6/sep/scale (110)
-I0510 14:48:30.148651  5307 net.cpp:572] conv6/sep/scale <- conv6/sep
-I0510 14:48:30.148655  5307 net.cpp:527] conv6/sep/scale -> conv6/sep (in-place)
-I0510 14:48:30.148696  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Bias'
-I0510 14:48:30.148701  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148789  5307 net.cpp:260] Setting up conv6/sep/scale
-I0510 14:48:30.148797  5307 net.cpp:267] TRAIN Top shape for layer 110 'conv6/sep/scale' 16 512 8 16 (1048576)
-I0510 14:48:30.148802  5307 layer_factory.hpp:172] Creating layer 'relu6/sep' of type 'ReLU'
-I0510 14:48:30.148813  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148820  5307 net.cpp:200] Created Layer relu6/sep (111)
-I0510 14:48:30.148829  5307 net.cpp:572] relu6/sep <- conv6/sep
-I0510 14:48:30.148834  5307 net.cpp:527] relu6/sep -> conv6/sep (in-place)
-I0510 14:48:30.148846  5307 net.cpp:260] Setting up relu6/sep
-I0510 14:48:30.148852  5307 net.cpp:267] TRAIN Top shape for layer 111 'relu6/sep' 16 512 8 16 (1048576)
-I0510 14:48:30.148861  5307 layer_factory.hpp:172] Creating layer 'conv6/sep_relu6/sep_0_split' of type 'Split'
-I0510 14:48:30.148867  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148877  5307 net.cpp:200] Created Layer conv6/sep_relu6/sep_0_split (112)
-I0510 14:48:30.148890  5307 net.cpp:572] conv6/sep_relu6/sep_0_split <- conv6/sep
-I0510 14:48:30.148902  5307 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_0
-I0510 14:48:30.148916  5307 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_1
-I0510 14:48:30.148953  5307 net.cpp:260] Setting up conv6/sep_relu6/sep_0_split
-I0510 14:48:30.148969  5307 net.cpp:267] TRAIN Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.148983  5307 net.cpp:267] TRAIN Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.148994  5307 layer_factory.hpp:172] Creating layer 'pool6' of type 'Pooling'
-I0510 14:48:30.149006  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149024  5307 net.cpp:200] Created Layer pool6 (113)
-I0510 14:48:30.149036  5307 net.cpp:572] pool6 <- conv6/sep_relu6/sep_0_split_0
-I0510 14:48:30.149049  5307 net.cpp:542] pool6 -> pool6
-I0510 14:48:30.149118  5307 net.cpp:260] Setting up pool6
-I0510 14:48:30.149134  5307 net.cpp:267] TRAIN Top shape for layer 113 'pool6' 16 512 5 9 (368640)
-I0510 14:48:30.149150  5307 layer_factory.hpp:172] Creating layer 'pool6_pool6_0_split' of type 'Split'
-I0510 14:48:30.149171  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149184  5307 net.cpp:200] Created Layer pool6_pool6_0_split (114)
-I0510 14:48:30.149196  5307 net.cpp:572] pool6_pool6_0_split <- pool6
-I0510 14:48:30.149209  5307 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_0
-I0510 14:48:30.149220  5307 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_1
-I0510 14:48:30.149258  5307 net.cpp:260] Setting up pool6_pool6_0_split
-I0510 14:48:30.149273  5307 net.cpp:267] TRAIN Top shape for layer 114 'pool6_pool6_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.149286  5307 net.cpp:267] TRAIN Top shape for layer 114 'pool6_pool6_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.149297  5307 layer_factory.hpp:172] Creating layer 'pool7' of type 'Pooling'
-I0510 14:48:30.149302  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149309  5307 net.cpp:200] Created Layer pool7 (115)
-I0510 14:48:30.149318  5307 net.cpp:572] pool7 <- pool6_pool6_0_split_0
-I0510 14:48:30.149324  5307 net.cpp:542] pool7 -> pool7
-I0510 14:48:30.149363  5307 net.cpp:260] Setting up pool7
-I0510 14:48:30.149369  5307 net.cpp:267] TRAIN Top shape for layer 115 'pool7' 16 512 3 5 (122880)
-I0510 14:48:30.149379  5307 layer_factory.hpp:172] Creating layer 'pool7_pool7_0_split' of type 'Split'
-I0510 14:48:30.149384  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149394  5307 net.cpp:200] Created Layer pool7_pool7_0_split (116)
-I0510 14:48:30.149399  5307 net.cpp:572] pool7_pool7_0_split <- pool7
-I0510 14:48:30.149408  5307 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_0
-I0510 14:48:30.149418  5307 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_1
-I0510 14:48:30.149449  5307 net.cpp:260] Setting up pool7_pool7_0_split
-I0510 14:48:30.149456  5307 net.cpp:267] TRAIN Top shape for layer 116 'pool7_pool7_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.149466  5307 net.cpp:267] TRAIN Top shape for layer 116 'pool7_pool7_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.149471  5307 layer_factory.hpp:172] Creating layer 'pool8' of type 'Pooling'
-I0510 14:48:30.149479  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149487  5307 net.cpp:200] Created Layer pool8 (117)
-I0510 14:48:30.149495  5307 net.cpp:572] pool8 <- pool7_pool7_0_split_0
-I0510 14:48:30.149500  5307 net.cpp:542] pool8 -> pool8
-I0510 14:48:30.149540  5307 net.cpp:260] Setting up pool8
-I0510 14:48:30.149546  5307 net.cpp:267] TRAIN Top shape for layer 117 'pool8' 16 512 3 5 (122880)
-I0510 14:48:30.149556  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1' of type 'Convolution'
-I0510 14:48:30.149562  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149576  5307 net.cpp:200] Created Layer ctx_output1/1x1 (118)
-I0510 14:48:30.149581  5307 net.cpp:572] ctx_output1/1x1 <- conv5_5/sep_relu5_5/sep_0_split_1
-I0510 14:48:30.149591  5307 net.cpp:542] ctx_output1/1x1 -> ctx_output1/1x1
-I0510 14:48:30.153045  5307 net.cpp:260] Setting up ctx_output1/1x1
-I0510 14:48:30.153059  5307 net.cpp:267] TRAIN Top shape for layer 118 'ctx_output1/1x1' 16 512 16 32 (4194304)
-I0510 14:48:30.153066  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.153079  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.153091  5307 net.cpp:200] Created Layer ctx_output1/1x1/bn (119)
-I0510 14:48:30.153097  5307 net.cpp:572] ctx_output1/1x1/bn <- ctx_output1/1x1
-I0510 14:48:30.153102  5307 net.cpp:527] ctx_output1/1x1/bn -> ctx_output1/1x1 (in-place)
-I0510 14:48:30.153360  5307 net.cpp:260] Setting up ctx_output1/1x1/bn
-I0510 14:48:30.153368  5307 net.cpp:267] TRAIN Top shape for layer 119 'ctx_output1/1x1/bn' 16 512 16 32 (4194304)
-I0510 14:48:30.153378  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/relu' of type 'ReLU'
-I0510 14:48:30.153395  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.153403  5307 net.cpp:200] Created Layer ctx_output1/1x1/relu (120)
-I0510 14:48:30.153412  5307 net.cpp:572] ctx_output1/1x1/relu <- ctx_output1/1x1
-I0510 14:48:30.153419  5307 net.cpp:527] ctx_output1/1x1/relu -> ctx_output1/1x1 (in-place)
-I0510 14:48:30.153429  5307 net.cpp:260] Setting up ctx_output1/1x1/relu
-I0510 14:48:30.153435  5307 net.cpp:267] TRAIN Top shape for layer 120 'ctx_output1/1x1/relu' 16 512 16 32 (4194304)
-I0510 14:48:30.153445  5307 layer_factory.hpp:172] Creating layer 'ctx_output1' of type 'Convolution'
-I0510 14:48:30.153450  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.153465  5307 net.cpp:200] Created Layer ctx_output1 (121)
-I0510 14:48:30.153470  5307 net.cpp:572] ctx_output1 <- ctx_output1/1x1
-I0510 14:48:30.153475  5307 net.cpp:542] ctx_output1 -> ctx_output1
-I0510 14:48:30.153739  5307 net.cpp:260] Setting up ctx_output1
-I0510 14:48:30.153748  5307 net.cpp:267] TRAIN Top shape for layer 121 'ctx_output1' 16 512 16 32 (4194304)
-I0510 14:48:30.153754  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/bn' of type 'BatchNorm'
-I0510 14:48:30.153764  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.153772  5307 net.cpp:200] Created Layer ctx_output1/bn (122)
-I0510 14:48:30.153781  5307 net.cpp:572] ctx_output1/bn <- ctx_output1
-I0510 14:48:30.153787  5307 net.cpp:527] ctx_output1/bn -> ctx_output1 (in-place)
-I0510 14:48:30.154044  5307 net.cpp:260] Setting up ctx_output1/bn
-I0510 14:48:30.154052  5307 net.cpp:267] TRAIN Top shape for layer 122 'ctx_output1/bn' 16 512 16 32 (4194304)
-I0510 14:48:30.154067  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu' of type 'ReLU'
-I0510 14:48:30.154073  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.154079  5307 net.cpp:200] Created Layer ctx_output1/relu (123)
-I0510 14:48:30.154088  5307 net.cpp:572] ctx_output1/relu <- ctx_output1
-I0510 14:48:30.154095  5307 net.cpp:527] ctx_output1/relu -> ctx_output1 (in-place)
-I0510 14:48:30.154106  5307 net.cpp:260] Setting up ctx_output1/relu
-I0510 14:48:30.154111  5307 net.cpp:267] TRAIN Top shape for layer 123 'ctx_output1/relu' 16 512 16 32 (4194304)
-I0510 14:48:30.154120  5307 layer_factory.hpp:172] Creating layer 'ctx_output1_ctx_output1/relu_0_split' of type 'Split'
-I0510 14:48:30.154126  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.154136  5307 net.cpp:200] Created Layer ctx_output1_ctx_output1/relu_0_split (124)
-I0510 14:48:30.154141  5307 net.cpp:572] ctx_output1_ctx_output1/relu_0_split <- ctx_output1
-I0510 14:48:30.154150  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_0
-I0510 14:48:30.154157  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_1
-I0510 14:48:30.154167  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_2
-I0510 14:48:30.154211  5307 net.cpp:260] Setting up ctx_output1_ctx_output1/relu_0_split
-I0510 14:48:30.154217  5307 net.cpp:267] TRAIN Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 16 512 16 32 (4194304)
-I0510 14:48:30.154227  5307 net.cpp:267] TRAIN Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 16 512 16 32 (4194304)
-I0510 14:48:30.154233  5307 net.cpp:267] TRAIN Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 16 512 16 32 (4194304)
-I0510 14:48:30.154242  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1' of type 'Convolution'
-I0510 14:48:30.154247  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.154265  5307 net.cpp:200] Created Layer ctx_output2/1x1 (125)
-I0510 14:48:30.154275  5307 net.cpp:572] ctx_output2/1x1 <- conv6/sep_relu6/sep_0_split_1
-I0510 14:48:30.154285  5307 net.cpp:542] ctx_output2/1x1 -> ctx_output2/1x1
-I0510 14:48:30.162034  5307 net.cpp:260] Setting up ctx_output2/1x1
-I0510 14:48:30.162204  5307 net.cpp:267] TRAIN Top shape for layer 125 'ctx_output2/1x1' 16 512 8 16 (1048576)
-I0510 14:48:30.162295  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.162374  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.162456  5307 net.cpp:200] Created Layer ctx_output2/1x1/bn (126)
-I0510 14:48:30.162525  5307 net.cpp:572] ctx_output2/1x1/bn <- ctx_output2/1x1
-I0510 14:48:30.162591  5307 net.cpp:527] ctx_output2/1x1/bn -> ctx_output2/1x1 (in-place)
-I0510 14:48:30.163060  5307 net.cpp:260] Setting up ctx_output2/1x1/bn
-I0510 14:48:30.163136  5307 net.cpp:267] TRAIN Top shape for layer 126 'ctx_output2/1x1/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.163213  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/relu' of type 'ReLU'
-I0510 14:48:30.163283  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.163358  5307 net.cpp:200] Created Layer ctx_output2/1x1/relu (127)
-I0510 14:48:30.163419  5307 net.cpp:572] ctx_output2/1x1/relu <- ctx_output2/1x1
-I0510 14:48:30.163480  5307 net.cpp:527] ctx_output2/1x1/relu -> ctx_output2/1x1 (in-place)
-I0510 14:48:30.163552  5307 net.cpp:260] Setting up ctx_output2/1x1/relu
-I0510 14:48:30.163614  5307 net.cpp:267] TRAIN Top shape for layer 127 'ctx_output2/1x1/relu' 16 512 8 16 (1048576)
-I0510 14:48:30.163682  5307 layer_factory.hpp:172] Creating layer 'ctx_output2' of type 'Convolution'
-I0510 14:48:30.163758  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.163839  5307 net.cpp:200] Created Layer ctx_output2 (128)
-I0510 14:48:30.163899  5307 net.cpp:572] ctx_output2 <- ctx_output2/1x1
-I0510 14:48:30.163960  5307 net.cpp:542] ctx_output2 -> ctx_output2
-I0510 14:48:30.164412  5307 net.cpp:260] Setting up ctx_output2
-I0510 14:48:30.164489  5307 net.cpp:267] TRAIN Top shape for layer 128 'ctx_output2' 16 512 8 16 (1048576)
-I0510 14:48:30.164567  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/bn' of type 'BatchNorm'
-I0510 14:48:30.164635  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.164711  5307 net.cpp:200] Created Layer ctx_output2/bn (129)
-I0510 14:48:30.164772  5307 net.cpp:572] ctx_output2/bn <- ctx_output2
-I0510 14:48:30.164831  5307 net.cpp:527] ctx_output2/bn -> ctx_output2 (in-place)
-I0510 14:48:30.165230  5307 net.cpp:260] Setting up ctx_output2/bn
-I0510 14:48:30.165298  5307 net.cpp:267] TRAIN Top shape for layer 129 'ctx_output2/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.165375  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu' of type 'ReLU'
-I0510 14:48:30.165443  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.165515  5307 net.cpp:200] Created Layer ctx_output2/relu (130)
-I0510 14:48:30.165576  5307 net.cpp:572] ctx_output2/relu <- ctx_output2
-I0510 14:48:30.165642  5307 net.cpp:527] ctx_output2/relu -> ctx_output2 (in-place)
-I0510 14:48:30.165704  5307 net.cpp:260] Setting up ctx_output2/relu
-I0510 14:48:30.165763  5307 net.cpp:267] TRAIN Top shape for layer 130 'ctx_output2/relu' 16 512 8 16 (1048576)
-I0510 14:48:30.165832  5307 layer_factory.hpp:172] Creating layer 'ctx_output2_ctx_output2/relu_0_split' of type 'Split'
-I0510 14:48:30.165905  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.165974  5307 net.cpp:200] Created Layer ctx_output2_ctx_output2/relu_0_split (131)
-I0510 14:48:30.166040  5307 net.cpp:572] ctx_output2_ctx_output2/relu_0_split <- ctx_output2
-I0510 14:48:30.166112  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_0
-I0510 14:48:30.166188  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_1
-I0510 14:48:30.166267  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_2
-I0510 14:48:30.166391  5307 net.cpp:260] Setting up ctx_output2_ctx_output2/relu_0_split
-I0510 14:48:30.166460  5307 net.cpp:267] TRAIN Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.166540  5307 net.cpp:267] TRAIN Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.166615  5307 net.cpp:267] TRAIN Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.166692  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1' of type 'Convolution'
-I0510 14:48:30.166769  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.166844  5307 net.cpp:200] Created Layer ctx_output3/1x1 (132)
-I0510 14:48:30.166905  5307 net.cpp:572] ctx_output3/1x1 <- pool6_pool6_0_split_1
-I0510 14:48:30.166970  5307 net.cpp:542] ctx_output3/1x1 -> ctx_output3/1x1
-I0510 14:48:30.175863  5307 net.cpp:260] Setting up ctx_output3/1x1
-I0510 14:48:30.175884  5307 net.cpp:267] TRAIN Top shape for layer 132 'ctx_output3/1x1' 16 512 5 9 (368640)
-I0510 14:48:30.175894  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.175899  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.175916  5307 net.cpp:200] Created Layer ctx_output3/1x1/bn (133)
-I0510 14:48:30.176038  5307 net.cpp:572] ctx_output3/1x1/bn <- ctx_output3/1x1
-I0510 14:48:30.176079  5307 net.cpp:527] ctx_output3/1x1/bn -> ctx_output3/1x1 (in-place)
-I0510 14:48:30.176417  5307 net.cpp:260] Setting up ctx_output3/1x1/bn
-I0510 14:48:30.176426  5307 net.cpp:267] TRAIN Top shape for layer 133 'ctx_output3/1x1/bn' 16 512 5 9 (368640)
-I0510 14:48:30.176435  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/relu' of type 'ReLU'
-I0510 14:48:30.176491  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.176533  5307 net.cpp:200] Created Layer ctx_output3/1x1/relu (134)
-I0510 14:48:30.176587  5307 net.cpp:572] ctx_output3/1x1/relu <- ctx_output3/1x1
-I0510 14:48:30.176594  5307 net.cpp:527] ctx_output3/1x1/relu -> ctx_output3/1x1 (in-place)
-I0510 14:48:30.176601  5307 net.cpp:260] Setting up ctx_output3/1x1/relu
-I0510 14:48:30.176676  5307 net.cpp:267] TRAIN Top shape for layer 134 'ctx_output3/1x1/relu' 16 512 5 9 (368640)
-I0510 14:48:30.176682  5307 layer_factory.hpp:172] Creating layer 'ctx_output3' of type 'Convolution'
-I0510 14:48:30.176738  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.176784  5307 net.cpp:200] Created Layer ctx_output3 (135)
-I0510 14:48:30.176790  5307 net.cpp:572] ctx_output3 <- ctx_output3/1x1
-I0510 14:48:30.176795  5307 net.cpp:542] ctx_output3 -> ctx_output3
-I0510 14:48:30.177225  5307 net.cpp:260] Setting up ctx_output3
-I0510 14:48:30.177243  5307 net.cpp:267] TRAIN Top shape for layer 135 'ctx_output3' 16 512 5 9 (368640)
-I0510 14:48:30.177256  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/bn' of type 'BatchNorm'
-I0510 14:48:30.177265  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.177276  5307 net.cpp:200] Created Layer ctx_output3/bn (136)
-I0510 14:48:30.177286  5307 net.cpp:572] ctx_output3/bn <- ctx_output3
-I0510 14:48:30.177296  5307 net.cpp:527] ctx_output3/bn -> ctx_output3 (in-place)
-I0510 14:48:30.177644  5307 net.cpp:260] Setting up ctx_output3/bn
-I0510 14:48:30.177659  5307 net.cpp:267] TRAIN Top shape for layer 136 'ctx_output3/bn' 16 512 5 9 (368640)
-I0510 14:48:30.177676  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu' of type 'ReLU'
-I0510 14:48:30.177685  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.177903  5307 net.cpp:200] Created Layer ctx_output3/relu (137)
-I0510 14:48:30.177911  5307 net.cpp:572] ctx_output3/relu <- ctx_output3
-I0510 14:48:30.177914  5307 net.cpp:527] ctx_output3/relu -> ctx_output3 (in-place)
-I0510 14:48:30.177976  5307 net.cpp:260] Setting up ctx_output3/relu
-I0510 14:48:30.177984  5307 net.cpp:267] TRAIN Top shape for layer 137 'ctx_output3/relu' 16 512 5 9 (368640)
-I0510 14:48:30.178035  5307 layer_factory.hpp:172] Creating layer 'ctx_output3_ctx_output3/relu_0_split' of type 'Split'
-I0510 14:48:30.178041  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.178047  5307 net.cpp:200] Created Layer ctx_output3_ctx_output3/relu_0_split (138)
-I0510 14:48:30.178133  5307 net.cpp:572] ctx_output3_ctx_output3/relu_0_split <- ctx_output3
-I0510 14:48:30.178143  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_0
-I0510 14:48:30.178200  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_1
-I0510 14:48:30.178207  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_2
-I0510 14:48:30.178302  5307 net.cpp:260] Setting up ctx_output3_ctx_output3/relu_0_split
-I0510 14:48:30.178309  5307 net.cpp:267] TRAIN Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.178367  5307 net.cpp:267] TRAIN Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.178375  5307 net.cpp:267] TRAIN Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.178445  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1' of type 'Convolution'
-I0510 14:48:30.178452  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.178521  5307 net.cpp:200] Created Layer ctx_output4/1x1 (139)
-I0510 14:48:30.178527  5307 net.cpp:572] ctx_output4/1x1 <- pool7_pool7_0_split_1
-I0510 14:48:30.178581  5307 net.cpp:542] ctx_output4/1x1 -> ctx_output4/1x1
-I0510 14:48:30.183876  5307 net.cpp:260] Setting up ctx_output4/1x1
-I0510 14:48:30.183899  5307 net.cpp:267] TRAIN Top shape for layer 139 'ctx_output4/1x1' 16 512 3 5 (122880)
-I0510 14:48:30.183907  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.183912  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.184043  5307 net.cpp:200] Created Layer ctx_output4/1x1/bn (140)
-I0510 14:48:30.184052  5307 net.cpp:572] ctx_output4/1x1/bn <- ctx_output4/1x1
-I0510 14:48:30.184064  5307 net.cpp:527] ctx_output4/1x1/bn -> ctx_output4/1x1 (in-place)
-I0510 14:48:30.184386  5307 net.cpp:260] Setting up ctx_output4/1x1/bn
-I0510 14:48:30.184393  5307 net.cpp:267] TRAIN Top shape for layer 140 'ctx_output4/1x1/bn' 16 512 3 5 (122880)
-I0510 14:48:30.184403  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/relu' of type 'ReLU'
-I0510 14:48:30.184415  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.184427  5307 net.cpp:200] Created Layer ctx_output4/1x1/relu (141)
-I0510 14:48:30.184437  5307 net.cpp:572] ctx_output4/1x1/relu <- ctx_output4/1x1
-I0510 14:48:30.184448  5307 net.cpp:527] ctx_output4/1x1/relu -> ctx_output4/1x1 (in-place)
-I0510 14:48:30.184461  5307 net.cpp:260] Setting up ctx_output4/1x1/relu
-I0510 14:48:30.184473  5307 net.cpp:267] TRAIN Top shape for layer 141 'ctx_output4/1x1/relu' 16 512 3 5 (122880)
-I0510 14:48:30.184482  5307 layer_factory.hpp:172] Creating layer 'ctx_output4' of type 'Convolution'
-I0510 14:48:30.184491  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.184509  5307 net.cpp:200] Created Layer ctx_output4 (142)
-I0510 14:48:30.184520  5307 net.cpp:572] ctx_output4 <- ctx_output4/1x1
-I0510 14:48:30.184541  5307 net.cpp:542] ctx_output4 -> ctx_output4
-I0510 14:48:30.184945  5307 net.cpp:260] Setting up ctx_output4
-I0510 14:48:30.184970  5307 net.cpp:267] TRAIN Top shape for layer 142 'ctx_output4' 16 512 3 5 (122880)
-I0510 14:48:30.184983  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/bn' of type 'BatchNorm'
-I0510 14:48:30.184994  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.185008  5307 net.cpp:200] Created Layer ctx_output4/bn (143)
-I0510 14:48:30.185017  5307 net.cpp:572] ctx_output4/bn <- ctx_output4
-I0510 14:48:30.185027  5307 net.cpp:527] ctx_output4/bn -> ctx_output4 (in-place)
-I0510 14:48:30.185374  5307 net.cpp:260] Setting up ctx_output4/bn
-I0510 14:48:30.185382  5307 net.cpp:267] TRAIN Top shape for layer 143 'ctx_output4/bn' 16 512 3 5 (122880)
-I0510 14:48:30.185391  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu' of type 'ReLU'
-I0510 14:48:30.185402  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.185415  5307 net.cpp:200] Created Layer ctx_output4/relu (144)
-I0510 14:48:30.185425  5307 net.cpp:572] ctx_output4/relu <- ctx_output4
-I0510 14:48:30.185436  5307 net.cpp:527] ctx_output4/relu -> ctx_output4 (in-place)
-I0510 14:48:30.185448  5307 net.cpp:260] Setting up ctx_output4/relu
-I0510 14:48:30.185459  5307 net.cpp:267] TRAIN Top shape for layer 144 'ctx_output4/relu' 16 512 3 5 (122880)
-I0510 14:48:30.185469  5307 layer_factory.hpp:172] Creating layer 'ctx_output4_ctx_output4/relu_0_split' of type 'Split'
-I0510 14:48:30.185479  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.185492  5307 net.cpp:200] Created Layer ctx_output4_ctx_output4/relu_0_split (145)
-I0510 14:48:30.185501  5307 net.cpp:572] ctx_output4_ctx_output4/relu_0_split <- ctx_output4
-I0510 14:48:30.185513  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_0
-I0510 14:48:30.185525  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_1
-I0510 14:48:30.185537  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_2
-I0510 14:48:30.185593  5307 net.cpp:260] Setting up ctx_output4_ctx_output4/relu_0_split
-I0510 14:48:30.185607  5307 net.cpp:267] TRAIN Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.185619  5307 net.cpp:267] TRAIN Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.185631  5307 net.cpp:267] TRAIN Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.185640  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1' of type 'Convolution'
-I0510 14:48:30.185650  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.185667  5307 net.cpp:200] Created Layer ctx_output5/1x1 (146)
-I0510 14:48:30.185678  5307 net.cpp:572] ctx_output5/1x1 <- pool8
-I0510 14:48:30.185688  5307 net.cpp:542] ctx_output5/1x1 -> ctx_output5/1x1
-I0510 14:48:30.194860  5307 net.cpp:260] Setting up ctx_output5/1x1
-I0510 14:48:30.194931  5307 net.cpp:267] TRAIN Top shape for layer 146 'ctx_output5/1x1' 16 512 3 5 (122880)
-I0510 14:48:30.194957  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.194974  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.194999  5307 net.cpp:200] Created Layer ctx_output5/1x1/bn (147)
-I0510 14:48:30.195019  5307 net.cpp:572] ctx_output5/1x1/bn <- ctx_output5/1x1
-I0510 14:48:30.195035  5307 net.cpp:527] ctx_output5/1x1/bn -> ctx_output5/1x1 (in-place)
-I0510 14:48:30.195438  5307 net.cpp:260] Setting up ctx_output5/1x1/bn
-I0510 14:48:30.195466  5307 net.cpp:267] TRAIN Top shape for layer 147 'ctx_output5/1x1/bn' 16 512 3 5 (122880)
-I0510 14:48:30.195488  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/relu' of type 'ReLU'
-I0510 14:48:30.195513  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.195540  5307 net.cpp:200] Created Layer ctx_output5/1x1/relu (148)
-I0510 14:48:30.195557  5307 net.cpp:572] ctx_output5/1x1/relu <- ctx_output5/1x1
-I0510 14:48:30.195574  5307 net.cpp:527] ctx_output5/1x1/relu -> ctx_output5/1x1 (in-place)
-I0510 14:48:30.195593  5307 net.cpp:260] Setting up ctx_output5/1x1/relu
-I0510 14:48:30.195610  5307 net.cpp:267] TRAIN Top shape for layer 148 'ctx_output5/1x1/relu' 16 512 3 5 (122880)
-I0510 14:48:30.195626  5307 layer_factory.hpp:172] Creating layer 'ctx_output5' of type 'Convolution'
-I0510 14:48:30.195641  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.195664  5307 net.cpp:200] Created Layer ctx_output5 (149)
-I0510 14:48:30.195683  5307 net.cpp:572] ctx_output5 <- ctx_output5/1x1
-I0510 14:48:30.195698  5307 net.cpp:542] ctx_output5 -> ctx_output5
-I0510 14:48:30.196110  5307 net.cpp:260] Setting up ctx_output5
-I0510 14:48:30.196135  5307 net.cpp:267] TRAIN Top shape for layer 149 'ctx_output5' 16 512 3 5 (122880)
-I0510 14:48:30.196156  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/bn' of type 'BatchNorm'
-I0510 14:48:30.196174  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.196193  5307 net.cpp:200] Created Layer ctx_output5/bn (150)
-I0510 14:48:30.196210  5307 net.cpp:572] ctx_output5/bn <- ctx_output5
-I0510 14:48:30.196226  5307 net.cpp:527] ctx_output5/bn -> ctx_output5 (in-place)
-I0510 14:48:30.196609  5307 net.cpp:260] Setting up ctx_output5/bn
-I0510 14:48:30.196635  5307 net.cpp:267] TRAIN Top shape for layer 150 'ctx_output5/bn' 16 512 3 5 (122880)
-I0510 14:48:30.196662  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu' of type 'ReLU'
-I0510 14:48:30.196681  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.196698  5307 net.cpp:200] Created Layer ctx_output5/relu (151)
-I0510 14:48:30.196717  5307 net.cpp:572] ctx_output5/relu <- ctx_output5
-I0510 14:48:30.196732  5307 net.cpp:527] ctx_output5/relu -> ctx_output5 (in-place)
-I0510 14:48:30.196750  5307 net.cpp:260] Setting up ctx_output5/relu
-I0510 14:48:30.196768  5307 net.cpp:267] TRAIN Top shape for layer 151 'ctx_output5/relu' 16 512 3 5 (122880)
-I0510 14:48:30.196784  5307 layer_factory.hpp:172] Creating layer 'ctx_output5_ctx_output5/relu_0_split' of type 'Split'
-I0510 14:48:30.196800  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.196818  5307 net.cpp:200] Created Layer ctx_output5_ctx_output5/relu_0_split (152)
-I0510 14:48:30.196833  5307 net.cpp:572] ctx_output5_ctx_output5/relu_0_split <- ctx_output5
-I0510 14:48:30.196849  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_0
-I0510 14:48:30.196867  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_1
-I0510 14:48:30.196887  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_2
-I0510 14:48:30.196943  5307 net.cpp:260] Setting up ctx_output5_ctx_output5/relu_0_split
-I0510 14:48:30.196961  5307 net.cpp:267] TRAIN Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.196979  5307 net.cpp:267] TRAIN Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.196995  5307 net.cpp:267] TRAIN Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.197012  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.197028  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.197051  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc (153)
-I0510 14:48:30.197068  5307 net.cpp:572] ctx_output1/relu_mbox_loc <- ctx_output1_ctx_output1/relu_0_split_0
-I0510 14:48:30.197089  5307 net.cpp:542] ctx_output1/relu_mbox_loc -> ctx_output1/relu_mbox_loc
-I0510 14:48:30.197599  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc
-I0510 14:48:30.197623  5307 net.cpp:267] TRAIN Top shape for layer 153 'ctx_output1/relu_mbox_loc' 16 16 16 32 (131072)
-I0510 14:48:30.197641  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.197657  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.197681  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_perm (154)
-I0510 14:48:30.197700  5307 net.cpp:572] ctx_output1/relu_mbox_loc_perm <- ctx_output1/relu_mbox_loc
-I0510 14:48:30.197717  5307 net.cpp:542] ctx_output1/relu_mbox_loc_perm -> ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.197830  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.197850  5307 net.cpp:267] TRAIN Top shape for layer 154 'ctx_output1/relu_mbox_loc_perm' 16 16 32 16 (131072)
-I0510 14:48:30.197866  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.197883  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.197902  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_flat (155)
-I0510 14:48:30.197918  5307 net.cpp:572] ctx_output1/relu_mbox_loc_flat <- ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.197934  5307 net.cpp:542] ctx_output1/relu_mbox_loc_flat -> ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.198081  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.198103  5307 net.cpp:267] TRAIN Top shape for layer 155 'ctx_output1/relu_mbox_loc_flat' 16 8192 (131072)
-I0510 14:48:30.198122  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.198138  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.198158  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf (156)
-I0510 14:48:30.198174  5307 net.cpp:572] ctx_output1/relu_mbox_conf <- ctx_output1_ctx_output1/relu_0_split_1
-I0510 14:48:30.198191  5307 net.cpp:542] ctx_output1/relu_mbox_conf -> ctx_output1/relu_mbox_conf
-I0510 14:48:30.199424  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf
-I0510 14:48:30.199432  5307 net.cpp:267] TRAIN Top shape for layer 156 'ctx_output1/relu_mbox_conf' 16 84 16 32 (688128)
-I0510 14:48:30.199439  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.199455  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.199476  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_perm (157)
-I0510 14:48:30.199491  5307 net.cpp:572] ctx_output1/relu_mbox_conf_perm <- ctx_output1/relu_mbox_conf
-I0510 14:48:30.199507  5307 net.cpp:542] ctx_output1/relu_mbox_conf_perm -> ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.199615  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.199636  5307 net.cpp:267] TRAIN Top shape for layer 157 'ctx_output1/relu_mbox_conf_perm' 16 16 32 84 (688128)
-I0510 14:48:30.199651  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.199667  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.199683  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_flat (158)
-I0510 14:48:30.199700  5307 net.cpp:572] ctx_output1/relu_mbox_conf_flat <- ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.199718  5307 net.cpp:542] ctx_output1/relu_mbox_conf_flat -> ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.202023  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.202046  5307 net.cpp:267] TRAIN Top shape for layer 158 'ctx_output1/relu_mbox_conf_flat' 16 43008 (688128)
-I0510 14:48:30.202054  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.202088  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.202116  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_priorbox (159)
-I0510 14:48:30.202134  5307 net.cpp:572] ctx_output1/relu_mbox_priorbox <- ctx_output1_ctx_output1/relu_0_split_2
-I0510 14:48:30.202153  5307 net.cpp:572] ctx_output1/relu_mbox_priorbox <- data_data_0_split_1
-I0510 14:48:30.202172  5307 net.cpp:542] ctx_output1/relu_mbox_priorbox -> ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.202232  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.202253  5307 net.cpp:267] TRAIN Top shape for layer 159 'ctx_output1/relu_mbox_priorbox' 1 2 8192 (16384)
-I0510 14:48:30.202270  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.202286  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.202309  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc (160)
-I0510 14:48:30.202325  5307 net.cpp:572] ctx_output2/relu_mbox_loc <- ctx_output2_ctx_output2/relu_0_split_0
-I0510 14:48:30.202342  5307 net.cpp:542] ctx_output2/relu_mbox_loc -> ctx_output2/relu_mbox_loc
-I0510 14:48:30.202988  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc
-I0510 14:48:30.203012  5307 net.cpp:267] TRAIN Top shape for layer 160 'ctx_output2/relu_mbox_loc' 16 24 8 16 (49152)
-I0510 14:48:30.203033  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.203050  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.203073  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_perm (161)
-I0510 14:48:30.203092  5307 net.cpp:572] ctx_output2/relu_mbox_loc_perm <- ctx_output2/relu_mbox_loc
-I0510 14:48:30.203110  5307 net.cpp:542] ctx_output2/relu_mbox_loc_perm -> ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.203215  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.203235  5307 net.cpp:267] TRAIN Top shape for layer 161 'ctx_output2/relu_mbox_loc_perm' 16 8 16 24 (49152)
-I0510 14:48:30.203253  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.203269  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.203286  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_flat (162)
-I0510 14:48:30.203301  5307 net.cpp:572] ctx_output2/relu_mbox_loc_flat <- ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.203318  5307 net.cpp:542] ctx_output2/relu_mbox_loc_flat -> ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.203414  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.203434  5307 net.cpp:267] TRAIN Top shape for layer 162 'ctx_output2/relu_mbox_loc_flat' 16 3072 (49152)
-I0510 14:48:30.203452  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.203469  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.203488  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf (163)
-I0510 14:48:30.203505  5307 net.cpp:572] ctx_output2/relu_mbox_conf <- ctx_output2_ctx_output2/relu_0_split_1
-I0510 14:48:30.203522  5307 net.cpp:542] ctx_output2/relu_mbox_conf -> ctx_output2/relu_mbox_conf
-I0510 14:48:30.205476  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf
-I0510 14:48:30.205487  5307 net.cpp:267] TRAIN Top shape for layer 163 'ctx_output2/relu_mbox_conf' 16 126 8 16 (258048)
-I0510 14:48:30.205520  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.205536  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.205556  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_perm (164)
-I0510 14:48:30.205574  5307 net.cpp:572] ctx_output2/relu_mbox_conf_perm <- ctx_output2/relu_mbox_conf
-I0510 14:48:30.205595  5307 net.cpp:542] ctx_output2/relu_mbox_conf_perm -> ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.205690  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.205698  5307 net.cpp:267] TRAIN Top shape for layer 164 'ctx_output2/relu_mbox_conf_perm' 16 8 16 126 (258048)
-I0510 14:48:30.205719  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.205734  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.205750  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_flat (165)
-I0510 14:48:30.205765  5307 net.cpp:572] ctx_output2/relu_mbox_conf_flat <- ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.205780  5307 net.cpp:542] ctx_output2/relu_mbox_conf_flat -> ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.206703  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.206729  5307 net.cpp:267] TRAIN Top shape for layer 165 'ctx_output2/relu_mbox_conf_flat' 16 16128 (258048)
-I0510 14:48:30.206745  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.206761  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.206779  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_priorbox (166)
-I0510 14:48:30.206794  5307 net.cpp:572] ctx_output2/relu_mbox_priorbox <- ctx_output2_ctx_output2/relu_0_split_2
-I0510 14:48:30.206810  5307 net.cpp:572] ctx_output2/relu_mbox_priorbox <- data_data_0_split_2
-I0510 14:48:30.206826  5307 net.cpp:542] ctx_output2/relu_mbox_priorbox -> ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.206867  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.206888  5307 net.cpp:267] TRAIN Top shape for layer 166 'ctx_output2/relu_mbox_priorbox' 1 2 3072 (6144)
-I0510 14:48:30.206904  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.206919  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.206944  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc (167)
-I0510 14:48:30.206959  5307 net.cpp:572] ctx_output3/relu_mbox_loc <- ctx_output3_ctx_output3/relu_0_split_0
-I0510 14:48:30.206975  5307 net.cpp:542] ctx_output3/relu_mbox_loc -> ctx_output3/relu_mbox_loc
-I0510 14:48:30.207593  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc
-I0510 14:48:30.207613  5307 net.cpp:267] TRAIN Top shape for layer 167 'ctx_output3/relu_mbox_loc' 16 24 5 9 (17280)
-I0510 14:48:30.207634  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.207653  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.207671  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_perm (168)
-I0510 14:48:30.207690  5307 net.cpp:572] ctx_output3/relu_mbox_loc_perm <- ctx_output3/relu_mbox_loc
-I0510 14:48:30.207707  5307 net.cpp:542] ctx_output3/relu_mbox_loc_perm -> ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.207818  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.207839  5307 net.cpp:267] TRAIN Top shape for layer 168 'ctx_output3/relu_mbox_loc_perm' 16 5 9 24 (17280)
-I0510 14:48:30.207854  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.207870  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.207886  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_flat (169)
-I0510 14:48:30.207901  5307 net.cpp:572] ctx_output3/relu_mbox_loc_flat <- ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.207916  5307 net.cpp:542] ctx_output3/relu_mbox_loc_flat -> ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.207991  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.208011  5307 net.cpp:267] TRAIN Top shape for layer 169 'ctx_output3/relu_mbox_loc_flat' 16 1080 (17280)
-I0510 14:48:30.208036  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.208052  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.208072  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf (170)
-I0510 14:48:30.208088  5307 net.cpp:572] ctx_output3/relu_mbox_conf <- ctx_output3_ctx_output3/relu_0_split_1
-I0510 14:48:30.208104  5307 net.cpp:542] ctx_output3/relu_mbox_conf -> ctx_output3/relu_mbox_conf
-I0510 14:48:30.209836  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf
-I0510 14:48:30.209846  5307 net.cpp:267] TRAIN Top shape for layer 170 'ctx_output3/relu_mbox_conf' 16 126 5 9 (90720)
-I0510 14:48:30.209878  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.209895  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.209915  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_perm (171)
-I0510 14:48:30.209931  5307 net.cpp:572] ctx_output3/relu_mbox_conf_perm <- ctx_output3/relu_mbox_conf
-I0510 14:48:30.209949  5307 net.cpp:542] ctx_output3/relu_mbox_conf_perm -> ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.210062  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.210083  5307 net.cpp:267] TRAIN Top shape for layer 171 'ctx_output3/relu_mbox_conf_perm' 16 5 9 126 (90720)
-I0510 14:48:30.210099  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.210116  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.210136  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_flat (172)
-I0510 14:48:30.210152  5307 net.cpp:572] ctx_output3/relu_mbox_conf_flat <- ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.210170  5307 net.cpp:542] ctx_output3/relu_mbox_conf_flat -> ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.210278  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.210299  5307 net.cpp:267] TRAIN Top shape for layer 172 'ctx_output3/relu_mbox_conf_flat' 16 5670 (90720)
-I0510 14:48:30.210316  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.210331  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.210348  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_priorbox (173)
-I0510 14:48:30.210366  5307 net.cpp:572] ctx_output3/relu_mbox_priorbox <- ctx_output3_ctx_output3/relu_0_split_2
-I0510 14:48:30.210383  5307 net.cpp:572] ctx_output3/relu_mbox_priorbox <- data_data_0_split_3
-I0510 14:48:30.210399  5307 net.cpp:542] ctx_output3/relu_mbox_priorbox -> ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.210436  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.210455  5307 net.cpp:267] TRAIN Top shape for layer 173 'ctx_output3/relu_mbox_priorbox' 1 2 1080 (2160)
-I0510 14:48:30.210472  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.210489  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.210510  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc (174)
-I0510 14:48:30.210525  5307 net.cpp:572] ctx_output4/relu_mbox_loc <- ctx_output4_ctx_output4/relu_0_split_0
-I0510 14:48:30.210542  5307 net.cpp:542] ctx_output4/relu_mbox_loc -> ctx_output4/relu_mbox_loc
-I0510 14:48:30.210978  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc
-I0510 14:48:30.210986  5307 net.cpp:267] TRAIN Top shape for layer 174 'ctx_output4/relu_mbox_loc' 16 16 3 5 (3840)
-I0510 14:48:30.211015  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.211032  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.211056  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_perm (175)
-I0510 14:48:30.211083  5307 net.cpp:572] ctx_output4/relu_mbox_loc_perm <- ctx_output4/relu_mbox_loc
-I0510 14:48:30.211099  5307 net.cpp:542] ctx_output4/relu_mbox_loc_perm -> ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.211210  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.211230  5307 net.cpp:267] TRAIN Top shape for layer 175 'ctx_output4/relu_mbox_loc_perm' 16 3 5 16 (3840)
-I0510 14:48:30.211247  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.211263  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.211282  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_flat (176)
-I0510 14:48:30.211297  5307 net.cpp:572] ctx_output4/relu_mbox_loc_flat <- ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.211313  5307 net.cpp:542] ctx_output4/relu_mbox_loc_flat -> ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.211381  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.211403  5307 net.cpp:267] TRAIN Top shape for layer 176 'ctx_output4/relu_mbox_loc_flat' 16 240 (3840)
-I0510 14:48:30.211419  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.211434  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.211457  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf (177)
-I0510 14:48:30.211473  5307 net.cpp:572] ctx_output4/relu_mbox_conf <- ctx_output4_ctx_output4/relu_0_split_1
-I0510 14:48:30.211493  5307 net.cpp:542] ctx_output4/relu_mbox_conf -> ctx_output4/relu_mbox_conf
-I0510 14:48:30.212776  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf
-I0510 14:48:30.212785  5307 net.cpp:267] TRAIN Top shape for layer 177 'ctx_output4/relu_mbox_conf' 16 84 3 5 (20160)
-I0510 14:48:30.212822  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.212841  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.212859  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_perm (178)
-I0510 14:48:30.212877  5307 net.cpp:572] ctx_output4/relu_mbox_conf_perm <- ctx_output4/relu_mbox_conf
-I0510 14:48:30.212894  5307 net.cpp:542] ctx_output4/relu_mbox_conf_perm -> ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.213009  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.213030  5307 net.cpp:267] TRAIN Top shape for layer 178 'ctx_output4/relu_mbox_conf_perm' 16 3 5 84 (20160)
-I0510 14:48:30.213047  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.213063  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.213080  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_flat (179)
-I0510 14:48:30.213096  5307 net.cpp:572] ctx_output4/relu_mbox_conf_flat <- ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.213112  5307 net.cpp:542] ctx_output4/relu_mbox_conf_flat -> ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.213191  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.213210  5307 net.cpp:267] TRAIN Top shape for layer 179 'ctx_output4/relu_mbox_conf_flat' 16 1260 (20160)
-I0510 14:48:30.213227  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.213241  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.213259  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_priorbox (180)
-I0510 14:48:30.213276  5307 net.cpp:572] ctx_output4/relu_mbox_priorbox <- ctx_output4_ctx_output4/relu_0_split_2
-I0510 14:48:30.213292  5307 net.cpp:572] ctx_output4/relu_mbox_priorbox <- data_data_0_split_4
-I0510 14:48:30.213310  5307 net.cpp:542] ctx_output4/relu_mbox_priorbox -> ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.213349  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.213374  5307 net.cpp:267] TRAIN Top shape for layer 180 'ctx_output4/relu_mbox_priorbox' 1 2 240 (480)
-I0510 14:48:30.213392  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.213407  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.213428  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc (181)
-I0510 14:48:30.213444  5307 net.cpp:572] ctx_output5/relu_mbox_loc <- ctx_output5_ctx_output5/relu_0_split_0
-I0510 14:48:30.213460  5307 net.cpp:542] ctx_output5/relu_mbox_loc -> ctx_output5/relu_mbox_loc
-I0510 14:48:30.213901  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc
-I0510 14:48:30.213910  5307 net.cpp:267] TRAIN Top shape for layer 181 'ctx_output5/relu_mbox_loc' 16 16 3 5 (3840)
-I0510 14:48:30.213917  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.213928  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.213940  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_perm (182)
-I0510 14:48:30.213950  5307 net.cpp:572] ctx_output5/relu_mbox_loc_perm <- ctx_output5/relu_mbox_loc
-I0510 14:48:30.213961  5307 net.cpp:542] ctx_output5/relu_mbox_loc_perm -> ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.214069  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.214084  5307 net.cpp:267] TRAIN Top shape for layer 182 'ctx_output5/relu_mbox_loc_perm' 16 3 5 16 (3840)
-I0510 14:48:30.214095  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.214105  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.214118  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_flat (183)
-I0510 14:48:30.214126  5307 net.cpp:572] ctx_output5/relu_mbox_loc_flat <- ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.214136  5307 net.cpp:542] ctx_output5/relu_mbox_loc_flat -> ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.214196  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.214210  5307 net.cpp:267] TRAIN Top shape for layer 183 'ctx_output5/relu_mbox_loc_flat' 16 240 (3840)
-I0510 14:48:30.214221  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.214232  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.214246  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf (184)
-I0510 14:48:30.214256  5307 net.cpp:572] ctx_output5/relu_mbox_conf <- ctx_output5_ctx_output5/relu_0_split_1
-I0510 14:48:30.214267  5307 net.cpp:542] ctx_output5/relu_mbox_conf -> ctx_output5/relu_mbox_conf
-I0510 14:48:30.215553  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf
-I0510 14:48:30.215562  5307 net.cpp:267] TRAIN Top shape for layer 184 'ctx_output5/relu_mbox_conf' 16 84 3 5 (20160)
-I0510 14:48:30.215569  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.215580  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.215595  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_perm (185)
-I0510 14:48:30.215605  5307 net.cpp:572] ctx_output5/relu_mbox_conf_perm <- ctx_output5/relu_mbox_conf
-I0510 14:48:30.215615  5307 net.cpp:542] ctx_output5/relu_mbox_conf_perm -> ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.215721  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.215736  5307 net.cpp:267] TRAIN Top shape for layer 185 'ctx_output5/relu_mbox_conf_perm' 16 3 5 84 (20160)
-I0510 14:48:30.215747  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.215757  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.215773  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_flat (186)
-I0510 14:48:30.215790  5307 net.cpp:572] ctx_output5/relu_mbox_conf_flat <- ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.215801  5307 net.cpp:542] ctx_output5/relu_mbox_conf_flat -> ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.215883  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.215898  5307 net.cpp:267] TRAIN Top shape for layer 186 'ctx_output5/relu_mbox_conf_flat' 16 1260 (20160)
-I0510 14:48:30.215907  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.215919  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.215931  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_priorbox (187)
-I0510 14:48:30.215942  5307 net.cpp:572] ctx_output5/relu_mbox_priorbox <- ctx_output5_ctx_output5/relu_0_split_2
-I0510 14:48:30.215953  5307 net.cpp:572] ctx_output5/relu_mbox_priorbox <- data_data_0_split_5
-I0510 14:48:30.215963  5307 net.cpp:542] ctx_output5/relu_mbox_priorbox -> ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.215996  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.216009  5307 net.cpp:267] TRAIN Top shape for layer 187 'ctx_output5/relu_mbox_priorbox' 1 2 240 (480)
-I0510 14:48:30.216018  5307 layer_factory.hpp:172] Creating layer 'mbox_loc' of type 'Concat'
-I0510 14:48:30.216028  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216044  5307 net.cpp:200] Created Layer mbox_loc (188)
-I0510 14:48:30.216055  5307 net.cpp:572] mbox_loc <- ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.216065  5307 net.cpp:572] mbox_loc <- ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.216076  5307 net.cpp:572] mbox_loc <- ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.216087  5307 net.cpp:572] mbox_loc <- ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.216099  5307 net.cpp:572] mbox_loc <- ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.216110  5307 net.cpp:542] mbox_loc -> mbox_loc
-I0510 14:48:30.216143  5307 net.cpp:260] Setting up mbox_loc
-I0510 14:48:30.216156  5307 net.cpp:267] TRAIN Top shape for layer 188 'mbox_loc' 16 12824 (205184)
-I0510 14:48:30.216167  5307 layer_factory.hpp:172] Creating layer 'mbox_conf' of type 'Concat'
-I0510 14:48:30.216177  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216187  5307 net.cpp:200] Created Layer mbox_conf (189)
-I0510 14:48:30.216197  5307 net.cpp:572] mbox_conf <- ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.216207  5307 net.cpp:572] mbox_conf <- ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.216219  5307 net.cpp:572] mbox_conf <- ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.216231  5307 net.cpp:572] mbox_conf <- ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.216241  5307 net.cpp:572] mbox_conf <- ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.216253  5307 net.cpp:542] mbox_conf -> mbox_conf
-I0510 14:48:30.216284  5307 net.cpp:260] Setting up mbox_conf
-I0510 14:48:30.216296  5307 net.cpp:267] TRAIN Top shape for layer 189 'mbox_conf' 16 67326 (1077216)
-I0510 14:48:30.216306  5307 layer_factory.hpp:172] Creating layer 'mbox_priorbox' of type 'Concat'
-I0510 14:48:30.216317  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216329  5307 net.cpp:200] Created Layer mbox_priorbox (190)
-I0510 14:48:30.216339  5307 net.cpp:572] mbox_priorbox <- ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.216351  5307 net.cpp:572] mbox_priorbox <- ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.216361  5307 net.cpp:572] mbox_priorbox <- ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.216372  5307 net.cpp:572] mbox_priorbox <- ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.216383  5307 net.cpp:572] mbox_priorbox <- ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.216393  5307 net.cpp:542] mbox_priorbox -> mbox_priorbox
-I0510 14:48:30.216425  5307 net.cpp:260] Setting up mbox_priorbox
-I0510 14:48:30.216442  5307 net.cpp:267] TRAIN Top shape for layer 190 'mbox_priorbox' 1 2 12824 (25648)
-I0510 14:48:30.216459  5307 layer_factory.hpp:172] Creating layer 'mbox_loss' of type 'MultiBoxLoss'
-I0510 14:48:30.216470  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216485  5307 net.cpp:200] Created Layer mbox_loss (191)
-I0510 14:48:30.216495  5307 net.cpp:572] mbox_loss <- mbox_loc
-I0510 14:48:30.216506  5307 net.cpp:572] mbox_loss <- mbox_conf
-I0510 14:48:30.216517  5307 net.cpp:572] mbox_loss <- mbox_priorbox
-I0510 14:48:30.216532  5307 net.cpp:572] mbox_loss <- label
-I0510 14:48:30.216547  5307 net.cpp:542] mbox_loss -> mbox_loss
-I0510 14:48:30.216626  5307 layer_factory.hpp:172] Creating layer 'mbox_loss_smooth_L1_loc' of type 'SmoothL1Loss'
-I0510 14:48:30.216639  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216751  5307 layer_factory.hpp:172] Creating layer 'mbox_loss_softmax_conf' of type 'SoftmaxWithLoss'
-I0510 14:48:30.216764  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216893  5307 net.cpp:260] Setting up mbox_loss
-I0510 14:48:30.216907  5307 net.cpp:267] TRAIN Top shape for layer 191 'mbox_loss' (1)
-I0510 14:48:30.216917  5307 net.cpp:271]     with loss weight 1
-I0510 14:48:30.216939  5307 net.cpp:336] mbox_loss needs backward computation.
-I0510 14:48:30.216951  5307 net.cpp:338] mbox_priorbox does not need backward computation.
-I0510 14:48:30.216964  5307 net.cpp:336] mbox_conf needs backward computation.
-I0510 14:48:30.216974  5307 net.cpp:336] mbox_loc needs backward computation.
-I0510 14:48:30.216984  5307 net.cpp:338] ctx_output5/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.216995  5307 net.cpp:336] ctx_output5/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217005  5307 net.cpp:336] ctx_output5/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217015  5307 net.cpp:336] ctx_output5/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217025  5307 net.cpp:336] ctx_output5/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217036  5307 net.cpp:336] ctx_output5/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217046  5307 net.cpp:336] ctx_output5/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217056  5307 net.cpp:338] ctx_output4/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.217067  5307 net.cpp:336] ctx_output4/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217077  5307 net.cpp:336] ctx_output4/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217087  5307 net.cpp:336] ctx_output4/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217098  5307 net.cpp:336] ctx_output4/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217108  5307 net.cpp:336] ctx_output4/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217118  5307 net.cpp:336] ctx_output4/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217128  5307 net.cpp:338] ctx_output3/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.217139  5307 net.cpp:336] ctx_output3/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217149  5307 net.cpp:336] ctx_output3/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217159  5307 net.cpp:336] ctx_output3/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217169  5307 net.cpp:336] ctx_output3/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217177  5307 net.cpp:336] ctx_output3/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217185  5307 net.cpp:336] ctx_output3/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217195  5307 net.cpp:338] ctx_output2/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.217206  5307 net.cpp:336] ctx_output2/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217214  5307 net.cpp:336] ctx_output2/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217227  5307 net.cpp:336] ctx_output2/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217242  5307 net.cpp:336] ctx_output2/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217250  5307 net.cpp:336] ctx_output2/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217259  5307 net.cpp:336] ctx_output2/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217268  5307 net.cpp:338] ctx_output1/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.217278  5307 net.cpp:336] ctx_output1/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217288  5307 net.cpp:336] ctx_output1/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217296  5307 net.cpp:336] ctx_output1/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217305  5307 net.cpp:336] ctx_output1/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217314  5307 net.cpp:336] ctx_output1/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217322  5307 net.cpp:336] ctx_output1/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217331  5307 net.cpp:336] ctx_output5_ctx_output5/relu_0_split needs backward computation.
-I0510 14:48:30.217340  5307 net.cpp:336] ctx_output5/relu needs backward computation.
-I0510 14:48:30.217350  5307 net.cpp:336] ctx_output5/bn needs backward computation.
-I0510 14:48:30.217358  5307 net.cpp:336] ctx_output5 needs backward computation.
-I0510 14:48:30.217367  5307 net.cpp:336] ctx_output5/1x1/relu needs backward computation.
-I0510 14:48:30.217376  5307 net.cpp:336] ctx_output5/1x1/bn needs backward computation.
-I0510 14:48:30.217386  5307 net.cpp:336] ctx_output5/1x1 needs backward computation.
-I0510 14:48:30.217394  5307 net.cpp:336] ctx_output4_ctx_output4/relu_0_split needs backward computation.
-I0510 14:48:30.217403  5307 net.cpp:336] ctx_output4/relu needs backward computation.
-I0510 14:48:30.217412  5307 net.cpp:336] ctx_output4/bn needs backward computation.
-I0510 14:48:30.217422  5307 net.cpp:336] ctx_output4 needs backward computation.
-I0510 14:48:30.217429  5307 net.cpp:336] ctx_output4/1x1/relu needs backward computation.
-I0510 14:48:30.217438  5307 net.cpp:336] ctx_output4/1x1/bn needs backward computation.
-I0510 14:48:30.217447  5307 net.cpp:336] ctx_output4/1x1 needs backward computation.
-I0510 14:48:30.217455  5307 net.cpp:336] ctx_output3_ctx_output3/relu_0_split needs backward computation.
-I0510 14:48:30.217463  5307 net.cpp:336] ctx_output3/relu needs backward computation.
-I0510 14:48:30.217473  5307 net.cpp:336] ctx_output3/bn needs backward computation.
-I0510 14:48:30.217480  5307 net.cpp:336] ctx_output3 needs backward computation.
-I0510 14:48:30.217489  5307 net.cpp:336] ctx_output3/1x1/relu needs backward computation.
-I0510 14:48:30.217496  5307 net.cpp:336] ctx_output3/1x1/bn needs backward computation.
-I0510 14:48:30.217505  5307 net.cpp:336] ctx_output3/1x1 needs backward computation.
-I0510 14:48:30.217514  5307 net.cpp:336] ctx_output2_ctx_output2/relu_0_split needs backward computation.
-I0510 14:48:30.217522  5307 net.cpp:336] ctx_output2/relu needs backward computation.
-I0510 14:48:30.217530  5307 net.cpp:336] ctx_output2/bn needs backward computation.
-I0510 14:48:30.217538  5307 net.cpp:336] ctx_output2 needs backward computation.
-I0510 14:48:30.217546  5307 net.cpp:336] ctx_output2/1x1/relu needs backward computation.
-I0510 14:48:30.217555  5307 net.cpp:336] ctx_output2/1x1/bn needs backward computation.
-I0510 14:48:30.217563  5307 net.cpp:336] ctx_output2/1x1 needs backward computation.
-I0510 14:48:30.217571  5307 net.cpp:336] ctx_output1_ctx_output1/relu_0_split needs backward computation.
-I0510 14:48:30.217581  5307 net.cpp:336] ctx_output1/relu needs backward computation.
-I0510 14:48:30.217588  5307 net.cpp:336] ctx_output1/bn needs backward computation.
-I0510 14:48:30.217597  5307 net.cpp:336] ctx_output1 needs backward computation.
-I0510 14:48:30.217605  5307 net.cpp:336] ctx_output1/1x1/relu needs backward computation.
-I0510 14:48:30.217617  5307 net.cpp:336] ctx_output1/1x1/bn needs backward computation.
-I0510 14:48:30.217628  5307 net.cpp:336] ctx_output1/1x1 needs backward computation.
-I0510 14:48:30.217638  5307 net.cpp:336] pool8 needs backward computation.
-I0510 14:48:30.217646  5307 net.cpp:336] pool7_pool7_0_split needs backward computation.
-I0510 14:48:30.217654  5307 net.cpp:336] pool7 needs backward computation.
-I0510 14:48:30.217664  5307 net.cpp:336] pool6_pool6_0_split needs backward computation.
-I0510 14:48:30.217671  5307 net.cpp:336] pool6 needs backward computation.
-I0510 14:48:30.217679  5307 net.cpp:336] conv6/sep_relu6/sep_0_split needs backward computation.
-I0510 14:48:30.217689  5307 net.cpp:336] relu6/sep needs backward computation.
-I0510 14:48:30.217697  5307 net.cpp:336] conv6/sep/scale needs backward computation.
-I0510 14:48:30.217705  5307 net.cpp:336] conv6/sep/bn needs backward computation.
-I0510 14:48:30.217713  5307 net.cpp:336] conv6/sep needs backward computation.
-I0510 14:48:30.217721  5307 net.cpp:336] relu6/dw needs backward computation.
-I0510 14:48:30.217730  5307 net.cpp:336] conv6/dw/scale needs backward computation.
-I0510 14:48:30.217738  5307 net.cpp:336] conv6/dw/bn needs backward computation.
-I0510 14:48:30.217747  5307 net.cpp:336] conv6/dw needs backward computation.
-I0510 14:48:30.217756  5307 net.cpp:336] relu5_6/sep needs backward computation.
-I0510 14:48:30.217766  5307 net.cpp:336] conv5_6/sep/scale needs backward computation.
-I0510 14:48:30.217774  5307 net.cpp:336] conv5_6/sep/bn needs backward computation.
-I0510 14:48:30.217782  5307 net.cpp:336] conv5_6/sep needs backward computation.
-I0510 14:48:30.217792  5307 net.cpp:336] relu5_6/dw needs backward computation.
-I0510 14:48:30.217800  5307 net.cpp:336] conv5_6/dw/scale needs backward computation.
-I0510 14:48:30.217808  5307 net.cpp:336] conv5_6/dw/bn needs backward computation.
-I0510 14:48:30.217816  5307 net.cpp:336] conv5_6/dw needs backward computation.
-I0510 14:48:30.217825  5307 net.cpp:336] conv5_5/sep_relu5_5/sep_0_split needs backward computation.
-I0510 14:48:30.217834  5307 net.cpp:336] relu5_5/sep needs backward computation.
-I0510 14:48:30.217842  5307 net.cpp:336] conv5_5/sep/scale needs backward computation.
-I0510 14:48:30.217850  5307 net.cpp:336] conv5_5/sep/bn needs backward computation.
-I0510 14:48:30.217859  5307 net.cpp:336] conv5_5/sep needs backward computation.
-I0510 14:48:30.217866  5307 net.cpp:336] relu5_5/dw needs backward computation.
-I0510 14:48:30.217875  5307 net.cpp:336] conv5_5/dw/scale needs backward computation.
-I0510 14:48:30.217883  5307 net.cpp:336] conv5_5/dw/bn needs backward computation.
-I0510 14:48:30.217891  5307 net.cpp:336] conv5_5/dw needs backward computation.
-I0510 14:48:30.217900  5307 net.cpp:336] relu5_4/sep needs backward computation.
-I0510 14:48:30.217908  5307 net.cpp:336] conv5_4/sep/scale needs backward computation.
-I0510 14:48:30.217916  5307 net.cpp:336] conv5_4/sep/bn needs backward computation.
-I0510 14:48:30.217924  5307 net.cpp:336] conv5_4/sep needs backward computation.
-I0510 14:48:30.217932  5307 net.cpp:336] relu5_4/dw needs backward computation.
-I0510 14:48:30.217941  5307 net.cpp:336] conv5_4/dw/scale needs backward computation.
-I0510 14:48:30.217949  5307 net.cpp:336] conv5_4/dw/bn needs backward computation.
-I0510 14:48:30.217959  5307 net.cpp:336] conv5_4/dw needs backward computation.
-I0510 14:48:30.217969  5307 net.cpp:336] relu5_3/sep needs backward computation.
-I0510 14:48:30.217978  5307 net.cpp:336] conv5_3/sep/scale needs backward computation.
-I0510 14:48:30.217988  5307 net.cpp:336] conv5_3/sep/bn needs backward computation.
-I0510 14:48:30.217998  5307 net.cpp:336] conv5_3/sep needs backward computation.
-I0510 14:48:30.218006  5307 net.cpp:336] relu5_3/dw needs backward computation.
-I0510 14:48:30.218016  5307 net.cpp:336] conv5_3/dw/scale needs backward computation.
-I0510 14:48:30.218026  5307 net.cpp:336] conv5_3/dw/bn needs backward computation.
-I0510 14:48:30.218035  5307 net.cpp:336] conv5_3/dw needs backward computation.
-I0510 14:48:30.218045  5307 net.cpp:336] relu5_2/sep needs backward computation.
-I0510 14:48:30.218058  5307 net.cpp:336] conv5_2/sep/scale needs backward computation.
-I0510 14:48:30.218072  5307 net.cpp:336] conv5_2/sep/bn needs backward computation.
-I0510 14:48:30.218082  5307 net.cpp:336] conv5_2/sep needs backward computation.
-I0510 14:48:30.218091  5307 net.cpp:336] relu5_2/dw needs backward computation.
-I0510 14:48:30.218101  5307 net.cpp:336] conv5_2/dw/scale needs backward computation.
-I0510 14:48:30.218111  5307 net.cpp:336] conv5_2/dw/bn needs backward computation.
-I0510 14:48:30.218120  5307 net.cpp:336] conv5_2/dw needs backward computation.
-I0510 14:48:30.218130  5307 net.cpp:336] relu5_1/sep needs backward computation.
-I0510 14:48:30.218140  5307 net.cpp:336] conv5_1/sep/scale needs backward computation.
-I0510 14:48:30.218150  5307 net.cpp:336] conv5_1/sep/bn needs backward computation.
-I0510 14:48:30.218160  5307 net.cpp:336] conv5_1/sep needs backward computation.
-I0510 14:48:30.218169  5307 net.cpp:336] relu5_1/dw needs backward computation.
-I0510 14:48:30.218179  5307 net.cpp:336] conv5_1/dw/scale needs backward computation.
-I0510 14:48:30.218189  5307 net.cpp:336] conv5_1/dw/bn needs backward computation.
-I0510 14:48:30.218199  5307 net.cpp:336] conv5_1/dw needs backward computation.
-I0510 14:48:30.218209  5307 net.cpp:336] relu4_2/sep needs backward computation.
-I0510 14:48:30.218219  5307 net.cpp:336] conv4_2/sep/scale needs backward computation.
-I0510 14:48:30.218227  5307 net.cpp:336] conv4_2/sep/bn needs backward computation.
-I0510 14:48:30.218237  5307 net.cpp:336] conv4_2/sep needs backward computation.
-I0510 14:48:30.218247  5307 net.cpp:336] relu4_2/dw needs backward computation.
-I0510 14:48:30.218256  5307 net.cpp:336] conv4_2/dw/scale needs backward computation.
-I0510 14:48:30.218266  5307 net.cpp:336] conv4_2/dw/bn needs backward computation.
-I0510 14:48:30.218276  5307 net.cpp:336] conv4_2/dw needs backward computation.
-I0510 14:48:30.218286  5307 net.cpp:336] relu4_1/sep needs backward computation.
-I0510 14:48:30.218295  5307 net.cpp:336] conv4_1/sep/scale needs backward computation.
-I0510 14:48:30.218305  5307 net.cpp:336] conv4_1/sep/bn needs backward computation.
-I0510 14:48:30.218314  5307 net.cpp:336] conv4_1/sep needs backward computation.
-I0510 14:48:30.218324  5307 net.cpp:336] relu4_1/dw needs backward computation.
-I0510 14:48:30.218334  5307 net.cpp:336] conv4_1/dw/scale needs backward computation.
-I0510 14:48:30.218343  5307 net.cpp:336] conv4_1/dw/bn needs backward computation.
-I0510 14:48:30.218353  5307 net.cpp:336] conv4_1/dw needs backward computation.
-I0510 14:48:30.218364  5307 net.cpp:336] relu3_2/sep needs backward computation.
-I0510 14:48:30.218372  5307 net.cpp:336] conv3_2/sep/scale needs backward computation.
-I0510 14:48:30.218382  5307 net.cpp:336] conv3_2/sep/bn needs backward computation.
-I0510 14:48:30.218392  5307 net.cpp:336] conv3_2/sep needs backward computation.
-I0510 14:48:30.218402  5307 net.cpp:336] relu3_2/dw needs backward computation.
-I0510 14:48:30.218411  5307 net.cpp:336] conv3_2/dw/scale needs backward computation.
-I0510 14:48:30.218421  5307 net.cpp:336] conv3_2/dw/bn needs backward computation.
-I0510 14:48:30.218430  5307 net.cpp:336] conv3_2/dw needs backward computation.
-I0510 14:48:30.218441  5307 net.cpp:336] relu3_1/sep needs backward computation.
-I0510 14:48:30.218451  5307 net.cpp:336] conv3_1/sep/scale needs backward computation.
-I0510 14:48:30.218459  5307 net.cpp:336] conv3_1/sep/bn needs backward computation.
-I0510 14:48:30.218469  5307 net.cpp:336] conv3_1/sep needs backward computation.
-I0510 14:48:30.218479  5307 net.cpp:336] relu3_1/dw needs backward computation.
-I0510 14:48:30.218488  5307 net.cpp:336] conv3_1/dw/scale needs backward computation.
-I0510 14:48:30.218497  5307 net.cpp:336] conv3_1/dw/bn needs backward computation.
-I0510 14:48:30.218508  5307 net.cpp:336] conv3_1/dw needs backward computation.
-I0510 14:48:30.218518  5307 net.cpp:336] relu2_2/sep needs backward computation.
-I0510 14:48:30.218528  5307 net.cpp:336] conv2_2/sep/scale needs backward computation.
-I0510 14:48:30.218539  5307 net.cpp:336] conv2_2/sep/bn needs backward computation.
-I0510 14:48:30.218554  5307 net.cpp:336] conv2_2/sep needs backward computation.
-I0510 14:48:30.218562  5307 net.cpp:336] relu2_2/dw needs backward computation.
-I0510 14:48:30.218571  5307 net.cpp:336] conv2_2/dw/scale needs backward computation.
-I0510 14:48:30.218580  5307 net.cpp:336] conv2_2/dw/bn needs backward computation.
-I0510 14:48:30.218586  5307 net.cpp:336] conv2_2/dw needs backward computation.
-I0510 14:48:30.218595  5307 net.cpp:336] relu2_1/sep needs backward computation.
-I0510 14:48:30.218602  5307 net.cpp:336] conv2_1/sep/scale needs backward computation.
-I0510 14:48:30.218611  5307 net.cpp:336] conv2_1/sep/bn needs backward computation.
-I0510 14:48:30.218618  5307 net.cpp:336] conv2_1/sep needs backward computation.
-I0510 14:48:30.218626  5307 net.cpp:336] relu2_1/dw needs backward computation.
-I0510 14:48:30.218634  5307 net.cpp:336] conv2_1/dw/scale needs backward computation.
-I0510 14:48:30.218642  5307 net.cpp:336] conv2_1/dw/bn needs backward computation.
-I0510 14:48:30.218650  5307 net.cpp:336] conv2_1/dw needs backward computation.
-I0510 14:48:30.218658  5307 net.cpp:336] relu1 needs backward computation.
-I0510 14:48:30.218667  5307 net.cpp:336] conv1/scale needs backward computation.
-I0510 14:48:30.218673  5307 net.cpp:336] conv1/bn needs backward computation.
-I0510 14:48:30.218681  5307 net.cpp:336] conv1 needs backward computation.
-I0510 14:48:30.218691  5307 net.cpp:338] data/bias does not need backward computation.
-I0510 14:48:30.218700  5307 net.cpp:338] data_data_0_split does not need backward computation.
-I0510 14:48:30.218709  5307 net.cpp:338] data does not need backward computation.
-I0510 14:48:30.218717  5307 net.cpp:380] This network produces output mbox_loss
-I0510 14:48:30.218881  5307 net.cpp:403] Top memory (TRAIN) required for data: 2150578120 diff: 2150578120
-I0510 14:48:30.218894  5307 net.cpp:406] Bottom memory (TRAIN) required for data: 2150578112 diff: 2150578112
-I0510 14:48:30.218901  5307 net.cpp:409] Shared (in-place) memory (TRAIN) by data: 1358299136 diff: 1358299136
-I0510 14:48:30.218910  5307 net.cpp:412] Parameters memory (TRAIN) required for data: 9462808 diff: 9462808
-I0510 14:48:30.218919  5307 net.cpp:415] Parameters shared memory (TRAIN) by data: 0 diff: 0
-I0510 14:48:30.218926  5307 net.cpp:421] Network initialization done.
-I0510 14:48:30.221627  5307 solver.cpp:175] Creating test net (#0) specified by test_net file: training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/test.prototxt
-I0510 14:48:30.222658  5307 net.cpp:80] Initializing net from parameters: 
-name: "mobiledetnet-0.5_test"
-state {
-  phase: TEST
-}
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 8
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_1/sep/scale"
-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/dw/scale"
-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/relu"
-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
-  name: "ctx_output3/1x1"
-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
-  name: "ctx_output3"
-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/relu"
-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19
-    max_size: 88
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/rel
-I0510 14:48:30.223242  5307 net.cpp:110] Using FLOAT as default forward math type
-I0510 14:48:30.223258  5307 net.cpp:116] Using FLOAT as default backward math type
-I0510 14:48:30.223271  5307 layer_factory.hpp:172] Creating layer 'data' of type 'AnnotatedData'
-I0510 14:48:30.223291  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.223315  5307 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0510 14:48:30.224280  5307 net.cpp:200] Created Layer data (0)
-I0510 14:48:30.224289  5307 net.cpp:542] data -> data
-I0510 14:48:30.224298  5307 net.cpp:542] data -> label
-I0510 14:48:30.224310  5307 data_reader.cpp:58] Data Reader threads: 1, out queues: 1, depth: 8
-I0510 14:48:30.224318  5307 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0510 14:48:30.225162  5353 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb
-I0510 14:48:30.226320  5307 annotated_data_layer.cpp:105] output data size: 8,3,256,512
-I0510 14:48:30.226392  5307 annotated_data_layer.cpp:150] (0) Output data size: 8, 3, 256, 512
-I0510 14:48:30.226428  5307 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0510 14:48:30.226449  5307 net.cpp:260] Setting up data
-I0510 14:48:30.226456  5307 net.cpp:267] TEST Top shape for layer 0 'data' 8 3 256 512 (3145728)
-I0510 14:48:30.227767  5354 data_layer.cpp:105] (0) Parser threads: 1
-I0510 14:48:30.227777  5354 data_layer.cpp:107] (0) Transformer threads: 1
-I0510 14:48:30.227795  5307 net.cpp:267] TEST Top shape for layer 0 'data' 1 1 2 8 (16)
-I0510 14:48:30.227813  5307 layer_factory.hpp:172] Creating layer 'data_data_0_split' of type 'Split'
-I0510 14:48:30.227828  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.227845  5307 net.cpp:200] Created Layer data_data_0_split (1)
-I0510 14:48:30.227859  5307 net.cpp:572] data_data_0_split <- data
-I0510 14:48:30.227874  5307 net.cpp:542] data_data_0_split -> data_data_0_split_0
-I0510 14:48:30.227890  5307 net.cpp:542] data_data_0_split -> data_data_0_split_1
-I0510 14:48:30.227902  5307 net.cpp:542] data_data_0_split -> data_data_0_split_2
-I0510 14:48:30.227917  5307 net.cpp:542] data_data_0_split -> data_data_0_split_3
-I0510 14:48:30.227931  5307 net.cpp:542] data_data_0_split -> data_data_0_split_4
-I0510 14:48:30.227943  5307 net.cpp:542] data_data_0_split -> data_data_0_split_5
-I0510 14:48:30.228044  5307 net.cpp:260] Setting up data_data_0_split
-I0510 14:48:30.228060  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228075  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228087  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228101  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228114  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228127  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228140  5307 layer_factory.hpp:172] Creating layer 'data/bias' of type 'Bias'
-I0510 14:48:30.228154  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.228170  5307 net.cpp:200] Created Layer data/bias (2)
-I0510 14:48:30.228183  5307 net.cpp:572] data/bias <- data_data_0_split_0
-I0510 14:48:30.228196  5307 net.cpp:542] data/bias -> data/bias
-I0510 14:48:30.228427  5307 net.cpp:260] Setting up data/bias
-I0510 14:48:30.228446  5307 net.cpp:267] TEST Top shape for layer 2 'data/bias' 8 3 256 512 (3145728)
-I0510 14:48:30.228464  5307 layer_factory.hpp:172] Creating layer 'conv1' of type 'Convolution'
-I0510 14:48:30.228478  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.228498  5307 net.cpp:200] Created Layer conv1 (3)
-I0510 14:48:30.228513  5307 net.cpp:572] conv1 <- data/bias
-I0510 14:48:30.228540  5307 net.cpp:542] conv1 -> conv1
-I0510 14:48:30.228772  5307 net.cpp:260] Setting up conv1
-I0510 14:48:30.228781  5307 net.cpp:267] TEST Top shape for layer 3 'conv1' 8 16 128 256 (4194304)
-I0510 14:48:30.228788  5307 layer_factory.hpp:172] Creating layer 'conv1/bn' of type 'BatchNorm'
-I0510 14:48:30.228801  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.228811  5307 net.cpp:200] Created Layer conv1/bn (4)
-I0510 14:48:30.228814  5307 net.cpp:572] conv1/bn <- conv1
-I0510 14:48:30.228818  5307 net.cpp:527] conv1/bn -> conv1 (in-place)
-I0510 14:48:30.242122  5307 net.cpp:260] Setting up conv1/bn
-I0510 14:48:30.242146  5307 net.cpp:267] TEST Top shape for layer 4 'conv1/bn' 8 16 128 256 (4194304)
-I0510 14:48:30.242161  5307 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Scale'
-I0510 14:48:30.242178  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242193  5307 net.cpp:200] Created Layer conv1/scale (5)
-I0510 14:48:30.242205  5307 net.cpp:572] conv1/scale <- conv1
-I0510 14:48:30.242216  5307 net.cpp:527] conv1/scale -> conv1 (in-place)
-I0510 14:48:30.242266  5307 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Bias'
-I0510 14:48:30.242278  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242435  5307 net.cpp:260] Setting up conv1/scale
-I0510 14:48:30.242456  5307 net.cpp:267] TEST Top shape for layer 5 'conv1/scale' 8 16 128 256 (4194304)
-I0510 14:48:30.242472  5307 layer_factory.hpp:172] Creating layer 'relu1' of type 'ReLU'
-I0510 14:48:30.242486  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242501  5307 net.cpp:200] Created Layer relu1 (6)
-I0510 14:48:30.242513  5307 net.cpp:572] relu1 <- conv1
-I0510 14:48:30.242527  5307 net.cpp:527] relu1 -> conv1 (in-place)
-I0510 14:48:30.242547  5307 net.cpp:260] Setting up relu1
-I0510 14:48:30.242563  5307 net.cpp:267] TEST Top shape for layer 6 'relu1' 8 16 128 256 (4194304)
-I0510 14:48:30.242575  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw' of type 'Convolution'
-I0510 14:48:30.242588  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242612  5307 net.cpp:200] Created Layer conv2_1/dw (7)
-I0510 14:48:30.242625  5307 net.cpp:572] conv2_1/dw <- conv1
-I0510 14:48:30.242638  5307 net.cpp:542] conv2_1/dw -> conv2_1/dw
-I0510 14:48:30.242871  5307 net.cpp:260] Setting up conv2_1/dw
-I0510 14:48:30.242893  5307 net.cpp:267] TEST Top shape for layer 7 'conv2_1/dw' 8 16 128 256 (4194304)
-I0510 14:48:30.242910  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.242925  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242943  5307 net.cpp:200] Created Layer conv2_1/dw/bn (8)
-I0510 14:48:30.242957  5307 net.cpp:572] conv2_1/dw/bn <- conv2_1/dw
-I0510 14:48:30.242971  5307 net.cpp:527] conv2_1/dw/bn -> conv2_1/dw (in-place)
-I0510 14:48:30.243391  5307 net.cpp:260] Setting up conv2_1/dw/bn
-I0510 14:48:30.243412  5307 net.cpp:267] TEST Top shape for layer 8 'conv2_1/dw/bn' 8 16 128 256 (4194304)
-I0510 14:48:30.243432  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Scale'
-I0510 14:48:30.243445  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.243461  5307 net.cpp:200] Created Layer conv2_1/dw/scale (9)
-I0510 14:48:30.243475  5307 net.cpp:572] conv2_1/dw/scale <- conv2_1/dw
-I0510 14:48:30.243489  5307 net.cpp:527] conv2_1/dw/scale -> conv2_1/dw (in-place)
-I0510 14:48:30.243537  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Bias'
-I0510 14:48:30.243553  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.243713  5307 net.cpp:260] Setting up conv2_1/dw/scale
-I0510 14:48:30.243731  5307 net.cpp:267] TEST Top shape for layer 9 'conv2_1/dw/scale' 8 16 128 256 (4194304)
-I0510 14:48:30.243748  5307 layer_factory.hpp:172] Creating layer 'relu2_1/dw' of type 'ReLU'
-I0510 14:48:30.243767  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.243791  5307 net.cpp:200] Created Layer relu2_1/dw (10)
-I0510 14:48:30.243805  5307 net.cpp:572] relu2_1/dw <- conv2_1/dw
-I0510 14:48:30.243819  5307 net.cpp:527] relu2_1/dw -> conv2_1/dw (in-place)
-I0510 14:48:30.243835  5307 net.cpp:260] Setting up relu2_1/dw
-I0510 14:48:30.243849  5307 net.cpp:267] TEST Top shape for layer 10 'relu2_1/dw' 8 16 128 256 (4194304)
-I0510 14:48:30.243863  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep' of type 'Convolution'
-I0510 14:48:30.243876  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.243896  5307 net.cpp:200] Created Layer conv2_1/sep (11)
-I0510 14:48:30.243911  5307 net.cpp:572] conv2_1/sep <- conv2_1/dw
-I0510 14:48:30.243927  5307 net.cpp:542] conv2_1/sep -> conv2_1/sep
-I0510 14:48:30.244163  5307 net.cpp:260] Setting up conv2_1/sep
-I0510 14:48:30.244171  5307 net.cpp:267] TEST Top shape for layer 11 'conv2_1/sep' 8 32 128 256 (8388608)
-I0510 14:48:30.244179  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.244184  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244190  5307 net.cpp:200] Created Layer conv2_1/sep/bn (12)
-I0510 14:48:30.244194  5307 net.cpp:572] conv2_1/sep/bn <- conv2_1/sep
-I0510 14:48:30.244199  5307 net.cpp:527] conv2_1/sep/bn -> conv2_1/sep (in-place)
-I0510 14:48:30.244614  5307 net.cpp:260] Setting up conv2_1/sep/bn
-I0510 14:48:30.244623  5307 net.cpp:267] TEST Top shape for layer 12 'conv2_1/sep/bn' 8 32 128 256 (8388608)
-I0510 14:48:30.244632  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Scale'
-I0510 14:48:30.244637  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244642  5307 net.cpp:200] Created Layer conv2_1/sep/scale (13)
-I0510 14:48:30.244647  5307 net.cpp:572] conv2_1/sep/scale <- conv2_1/sep
-I0510 14:48:30.244650  5307 net.cpp:527] conv2_1/sep/scale -> conv2_1/sep (in-place)
-I0510 14:48:30.244686  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Bias'
-I0510 14:48:30.244701  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244850  5307 net.cpp:260] Setting up conv2_1/sep/scale
-I0510 14:48:30.244863  5307 net.cpp:267] TEST Top shape for layer 13 'conv2_1/sep/scale' 8 32 128 256 (8388608)
-I0510 14:48:30.244875  5307 layer_factory.hpp:172] Creating layer 'relu2_1/sep' of type 'ReLU'
-I0510 14:48:30.244884  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244894  5307 net.cpp:200] Created Layer relu2_1/sep (14)
-I0510 14:48:30.244902  5307 net.cpp:572] relu2_1/sep <- conv2_1/sep
-I0510 14:48:30.244911  5307 net.cpp:527] relu2_1/sep -> conv2_1/sep (in-place)
-I0510 14:48:30.244922  5307 net.cpp:260] Setting up relu2_1/sep
-I0510 14:48:30.244932  5307 net.cpp:267] TEST Top shape for layer 14 'relu2_1/sep' 8 32 128 256 (8388608)
-I0510 14:48:30.244941  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw' of type 'Convolution'
-I0510 14:48:30.244951  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244962  5307 net.cpp:200] Created Layer conv2_2/dw (15)
-I0510 14:48:30.244971  5307 net.cpp:572] conv2_2/dw <- conv2_1/sep
-I0510 14:48:30.244979  5307 net.cpp:542] conv2_2/dw -> conv2_2/dw
-I0510 14:48:30.245188  5307 net.cpp:260] Setting up conv2_2/dw
-I0510 14:48:30.245209  5307 net.cpp:267] TEST Top shape for layer 15 'conv2_2/dw' 8 32 64 128 (2097152)
-I0510 14:48:30.245224  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.245237  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.245254  5307 net.cpp:200] Created Layer conv2_2/dw/bn (16)
-I0510 14:48:30.245270  5307 net.cpp:572] conv2_2/dw/bn <- conv2_2/dw
-I0510 14:48:30.245283  5307 net.cpp:527] conv2_2/dw/bn -> conv2_2/dw (in-place)
-I0510 14:48:30.245674  5307 net.cpp:260] Setting up conv2_2/dw/bn
-I0510 14:48:30.245693  5307 net.cpp:267] TEST Top shape for layer 16 'conv2_2/dw/bn' 8 32 64 128 (2097152)
-I0510 14:48:30.245710  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Scale'
-I0510 14:48:30.245724  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.245738  5307 net.cpp:200] Created Layer conv2_2/dw/scale (17)
-I0510 14:48:30.245751  5307 net.cpp:572] conv2_2/dw/scale <- conv2_2/dw
-I0510 14:48:30.245764  5307 net.cpp:527] conv2_2/dw/scale -> conv2_2/dw (in-place)
-I0510 14:48:30.245811  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Bias'
-I0510 14:48:30.245826  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.245949  5307 net.cpp:260] Setting up conv2_2/dw/scale
-I0510 14:48:30.245966  5307 net.cpp:267] TEST Top shape for layer 17 'conv2_2/dw/scale' 8 32 64 128 (2097152)
-I0510 14:48:30.245982  5307 layer_factory.hpp:172] Creating layer 'relu2_2/dw' of type 'ReLU'
-I0510 14:48:30.245995  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.246008  5307 net.cpp:200] Created Layer relu2_2/dw (18)
-I0510 14:48:30.246021  5307 net.cpp:572] relu2_2/dw <- conv2_2/dw
-I0510 14:48:30.246035  5307 net.cpp:527] relu2_2/dw -> conv2_2/dw (in-place)
-I0510 14:48:30.246049  5307 net.cpp:260] Setting up relu2_2/dw
-I0510 14:48:30.246063  5307 net.cpp:267] TEST Top shape for layer 18 'relu2_2/dw' 8 32 64 128 (2097152)
-I0510 14:48:30.246076  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep' of type 'Convolution'
-I0510 14:48:30.246093  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.246112  5307 net.cpp:200] Created Layer conv2_2/sep (19)
-I0510 14:48:30.246125  5307 net.cpp:572] conv2_2/sep <- conv2_2/dw
-I0510 14:48:30.246139  5307 net.cpp:542] conv2_2/sep -> conv2_2/sep
-I0510 14:48:30.246407  5307 net.cpp:260] Setting up conv2_2/sep
-I0510 14:48:30.246417  5307 net.cpp:267] TEST Top shape for layer 19 'conv2_2/sep' 8 64 64 128 (4194304)
-I0510 14:48:30.246421  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.246425  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.246431  5307 net.cpp:200] Created Layer conv2_2/sep/bn (20)
-I0510 14:48:30.246435  5307 net.cpp:572] conv2_2/sep/bn <- conv2_2/sep
-I0510 14:48:30.246439  5307 net.cpp:527] conv2_2/sep/bn -> conv2_2/sep (in-place)
-I0510 14:48:30.246834  5307 net.cpp:260] Setting up conv2_2/sep/bn
-I0510 14:48:30.246841  5307 net.cpp:267] TEST Top shape for layer 20 'conv2_2/sep/bn' 8 64 64 128 (4194304)
-I0510 14:48:30.246850  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Scale'
-I0510 14:48:30.246853  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.246860  5307 net.cpp:200] Created Layer conv2_2/sep/scale (21)
-I0510 14:48:30.246862  5307 net.cpp:572] conv2_2/sep/scale <- conv2_2/sep
-I0510 14:48:30.246866  5307 net.cpp:527] conv2_2/sep/scale -> conv2_2/sep (in-place)
-I0510 14:48:30.246904  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Bias'
-I0510 14:48:30.246909  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247018  5307 net.cpp:260] Setting up conv2_2/sep/scale
-I0510 14:48:30.247025  5307 net.cpp:267] TEST Top shape for layer 21 'conv2_2/sep/scale' 8 64 64 128 (4194304)
-I0510 14:48:30.247032  5307 layer_factory.hpp:172] Creating layer 'relu2_2/sep' of type 'ReLU'
-I0510 14:48:30.247036  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247041  5307 net.cpp:200] Created Layer relu2_2/sep (22)
-I0510 14:48:30.247045  5307 net.cpp:572] relu2_2/sep <- conv2_2/sep
-I0510 14:48:30.247058  5307 net.cpp:527] relu2_2/sep -> conv2_2/sep (in-place)
-I0510 14:48:30.247064  5307 net.cpp:260] Setting up relu2_2/sep
-I0510 14:48:30.247068  5307 net.cpp:267] TEST Top shape for layer 22 'relu2_2/sep' 8 64 64 128 (4194304)
-I0510 14:48:30.247072  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw' of type 'Convolution'
-I0510 14:48:30.247076  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247084  5307 net.cpp:200] Created Layer conv3_1/dw (23)
-I0510 14:48:30.247088  5307 net.cpp:572] conv3_1/dw <- conv2_2/sep
-I0510 14:48:30.247092  5307 net.cpp:542] conv3_1/dw -> conv3_1/dw
-I0510 14:48:30.247303  5307 net.cpp:260] Setting up conv3_1/dw
-I0510 14:48:30.247310  5307 net.cpp:267] TEST Top shape for layer 23 'conv3_1/dw' 8 64 64 128 (4194304)
-I0510 14:48:30.247316  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.247321  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247328  5307 net.cpp:200] Created Layer conv3_1/dw/bn (24)
-I0510 14:48:30.247333  5307 net.cpp:572] conv3_1/dw/bn <- conv3_1/dw
-I0510 14:48:30.247337  5307 net.cpp:527] conv3_1/dw/bn -> conv3_1/dw (in-place)
-I0510 14:48:30.247715  5307 net.cpp:260] Setting up conv3_1/dw/bn
-I0510 14:48:30.247725  5307 net.cpp:267] TEST Top shape for layer 24 'conv3_1/dw/bn' 8 64 64 128 (4194304)
-I0510 14:48:30.247738  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Scale'
-I0510 14:48:30.247743  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247751  5307 net.cpp:200] Created Layer conv3_1/dw/scale (25)
-I0510 14:48:30.247756  5307 net.cpp:572] conv3_1/dw/scale <- conv3_1/dw
-I0510 14:48:30.247761  5307 net.cpp:527] conv3_1/dw/scale -> conv3_1/dw (in-place)
-I0510 14:48:30.247802  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Bias'
-I0510 14:48:30.247807  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247918  5307 net.cpp:260] Setting up conv3_1/dw/scale
-I0510 14:48:30.247925  5307 net.cpp:267] TEST Top shape for layer 25 'conv3_1/dw/scale' 8 64 64 128 (4194304)
-I0510 14:48:30.247941  5307 layer_factory.hpp:172] Creating layer 'relu3_1/dw' of type 'ReLU'
-I0510 14:48:30.247951  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247962  5307 net.cpp:200] Created Layer relu3_1/dw (26)
-I0510 14:48:30.247972  5307 net.cpp:572] relu3_1/dw <- conv3_1/dw
-I0510 14:48:30.247982  5307 net.cpp:527] relu3_1/dw -> conv3_1/dw (in-place)
-I0510 14:48:30.247993  5307 net.cpp:260] Setting up relu3_1/dw
-I0510 14:48:30.248004  5307 net.cpp:267] TEST Top shape for layer 26 'relu3_1/dw' 8 64 64 128 (4194304)
-I0510 14:48:30.248014  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep' of type 'Convolution'
-I0510 14:48:30.248024  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.248037  5307 net.cpp:200] Created Layer conv3_1/sep (27)
-I0510 14:48:30.248047  5307 net.cpp:572] conv3_1/sep <- conv3_1/dw
-I0510 14:48:30.248057  5307 net.cpp:542] conv3_1/sep -> conv3_1/sep
-I0510 14:48:30.248392  5307 net.cpp:260] Setting up conv3_1/sep
-I0510 14:48:30.248400  5307 net.cpp:267] TEST Top shape for layer 27 'conv3_1/sep' 8 64 64 128 (4194304)
-I0510 14:48:30.248407  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.248411  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.248417  5307 net.cpp:200] Created Layer conv3_1/sep/bn (28)
-I0510 14:48:30.248421  5307 net.cpp:572] conv3_1/sep/bn <- conv3_1/sep
-I0510 14:48:30.248426  5307 net.cpp:527] conv3_1/sep/bn -> conv3_1/sep (in-place)
-I0510 14:48:30.248793  5307 net.cpp:260] Setting up conv3_1/sep/bn
-I0510 14:48:30.248801  5307 net.cpp:267] TEST Top shape for layer 28 'conv3_1/sep/bn' 8 64 64 128 (4194304)
-I0510 14:48:30.248826  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Scale'
-I0510 14:48:30.248831  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.248837  5307 net.cpp:200] Created Layer conv3_1/sep/scale (29)
-I0510 14:48:30.248842  5307 net.cpp:572] conv3_1/sep/scale <- conv3_1/sep
-I0510 14:48:30.248845  5307 net.cpp:527] conv3_1/sep/scale -> conv3_1/sep (in-place)
-I0510 14:48:30.248880  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Bias'
-I0510 14:48:30.248893  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249006  5307 net.cpp:260] Setting up conv3_1/sep/scale
-I0510 14:48:30.249013  5307 net.cpp:267] TEST Top shape for layer 29 'conv3_1/sep/scale' 8 64 64 128 (4194304)
-I0510 14:48:30.249020  5307 layer_factory.hpp:172] Creating layer 'relu3_1/sep' of type 'ReLU'
-I0510 14:48:30.249025  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249030  5307 net.cpp:200] Created Layer relu3_1/sep (30)
-I0510 14:48:30.249034  5307 net.cpp:572] relu3_1/sep <- conv3_1/sep
-I0510 14:48:30.249039  5307 net.cpp:527] relu3_1/sep -> conv3_1/sep (in-place)
-I0510 14:48:30.249044  5307 net.cpp:260] Setting up relu3_1/sep
-I0510 14:48:30.249049  5307 net.cpp:267] TEST Top shape for layer 30 'relu3_1/sep' 8 64 64 128 (4194304)
-I0510 14:48:30.249053  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw' of type 'Convolution'
-I0510 14:48:30.249058  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249065  5307 net.cpp:200] Created Layer conv3_2/dw (31)
-I0510 14:48:30.249069  5307 net.cpp:572] conv3_2/dw <- conv3_1/sep
-I0510 14:48:30.249074  5307 net.cpp:542] conv3_2/dw -> conv3_2/dw
-I0510 14:48:30.249277  5307 net.cpp:260] Setting up conv3_2/dw
-I0510 14:48:30.249285  5307 net.cpp:267] TEST Top shape for layer 31 'conv3_2/dw' 8 64 32 64 (1048576)
-I0510 14:48:30.249291  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.249296  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249305  5307 net.cpp:200] Created Layer conv3_2/dw/bn (32)
-I0510 14:48:30.249310  5307 net.cpp:572] conv3_2/dw/bn <- conv3_2/dw
-I0510 14:48:30.249315  5307 net.cpp:527] conv3_2/dw/bn -> conv3_2/dw (in-place)
-I0510 14:48:30.249661  5307 net.cpp:260] Setting up conv3_2/dw/bn
-I0510 14:48:30.249670  5307 net.cpp:267] TEST Top shape for layer 32 'conv3_2/dw/bn' 8 64 32 64 (1048576)
-I0510 14:48:30.249685  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Scale'
-I0510 14:48:30.249694  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249706  5307 net.cpp:200] Created Layer conv3_2/dw/scale (33)
-I0510 14:48:30.249714  5307 net.cpp:572] conv3_2/dw/scale <- conv3_2/dw
-I0510 14:48:30.249723  5307 net.cpp:527] conv3_2/dw/scale -> conv3_2/dw (in-place)
-I0510 14:48:30.249765  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Bias'
-I0510 14:48:30.249776  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249883  5307 net.cpp:260] Setting up conv3_2/dw/scale
-I0510 14:48:30.249891  5307 net.cpp:267] TEST Top shape for layer 33 'conv3_2/dw/scale' 8 64 32 64 (1048576)
-I0510 14:48:30.249898  5307 layer_factory.hpp:172] Creating layer 'relu3_2/dw' of type 'ReLU'
-I0510 14:48:30.249903  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249908  5307 net.cpp:200] Created Layer relu3_2/dw (34)
-I0510 14:48:30.249913  5307 net.cpp:572] relu3_2/dw <- conv3_2/dw
-I0510 14:48:30.249917  5307 net.cpp:527] relu3_2/dw -> conv3_2/dw (in-place)
-I0510 14:48:30.249923  5307 net.cpp:260] Setting up relu3_2/dw
-I0510 14:48:30.249938  5307 net.cpp:267] TEST Top shape for layer 34 'relu3_2/dw' 8 64 32 64 (1048576)
-I0510 14:48:30.249953  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep' of type 'Convolution'
-I0510 14:48:30.249963  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249975  5307 net.cpp:200] Created Layer conv3_2/sep (35)
-I0510 14:48:30.249984  5307 net.cpp:572] conv3_2/sep <- conv3_2/dw
-I0510 14:48:30.249992  5307 net.cpp:542] conv3_2/sep -> conv3_2/sep
-I0510 14:48:30.250567  5307 net.cpp:260] Setting up conv3_2/sep
-I0510 14:48:30.250586  5307 net.cpp:267] TEST Top shape for layer 35 'conv3_2/sep' 8 128 32 64 (2097152)
-I0510 14:48:30.250597  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.250604  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.250614  5307 net.cpp:200] Created Layer conv3_2/sep/bn (36)
-I0510 14:48:30.250622  5307 net.cpp:572] conv3_2/sep/bn <- conv3_2/sep
-I0510 14:48:30.250630  5307 net.cpp:527] conv3_2/sep/bn -> conv3_2/sep (in-place)
-I0510 14:48:30.251098  5307 net.cpp:260] Setting up conv3_2/sep/bn
-I0510 14:48:30.251116  5307 net.cpp:267] TEST Top shape for layer 36 'conv3_2/sep/bn' 8 128 32 64 (2097152)
-I0510 14:48:30.251128  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Scale'
-I0510 14:48:30.251137  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251147  5307 net.cpp:200] Created Layer conv3_2/sep/scale (37)
-I0510 14:48:30.251157  5307 net.cpp:572] conv3_2/sep/scale <- conv3_2/sep
-I0510 14:48:30.251164  5307 net.cpp:527] conv3_2/sep/scale -> conv3_2/sep (in-place)
-I0510 14:48:30.251205  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Bias'
-I0510 14:48:30.251215  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251317  5307 net.cpp:260] Setting up conv3_2/sep/scale
-I0510 14:48:30.251330  5307 net.cpp:267] TEST Top shape for layer 37 'conv3_2/sep/scale' 8 128 32 64 (2097152)
-I0510 14:48:30.251341  5307 layer_factory.hpp:172] Creating layer 'relu3_2/sep' of type 'ReLU'
-I0510 14:48:30.251350  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251360  5307 net.cpp:200] Created Layer relu3_2/sep (38)
-I0510 14:48:30.251369  5307 net.cpp:572] relu3_2/sep <- conv3_2/sep
-I0510 14:48:30.251379  5307 net.cpp:527] relu3_2/sep -> conv3_2/sep (in-place)
-I0510 14:48:30.251389  5307 net.cpp:260] Setting up relu3_2/sep
-I0510 14:48:30.251399  5307 net.cpp:267] TEST Top shape for layer 38 'relu3_2/sep' 8 128 32 64 (2097152)
-I0510 14:48:30.251407  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw' of type 'Convolution'
-I0510 14:48:30.251416  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251430  5307 net.cpp:200] Created Layer conv4_1/dw (39)
-I0510 14:48:30.251438  5307 net.cpp:572] conv4_1/dw <- conv3_2/sep
-I0510 14:48:30.251447  5307 net.cpp:542] conv4_1/dw -> conv4_1/dw
-I0510 14:48:30.251679  5307 net.cpp:260] Setting up conv4_1/dw
-I0510 14:48:30.251698  5307 net.cpp:267] TEST Top shape for layer 39 'conv4_1/dw' 8 128 32 64 (2097152)
-I0510 14:48:30.251710  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.251720  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251732  5307 net.cpp:200] Created Layer conv4_1/dw/bn (40)
-I0510 14:48:30.251742  5307 net.cpp:572] conv4_1/dw/bn <- conv4_1/dw
-I0510 14:48:30.251752  5307 net.cpp:527] conv4_1/dw/bn -> conv4_1/dw (in-place)
-I0510 14:48:30.252107  5307 net.cpp:260] Setting up conv4_1/dw/bn
-I0510 14:48:30.252125  5307 net.cpp:267] TEST Top shape for layer 40 'conv4_1/dw/bn' 8 128 32 64 (2097152)
-I0510 14:48:30.252138  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Scale'
-I0510 14:48:30.252153  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.252174  5307 net.cpp:200] Created Layer conv4_1/dw/scale (41)
-I0510 14:48:30.252184  5307 net.cpp:572] conv4_1/dw/scale <- conv4_1/dw
-I0510 14:48:30.252193  5307 net.cpp:527] conv4_1/dw/scale -> conv4_1/dw (in-place)
-I0510 14:48:30.252236  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Bias'
-I0510 14:48:30.252249  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.252357  5307 net.cpp:260] Setting up conv4_1/dw/scale
-I0510 14:48:30.252372  5307 net.cpp:267] TEST Top shape for layer 41 'conv4_1/dw/scale' 8 128 32 64 (2097152)
-I0510 14:48:30.252387  5307 layer_factory.hpp:172] Creating layer 'relu4_1/dw' of type 'ReLU'
-I0510 14:48:30.252398  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.252408  5307 net.cpp:200] Created Layer relu4_1/dw (42)
-I0510 14:48:30.252418  5307 net.cpp:572] relu4_1/dw <- conv4_1/dw
-I0510 14:48:30.252429  5307 net.cpp:527] relu4_1/dw -> conv4_1/dw (in-place)
-I0510 14:48:30.252442  5307 net.cpp:260] Setting up relu4_1/dw
-I0510 14:48:30.252454  5307 net.cpp:267] TEST Top shape for layer 42 'relu4_1/dw' 8 128 32 64 (2097152)
-I0510 14:48:30.252465  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep' of type 'Convolution'
-I0510 14:48:30.252475  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.252490  5307 net.cpp:200] Created Layer conv4_1/sep (43)
-I0510 14:48:30.252501  5307 net.cpp:572] conv4_1/sep <- conv4_1/dw
-I0510 14:48:30.252511  5307 net.cpp:542] conv4_1/sep -> conv4_1/sep
-I0510 14:48:30.253233  5307 net.cpp:260] Setting up conv4_1/sep
-I0510 14:48:30.253252  5307 net.cpp:267] TEST Top shape for layer 43 'conv4_1/sep' 8 128 32 64 (2097152)
-I0510 14:48:30.253264  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.253273  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253284  5307 net.cpp:200] Created Layer conv4_1/sep/bn (44)
-I0510 14:48:30.253293  5307 net.cpp:572] conv4_1/sep/bn <- conv4_1/sep
-I0510 14:48:30.253302  5307 net.cpp:527] conv4_1/sep/bn -> conv4_1/sep (in-place)
-I0510 14:48:30.253645  5307 net.cpp:260] Setting up conv4_1/sep/bn
-I0510 14:48:30.253659  5307 net.cpp:267] TEST Top shape for layer 44 'conv4_1/sep/bn' 8 128 32 64 (2097152)
-I0510 14:48:30.253674  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Scale'
-I0510 14:48:30.253684  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253695  5307 net.cpp:200] Created Layer conv4_1/sep/scale (45)
-I0510 14:48:30.253705  5307 net.cpp:572] conv4_1/sep/scale <- conv4_1/sep
-I0510 14:48:30.253713  5307 net.cpp:527] conv4_1/sep/scale -> conv4_1/sep (in-place)
-I0510 14:48:30.253756  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Bias'
-I0510 14:48:30.253767  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253870  5307 net.cpp:260] Setting up conv4_1/sep/scale
-I0510 14:48:30.253882  5307 net.cpp:267] TEST Top shape for layer 45 'conv4_1/sep/scale' 8 128 32 64 (2097152)
-I0510 14:48:30.253895  5307 layer_factory.hpp:172] Creating layer 'relu4_1/sep' of type 'ReLU'
-I0510 14:48:30.253902  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253912  5307 net.cpp:200] Created Layer relu4_1/sep (46)
-I0510 14:48:30.253921  5307 net.cpp:572] relu4_1/sep <- conv4_1/sep
-I0510 14:48:30.253929  5307 net.cpp:527] relu4_1/sep -> conv4_1/sep (in-place)
-I0510 14:48:30.253939  5307 net.cpp:260] Setting up relu4_1/sep
-I0510 14:48:30.253949  5307 net.cpp:267] TEST Top shape for layer 46 'relu4_1/sep' 8 128 32 64 (2097152)
-I0510 14:48:30.253957  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw' of type 'Convolution'
-I0510 14:48:30.253969  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253988  5307 net.cpp:200] Created Layer conv4_2/dw (47)
-I0510 14:48:30.253998  5307 net.cpp:572] conv4_2/dw <- conv4_1/sep
-I0510 14:48:30.254006  5307 net.cpp:542] conv4_2/dw -> conv4_2/dw
-I0510 14:48:30.254235  5307 net.cpp:260] Setting up conv4_2/dw
-I0510 14:48:30.254248  5307 net.cpp:267] TEST Top shape for layer 47 'conv4_2/dw' 8 128 16 32 (524288)
-I0510 14:48:30.254259  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.254268  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254278  5307 net.cpp:200] Created Layer conv4_2/dw/bn (48)
-I0510 14:48:30.254287  5307 net.cpp:572] conv4_2/dw/bn <- conv4_2/dw
-I0510 14:48:30.254297  5307 net.cpp:527] conv4_2/dw/bn -> conv4_2/dw (in-place)
-I0510 14:48:30.254638  5307 net.cpp:260] Setting up conv4_2/dw/bn
-I0510 14:48:30.254652  5307 net.cpp:267] TEST Top shape for layer 48 'conv4_2/dw/bn' 8 128 16 32 (524288)
-I0510 14:48:30.254663  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Scale'
-I0510 14:48:30.254673  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254683  5307 net.cpp:200] Created Layer conv4_2/dw/scale (49)
-I0510 14:48:30.254691  5307 net.cpp:572] conv4_2/dw/scale <- conv4_2/dw
-I0510 14:48:30.254699  5307 net.cpp:527] conv4_2/dw/scale -> conv4_2/dw (in-place)
-I0510 14:48:30.254740  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Bias'
-I0510 14:48:30.254750  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254853  5307 net.cpp:260] Setting up conv4_2/dw/scale
-I0510 14:48:30.254865  5307 net.cpp:267] TEST Top shape for layer 49 'conv4_2/dw/scale' 8 128 16 32 (524288)
-I0510 14:48:30.254876  5307 layer_factory.hpp:172] Creating layer 'relu4_2/dw' of type 'ReLU'
-I0510 14:48:30.254885  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254895  5307 net.cpp:200] Created Layer relu4_2/dw (50)
-I0510 14:48:30.254906  5307 net.cpp:572] relu4_2/dw <- conv4_2/dw
-I0510 14:48:30.254916  5307 net.cpp:527] relu4_2/dw -> conv4_2/dw (in-place)
-I0510 14:48:30.254928  5307 net.cpp:260] Setting up relu4_2/dw
-I0510 14:48:30.254940  5307 net.cpp:267] TEST Top shape for layer 50 'relu4_2/dw' 8 128 16 32 (524288)
-I0510 14:48:30.254951  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep' of type 'Convolution'
-I0510 14:48:30.254961  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254974  5307 net.cpp:200] Created Layer conv4_2/sep (51)
-I0510 14:48:30.254982  5307 net.cpp:572] conv4_2/sep <- conv4_2/dw
-I0510 14:48:30.254992  5307 net.cpp:542] conv4_2/sep -> conv4_2/sep
-I0510 14:48:30.256186  5307 net.cpp:260] Setting up conv4_2/sep
-I0510 14:48:30.256203  5307 net.cpp:267] TEST Top shape for layer 51 'conv4_2/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.256216  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.256224  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256237  5307 net.cpp:200] Created Layer conv4_2/sep/bn (52)
-I0510 14:48:30.256247  5307 net.cpp:572] conv4_2/sep/bn <- conv4_2/sep
-I0510 14:48:30.256256  5307 net.cpp:527] conv4_2/sep/bn -> conv4_2/sep (in-place)
-I0510 14:48:30.256623  5307 net.cpp:260] Setting up conv4_2/sep/bn
-I0510 14:48:30.256640  5307 net.cpp:267] TEST Top shape for layer 52 'conv4_2/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.256654  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Scale'
-I0510 14:48:30.256664  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256675  5307 net.cpp:200] Created Layer conv4_2/sep/scale (53)
-I0510 14:48:30.256683  5307 net.cpp:572] conv4_2/sep/scale <- conv4_2/sep
-I0510 14:48:30.256696  5307 net.cpp:527] conv4_2/sep/scale -> conv4_2/sep (in-place)
-I0510 14:48:30.256747  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Bias'
-I0510 14:48:30.256757  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256861  5307 net.cpp:260] Setting up conv4_2/sep/scale
-I0510 14:48:30.256873  5307 net.cpp:267] TEST Top shape for layer 53 'conv4_2/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.256886  5307 layer_factory.hpp:172] Creating layer 'relu4_2/sep' of type 'ReLU'
-I0510 14:48:30.256893  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256903  5307 net.cpp:200] Created Layer relu4_2/sep (54)
-I0510 14:48:30.256912  5307 net.cpp:572] relu4_2/sep <- conv4_2/sep
-I0510 14:48:30.256920  5307 net.cpp:527] relu4_2/sep -> conv4_2/sep (in-place)
-I0510 14:48:30.256932  5307 net.cpp:260] Setting up relu4_2/sep
-I0510 14:48:30.256940  5307 net.cpp:267] TEST Top shape for layer 54 'relu4_2/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.256949  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw' of type 'Convolution'
-I0510 14:48:30.256958  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256971  5307 net.cpp:200] Created Layer conv5_1/dw (55)
-I0510 14:48:30.256980  5307 net.cpp:572] conv5_1/dw <- conv4_2/sep
-I0510 14:48:30.256989  5307 net.cpp:542] conv5_1/dw -> conv5_1/dw
-I0510 14:48:30.257251  5307 net.cpp:260] Setting up conv5_1/dw
-I0510 14:48:30.257264  5307 net.cpp:267] TEST Top shape for layer 55 'conv5_1/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.257275  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.257284  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257295  5307 net.cpp:200] Created Layer conv5_1/dw/bn (56)
-I0510 14:48:30.257304  5307 net.cpp:572] conv5_1/dw/bn <- conv5_1/dw
-I0510 14:48:30.257313  5307 net.cpp:527] conv5_1/dw/bn -> conv5_1/dw (in-place)
-I0510 14:48:30.257652  5307 net.cpp:260] Setting up conv5_1/dw/bn
-I0510 14:48:30.257665  5307 net.cpp:267] TEST Top shape for layer 56 'conv5_1/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.257678  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Scale'
-I0510 14:48:30.257686  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257697  5307 net.cpp:200] Created Layer conv5_1/dw/scale (57)
-I0510 14:48:30.257706  5307 net.cpp:572] conv5_1/dw/scale <- conv5_1/dw
-I0510 14:48:30.257714  5307 net.cpp:527] conv5_1/dw/scale -> conv5_1/dw (in-place)
-I0510 14:48:30.257757  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Bias'
-I0510 14:48:30.257767  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257871  5307 net.cpp:260] Setting up conv5_1/dw/scale
-I0510 14:48:30.257884  5307 net.cpp:267] TEST Top shape for layer 57 'conv5_1/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.257895  5307 layer_factory.hpp:172] Creating layer 'relu5_1/dw' of type 'ReLU'
-I0510 14:48:30.257903  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257912  5307 net.cpp:200] Created Layer relu5_1/dw (58)
-I0510 14:48:30.257921  5307 net.cpp:572] relu5_1/dw <- conv5_1/dw
-I0510 14:48:30.257930  5307 net.cpp:527] relu5_1/dw -> conv5_1/dw (in-place)
-I0510 14:48:30.257941  5307 net.cpp:260] Setting up relu5_1/dw
-I0510 14:48:30.257951  5307 net.cpp:267] TEST Top shape for layer 58 'relu5_1/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.257958  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep' of type 'Convolution'
-I0510 14:48:30.257967  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257982  5307 net.cpp:200] Created Layer conv5_1/sep (59)
-I0510 14:48:30.257990  5307 net.cpp:572] conv5_1/sep <- conv5_1/dw
-I0510 14:48:30.258002  5307 net.cpp:542] conv5_1/sep -> conv5_1/sep
-I0510 14:48:30.260092  5307 net.cpp:260] Setting up conv5_1/sep
-I0510 14:48:30.260109  5307 net.cpp:267] TEST Top shape for layer 59 'conv5_1/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.260119  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.260128  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260138  5307 net.cpp:200] Created Layer conv5_1/sep/bn (60)
-I0510 14:48:30.260145  5307 net.cpp:572] conv5_1/sep/bn <- conv5_1/sep
-I0510 14:48:30.260154  5307 net.cpp:527] conv5_1/sep/bn -> conv5_1/sep (in-place)
-I0510 14:48:30.260478  5307 net.cpp:260] Setting up conv5_1/sep/bn
-I0510 14:48:30.260491  5307 net.cpp:267] TEST Top shape for layer 60 'conv5_1/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.260504  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Scale'
-I0510 14:48:30.260514  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260529  5307 net.cpp:200] Created Layer conv5_1/sep/scale (61)
-I0510 14:48:30.260540  5307 net.cpp:572] conv5_1/sep/scale <- conv5_1/sep
-I0510 14:48:30.260550  5307 net.cpp:527] conv5_1/sep/scale -> conv5_1/sep (in-place)
-I0510 14:48:30.260593  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Bias'
-I0510 14:48:30.260604  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260711  5307 net.cpp:260] Setting up conv5_1/sep/scale
-I0510 14:48:30.260723  5307 net.cpp:267] TEST Top shape for layer 61 'conv5_1/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.260735  5307 layer_factory.hpp:172] Creating layer 'relu5_1/sep' of type 'ReLU'
-I0510 14:48:30.260743  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260752  5307 net.cpp:200] Created Layer relu5_1/sep (62)
-I0510 14:48:30.260761  5307 net.cpp:572] relu5_1/sep <- conv5_1/sep
-I0510 14:48:30.260771  5307 net.cpp:527] relu5_1/sep -> conv5_1/sep (in-place)
-I0510 14:48:30.260782  5307 net.cpp:260] Setting up relu5_1/sep
-I0510 14:48:30.260792  5307 net.cpp:267] TEST Top shape for layer 62 'relu5_1/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.260800  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw' of type 'Convolution'
-I0510 14:48:30.260809  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260821  5307 net.cpp:200] Created Layer conv5_2/dw (63)
-I0510 14:48:30.260830  5307 net.cpp:572] conv5_2/dw <- conv5_1/sep
-I0510 14:48:30.260838  5307 net.cpp:542] conv5_2/dw -> conv5_2/dw
-I0510 14:48:30.261092  5307 net.cpp:260] Setting up conv5_2/dw
-I0510 14:48:30.261106  5307 net.cpp:267] TEST Top shape for layer 63 'conv5_2/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.261116  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.261124  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261135  5307 net.cpp:200] Created Layer conv5_2/dw/bn (64)
-I0510 14:48:30.261144  5307 net.cpp:572] conv5_2/dw/bn <- conv5_2/dw
-I0510 14:48:30.261152  5307 net.cpp:527] conv5_2/dw/bn -> conv5_2/dw (in-place)
-I0510 14:48:30.261476  5307 net.cpp:260] Setting up conv5_2/dw/bn
-I0510 14:48:30.261487  5307 net.cpp:267] TEST Top shape for layer 64 'conv5_2/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.261499  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Scale'
-I0510 14:48:30.261507  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261519  5307 net.cpp:200] Created Layer conv5_2/dw/scale (65)
-I0510 14:48:30.261528  5307 net.cpp:572] conv5_2/dw/scale <- conv5_2/dw
-I0510 14:48:30.261535  5307 net.cpp:527] conv5_2/dw/scale -> conv5_2/dw (in-place)
-I0510 14:48:30.261574  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Bias'
-I0510 14:48:30.261586  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261684  5307 net.cpp:260] Setting up conv5_2/dw/scale
-I0510 14:48:30.261696  5307 net.cpp:267] TEST Top shape for layer 65 'conv5_2/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.261708  5307 layer_factory.hpp:172] Creating layer 'relu5_2/dw' of type 'ReLU'
-I0510 14:48:30.261715  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261723  5307 net.cpp:200] Created Layer relu5_2/dw (66)
-I0510 14:48:30.261732  5307 net.cpp:572] relu5_2/dw <- conv5_2/dw
-I0510 14:48:30.261740  5307 net.cpp:527] relu5_2/dw -> conv5_2/dw (in-place)
-I0510 14:48:30.261749  5307 net.cpp:260] Setting up relu5_2/dw
-I0510 14:48:30.261759  5307 net.cpp:267] TEST Top shape for layer 66 'relu5_2/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.261766  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep' of type 'Convolution'
-I0510 14:48:30.261775  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261786  5307 net.cpp:200] Created Layer conv5_2/sep (67)
-I0510 14:48:30.261795  5307 net.cpp:572] conv5_2/sep <- conv5_2/dw
-I0510 14:48:30.261802  5307 net.cpp:542] conv5_2/sep -> conv5_2/sep
-I0510 14:48:30.263923  5307 net.cpp:260] Setting up conv5_2/sep
-I0510 14:48:30.263937  5307 net.cpp:267] TEST Top shape for layer 67 'conv5_2/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.263947  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.263955  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.263967  5307 net.cpp:200] Created Layer conv5_2/sep/bn (68)
-I0510 14:48:30.263975  5307 net.cpp:572] conv5_2/sep/bn <- conv5_2/sep
-I0510 14:48:30.263983  5307 net.cpp:527] conv5_2/sep/bn -> conv5_2/sep (in-place)
-I0510 14:48:30.264274  5307 net.cpp:260] Setting up conv5_2/sep/bn
-I0510 14:48:30.264288  5307 net.cpp:267] TEST Top shape for layer 68 'conv5_2/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.264300  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Scale'
-I0510 14:48:30.264310  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264320  5307 net.cpp:200] Created Layer conv5_2/sep/scale (69)
-I0510 14:48:30.264329  5307 net.cpp:572] conv5_2/sep/scale <- conv5_2/sep
-I0510 14:48:30.264338  5307 net.cpp:527] conv5_2/sep/scale -> conv5_2/sep (in-place)
-I0510 14:48:30.264381  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Bias'
-I0510 14:48:30.264392  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264497  5307 net.cpp:260] Setting up conv5_2/sep/scale
-I0510 14:48:30.264510  5307 net.cpp:267] TEST Top shape for layer 69 'conv5_2/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.264521  5307 layer_factory.hpp:172] Creating layer 'relu5_2/sep' of type 'ReLU'
-I0510 14:48:30.264536  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264545  5307 net.cpp:200] Created Layer relu5_2/sep (70)
-I0510 14:48:30.264554  5307 net.cpp:572] relu5_2/sep <- conv5_2/sep
-I0510 14:48:30.264564  5307 net.cpp:527] relu5_2/sep -> conv5_2/sep (in-place)
-I0510 14:48:30.264575  5307 net.cpp:260] Setting up relu5_2/sep
-I0510 14:48:30.264585  5307 net.cpp:267] TEST Top shape for layer 70 'relu5_2/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.264592  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw' of type 'Convolution'
-I0510 14:48:30.264601  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264616  5307 net.cpp:200] Created Layer conv5_3/dw (71)
-I0510 14:48:30.264626  5307 net.cpp:572] conv5_3/dw <- conv5_2/sep
-I0510 14:48:30.264633  5307 net.cpp:542] conv5_3/dw -> conv5_3/dw
-I0510 14:48:30.264899  5307 net.cpp:260] Setting up conv5_3/dw
-I0510 14:48:30.264914  5307 net.cpp:267] TEST Top shape for layer 71 'conv5_3/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.264930  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.264946  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264956  5307 net.cpp:200] Created Layer conv5_3/dw/bn (72)
-I0510 14:48:30.264966  5307 net.cpp:572] conv5_3/dw/bn <- conv5_3/dw
-I0510 14:48:30.264974  5307 net.cpp:527] conv5_3/dw/bn -> conv5_3/dw (in-place)
-I0510 14:48:30.265358  5307 net.cpp:260] Setting up conv5_3/dw/bn
-I0510 14:48:30.265375  5307 net.cpp:267] TEST Top shape for layer 72 'conv5_3/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.265388  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Scale'
-I0510 14:48:30.265398  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.265409  5307 net.cpp:200] Created Layer conv5_3/dw/scale (73)
-I0510 14:48:30.265419  5307 net.cpp:572] conv5_3/dw/scale <- conv5_3/dw
-I0510 14:48:30.265429  5307 net.cpp:527] conv5_3/dw/scale -> conv5_3/dw (in-place)
-I0510 14:48:30.265482  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Bias'
-I0510 14:48:30.265493  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.265604  5307 net.cpp:260] Setting up conv5_3/dw/scale
-I0510 14:48:30.265615  5307 net.cpp:267] TEST Top shape for layer 73 'conv5_3/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.265626  5307 layer_factory.hpp:172] Creating layer 'relu5_3/dw' of type 'ReLU'
-I0510 14:48:30.265635  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.265643  5307 net.cpp:200] Created Layer relu5_3/dw (74)
-I0510 14:48:30.265651  5307 net.cpp:572] relu5_3/dw <- conv5_3/dw
-I0510 14:48:30.265658  5307 net.cpp:527] relu5_3/dw -> conv5_3/dw (in-place)
-I0510 14:48:30.265668  5307 net.cpp:260] Setting up relu5_3/dw
-I0510 14:48:30.265676  5307 net.cpp:267] TEST Top shape for layer 74 'relu5_3/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.265684  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep' of type 'Convolution'
-I0510 14:48:30.265692  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.265704  5307 net.cpp:200] Created Layer conv5_3/sep (75)
-I0510 14:48:30.265712  5307 net.cpp:572] conv5_3/sep <- conv5_3/dw
-I0510 14:48:30.265720  5307 net.cpp:542] conv5_3/sep -> conv5_3/sep
-I0510 14:48:30.277580  5307 net.cpp:260] Setting up conv5_3/sep
-I0510 14:48:30.277678  5307 net.cpp:267] TEST Top shape for layer 75 'conv5_3/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.277724  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.277750  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.277782  5307 net.cpp:200] Created Layer conv5_3/sep/bn (76)
-I0510 14:48:30.277806  5307 net.cpp:572] conv5_3/sep/bn <- conv5_3/sep
-I0510 14:48:30.277829  5307 net.cpp:527] conv5_3/sep/bn -> conv5_3/sep (in-place)
-I0510 14:48:30.278512  5307 net.cpp:260] Setting up conv5_3/sep/bn
-I0510 14:48:30.278524  5307 net.cpp:267] TEST Top shape for layer 76 'conv5_3/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.278535  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Scale'
-I0510 14:48:30.278543  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.278571  5307 net.cpp:200] Created Layer conv5_3/sep/scale (77)
-I0510 14:48:30.278589  5307 net.cpp:572] conv5_3/sep/scale <- conv5_3/sep
-I0510 14:48:30.278605  5307 net.cpp:527] conv5_3/sep/scale -> conv5_3/sep (in-place)
-I0510 14:48:30.278686  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Bias'
-I0510 14:48:30.278695  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.279238  5307 net.cpp:260] Setting up conv5_3/sep/scale
-I0510 14:48:30.279259  5307 net.cpp:267] TEST Top shape for layer 77 'conv5_3/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.279630  5307 layer_factory.hpp:172] Creating layer 'relu5_3/sep' of type 'ReLU'
-I0510 14:48:30.279650  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.279662  5307 net.cpp:200] Created Layer relu5_3/sep (78)
-I0510 14:48:30.279671  5307 net.cpp:572] relu5_3/sep <- conv5_3/sep
-I0510 14:48:30.279681  5307 net.cpp:527] relu5_3/sep -> conv5_3/sep (in-place)
-I0510 14:48:30.279696  5307 net.cpp:260] Setting up relu5_3/sep
-I0510 14:48:30.279707  5307 net.cpp:267] TEST Top shape for layer 78 'relu5_3/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.279716  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw' of type 'Convolution'
-I0510 14:48:30.279726  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.279747  5307 net.cpp:200] Created Layer conv5_4/dw (79)
-I0510 14:48:30.279757  5307 net.cpp:572] conv5_4/dw <- conv5_3/sep
-I0510 14:48:30.279765  5307 net.cpp:542] conv5_4/dw -> conv5_4/dw
-I0510 14:48:30.280048  5307 net.cpp:260] Setting up conv5_4/dw
-I0510 14:48:30.280062  5307 net.cpp:267] TEST Top shape for layer 79 'conv5_4/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.280073  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.280082  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.280093  5307 net.cpp:200] Created Layer conv5_4/dw/bn (80)
-I0510 14:48:30.280102  5307 net.cpp:572] conv5_4/dw/bn <- conv5_4/dw
-I0510 14:48:30.280112  5307 net.cpp:527] conv5_4/dw/bn -> conv5_4/dw (in-place)
-I0510 14:48:30.281548  5307 net.cpp:260] Setting up conv5_4/dw/bn
-I0510 14:48:30.281565  5307 net.cpp:267] TEST Top shape for layer 80 'conv5_4/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.281579  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Scale'
-I0510 14:48:30.281587  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.281599  5307 net.cpp:200] Created Layer conv5_4/dw/scale (81)
-I0510 14:48:30.281606  5307 net.cpp:572] conv5_4/dw/scale <- conv5_4/dw
-I0510 14:48:30.281615  5307 net.cpp:527] conv5_4/dw/scale -> conv5_4/dw (in-place)
-I0510 14:48:30.281661  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Bias'
-I0510 14:48:30.281672  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.281785  5307 net.cpp:260] Setting up conv5_4/dw/scale
-I0510 14:48:30.281801  5307 net.cpp:267] TEST Top shape for layer 81 'conv5_4/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.281816  5307 layer_factory.hpp:172] Creating layer 'relu5_4/dw' of type 'ReLU'
-I0510 14:48:30.281826  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.281837  5307 net.cpp:200] Created Layer relu5_4/dw (82)
-I0510 14:48:30.281848  5307 net.cpp:572] relu5_4/dw <- conv5_4/dw
-I0510 14:48:30.281859  5307 net.cpp:527] relu5_4/dw -> conv5_4/dw (in-place)
-I0510 14:48:30.281872  5307 net.cpp:260] Setting up relu5_4/dw
-I0510 14:48:30.282164  5307 net.cpp:267] TEST Top shape for layer 82 'relu5_4/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.282176  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep' of type 'Convolution'
-I0510 14:48:30.282184  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.282199  5307 net.cpp:200] Created Layer conv5_4/sep (83)
-I0510 14:48:30.282209  5307 net.cpp:572] conv5_4/sep <- conv5_4/dw
-I0510 14:48:30.282219  5307 net.cpp:542] conv5_4/sep -> conv5_4/sep
-I0510 14:48:30.288540  5307 net.cpp:260] Setting up conv5_4/sep
-I0510 14:48:30.288624  5307 net.cpp:267] TEST Top shape for layer 83 'conv5_4/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.288655  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.288674  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.288705  5307 net.cpp:200] Created Layer conv5_4/sep/bn (84)
-I0510 14:48:30.288733  5307 net.cpp:572] conv5_4/sep/bn <- conv5_4/sep
-I0510 14:48:30.288749  5307 net.cpp:527] conv5_4/sep/bn -> conv5_4/sep (in-place)
-I0510 14:48:30.289172  5307 net.cpp:260] Setting up conv5_4/sep/bn
-I0510 14:48:30.289194  5307 net.cpp:267] TEST Top shape for layer 84 'conv5_4/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.289214  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Scale'
-I0510 14:48:30.289229  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.289247  5307 net.cpp:200] Created Layer conv5_4/sep/scale (85)
-I0510 14:48:30.289263  5307 net.cpp:572] conv5_4/sep/scale <- conv5_4/sep
-I0510 14:48:30.289278  5307 net.cpp:527] conv5_4/sep/scale -> conv5_4/sep (in-place)
-I0510 14:48:30.289335  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Bias'
-I0510 14:48:30.289351  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.289476  5307 net.cpp:260] Setting up conv5_4/sep/scale
-I0510 14:48:30.289496  5307 net.cpp:267] TEST Top shape for layer 85 'conv5_4/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.289515  5307 layer_factory.hpp:172] Creating layer 'relu5_4/sep' of type 'ReLU'
-I0510 14:48:30.289530  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.289546  5307 net.cpp:200] Created Layer relu5_4/sep (86)
-I0510 14:48:30.289561  5307 net.cpp:572] relu5_4/sep <- conv5_4/sep
-I0510 14:48:30.289575  5307 net.cpp:527] relu5_4/sep -> conv5_4/sep (in-place)
-I0510 14:48:30.289592  5307 net.cpp:260] Setting up relu5_4/sep
-I0510 14:48:30.289608  5307 net.cpp:267] TEST Top shape for layer 86 'relu5_4/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.289626  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw' of type 'Convolution'
-I0510 14:48:30.289643  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.289662  5307 net.cpp:200] Created Layer conv5_5/dw (87)
-I0510 14:48:30.289677  5307 net.cpp:572] conv5_5/dw <- conv5_4/sep
-I0510 14:48:30.289691  5307 net.cpp:542] conv5_5/dw -> conv5_5/dw
-I0510 14:48:30.289973  5307 net.cpp:260] Setting up conv5_5/dw
-I0510 14:48:30.289995  5307 net.cpp:267] TEST Top shape for layer 87 'conv5_5/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.290016  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.290036  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.290056  5307 net.cpp:200] Created Layer conv5_5/dw/bn (88)
-I0510 14:48:30.290076  5307 net.cpp:572] conv5_5/dw/bn <- conv5_5/dw
-I0510 14:48:30.290094  5307 net.cpp:527] conv5_5/dw/bn -> conv5_5/dw (in-place)
-I0510 14:48:30.290571  5307 net.cpp:260] Setting up conv5_5/dw/bn
-I0510 14:48:30.290596  5307 net.cpp:267] TEST Top shape for layer 88 'conv5_5/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.290626  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Scale'
-I0510 14:48:30.290642  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.290661  5307 net.cpp:200] Created Layer conv5_5/dw/scale (89)
-I0510 14:48:30.290678  5307 net.cpp:572] conv5_5/dw/scale <- conv5_5/dw
-I0510 14:48:30.290693  5307 net.cpp:527] conv5_5/dw/scale -> conv5_5/dw (in-place)
-I0510 14:48:30.290745  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Bias'
-I0510 14:48:30.290763  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.290879  5307 net.cpp:260] Setting up conv5_5/dw/scale
-I0510 14:48:30.290900  5307 net.cpp:267] TEST Top shape for layer 89 'conv5_5/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.290920  5307 layer_factory.hpp:172] Creating layer 'relu5_5/dw' of type 'ReLU'
-I0510 14:48:30.290935  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.290956  5307 net.cpp:200] Created Layer relu5_5/dw (90)
-I0510 14:48:30.290980  5307 net.cpp:572] relu5_5/dw <- conv5_5/dw
-I0510 14:48:30.290997  5307 net.cpp:527] relu5_5/dw -> conv5_5/dw (in-place)
-I0510 14:48:30.291014  5307 net.cpp:260] Setting up relu5_5/dw
-I0510 14:48:30.291031  5307 net.cpp:267] TEST Top shape for layer 90 'relu5_5/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.291046  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep' of type 'Convolution'
-I0510 14:48:30.291062  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.291085  5307 net.cpp:200] Created Layer conv5_5/sep (91)
-I0510 14:48:30.291100  5307 net.cpp:572] conv5_5/sep <- conv5_5/dw
-I0510 14:48:30.291116  5307 net.cpp:542] conv5_5/sep -> conv5_5/sep
-I0510 14:48:30.295755  5307 net.cpp:260] Setting up conv5_5/sep
-I0510 14:48:30.295776  5307 net.cpp:267] TEST Top shape for layer 91 'conv5_5/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.295784  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.295789  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.295799  5307 net.cpp:200] Created Layer conv5_5/sep/bn (92)
-I0510 14:48:30.295804  5307 net.cpp:572] conv5_5/sep/bn <- conv5_5/sep
-I0510 14:48:30.295809  5307 net.cpp:527] conv5_5/sep/bn -> conv5_5/sep (in-place)
-I0510 14:48:30.296200  5307 net.cpp:260] Setting up conv5_5/sep/bn
-I0510 14:48:30.296209  5307 net.cpp:267] TEST Top shape for layer 92 'conv5_5/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.296223  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Scale'
-I0510 14:48:30.296231  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296252  5307 net.cpp:200] Created Layer conv5_5/sep/scale (93)
-I0510 14:48:30.296265  5307 net.cpp:572] conv5_5/sep/scale <- conv5_5/sep
-I0510 14:48:30.296277  5307 net.cpp:527] conv5_5/sep/scale -> conv5_5/sep (in-place)
-I0510 14:48:30.296329  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Bias'
-I0510 14:48:30.296336  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296476  5307 net.cpp:260] Setting up conv5_5/sep/scale
-I0510 14:48:30.296484  5307 net.cpp:267] TEST Top shape for layer 93 'conv5_5/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.296499  5307 layer_factory.hpp:172] Creating layer 'relu5_5/sep' of type 'ReLU'
-I0510 14:48:30.296509  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296520  5307 net.cpp:200] Created Layer relu5_5/sep (94)
-I0510 14:48:30.296541  5307 net.cpp:572] relu5_5/sep <- conv5_5/sep
-I0510 14:48:30.296551  5307 net.cpp:527] relu5_5/sep -> conv5_5/sep (in-place)
-I0510 14:48:30.296564  5307 net.cpp:260] Setting up relu5_5/sep
-I0510 14:48:30.296576  5307 net.cpp:267] TEST Top shape for layer 94 'relu5_5/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.296584  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep_relu5_5/sep_0_split' of type 'Split'
-I0510 14:48:30.296594  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296604  5307 net.cpp:200] Created Layer conv5_5/sep_relu5_5/sep_0_split (95)
-I0510 14:48:30.296614  5307 net.cpp:572] conv5_5/sep_relu5_5/sep_0_split <- conv5_5/sep
-I0510 14:48:30.296623  5307 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_0
-I0510 14:48:30.296635  5307 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_1
-I0510 14:48:30.296679  5307 net.cpp:260] Setting up conv5_5/sep_relu5_5/sep_0_split
-I0510 14:48:30.296685  5307 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 8 256 16 32 (1048576)
-I0510 14:48:30.296691  5307 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 8 256 16 32 (1048576)
-I0510 14:48:30.296696  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw' of type 'Convolution'
-I0510 14:48:30.296710  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296722  5307 net.cpp:200] Created Layer conv5_6/dw (96)
-I0510 14:48:30.296726  5307 net.cpp:572] conv5_6/dw <- conv5_5/sep_relu5_5/sep_0_split_0
-I0510 14:48:30.296731  5307 net.cpp:542] conv5_6/dw -> conv5_6/dw
-I0510 14:48:30.297003  5307 net.cpp:260] Setting up conv5_6/dw
-I0510 14:48:30.297011  5307 net.cpp:267] TEST Top shape for layer 96 'conv5_6/dw' 8 256 8 16 (262144)
-I0510 14:48:30.297017  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.297030  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297049  5307 net.cpp:200] Created Layer conv5_6/dw/bn (97)
-I0510 14:48:30.297062  5307 net.cpp:572] conv5_6/dw/bn <- conv5_6/dw
-I0510 14:48:30.297076  5307 net.cpp:527] conv5_6/dw/bn -> conv5_6/dw (in-place)
-I0510 14:48:30.297441  5307 net.cpp:260] Setting up conv5_6/dw/bn
-I0510 14:48:30.297461  5307 net.cpp:267] TEST Top shape for layer 97 'conv5_6/dw/bn' 8 256 8 16 (262144)
-I0510 14:48:30.297479  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Scale'
-I0510 14:48:30.297493  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297510  5307 net.cpp:200] Created Layer conv5_6/dw/scale (98)
-I0510 14:48:30.297524  5307 net.cpp:572] conv5_6/dw/scale <- conv5_6/dw
-I0510 14:48:30.297538  5307 net.cpp:527] conv5_6/dw/scale -> conv5_6/dw (in-place)
-I0510 14:48:30.297588  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Bias'
-I0510 14:48:30.297605  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297725  5307 net.cpp:260] Setting up conv5_6/dw/scale
-I0510 14:48:30.297744  5307 net.cpp:267] TEST Top shape for layer 98 'conv5_6/dw/scale' 8 256 8 16 (262144)
-I0510 14:48:30.297760  5307 layer_factory.hpp:172] Creating layer 'relu5_6/dw' of type 'ReLU'
-I0510 14:48:30.297775  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297789  5307 net.cpp:200] Created Layer relu5_6/dw (99)
-I0510 14:48:30.297802  5307 net.cpp:572] relu5_6/dw <- conv5_6/dw
-I0510 14:48:30.297816  5307 net.cpp:527] relu5_6/dw -> conv5_6/dw (in-place)
-I0510 14:48:30.297832  5307 net.cpp:260] Setting up relu5_6/dw
-I0510 14:48:30.297839  5307 net.cpp:267] TEST Top shape for layer 99 'relu5_6/dw' 8 256 8 16 (262144)
-I0510 14:48:30.297843  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep' of type 'Convolution'
-I0510 14:48:30.297848  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297857  5307 net.cpp:200] Created Layer conv5_6/sep (100)
-I0510 14:48:30.297860  5307 net.cpp:572] conv5_6/sep <- conv5_6/dw
-I0510 14:48:30.297864  5307 net.cpp:542] conv5_6/sep -> conv5_6/sep
-I0510 14:48:30.301995  5307 net.cpp:260] Setting up conv5_6/sep
-I0510 14:48:30.302006  5307 net.cpp:267] TEST Top shape for layer 100 'conv5_6/sep' 8 512 8 16 (524288)
-I0510 14:48:30.302012  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.302016  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302022  5307 net.cpp:200] Created Layer conv5_6/sep/bn (101)
-I0510 14:48:30.302027  5307 net.cpp:572] conv5_6/sep/bn <- conv5_6/sep
-I0510 14:48:30.302031  5307 net.cpp:527] conv5_6/sep/bn -> conv5_6/sep (in-place)
-I0510 14:48:30.302390  5307 net.cpp:260] Setting up conv5_6/sep/bn
-I0510 14:48:30.302413  5307 net.cpp:267] TEST Top shape for layer 101 'conv5_6/sep/bn' 8 512 8 16 (524288)
-I0510 14:48:30.302433  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Scale'
-I0510 14:48:30.302446  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302469  5307 net.cpp:200] Created Layer conv5_6/sep/scale (102)
-I0510 14:48:30.302484  5307 net.cpp:572] conv5_6/sep/scale <- conv5_6/sep
-I0510 14:48:30.302505  5307 net.cpp:527] conv5_6/sep/scale -> conv5_6/sep (in-place)
-I0510 14:48:30.302554  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Bias'
-I0510 14:48:30.302570  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302696  5307 net.cpp:260] Setting up conv5_6/sep/scale
-I0510 14:48:30.302714  5307 net.cpp:267] TEST Top shape for layer 102 'conv5_6/sep/scale' 8 512 8 16 (524288)
-I0510 14:48:30.302731  5307 layer_factory.hpp:172] Creating layer 'relu5_6/sep' of type 'ReLU'
-I0510 14:48:30.302743  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302758  5307 net.cpp:200] Created Layer relu5_6/sep (103)
-I0510 14:48:30.302772  5307 net.cpp:572] relu5_6/sep <- conv5_6/sep
-I0510 14:48:30.302784  5307 net.cpp:527] relu5_6/sep -> conv5_6/sep (in-place)
-I0510 14:48:30.302799  5307 net.cpp:260] Setting up relu5_6/sep
-I0510 14:48:30.302814  5307 net.cpp:267] TEST Top shape for layer 103 'relu5_6/sep' 8 512 8 16 (524288)
-I0510 14:48:30.302826  5307 layer_factory.hpp:172] Creating layer 'conv6/dw' of type 'Convolution'
-I0510 14:48:30.302839  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302856  5307 net.cpp:200] Created Layer conv6/dw (104)
-I0510 14:48:30.302870  5307 net.cpp:572] conv6/dw <- conv5_6/sep
-I0510 14:48:30.302882  5307 net.cpp:542] conv6/dw -> conv6/dw
-I0510 14:48:30.303230  5307 net.cpp:260] Setting up conv6/dw
-I0510 14:48:30.303238  5307 net.cpp:267] TEST Top shape for layer 104 'conv6/dw' 8 512 8 16 (524288)
-I0510 14:48:30.303262  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.303278  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.303295  5307 net.cpp:200] Created Layer conv6/dw/bn (105)
-I0510 14:48:30.303308  5307 net.cpp:572] conv6/dw/bn <- conv6/dw
-I0510 14:48:30.303320  5307 net.cpp:527] conv6/dw/bn -> conv6/dw (in-place)
-I0510 14:48:30.303689  5307 net.cpp:260] Setting up conv6/dw/bn
-I0510 14:48:30.303696  5307 net.cpp:267] TEST Top shape for layer 105 'conv6/dw/bn' 8 512 8 16 (524288)
-I0510 14:48:30.303721  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Scale'
-I0510 14:48:30.303735  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.303750  5307 net.cpp:200] Created Layer conv6/dw/scale (106)
-I0510 14:48:30.303763  5307 net.cpp:572] conv6/dw/scale <- conv6/dw
-I0510 14:48:30.303776  5307 net.cpp:527] conv6/dw/scale -> conv6/dw (in-place)
-I0510 14:48:30.303827  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Bias'
-I0510 14:48:30.303833  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.303958  5307 net.cpp:260] Setting up conv6/dw/scale
-I0510 14:48:30.303972  5307 net.cpp:267] TEST Top shape for layer 106 'conv6/dw/scale' 8 512 8 16 (524288)
-I0510 14:48:30.303988  5307 layer_factory.hpp:172] Creating layer 'relu6/dw' of type 'ReLU'
-I0510 14:48:30.304003  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.304016  5307 net.cpp:200] Created Layer relu6/dw (107)
-I0510 14:48:30.304029  5307 net.cpp:572] relu6/dw <- conv6/dw
-I0510 14:48:30.304041  5307 net.cpp:527] relu6/dw -> conv6/dw (in-place)
-I0510 14:48:30.304055  5307 net.cpp:260] Setting up relu6/dw
-I0510 14:48:30.304069  5307 net.cpp:267] TEST Top shape for layer 107 'relu6/dw' 8 512 8 16 (524288)
-I0510 14:48:30.304082  5307 layer_factory.hpp:172] Creating layer 'conv6/sep' of type 'Convolution'
-I0510 14:48:30.304095  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.304113  5307 net.cpp:200] Created Layer conv6/sep (108)
-I0510 14:48:30.304129  5307 net.cpp:572] conv6/sep <- conv6/dw
-I0510 14:48:30.304143  5307 net.cpp:542] conv6/sep -> conv6/sep
-I0510 14:48:30.314024  5307 net.cpp:260] Setting up conv6/sep
-I0510 14:48:30.314102  5307 net.cpp:267] TEST Top shape for layer 108 'conv6/sep' 8 512 8 16 (524288)
-I0510 14:48:30.314126  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.314141  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.314159  5307 net.cpp:200] Created Layer conv6/sep/bn (109)
-I0510 14:48:30.314174  5307 net.cpp:572] conv6/sep/bn <- conv6/sep
-I0510 14:48:30.314188  5307 net.cpp:527] conv6/sep/bn -> conv6/sep (in-place)
-I0510 14:48:30.314595  5307 net.cpp:260] Setting up conv6/sep/bn
-I0510 14:48:30.314612  5307 net.cpp:267] TEST Top shape for layer 109 'conv6/sep/bn' 8 512 8 16 (524288)
-I0510 14:48:30.314628  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Scale'
-I0510 14:48:30.314641  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.314657  5307 net.cpp:200] Created Layer conv6/sep/scale (110)
-I0510 14:48:30.314668  5307 net.cpp:572] conv6/sep/scale <- conv6/sep
-I0510 14:48:30.314680  5307 net.cpp:527] conv6/sep/scale -> conv6/sep (in-place)
-I0510 14:48:30.314728  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Bias'
-I0510 14:48:30.314743  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.314865  5307 net.cpp:260] Setting up conv6/sep/scale
-I0510 14:48:30.314882  5307 net.cpp:267] TEST Top shape for layer 110 'conv6/sep/scale' 8 512 8 16 (524288)
-I0510 14:48:30.314896  5307 layer_factory.hpp:172] Creating layer 'relu6/sep' of type 'ReLU'
-I0510 14:48:30.314914  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.314929  5307 net.cpp:200] Created Layer relu6/sep (111)
-I0510 14:48:30.314939  5307 net.cpp:572] relu6/sep <- conv6/sep
-I0510 14:48:30.314950  5307 net.cpp:527] relu6/sep -> conv6/sep (in-place)
-I0510 14:48:30.314965  5307 net.cpp:260] Setting up relu6/sep
-I0510 14:48:30.314977  5307 net.cpp:267] TEST Top shape for layer 111 'relu6/sep' 8 512 8 16 (524288)
-I0510 14:48:30.314988  5307 layer_factory.hpp:172] Creating layer 'conv6/sep_relu6/sep_0_split' of type 'Split'
-I0510 14:48:30.315001  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315013  5307 net.cpp:200] Created Layer conv6/sep_relu6/sep_0_split (112)
-I0510 14:48:30.315024  5307 net.cpp:572] conv6/sep_relu6/sep_0_split <- conv6/sep
-I0510 14:48:30.315035  5307 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_0
-I0510 14:48:30.315048  5307 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_1
-I0510 14:48:30.315089  5307 net.cpp:260] Setting up conv6/sep_relu6/sep_0_split
-I0510 14:48:30.315105  5307 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.315117  5307 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.315129  5307 layer_factory.hpp:172] Creating layer 'pool6' of type 'Pooling'
-I0510 14:48:30.315140  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315155  5307 net.cpp:200] Created Layer pool6 (113)
-I0510 14:48:30.315165  5307 net.cpp:572] pool6 <- conv6/sep_relu6/sep_0_split_0
-I0510 14:48:30.315177  5307 net.cpp:542] pool6 -> pool6
-I0510 14:48:30.315233  5307 net.cpp:260] Setting up pool6
-I0510 14:48:30.315248  5307 net.cpp:267] TEST Top shape for layer 113 'pool6' 8 512 5 9 (184320)
-I0510 14:48:30.315259  5307 layer_factory.hpp:172] Creating layer 'pool6_pool6_0_split' of type 'Split'
-I0510 14:48:30.315271  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315284  5307 net.cpp:200] Created Layer pool6_pool6_0_split (114)
-I0510 14:48:30.315300  5307 net.cpp:572] pool6_pool6_0_split <- pool6
-I0510 14:48:30.315312  5307 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_0
-I0510 14:48:30.315332  5307 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_1
-I0510 14:48:30.315374  5307 net.cpp:260] Setting up pool6_pool6_0_split
-I0510 14:48:30.315388  5307 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.315400  5307 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.315412  5307 layer_factory.hpp:172] Creating layer 'pool7' of type 'Pooling'
-I0510 14:48:30.315423  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315435  5307 net.cpp:200] Created Layer pool7 (115)
-I0510 14:48:30.315448  5307 net.cpp:572] pool7 <- pool6_pool6_0_split_0
-I0510 14:48:30.315459  5307 net.cpp:542] pool7 -> pool7
-I0510 14:48:30.315513  5307 net.cpp:260] Setting up pool7
-I0510 14:48:30.315528  5307 net.cpp:267] TEST Top shape for layer 115 'pool7' 8 512 3 5 (61440)
-I0510 14:48:30.315539  5307 layer_factory.hpp:172] Creating layer 'pool7_pool7_0_split' of type 'Split'
-I0510 14:48:30.315551  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315563  5307 net.cpp:200] Created Layer pool7_pool7_0_split (116)
-I0510 14:48:30.315574  5307 net.cpp:572] pool7_pool7_0_split <- pool7
-I0510 14:48:30.315585  5307 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_0
-I0510 14:48:30.315598  5307 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_1
-I0510 14:48:30.315639  5307 net.cpp:260] Setting up pool7_pool7_0_split
-I0510 14:48:30.315654  5307 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.315670  5307 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.315681  5307 layer_factory.hpp:172] Creating layer 'pool8' of type 'Pooling'
-I0510 14:48:30.315692  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315706  5307 net.cpp:200] Created Layer pool8 (117)
-I0510 14:48:30.315717  5307 net.cpp:572] pool8 <- pool7_pool7_0_split_0
-I0510 14:48:30.315729  5307 net.cpp:542] pool8 -> pool8
-I0510 14:48:30.315781  5307 net.cpp:260] Setting up pool8
-I0510 14:48:30.315796  5307 net.cpp:267] TEST Top shape for layer 117 'pool8' 8 512 3 5 (61440)
-I0510 14:48:30.315809  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1' of type 'Convolution'
-I0510 14:48:30.315819  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315837  5307 net.cpp:200] Created Layer ctx_output1/1x1 (118)
-I0510 14:48:30.315850  5307 net.cpp:572] ctx_output1/1x1 <- conv5_5/sep_relu5_5/sep_0_split_1
-I0510 14:48:30.315862  5307 net.cpp:542] ctx_output1/1x1 -> ctx_output1/1x1
-I0510 14:48:30.319830  5307 net.cpp:260] Setting up ctx_output1/1x1
-I0510 14:48:30.319865  5307 net.cpp:267] TEST Top shape for layer 118 'ctx_output1/1x1' 8 512 16 32 (2097152)
-I0510 14:48:30.319883  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.319895  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.319916  5307 net.cpp:200] Created Layer ctx_output1/1x1/bn (119)
-I0510 14:48:30.319929  5307 net.cpp:572] ctx_output1/1x1/bn <- ctx_output1/1x1
-I0510 14:48:30.319944  5307 net.cpp:527] ctx_output1/1x1/bn -> ctx_output1/1x1 (in-place)
-I0510 14:48:30.320313  5307 net.cpp:260] Setting up ctx_output1/1x1/bn
-I0510 14:48:30.320389  5307 net.cpp:267] TEST Top shape for layer 119 'ctx_output1/1x1/bn' 8 512 16 32 (2097152)
-I0510 14:48:30.320462  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/relu' of type 'ReLU'
-I0510 14:48:30.320534  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.320606  5307 net.cpp:200] Created Layer ctx_output1/1x1/relu (120)
-I0510 14:48:30.320670  5307 net.cpp:572] ctx_output1/1x1/relu <- ctx_output1/1x1
-I0510 14:48:30.320737  5307 net.cpp:527] ctx_output1/1x1/relu -> ctx_output1/1x1 (in-place)
-I0510 14:48:30.320801  5307 net.cpp:260] Setting up ctx_output1/1x1/relu
-I0510 14:48:30.320860  5307 net.cpp:267] TEST Top shape for layer 120 'ctx_output1/1x1/relu' 8 512 16 32 (2097152)
-I0510 14:48:30.320928  5307 layer_factory.hpp:172] Creating layer 'ctx_output1' of type 'Convolution'
-I0510 14:48:30.320991  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.321064  5307 net.cpp:200] Created Layer ctx_output1 (121)
-I0510 14:48:30.321121  5307 net.cpp:572] ctx_output1 <- ctx_output1/1x1
-I0510 14:48:30.321177  5307 net.cpp:542] ctx_output1 -> ctx_output1
-I0510 14:48:30.321615  5307 net.cpp:260] Setting up ctx_output1
-I0510 14:48:30.321679  5307 net.cpp:267] TEST Top shape for layer 121 'ctx_output1' 8 512 16 32 (2097152)
-I0510 14:48:30.321748  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/bn' of type 'BatchNorm'
-I0510 14:48:30.321811  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.321873  5307 net.cpp:200] Created Layer ctx_output1/bn (122)
-I0510 14:48:30.321925  5307 net.cpp:572] ctx_output1/bn <- ctx_output1
-I0510 14:48:30.321975  5307 net.cpp:527] ctx_output1/bn -> ctx_output1 (in-place)
-I0510 14:48:30.322360  5307 net.cpp:260] Setting up ctx_output1/bn
-I0510 14:48:30.322424  5307 net.cpp:267] TEST Top shape for layer 122 'ctx_output1/bn' 8 512 16 32 (2097152)
-I0510 14:48:30.322499  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu' of type 'ReLU'
-I0510 14:48:30.322566  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.322643  5307 net.cpp:200] Created Layer ctx_output1/relu (123)
-I0510 14:48:30.322703  5307 net.cpp:572] ctx_output1/relu <- ctx_output1
-I0510 14:48:30.322757  5307 net.cpp:527] ctx_output1/relu -> ctx_output1 (in-place)
-I0510 14:48:30.322819  5307 net.cpp:260] Setting up ctx_output1/relu
-I0510 14:48:30.322877  5307 net.cpp:267] TEST Top shape for layer 123 'ctx_output1/relu' 8 512 16 32 (2097152)
-I0510 14:48:30.322943  5307 layer_factory.hpp:172] Creating layer 'ctx_output1_ctx_output1/relu_0_split' of type 'Split'
-I0510 14:48:30.323010  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.323079  5307 net.cpp:200] Created Layer ctx_output1_ctx_output1/relu_0_split (124)
-I0510 14:48:30.323150  5307 net.cpp:572] ctx_output1_ctx_output1/relu_0_split <- ctx_output1
-I0510 14:48:30.323212  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_0
-I0510 14:48:30.323287  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_1
-I0510 14:48:30.323357  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_2
-I0510 14:48:30.323474  5307 net.cpp:260] Setting up ctx_output1_ctx_output1/relu_0_split
-I0510 14:48:30.323539  5307 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 8 512 16 32 (2097152)
-I0510 14:48:30.323612  5307 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 8 512 16 32 (2097152)
-I0510 14:48:30.323689  5307 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 8 512 16 32 (2097152)
-I0510 14:48:30.323763  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1' of type 'Convolution'
-I0510 14:48:30.323829  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.323902  5307 net.cpp:200] Created Layer ctx_output2/1x1 (125)
-I0510 14:48:30.323961  5307 net.cpp:572] ctx_output2/1x1 <- conv6/sep_relu6/sep_0_split_1
-I0510 14:48:30.324023  5307 net.cpp:542] ctx_output2/1x1 -> ctx_output2/1x1
-I0510 14:48:30.333039  5307 net.cpp:260] Setting up ctx_output2/1x1
-I0510 14:48:30.333173  5307 net.cpp:267] TEST Top shape for layer 125 'ctx_output2/1x1' 8 512 8 16 (524288)
-I0510 14:48:30.333248  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.333317  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.333382  5307 net.cpp:200] Created Layer ctx_output2/1x1/bn (126)
-I0510 14:48:30.333403  5307 net.cpp:572] ctx_output2/1x1/bn <- ctx_output2/1x1
-I0510 14:48:30.333421  5307 net.cpp:527] ctx_output2/1x1/bn -> ctx_output2/1x1 (in-place)
-I0510 14:48:30.333811  5307 net.cpp:260] Setting up ctx_output2/1x1/bn
-I0510 14:48:30.333820  5307 net.cpp:267] TEST Top shape for layer 126 'ctx_output2/1x1/bn' 8 512 8 16 (524288)
-I0510 14:48:30.333829  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/relu' of type 'ReLU'
-I0510 14:48:30.333834  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.333840  5307 net.cpp:200] Created Layer ctx_output2/1x1/relu (127)
-I0510 14:48:30.333844  5307 net.cpp:572] ctx_output2/1x1/relu <- ctx_output2/1x1
-I0510 14:48:30.333875  5307 net.cpp:527] ctx_output2/1x1/relu -> ctx_output2/1x1 (in-place)
-I0510 14:48:30.333899  5307 net.cpp:260] Setting up ctx_output2/1x1/relu
-I0510 14:48:30.333911  5307 net.cpp:267] TEST Top shape for layer 127 'ctx_output2/1x1/relu' 8 512 8 16 (524288)
-I0510 14:48:30.333925  5307 layer_factory.hpp:172] Creating layer 'ctx_output2' of type 'Convolution'
-I0510 14:48:30.333938  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.333961  5307 net.cpp:200] Created Layer ctx_output2 (128)
-I0510 14:48:30.333966  5307 net.cpp:572] ctx_output2 <- ctx_output2/1x1
-I0510 14:48:30.333986  5307 net.cpp:542] ctx_output2 -> ctx_output2
-I0510 14:48:30.334405  5307 net.cpp:260] Setting up ctx_output2
-I0510 14:48:30.334429  5307 net.cpp:267] TEST Top shape for layer 128 'ctx_output2' 8 512 8 16 (524288)
-I0510 14:48:30.334444  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/bn' of type 'BatchNorm'
-I0510 14:48:30.334450  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.334468  5307 net.cpp:200] Created Layer ctx_output2/bn (129)
-I0510 14:48:30.334473  5307 net.cpp:572] ctx_output2/bn <- ctx_output2
-I0510 14:48:30.334491  5307 net.cpp:527] ctx_output2/bn -> ctx_output2 (in-place)
-I0510 14:48:30.334856  5307 net.cpp:260] Setting up ctx_output2/bn
-I0510 14:48:30.334874  5307 net.cpp:267] TEST Top shape for layer 129 'ctx_output2/bn' 8 512 8 16 (524288)
-I0510 14:48:30.334892  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu' of type 'ReLU'
-I0510 14:48:30.334905  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.334919  5307 net.cpp:200] Created Layer ctx_output2/relu (130)
-I0510 14:48:30.334933  5307 net.cpp:572] ctx_output2/relu <- ctx_output2
-I0510 14:48:30.334944  5307 net.cpp:527] ctx_output2/relu -> ctx_output2 (in-place)
-I0510 14:48:30.334959  5307 net.cpp:260] Setting up ctx_output2/relu
-I0510 14:48:30.334972  5307 net.cpp:267] TEST Top shape for layer 130 'ctx_output2/relu' 8 512 8 16 (524288)
-I0510 14:48:30.334985  5307 layer_factory.hpp:172] Creating layer 'ctx_output2_ctx_output2/relu_0_split' of type 'Split'
-I0510 14:48:30.334997  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.335011  5307 net.cpp:200] Created Layer ctx_output2_ctx_output2/relu_0_split (131)
-I0510 14:48:30.335023  5307 net.cpp:572] ctx_output2_ctx_output2/relu_0_split <- ctx_output2
-I0510 14:48:30.335036  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_0
-I0510 14:48:30.335050  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_1
-I0510 14:48:30.335064  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_2
-I0510 14:48:30.335119  5307 net.cpp:260] Setting up ctx_output2_ctx_output2/relu_0_split
-I0510 14:48:30.335137  5307 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.335158  5307 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.335171  5307 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.335183  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1' of type 'Convolution'
-I0510 14:48:30.335196  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.335212  5307 net.cpp:200] Created Layer ctx_output3/1x1 (132)
-I0510 14:48:30.335225  5307 net.cpp:572] ctx_output3/1x1 <- pool6_pool6_0_split_1
-I0510 14:48:30.335238  5307 net.cpp:542] ctx_output3/1x1 -> ctx_output3/1x1
-I0510 14:48:30.343972  5307 net.cpp:260] Setting up ctx_output3/1x1
-I0510 14:48:30.344038  5307 net.cpp:267] TEST Top shape for layer 132 'ctx_output3/1x1' 8 512 5 9 (184320)
-I0510 14:48:30.344063  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.344081  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.344110  5307 net.cpp:200] Created Layer ctx_output3/1x1/bn (133)
-I0510 14:48:30.344127  5307 net.cpp:572] ctx_output3/1x1/bn <- ctx_output3/1x1
-I0510 14:48:30.344146  5307 net.cpp:527] ctx_output3/1x1/bn -> ctx_output3/1x1 (in-place)
-I0510 14:48:30.344579  5307 net.cpp:260] Setting up ctx_output3/1x1/bn
-I0510 14:48:30.344604  5307 net.cpp:267] TEST Top shape for layer 133 'ctx_output3/1x1/bn' 8 512 5 9 (184320)
-I0510 14:48:30.344625  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/relu' of type 'ReLU'
-I0510 14:48:30.344641  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.344671  5307 net.cpp:200] Created Layer ctx_output3/1x1/relu (134)
-I0510 14:48:30.344687  5307 net.cpp:572] ctx_output3/1x1/relu <- ctx_output3/1x1
-I0510 14:48:30.344702  5307 net.cpp:527] ctx_output3/1x1/relu -> ctx_output3/1x1 (in-place)
-I0510 14:48:30.344722  5307 net.cpp:260] Setting up ctx_output3/1x1/relu
-I0510 14:48:30.344739  5307 net.cpp:267] TEST Top shape for layer 134 'ctx_output3/1x1/relu' 8 512 5 9 (184320)
-I0510 14:48:30.344755  5307 layer_factory.hpp:172] Creating layer 'ctx_output3' of type 'Convolution'
-I0510 14:48:30.344771  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.344795  5307 net.cpp:200] Created Layer ctx_output3 (135)
-I0510 14:48:30.344811  5307 net.cpp:572] ctx_output3 <- ctx_output3/1x1
-I0510 14:48:30.344826  5307 net.cpp:542] ctx_output3 -> ctx_output3
-I0510 14:48:30.345271  5307 net.cpp:260] Setting up ctx_output3
-I0510 14:48:30.345295  5307 net.cpp:267] TEST Top shape for layer 135 'ctx_output3' 8 512 5 9 (184320)
-I0510 14:48:30.345315  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/bn' of type 'BatchNorm'
-I0510 14:48:30.345333  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.345353  5307 net.cpp:200] Created Layer ctx_output3/bn (136)
-I0510 14:48:30.345371  5307 net.cpp:572] ctx_output3/bn <- ctx_output3
-I0510 14:48:30.345386  5307 net.cpp:527] ctx_output3/bn -> ctx_output3 (in-place)
-I0510 14:48:30.345791  5307 net.cpp:260] Setting up ctx_output3/bn
-I0510 14:48:30.345813  5307 net.cpp:267] TEST Top shape for layer 136 'ctx_output3/bn' 8 512 5 9 (184320)
-I0510 14:48:30.345834  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu' of type 'ReLU'
-I0510 14:48:30.345852  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.345870  5307 net.cpp:200] Created Layer ctx_output3/relu (137)
-I0510 14:48:30.345885  5307 net.cpp:572] ctx_output3/relu <- ctx_output3
-I0510 14:48:30.345902  5307 net.cpp:527] ctx_output3/relu -> ctx_output3 (in-place)
-I0510 14:48:30.345921  5307 net.cpp:260] Setting up ctx_output3/relu
-I0510 14:48:30.345937  5307 net.cpp:267] TEST Top shape for layer 137 'ctx_output3/relu' 8 512 5 9 (184320)
-I0510 14:48:30.345960  5307 layer_factory.hpp:172] Creating layer 'ctx_output3_ctx_output3/relu_0_split' of type 'Split'
-I0510 14:48:30.345985  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.346002  5307 net.cpp:200] Created Layer ctx_output3_ctx_output3/relu_0_split (138)
-I0510 14:48:30.346017  5307 net.cpp:572] ctx_output3_ctx_output3/relu_0_split <- ctx_output3
-I0510 14:48:30.346036  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_0
-I0510 14:48:30.346053  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_1
-I0510 14:48:30.346071  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_2
-I0510 14:48:30.346129  5307 net.cpp:260] Setting up ctx_output3_ctx_output3/relu_0_split
-I0510 14:48:30.346148  5307 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.346166  5307 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.346181  5307 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.346196  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1' of type 'Convolution'
-I0510 14:48:30.346211  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.346231  5307 net.cpp:200] Created Layer ctx_output4/1x1 (139)
-I0510 14:48:30.346248  5307 net.cpp:572] ctx_output4/1x1 <- pool7_pool7_0_split_1
-I0510 14:48:30.346264  5307 net.cpp:542] ctx_output4/1x1 -> ctx_output4/1x1
-I0510 14:48:30.355239  5307 net.cpp:260] Setting up ctx_output4/1x1
-I0510 14:48:30.355317  5307 net.cpp:267] TEST Top shape for layer 139 'ctx_output4/1x1' 8 512 3 5 (61440)
-I0510 14:48:30.355342  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.355360  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.355389  5307 net.cpp:200] Created Layer ctx_output4/1x1/bn (140)
-I0510 14:48:30.355408  5307 net.cpp:572] ctx_output4/1x1/bn <- ctx_output4/1x1
-I0510 14:48:30.355425  5307 net.cpp:527] ctx_output4/1x1/bn -> ctx_output4/1x1 (in-place)
-I0510 14:48:30.355901  5307 net.cpp:260] Setting up ctx_output4/1x1/bn
-I0510 14:48:30.355921  5307 net.cpp:267] TEST Top shape for layer 140 'ctx_output4/1x1/bn' 8 512 3 5 (61440)
-I0510 14:48:30.355939  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/relu' of type 'ReLU'
-I0510 14:48:30.355952  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.355965  5307 net.cpp:200] Created Layer ctx_output4/1x1/relu (141)
-I0510 14:48:30.355976  5307 net.cpp:572] ctx_output4/1x1/relu <- ctx_output4/1x1
-I0510 14:48:30.355988  5307 net.cpp:527] ctx_output4/1x1/relu -> ctx_output4/1x1 (in-place)
-I0510 14:48:30.356003  5307 net.cpp:260] Setting up ctx_output4/1x1/relu
-I0510 14:48:30.356014  5307 net.cpp:267] TEST Top shape for layer 141 'ctx_output4/1x1/relu' 8 512 3 5 (61440)
-I0510 14:48:30.356026  5307 layer_factory.hpp:172] Creating layer 'ctx_output4' of type 'Convolution'
-I0510 14:48:30.356039  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.356055  5307 net.cpp:200] Created Layer ctx_output4 (142)
-I0510 14:48:30.356066  5307 net.cpp:572] ctx_output4 <- ctx_output4/1x1
-I0510 14:48:30.356077  5307 net.cpp:542] ctx_output4 -> ctx_output4
-I0510 14:48:30.356488  5307 net.cpp:260] Setting up ctx_output4
-I0510 14:48:30.356510  5307 net.cpp:267] TEST Top shape for layer 142 'ctx_output4' 8 512 3 5 (61440)
-I0510 14:48:30.356542  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/bn' of type 'BatchNorm'
-I0510 14:48:30.356559  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.356581  5307 net.cpp:200] Created Layer ctx_output4/bn (143)
-I0510 14:48:30.356603  5307 net.cpp:572] ctx_output4/bn <- ctx_output4
-I0510 14:48:30.356616  5307 net.cpp:527] ctx_output4/bn -> ctx_output4 (in-place)
-I0510 14:48:30.356990  5307 net.cpp:260] Setting up ctx_output4/bn
-I0510 14:48:30.357010  5307 net.cpp:267] TEST Top shape for layer 143 'ctx_output4/bn' 8 512 3 5 (61440)
-I0510 14:48:30.357029  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu' of type 'ReLU'
-I0510 14:48:30.357046  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.357069  5307 net.cpp:200] Created Layer ctx_output4/relu (144)
-I0510 14:48:30.357084  5307 net.cpp:572] ctx_output4/relu <- ctx_output4
-I0510 14:48:30.357100  5307 net.cpp:527] ctx_output4/relu -> ctx_output4 (in-place)
-I0510 14:48:30.357116  5307 net.cpp:260] Setting up ctx_output4/relu
-I0510 14:48:30.357132  5307 net.cpp:267] TEST Top shape for layer 144 'ctx_output4/relu' 8 512 3 5 (61440)
-I0510 14:48:30.357147  5307 layer_factory.hpp:172] Creating layer 'ctx_output4_ctx_output4/relu_0_split' of type 'Split'
-I0510 14:48:30.357162  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.357178  5307 net.cpp:200] Created Layer ctx_output4_ctx_output4/relu_0_split (145)
-I0510 14:48:30.357193  5307 net.cpp:572] ctx_output4_ctx_output4/relu_0_split <- ctx_output4
-I0510 14:48:30.357208  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_0
-I0510 14:48:30.357230  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_1
-I0510 14:48:30.357247  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_2
-I0510 14:48:30.357311  5307 net.cpp:260] Setting up ctx_output4_ctx_output4/relu_0_split
-I0510 14:48:30.357331  5307 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.357347  5307 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.357362  5307 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.357376  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1' of type 'Convolution'
-I0510 14:48:30.357389  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.357409  5307 net.cpp:200] Created Layer ctx_output5/1x1 (146)
-I0510 14:48:30.357424  5307 net.cpp:572] ctx_output5/1x1 <- pool8
-I0510 14:48:30.357439  5307 net.cpp:542] ctx_output5/1x1 -> ctx_output5/1x1
-I0510 14:48:30.365607  5307 net.cpp:260] Setting up ctx_output5/1x1
-I0510 14:48:30.365667  5307 net.cpp:267] TEST Top shape for layer 146 'ctx_output5/1x1' 8 512 3 5 (61440)
-I0510 14:48:30.365686  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.365700  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.365716  5307 net.cpp:200] Created Layer ctx_output5/1x1/bn (147)
-I0510 14:48:30.365731  5307 net.cpp:572] ctx_output5/1x1/bn <- ctx_output5/1x1
-I0510 14:48:30.365743  5307 net.cpp:527] ctx_output5/1x1/bn -> ctx_output5/1x1 (in-place)
-I0510 14:48:30.366083  5307 net.cpp:260] Setting up ctx_output5/1x1/bn
-I0510 14:48:30.366092  5307 net.cpp:267] TEST Top shape for layer 147 'ctx_output5/1x1/bn' 8 512 3 5 (61440)
-I0510 14:48:30.366101  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/relu' of type 'ReLU'
-I0510 14:48:30.366104  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.366109  5307 net.cpp:200] Created Layer ctx_output5/1x1/relu (148)
-I0510 14:48:30.366113  5307 net.cpp:572] ctx_output5/1x1/relu <- ctx_output5/1x1
-I0510 14:48:30.366117  5307 net.cpp:527] ctx_output5/1x1/relu -> ctx_output5/1x1 (in-place)
-I0510 14:48:30.366137  5307 net.cpp:260] Setting up ctx_output5/1x1/relu
-I0510 14:48:30.366158  5307 net.cpp:267] TEST Top shape for layer 148 'ctx_output5/1x1/relu' 8 512 3 5 (61440)
-I0510 14:48:30.366180  5307 layer_factory.hpp:172] Creating layer 'ctx_output5' of type 'Convolution'
-I0510 14:48:30.366194  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.366211  5307 net.cpp:200] Created Layer ctx_output5 (149)
-I0510 14:48:30.366223  5307 net.cpp:572] ctx_output5 <- ctx_output5/1x1
-I0510 14:48:30.366236  5307 net.cpp:542] ctx_output5 -> ctx_output5
-I0510 14:48:30.366629  5307 net.cpp:260] Setting up ctx_output5
-I0510 14:48:30.366637  5307 net.cpp:267] TEST Top shape for layer 149 'ctx_output5' 8 512 3 5 (61440)
-I0510 14:48:30.366662  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/bn' of type 'BatchNorm'
-I0510 14:48:30.366677  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.366693  5307 net.cpp:200] Created Layer ctx_output5/bn (150)
-I0510 14:48:30.366706  5307 net.cpp:572] ctx_output5/bn <- ctx_output5
-I0510 14:48:30.366720  5307 net.cpp:527] ctx_output5/bn -> ctx_output5 (in-place)
-I0510 14:48:30.367090  5307 net.cpp:260] Setting up ctx_output5/bn
-I0510 14:48:30.367097  5307 net.cpp:267] TEST Top shape for layer 150 'ctx_output5/bn' 8 512 3 5 (61440)
-I0510 14:48:30.367121  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu' of type 'ReLU'
-I0510 14:48:30.367133  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.367146  5307 net.cpp:200] Created Layer ctx_output5/relu (151)
-I0510 14:48:30.367158  5307 net.cpp:572] ctx_output5/relu <- ctx_output5
-I0510 14:48:30.367171  5307 net.cpp:527] ctx_output5/relu -> ctx_output5 (in-place)
-I0510 14:48:30.367187  5307 net.cpp:260] Setting up ctx_output5/relu
-I0510 14:48:30.367200  5307 net.cpp:267] TEST Top shape for layer 151 'ctx_output5/relu' 8 512 3 5 (61440)
-I0510 14:48:30.367213  5307 layer_factory.hpp:172] Creating layer 'ctx_output5_ctx_output5/relu_0_split' of type 'Split'
-I0510 14:48:30.367224  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.367238  5307 net.cpp:200] Created Layer ctx_output5_ctx_output5/relu_0_split (152)
-I0510 14:48:30.367249  5307 net.cpp:572] ctx_output5_ctx_output5/relu_0_split <- ctx_output5
-I0510 14:48:30.367261  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_0
-I0510 14:48:30.367274  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_1
-I0510 14:48:30.367288  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_2
-I0510 14:48:30.367344  5307 net.cpp:260] Setting up ctx_output5_ctx_output5/relu_0_split
-I0510 14:48:30.367359  5307 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.367372  5307 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.367385  5307 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.367398  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.367411  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.367432  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc (153)
-I0510 14:48:30.367446  5307 net.cpp:572] ctx_output1/relu_mbox_loc <- ctx_output1_ctx_output1/relu_0_split_0
-I0510 14:48:30.367461  5307 net.cpp:542] ctx_output1/relu_mbox_loc -> ctx_output1/relu_mbox_loc
-I0510 14:48:30.367933  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc
-I0510 14:48:30.367951  5307 net.cpp:267] TEST Top shape for layer 153 'ctx_output1/relu_mbox_loc' 8 16 16 32 (65536)
-I0510 14:48:30.367966  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.367979  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.368005  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_perm (154)
-I0510 14:48:30.368018  5307 net.cpp:572] ctx_output1/relu_mbox_loc_perm <- ctx_output1/relu_mbox_loc
-I0510 14:48:30.368031  5307 net.cpp:542] ctx_output1/relu_mbox_loc_perm -> ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.368134  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.368149  5307 net.cpp:267] TEST Top shape for layer 154 'ctx_output1/relu_mbox_loc_perm' 8 16 32 16 (65536)
-I0510 14:48:30.368162  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.368175  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.368188  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_flat (155)
-I0510 14:48:30.368201  5307 net.cpp:572] ctx_output1/relu_mbox_loc_flat <- ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.368214  5307 net.cpp:542] ctx_output1/relu_mbox_loc_flat -> ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.368324  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.368340  5307 net.cpp:267] TEST Top shape for layer 155 'ctx_output1/relu_mbox_loc_flat' 8 8192 (65536)
-I0510 14:48:30.368352  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.368366  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.368384  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf (156)
-I0510 14:48:30.368396  5307 net.cpp:572] ctx_output1/relu_mbox_conf <- ctx_output1_ctx_output1/relu_0_split_1
-I0510 14:48:30.368410  5307 net.cpp:542] ctx_output1/relu_mbox_conf -> ctx_output1/relu_mbox_conf
-I0510 14:48:30.369997  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf
-I0510 14:48:30.370007  5307 net.cpp:267] TEST Top shape for layer 156 'ctx_output1/relu_mbox_conf' 8 84 16 32 (344064)
-I0510 14:48:30.370031  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.370044  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.370059  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_perm (157)
-I0510 14:48:30.370071  5307 net.cpp:572] ctx_output1/relu_mbox_conf_perm <- ctx_output1/relu_mbox_conf
-I0510 14:48:30.370085  5307 net.cpp:542] ctx_output1/relu_mbox_conf_perm -> ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.370190  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.370206  5307 net.cpp:267] TEST Top shape for layer 157 'ctx_output1/relu_mbox_conf_perm' 8 16 32 84 (344064)
-I0510 14:48:30.370219  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.370232  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.370245  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_flat (158)
-I0510 14:48:30.370257  5307 net.cpp:572] ctx_output1/relu_mbox_conf_flat <- ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.370270  5307 net.cpp:542] ctx_output1/relu_mbox_conf_flat -> ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.379266  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.379313  5307 net.cpp:267] TEST Top shape for layer 158 'ctx_output1/relu_mbox_conf_flat' 8 43008 (344064)
-I0510 14:48:30.379328  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.379344  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.379364  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_priorbox (159)
-I0510 14:48:30.379375  5307 net.cpp:572] ctx_output1/relu_mbox_priorbox <- ctx_output1_ctx_output1/relu_0_split_2
-I0510 14:48:30.379390  5307 net.cpp:572] ctx_output1/relu_mbox_priorbox <- data_data_0_split_1
-I0510 14:48:30.379401  5307 net.cpp:542] ctx_output1/relu_mbox_priorbox -> ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.379524  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.379534  5307 net.cpp:267] TEST Top shape for layer 159 'ctx_output1/relu_mbox_priorbox' 1 2 8192 (16384)
-I0510 14:48:30.379539  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.379546  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.379560  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc (160)
-I0510 14:48:30.379565  5307 net.cpp:572] ctx_output2/relu_mbox_loc <- ctx_output2_ctx_output2/relu_0_split_0
-I0510 14:48:30.379570  5307 net.cpp:542] ctx_output2/relu_mbox_loc -> ctx_output2/relu_mbox_loc
-I0510 14:48:30.380260  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc
-I0510 14:48:30.380270  5307 net.cpp:267] TEST Top shape for layer 160 'ctx_output2/relu_mbox_loc' 8 24 8 16 (24576)
-I0510 14:48:30.380276  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.380281  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.380288  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_perm (161)
-I0510 14:48:30.380293  5307 net.cpp:572] ctx_output2/relu_mbox_loc_perm <- ctx_output2/relu_mbox_loc
-I0510 14:48:30.380297  5307 net.cpp:542] ctx_output2/relu_mbox_loc_perm -> ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.380390  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.380398  5307 net.cpp:267] TEST Top shape for layer 161 'ctx_output2/relu_mbox_loc_perm' 8 8 16 24 (24576)
-I0510 14:48:30.380403  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.380406  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.380411  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_flat (162)
-I0510 14:48:30.380415  5307 net.cpp:572] ctx_output2/relu_mbox_loc_flat <- ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.380420  5307 net.cpp:542] ctx_output2/relu_mbox_loc_flat -> ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.380486  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.380492  5307 net.cpp:267] TEST Top shape for layer 162 'ctx_output2/relu_mbox_loc_flat' 8 3072 (24576)
-I0510 14:48:30.380497  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.380501  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.380509  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf (163)
-I0510 14:48:30.380513  5307 net.cpp:572] ctx_output2/relu_mbox_conf <- ctx_output2_ctx_output2/relu_0_split_1
-I0510 14:48:30.380518  5307 net.cpp:542] ctx_output2/relu_mbox_conf -> ctx_output2/relu_mbox_conf
-I0510 14:48:30.382915  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf
-I0510 14:48:30.382927  5307 net.cpp:267] TEST Top shape for layer 163 'ctx_output2/relu_mbox_conf' 8 126 8 16 (129024)
-I0510 14:48:30.382935  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.382939  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.382946  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_perm (164)
-I0510 14:48:30.382951  5307 net.cpp:572] ctx_output2/relu_mbox_conf_perm <- ctx_output2/relu_mbox_conf
-I0510 14:48:30.382954  5307 net.cpp:542] ctx_output2/relu_mbox_conf_perm -> ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.383042  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.383049  5307 net.cpp:267] TEST Top shape for layer 164 'ctx_output2/relu_mbox_conf_perm' 8 8 16 126 (129024)
-I0510 14:48:30.383052  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.383057  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.383070  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_flat (165)
-I0510 14:48:30.383074  5307 net.cpp:572] ctx_output2/relu_mbox_conf_flat <- ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.383080  5307 net.cpp:542] ctx_output2/relu_mbox_conf_flat -> ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.383201  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.383208  5307 net.cpp:267] TEST Top shape for layer 165 'ctx_output2/relu_mbox_conf_flat' 8 16128 (129024)
-I0510 14:48:30.383213  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.383216  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.383221  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_priorbox (166)
-I0510 14:48:30.383224  5307 net.cpp:572] ctx_output2/relu_mbox_priorbox <- ctx_output2_ctx_output2/relu_0_split_2
-I0510 14:48:30.383229  5307 net.cpp:572] ctx_output2/relu_mbox_priorbox <- data_data_0_split_2
-I0510 14:48:30.383234  5307 net.cpp:542] ctx_output2/relu_mbox_priorbox -> ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.383253  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.383260  5307 net.cpp:267] TEST Top shape for layer 166 'ctx_output2/relu_mbox_priorbox' 1 2 3072 (6144)
-I0510 14:48:30.383263  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.383266  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.383277  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc (167)
-I0510 14:48:30.383281  5307 net.cpp:572] ctx_output3/relu_mbox_loc <- ctx_output3_ctx_output3/relu_0_split_0
-I0510 14:48:30.383285  5307 net.cpp:542] ctx_output3/relu_mbox_loc -> ctx_output3/relu_mbox_loc
-I0510 14:48:30.383890  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc
-I0510 14:48:30.383898  5307 net.cpp:267] TEST Top shape for layer 167 'ctx_output3/relu_mbox_loc' 8 24 5 9 (8640)
-I0510 14:48:30.383905  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.383908  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.383913  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_perm (168)
-I0510 14:48:30.383918  5307 net.cpp:572] ctx_output3/relu_mbox_loc_perm <- ctx_output3/relu_mbox_loc
-I0510 14:48:30.383921  5307 net.cpp:542] ctx_output3/relu_mbox_loc_perm -> ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.384006  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.384011  5307 net.cpp:267] TEST Top shape for layer 168 'ctx_output3/relu_mbox_loc_perm' 8 5 9 24 (8640)
-I0510 14:48:30.384016  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.384018  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.384022  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_flat (169)
-I0510 14:48:30.384027  5307 net.cpp:572] ctx_output3/relu_mbox_loc_flat <- ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.384032  5307 net.cpp:542] ctx_output3/relu_mbox_loc_flat -> ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.384083  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.384089  5307 net.cpp:267] TEST Top shape for layer 169 'ctx_output3/relu_mbox_loc_flat' 8 1080 (8640)
-I0510 14:48:30.384093  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.384096  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.384102  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf (170)
-I0510 14:48:30.384106  5307 net.cpp:572] ctx_output3/relu_mbox_conf <- ctx_output3_ctx_output3/relu_0_split_1
-I0510 14:48:30.384110  5307 net.cpp:542] ctx_output3/relu_mbox_conf -> ctx_output3/relu_mbox_conf
-I0510 14:48:30.386309  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf
-I0510 14:48:30.386322  5307 net.cpp:267] TEST Top shape for layer 170 'ctx_output3/relu_mbox_conf' 8 126 5 9 (45360)
-I0510 14:48:30.386328  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.386333  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.386339  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_perm (171)
-I0510 14:48:30.386343  5307 net.cpp:572] ctx_output3/relu_mbox_conf_perm <- ctx_output3/relu_mbox_conf
-I0510 14:48:30.386348  5307 net.cpp:542] ctx_output3/relu_mbox_conf_perm -> ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.386449  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.386456  5307 net.cpp:267] TEST Top shape for layer 171 'ctx_output3/relu_mbox_conf_perm' 8 5 9 126 (45360)
-I0510 14:48:30.386461  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.386464  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.386468  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_flat (172)
-I0510 14:48:30.386472  5307 net.cpp:572] ctx_output3/relu_mbox_conf_flat <- ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.386476  5307 net.cpp:542] ctx_output3/relu_mbox_conf_flat -> ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.387451  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.387465  5307 net.cpp:267] TEST Top shape for layer 172 'ctx_output3/relu_mbox_conf_flat' 8 5670 (45360)
-I0510 14:48:30.387470  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.387476  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.387483  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_priorbox (173)
-I0510 14:48:30.387488  5307 net.cpp:572] ctx_output3/relu_mbox_priorbox <- ctx_output3_ctx_output3/relu_0_split_2
-I0510 14:48:30.387495  5307 net.cpp:572] ctx_output3/relu_mbox_priorbox <- data_data_0_split_3
-I0510 14:48:30.387501  5307 net.cpp:542] ctx_output3/relu_mbox_priorbox -> ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.387526  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.387534  5307 net.cpp:267] TEST Top shape for layer 173 'ctx_output3/relu_mbox_priorbox' 1 2 1080 (2160)
-I0510 14:48:30.387538  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.387543  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.387553  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc (174)
-I0510 14:48:30.387557  5307 net.cpp:572] ctx_output4/relu_mbox_loc <- ctx_output4_ctx_output4/relu_0_split_0
-I0510 14:48:30.387562  5307 net.cpp:542] ctx_output4/relu_mbox_loc -> ctx_output4/relu_mbox_loc
-I0510 14:48:30.388070  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc
-I0510 14:48:30.388082  5307 net.cpp:267] TEST Top shape for layer 174 'ctx_output4/relu_mbox_loc' 8 16 3 5 (1920)
-I0510 14:48:30.388089  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.388094  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.388101  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_perm (175)
-I0510 14:48:30.388108  5307 net.cpp:572] ctx_output4/relu_mbox_loc_perm <- ctx_output4/relu_mbox_loc
-I0510 14:48:30.388113  5307 net.cpp:542] ctx_output4/relu_mbox_loc_perm -> ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.388193  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.388201  5307 net.cpp:267] TEST Top shape for layer 175 'ctx_output4/relu_mbox_loc_perm' 8 3 5 16 (1920)
-I0510 14:48:30.388206  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.388226  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.388233  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_flat (176)
-I0510 14:48:30.388237  5307 net.cpp:572] ctx_output4/relu_mbox_loc_flat <- ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.388242  5307 net.cpp:542] ctx_output4/relu_mbox_loc_flat -> ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.388301  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.388309  5307 net.cpp:267] TEST Top shape for layer 176 'ctx_output4/relu_mbox_loc_flat' 8 240 (1920)
-I0510 14:48:30.388314  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.388319  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.388327  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf (177)
-I0510 14:48:30.388331  5307 net.cpp:572] ctx_output4/relu_mbox_conf <- ctx_output4_ctx_output4/relu_0_split_1
-I0510 14:48:30.388336  5307 net.cpp:542] ctx_output4/relu_mbox_conf -> ctx_output4/relu_mbox_conf
-I0510 14:48:30.389809  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf
-I0510 14:48:30.389820  5307 net.cpp:267] TEST Top shape for layer 177 'ctx_output4/relu_mbox_conf' 8 84 3 5 (10080)
-I0510 14:48:30.389827  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.389832  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.389837  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_perm (178)
-I0510 14:48:30.389842  5307 net.cpp:572] ctx_output4/relu_mbox_conf_perm <- ctx_output4/relu_mbox_conf
-I0510 14:48:30.389847  5307 net.cpp:542] ctx_output4/relu_mbox_conf_perm -> ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.389919  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.389926  5307 net.cpp:267] TEST Top shape for layer 178 'ctx_output4/relu_mbox_conf_perm' 8 3 5 84 (10080)
-I0510 14:48:30.389930  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.389935  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.389940  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_flat (179)
-I0510 14:48:30.389943  5307 net.cpp:572] ctx_output4/relu_mbox_conf_flat <- ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.389959  5307 net.cpp:542] ctx_output4/relu_mbox_conf_flat -> ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.391364  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.391393  5307 net.cpp:267] TEST Top shape for layer 179 'ctx_output4/relu_mbox_conf_flat' 8 1260 (10080)
-I0510 14:48:30.391407  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.391420  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.391439  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_priorbox (180)
-I0510 14:48:30.391455  5307 net.cpp:572] ctx_output4/relu_mbox_priorbox <- ctx_output4_ctx_output4/relu_0_split_2
-I0510 14:48:30.391474  5307 net.cpp:572] ctx_output4/relu_mbox_priorbox <- data_data_0_split_4
-I0510 14:48:30.391490  5307 net.cpp:542] ctx_output4/relu_mbox_priorbox -> ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.391535  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.391548  5307 net.cpp:267] TEST Top shape for layer 180 'ctx_output4/relu_mbox_priorbox' 1 2 240 (480)
-I0510 14:48:30.391559  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.391571  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.391589  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc (181)
-I0510 14:48:30.391605  5307 net.cpp:572] ctx_output5/relu_mbox_loc <- ctx_output5_ctx_output5/relu_0_split_0
-I0510 14:48:30.391626  5307 net.cpp:542] ctx_output5/relu_mbox_loc -> ctx_output5/relu_mbox_loc
-I0510 14:48:30.393018  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc
-I0510 14:48:30.393043  5307 net.cpp:267] TEST Top shape for layer 181 'ctx_output5/relu_mbox_loc' 8 16 3 5 (1920)
-I0510 14:48:30.393057  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.393067  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.393081  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_perm (182)
-I0510 14:48:30.393092  5307 net.cpp:572] ctx_output5/relu_mbox_loc_perm <- ctx_output5/relu_mbox_loc
-I0510 14:48:30.393103  5307 net.cpp:542] ctx_output5/relu_mbox_loc_perm -> ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.393191  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.393204  5307 net.cpp:267] TEST Top shape for layer 182 'ctx_output5/relu_mbox_loc_perm' 8 3 5 16 (1920)
-I0510 14:48:30.393214  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.393224  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.393236  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_flat (183)
-I0510 14:48:30.393246  5307 net.cpp:572] ctx_output5/relu_mbox_loc_flat <- ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.393257  5307 net.cpp:542] ctx_output5/relu_mbox_loc_flat -> ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.393319  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.393332  5307 net.cpp:267] TEST Top shape for layer 183 'ctx_output5/relu_mbox_loc_flat' 8 240 (1920)
-I0510 14:48:30.393343  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.393352  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.393366  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf (184)
-I0510 14:48:30.393378  5307 net.cpp:572] ctx_output5/relu_mbox_conf <- ctx_output5_ctx_output5/relu_0_split_1
-I0510 14:48:30.393398  5307 net.cpp:542] ctx_output5/relu_mbox_conf -> ctx_output5/relu_mbox_conf
-I0510 14:48:30.395787  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf
-I0510 14:48:30.395815  5307 net.cpp:267] TEST Top shape for layer 184 'ctx_output5/relu_mbox_conf' 8 84 3 5 (10080)
-I0510 14:48:30.395833  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.395848  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.395864  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_perm (185)
-I0510 14:48:30.395879  5307 net.cpp:572] ctx_output5/relu_mbox_conf_perm <- ctx_output5/relu_mbox_conf
-I0510 14:48:30.395893  5307 net.cpp:542] ctx_output5/relu_mbox_conf_perm -> ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.395985  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.396003  5307 net.cpp:267] TEST Top shape for layer 185 'ctx_output5/relu_mbox_conf_perm' 8 3 5 84 (10080)
-I0510 14:48:30.396016  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.396030  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396046  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_flat (186)
-I0510 14:48:30.396060  5307 net.cpp:572] ctx_output5/relu_mbox_conf_flat <- ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.396075  5307 net.cpp:542] ctx_output5/relu_mbox_conf_flat -> ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.396143  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.396162  5307 net.cpp:267] TEST Top shape for layer 186 'ctx_output5/relu_mbox_conf_flat' 8 1260 (10080)
-I0510 14:48:30.396179  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.396200  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396216  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_priorbox (187)
-I0510 14:48:30.396230  5307 net.cpp:572] ctx_output5/relu_mbox_priorbox <- ctx_output5_ctx_output5/relu_0_split_2
-I0510 14:48:30.396245  5307 net.cpp:572] ctx_output5/relu_mbox_priorbox <- data_data_0_split_5
-I0510 14:48:30.396260  5307 net.cpp:542] ctx_output5/relu_mbox_priorbox -> ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.396292  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.396317  5307 net.cpp:267] TEST Top shape for layer 187 'ctx_output5/relu_mbox_priorbox' 1 2 240 (480)
-I0510 14:48:30.396332  5307 layer_factory.hpp:172] Creating layer 'mbox_loc' of type 'Concat'
-I0510 14:48:30.396344  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396360  5307 net.cpp:200] Created Layer mbox_loc (188)
-I0510 14:48:30.396374  5307 net.cpp:572] mbox_loc <- ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.396389  5307 net.cpp:572] mbox_loc <- ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.396404  5307 net.cpp:572] mbox_loc <- ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.396417  5307 net.cpp:572] mbox_loc <- ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.396438  5307 net.cpp:572] mbox_loc <- ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.396452  5307 net.cpp:542] mbox_loc -> mbox_loc
-I0510 14:48:30.396486  5307 net.cpp:260] Setting up mbox_loc
-I0510 14:48:30.396502  5307 net.cpp:267] TEST Top shape for layer 188 'mbox_loc' 8 12824 (102592)
-I0510 14:48:30.396515  5307 layer_factory.hpp:172] Creating layer 'mbox_conf' of type 'Concat'
-I0510 14:48:30.396543  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396560  5307 net.cpp:200] Created Layer mbox_conf (189)
-I0510 14:48:30.396574  5307 net.cpp:572] mbox_conf <- ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.396589  5307 net.cpp:572] mbox_conf <- ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.396603  5307 net.cpp:572] mbox_conf <- ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.396617  5307 net.cpp:572] mbox_conf <- ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.396631  5307 net.cpp:572] mbox_conf <- ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.396648  5307 net.cpp:542] mbox_conf -> mbox_conf
-I0510 14:48:30.396682  5307 net.cpp:260] Setting up mbox_conf
-I0510 14:48:30.396697  5307 net.cpp:267] TEST Top shape for layer 189 'mbox_conf' 8 67326 (538608)
-I0510 14:48:30.396711  5307 layer_factory.hpp:172] Creating layer 'mbox_priorbox' of type 'Concat'
-I0510 14:48:30.396724  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396739  5307 net.cpp:200] Created Layer mbox_priorbox (190)
-I0510 14:48:30.396751  5307 net.cpp:572] mbox_priorbox <- ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.396765  5307 net.cpp:572] mbox_priorbox <- ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.396780  5307 net.cpp:572] mbox_priorbox <- ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.396793  5307 net.cpp:572] mbox_priorbox <- ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.396806  5307 net.cpp:572] mbox_priorbox <- ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.396821  5307 net.cpp:542] mbox_priorbox -> mbox_priorbox
-I0510 14:48:30.396848  5307 net.cpp:260] Setting up mbox_priorbox
-I0510 14:48:30.396864  5307 net.cpp:267] TEST Top shape for layer 190 'mbox_priorbox' 1 2 12824 (25648)
-I0510 14:48:30.396878  5307 layer_factory.hpp:172] Creating layer 'mbox_conf_reshape' of type 'Reshape'
-I0510 14:48:30.396891  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396908  5307 net.cpp:200] Created Layer mbox_conf_reshape (191)
-I0510 14:48:30.396921  5307 net.cpp:572] mbox_conf_reshape <- mbox_conf
-I0510 14:48:30.396935  5307 net.cpp:542] mbox_conf_reshape -> mbox_conf_reshape
-I0510 14:48:30.396970  5307 net.cpp:260] Setting up mbox_conf_reshape
-I0510 14:48:30.396992  5307 net.cpp:267] TEST Top shape for layer 191 'mbox_conf_reshape' 8 3206 21 (538608)
-I0510 14:48:30.397006  5307 layer_factory.hpp:172] Creating layer 'mbox_conf_softmax' of type 'Softmax'
-I0510 14:48:30.397020  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.397042  5307 net.cpp:200] Created Layer mbox_conf_softmax (192)
-I0510 14:48:30.397056  5307 net.cpp:572] mbox_conf_softmax <- mbox_conf_reshape
-I0510 14:48:30.397070  5307 net.cpp:542] mbox_conf_softmax -> mbox_conf_softmax
-I0510 14:48:30.397140  5307 net.cpp:260] Setting up mbox_conf_softmax
-I0510 14:48:30.397156  5307 net.cpp:267] TEST Top shape for layer 192 'mbox_conf_softmax' 8 3206 21 (538608)
-I0510 14:48:30.397169  5307 layer_factory.hpp:172] Creating layer 'mbox_conf_flatten' of type 'Flatten'
-I0510 14:48:30.397182  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.397215  5307 net.cpp:200] Created Layer mbox_conf_flatten (193)
-I0510 14:48:30.397230  5307 net.cpp:572] mbox_conf_flatten <- mbox_conf_softmax
-I0510 14:48:30.397243  5307 net.cpp:542] mbox_conf_flatten -> mbox_conf_flatten
-I0510 14:48:30.399592  5307 net.cpp:260] Setting up mbox_conf_flatten
-I0510 14:48:30.399636  5307 net.cpp:267] TEST Top shape for layer 193 'mbox_conf_flatten' 8 67326 (538608)
-I0510 14:48:30.399652  5307 layer_factory.hpp:172] Creating layer 'detection_out' of type 'DetectionOutput'
-I0510 14:48:30.399667  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.399698  5307 net.cpp:200] Created Layer detection_out (194)
-I0510 14:48:30.399714  5307 net.cpp:572] detection_out <- mbox_loc
-I0510 14:48:30.399745  5307 net.cpp:572] detection_out <- mbox_conf_flatten
-I0510 14:48:30.399768  5307 net.cpp:572] detection_out <- mbox_priorbox
-I0510 14:48:30.399790  5307 net.cpp:542] detection_out -> detection_out
-I0510 14:48:30.401743  5307 net.cpp:260] Setting up detection_out
-I0510 14:48:30.401783  5307 net.cpp:267] TEST Top shape for layer 194 'detection_out' 1 1 1 7 (7)
-I0510 14:48:30.401799  5307 layer_factory.hpp:172] Creating layer 'detection_eval' of type 'DetectionEvaluate'
-I0510 14:48:30.401813  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.401832  5307 net.cpp:200] Created Layer detection_eval (195)
-I0510 14:48:30.401847  5307 net.cpp:572] detection_eval <- detection_out
-I0510 14:48:30.401861  5307 net.cpp:572] detection_eval <- label
-I0510 14:48:30.401875  5307 net.cpp:542] detection_eval -> detection_eval
-I0510 14:48:30.403245  5307 net.cpp:260] Setting up detection_eval
-I0510 14:48:30.403267  5307 net.cpp:267] TEST Top shape for layer 195 'detection_eval' 1 1 21 5 (105)
-I0510 14:48:30.403282  5307 net.cpp:338] detection_eval does not need backward computation.
-I0510 14:48:30.403296  5307 net.cpp:338] detection_out does not need backward computation.
-I0510 14:48:30.403309  5307 net.cpp:338] mbox_conf_flatten does not need backward computation.
-I0510 14:48:30.403322  5307 net.cpp:338] mbox_conf_softmax does not need backward computation.
-I0510 14:48:30.403334  5307 net.cpp:338] mbox_conf_reshape does not need backward computation.
-I0510 14:48:30.403347  5307 net.cpp:338] mbox_priorbox does not need backward computation.
-I0510 14:48:30.403362  5307 net.cpp:338] mbox_conf does not need backward computation.
-I0510 14:48:30.403375  5307 net.cpp:338] mbox_loc does not need backward computation.
-I0510 14:48:30.403389  5307 net.cpp:338] ctx_output5/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403403  5307 net.cpp:338] ctx_output5/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403415  5307 net.cpp:338] ctx_output5/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403429  5307 net.cpp:338] ctx_output5/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403450  5307 net.cpp:338] ctx_output5/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403471  5307 net.cpp:338] ctx_output5/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403484  5307 net.cpp:338] ctx_output5/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403497  5307 net.cpp:338] ctx_output4/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403511  5307 net.cpp:338] ctx_output4/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403522  5307 net.cpp:338] ctx_output4/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403537  5307 net.cpp:338] ctx_output4/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403549  5307 net.cpp:338] ctx_output4/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403563  5307 net.cpp:338] ctx_output4/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403575  5307 net.cpp:338] ctx_output4/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403589  5307 net.cpp:338] ctx_output3/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403602  5307 net.cpp:338] ctx_output3/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403615  5307 net.cpp:338] ctx_output3/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403628  5307 net.cpp:338] ctx_output3/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403641  5307 net.cpp:338] ctx_output3/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403654  5307 net.cpp:338] ctx_output3/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403666  5307 net.cpp:338] ctx_output3/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403682  5307 net.cpp:338] ctx_output2/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403695  5307 net.cpp:338] ctx_output2/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403708  5307 net.cpp:338] ctx_output2/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403722  5307 net.cpp:338] ctx_output2/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403733  5307 net.cpp:338] ctx_output2/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403746  5307 net.cpp:338] ctx_output2/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403759  5307 net.cpp:338] ctx_output2/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403770  5307 net.cpp:338] ctx_output1/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403787  5307 net.cpp:338] ctx_output1/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403803  5307 net.cpp:338] ctx_output1/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403818  5307 net.cpp:338] ctx_output1/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403834  5307 net.cpp:338] ctx_output1/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403849  5307 net.cpp:338] ctx_output1/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403864  5307 net.cpp:338] ctx_output1/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403879  5307 net.cpp:338] ctx_output5_ctx_output5/relu_0_split does not need backward computation.
-I0510 14:48:30.403895  5307 net.cpp:338] ctx_output5/relu does not need backward computation.
-I0510 14:48:30.403910  5307 net.cpp:338] ctx_output5/bn does not need backward computation.
-I0510 14:48:30.403926  5307 net.cpp:338] ctx_output5 does not need backward computation.
-I0510 14:48:30.403944  5307 net.cpp:338] ctx_output5/1x1/relu does not need backward computation.
-I0510 14:48:30.403959  5307 net.cpp:338] ctx_output5/1x1/bn does not need backward computation.
-I0510 14:48:30.403973  5307 net.cpp:338] ctx_output5/1x1 does not need backward computation.
-I0510 14:48:30.403988  5307 net.cpp:338] ctx_output4_ctx_output4/relu_0_split does not need backward computation.
-I0510 14:48:30.404006  5307 net.cpp:338] ctx_output4/relu does not need backward computation.
-I0510 14:48:30.404026  5307 net.cpp:338] ctx_output4/bn does not need backward computation.
-I0510 14:48:30.404042  5307 net.cpp:338] ctx_output4 does not need backward computation.
-I0510 14:48:30.404057  5307 net.cpp:338] ctx_output4/1x1/relu does not need backward computation.
-I0510 14:48:30.404072  5307 net.cpp:338] ctx_output4/1x1/bn does not need backward computation.
-I0510 14:48:30.404086  5307 net.cpp:338] ctx_output4/1x1 does not need backward computation.
-I0510 14:48:30.404101  5307 net.cpp:338] ctx_output3_ctx_output3/relu_0_split does not need backward computation.
-I0510 14:48:30.404116  5307 net.cpp:338] ctx_output3/relu does not need backward computation.
-I0510 14:48:30.404131  5307 net.cpp:338] ctx_output3/bn does not need backward computation.
-I0510 14:48:30.404146  5307 net.cpp:338] ctx_output3 does not need backward computation.
-I0510 14:48:30.404161  5307 net.cpp:338] ctx_output3/1x1/relu does not need backward computation.
-I0510 14:48:30.404176  5307 net.cpp:338] ctx_output3/1x1/bn does not need backward computation.
-I0510 14:48:30.404191  5307 net.cpp:338] ctx_output3/1x1 does not need backward computation.
-I0510 14:48:30.404206  5307 net.cpp:338] ctx_output2_ctx_output2/relu_0_split does not need backward computation.
-I0510 14:48:30.404222  5307 net.cpp:338] ctx_output2/relu does not need backward computation.
-I0510 14:48:30.404237  5307 net.cpp:338] ctx_output2/bn does not need backward computation.
-I0510 14:48:30.404251  5307 net.cpp:338] ctx_output2 does not need backward computation.
-I0510 14:48:30.404266  5307 net.cpp:338] ctx_output2/1x1/relu does not need backward computation.
-I0510 14:48:30.404283  5307 net.cpp:338] ctx_output2/1x1/bn does not need backward computation.
-I0510 14:48:30.404299  5307 net.cpp:338] ctx_output2/1x1 does not need backward computation.
-I0510 14:48:30.404315  5307 net.cpp:338] ctx_output1_ctx_output1/relu_0_split does not need backward computation.
-I0510 14:48:30.404330  5307 net.cpp:338] ctx_output1/relu does not need backward computation.
-I0510 14:48:30.404345  5307 net.cpp:338] ctx_output1/bn does not need backward computation.
-I0510 14:48:30.404359  5307 net.cpp:338] ctx_output1 does not need backward computation.
-I0510 14:48:30.404374  5307 net.cpp:338] ctx_output1/1x1/relu does not need backward computation.
-I0510 14:48:30.404389  5307 net.cpp:338] ctx_output1/1x1/bn does not need backward computation.
-I0510 14:48:30.404404  5307 net.cpp:338] ctx_output1/1x1 does not need backward computation.
-I0510 14:48:30.404419  5307 net.cpp:338] pool8 does not need backward computation.
-I0510 14:48:30.404434  5307 net.cpp:338] pool7_pool7_0_split does not need backward computation.
-I0510 14:48:30.404449  5307 net.cpp:338] pool7 does not need backward computation.
-I0510 14:48:30.404464  5307 net.cpp:338] pool6_pool6_0_split does not need backward computation.
-I0510 14:48:30.404479  5307 net.cpp:338] pool6 does not need backward computation.
-I0510 14:48:30.404495  5307 net.cpp:338] conv6/sep_relu6/sep_0_split does not need backward computation.
-I0510 14:48:30.404510  5307 net.cpp:338] relu6/sep does not need backward computation.
-I0510 14:48:30.404530  5307 net.cpp:338] conv6/sep/scale does not need backward computation.
-I0510 14:48:30.404546  5307 net.cpp:338] conv6/sep/bn does not need backward computation.
-I0510 14:48:30.404561  5307 net.cpp:338] conv6/sep does not need backward computation.
-I0510 14:48:30.404577  5307 net.cpp:338] relu6/dw does not need backward computation.
-I0510 14:48:30.404592  5307 net.cpp:338] conv6/dw/scale does not need backward computation.
-I0510 14:48:30.404606  5307 net.cpp:338] conv6/dw/bn does not need backward computation.
-I0510 14:48:30.404621  5307 net.cpp:338] conv6/dw does not need backward computation.
-I0510 14:48:30.404636  5307 net.cpp:338] relu5_6/sep does not need backward computation.
-I0510 14:48:30.404650  5307 net.cpp:338] conv5_6/sep/scale does not need backward computation.
-I0510 14:48:30.404665  5307 net.cpp:338] conv5_6/sep/bn does not need backward computation.
-I0510 14:48:30.404683  5307 net.cpp:338] conv5_6/sep does not need backward computation.
-I0510 14:48:30.404705  5307 net.cpp:338] relu5_6/dw does not need backward computation.
-I0510 14:48:30.404719  5307 net.cpp:338] conv5_6/dw/scale does not need backward computation.
-I0510 14:48:30.404733  5307 net.cpp:338] conv5_6/dw/bn does not need backward computation.
-I0510 14:48:30.404748  5307 net.cpp:338] conv5_6/dw does not need backward computation.
-I0510 14:48:30.404763  5307 net.cpp:338] conv5_5/sep_relu5_5/sep_0_split does not need backward computation.
-I0510 14:48:30.404779  5307 net.cpp:338] relu5_5/sep does not need backward computation.
-I0510 14:48:30.404793  5307 net.cpp:338] conv5_5/sep/scale does not need backward computation.
-I0510 14:48:30.404808  5307 net.cpp:338] conv5_5/sep/bn does not need backward computation.
-I0510 14:48:30.404824  5307 net.cpp:338] conv5_5/sep does not need backward computation.
-I0510 14:48:30.404842  5307 net.cpp:338] relu5_5/dw does not need backward computation.
-I0510 14:48:30.404860  5307 net.cpp:338] conv5_5/dw/scale does not need backward computation.
-I0510 14:48:30.404875  5307 net.cpp:338] conv5_5/dw/bn does not need backward computation.
-I0510 14:48:30.404891  5307 net.cpp:338] conv5_5/dw does not need backward computation.
-I0510 14:48:30.404906  5307 net.cpp:338] relu5_4/sep does not need backward computation.
-I0510 14:48:30.404920  5307 net.cpp:338] conv5_4/sep/scale does not need backward computation.
-I0510 14:48:30.404935  5307 net.cpp:338] conv5_4/sep/bn does not need backward computation.
-I0510 14:48:30.404949  5307 net.cpp:338] conv5_4/sep does not need backward computation.
-I0510 14:48:30.404964  5307 net.cpp:338] relu5_4/dw does not need backward computation.
-I0510 14:48:30.404978  5307 net.cpp:338] conv5_4/dw/scale does not need backward computation.
-I0510 14:48:30.404996  5307 net.cpp:338] conv5_4/dw/bn does not need backward computation.
-I0510 14:48:30.405012  5307 net.cpp:338] conv5_4/dw does not need backward computation.
-I0510 14:48:30.405027  5307 net.cpp:338] relu5_3/sep does not need backward computation.
-I0510 14:48:30.405042  5307 net.cpp:338] conv5_3/sep/scale does not need backward computation.
-I0510 14:48:30.405057  5307 net.cpp:338] conv5_3/sep/bn does not need backward computation.
-I0510 14:48:30.405076  5307 net.cpp:338] conv5_3/sep does not need backward computation.
-I0510 14:48:30.405092  5307 net.cpp:338] relu5_3/dw does not need backward computation.
-I0510 14:48:30.405107  5307 net.cpp:338] conv5_3/dw/scale does not need backward computation.
-I0510 14:48:30.405122  5307 net.cpp:338] conv5_3/dw/bn does not need backward computation.
-I0510 14:48:30.405136  5307 net.cpp:338] conv5_3/dw does not need backward computation.
-I0510 14:48:30.405153  5307 net.cpp:338] relu5_2/sep does not need backward computation.
-I0510 14:48:30.405167  5307 net.cpp:338] conv5_2/sep/scale does not need backward computation.
-I0510 14:48:30.405182  5307 net.cpp:338] conv5_2/sep/bn does not need backward computation.
-I0510 14:48:30.405198  5307 net.cpp:338] conv5_2/sep does not need backward computation.
-I0510 14:48:30.405213  5307 net.cpp:338] relu5_2/dw does not need backward computation.
-I0510 14:48:30.405228  5307 net.cpp:338] conv5_2/dw/scale does not need backward computation.
-I0510 14:48:30.405243  5307 net.cpp:338] conv5_2/dw/bn does not need backward computation.
-I0510 14:48:30.405258  5307 net.cpp:338] conv5_2/dw does not need backward computation.
-I0510 14:48:30.405273  5307 net.cpp:338] relu5_1/sep does not need backward computation.
-I0510 14:48:30.405287  5307 net.cpp:338] conv5_1/sep/scale does not need backward computation.
-I0510 14:48:30.405303  5307 net.cpp:338] conv5_1/sep/bn does not need backward computation.
-I0510 14:48:30.405318  5307 net.cpp:338] conv5_1/sep does not need backward computation.
-I0510 14:48:30.405333  5307 net.cpp:338] relu5_1/dw does not need backward computation.
-I0510 14:48:30.405346  5307 net.cpp:338] conv5_1/dw/scale does not need backward computation.
-I0510 14:48:30.405361  5307 net.cpp:338] conv5_1/dw/bn does not need backward computation.
-I0510 14:48:30.405386  5307 net.cpp:338] conv5_1/dw does not need backward computation.
-I0510 14:48:30.405408  5307 net.cpp:338] relu4_2/sep does not need backward computation.
-I0510 14:48:30.405423  5307 net.cpp:338] conv4_2/sep/scale does not need backward computation.
-I0510 14:48:30.405438  5307 net.cpp:338] conv4_2/sep/bn does not need backward computation.
-I0510 14:48:30.405453  5307 net.cpp:338] conv4_2/sep does not need backward computation.
-I0510 14:48:30.405468  5307 net.cpp:338] relu4_2/dw does not need backward computation.
-I0510 14:48:30.405483  5307 net.cpp:338] conv4_2/dw/scale does not need backward computation.
-I0510 14:48:30.405498  5307 net.cpp:338] conv4_2/dw/bn does not need backward computation.
-I0510 14:48:30.405513  5307 net.cpp:338] conv4_2/dw does not need backward computation.
-I0510 14:48:30.405527  5307 net.cpp:338] relu4_1/sep does not need backward computation.
-I0510 14:48:30.405542  5307 net.cpp:338] conv4_1/sep/scale does not need backward computation.
-I0510 14:48:30.405557  5307 net.cpp:338] conv4_1/sep/bn does not need backward computation.
-I0510 14:48:30.405571  5307 net.cpp:338] conv4_1/sep does not need backward computation.
-I0510 14:48:30.405586  5307 net.cpp:338] relu4_1/dw does not need backward computation.
-I0510 14:48:30.405601  5307 net.cpp:338] conv4_1/dw/scale does not need backward computation.
-I0510 14:48:30.405614  5307 net.cpp:338] conv4_1/dw/bn does not need backward computation.
-I0510 14:48:30.405630  5307 net.cpp:338] conv4_1/dw does not need backward computation.
-I0510 14:48:30.405644  5307 net.cpp:338] relu3_2/sep does not need backward computation.
-I0510 14:48:30.405659  5307 net.cpp:338] conv3_2/sep/scale does not need backward computation.
-I0510 14:48:30.405673  5307 net.cpp:338] conv3_2/sep/bn does not need backward computation.
-I0510 14:48:30.405691  5307 net.cpp:338] conv3_2/sep does not need backward computation.
-I0510 14:48:30.405706  5307 net.cpp:338] relu3_2/dw does not need backward computation.
-I0510 14:48:30.405722  5307 net.cpp:338] conv3_2/dw/scale does not need backward computation.
-I0510 14:48:30.405736  5307 net.cpp:338] conv3_2/dw/bn does not need backward computation.
-I0510 14:48:30.405751  5307 net.cpp:338] conv3_2/dw does not need backward computation.
-I0510 14:48:30.405766  5307 net.cpp:338] relu3_1/sep does not need backward computation.
-I0510 14:48:30.405781  5307 net.cpp:338] conv3_1/sep/scale does not need backward computation.
-I0510 14:48:30.405797  5307 net.cpp:338] conv3_1/sep/bn does not need backward computation.
-I0510 14:48:30.405812  5307 net.cpp:338] conv3_1/sep does not need backward computation.
-I0510 14:48:30.405827  5307 net.cpp:338] relu3_1/dw does not need backward computation.
-I0510 14:48:30.405841  5307 net.cpp:338] conv3_1/dw/scale does not need backward computation.
-I0510 14:48:30.405856  5307 net.cpp:338] conv3_1/dw/bn does not need backward computation.
-I0510 14:48:30.405870  5307 net.cpp:338] conv3_1/dw does not need backward computation.
-I0510 14:48:30.405886  5307 net.cpp:338] relu2_2/sep does not need backward computation.
-I0510 14:48:30.405901  5307 net.cpp:338] conv2_2/sep/scale does not need backward computation.
-I0510 14:48:30.405916  5307 net.cpp:338] conv2_2/sep/bn does not need backward computation.
-I0510 14:48:30.405930  5307 net.cpp:338] conv2_2/sep does not need backward computation.
-I0510 14:48:30.405944  5307 net.cpp:338] relu2_2/dw does not need backward computation.
-I0510 14:48:30.405959  5307 net.cpp:338] conv2_2/dw/scale does not need backward computation.
-I0510 14:48:30.405974  5307 net.cpp:338] conv2_2/dw/bn does not need backward computation.
-I0510 14:48:30.405989  5307 net.cpp:338] conv2_2/dw does not need backward computation.
-I0510 14:48:30.406004  5307 net.cpp:338] relu2_1/sep does not need backward computation.
-I0510 14:48:30.406018  5307 net.cpp:338] conv2_1/sep/scale does not need backward computation.
-I0510 14:48:30.406033  5307 net.cpp:338] conv2_1/sep/bn does not need backward computation.
-I0510 14:48:30.406046  5307 net.cpp:338] conv2_1/sep does not need backward computation.
-I0510 14:48:30.406064  5307 net.cpp:338] relu2_1/dw does not need backward computation.
-I0510 14:48:30.406086  5307 net.cpp:338] conv2_1/dw/scale does not need backward computation.
-I0510 14:48:30.406100  5307 net.cpp:338] conv2_1/dw/bn does not need backward computation.
-I0510 14:48:30.406116  5307 net.cpp:338] conv2_1/dw does not need backward computation.
-I0510 14:48:30.406131  5307 net.cpp:338] relu1 does not need backward computation.
-I0510 14:48:30.406146  5307 net.cpp:338] conv1/scale does not need backward computation.
-I0510 14:48:30.406160  5307 net.cpp:338] conv1/bn does not need backward computation.
-I0510 14:48:30.406175  5307 net.cpp:338] conv1 does not need backward computation.
-I0510 14:48:30.406190  5307 net.cpp:338] data/bias does not need backward computation.
-I0510 14:48:30.406205  5307 net.cpp:338] data_data_0_split does not need backward computation.
-I0510 14:48:30.406220  5307 net.cpp:338] data does not need backward computation.
-I0510 14:48:30.406234  5307 net.cpp:380] This network produces output detection_eval
-I0510 14:48:30.406448  5307 net.cpp:403] Top memory (TEST) required for data: 1081855432 diff: 1081855432
-I0510 14:48:30.406466  5307 net.cpp:406] Bottom memory (TEST) required for data: 1081855008 diff: 1081855008
-I0510 14:48:30.406481  5307 net.cpp:409] Shared (in-place) memory (TEST) by data: 679149568 diff: 679149568
-I0510 14:48:30.406496  5307 net.cpp:412] Parameters memory (TEST) required for data: 9462808 diff: 9462808
-I0510 14:48:30.406510  5307 net.cpp:415] Parameters shared memory (TEST) by data: 0 diff: 0
-I0510 14:48:30.406525  5307 net.cpp:421] Network initialization done.
-I0510 14:48:30.406883  5307 solver.cpp:55] Solver scaffolding done.
-I0510 14:48:30.413641  5307 caffe.cpp:158] Finetuning from ../trained/image_classification/imagenet_mobilenet-0.5/initial/imagenet_mobilenet-0.5_iter_320000.caffemodel
-I0510 14:48:30.415630  5307 net.cpp:1144] Copying source layer data Type:Data #blobs=0
-I0510 14:48:30.415675  5307 net.cpp:1144] Copying source layer data/bias Type:Bias #blobs=1
-I0510 14:48:30.415719  5307 net.cpp:1144] Copying source layer conv1 Type:Convolution #blobs=1
-I0510 14:48:30.415745  5307 net.cpp:1144] Copying source layer conv1/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.415774  5307 net.cpp:1144] Copying source layer conv1/scale Type:Scale #blobs=2
-I0510 14:48:30.415802  5307 net.cpp:1144] Copying source layer relu1 Type:ReLU #blobs=0
-I0510 14:48:30.415817  5307 net.cpp:1144] Copying source layer conv2_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.415838  5307 net.cpp:1144] Copying source layer conv2_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.415866  5307 net.cpp:1144] Copying source layer conv2_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.415891  5307 net.cpp:1144] Copying source layer relu2_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.415906  5307 net.cpp:1144] Copying source layer conv2_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.415927  5307 net.cpp:1144] Copying source layer conv2_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.415959  5307 net.cpp:1144] Copying source layer conv2_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.415987  5307 net.cpp:1144] Copying source layer relu2_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.416002  5307 net.cpp:1144] Copying source layer conv2_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.416023  5307 net.cpp:1144] Copying source layer conv2_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416052  5307 net.cpp:1144] Copying source layer conv2_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416079  5307 net.cpp:1144] Copying source layer relu2_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.416095  5307 net.cpp:1144] Copying source layer conv2_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.416118  5307 net.cpp:1144] Copying source layer conv2_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416151  5307 net.cpp:1144] Copying source layer conv2_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416177  5307 net.cpp:1144] Copying source layer relu2_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.416193  5307 net.cpp:1144] Copying source layer conv3_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.416219  5307 net.cpp:1144] Copying source layer conv3_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416255  5307 net.cpp:1144] Copying source layer conv3_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416281  5307 net.cpp:1144] Copying source layer relu3_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.416297  5307 net.cpp:1144] Copying source layer conv3_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.416319  5307 net.cpp:1144] Copying source layer conv3_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416348  5307 net.cpp:1144] Copying source layer conv3_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416374  5307 net.cpp:1144] Copying source layer relu3_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.416389  5307 net.cpp:1144] Copying source layer conv3_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.416410  5307 net.cpp:1144] Copying source layer conv3_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416440  5307 net.cpp:1144] Copying source layer conv3_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416465  5307 net.cpp:1144] Copying source layer relu3_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.416479  5307 net.cpp:1144] Copying source layer conv3_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.416503  5307 net.cpp:1144] Copying source layer conv3_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416546  5307 net.cpp:1144] Copying source layer conv3_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416574  5307 net.cpp:1144] Copying source layer relu3_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.416589  5307 net.cpp:1144] Copying source layer conv4_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.416610  5307 net.cpp:1144] Copying source layer conv4_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416638  5307 net.cpp:1144] Copying source layer conv4_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416666  5307 net.cpp:1144] Copying source layer relu4_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.416682  5307 net.cpp:1144] Copying source layer conv4_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.416709  5307 net.cpp:1144] Copying source layer conv4_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416739  5307 net.cpp:1144] Copying source layer conv4_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416764  5307 net.cpp:1144] Copying source layer relu4_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.416779  5307 net.cpp:1144] Copying source layer conv4_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.416802  5307 net.cpp:1144] Copying source layer conv4_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416828  5307 net.cpp:1144] Copying source layer conv4_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416851  5307 net.cpp:1144] Copying source layer relu4_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.416863  5307 net.cpp:1144] Copying source layer conv4_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.416894  5307 net.cpp:1144] Copying source layer conv4_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416921  5307 net.cpp:1144] Copying source layer conv4_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416944  5307 net.cpp:1144] Copying source layer relu4_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.416956  5307 net.cpp:1144] Copying source layer conv5_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.416975  5307 net.cpp:1144] Copying source layer conv5_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417001  5307 net.cpp:1144] Copying source layer conv5_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417021  5307 net.cpp:1144] Copying source layer relu5_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.417034  5307 net.cpp:1144] Copying source layer conv5_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.417079  5307 net.cpp:1144] Copying source layer conv5_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417106  5307 net.cpp:1144] Copying source layer conv5_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417129  5307 net.cpp:1144] Copying source layer relu5_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.417141  5307 net.cpp:1144] Copying source layer conv5_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.417158  5307 net.cpp:1144] Copying source layer conv5_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417186  5307 net.cpp:1144] Copying source layer conv5_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417217  5307 net.cpp:1144] Copying source layer relu5_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.417229  5307 net.cpp:1144] Copying source layer conv5_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.417277  5307 net.cpp:1144] Copying source layer conv5_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417304  5307 net.cpp:1144] Copying source layer conv5_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417327  5307 net.cpp:1144] Copying source layer relu5_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.417340  5307 net.cpp:1144] Copying source layer conv5_3/dw Type:Convolution #blobs=1
-I0510 14:48:30.417358  5307 net.cpp:1144] Copying source layer conv5_3/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417383  5307 net.cpp:1144] Copying source layer conv5_3/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417405  5307 net.cpp:1144] Copying source layer relu5_3/dw Type:ReLU #blobs=0
-I0510 14:48:30.417418  5307 net.cpp:1144] Copying source layer conv5_3/sep Type:Convolution #blobs=1
-I0510 14:48:30.417486  5307 net.cpp:1144] Copying source layer conv5_3/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417515  5307 net.cpp:1144] Copying source layer conv5_3/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417536  5307 net.cpp:1144] Copying source layer relu5_3/sep Type:ReLU #blobs=0
-I0510 14:48:30.417549  5307 net.cpp:1144] Copying source layer conv5_4/dw Type:Convolution #blobs=1
-I0510 14:48:30.417567  5307 net.cpp:1144] Copying source layer conv5_4/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417593  5307 net.cpp:1144] Copying source layer conv5_4/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417614  5307 net.cpp:1144] Copying source layer relu5_4/dw Type:ReLU #blobs=0
-I0510 14:48:30.417626  5307 net.cpp:1144] Copying source layer conv5_4/sep Type:Convolution #blobs=1
-I0510 14:48:30.417673  5307 net.cpp:1144] Copying source layer conv5_4/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417699  5307 net.cpp:1144] Copying source layer conv5_4/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417721  5307 net.cpp:1144] Copying source layer relu5_4/sep Type:ReLU #blobs=0
-I0510 14:48:30.417733  5307 net.cpp:1144] Copying source layer conv5_5/dw Type:Convolution #blobs=1
-I0510 14:48:30.417752  5307 net.cpp:1144] Copying source layer conv5_5/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417776  5307 net.cpp:1144] Copying source layer conv5_5/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417798  5307 net.cpp:1144] Copying source layer relu5_5/dw Type:ReLU #blobs=0
-I0510 14:48:30.417810  5307 net.cpp:1144] Copying source layer conv5_5/sep Type:Convolution #blobs=1
-I0510 14:48:30.417853  5307 net.cpp:1144] Copying source layer conv5_5/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417879  5307 net.cpp:1144] Copying source layer conv5_5/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417902  5307 net.cpp:1144] Copying source layer relu5_5/sep Type:ReLU #blobs=0
-I0510 14:48:30.417915  5307 net.cpp:1144] Copying source layer conv5_6/dw Type:Convolution #blobs=1
-I0510 14:48:30.417933  5307 net.cpp:1144] Copying source layer conv5_6/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417958  5307 net.cpp:1144] Copying source layer conv5_6/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417980  5307 net.cpp:1144] Copying source layer relu5_6/dw Type:ReLU #blobs=0
-I0510 14:48:30.417992  5307 net.cpp:1144] Copying source layer conv5_6/sep Type:Convolution #blobs=1
-I0510 14:48:30.418058  5307 net.cpp:1144] Copying source layer conv5_6/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.418087  5307 net.cpp:1144] Copying source layer conv5_6/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.418109  5307 net.cpp:1144] Copying source layer relu5_6/sep Type:ReLU #blobs=0
-I0510 14:48:30.418121  5307 net.cpp:1144] Copying source layer conv6/dw Type:Convolution #blobs=1
-I0510 14:48:30.418140  5307 net.cpp:1144] Copying source layer conv6/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.418165  5307 net.cpp:1144] Copying source layer conv6/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.418189  5307 net.cpp:1144] Copying source layer relu6/dw Type:ReLU #blobs=0
-I0510 14:48:30.418203  5307 net.cpp:1144] Copying source layer conv6/sep Type:Convolution #blobs=1
-I0510 14:48:30.418311  5307 net.cpp:1144] Copying source layer conv6/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.418339  5307 net.cpp:1144] Copying source layer conv6/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.418361  5307 net.cpp:1144] Copying source layer relu6/sep Type:ReLU #blobs=0
-I0510 14:48:30.418375  5307 net.cpp:1144] Copying source layer pool6 Type:Pooling #blobs=0
-I0510 14:48:30.418385  5307 net.cpp:1136] Ignoring source layer fc7
-I0510 14:48:30.418396  5307 net.cpp:1136] Ignoring source layer loss
-I0510 14:48:30.420141  5307 net.cpp:1144] Copying source layer data Type:Data #blobs=0
-I0510 14:48:30.420172  5307 net.cpp:1144] Copying source layer data/bias Type:Bias #blobs=1
-I0510 14:48:30.420200  5307 net.cpp:1144] Copying source layer conv1 Type:Convolution #blobs=1
-I0510 14:48:30.420218  5307 net.cpp:1144] Copying source layer conv1/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420244  5307 net.cpp:1144] Copying source layer conv1/scale Type:Scale #blobs=2
-I0510 14:48:30.420265  5307 net.cpp:1144] Copying source layer relu1 Type:ReLU #blobs=0
-I0510 14:48:30.420277  5307 net.cpp:1144] Copying source layer conv2_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.420295  5307 net.cpp:1144] Copying source layer conv2_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420320  5307 net.cpp:1144] Copying source layer conv2_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420341  5307 net.cpp:1144] Copying source layer relu2_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.420352  5307 net.cpp:1144] Copying source layer conv2_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.420369  5307 net.cpp:1144] Copying source layer conv2_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420398  5307 net.cpp:1144] Copying source layer conv2_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.420421  5307 net.cpp:1144] Copying source layer relu2_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.420433  5307 net.cpp:1144] Copying source layer conv2_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.420450  5307 net.cpp:1144] Copying source layer conv2_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420476  5307 net.cpp:1144] Copying source layer conv2_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420500  5307 net.cpp:1144] Copying source layer relu2_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.420512  5307 net.cpp:1144] Copying source layer conv2_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.420537  5307 net.cpp:1144] Copying source layer conv2_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420565  5307 net.cpp:1144] Copying source layer conv2_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.420586  5307 net.cpp:1144] Copying source layer relu2_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.420598  5307 net.cpp:1144] Copying source layer conv3_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.420616  5307 net.cpp:1144] Copying source layer conv3_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420640  5307 net.cpp:1144] Copying source layer conv3_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420662  5307 net.cpp:1144] Copying source layer relu3_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.420675  5307 net.cpp:1144] Copying source layer conv3_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.420693  5307 net.cpp:1144] Copying source layer conv3_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420718  5307 net.cpp:1144] Copying source layer conv3_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.420740  5307 net.cpp:1144] Copying source layer relu3_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.420753  5307 net.cpp:1144] Copying source layer conv3_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.420769  5307 net.cpp:1144] Copying source layer conv3_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420794  5307 net.cpp:1144] Copying source layer conv3_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420815  5307 net.cpp:1144] Copying source layer relu3_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.420827  5307 net.cpp:1144] Copying source layer conv3_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.420851  5307 net.cpp:1144] Copying source layer conv3_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420883  5307 net.cpp:1144] Copying source layer conv3_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.420905  5307 net.cpp:1144] Copying source layer relu3_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.420918  5307 net.cpp:1144] Copying source layer conv4_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.420936  5307 net.cpp:1144] Copying source layer conv4_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420960  5307 net.cpp:1144] Copying source layer conv4_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420982  5307 net.cpp:1144] Copying source layer relu4_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.420994  5307 net.cpp:1144] Copying source layer conv4_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.421017  5307 net.cpp:1144] Copying source layer conv4_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421042  5307 net.cpp:1144] Copying source layer conv4_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421064  5307 net.cpp:1144] Copying source layer relu4_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.421077  5307 net.cpp:1144] Copying source layer conv4_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.421095  5307 net.cpp:1144] Copying source layer conv4_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421119  5307 net.cpp:1144] Copying source layer conv4_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421141  5307 net.cpp:1144] Copying source layer relu4_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.421154  5307 net.cpp:1144] Copying source layer conv4_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.421190  5307 net.cpp:1144] Copying source layer conv4_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421217  5307 net.cpp:1144] Copying source layer conv4_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421241  5307 net.cpp:1144] Copying source layer relu4_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.421254  5307 net.cpp:1144] Copying source layer conv5_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.421272  5307 net.cpp:1144] Copying source layer conv5_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421298  5307 net.cpp:1144] Copying source layer conv5_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421319  5307 net.cpp:1144] Copying source layer relu5_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.421331  5307 net.cpp:1144] Copying source layer conv5_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.421375  5307 net.cpp:1144] Copying source layer conv5_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421401  5307 net.cpp:1144] Copying source layer conv5_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421423  5307 net.cpp:1144] Copying source layer relu5_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.421435  5307 net.cpp:1144] Copying source layer conv5_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.421452  5307 net.cpp:1144] Copying source layer conv5_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421476  5307 net.cpp:1144] Copying source layer conv5_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421499  5307 net.cpp:1144] Copying source layer relu5_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.421510  5307 net.cpp:1144] Copying source layer conv5_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.421555  5307 net.cpp:1144] Copying source layer conv5_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421581  5307 net.cpp:1144] Copying source layer conv5_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421603  5307 net.cpp:1144] Copying source layer relu5_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.421615  5307 net.cpp:1144] Copying source layer conv5_3/dw Type:Convolution #blobs=1
-I0510 14:48:30.421633  5307 net.cpp:1144] Copying source layer conv5_3/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421658  5307 net.cpp:1144] Copying source layer conv5_3/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421681  5307 net.cpp:1144] Copying source layer relu5_3/dw Type:ReLU #blobs=0
-I0510 14:48:30.421694  5307 net.cpp:1144] Copying source layer conv5_3/sep Type:Convolution #blobs=1
-I0510 14:48:30.421737  5307 net.cpp:1144] Copying source layer conv5_3/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421762  5307 net.cpp:1144] Copying source layer conv5_3/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421788  5307 net.cpp:1144] Copying source layer relu5_3/sep Type:ReLU #blobs=0
-I0510 14:48:30.421805  5307 net.cpp:1144] Copying source layer conv5_4/dw Type:Convolution #blobs=1
-I0510 14:48:30.421824  5307 net.cpp:1144] Copying source layer conv5_4/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421849  5307 net.cpp:1144] Copying source layer conv5_4/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421871  5307 net.cpp:1144] Copying source layer relu5_4/dw Type:ReLU #blobs=0
-I0510 14:48:30.421883  5307 net.cpp:1144] Copying source layer conv5_4/sep Type:Convolution #blobs=1
-I0510 14:48:30.421927  5307 net.cpp:1144] Copying source layer conv5_4/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421955  5307 net.cpp:1144] Copying source layer conv5_4/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421979  5307 net.cpp:1144] Copying source layer relu5_4/sep Type:ReLU #blobs=0
-I0510 14:48:30.421993  5307 net.cpp:1144] Copying source layer conv5_5/dw Type:Convolution #blobs=1
-I0510 14:48:30.422011  5307 net.cpp:1144] Copying source layer conv5_5/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422036  5307 net.cpp:1144] Copying source layer conv5_5/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.422060  5307 net.cpp:1144] Copying source layer relu5_5/dw Type:ReLU #blobs=0
-I0510 14:48:30.422073  5307 net.cpp:1144] Copying source layer conv5_5/sep Type:Convolution #blobs=1
-I0510 14:48:30.422117  5307 net.cpp:1144] Copying source layer conv5_5/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422147  5307 net.cpp:1144] Copying source layer conv5_5/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.422169  5307 net.cpp:1144] Copying source layer relu5_5/sep Type:ReLU #blobs=0
-I0510 14:48:30.422183  5307 net.cpp:1144] Copying source layer conv5_6/dw Type:Convolution #blobs=1
-I0510 14:48:30.422205  5307 net.cpp:1144] Copying source layer conv5_6/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422232  5307 net.cpp:1144] Copying source layer conv5_6/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.422255  5307 net.cpp:1144] Copying source layer relu5_6/dw Type:ReLU #blobs=0
-I0510 14:48:30.422268  5307 net.cpp:1144] Copying source layer conv5_6/sep Type:Convolution #blobs=1
-I0510 14:48:30.422336  5307 net.cpp:1144] Copying source layer conv5_6/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422365  5307 net.cpp:1144] Copying source layer conv5_6/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.422389  5307 net.cpp:1144] Copying source layer relu5_6/sep Type:ReLU #blobs=0
-I0510 14:48:30.422402  5307 net.cpp:1144] Copying source layer conv6/dw Type:Convolution #blobs=1
-I0510 14:48:30.422422  5307 net.cpp:1144] Copying source layer conv6/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422449  5307 net.cpp:1144] Copying source layer conv6/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.422472  5307 net.cpp:1144] Copying source layer relu6/dw Type:ReLU #blobs=0
-I0510 14:48:30.422485  5307 net.cpp:1144] Copying source layer conv6/sep Type:Convolution #blobs=1
-I0510 14:48:30.422605  5307 net.cpp:1144] Copying source layer conv6/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422636  5307 net.cpp:1144] Copying source layer conv6/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.422662  5307 net.cpp:1144] Copying source layer relu6/sep Type:ReLU #blobs=0
-I0510 14:48:30.422675  5307 net.cpp:1144] Copying source layer pool6 Type:Pooling #blobs=0
-I0510 14:48:30.422689  5307 net.cpp:1136] Ignoring source layer fc7
-I0510 14:48:30.422701  5307 net.cpp:1136] Ignoring source layer loss
-I0510 14:48:30.422816  5307 caffe.cpp:260] Starting Optimization
-I0510 14:48:30.422832  5307 solver.cpp:453] Solving mobiledetnet-0.5
-I0510 14:48:30.422842  5307 solver.cpp:454] Learning Rate Policy: multistep
-I0510 14:48:30.422900  5307 net.cpp:1443] [0] Reserving 9381120 bytes of shared learnable space for type FLOAT
-I0510 14:48:30.428328  5307 solver.cpp:269] Initial Test started...
-I0510 14:48:30.428369  5307 solver.cpp:635] Iteration 0, Testing net (#0)
-I0510 14:48:30.429464  5355 common.cpp:528] NVML initialized, thread 5355
-I0510 14:48:30.433272  5307 net.cpp:1071] Ignoring source layer mbox_loss
-I0510 14:48:30.508715  5355 common.cpp:550] NVML succeeded to set CPU affinity on device 0, thread 5355
-I0510 14:49:00.809654  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 14:49:00.990506  5307 solver.cpp:747] class AP 1: 4.20608e-06
-I0510 14:49:00.998561  5307 solver.cpp:747] class AP 2: 2.36312e-05
-I0510 14:49:01.033555  5307 solver.cpp:747] class AP 3: 3.95601e-05
-I0510 14:49:01.033614  5307 solver.cpp:747] class AP 4: 0
-W0510 14:49:01.033622  5307 solver.cpp:731] Missing true_pos for label: 5
-W0510 14:49:01.033705  5307 solver.cpp:731] Missing true_pos for label: 6
-W0510 14:49:01.033710  5307 solver.cpp:731] Missing true_pos for label: 7
-W0510 14:49:01.033713  5307 solver.cpp:731] Missing true_pos for label: 8
-W0510 14:49:01.033716  5307 solver.cpp:731] Missing true_pos for label: 9
-W0510 14:49:01.033718  5307 solver.cpp:731] Missing true_pos for label: 10
-W0510 14:49:01.033721  5307 solver.cpp:731] Missing true_pos for label: 11
-W0510 14:49:01.033723  5307 solver.cpp:731] Missing true_pos for label: 12
-W0510 14:49:01.033726  5307 solver.cpp:731] Missing true_pos for label: 13
-W0510 14:49:01.033728  5307 solver.cpp:731] Missing true_pos for label: 14
-W0510 14:49:01.033731  5307 solver.cpp:731] Missing true_pos for label: 15
-W0510 14:49:01.033735  5307 solver.cpp:731] Missing true_pos for label: 16
-W0510 14:49:01.033736  5307 solver.cpp:731] Missing true_pos for label: 17
-W0510 14:49:01.033740  5307 solver.cpp:731] Missing true_pos for label: 18
-W0510 14:49:01.033741  5307 solver.cpp:731] Missing true_pos for label: 19
-W0510 14:49:01.033744  5307 solver.cpp:731] Missing true_pos for label: 20
-I0510 14:49:01.033747  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 3.36987e-06
-I0510 14:49:01.033784  5307 solver.cpp:274] Initial Test completed in 30.6046s
-I0510 14:49:01.729894  5307 solver.cpp:358] Iteration 0 (0.696069 s), loss = 30.2997
-I0510 14:49:01.729921  5307 solver.cpp:376]     Train net output #0: mbox_loss = 28.8664 (* 1 = 28.8664 loss)
-I0510 14:49:01.729928  5307 sgd_solver.cpp:172] Iteration 0, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:49:01.750205  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv1' with space 3.29M 3/1 1 1 3     (avail 1.28G, req 3.29M)        t: 0 0 0.92
-I0510 14:49:01.872751  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv2_1/dw' with space 3.29M 16/16. 0 1 3     (avail 1.28G, req 3.29M)        t: 0 2.47 8.62
-I0510 14:49:01.937407  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv2_1/sep' with space 3.29M 16/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.33 1.49
-I0510 14:49:02.031493  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv2_2/dw' with space 3.29M 32/32. 0 0 3     (avail 1.28G, req 3.29M)        t: 0 3.58 4.43
-I0510 14:49:02.084003  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv2_2/sep' with space 3.29M 32/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.31 0.83
-I0510 14:49:02.237854  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv3_1/dw' with space 3.29M 64/64. 0 1 3     (avail 1.28G, req 3.29M)        t: 0 2.74 8.84
-I0510 14:49:02.313946  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv3_1/sep' with space 3.29M 64/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.29 0.87
-I0510 14:49:02.403553  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv3_2/dw' with space 3.29M 64/64. 0 0 0     (avail 1.28G, req 3.29M)        t: 0 1.87 2.19
-I0510 14:49:02.433367  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv3_2/sep' with space 3.29M 64/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.13 0.22
-I0510 14:49:02.500931  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv4_1/dw' with space 3.29M 128/128. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.43 4.07
-I0510 14:49:02.541015  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv4_1/sep' with space 3.29M 128/1 1 1 3     (avail 1.28G, req 3.29M)        t: 0 0.17 0.24
-I0510 14:49:02.578392  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv4_2/dw' with space 3.29M 128/128. 0 1 3   (avail 1.28G, req 3.29M)        t: 0 1.86 1.51
-I0510 14:49:02.594458  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv4_2/sep' with space 3.29M 128/1 1 1 3     (avail 1.28G, req 3.29M)        t: 0 0.1 0.13
-I0510 14:49:02.656378  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_1/dw' with space 3.29M 256/256. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.8 2.88
-I0510 14:49:02.687712  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_1/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.15 0.22
-I0510 14:49:02.751070  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_2/dw' with space 3.29M 256/256. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.9 2.91
-I0510 14:49:02.783671  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_2/sep' with space 3.29M 256/1 1 1 3     (avail 1.28G, req 3.29M)        t: 0 0.22 0.29
-I0510 14:49:02.885000  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_3/dw' with space 3.29M 256/256. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.84 2.91
-I0510 14:49:02.918089  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_3/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.21 0.21
-I0510 14:49:03.025629  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_4/dw' with space 3.29M 256/256. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.82 2.9
-I0510 14:49:03.055307  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_4/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.18 0.24
-I0510 14:49:03.127607  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_5/dw' with space 3.29M 256/256. 0 1 3   (avail 1.28G, req 3.29M)        t: 0 2.09 3.49
-I0510 14:49:03.155717  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_5/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.15 0.21
-I0510 14:49:03.205742  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_6/dw' with space 3.29M 256/256. 0 0 3   (avail 1.28G, req 3.29M)        t: 0 4.67 2.27
-I0510 14:49:03.221109  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_6/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.11 0.11
-I0510 14:49:03.308890  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv6/dw' with space 3.29M 512/512. 0 1 0     (avail 1.28G, req 3.29M)        t: 0 3.54 4.82
-I0510 14:49:03.339993  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv6/sep' with space 3.29M 512/1 1 1 1       (avail 1.28G, req 3.29M)        t: 0 0.17 0.18
-I0510 14:49:03.385284  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output1/1x1' with space 3.29M 256/1 1 1 1         (avail 1.28G, req 3.29M)        t: 0 0.29 0.31
-I0510 14:49:03.546432  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output1' with space 3.29M 512/512. 0 1 0  (avail 1.28G, req 3.29M)        t: 0 3.56 5.95
-I0510 14:49:03.576686  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output2/1x1' with space 3.29M 512/1 1 1 1         (avail 1.28G, req 3.29M)        t: 0 0.17 0.17
-I0510 14:49:03.656278  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output2' with space 3.29M 512/512. 0 1 3  (avail 1.28G, req 3.29M)        t: 0 3.55 4.45
-I0510 14:49:03.679927  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output3/1x1' with space 3.29M 512/1 1 1 1         (avail 1.28G, req 3.29M)        t: 0 0.09 0.11
-I0510 14:49:03.779830  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output3' with space 3.29M 512/512. 0 1 3  (avail 1.28G, req 3.29M)        t: 0 3.66 4.51
-I0510 14:49:03.805711  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output4/1x1' with space 3.29M 512/1 1 0 1         (avail 1.28G, req 3.29M)        t: 0 0.07 0.06
-I0510 14:49:03.892918  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output4' with space 3.29M 512/512. 0 1 0  (avail 1.28G, req 3.29M)        t: 0 3.58 4.73
-I0510 14:49:03.916041  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output5/1x1' with space 3.29M 512/1 1 0 1         (avail 1.28G, req 3.29M)        t: 0 0.07 0.06
-I0510 14:49:04.017879  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output5' with space 3.29M 512/512. 0 1 0  (avail 1.28G, req 3.29M)        t: 0 3.56 4.66
-I0510 14:49:04.029551  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output1/relu_mbox_loc' with space 3.29M 512/1 1 1 3       (avail 1.28G, req 3.29M)        t: 0 0.08 0.14
-I0510 14:49:04.056619  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output1/relu_mbox_conf' with space 3.29M 512/1 1 1 0      (avail 1.28G, req 3.29M)        t: 0 0.14 0.25
-I0510 14:49:04.066035  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output2/relu_mbox_loc' with space 3.29M 512/1 1 1 0       (avail 1.28G, req 3.29M)        t: 0 0.04 0.05
-I0510 14:49:04.076759  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output2/relu_mbox_conf' with space 3.29M 512/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.07 0.08
-I0510 14:49:04.083274  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output3/relu_mbox_loc' with space 3.29M 512/1 1 1 0       (avail 1.28G, req 3.29M)        t: 0 0.03 0.03
-I0510 14:49:04.094904  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output3/relu_mbox_conf' with space 3.29M 512/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.04 0.05
-I0510 14:49:04.101155  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output4/relu_mbox_loc' with space 3.29M 512/1 1 0 0       (avail 1.28G, req 3.29M)        t: 0 0.03 0.02
-I0510 14:49:04.115995  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output4/relu_mbox_conf' with space 3.29M 512/1 1 0 3      (avail 1.28G, req 3.29M)        t: 0 0.04 0.04
-I0510 14:49:04.123507  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output5/relu_mbox_loc' with space 3.29M 512/1 0 0 0       (avail 1.28G, req 3.29M)        t: 0 0.04 0.03
-I0510 14:49:04.138696  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output5/relu_mbox_conf' with space 3.29M 512/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.05 0.06
-I0510 14:49:04.617333  5307 solver.cpp:358] Iteration 1 (2.88736 s), loss = 27.6163
-I0510 14:49:04.617358  5307 solver.cpp:376]     Train net output #0: mbox_loss = 25.7089 (* 1 = 25.7089 loss)
-I0510 14:49:05.138526  5307 solver.cpp:358] Iteration 2 (0.521175 s), loss = 26.3567
-I0510 14:49:05.138555  5307 solver.cpp:376]     Train net output #0: mbox_loss = 24.5248 (* 1 = 24.5248 loss)
-I0510 14:49:53.104404  5307 solver.cpp:352] Iteration 100 (2.04317 iter/s, 47.9647s/98 iter), loss = 7.17953
-I0510 14:49:53.104457  5307 solver.cpp:376]     Train net output #0: mbox_loss = 7.1951 (* 1 = 7.1951 loss)
-I0510 14:49:53.104465  5307 sgd_solver.cpp:172] Iteration 100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:50:44.360132  5307 solver.cpp:352] Iteration 200 (1.95105 iter/s, 51.2546s/100 iter), loss = 6.72388
-I0510 14:50:44.360198  5307 solver.cpp:376]     Train net output #0: mbox_loss = 6.90003 (* 1 = 6.90003 loss)
-I0510 14:50:44.360209  5307 sgd_solver.cpp:172] Iteration 200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:51:45.371630  5307 solver.cpp:352] Iteration 300 (1.63907 iter/s, 61.0102s/100 iter), loss = 6.42418
-I0510 14:51:45.371706  5307 solver.cpp:376]     Train net output #0: mbox_loss = 6.27518 (* 1 = 6.27518 loss)
-I0510 14:51:45.371714  5307 sgd_solver.cpp:172] Iteration 300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:52:45.343096  5307 solver.cpp:352] Iteration 400 (1.66749 iter/s, 59.9703s/100 iter), loss = 6.34919
-I0510 14:52:45.343987  5307 solver.cpp:376]     Train net output #0: mbox_loss = 7.68054 (* 1 = 7.68054 loss)
-I0510 14:52:45.344005  5307 sgd_solver.cpp:172] Iteration 400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:53:45.887753  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 14:53:46.284636  5307 solver.cpp:352] Iteration 500 (1.64095 iter/s, 60.9404s/100 iter), 1/231.9ep, loss = 6.23284
-I0510 14:53:46.284762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 6.66315 (* 1 = 6.66315 loss)
-I0510 14:53:46.284775  5307 sgd_solver.cpp:172] Iteration 500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:54:46.641153  5307 solver.cpp:352] Iteration 600 (1.65685 iter/s, 60.3554s/100 iter), 1.2/232ep, loss = 6.05849
-I0510 14:54:46.641240  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.92231 (* 1 = 5.92231 loss)
-I0510 14:54:46.641304  5307 sgd_solver.cpp:172] Iteration 600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:55:47.433953  5307 solver.cpp:352] Iteration 700 (1.64496 iter/s, 60.7917s/100 iter), 1.4/232ep, loss = 6.17512
-I0510 14:55:47.434027  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.76096 (* 1 = 5.76096 loss)
-I0510 14:55:47.434036  5307 sgd_solver.cpp:172] Iteration 700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:56:47.787348  5307 solver.cpp:352] Iteration 800 (1.65694 iter/s, 60.3523s/100 iter), 1.5/232ep, loss = 5.85499
-I0510 14:56:47.787832  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.32266 (* 1 = 5.32266 loss)
-I0510 14:56:47.787853  5307 sgd_solver.cpp:172] Iteration 800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:57:48.278928  5307 solver.cpp:352] Iteration 900 (1.65315 iter/s, 60.4905s/100 iter), 1.7/232ep, loss = 5.92378
-I0510 14:57:48.278992  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.94175 (* 1 = 4.94175 loss)
-I0510 14:57:48.279001  5307 sgd_solver.cpp:172] Iteration 900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:58:48.328603  5307 solver.cpp:352] Iteration 1000 (1.66532 iter/s, 60.0486s/100 iter), 1.9/232ep, loss = 5.526
-I0510 14:58:48.328774  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.45025 (* 1 = 5.45025 loss)
-I0510 14:58:48.328784  5307 sgd_solver.cpp:172] Iteration 1000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:58:58.570034  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 14:59:48.448968  5307 solver.cpp:352] Iteration 1100 (1.66336 iter/s, 60.1193s/100 iter), 2.1/232ep, loss = 5.69474
-I0510 14:59:48.449040  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.50119 (* 1 = 5.50119 loss)
-I0510 14:59:48.449049  5307 sgd_solver.cpp:172] Iteration 1100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:00:48.629653  5307 solver.cpp:352] Iteration 1200 (1.66169 iter/s, 60.1796s/100 iter), 2.3/232ep, loss = 5.57004
-I0510 15:00:48.629717  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.65429 (* 1 = 5.65429 loss)
-I0510 15:00:48.629725  5307 sgd_solver.cpp:172] Iteration 1200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:01:49.735715  5307 solver.cpp:352] Iteration 1300 (1.63653 iter/s, 61.1049s/100 iter), 2.5/232ep, loss = 5.30555
-I0510 15:01:49.735811  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.14266 (* 1 = 5.14266 loss)
-I0510 15:01:49.735837  5307 sgd_solver.cpp:172] Iteration 1300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:02:49.690517  5307 solver.cpp:352] Iteration 1400 (1.66795 iter/s, 59.9537s/100 iter), 2.7/232ep, loss = 5.25238
-I0510 15:02:49.690871  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.66859 (* 1 = 4.66859 loss)
-I0510 15:02:49.690878  5307 sgd_solver.cpp:172] Iteration 1400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:03:50.002152  5307 solver.cpp:352] Iteration 1500 (1.65809 iter/s, 60.3105s/100 iter), 2.9/232ep, loss = 5.29437
-I0510 15:03:50.002264  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.88893 (* 1 = 4.88893 loss)
-I0510 15:03:50.002279  5307 sgd_solver.cpp:172] Iteration 1500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:04:09.962220  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:04:51.827756  5307 solver.cpp:352] Iteration 1600 (1.61748 iter/s, 61.8245s/100 iter), 3.1/232ep, loss = 5.31895
-I0510 15:04:51.827807  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.96819 (* 1 = 4.96819 loss)
-I0510 15:04:51.827816  5307 sgd_solver.cpp:172] Iteration 1600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:05:53.059509  5307 solver.cpp:352] Iteration 1700 (1.63317 iter/s, 61.2306s/100 iter), 3.3/232ep, loss = 5.27998
-I0510 15:05:53.059577  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.47371 (* 1 = 4.47371 loss)
-I0510 15:05:53.059587  5307 sgd_solver.cpp:172] Iteration 1700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:06:53.011014  5307 solver.cpp:352] Iteration 1800 (1.66805 iter/s, 59.9504s/100 iter), 3.5/232ep, loss = 5.39397
-I0510 15:06:53.011147  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.32477 (* 1 = 5.32477 loss)
-I0510 15:06:53.011168  5307 sgd_solver.cpp:172] Iteration 1800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:07:52.740694  5307 solver.cpp:352] Iteration 1900 (1.67424 iter/s, 59.7286s/100 iter), 3.7/232ep, loss = 5.28387
-I0510 15:07:52.741019  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.91122 (* 1 = 4.91122 loss)
-I0510 15:07:52.741029  5307 sgd_solver.cpp:172] Iteration 1900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:08:52.557755  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_2000.caffemodel
-I0510 15:08:52.587344  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_2000.solverstate
-I0510 15:08:52.593171  5307 solver.cpp:635] Iteration 2000, Testing net (#0)
-I0510 15:09:36.971422  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:09:37.205752  5307 solver.cpp:747] class AP 1: 0.241176
-I0510 15:09:37.205962  5307 solver.cpp:747] class AP 2: 0.276057
-I0510 15:09:37.207545  5307 solver.cpp:747] class AP 3: 0.14808
-I0510 15:09:37.208468  5307 solver.cpp:747] class AP 4: 0.104791
-I0510 15:09:37.210508  5307 solver.cpp:747] class AP 5: 0.00422833
-I0510 15:09:37.210934  5307 solver.cpp:747] class AP 6: 0.308869
-I0510 15:09:37.216711  5307 solver.cpp:747] class AP 7: 0.388322
-I0510 15:09:37.217422  5307 solver.cpp:747] class AP 8: 0.392466
-I0510 15:09:37.275566  5307 solver.cpp:747] class AP 9: 0.135234
-I0510 15:09:37.276011  5307 solver.cpp:747] class AP 10: 0.146175
-I0510 15:09:37.276978  5307 solver.cpp:747] class AP 11: 0.059112
-I0510 15:09:37.277819  5307 solver.cpp:747] class AP 12: 0.288268
-I0510 15:09:37.278260  5307 solver.cpp:747] class AP 13: 0.337969
-I0510 15:09:37.278450  5307 solver.cpp:747] class AP 14: 0.24926
-I0510 15:09:37.347717  5307 solver.cpp:747] class AP 15: 0.433317
-I0510 15:09:37.347993  5307 solver.cpp:747] class AP 16: 0.0127273
-I0510 15:09:37.348687  5307 solver.cpp:747] class AP 17: 0.19425
-I0510 15:09:37.349203  5307 solver.cpp:747] class AP 18: 0.166066
-I0510 15:09:37.349592  5307 solver.cpp:747] class AP 19: 0.265589
-I0510 15:09:37.351342  5307 solver.cpp:747] class AP 20: 0.112928
-I0510 15:09:37.351349  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.213244
-I0510 15:09:37.351563  5307 solver.cpp:283] Tests completed in 104.609s
-I0510 15:09:37.907531  5307 solver.cpp:352] Iteration 2000 (0.955941 iter/s, 104.609s/100 iter), 3.9/232ep, loss = 5.1678
-I0510 15:09:37.907558  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.39318 (* 1 = 5.39318 loss)
-I0510 15:09:37.907567  5307 sgd_solver.cpp:172] Iteration 2000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:10:08.820240  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:10:37.929075  5307 solver.cpp:352] Iteration 2100 (1.6661 iter/s, 60.0204s/100 iter), 4.1/232ep, loss = 5.23718
-I0510 15:10:37.929100  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.6325 (* 1 = 4.6325 loss)
-I0510 15:10:37.929107  5307 sgd_solver.cpp:172] Iteration 2100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:11:38.703663  5307 solver.cpp:352] Iteration 2200 (1.64545 iter/s, 60.7735s/100 iter), 4.3/232ep, loss = 5.204
-I0510 15:11:38.703722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.60013 (* 1 = 5.60013 loss)
-I0510 15:11:38.703730  5307 sgd_solver.cpp:172] Iteration 2200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:12:38.392817  5307 solver.cpp:352] Iteration 2300 (1.67538 iter/s, 59.6881s/100 iter), 4.4/232ep, loss = 5.23689
-I0510 15:12:38.392879  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.4605 (* 1 = 5.4605 loss)
-I0510 15:12:38.392889  5307 sgd_solver.cpp:172] Iteration 2300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:13:39.239018  5307 solver.cpp:352] Iteration 2400 (1.64352 iter/s, 60.8451s/100 iter), 4.6/232ep, loss = 4.8862
-I0510 15:13:39.239135  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.68924 (* 1 = 4.68924 loss)
-I0510 15:13:39.239411  5307 sgd_solver.cpp:172] Iteration 2400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:14:40.495874  5307 solver.cpp:352] Iteration 2500 (1.6325 iter/s, 61.2558s/100 iter), 4.8/232ep, loss = 4.9742
-I0510 15:14:40.495930  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.79053 (* 1 = 5.79053 loss)
-I0510 15:14:40.495941  5307 sgd_solver.cpp:172] Iteration 2500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:15:22.295766  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:15:41.688493  5307 solver.cpp:352] Iteration 2600 (1.63421 iter/s, 61.1915s/100 iter), 5/232ep, loss = 5.10483
-I0510 15:15:41.688520  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.85971 (* 1 = 4.85971 loss)
-I0510 15:15:41.688539  5307 sgd_solver.cpp:172] Iteration 2600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:16:42.982174  5307 solver.cpp:352] Iteration 2700 (1.63152 iter/s, 61.2926s/100 iter), 5.2/232ep, loss = 5.12771
-I0510 15:16:42.982233  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.38579 (* 1 = 4.38579 loss)
-I0510 15:16:42.982241  5307 sgd_solver.cpp:172] Iteration 2700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:17:43.821645  5307 solver.cpp:352] Iteration 2800 (1.6437 iter/s, 60.8384s/100 iter), 5.4/232ep, loss = 4.86479
-I0510 15:17:43.821764  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.85436 (* 1 = 4.85436 loss)
-I0510 15:17:43.821818  5307 sgd_solver.cpp:172] Iteration 2800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:18:44.342092  5307 solver.cpp:352] Iteration 2900 (1.65236 iter/s, 60.5194s/100 iter), 5.6/232ep, loss = 4.99139
-I0510 15:18:44.342231  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.15122 (* 1 = 5.15122 loss)
-I0510 15:18:44.342245  5307 sgd_solver.cpp:172] Iteration 2900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:19:46.351919  5307 solver.cpp:352] Iteration 3000 (1.61268 iter/s, 62.0087s/100 iter), 5.8/232ep, loss = 4.95241
-I0510 15:19:46.352030  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.45109 (* 1 = 4.45109 loss)
-I0510 15:19:46.352042  5307 sgd_solver.cpp:172] Iteration 3000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:20:38.992974  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:20:48.269686  5307 solver.cpp:352] Iteration 3100 (1.61507 iter/s, 61.9167s/100 iter), 6/232ep, loss = 5.13158
-I0510 15:20:48.269755  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.02616 (* 1 = 5.02616 loss)
-I0510 15:20:48.269775  5307 sgd_solver.cpp:172] Iteration 3100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:21:50.193011  5307 solver.cpp:352] Iteration 3200 (1.61493 iter/s, 61.9222s/100 iter), 6.2/232ep, loss = 4.95878
-I0510 15:21:50.193161  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.99084 (* 1 = 4.99084 loss)
-I0510 15:21:50.193187  5307 sgd_solver.cpp:172] Iteration 3200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:22:52.971943  5307 solver.cpp:352] Iteration 3300 (1.59292 iter/s, 62.7777s/100 iter), 6.4/232ep, loss = 4.71981
-I0510 15:22:52.972044  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.98499 (* 1 = 4.98499 loss)
-I0510 15:22:52.972054  5307 sgd_solver.cpp:172] Iteration 3300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:23:54.334111  5307 solver.cpp:352] Iteration 3400 (1.6297 iter/s, 61.3611s/100 iter), 6.6/232ep, loss = 4.78574
-I0510 15:23:54.334228  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49641 (* 1 = 4.49641 loss)
-I0510 15:23:54.334244  5307 sgd_solver.cpp:172] Iteration 3400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:24:55.895929  5307 solver.cpp:352] Iteration 3500 (1.62441 iter/s, 61.5607s/100 iter), 6.8/232ep, loss = 4.77709
-I0510 15:24:55.897032  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.93638 (* 1 = 4.93638 loss)
-I0510 15:24:55.897043  5307 sgd_solver.cpp:172] Iteration 3500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:25:56.356941  5307 solver.cpp:352] Iteration 3600 (1.65399 iter/s, 60.4599s/100 iter), 7/232ep, loss = 4.90801
-I0510 15:25:56.358294  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.33671 (* 1 = 4.33671 loss)
-I0510 15:25:56.358317  5307 sgd_solver.cpp:172] Iteration 3600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:25:58.086321  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:26:57.752619  5307 solver.cpp:352] Iteration 3700 (1.62881 iter/s, 61.3946s/100 iter), 7.2/232ep, loss = 4.89432
-I0510 15:26:57.752725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.51655 (* 1 = 4.51655 loss)
-I0510 15:26:57.752748  5307 sgd_solver.cpp:172] Iteration 3700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:27:59.361323  5307 solver.cpp:352] Iteration 3800 (1.62318 iter/s, 61.6076s/100 iter), 7.3/232ep, loss = 4.72437
-I0510 15:27:59.364637  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02982 (* 1 = 4.02982 loss)
-I0510 15:27:59.364663  5307 sgd_solver.cpp:172] Iteration 3800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:29:00.746966  5307 solver.cpp:352] Iteration 3900 (1.62908 iter/s, 61.3845s/100 iter), 7.5/232ep, loss = 4.54618
-I0510 15:29:00.752626  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.57019 (* 1 = 4.57019 loss)
-I0510 15:29:00.752717  5307 sgd_solver.cpp:172] Iteration 3900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:30:01.201730  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_4000.caffemodel
-I0510 15:30:01.218586  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_4000.solverstate
-I0510 15:30:01.223902  5307 solver.cpp:635] Iteration 4000, Testing net (#0)
-I0510 15:30:45.120575  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:30:45.351639  5307 solver.cpp:747] class AP 1: 0.206601
-I0510 15:30:45.352443  5307 solver.cpp:747] class AP 2: 0.367045
-I0510 15:30:45.355480  5307 solver.cpp:747] class AP 3: 0.230397
-I0510 15:30:45.356767  5307 solver.cpp:747] class AP 4: 0.135427
-I0510 15:30:45.374042  5307 solver.cpp:747] class AP 5: 0.0700225
-I0510 15:30:45.374305  5307 solver.cpp:747] class AP 6: 0.389016
-I0510 15:30:45.376086  5307 solver.cpp:747] class AP 7: 0.423877
-I0510 15:30:45.376555  5307 solver.cpp:747] class AP 8: 0.466201
-I0510 15:30:45.418108  5307 solver.cpp:747] class AP 9: 0.152882
-I0510 15:30:45.418695  5307 solver.cpp:747] class AP 10: 0.224414
-I0510 15:30:45.420948  5307 solver.cpp:747] class AP 11: 0.260761
-I0510 15:30:45.421463  5307 solver.cpp:747] class AP 12: 0.367263
-I0510 15:30:45.421973  5307 solver.cpp:747] class AP 13: 0.403105
-I0510 15:30:45.422230  5307 solver.cpp:747] class AP 14: 0.355312
-I0510 15:30:45.484895  5307 solver.cpp:747] class AP 15: 0.501333
-I0510 15:30:45.488716  5307 solver.cpp:747] class AP 16: 0.0390343
-I0510 15:30:45.490855  5307 solver.cpp:747] class AP 17: 0.256806
-I0510 15:30:45.492317  5307 solver.cpp:747] class AP 18: 0.220857
-I0510 15:30:45.492729  5307 solver.cpp:747] class AP 19: 0.323311
-I0510 15:30:45.493448  5307 solver.cpp:747] class AP 20: 0.171304
-I0510 15:30:45.493455  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.278248
-I0510 15:30:45.493628  5307 solver.cpp:283] Tests completed in 104.745s
-I0510 15:30:46.064640  5307 solver.cpp:352] Iteration 4000 (0.954702 iter/s, 104.745s/100 iter), 7.7/232ep, loss = 4.75776
-I0510 15:30:46.064726  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.69811 (* 1 = 4.69811 loss)
-I0510 15:30:46.064749  5307 sgd_solver.cpp:172] Iteration 4000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:31:46.889731  5307 solver.cpp:352] Iteration 4100 (1.64409 iter/s, 60.824s/100 iter), 7.9/232ep, loss = 4.62315
-I0510 15:31:46.889819  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65004 (* 1 = 3.65004 loss)
-I0510 15:31:46.889827  5307 sgd_solver.cpp:172] Iteration 4100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:31:58.322438  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:32:47.780087  5307 solver.cpp:352] Iteration 4200 (1.64233 iter/s, 60.8892s/100 iter), 8.1/232ep, loss = 4.93722
-I0510 15:32:47.780309  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.30114 (* 1 = 4.30114 loss)
-I0510 15:32:47.780371  5307 sgd_solver.cpp:172] Iteration 4200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:33:48.548478  5307 solver.cpp:352] Iteration 4300 (1.64562 iter/s, 60.7673s/100 iter), 8.3/232ep, loss = 4.73264
-I0510 15:33:48.548557  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.864 (* 1 = 4.864 loss)
-I0510 15:33:48.548565  5307 sgd_solver.cpp:172] Iteration 4300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:34:49.456447  5307 solver.cpp:352] Iteration 4400 (1.64185 iter/s, 60.9069s/100 iter), 8.5/232ep, loss = 4.58244
-I0510 15:34:49.456498  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41459 (* 1 = 4.41459 loss)
-I0510 15:34:49.456506  5307 sgd_solver.cpp:172] Iteration 4400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:35:49.381788  5307 solver.cpp:352] Iteration 4500 (1.66877 iter/s, 59.9243s/100 iter), 8.7/232ep, loss = 4.66685
-I0510 15:35:49.381906  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.01909 (* 1 = 4.01909 loss)
-I0510 15:35:49.381916  5307 sgd_solver.cpp:172] Iteration 4500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:36:50.129918  5307 solver.cpp:352] Iteration 4600 (1.64617 iter/s, 60.747s/100 iter), 8.9/232ep, loss = 4.64371
-I0510 15:36:50.131379  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.87533 (* 1 = 4.87533 loss)
-I0510 15:36:50.131404  5307 sgd_solver.cpp:172] Iteration 4600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:37:12.411576  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:37:49.867966  5307 solver.cpp:352] Iteration 4700 (1.674 iter/s, 59.737s/100 iter), 9.1/232ep, loss = 4.62321
-I0510 15:37:49.868119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 6.32694 (* 1 = 6.32694 loss)
-I0510 15:37:49.868136  5307 sgd_solver.cpp:172] Iteration 4700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:38:50.386214  5307 solver.cpp:352] Iteration 4800 (1.65242 iter/s, 60.5172s/100 iter), 9.3/232ep, loss = 4.515
-I0510 15:38:50.386273  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.09599 (* 1 = 4.09599 loss)
-I0510 15:38:50.386282  5307 sgd_solver.cpp:172] Iteration 4800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:39:51.384122  5307 solver.cpp:352] Iteration 4900 (1.63943 iter/s, 60.9968s/100 iter), 9.5/232ep, loss = 4.58634
-I0510 15:39:51.384201  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49087 (* 1 = 4.49087 loss)
-I0510 15:39:51.384210  5307 sgd_solver.cpp:172] Iteration 4900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:40:51.456099  5307 solver.cpp:352] Iteration 5000 (1.6647 iter/s, 60.0709s/100 iter), 9.7/232ep, loss = 4.79531
-I0510 15:40:51.461995  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.5938 (* 1 = 4.5938 loss)
-I0510 15:40:51.462021  5307 sgd_solver.cpp:172] Iteration 5000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:41:52.329574  5307 solver.cpp:352] Iteration 5100 (1.64278 iter/s, 60.8724s/100 iter), 9.9/232ep, loss = 4.69331
-I0510 15:41:52.329661  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.59687 (* 1 = 4.59687 loss)
-I0510 15:41:52.329679  5307 sgd_solver.cpp:172] Iteration 5100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:42:25.642316  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:42:52.869071  5307 solver.cpp:352] Iteration 5200 (1.65184 iter/s, 60.5384s/100 iter), 10.1/232ep, loss = 4.61058
-I0510 15:42:52.869096  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73034 (* 1 = 3.73034 loss)
-I0510 15:42:52.869102  5307 sgd_solver.cpp:172] Iteration 5200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:43:53.011672  5307 solver.cpp:352] Iteration 5300 (1.66274 iter/s, 60.1415s/100 iter), 10.2/232ep, loss = 4.53749
-I0510 15:43:53.016227  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06435 (* 1 = 4.06435 loss)
-I0510 15:43:53.016248  5307 sgd_solver.cpp:172] Iteration 5300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:44:52.968842  5307 solver.cpp:352] Iteration 5400 (1.66789 iter/s, 59.9561s/100 iter), 10.4/232ep, loss = 4.64367
-I0510 15:44:52.969082  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.59465 (* 1 = 4.59465 loss)
-I0510 15:44:52.969095  5307 sgd_solver.cpp:172] Iteration 5400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:45:53.614475  5307 solver.cpp:352] Iteration 5500 (1.64895 iter/s, 60.6446s/100 iter), 10.6/232ep, loss = 4.76142
-I0510 15:45:53.614565  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.71894 (* 1 = 4.71894 loss)
-I0510 15:45:53.614584  5307 sgd_solver.cpp:172] Iteration 5500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:46:54.232838  5307 solver.cpp:352] Iteration 5600 (1.6497 iter/s, 60.6173s/100 iter), 10.8/232ep, loss = 4.59661
-I0510 15:46:54.232895  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.42444 (* 1 = 3.42444 loss)
-I0510 15:46:54.232906  5307 sgd_solver.cpp:172] Iteration 5600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:47:37.166826  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:47:54.647212  5307 solver.cpp:352] Iteration 5700 (1.65527 iter/s, 60.4133s/100 iter), 11/232ep, loss = 4.50432
-I0510 15:47:54.647388  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91722 (* 1 = 3.91722 loss)
-I0510 15:47:54.647413  5307 sgd_solver.cpp:172] Iteration 5700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:48:54.521733  5307 solver.cpp:352] Iteration 5800 (1.67019 iter/s, 59.8734s/100 iter), 11.2/232ep, loss = 4.55135
-I0510 15:48:54.521875  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.27885 (* 1 = 5.27885 loss)
-I0510 15:48:54.521898  5307 sgd_solver.cpp:172] Iteration 5800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:49:54.036702  5307 solver.cpp:352] Iteration 5900 (1.68028 iter/s, 59.5139s/100 iter), 11.4/232ep, loss = 4.54151
-I0510 15:49:54.036756  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00221 (* 1 = 4.00221 loss)
-I0510 15:49:54.036764  5307 sgd_solver.cpp:172] Iteration 5900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:50:53.529439  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_6000.caffemodel
-I0510 15:50:53.545519  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_6000.solverstate
-I0510 15:50:53.550115  5307 solver.cpp:635] Iteration 6000, Testing net (#0)
-I0510 15:51:35.765430  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:51:36.005661  5307 solver.cpp:747] class AP 1: 0.343603
-I0510 15:51:36.005951  5307 solver.cpp:747] class AP 2: 0.339176
-I0510 15:51:36.008163  5307 solver.cpp:747] class AP 3: 0.200234
-I0510 15:51:36.009189  5307 solver.cpp:747] class AP 4: 0.132322
-I0510 15:51:36.045416  5307 solver.cpp:747] class AP 5: 0.143882
-I0510 15:51:36.045706  5307 solver.cpp:747] class AP 6: 0.421355
-I0510 15:51:36.047044  5307 solver.cpp:747] class AP 7: 0.482913
-I0510 15:51:36.047725  5307 solver.cpp:747] class AP 8: 0.503616
-I0510 15:51:36.076642  5307 solver.cpp:747] class AP 9: 0.170713
-I0510 15:51:36.076894  5307 solver.cpp:747] class AP 10: 0.266493
-I0510 15:51:36.078565  5307 solver.cpp:747] class AP 11: 0.231238
-I0510 15:51:36.080288  5307 solver.cpp:747] class AP 12: 0.375903
-I0510 15:51:36.080466  5307 solver.cpp:747] class AP 13: 0.504411
-I0510 15:51:36.080862  5307 solver.cpp:747] class AP 14: 0.371008
-I0510 15:51:36.137048  5307 solver.cpp:747] class AP 15: 0.498699
-I0510 15:51:36.140677  5307 solver.cpp:747] class AP 16: 0.0532492
-I0510 15:51:36.142189  5307 solver.cpp:747] class AP 17: 0.250349
-I0510 15:51:36.143249  5307 solver.cpp:747] class AP 18: 0.233757
-I0510 15:51:36.143421  5307 solver.cpp:747] class AP 19: 0.337436
-I0510 15:51:36.144233  5307 solver.cpp:747] class AP 20: 0.298036
-I0510 15:51:36.144239  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.30792
-I0510 15:51:36.144384  5307 solver.cpp:283] Tests completed in 102.106s
-I0510 15:51:36.718585  5307 solver.cpp:352] Iteration 6000 (0.979376 iter/s, 102.106s/100 iter), 11.6/232ep, loss = 4.49617
-I0510 15:51:36.718739  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89786 (* 1 = 3.89786 loss)
-I0510 15:51:36.718768  5307 sgd_solver.cpp:172] Iteration 6000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:52:36.928555  5307 solver.cpp:352] Iteration 6100 (1.66089 iter/s, 60.2088s/100 iter), 11.8/232ep, loss = 4.57125
-I0510 15:52:36.928704  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78149 (* 1 = 3.78149 loss)
-I0510 15:52:36.928714  5307 sgd_solver.cpp:172] Iteration 6100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:53:30.810858  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:53:37.308396  5307 solver.cpp:352] Iteration 6200 (1.65621 iter/s, 60.3787s/100 iter), 12/232ep, loss = 4.49143
-I0510 15:53:37.308425  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49279 (* 1 = 4.49279 loss)
-I0510 15:53:37.308434  5307 sgd_solver.cpp:172] Iteration 6200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:54:37.473292  5307 solver.cpp:352] Iteration 6300 (1.66213 iter/s, 60.1638s/100 iter), 12.2/232ep, loss = 4.48289
-I0510 15:54:37.473388  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.74283 (* 1 = 4.74283 loss)
-I0510 15:54:37.473410  5307 sgd_solver.cpp:172] Iteration 6300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:55:37.702651  5307 solver.cpp:352] Iteration 6400 (1.66035 iter/s, 60.2283s/100 iter), 12.4/232ep, loss = 4.56006
-I0510 15:55:37.702899  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.82329 (* 1 = 4.82329 loss)
-I0510 15:55:37.702926  5307 sgd_solver.cpp:172] Iteration 6400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:56:37.662981  5307 solver.cpp:352] Iteration 6500 (1.6678 iter/s, 59.9593s/100 iter), 12.6/232ep, loss = 4.48101
-I0510 15:56:37.663030  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.19505 (* 1 = 4.19505 loss)
-I0510 15:56:37.663039  5307 sgd_solver.cpp:172] Iteration 6500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:57:36.854810  5307 solver.cpp:352] Iteration 6600 (1.68945 iter/s, 59.1908s/100 iter), 12.8/232ep, loss = 4.38066
-I0510 15:57:36.855403  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.18159 (* 1 = 4.18159 loss)
-I0510 15:57:36.855425  5307 sgd_solver.cpp:172] Iteration 6600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:58:44.572839  5307 solver.cpp:352] Iteration 6700 (1.47674 iter/s, 67.7168s/100 iter), 13/232ep, loss = 4.418
-I0510 15:58:44.572919  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.71588 (* 1 = 4.71588 loss)
-I0510 15:58:44.572929  5307 sgd_solver.cpp:172] Iteration 6700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:58:48.144181  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:59:47.231030  5307 solver.cpp:352] Iteration 6800 (1.59599 iter/s, 62.6571s/100 iter), 13.1/232ep, loss = 4.3694
-I0510 15:59:47.231144  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.31186 (* 1 = 4.31186 loss)
-I0510 15:59:47.231168  5307 sgd_solver.cpp:172] Iteration 6800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:00:47.528723  5307 solver.cpp:352] Iteration 6900 (1.65847 iter/s, 60.2966s/100 iter), 13.3/232ep, loss = 4.40375
-I0510 16:00:47.529601  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.53692 (* 1 = 5.53692 loss)
-I0510 16:00:47.529611  5307 sgd_solver.cpp:172] Iteration 6900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:01:47.887481  5307 solver.cpp:352] Iteration 7000 (1.65679 iter/s, 60.3577s/100 iter), 13.5/232ep, loss = 4.29458
-I0510 16:01:47.887647  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.5077 (* 1 = 4.5077 loss)
-I0510 16:01:47.887661  5307 sgd_solver.cpp:172] Iteration 7000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:02:48.194983  5307 solver.cpp:352] Iteration 7100 (1.6582 iter/s, 60.3065s/100 iter), 13.7/232ep, loss = 4.34698
-I0510 16:02:48.195036  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.99513 (* 1 = 3.99513 loss)
-I0510 16:02:48.195044  5307 sgd_solver.cpp:172] Iteration 7100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:03:47.820672  5307 solver.cpp:352] Iteration 7200 (1.67716 iter/s, 59.6247s/100 iter), 13.9/232ep, loss = 4.21892
-I0510 16:03:47.820744  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91532 (* 1 = 3.91532 loss)
-I0510 16:03:47.820753  5307 sgd_solver.cpp:172] Iteration 7200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:04:01.660982  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:04:48.659145  5307 solver.cpp:352] Iteration 7300 (1.64373 iter/s, 60.8374s/100 iter), 14.1/232ep, loss = 4.43065
-I0510 16:04:48.659251  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.29698 (* 1 = 4.29698 loss)
-I0510 16:04:48.659278  5307 sgd_solver.cpp:172] Iteration 7300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:05:48.998246  5307 solver.cpp:352] Iteration 7400 (1.65733 iter/s, 60.338s/100 iter), 14.3/232ep, loss = 4.41088
-I0510 16:05:48.998353  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.48164 (* 1 = 3.48164 loss)
-I0510 16:05:48.998364  5307 sgd_solver.cpp:172] Iteration 7400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:06:49.963078  5307 solver.cpp:352] Iteration 7500 (1.64032 iter/s, 60.9638s/100 iter), 14.5/232ep, loss = 4.42881
-I0510 16:06:49.963234  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.26356 (* 1 = 4.26356 loss)
-I0510 16:06:49.963246  5307 sgd_solver.cpp:172] Iteration 7500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:07:51.170918  5307 solver.cpp:352] Iteration 7600 (1.63381 iter/s, 61.2068s/100 iter), 14.7/232ep, loss = 4.38766
-I0510 16:07:51.171381  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.86193 (* 1 = 4.86193 loss)
-I0510 16:07:51.171404  5307 sgd_solver.cpp:172] Iteration 7600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:08:52.659510  5307 solver.cpp:352] Iteration 7700 (1.62635 iter/s, 61.4875s/100 iter), 14.9/232ep, loss = 4.28137
-I0510 16:08:52.659694  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95457 (* 1 = 3.95457 loss)
-I0510 16:08:52.659721  5307 sgd_solver.cpp:172] Iteration 7700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:09:17.163449  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:09:53.273126  5307 solver.cpp:352] Iteration 7800 (1.64982 iter/s, 60.6125s/100 iter), 15.1/232ep, loss = 4.28748
-I0510 16:09:53.273193  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.74378 (* 1 = 4.74378 loss)
-I0510 16:09:53.273202  5307 sgd_solver.cpp:172] Iteration 7800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:10:53.718170  5307 solver.cpp:352] Iteration 7900 (1.65443 iter/s, 60.444s/100 iter), 15.3/232ep, loss = 4.48724
-I0510 16:10:53.718232  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.72057 (* 1 = 4.72057 loss)
-I0510 16:10:53.718240  5307 sgd_solver.cpp:172] Iteration 7900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:11:53.707036  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_8000.caffemodel
-I0510 16:11:53.729109  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_8000.solverstate
-I0510 16:11:53.735050  5307 solver.cpp:635] Iteration 8000, Testing net (#0)
-I0510 16:12:35.622887  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:12:35.819828  5307 solver.cpp:747] class AP 1: 0.187161
-I0510 16:12:35.819895  5307 solver.cpp:747] class AP 2: 0.132867
-I0510 16:12:35.820551  5307 solver.cpp:747] class AP 3: 0.093213
-I0510 16:12:35.822451  5307 solver.cpp:747] class AP 4: 0.134172
-I0510 16:12:35.833393  5307 solver.cpp:747] class AP 5: 0.116078
-I0510 16:12:35.833920  5307 solver.cpp:747] class AP 6: 0.18732
-I0510 16:12:35.843909  5307 solver.cpp:747] class AP 7: 0.326991
-I0510 16:12:35.844079  5307 solver.cpp:747] class AP 8: 0.380603
-I0510 16:12:35.871490  5307 solver.cpp:747] class AP 9: 0.0880095
-I0510 16:12:35.871589  5307 solver.cpp:747] class AP 10: 0.23624
-I0510 16:12:35.871991  5307 solver.cpp:747] class AP 11: 0.147733
-I0510 16:12:35.872153  5307 solver.cpp:747] class AP 12: 0.253221
-I0510 16:12:35.872205  5307 solver.cpp:747] class AP 13: 0.174242
-I0510 16:12:35.872351  5307 solver.cpp:747] class AP 14: 0.146544
-I0510 16:12:36.012958  5307 solver.cpp:747] class AP 15: 0.278914
-I0510 16:12:36.013765  5307 solver.cpp:747] class AP 16: 0.0510046
-I0510 16:12:36.014111  5307 solver.cpp:747] class AP 17: 0.115495
-I0510 16:12:36.015322  5307 solver.cpp:747] class AP 18: 0.170786
-I0510 16:12:36.015656  5307 solver.cpp:747] class AP 19: 0.274256
-I0510 16:12:36.022532  5307 solver.cpp:747] class AP 20: 0.157187
-I0510 16:12:36.022603  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.182602
-I0510 16:12:36.023149  5307 solver.cpp:283] Tests completed in 102.303s
-I0510 16:12:36.587702  5307 solver.cpp:352] Iteration 8000 (0.977487 iter/s, 102.303s/100 iter), 15.5/232ep, loss = 4.39346
-I0510 16:12:36.587725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.59318 (* 1 = 5.59318 loss)
-I0510 16:12:36.587734  5307 sgd_solver.cpp:172] Iteration 8000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:13:36.125911  5307 solver.cpp:352] Iteration 8100 (1.67963 iter/s, 59.5371s/100 iter), 15.7/232ep, loss = 4.40548
-I0510 16:13:36.126049  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.30731 (* 1 = 4.30731 loss)
-I0510 16:13:36.126067  5307 sgd_solver.cpp:172] Iteration 8100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:14:37.028736  5307 solver.cpp:352] Iteration 8200 (1.64199 iter/s, 60.9017s/100 iter), 15.9/232ep, loss = 4.36387
-I0510 16:14:37.028792  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.04558 (* 1 = 4.04558 loss)
-I0510 16:14:37.028800  5307 sgd_solver.cpp:172] Iteration 8200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:15:11.105940  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:15:37.020285  5307 solver.cpp:352] Iteration 8300 (1.66693 iter/s, 59.9904s/100 iter), 16/232ep, loss = 4.31154
-I0510 16:15:37.020372  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.1889 (* 1 = 5.1889 loss)
-I0510 16:15:37.020390  5307 sgd_solver.cpp:172] Iteration 8300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:16:37.154593  5307 solver.cpp:352] Iteration 8400 (1.66297 iter/s, 60.1332s/100 iter), 16.2/232ep, loss = 4.4104
-I0510 16:16:37.154779  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.68552 (* 1 = 4.68552 loss)
-I0510 16:16:37.154812  5307 sgd_solver.cpp:172] Iteration 8400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:17:38.530937  5307 solver.cpp:352] Iteration 8500 (1.62932 iter/s, 61.3753s/100 iter), 16.4/232ep, loss = 4.27246
-I0510 16:17:38.531033  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4225 (* 1 = 3.4225 loss)
-I0510 16:17:38.531054  5307 sgd_solver.cpp:172] Iteration 8500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:18:39.009922  5307 solver.cpp:352] Iteration 8600 (1.6535 iter/s, 60.4779s/100 iter), 16.6/232ep, loss = 4.39125
-I0510 16:18:39.010030  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.33212 (* 1 = 4.33212 loss)
-I0510 16:18:39.010053  5307 sgd_solver.cpp:172] Iteration 8600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:19:40.334738  5307 solver.cpp:352] Iteration 8700 (1.63069 iter/s, 61.3237s/100 iter), 16.8/232ep, loss = 4.33689
-I0510 16:19:40.335502  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.9013 (* 1 = 4.9013 loss)
-I0510 16:19:40.335515  5307 sgd_solver.cpp:172] Iteration 8700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:20:26.046443  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:20:41.286645  5307 solver.cpp:352] Iteration 8800 (1.64067 iter/s, 60.9509s/100 iter), 17/232ep, loss = 4.26008
-I0510 16:20:41.286676  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.38479 (* 1 = 5.38479 loss)
-I0510 16:20:41.286685  5307 sgd_solver.cpp:172] Iteration 8800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:21:41.783578  5307 solver.cpp:352] Iteration 8900 (1.65301 iter/s, 60.4959s/100 iter), 17.2/232ep, loss = 4.10042
-I0510 16:21:41.783674  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54616 (* 1 = 3.54616 loss)
-I0510 16:21:41.783684  5307 sgd_solver.cpp:172] Iteration 8900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:22:43.384639  5307 solver.cpp:352] Iteration 9000 (1.62338 iter/s, 61.6s/100 iter), 17.4/232ep, loss = 4.29836
-I0510 16:22:43.384814  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.46384 (* 1 = 4.46384 loss)
-I0510 16:22:43.384824  5307 sgd_solver.cpp:172] Iteration 9000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:23:44.433280  5307 solver.cpp:352] Iteration 9100 (1.63807 iter/s, 61.0476s/100 iter), 17.6/232ep, loss = 4.13168
-I0510 16:23:44.433372  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.40502 (* 1 = 4.40502 loss)
-I0510 16:23:44.433382  5307 sgd_solver.cpp:172] Iteration 9100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:24:46.060052  5307 solver.cpp:352] Iteration 9200 (1.6227 iter/s, 61.6257s/100 iter), 17.8/232ep, loss = 4.21399
-I0510 16:24:46.060153  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.21245 (* 1 = 4.21245 loss)
-I0510 16:24:46.060163  5307 sgd_solver.cpp:172] Iteration 9200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:25:42.008615  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:25:47.175756  5307 solver.cpp:352] Iteration 9300 (1.63627 iter/s, 61.1146s/100 iter), 18/232ep, loss = 4.42703
-I0510 16:25:47.175787  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93399 (* 1 = 3.93399 loss)
-I0510 16:25:47.175796  5307 sgd_solver.cpp:172] Iteration 9300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:26:48.714920  5307 solver.cpp:352] Iteration 9400 (1.62501 iter/s, 61.5381s/100 iter), 18.2/232ep, loss = 4.3202
-I0510 16:26:48.715634  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.67566 (* 1 = 4.67566 loss)
-I0510 16:26:48.715649  5307 sgd_solver.cpp:172] Iteration 9400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:27:49.669996  5307 solver.cpp:352] Iteration 9500 (1.64058 iter/s, 60.954s/100 iter), 18.4/232ep, loss = 4.3158
-I0510 16:27:49.670137  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.50218 (* 1 = 4.50218 loss)
-I0510 16:27:49.670156  5307 sgd_solver.cpp:172] Iteration 9500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:28:50.534543  5307 solver.cpp:352] Iteration 9600 (1.64302 iter/s, 60.8635s/100 iter), 18.6/232ep, loss = 4.31481
-I0510 16:28:50.534724  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.78233 (* 1 = 4.78233 loss)
-I0510 16:28:50.534744  5307 sgd_solver.cpp:172] Iteration 9600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:29:52.043104  5307 solver.cpp:352] Iteration 9700 (1.62582 iter/s, 61.5075s/100 iter), 18.8/232ep, loss = 4.26232
-I0510 16:29:52.044564  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.77904 (* 1 = 3.77904 loss)
-I0510 16:29:52.044596  5307 sgd_solver.cpp:172] Iteration 9700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:30:52.859931  5307 solver.cpp:352] Iteration 9800 (1.64431 iter/s, 60.8158s/100 iter), 18.9/232ep, loss = 4.17125
-I0510 16:30:52.860009  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84245 (* 1 = 3.84245 loss)
-I0510 16:30:52.860018  5307 sgd_solver.cpp:172] Iteration 9800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:30:58.494596  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:31:53.523766  5307 solver.cpp:352] Iteration 9900 (1.64846 iter/s, 60.6627s/100 iter), 19.1/232ep, loss = 4.19495
-I0510 16:31:53.523844  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.45795 (* 1 = 4.45795 loss)
-I0510 16:31:53.523854  5307 sgd_solver.cpp:172] Iteration 9900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:32:53.689491  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_10000.caffemodel
-I0510 16:32:53.705381  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_10000.solverstate
-I0510 16:32:53.710855  5307 solver.cpp:635] Iteration 10000, Testing net (#0)
-I0510 16:33:35.652021  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:33:35.887356  5307 solver.cpp:747] class AP 1: 0.378373
-I0510 16:33:35.887681  5307 solver.cpp:747] class AP 2: 0.446617
-I0510 16:33:35.890889  5307 solver.cpp:747] class AP 3: 0.323297
-I0510 16:33:35.893777  5307 solver.cpp:747] class AP 4: 0.22195
-I0510 16:33:35.909973  5307 solver.cpp:747] class AP 5: 0.127367
-I0510 16:33:35.910291  5307 solver.cpp:747] class AP 6: 0.42865
-I0510 16:33:35.913208  5307 solver.cpp:747] class AP 7: 0.439762
-I0510 16:33:35.913678  5307 solver.cpp:747] class AP 8: 0.564868
-I0510 16:33:35.935222  5307 solver.cpp:747] class AP 9: 0.217799
-I0510 16:33:35.935350  5307 solver.cpp:747] class AP 10: 0.278676
-I0510 16:33:35.936563  5307 solver.cpp:747] class AP 11: 0.347657
-I0510 16:33:35.937006  5307 solver.cpp:747] class AP 12: 0.462001
-I0510 16:33:35.937166  5307 solver.cpp:747] class AP 13: 0.457945
-I0510 16:33:35.937306  5307 solver.cpp:747] class AP 14: 0.48744
-I0510 16:33:36.011561  5307 solver.cpp:747] class AP 15: 0.539054
-I0510 16:33:36.020725  5307 solver.cpp:747] class AP 16: 0.150607
-I0510 16:33:36.021001  5307 solver.cpp:747] class AP 17: 0.341589
-I0510 16:33:36.021291  5307 solver.cpp:747] class AP 18: 0.307463
-I0510 16:33:36.021807  5307 solver.cpp:747] class AP 19: 0.426576
-I0510 16:33:36.023761  5307 solver.cpp:747] class AP 20: 0.277367
-I0510 16:33:36.023767  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.361253
-I0510 16:33:36.023957  5307 solver.cpp:283] Tests completed in 102.498s
-I0510 16:33:36.602188  5307 solver.cpp:352] Iteration 10000 (0.975625 iter/s, 102.498s/100 iter), 19.3/232ep, loss = 4.38477
-I0510 16:33:36.602257  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.72253 (* 1 = 4.72253 loss)
-I0510 16:33:36.602274  5307 sgd_solver.cpp:172] Iteration 10000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:34:38.145097  5307 solver.cpp:352] Iteration 10100 (1.62491 iter/s, 61.5418s/100 iter), 19.5/232ep, loss = 4.14872
-I0510 16:34:38.145155  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.9657 (* 1 = 3.9657 loss)
-I0510 16:34:38.145354  5307 sgd_solver.cpp:172] Iteration 10100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:35:39.481259  5307 solver.cpp:352] Iteration 10200 (1.63039 iter/s, 61.335s/100 iter), 19.7/232ep, loss = 4.3917
-I0510 16:35:39.481500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11003 (* 1 = 4.11003 loss)
-I0510 16:35:39.481559  5307 sgd_solver.cpp:172] Iteration 10200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:36:40.322700  5307 solver.cpp:352] Iteration 10300 (1.64365 iter/s, 60.8404s/100 iter), 19.9/232ep, loss = 4.11278
-I0510 16:36:40.322809  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95169 (* 1 = 3.95169 loss)
-I0510 16:36:40.322818  5307 sgd_solver.cpp:172] Iteration 10300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:36:56.879952  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:37:41.590212  5307 solver.cpp:352] Iteration 10400 (1.63222 iter/s, 61.2664s/100 iter), 20.1/232ep, loss = 4.2348
-I0510 16:37:41.590725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0292 (* 1 = 4.0292 loss)
-I0510 16:37:41.590734  5307 sgd_solver.cpp:172] Iteration 10400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:38:42.635974  5307 solver.cpp:352] Iteration 10500 (1.63814 iter/s, 61.0447s/100 iter), 20.3/232ep, loss = 4.43859
-I0510 16:38:42.636080  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.53269 (* 1 = 4.53269 loss)
-I0510 16:38:42.636142  5307 sgd_solver.cpp:172] Iteration 10500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:39:43.396457  5307 solver.cpp:352] Iteration 10600 (1.64584 iter/s, 60.7594s/100 iter), 20.5/232ep, loss = 4.08796
-I0510 16:39:43.396561  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.48421 (* 1 = 4.48421 loss)
-I0510 16:39:43.396579  5307 sgd_solver.cpp:172] Iteration 10600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:40:44.580492  5307 solver.cpp:352] Iteration 10700 (1.63444 iter/s, 61.183s/100 iter), 20.7/232ep, loss = 4.25233
-I0510 16:40:44.582834  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41945 (* 1 = 3.41945 loss)
-I0510 16:40:44.582845  5307 sgd_solver.cpp:172] Iteration 10700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:41:46.095185  5307 solver.cpp:352] Iteration 10800 (1.62566 iter/s, 61.5136s/100 iter), 20.9/232ep, loss = 4.1095
-I0510 16:41:46.095281  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.14543 (* 1 = 5.14543 loss)
-I0510 16:41:46.095299  5307 sgd_solver.cpp:172] Iteration 10800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:42:12.404253  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:42:47.050778  5307 solver.cpp:352] Iteration 10900 (1.64057 iter/s, 60.9545s/100 iter), 21.1/232ep, loss = 4.19932
-I0510 16:42:47.050837  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.53899 (* 1 = 4.53899 loss)
-I0510 16:42:47.050843  5307 sgd_solver.cpp:172] Iteration 10900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:43:48.170625  5307 solver.cpp:352] Iteration 11000 (1.63616 iter/s, 61.1188s/100 iter), 21.3/232ep, loss = 4.08915
-I0510 16:43:48.170718  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.08948 (* 1 = 4.08948 loss)
-I0510 16:43:48.170742  5307 sgd_solver.cpp:172] Iteration 11000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:44:48.368515  5307 solver.cpp:352] Iteration 11100 (1.66122 iter/s, 60.1968s/100 iter), 21.5/232ep, loss = 3.97626
-I0510 16:44:48.368626  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.17662 (* 1 = 4.17662 loss)
-I0510 16:44:48.368635  5307 sgd_solver.cpp:172] Iteration 11100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:45:48.322374  5307 solver.cpp:352] Iteration 11200 (1.66798 iter/s, 59.9528s/100 iter), 21.7/232ep, loss = 4.23018
-I0510 16:45:48.322760  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64182 (* 1 = 3.64182 loss)
-I0510 16:45:48.322772  5307 sgd_solver.cpp:172] Iteration 11200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:46:48.441637  5307 solver.cpp:352] Iteration 11300 (1.66339 iter/s, 60.1182s/100 iter), 21.8/232ep, loss = 4.2839
-I0510 16:46:48.441692  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20155 (* 1 = 3.20155 loss)
-I0510 16:46:48.441699  5307 sgd_solver.cpp:172] Iteration 11300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:47:25.483207  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:47:49.252192  5307 solver.cpp:352] Iteration 11400 (1.64448 iter/s, 60.8095s/100 iter), 22/232ep, loss = 4.16623
-I0510 16:47:49.252215  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13885 (* 1 = 3.13885 loss)
-I0510 16:47:49.252223  5307 sgd_solver.cpp:172] Iteration 11400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:48:50.116747  5307 solver.cpp:352] Iteration 11500 (1.64302 iter/s, 60.8635s/100 iter), 22.2/232ep, loss = 4.14411
-I0510 16:48:50.116850  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.16257 (* 1 = 4.16257 loss)
-I0510 16:48:50.116873  5307 sgd_solver.cpp:172] Iteration 11500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:49:51.222333  5307 solver.cpp:352] Iteration 11600 (1.63654 iter/s, 61.1045s/100 iter), 22.4/232ep, loss = 4.14758
-I0510 16:49:51.222458  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.1045 (* 1 = 4.1045 loss)
-I0510 16:49:51.222470  5307 sgd_solver.cpp:172] Iteration 11600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:50:52.188690  5307 solver.cpp:352] Iteration 11700 (1.64028 iter/s, 60.9653s/100 iter), 22.6/232ep, loss = 4.45619
-I0510 16:50:52.188776  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.1889 (* 1 = 5.1889 loss)
-I0510 16:50:52.188787  5307 sgd_solver.cpp:172] Iteration 11700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:51:53.544272  5307 solver.cpp:352] Iteration 11800 (1.62987 iter/s, 61.3545s/100 iter), 22.8/232ep, loss = 4.10034
-I0510 16:51:53.544347  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.12696 (* 1 = 4.12696 loss)
-I0510 16:51:53.544355  5307 sgd_solver.cpp:172] Iteration 11800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:52:40.321614  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:52:54.253976  5307 solver.cpp:352] Iteration 11900 (1.64721 iter/s, 60.7086s/100 iter), 23/232ep, loss = 4.27672
-I0510 16:52:54.254007  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.39659 (* 1 = 4.39659 loss)
-I0510 16:52:54.254089  5307 sgd_solver.cpp:172] Iteration 11900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:53:53.266656  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_12000.caffemodel
-I0510 16:53:53.284037  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_12000.solverstate
-I0510 16:53:53.289765  5307 solver.cpp:635] Iteration 12000, Testing net (#0)
-I0510 16:54:34.372668  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:54:34.597332  5307 solver.cpp:747] class AP 1: 0.377338
-I0510 16:54:34.598632  5307 solver.cpp:747] class AP 2: 0.473243
-I0510 16:54:34.606649  5307 solver.cpp:747] class AP 3: 0.28361
-I0510 16:54:34.609349  5307 solver.cpp:747] class AP 4: 0.236268
-I0510 16:54:34.614091  5307 solver.cpp:747] class AP 5: 0.154874
-I0510 16:54:34.614581  5307 solver.cpp:747] class AP 6: 0.430217
-I0510 16:54:34.625377  5307 solver.cpp:747] class AP 7: 0.498381
-I0510 16:54:34.625912  5307 solver.cpp:747] class AP 8: 0.514091
-I0510 16:54:34.643224  5307 solver.cpp:747] class AP 9: 0.185966
-I0510 16:54:34.643985  5307 solver.cpp:747] class AP 10: 0.279618
-I0510 16:54:34.644327  5307 solver.cpp:747] class AP 11: 0.260463
-I0510 16:54:34.645735  5307 solver.cpp:747] class AP 12: 0.434783
-I0510 16:54:34.646425  5307 solver.cpp:747] class AP 13: 0.544954
-I0510 16:54:34.646972  5307 solver.cpp:747] class AP 14: 0.511976
-I0510 16:54:34.737347  5307 solver.cpp:747] class AP 15: 0.500064
-I0510 16:54:34.738363  5307 solver.cpp:747] class AP 16: 0.167407
-I0510 16:54:34.741420  5307 solver.cpp:747] class AP 17: 0.288721
-I0510 16:54:34.741683  5307 solver.cpp:747] class AP 18: 0.227028
-I0510 16:54:34.742285  5307 solver.cpp:747] class AP 19: 0.392775
-I0510 16:54:34.742945  5307 solver.cpp:747] class AP 20: 0.278508
-I0510 16:54:34.742951  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.352014
-I0510 16:54:34.743127  5307 solver.cpp:283] Tests completed in 100.487s
-I0510 16:54:35.285920  5307 solver.cpp:352] Iteration 12000 (0.99515 iter/s, 100.487s/100 iter), 23.2/232ep, loss = 4.13124
-I0510 16:54:35.285944  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.88816 (* 1 = 3.88816 loss)
-I0510 16:54:35.285953  5307 sgd_solver.cpp:172] Iteration 12000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:55:34.848623  5307 solver.cpp:352] Iteration 12100 (1.67893 iter/s, 59.5616s/100 iter), 23.4/232ep, loss = 3.97695
-I0510 16:55:34.848683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20505 (* 1 = 3.20505 loss)
-I0510 16:55:34.848691  5307 sgd_solver.cpp:172] Iteration 12100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:56:35.011502  5307 solver.cpp:352] Iteration 12200 (1.66219 iter/s, 60.1617s/100 iter), 23.6/232ep, loss = 4.0189
-I0510 16:56:35.012388  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4049 (* 1 = 3.4049 loss)
-I0510 16:56:35.012408  5307 sgd_solver.cpp:172] Iteration 12200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:57:35.002763  5307 solver.cpp:352] Iteration 12300 (1.66694 iter/s, 59.9902s/100 iter), 23.8/232ep, loss = 4.05656
-I0510 16:57:35.003190  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.29515 (* 1 = 4.29515 loss)
-I0510 16:57:35.003201  5307 sgd_solver.cpp:172] Iteration 12300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:58:32.893283  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:58:35.812647  5307 solver.cpp:352] Iteration 12400 (1.6445 iter/s, 60.8088s/100 iter), 24/232ep, loss = 4.24311
-I0510 16:58:35.812897  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02051 (* 1 = 4.02051 loss)
-I0510 16:58:35.812952  5307 sgd_solver.cpp:172] Iteration 12400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:59:37.592346  5307 solver.cpp:352] Iteration 12500 (1.61868 iter/s, 61.7786s/100 iter), 24.2/232ep, loss = 4.08884
-I0510 16:59:37.596276  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82929 (* 1 = 3.82929 loss)
-I0510 16:59:37.596339  5307 sgd_solver.cpp:172] Iteration 12500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:00:38.686198  5307 solver.cpp:352] Iteration 12600 (1.63686 iter/s, 61.0928s/100 iter), 24.4/232ep, loss = 4.14987
-I0510 17:00:38.686290  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.31445 (* 1 = 4.31445 loss)
-I0510 17:00:38.686305  5307 sgd_solver.cpp:172] Iteration 12600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:01:38.478579  5307 solver.cpp:352] Iteration 12700 (1.67248 iter/s, 59.7913s/100 iter), 24.6/232ep, loss = 3.97729
-I0510 17:01:38.479331  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.01469 (* 1 = 4.01469 loss)
-I0510 17:01:38.479349  5307 sgd_solver.cpp:172] Iteration 12700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:02:39.137495  5307 solver.cpp:352] Iteration 12800 (1.64859 iter/s, 60.6578s/100 iter), 24.7/232ep, loss = 4.10032
-I0510 17:02:39.137583  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.73172 (* 1 = 4.73172 loss)
-I0510 17:02:39.137591  5307 sgd_solver.cpp:172] Iteration 12800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:03:39.246263  5307 solver.cpp:352] Iteration 12900 (1.66368 iter/s, 60.1077s/100 iter), 24.9/232ep, loss = 4.03988
-I0510 17:03:39.246330  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.31536 (* 1 = 4.31536 loss)
-I0510 17:03:39.246340  5307 sgd_solver.cpp:172] Iteration 12900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:03:47.180572  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:04:40.025022  5307 solver.cpp:352] Iteration 13000 (1.64534 iter/s, 60.7777s/100 iter), 25.1/232ep, loss = 4.02856
-I0510 17:04:40.025166  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68971 (* 1 = 3.68971 loss)
-I0510 17:04:40.025225  5307 sgd_solver.cpp:172] Iteration 13000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:05:40.191223  5307 solver.cpp:352] Iteration 13100 (1.66209 iter/s, 60.1651s/100 iter), 25.3/232ep, loss = 4.16508
-I0510 17:05:40.191306  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49254 (* 1 = 4.49254 loss)
-I0510 17:05:40.191313  5307 sgd_solver.cpp:172] Iteration 13100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:06:48.350085  5307 solver.cpp:352] Iteration 13200 (1.46719 iter/s, 68.1577s/100 iter), 25.5/232ep, loss = 4.01508
-I0510 17:06:48.354142  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.76144 (* 1 = 4.76144 loss)
-I0510 17:06:48.354167  5307 sgd_solver.cpp:172] Iteration 13200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:07:53.096518  5307 solver.cpp:352] Iteration 13300 (1.54451 iter/s, 64.7453s/100 iter), 25.7/232ep, loss = 4.15617
-I0510 17:07:53.096621  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.55177 (* 1 = 4.55177 loss)
-I0510 17:07:53.096631  5307 sgd_solver.cpp:172] Iteration 13300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:08:52.704501  5307 solver.cpp:352] Iteration 13400 (1.67766 iter/s, 59.6069s/100 iter), 25.9/232ep, loss = 4.03562
-I0510 17:08:52.704582  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56205 (* 1 = 3.56205 loss)
-I0510 17:08:52.704591  5307 sgd_solver.cpp:172] Iteration 13400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:09:10.333612  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:09:53.295830  5307 solver.cpp:352] Iteration 13500 (1.65043 iter/s, 60.5903s/100 iter), 26.1/232ep, loss = 4.18251
-I0510 17:09:53.295914  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89812 (* 1 = 3.89812 loss)
-I0510 17:09:53.295923  5307 sgd_solver.cpp:172] Iteration 13500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:10:53.762625  5307 solver.cpp:352] Iteration 13600 (1.65383 iter/s, 60.4657s/100 iter), 26.3/232ep, loss = 4.3044
-I0510 17:10:53.762749  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.40704 (* 1 = 4.40704 loss)
-I0510 17:10:53.762779  5307 sgd_solver.cpp:172] Iteration 13600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:11:53.526618  5307 solver.cpp:352] Iteration 13700 (1.67328 iter/s, 59.763s/100 iter), 26.5/232ep, loss = 4.05516
-I0510 17:11:53.526890  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.48273 (* 1 = 4.48273 loss)
-I0510 17:11:53.526914  5307 sgd_solver.cpp:172] Iteration 13700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:12:54.021212  5307 solver.cpp:352] Iteration 13800 (1.65307 iter/s, 60.4935s/100 iter), 26.7/232ep, loss = 4.13883
-I0510 17:12:54.023648  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82784 (* 1 = 3.82784 loss)
-I0510 17:12:54.023679  5307 sgd_solver.cpp:172] Iteration 13800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:13:53.147681  5307 solver.cpp:352] Iteration 13900 (1.69132 iter/s, 59.1254s/100 iter), 26.9/232ep, loss = 3.92843
-I0510 17:13:53.147752  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.15256 (* 1 = 5.15256 loss)
-I0510 17:13:53.147760  5307 sgd_solver.cpp:172] Iteration 13900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:14:21.294966  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:14:53.081138  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_14000.caffemodel
-I0510 17:14:53.106668  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_14000.solverstate
-I0510 17:14:53.115489  5307 solver.cpp:635] Iteration 14000, Testing net (#0)
-I0510 17:15:36.413102  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:15:36.644253  5307 solver.cpp:747] class AP 1: 0.26767
-I0510 17:15:36.644846  5307 solver.cpp:747] class AP 2: 0.521108
-I0510 17:15:36.645982  5307 solver.cpp:747] class AP 3: 0.190442
-I0510 17:15:36.649343  5307 solver.cpp:747] class AP 4: 0.209313
-I0510 17:15:36.675809  5307 solver.cpp:747] class AP 5: 0.196156
-I0510 17:15:36.676244  5307 solver.cpp:747] class AP 6: 0.524823
-I0510 17:15:36.684424  5307 solver.cpp:747] class AP 7: 0.544608
-I0510 17:15:36.684862  5307 solver.cpp:747] class AP 8: 0.460104
-I0510 17:15:36.702005  5307 solver.cpp:747] class AP 9: 0.141894
-I0510 17:15:36.702060  5307 solver.cpp:747] class AP 10: 0.171285
-I0510 17:15:36.704457  5307 solver.cpp:747] class AP 11: 0.324904
-I0510 17:15:36.704716  5307 solver.cpp:747] class AP 12: 0.356893
-I0510 17:15:36.704767  5307 solver.cpp:747] class AP 13: 0.244357
-I0510 17:15:36.705610  5307 solver.cpp:747] class AP 14: 0.572795
-I0510 17:15:36.763828  5307 solver.cpp:747] class AP 15: 0.551995
-I0510 17:15:36.782464  5307 solver.cpp:747] class AP 16: 0.160565
-I0510 17:15:36.782575  5307 solver.cpp:747] class AP 17: 0.262686
-I0510 17:15:36.783303  5307 solver.cpp:747] class AP 18: 0.248361
-I0510 17:15:36.783385  5307 solver.cpp:747] class AP 19: 0.502314
-I0510 17:15:36.785104  5307 solver.cpp:747] class AP 20: 0.379687
-I0510 17:15:36.785117  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.341598
-I0510 17:15:36.785410  5307 solver.cpp:283] Tests completed in 103.636s
-I0510 17:15:37.416332  5307 solver.cpp:352] Iteration 14000 (0.964917 iter/s, 103.636s/100 iter), 27.1/232ep, loss = 4.10391
-I0510 17:15:37.416354  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.94686 (* 1 = 3.94686 loss)
-I0510 17:15:37.416363  5307 sgd_solver.cpp:172] Iteration 14000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:16:38.509384  5307 solver.cpp:352] Iteration 14100 (1.63688 iter/s, 61.0919s/100 iter), 27.3/232ep, loss = 4.0748
-I0510 17:16:38.509459  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.024 (* 1 = 4.024 loss)
-I0510 17:16:38.509469  5307 sgd_solver.cpp:172] Iteration 14100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:17:39.031899  5307 solver.cpp:352] Iteration 14200 (1.65231 iter/s, 60.5214s/100 iter), 27.5/232ep, loss = 4.04891
-I0510 17:17:39.031961  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.72282 (* 1 = 4.72282 loss)
-I0510 17:17:39.031971  5307 sgd_solver.cpp:172] Iteration 14200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:18:39.693130  5307 solver.cpp:352] Iteration 14300 (1.64853 iter/s, 60.6601s/100 iter), 27.6/232ep, loss = 4.06177
-I0510 17:18:39.693199  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.31345 (* 1 = 4.31345 loss)
-I0510 17:18:39.693244  5307 sgd_solver.cpp:172] Iteration 14300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:19:40.746486  5307 solver.cpp:352] Iteration 14400 (1.63794 iter/s, 61.0523s/100 iter), 27.8/232ep, loss = 4.2231
-I0510 17:19:40.746574  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.62917 (* 1 = 4.62917 loss)
-I0510 17:19:40.746584  5307 sgd_solver.cpp:172] Iteration 14400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:20:20.180049  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:20:41.706598  5307 solver.cpp:352] Iteration 14500 (1.64045 iter/s, 60.959s/100 iter), 28/232ep, loss = 3.993
-I0510 17:20:41.706683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.50615 (* 1 = 4.50615 loss)
-I0510 17:20:41.706708  5307 sgd_solver.cpp:172] Iteration 14500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:21:42.623369  5307 solver.cpp:352] Iteration 14600 (1.64161 iter/s, 60.9157s/100 iter), 28.2/232ep, loss = 4.06883
-I0510 17:21:42.623472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08766 (* 1 = 3.08766 loss)
-I0510 17:21:42.623486  5307 sgd_solver.cpp:172] Iteration 14600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:22:43.666040  5307 solver.cpp:352] Iteration 14700 (1.63823 iter/s, 61.0416s/100 iter), 28.4/232ep, loss = 3.97623
-I0510 17:22:43.666119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33782 (* 1 = 3.33782 loss)
-I0510 17:22:43.666136  5307 sgd_solver.cpp:172] Iteration 14700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:23:44.337112  5307 solver.cpp:352] Iteration 14800 (1.64826 iter/s, 60.67s/100 iter), 28.6/232ep, loss = 4.22662
-I0510 17:23:44.337558  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.92494 (* 1 = 3.92494 loss)
-I0510 17:23:44.337577  5307 sgd_solver.cpp:172] Iteration 14800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:24:44.634955  5307 solver.cpp:352] Iteration 14900 (1.65846 iter/s, 60.2968s/100 iter), 28.8/232ep, loss = 4.08335
-I0510 17:24:44.635013  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.69729 (* 1 = 4.69729 loss)
-I0510 17:24:44.635020  5307 sgd_solver.cpp:172] Iteration 14900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:25:33.500568  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:25:44.786931  5307 solver.cpp:352] Iteration 15000 (1.66249 iter/s, 60.1509s/100 iter), 29/232ep, loss = 4.09779
-I0510 17:25:44.786994  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80358 (* 1 = 3.80358 loss)
-I0510 17:25:44.787019  5307 sgd_solver.cpp:172] Iteration 15000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:26:45.754842  5307 solver.cpp:352] Iteration 15100 (1.64024 iter/s, 60.9668s/100 iter), 29.2/232ep, loss = 3.83954
-I0510 17:26:45.759059  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.36041 (* 1 = 4.36041 loss)
-I0510 17:26:45.759080  5307 sgd_solver.cpp:172] Iteration 15100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:27:46.087405  5307 solver.cpp:352] Iteration 15200 (1.65751 iter/s, 60.3315s/100 iter), 29.4/232ep, loss = 3.79234
-I0510 17:27:46.087489  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89815 (* 1 = 3.89815 loss)
-I0510 17:27:46.087505  5307 sgd_solver.cpp:172] Iteration 15200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:28:47.248160  5307 solver.cpp:352] Iteration 15300 (1.63506 iter/s, 61.1597s/100 iter), 29.6/232ep, loss = 4.25529
-I0510 17:28:47.248291  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.52093 (* 1 = 4.52093 loss)
-I0510 17:28:47.248311  5307 sgd_solver.cpp:172] Iteration 15300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:29:47.624392  5307 solver.cpp:352] Iteration 15400 (1.65631 iter/s, 60.3752s/100 iter), 29.8/232ep, loss = 3.90185
-I0510 17:29:47.624768  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.14909 (* 1 = 4.14909 loss)
-I0510 17:29:47.624789  5307 sgd_solver.cpp:172] Iteration 15400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:30:47.525804  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:30:48.213439  5307 solver.cpp:352] Iteration 15500 (1.65049 iter/s, 60.588s/100 iter), 30/232ep, loss = 4.31352
-I0510 17:30:48.213562  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.92865 (* 1 = 4.92865 loss)
-I0510 17:30:48.213585  5307 sgd_solver.cpp:172] Iteration 15500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:31:49.500659  5307 solver.cpp:352] Iteration 15600 (1.63169 iter/s, 61.2862s/100 iter), 30.2/232ep, loss = 4.06144
-I0510 17:31:49.500794  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.67102 (* 1 = 4.67102 loss)
-I0510 17:31:49.500823  5307 sgd_solver.cpp:172] Iteration 15600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:32:49.536686  5307 solver.cpp:352] Iteration 15700 (1.6657 iter/s, 60.035s/100 iter), 30.4/232ep, loss = 4.13441
-I0510 17:32:49.537791  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47626 (* 1 = 3.47626 loss)
-I0510 17:32:49.537806  5307 sgd_solver.cpp:172] Iteration 15700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:33:50.337203  5307 solver.cpp:352] Iteration 15800 (1.64475 iter/s, 60.7995s/100 iter), 30.5/232ep, loss = 3.98306
-I0510 17:33:50.337349  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89969 (* 1 = 3.89969 loss)
-I0510 17:33:50.337357  5307 sgd_solver.cpp:172] Iteration 15800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:34:50.994805  5307 solver.cpp:352] Iteration 15900 (1.64863 iter/s, 60.6565s/100 iter), 30.7/232ep, loss = 3.94058
-I0510 17:34:50.995951  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15672 (* 1 = 4.15672 loss)
-I0510 17:34:50.995962  5307 sgd_solver.cpp:172] Iteration 15900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:35:51.081809  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_16000.caffemodel
-I0510 17:35:51.098748  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_16000.solverstate
-I0510 17:35:51.104290  5307 solver.cpp:635] Iteration 16000, Testing net (#0)
-I0510 17:36:33.383131  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:36:33.610116  5307 solver.cpp:747] class AP 1: 0.486965
-I0510 17:36:33.610594  5307 solver.cpp:747] class AP 2: 0.526476
-I0510 17:36:33.614055  5307 solver.cpp:747] class AP 3: 0.364743
-I0510 17:36:33.615774  5307 solver.cpp:747] class AP 4: 0.298434
-I0510 17:36:33.624733  5307 solver.cpp:747] class AP 5: 0.151348
-I0510 17:36:33.625550  5307 solver.cpp:747] class AP 6: 0.594422
-I0510 17:36:33.635076  5307 solver.cpp:747] class AP 7: 0.564054
-I0510 17:36:33.635455  5307 solver.cpp:747] class AP 8: 0.653435
-I0510 17:36:33.657244  5307 solver.cpp:747] class AP 9: 0.246602
-I0510 17:36:33.657665  5307 solver.cpp:747] class AP 10: 0.407204
-I0510 17:36:33.658128  5307 solver.cpp:747] class AP 11: 0.326416
-I0510 17:36:33.659003  5307 solver.cpp:747] class AP 12: 0.557808
-I0510 17:36:33.659384  5307 solver.cpp:747] class AP 13: 0.654049
-I0510 17:36:33.659610  5307 solver.cpp:747] class AP 14: 0.561787
-I0510 17:36:33.743221  5307 solver.cpp:747] class AP 15: 0.609836
-I0510 17:36:33.745687  5307 solver.cpp:747] class AP 16: 0.204773
-I0510 17:36:33.746655  5307 solver.cpp:747] class AP 17: 0.436756
-I0510 17:36:33.747130  5307 solver.cpp:747] class AP 18: 0.468889
-I0510 17:36:33.747989  5307 solver.cpp:747] class AP 19: 0.595545
-I0510 17:36:33.749708  5307 solver.cpp:747] class AP 20: 0.467597
-I0510 17:36:33.749716  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.458857
-I0510 17:36:33.749986  5307 solver.cpp:283] Tests completed in 102.753s
-I0510 17:36:34.340684  5307 solver.cpp:352] Iteration 16000 (0.973204 iter/s, 102.753s/100 iter), 30.9/232ep, loss = 3.82997
-I0510 17:36:34.340775  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73402 (* 1 = 2.73402 loss)
-I0510 17:36:34.340798  5307 sgd_solver.cpp:172] Iteration 16000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:36:43.517487  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:37:35.048465  5307 solver.cpp:352] Iteration 16100 (1.64727 iter/s, 60.7067s/100 iter), 31.1/232ep, loss = 4.22994
-I0510 17:37:35.048614  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.20404 (* 1 = 5.20404 loss)
-I0510 17:37:35.048635  5307 sgd_solver.cpp:172] Iteration 16100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:38:35.793680  5307 solver.cpp:352] Iteration 16200 (1.64625 iter/s, 60.7441s/100 iter), 31.3/232ep, loss = 3.97765
-I0510 17:38:35.793766  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.58101 (* 1 = 4.58101 loss)
-I0510 17:38:35.793776  5307 sgd_solver.cpp:172] Iteration 16200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:39:35.721940  5307 solver.cpp:352] Iteration 16300 (1.66869 iter/s, 59.9272s/100 iter), 31.5/232ep, loss = 3.78574
-I0510 17:39:35.722015  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.64567 (* 1 = 4.64567 loss)
-I0510 17:39:35.722024  5307 sgd_solver.cpp:172] Iteration 16300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:40:35.965342  5307 solver.cpp:352] Iteration 16400 (1.65996 iter/s, 60.2423s/100 iter), 31.7/232ep, loss = 3.97578
-I0510 17:40:35.965407  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22316 (* 1 = 3.22316 loss)
-I0510 17:40:35.965415  5307 sgd_solver.cpp:172] Iteration 16400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:41:37.109102  5307 solver.cpp:352] Iteration 16500 (1.63552 iter/s, 61.1426s/100 iter), 31.9/232ep, loss = 3.84236
-I0510 17:41:37.112644  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.35575 (* 1 = 4.35575 loss)
-I0510 17:41:37.112681  5307 sgd_solver.cpp:172] Iteration 16500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:41:57.559957  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:42:38.290222  5307 solver.cpp:352] Iteration 16600 (1.63452 iter/s, 61.18s/100 iter), 32.1/232ep, loss = 3.9832
-I0510 17:42:38.290297  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06678 (* 1 = 4.06678 loss)
-I0510 17:42:38.290305  5307 sgd_solver.cpp:172] Iteration 16600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:43:39.620643  5307 solver.cpp:352] Iteration 16700 (1.63054 iter/s, 61.3293s/100 iter), 32.3/232ep, loss = 3.93954
-I0510 17:43:39.620726  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65763 (* 1 = 3.65763 loss)
-I0510 17:43:39.620740  5307 sgd_solver.cpp:172] Iteration 16700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:44:40.493341  5307 solver.cpp:352] Iteration 16800 (1.6428 iter/s, 60.8716s/100 iter), 32.5/232ep, loss = 4.09846
-I0510 17:44:40.493398  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68261 (* 1 = 3.68261 loss)
-I0510 17:44:40.493405  5307 sgd_solver.cpp:172] Iteration 16800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:45:41.239418  5307 solver.cpp:352] Iteration 16900 (1.64623 iter/s, 60.745s/100 iter), 32.7/232ep, loss = 3.76668
-I0510 17:45:41.239538  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.29666 (* 1 = 3.29666 loss)
-I0510 17:45:41.239555  5307 sgd_solver.cpp:172] Iteration 16900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:46:42.703081  5307 solver.cpp:352] Iteration 17000 (1.62701 iter/s, 61.4626s/100 iter), 32.9/232ep, loss = 3.9525
-I0510 17:46:42.703943  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58665 (* 1 = 3.58665 loss)
-I0510 17:46:42.703951  5307 sgd_solver.cpp:172] Iteration 17000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:47:13.536533  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:47:43.672152  5307 solver.cpp:352] Iteration 17100 (1.64021 iter/s, 60.968s/100 iter), 33.1/232ep, loss = 4.24186
-I0510 17:47:43.672236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.35574 (* 1 = 4.35574 loss)
-I0510 17:47:43.672252  5307 sgd_solver.cpp:172] Iteration 17100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:48:44.434834  5307 solver.cpp:352] Iteration 17200 (1.64578 iter/s, 60.7616s/100 iter), 33.3/232ep, loss = 4.11966
-I0510 17:48:44.434926  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3499 (* 1 = 3.3499 loss)
-I0510 17:48:44.434934  5307 sgd_solver.cpp:172] Iteration 17200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:49:45.975968  5307 solver.cpp:352] Iteration 17300 (1.62496 iter/s, 61.54s/100 iter), 33.4/232ep, loss = 3.93047
-I0510 17:49:45.976122  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.90535 (* 1 = 3.90535 loss)
-I0510 17:49:45.976135  5307 sgd_solver.cpp:172] Iteration 17300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:50:46.313288  5307 solver.cpp:352] Iteration 17400 (1.65738 iter/s, 60.3363s/100 iter), 33.6/232ep, loss = 3.95524
-I0510 17:50:46.315484  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67539 (* 1 = 3.67539 loss)
-I0510 17:50:46.315497  5307 sgd_solver.cpp:172] Iteration 17400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:51:47.110417  5307 solver.cpp:352] Iteration 17500 (1.64484 iter/s, 60.7961s/100 iter), 33.8/232ep, loss = 4.11225
-I0510 17:51:47.110472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.59651 (* 1 = 4.59651 loss)
-I0510 17:51:47.110479  5307 sgd_solver.cpp:172] Iteration 17500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:52:27.470515  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:52:47.254881  5307 solver.cpp:352] Iteration 17600 (1.66269 iter/s, 60.1434s/100 iter), 34/232ep, loss = 4.07409
-I0510 17:52:47.254906  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87837 (* 1 = 3.87837 loss)
-I0510 17:52:47.254914  5307 sgd_solver.cpp:172] Iteration 17600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:53:47.585824  5307 solver.cpp:352] Iteration 17700 (1.65755 iter/s, 60.3299s/100 iter), 34.2/232ep, loss = 4.09266
-I0510 17:53:47.585917  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.20773 (* 1 = 4.20773 loss)
-I0510 17:53:47.585937  5307 sgd_solver.cpp:172] Iteration 17700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:54:49.169430  5307 solver.cpp:352] Iteration 17800 (1.62384 iter/s, 61.5825s/100 iter), 34.4/232ep, loss = 4.06271
-I0510 17:54:49.169489  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.08636 (* 1 = 4.08636 loss)
-I0510 17:54:49.169497  5307 sgd_solver.cpp:172] Iteration 17800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:55:51.290794  5307 solver.cpp:352] Iteration 17900 (1.60978 iter/s, 62.1203s/100 iter), 34.6/232ep, loss = 3.95755
-I0510 17:55:51.290895  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02087 (* 1 = 4.02087 loss)
-I0510 17:55:51.290905  5307 sgd_solver.cpp:172] Iteration 17900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:56:51.971354  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_18000.caffemodel
-I0510 17:56:51.990205  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_18000.solverstate
-I0510 17:56:51.995992  5307 solver.cpp:635] Iteration 18000, Testing net (#0)
-I0510 17:57:33.766407  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:57:33.960752  5307 solver.cpp:747] class AP 1: 0.406091
-I0510 17:57:33.961108  5307 solver.cpp:747] class AP 2: 0.464497
-I0510 17:57:33.964440  5307 solver.cpp:747] class AP 3: 0.2912
-I0510 17:57:33.965749  5307 solver.cpp:747] class AP 4: 0.207739
-I0510 17:57:33.996084  5307 solver.cpp:747] class AP 5: 0.167533
-I0510 17:57:33.996301  5307 solver.cpp:747] class AP 6: 0.579484
-I0510 17:57:34.003047  5307 solver.cpp:747] class AP 7: 0.549524
-I0510 17:57:34.003806  5307 solver.cpp:747] class AP 8: 0.616621
-I0510 17:57:34.028941  5307 solver.cpp:747] class AP 9: 0.269421
-I0510 17:57:34.029110  5307 solver.cpp:747] class AP 10: 0.293091
-I0510 17:57:34.030127  5307 solver.cpp:747] class AP 11: 0.404158
-I0510 17:57:34.030670  5307 solver.cpp:747] class AP 12: 0.489255
-I0510 17:57:34.030750  5307 solver.cpp:747] class AP 13: 0.475573
-I0510 17:57:34.031006  5307 solver.cpp:747] class AP 14: 0.444097
-I0510 17:57:34.081130  5307 solver.cpp:747] class AP 15: 0.539198
-I0510 17:57:34.096513  5307 solver.cpp:747] class AP 16: 0.149469
-I0510 17:57:34.096949  5307 solver.cpp:747] class AP 17: 0.370188
-I0510 17:57:34.097833  5307 solver.cpp:747] class AP 18: 0.353684
-I0510 17:57:34.098188  5307 solver.cpp:747] class AP 19: 0.501156
-I0510 17:57:34.101331  5307 solver.cpp:747] class AP 20: 0.364472
-I0510 17:57:34.101347  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.396823
-I0510 17:57:34.101477  5307 solver.cpp:283] Tests completed in 102.809s
-I0510 17:57:34.706904  5307 solver.cpp:352] Iteration 18000 (0.972679 iter/s, 102.809s/100 iter), 34.8/232ep, loss = 4.1169
-I0510 17:57:34.706931  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.28014 (* 1 = 4.28014 loss)
-I0510 17:57:34.706939  5307 sgd_solver.cpp:172] Iteration 18000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:58:26.168864  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:58:34.832660  5307 solver.cpp:352] Iteration 18100 (1.66321 iter/s, 60.1246s/100 iter), 35/232ep, loss = 4.08924
-I0510 17:58:34.832814  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.48788 (* 1 = 4.48788 loss)
-I0510 17:58:34.832832  5307 sgd_solver.cpp:172] Iteration 18100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:59:35.985110  5307 solver.cpp:352] Iteration 18200 (1.63529 iter/s, 61.1514s/100 iter), 35.2/232ep, loss = 3.75936
-I0510 17:59:35.985201  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16756 (* 1 = 3.16756 loss)
-I0510 17:59:35.985221  5307 sgd_solver.cpp:172] Iteration 18200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:00:36.783682  5307 solver.cpp:352] Iteration 18300 (1.64481 iter/s, 60.7975s/100 iter), 35.4/232ep, loss = 3.86903
-I0510 18:00:36.783763  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.3618 (* 1 = 4.3618 loss)
-I0510 18:00:36.783771  5307 sgd_solver.cpp:172] Iteration 18300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:01:38.399515  5307 solver.cpp:352] Iteration 18400 (1.62299 iter/s, 61.6147s/100 iter), 35.6/232ep, loss = 4.0389
-I0510 18:01:38.399615  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.60873 (* 1 = 3.60873 loss)
-I0510 18:01:38.399624  5307 sgd_solver.cpp:172] Iteration 18400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:02:40.127353  5307 solver.cpp:352] Iteration 18500 (1.62004 iter/s, 61.7267s/100 iter), 35.8/232ep, loss = 3.90535
-I0510 18:02:40.127506  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57586 (* 1 = 3.57586 loss)
-I0510 18:02:40.127534  5307 sgd_solver.cpp:172] Iteration 18500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:03:39.942431  5307 solver.cpp:352] Iteration 18600 (1.67185 iter/s, 59.814s/100 iter), 36/232ep, loss = 3.91408
-I0510 18:03:39.942529  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.13427 (* 1 = 5.13427 loss)
-I0510 18:03:39.942539  5307 sgd_solver.cpp:172] Iteration 18600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:03:40.720665  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:04:39.985424  5307 solver.cpp:352] Iteration 18700 (1.6655 iter/s, 60.0419s/100 iter), 36.2/232ep, loss = 3.97106
-I0510 18:04:39.985500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63197 (* 1 = 3.63197 loss)
-I0510 18:04:39.985510  5307 sgd_solver.cpp:172] Iteration 18700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:05:40.361156  5307 solver.cpp:352] Iteration 18800 (1.65632 iter/s, 60.3746s/100 iter), 36.3/232ep, loss = 3.98146
-I0510 18:05:40.364639  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.842 (* 1 = 4.842 loss)
-I0510 18:05:40.364675  5307 sgd_solver.cpp:172] Iteration 18800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:06:40.600116  5307 solver.cpp:352] Iteration 18900 (1.66008 iter/s, 60.2379s/100 iter), 36.5/232ep, loss = 3.86298
-I0510 18:06:40.600175  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85125 (* 1 = 3.85125 loss)
-I0510 18:06:40.600183  5307 sgd_solver.cpp:172] Iteration 18900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:07:41.151947  5307 solver.cpp:352] Iteration 19000 (1.65151 iter/s, 60.5508s/100 iter), 36.7/232ep, loss = 4.04988
-I0510 18:07:41.152015  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93703 (* 1 = 3.93703 loss)
-I0510 18:07:41.152024  5307 sgd_solver.cpp:172] Iteration 19000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:08:41.814600  5307 solver.cpp:352] Iteration 19100 (1.64849 iter/s, 60.6616s/100 iter), 36.9/232ep, loss = 3.8313
-I0510 18:08:41.815102  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.45588 (* 1 = 4.45588 loss)
-I0510 18:08:41.815121  5307 sgd_solver.cpp:172] Iteration 19100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:08:53.398103  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:09:41.547041  5307 solver.cpp:352] Iteration 19200 (1.67416 iter/s, 59.7314s/100 iter), 37.1/232ep, loss = 3.9092
-I0510 18:09:41.547230  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30575 (* 1 = 3.30575 loss)
-I0510 18:09:41.547346  5307 sgd_solver.cpp:172] Iteration 19200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:10:41.878931  5307 solver.cpp:352] Iteration 19300 (1.65753 iter/s, 60.3308s/100 iter), 37.3/232ep, loss = 4.02067
-I0510 18:10:41.879042  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05662 (* 1 = 4.05662 loss)
-I0510 18:10:41.879062  5307 sgd_solver.cpp:172] Iteration 19300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:11:41.982174  5307 solver.cpp:352] Iteration 19400 (1.66383 iter/s, 60.1022s/100 iter), 37.5/232ep, loss = 3.94155
-I0510 18:11:41.982257  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.74712 (* 1 = 4.74712 loss)
-I0510 18:11:41.982267  5307 sgd_solver.cpp:172] Iteration 19400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:12:42.256016  5307 solver.cpp:352] Iteration 19500 (1.65912 iter/s, 60.2727s/100 iter), 37.7/232ep, loss = 3.96735
-I0510 18:12:42.256213  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91876 (* 1 = 3.91876 loss)
-I0510 18:12:42.256234  5307 sgd_solver.cpp:172] Iteration 19500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:13:42.999758  5307 solver.cpp:352] Iteration 19600 (1.64629 iter/s, 60.7427s/100 iter), 37.9/232ep, loss = 4.12041
-I0510 18:13:42.999848  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56942 (* 1 = 3.56942 loss)
-I0510 18:13:42.999858  5307 sgd_solver.cpp:172] Iteration 19600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:14:06.984825  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:14:50.224472  5307 solver.cpp:352] Iteration 19700 (1.48757 iter/s, 67.2235s/100 iter), 38.1/232ep, loss = 4.04457
-I0510 18:14:50.224571  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.32989 (* 1 = 4.32989 loss)
-I0510 18:14:50.224588  5307 sgd_solver.cpp:172] Iteration 19700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:15:55.267130  5307 solver.cpp:352] Iteration 19800 (1.53748 iter/s, 65.0415s/100 iter), 38.3/232ep, loss = 3.97563
-I0510 18:15:55.267290  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43165 (* 1 = 3.43165 loss)
-I0510 18:15:55.267304  5307 sgd_solver.cpp:172] Iteration 19800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:16:56.501657  5307 solver.cpp:352] Iteration 19900 (1.63309 iter/s, 61.2334s/100 iter), 38.5/232ep, loss = 3.9215
-I0510 18:16:56.501725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38991 (* 1 = 3.38991 loss)
-I0510 18:16:56.501735  5307 sgd_solver.cpp:172] Iteration 19900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:17:55.653561  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_20000.caffemodel
-I0510 18:17:55.693248  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_20000.solverstate
-I0510 18:17:55.697934  5307 solver.cpp:635] Iteration 20000, Testing net (#0)
-I0510 18:18:37.112228  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:18:37.306205  5307 solver.cpp:747] class AP 1: 0.34128
-I0510 18:18:37.306692  5307 solver.cpp:747] class AP 2: 0.466179
-I0510 18:18:37.316076  5307 solver.cpp:747] class AP 3: 0.338858
-I0510 18:18:37.320827  5307 solver.cpp:747] class AP 4: 0.227758
-I0510 18:18:37.331344  5307 solver.cpp:747] class AP 5: 0.208365
-I0510 18:18:37.332031  5307 solver.cpp:747] class AP 6: 0.544774
-I0510 18:18:37.339907  5307 solver.cpp:747] class AP 7: 0.530615
-I0510 18:18:37.341220  5307 solver.cpp:747] class AP 8: 0.540702
-I0510 18:18:37.378499  5307 solver.cpp:747] class AP 9: 0.206761
-I0510 18:18:37.379087  5307 solver.cpp:747] class AP 10: 0.379273
-I0510 18:18:37.379915  5307 solver.cpp:747] class AP 11: 0.333792
-I0510 18:18:37.380676  5307 solver.cpp:747] class AP 12: 0.447937
-I0510 18:18:37.381017  5307 solver.cpp:747] class AP 13: 0.587963
-I0510 18:18:37.381248  5307 solver.cpp:747] class AP 14: 0.473695
-I0510 18:18:37.442178  5307 solver.cpp:747] class AP 15: 0.517321
-I0510 18:18:37.448504  5307 solver.cpp:747] class AP 16: 0.189493
-I0510 18:18:37.452178  5307 solver.cpp:747] class AP 17: 0.361723
-I0510 18:18:37.452957  5307 solver.cpp:747] class AP 18: 0.335269
-I0510 18:18:37.454664  5307 solver.cpp:747] class AP 19: 0.548444
-I0510 18:18:37.459687  5307 solver.cpp:747] class AP 20: 0.405736
-I0510 18:18:37.459728  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.399297
-I0510 18:18:37.460028  5307 solver.cpp:283] Tests completed in 100.957s
-I0510 18:18:38.128073  5307 solver.cpp:352] Iteration 20000 (0.990525 iter/s, 100.957s/100 iter), 38.7/232ep, loss = 3.92276
-I0510 18:18:38.128098  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68845 (* 1 = 3.68845 loss)
-I0510 18:18:38.128104  5307 sgd_solver.cpp:172] Iteration 20000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:19:38.890480  5307 solver.cpp:352] Iteration 20100 (1.64578 iter/s, 60.7613s/100 iter), 38.9/232ep, loss = 3.81434
-I0510 18:19:38.890576  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05766 (* 1 = 4.05766 loss)
-I0510 18:19:38.890584  5307 sgd_solver.cpp:172] Iteration 20100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:20:10.870867  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:20:39.101873  5307 solver.cpp:352] Iteration 20200 (1.66085 iter/s, 60.2103s/100 iter), 39.1/232ep, loss = 3.93665
-I0510 18:20:39.101954  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.36537 (* 1 = 4.36537 loss)
-I0510 18:20:39.101975  5307 sgd_solver.cpp:172] Iteration 20200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:21:39.325006  5307 solver.cpp:352] Iteration 20300 (1.66052 iter/s, 60.2221s/100 iter), 39.2/232ep, loss = 3.84677
-I0510 18:21:39.325109  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61705 (* 1 = 3.61705 loss)
-I0510 18:21:39.325120  5307 sgd_solver.cpp:172] Iteration 20300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:22:39.772847  5307 solver.cpp:352] Iteration 20400 (1.65435 iter/s, 60.4467s/100 iter), 39.4/232ep, loss = 3.83104
-I0510 18:22:39.773057  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03349 (* 1 = 4.03349 loss)
-I0510 18:22:39.773083  5307 sgd_solver.cpp:172] Iteration 20400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:23:39.822788  5307 solver.cpp:352] Iteration 20500 (1.66531 iter/s, 60.0489s/100 iter), 39.6/232ep, loss = 3.87636
-I0510 18:23:39.822922  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.35261 (* 1 = 4.35261 loss)
-I0510 18:23:39.822937  5307 sgd_solver.cpp:172] Iteration 20500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:24:39.488035  5307 solver.cpp:352] Iteration 20600 (1.67605 iter/s, 59.6642s/100 iter), 39.8/232ep, loss = 3.97765
-I0510 18:24:39.488114  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.28101 (* 1 = 4.28101 loss)
-I0510 18:24:39.488124  5307 sgd_solver.cpp:172] Iteration 20600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:25:22.277652  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:25:39.628329  5307 solver.cpp:352] Iteration 20700 (1.66281 iter/s, 60.1392s/100 iter), 40/232ep, loss = 3.92331
-I0510 18:25:39.628352  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61269 (* 1 = 3.61269 loss)
-I0510 18:25:39.628358  5307 sgd_solver.cpp:172] Iteration 20700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:26:39.289927  5307 solver.cpp:352] Iteration 20800 (1.67615 iter/s, 59.6605s/100 iter), 40.2/232ep, loss = 3.75517
-I0510 18:26:39.289999  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53533 (* 1 = 3.53533 loss)
-I0510 18:26:39.290007  5307 sgd_solver.cpp:172] Iteration 20800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:27:40.264546  5307 solver.cpp:352] Iteration 20900 (1.64006 iter/s, 60.9735s/100 iter), 40.4/232ep, loss = 4.09701
-I0510 18:27:40.265084  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93349 (* 1 = 3.93349 loss)
-I0510 18:27:40.265094  5307 sgd_solver.cpp:172] Iteration 20900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:28:41.227520  5307 solver.cpp:352] Iteration 21000 (1.64037 iter/s, 60.9619s/100 iter), 40.6/232ep, loss = 3.9031
-I0510 18:28:41.229018  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82276 (* 1 = 3.82276 loss)
-I0510 18:28:41.229033  5307 sgd_solver.cpp:172] Iteration 21000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:29:41.710839  5307 solver.cpp:352] Iteration 21100 (1.65338 iter/s, 60.4822s/100 iter), 40.8/232ep, loss = 4.0459
-I0510 18:29:41.710918  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.45003 (* 1 = 5.45003 loss)
-I0510 18:29:41.710929  5307 sgd_solver.cpp:172] Iteration 21100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:30:34.003978  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:30:41.507900  5307 solver.cpp:352] Iteration 21200 (1.67235 iter/s, 59.796s/100 iter), 41/232ep, loss = 4.03447
-I0510 18:30:41.507969  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.2517 (* 1 = 4.2517 loss)
-I0510 18:30:41.507989  5307 sgd_solver.cpp:172] Iteration 21200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:31:41.589257  5307 solver.cpp:352] Iteration 21300 (1.66444 iter/s, 60.0803s/100 iter), 41.2/232ep, loss = 4.00796
-I0510 18:31:41.589359  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.64948 (* 1 = 4.64948 loss)
-I0510 18:31:41.589378  5307 sgd_solver.cpp:172] Iteration 21300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:32:41.931206  5307 solver.cpp:352] Iteration 21400 (1.65725 iter/s, 60.3409s/100 iter), 41.4/232ep, loss = 3.80331
-I0510 18:32:41.931308  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65604 (* 1 = 3.65604 loss)
-I0510 18:32:41.931512  5307 sgd_solver.cpp:172] Iteration 21400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:33:42.036473  5307 solver.cpp:352] Iteration 21500 (1.66378 iter/s, 60.1042s/100 iter), 41.6/232ep, loss = 4.00471
-I0510 18:33:42.036576  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.9934 (* 1 = 5.9934 loss)
-I0510 18:33:42.036587  5307 sgd_solver.cpp:172] Iteration 21500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:34:41.460405  5307 solver.cpp:352] Iteration 21600 (1.68285 iter/s, 59.4229s/100 iter), 41.8/232ep, loss = 3.79898
-I0510 18:34:41.460487  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.68195 (* 1 = 4.68195 loss)
-I0510 18:34:41.460497  5307 sgd_solver.cpp:172] Iteration 21600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:35:41.398211  5307 solver.cpp:352] Iteration 21700 (1.66843 iter/s, 59.9368s/100 iter), 42/232ep, loss = 3.8566
-I0510 18:35:41.398293  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.24144 (* 1 = 4.24144 loss)
-I0510 18:35:41.398301  5307 sgd_solver.cpp:172] Iteration 21700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:35:44.294472  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:36:41.684083  5307 solver.cpp:352] Iteration 21800 (1.65879 iter/s, 60.2848s/100 iter), 42.1/232ep, loss = 3.88238
-I0510 18:36:41.684232  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80177 (* 1 = 3.80177 loss)
-I0510 18:36:41.684255  5307 sgd_solver.cpp:172] Iteration 21800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:37:42.083560  5307 solver.cpp:352] Iteration 21900 (1.65567 iter/s, 60.3984s/100 iter), 42.3/232ep, loss = 3.93615
-I0510 18:37:42.083660  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.17012 (* 1 = 3.17012 loss)
-I0510 18:37:42.083669  5307 sgd_solver.cpp:172] Iteration 21900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:38:42.316890  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_22000.caffemodel
-I0510 18:38:42.336257  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_22000.solverstate
-I0510 18:38:42.343206  5307 solver.cpp:635] Iteration 22000, Testing net (#0)
-I0510 18:39:23.263263  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:39:23.482539  5307 solver.cpp:747] class AP 1: 0.530255
-I0510 18:39:23.483283  5307 solver.cpp:747] class AP 2: 0.599847
-I0510 18:39:23.490195  5307 solver.cpp:747] class AP 3: 0.416361
-I0510 18:39:23.492012  5307 solver.cpp:747] class AP 4: 0.327485
-I0510 18:39:23.506052  5307 solver.cpp:747] class AP 5: 0.238198
-I0510 18:39:23.506343  5307 solver.cpp:747] class AP 6: 0.611445
-I0510 18:39:23.512264  5307 solver.cpp:747] class AP 7: 0.597716
-I0510 18:39:23.513100  5307 solver.cpp:747] class AP 8: 0.673315
-I0510 18:39:23.529266  5307 solver.cpp:747] class AP 9: 0.239872
-I0510 18:39:23.530041  5307 solver.cpp:747] class AP 10: 0.456606
-I0510 18:39:23.530591  5307 solver.cpp:747] class AP 11: 0.429406
-I0510 18:39:23.532676  5307 solver.cpp:747] class AP 12: 0.59359
-I0510 18:39:23.533262  5307 solver.cpp:747] class AP 13: 0.692092
-I0510 18:39:23.533761  5307 solver.cpp:747] class AP 14: 0.583687
-I0510 18:39:23.602900  5307 solver.cpp:747] class AP 15: 0.641689
-I0510 18:39:23.609939  5307 solver.cpp:747] class AP 16: 0.227152
-I0510 18:39:23.611941  5307 solver.cpp:747] class AP 17: 0.475418
-I0510 18:39:23.613131  5307 solver.cpp:747] class AP 18: 0.426319
-I0510 18:39:23.614387  5307 solver.cpp:747] class AP 19: 0.632528
-I0510 18:39:23.615263  5307 solver.cpp:747] class AP 20: 0.441181
-I0510 18:39:23.615268  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.491708
-I0510 18:39:23.615408  5307 solver.cpp:283] Tests completed in 101.53s
-I0510 18:39:24.182399  5307 solver.cpp:352] Iteration 22000 (0.98493 iter/s, 101.53s/100 iter), 42.5/232ep, loss = 3.75261
-I0510 18:39:24.182422  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.98661 (* 1 = 3.98661 loss)
-I0510 18:39:24.182430  5307 sgd_solver.cpp:172] Iteration 22000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:40:24.254237  5307 solver.cpp:352] Iteration 22100 (1.6647 iter/s, 60.0707s/100 iter), 42.7/232ep, loss = 3.94477
-I0510 18:40:24.255007  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.10083 (* 1 = 4.10083 loss)
-I0510 18:40:24.255017  5307 sgd_solver.cpp:172] Iteration 22100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:41:25.275432  5307 solver.cpp:352] Iteration 22200 (1.63881 iter/s, 61.0201s/100 iter), 42.9/232ep, loss = 3.93176
-I0510 18:41:25.275652  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.34443 (* 1 = 4.34443 loss)
-I0510 18:41:25.275666  5307 sgd_solver.cpp:172] Iteration 22200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:41:39.151403  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:42:25.048168  5307 solver.cpp:352] Iteration 22300 (1.67303 iter/s, 59.7717s/100 iter), 43.1/232ep, loss = 3.80451
-I0510 18:42:25.048316  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.18245 (* 1 = 3.18245 loss)
-I0510 18:42:25.048336  5307 sgd_solver.cpp:172] Iteration 22300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:43:24.551668  5307 solver.cpp:352] Iteration 22400 (1.6806 iter/s, 59.5024s/100 iter), 43.3/232ep, loss = 3.88076
-I0510 18:43:24.551745  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.97335 (* 1 = 2.97335 loss)
-I0510 18:43:24.551754  5307 sgd_solver.cpp:172] Iteration 22400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:44:24.905186  5307 solver.cpp:352] Iteration 22500 (1.65693 iter/s, 60.3524s/100 iter), 43.5/232ep, loss = 3.91015
-I0510 18:44:24.905256  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46989 (* 1 = 3.46989 loss)
-I0510 18:44:24.905262  5307 sgd_solver.cpp:172] Iteration 22500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:45:25.671592  5307 solver.cpp:352] Iteration 22600 (1.64568 iter/s, 60.7653s/100 iter), 43.7/232ep, loss = 3.83031
-I0510 18:45:25.671681  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.12052 (* 1 = 3.12052 loss)
-I0510 18:45:25.671700  5307 sgd_solver.cpp:172] Iteration 22600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:46:25.727347  5307 solver.cpp:352] Iteration 22700 (1.66515 iter/s, 60.0547s/100 iter), 43.9/232ep, loss = 3.77082
-I0510 18:46:25.727466  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15335 (* 1 = 4.15335 loss)
-I0510 18:46:25.727480  5307 sgd_solver.cpp:172] Iteration 22700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:46:49.056587  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:47:25.671694  5307 solver.cpp:352] Iteration 22800 (1.66824 iter/s, 59.9433s/100 iter), 44.1/232ep, loss = 3.75317
-I0510 18:47:25.675361  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.52456 (* 1 = 3.52456 loss)
-I0510 18:47:25.675397  5307 sgd_solver.cpp:172] Iteration 22800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:48:26.058811  5307 solver.cpp:352] Iteration 22900 (1.65601 iter/s, 60.386s/100 iter), 44.3/232ep, loss = 3.91824
-I0510 18:48:26.058909  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.12324 (* 1 = 3.12324 loss)
-I0510 18:48:26.058931  5307 sgd_solver.cpp:172] Iteration 22900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:49:25.958818  5307 solver.cpp:352] Iteration 23000 (1.66948 iter/s, 59.8989s/100 iter), 44.5/232ep, loss = 3.88529
-I0510 18:49:25.958876  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82834 (* 1 = 3.82834 loss)
-I0510 18:49:25.958884  5307 sgd_solver.cpp:172] Iteration 23000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:50:26.141391  5307 solver.cpp:352] Iteration 23100 (1.66164 iter/s, 60.1815s/100 iter), 44.7/232ep, loss = 3.84205
-I0510 18:50:26.141486  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80804 (* 1 = 3.80804 loss)
-I0510 18:50:26.141495  5307 sgd_solver.cpp:172] Iteration 23100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:51:26.120424  5307 solver.cpp:352] Iteration 23200 (1.66728 iter/s, 59.978s/100 iter), 44.9/232ep, loss = 3.85392
-I0510 18:51:26.120483  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56861 (* 1 = 3.56861 loss)
-I0510 18:51:26.120492  5307 sgd_solver.cpp:172] Iteration 23200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:52:00.375195  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:52:25.731971  5307 solver.cpp:352] Iteration 23300 (1.67756 iter/s, 59.6105s/100 iter), 45/232ep, loss = 3.81557
-I0510 18:52:25.732010  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.45628 (* 1 = 3.45628 loss)
-I0510 18:52:25.732020  5307 sgd_solver.cpp:172] Iteration 23300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:53:26.464812  5307 solver.cpp:352] Iteration 23400 (1.64658 iter/s, 60.7318s/100 iter), 45.2/232ep, loss = 3.80069
-I0510 18:53:26.464896  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2912 (* 1 = 3.2912 loss)
-I0510 18:53:26.464906  5307 sgd_solver.cpp:172] Iteration 23400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:54:27.701195  5307 solver.cpp:352] Iteration 23500 (1.63304 iter/s, 61.2353s/100 iter), 45.4/232ep, loss = 3.89957
-I0510 18:54:27.701269  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27479 (* 1 = 3.27479 loss)
-I0510 18:54:27.701277  5307 sgd_solver.cpp:172] Iteration 23500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:55:29.363590  5307 solver.cpp:352] Iteration 23600 (1.62176 iter/s, 61.6613s/100 iter), 45.6/232ep, loss = 4.05547
-I0510 18:55:29.363911  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.68351 (* 1 = 4.68351 loss)
-I0510 18:55:29.363940  5307 sgd_solver.cpp:172] Iteration 23600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:56:31.339885  5307 solver.cpp:352] Iteration 23700 (1.61355 iter/s, 61.9752s/100 iter), 45.8/232ep, loss = 3.94768
-I0510 18:56:31.339956  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78877 (* 1 = 3.78877 loss)
-I0510 18:56:31.339964  5307 sgd_solver.cpp:172] Iteration 23700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:57:16.840919  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:57:32.433218  5307 solver.cpp:352] Iteration 23800 (1.63687 iter/s, 61.0923s/100 iter), 46/232ep, loss = 3.87
-I0510 18:57:32.433284  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.22068 (* 1 = 4.22068 loss)
-I0510 18:57:32.433292  5307 sgd_solver.cpp:172] Iteration 23800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:58:33.108304  5307 solver.cpp:352] Iteration 23900 (1.64815 iter/s, 60.674s/100 iter), 46.2/232ep, loss = 3.5852
-I0510 18:58:33.108393  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06789 (* 1 = 4.06789 loss)
-I0510 18:58:33.108404  5307 sgd_solver.cpp:172] Iteration 23900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:59:33.702417  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_24000.caffemodel
-I0510 18:59:33.715880  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_24000.solverstate
-I0510 18:59:33.719976  5307 solver.cpp:635] Iteration 24000, Testing net (#0)
-I0510 19:00:15.762233  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:00:15.999637  5307 solver.cpp:747] class AP 1: 0.484444
-I0510 19:00:15.999975  5307 solver.cpp:747] class AP 2: 0.482623
-I0510 19:00:16.003038  5307 solver.cpp:747] class AP 3: 0.351549
-I0510 19:00:16.006753  5307 solver.cpp:747] class AP 4: 0.350077
-I0510 19:00:16.033462  5307 solver.cpp:747] class AP 5: 0.213984
-I0510 19:00:16.034142  5307 solver.cpp:747] class AP 6: 0.605831
-I0510 19:00:16.040594  5307 solver.cpp:747] class AP 7: 0.574534
-I0510 19:00:16.041268  5307 solver.cpp:747] class AP 8: 0.637335
-I0510 19:00:16.059988  5307 solver.cpp:747] class AP 9: 0.269435
-I0510 19:00:16.060272  5307 solver.cpp:747] class AP 10: 0.375766
-I0510 19:00:16.061775  5307 solver.cpp:747] class AP 11: 0.40548
-I0510 19:00:16.062548  5307 solver.cpp:747] class AP 12: 0.519061
-I0510 19:00:16.062849  5307 solver.cpp:747] class AP 13: 0.527503
-I0510 19:00:16.063004  5307 solver.cpp:747] class AP 14: 0.472097
-I0510 19:00:16.124413  5307 solver.cpp:747] class AP 15: 0.617836
-I0510 19:00:16.132398  5307 solver.cpp:747] class AP 16: 0.211552
-I0510 19:00:16.133635  5307 solver.cpp:747] class AP 17: 0.336798
-I0510 19:00:16.134557  5307 solver.cpp:747] class AP 18: 0.421108
-I0510 19:00:16.135125  5307 solver.cpp:747] class AP 19: 0.594174
-I0510 19:00:16.136035  5307 solver.cpp:747] class AP 20: 0.435553
-I0510 19:00:16.136041  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.444337
-I0510 19:00:16.136257  5307 solver.cpp:283] Tests completed in 103.026s
-I0510 19:00:16.756871  5307 solver.cpp:352] Iteration 24000 (0.970627 iter/s, 103.026s/100 iter), 46.4/232ep, loss = 3.9067
-I0510 19:00:16.756903  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44319 (* 1 = 3.44319 loss)
-I0510 19:00:16.756912  5307 sgd_solver.cpp:172] Iteration 24000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:01:17.363162  5307 solver.cpp:352] Iteration 24100 (1.65002 iter/s, 60.6052s/100 iter), 46.6/232ep, loss = 3.77663
-I0510 19:01:17.363291  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.04249 (* 1 = 4.04249 loss)
-I0510 19:01:17.363312  5307 sgd_solver.cpp:172] Iteration 24100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:02:18.204226  5307 solver.cpp:352] Iteration 24200 (1.64366 iter/s, 60.84s/100 iter), 46.8/232ep, loss = 3.9649
-I0510 19:02:18.204455  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57627 (* 1 = 3.57627 loss)
-I0510 19:02:18.204466  5307 sgd_solver.cpp:172] Iteration 24200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:03:14.237166  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:03:19.448635  5307 solver.cpp:352] Iteration 24300 (1.63283 iter/s, 61.2433s/100 iter), 47/232ep, loss = 3.96085
-I0510 19:03:19.448683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11814 (* 1 = 3.11814 loss)
-I0510 19:03:19.448693  5307 sgd_solver.cpp:172] Iteration 24300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:04:19.763339  5307 solver.cpp:352] Iteration 24400 (1.658 iter/s, 60.3136s/100 iter), 47.2/232ep, loss = 3.78938
-I0510 19:04:19.763430  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58582 (* 1 = 3.58582 loss)
-I0510 19:04:19.763447  5307 sgd_solver.cpp:172] Iteration 24400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:05:20.826309  5307 solver.cpp:352] Iteration 24500 (1.63768 iter/s, 61.0619s/100 iter), 47.4/232ep, loss = 3.86039
-I0510 19:05:20.826555  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19428 (* 1 = 3.19428 loss)
-I0510 19:05:20.826565  5307 sgd_solver.cpp:172] Iteration 24500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:06:21.950335  5307 solver.cpp:352] Iteration 24600 (1.63605 iter/s, 61.1229s/100 iter), 47.6/232ep, loss = 3.78745
-I0510 19:06:21.950456  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.91877 (* 1 = 4.91877 loss)
-I0510 19:06:21.950484  5307 sgd_solver.cpp:172] Iteration 24600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:07:24.160080  5307 solver.cpp:352] Iteration 24700 (1.60749 iter/s, 62.2086s/100 iter), 47.8/232ep, loss = 3.66962
-I0510 19:07:24.160152  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87449 (* 1 = 3.87449 loss)
-I0510 19:07:24.160161  5307 sgd_solver.cpp:172] Iteration 24700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:08:25.133620  5307 solver.cpp:352] Iteration 24800 (1.64009 iter/s, 60.9724s/100 iter), 47.9/232ep, loss = 3.65032
-I0510 19:08:25.133761  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.49542 (* 1 = 3.49542 loss)
-I0510 19:08:25.133775  5307 sgd_solver.cpp:172] Iteration 24800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:08:30.483697  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:09:26.062394  5307 solver.cpp:352] Iteration 24900 (1.64129 iter/s, 60.9277s/100 iter), 48.1/232ep, loss = 3.83275
-I0510 19:09:26.062619  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.22737 (* 1 = 5.22737 loss)
-I0510 19:09:26.062644  5307 sgd_solver.cpp:172] Iteration 24900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:10:27.073468  5307 solver.cpp:352] Iteration 25000 (1.63908 iter/s, 61.01s/100 iter), 48.3/232ep, loss = 4.03657
-I0510 19:10:27.073570  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51471 (* 1 = 3.51471 loss)
-I0510 19:10:27.073578  5307 sgd_solver.cpp:172] Iteration 25000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:11:28.260156  5307 solver.cpp:352] Iteration 25100 (1.63437 iter/s, 61.1856s/100 iter), 48.5/232ep, loss = 3.5904
-I0510 19:11:28.260237  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.638 (* 1 = 3.638 loss)
-I0510 19:11:28.260244  5307 sgd_solver.cpp:172] Iteration 25100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:12:29.748556  5307 solver.cpp:352] Iteration 25200 (1.62635 iter/s, 61.4873s/100 iter), 48.7/232ep, loss = 3.85716
-I0510 19:12:29.748668  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36624 (* 1 = 3.36624 loss)
-I0510 19:12:29.748684  5307 sgd_solver.cpp:172] Iteration 25200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:13:30.301437  5307 solver.cpp:352] Iteration 25300 (1.65148 iter/s, 60.5518s/100 iter), 48.9/232ep, loss = 3.68767
-I0510 19:13:30.301498  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43387 (* 1 = 3.43387 loss)
-I0510 19:13:30.301506  5307 sgd_solver.cpp:172] Iteration 25300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:13:45.276093  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:14:29.971930  5307 solver.cpp:352] Iteration 25400 (1.6759 iter/s, 59.6694s/100 iter), 49.1/232ep, loss = 3.84171
-I0510 19:14:29.972039  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.54642 (* 1 = 4.54642 loss)
-I0510 19:14:29.972059  5307 sgd_solver.cpp:172] Iteration 25400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:15:30.884881  5307 solver.cpp:352] Iteration 25500 (1.64172 iter/s, 60.9119s/100 iter), 49.3/232ep, loss = 4.00768
-I0510 19:15:30.884943  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93366 (* 1 = 3.93366 loss)
-I0510 19:15:30.884948  5307 sgd_solver.cpp:172] Iteration 25500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:16:30.960016  5307 solver.cpp:352] Iteration 25600 (1.66461 iter/s, 60.0741s/100 iter), 49.5/232ep, loss = 3.89147
-I0510 19:16:30.960086  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27457 (* 1 = 3.27457 loss)
-I0510 19:16:30.960094  5307 sgd_solver.cpp:172] Iteration 25600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:17:31.220655  5307 solver.cpp:352] Iteration 25700 (1.65949 iter/s, 60.2596s/100 iter), 49.7/232ep, loss = 3.77153
-I0510 19:17:31.222297  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89295 (* 1 = 3.89295 loss)
-I0510 19:17:31.222306  5307 sgd_solver.cpp:172] Iteration 25700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:18:31.005316  5307 solver.cpp:352] Iteration 25800 (1.6727 iter/s, 59.7836s/100 iter), 49.9/232ep, loss = 3.86166
-I0510 19:18:31.005399  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.19522 (* 1 = 4.19522 loss)
-I0510 19:18:31.005409  5307 sgd_solver.cpp:172] Iteration 25800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:18:57.666621  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:19:31.365808  5307 solver.cpp:352] Iteration 25900 (1.65674 iter/s, 60.3594s/100 iter), 50.1/232ep, loss = 3.97279
-I0510 19:19:31.365890  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03542 (* 1 = 4.03542 loss)
-I0510 19:19:31.365897  5307 sgd_solver.cpp:172] Iteration 25900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:20:31.104477  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_26000.caffemodel
-I0510 19:20:31.123970  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_26000.solverstate
-I0510 19:20:31.131429  5307 solver.cpp:635] Iteration 26000, Testing net (#0)
-I0510 19:21:12.665139  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:21:12.910117  5307 solver.cpp:747] class AP 1: 0.527658
-I0510 19:21:12.910953  5307 solver.cpp:747] class AP 2: 0.58519
-I0510 19:21:12.918699  5307 solver.cpp:747] class AP 3: 0.408892
-I0510 19:21:12.925354  5307 solver.cpp:747] class AP 4: 0.323238
-I0510 19:21:12.933722  5307 solver.cpp:747] class AP 5: 0.196721
-I0510 19:21:12.934037  5307 solver.cpp:747] class AP 6: 0.601376
-I0510 19:21:12.953480  5307 solver.cpp:747] class AP 7: 0.617601
-I0510 19:21:12.954058  5307 solver.cpp:747] class AP 8: 0.655444
-I0510 19:21:12.971992  5307 solver.cpp:747] class AP 9: 0.291683
-I0510 19:21:12.972307  5307 solver.cpp:747] class AP 10: 0.440488
-I0510 19:21:12.972625  5307 solver.cpp:747] class AP 11: 0.432128
-I0510 19:21:12.973682  5307 solver.cpp:747] class AP 12: 0.558183
-I0510 19:21:12.973996  5307 solver.cpp:747] class AP 13: 0.66504
-I0510 19:21:12.974239  5307 solver.cpp:747] class AP 14: 0.63709
-I0510 19:21:13.041898  5307 solver.cpp:747] class AP 15: 0.59983
-I0510 19:21:13.044495  5307 solver.cpp:747] class AP 16: 0.20258
-I0510 19:21:13.047165  5307 solver.cpp:747] class AP 17: 0.391476
-I0510 19:21:13.048035  5307 solver.cpp:747] class AP 18: 0.391003
-I0510 19:21:13.048532  5307 solver.cpp:747] class AP 19: 0.637381
-I0510 19:21:13.049194  5307 solver.cpp:747] class AP 20: 0.471418
-I0510 19:21:13.049202  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.481721
-I0510 19:21:13.049327  5307 solver.cpp:283] Tests completed in 101.682s
-I0510 19:21:13.606369  5307 solver.cpp:352] Iteration 26000 (0.983461 iter/s, 101.682s/100 iter), 50.3/232ep, loss = 3.93858
-I0510 19:21:13.606431  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02108 (* 1 = 4.02108 loss)
-I0510 19:21:13.606443  5307 sgd_solver.cpp:172] Iteration 26000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:22:16.320257  5307 solver.cpp:352] Iteration 26100 (1.59457 iter/s, 62.7127s/100 iter), 50.5/232ep, loss = 3.82841
-I0510 19:22:16.320799  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68787 (* 1 = 3.68787 loss)
-I0510 19:22:16.320818  5307 sgd_solver.cpp:172] Iteration 26100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:23:24.497467  5307 solver.cpp:352] Iteration 26200 (1.46679 iter/s, 68.176s/100 iter), 50.7/232ep, loss = 3.76185
-I0510 19:23:24.497622  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67768 (* 1 = 3.67768 loss)
-I0510 19:23:24.497642  5307 sgd_solver.cpp:172] Iteration 26200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:24:25.847491  5307 solver.cpp:352] Iteration 26300 (1.63002 iter/s, 61.3489s/100 iter), 50.8/232ep, loss = 3.94741
-I0510 19:24:25.847573  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.27126 (* 1 = 4.27126 loss)
-I0510 19:24:25.847581  5307 sgd_solver.cpp:172] Iteration 26300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:25:02.195729  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:25:25.784054  5307 solver.cpp:352] Iteration 26400 (1.66846 iter/s, 59.9355s/100 iter), 51/232ep, loss = 3.76409
-I0510 19:25:25.784085  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.58813 (* 1 = 4.58813 loss)
-I0510 19:25:25.784093  5307 sgd_solver.cpp:172] Iteration 26400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:26:26.028339  5307 solver.cpp:352] Iteration 26500 (1.65994 iter/s, 60.2432s/100 iter), 51.2/232ep, loss = 3.84718
-I0510 19:26:26.028415  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.04022 (* 1 = 4.04022 loss)
-I0510 19:26:26.028424  5307 sgd_solver.cpp:172] Iteration 26500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:27:27.105324  5307 solver.cpp:352] Iteration 26600 (1.63731 iter/s, 61.0759s/100 iter), 51.4/232ep, loss = 3.73108
-I0510 19:27:27.105420  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22452 (* 1 = 3.22452 loss)
-I0510 19:27:27.105428  5307 sgd_solver.cpp:172] Iteration 26600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:28:27.265174  5307 solver.cpp:352] Iteration 26700 (1.66227 iter/s, 60.1588s/100 iter), 51.6/232ep, loss = 3.73865
-I0510 19:28:27.265241  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65277 (* 1 = 3.65277 loss)
-I0510 19:28:27.265247  5307 sgd_solver.cpp:172] Iteration 26700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:29:27.365866  5307 solver.cpp:352] Iteration 26800 (1.6639 iter/s, 60.0996s/100 iter), 51.8/232ep, loss = 3.82671
-I0510 19:29:27.365945  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49587 (* 1 = 4.49587 loss)
-I0510 19:29:27.365955  5307 sgd_solver.cpp:172] Iteration 26800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:30:13.481175  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:30:27.466990  5307 solver.cpp:352] Iteration 26900 (1.66389 iter/s, 60.1s/100 iter), 52/232ep, loss = 3.72676
-I0510 19:30:27.467074  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.70798 (* 1 = 3.70798 loss)
-I0510 19:30:27.467095  5307 sgd_solver.cpp:172] Iteration 26900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:31:27.867920  5307 solver.cpp:352] Iteration 27000 (1.65563 iter/s, 60.3998s/100 iter), 52.2/232ep, loss = 3.60723
-I0510 19:31:27.868335  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30788 (* 1 = 3.30788 loss)
-I0510 19:31:27.868350  5307 sgd_solver.cpp:172] Iteration 27000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:32:27.997393  5307 solver.cpp:352] Iteration 27100 (1.66311 iter/s, 60.1284s/100 iter), 52.4/232ep, loss = 3.60799
-I0510 19:32:27.998000  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05221 (* 1 = 3.05221 loss)
-I0510 19:32:27.998009  5307 sgd_solver.cpp:172] Iteration 27100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:33:28.887500  5307 solver.cpp:352] Iteration 27200 (1.64233 iter/s, 60.889s/100 iter), 52.6/232ep, loss = 3.85192
-I0510 19:33:28.887666  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.21449 (* 1 = 4.21449 loss)
-I0510 19:33:28.887676  5307 sgd_solver.cpp:172] Iteration 27200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:34:29.287021  5307 solver.cpp:352] Iteration 27300 (1.65567 iter/s, 60.3984s/100 iter), 52.8/232ep, loss = 3.80451
-I0510 19:34:29.290815  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61041 (* 1 = 3.61041 loss)
-I0510 19:34:29.290830  5307 sgd_solver.cpp:172] Iteration 27300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:35:27.106932  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:35:30.255291  5307 solver.cpp:352] Iteration 27400 (1.64023 iter/s, 60.9672s/100 iter), 53/232ep, loss = 3.9971
-I0510 19:35:30.255317  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47735 (* 1 = 3.47735 loss)
-I0510 19:35:30.255324  5307 sgd_solver.cpp:172] Iteration 27400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:36:30.755306  5307 solver.cpp:352] Iteration 27500 (1.65292 iter/s, 60.4989s/100 iter), 53.2/232ep, loss = 3.76978
-I0510 19:36:30.755390  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83909 (* 1 = 3.83909 loss)
-I0510 19:36:30.755400  5307 sgd_solver.cpp:172] Iteration 27500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:37:31.814741  5307 solver.cpp:352] Iteration 27600 (1.63778 iter/s, 61.0584s/100 iter), 53.4/232ep, loss = 3.97396
-I0510 19:37:31.814800  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91227 (* 1 = 3.91227 loss)
-I0510 19:37:31.814810  5307 sgd_solver.cpp:172] Iteration 27600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:38:32.215876  5307 solver.cpp:352] Iteration 27700 (1.65563 iter/s, 60.4001s/100 iter), 53.6/232ep, loss = 3.80746
-I0510 19:38:32.215960  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0961 (* 1 = 4.0961 loss)
-I0510 19:38:32.215975  5307 sgd_solver.cpp:172] Iteration 27700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:39:32.541234  5307 solver.cpp:352] Iteration 27800 (1.65771 iter/s, 60.3243s/100 iter), 53.7/232ep, loss = 3.68896
-I0510 19:39:32.541684  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.45826 (* 1 = 3.45826 loss)
-I0510 19:39:32.541694  5307 sgd_solver.cpp:172] Iteration 27800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:40:32.999799  5307 solver.cpp:352] Iteration 27900 (1.65406 iter/s, 60.4575s/100 iter), 53.9/232ep, loss = 3.7588
-I0510 19:40:33.000018  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.83248 (* 1 = 4.83248 loss)
-I0510 19:40:33.000042  5307 sgd_solver.cpp:172] Iteration 27900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:40:39.858031  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:41:32.854823  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_28000.caffemodel
-I0510 19:41:32.869741  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_28000.solverstate
-I0510 19:41:32.875227  5307 solver.cpp:635] Iteration 28000, Testing net (#0)
-I0510 19:42:13.878679  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:42:14.101833  5307 solver.cpp:747] class AP 1: 0.447821
-I0510 19:42:14.102130  5307 solver.cpp:747] class AP 2: 0.514945
-I0510 19:42:14.110472  5307 solver.cpp:747] class AP 3: 0.332307
-I0510 19:42:14.113862  5307 solver.cpp:747] class AP 4: 0.276696
-I0510 19:42:14.147543  5307 solver.cpp:747] class AP 5: 0.218325
-I0510 19:42:14.147663  5307 solver.cpp:747] class AP 6: 0.566076
-I0510 19:42:14.150702  5307 solver.cpp:747] class AP 7: 0.520006
-I0510 19:42:14.151751  5307 solver.cpp:747] class AP 8: 0.57054
-I0510 19:42:14.180486  5307 solver.cpp:747] class AP 9: 0.224394
-I0510 19:42:14.181216  5307 solver.cpp:747] class AP 10: 0.335236
-I0510 19:42:14.183318  5307 solver.cpp:747] class AP 11: 0.356538
-I0510 19:42:14.184463  5307 solver.cpp:747] class AP 12: 0.474195
-I0510 19:42:14.184739  5307 solver.cpp:747] class AP 13: 0.507128
-I0510 19:42:14.184957  5307 solver.cpp:747] class AP 14: 0.516949
-I0510 19:42:14.219790  5307 solver.cpp:747] class AP 15: 0.595535
-I0510 19:42:14.231107  5307 solver.cpp:747] class AP 16: 0.219246
-I0510 19:42:14.232429  5307 solver.cpp:747] class AP 17: 0.385486
-I0510 19:42:14.233534  5307 solver.cpp:747] class AP 18: 0.332484
-I0510 19:42:14.233866  5307 solver.cpp:747] class AP 19: 0.542427
-I0510 19:42:14.234956  5307 solver.cpp:747] class AP 20: 0.421216
-I0510 19:42:14.234963  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.417878
-I0510 19:42:14.235227  5307 solver.cpp:283] Tests completed in 101.234s
-I0510 19:42:14.854811  5307 solver.cpp:352] Iteration 28000 (0.987813 iter/s, 101.234s/100 iter), 54.1/232ep, loss = 3.52533
-I0510 19:42:14.854843  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06378 (* 1 = 4.06378 loss)
-I0510 19:42:14.854853  5307 sgd_solver.cpp:172] Iteration 28000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:43:15.252923  5307 solver.cpp:352] Iteration 28100 (1.65571 iter/s, 60.397s/100 iter), 54.3/232ep, loss = 3.81855
-I0510 19:43:15.253015  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67796 (* 1 = 3.67796 loss)
-I0510 19:43:15.253027  5307 sgd_solver.cpp:172] Iteration 28100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:44:15.360148  5307 solver.cpp:352] Iteration 28200 (1.66372 iter/s, 60.1062s/100 iter), 54.5/232ep, loss = 3.75696
-I0510 19:44:15.360235  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11185 (* 1 = 4.11185 loss)
-I0510 19:44:15.360249  5307 sgd_solver.cpp:172] Iteration 28200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:45:16.344228  5307 solver.cpp:352] Iteration 28300 (1.6398 iter/s, 60.983s/100 iter), 54.7/232ep, loss = 3.74448
-I0510 19:45:16.344310  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.81193 (* 1 = 3.81193 loss)
-I0510 19:45:16.344317  5307 sgd_solver.cpp:172] Iteration 28300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:46:16.309695  5307 solver.cpp:352] Iteration 28400 (1.66766 iter/s, 59.9644s/100 iter), 54.9/232ep, loss = 3.7683
-I0510 19:46:16.309792  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.79755 (* 1 = 3.79755 loss)
-I0510 19:46:16.309808  5307 sgd_solver.cpp:172] Iteration 28400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:46:33.785228  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:47:16.645256  5307 solver.cpp:352] Iteration 28500 (1.65743 iter/s, 60.3345s/100 iter), 55.1/232ep, loss = 3.87838
-I0510 19:47:16.645334  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.06779 (* 1 = 3.06779 loss)
-I0510 19:47:16.645344  5307 sgd_solver.cpp:172] Iteration 28500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:48:16.931111  5307 solver.cpp:352] Iteration 28600 (1.65879 iter/s, 60.2848s/100 iter), 55.3/232ep, loss = 3.7845
-I0510 19:48:16.931172  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.90429 (* 1 = 3.90429 loss)
-I0510 19:48:16.931180  5307 sgd_solver.cpp:172] Iteration 28600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:49:17.907735  5307 solver.cpp:352] Iteration 28700 (1.64 iter/s, 60.9755s/100 iter), 55.5/232ep, loss = 3.6071
-I0510 19:49:17.907867  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59682 (* 1 = 3.59682 loss)
-I0510 19:49:17.907881  5307 sgd_solver.cpp:172] Iteration 28700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:50:18.755187  5307 solver.cpp:352] Iteration 28800 (1.64348 iter/s, 60.8463s/100 iter), 55.7/232ep, loss = 3.75675
-I0510 19:50:18.755365  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5903 (* 1 = 3.5903 loss)
-I0510 19:50:18.755391  5307 sgd_solver.cpp:172] Iteration 28800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:51:19.042055  5307 solver.cpp:352] Iteration 28900 (1.65877 iter/s, 60.2858s/100 iter), 55.9/232ep, loss = 3.71257
-I0510 19:51:19.042114  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.48781 (* 1 = 4.48781 loss)
-I0510 19:51:19.042121  5307 sgd_solver.cpp:172] Iteration 28900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:51:47.191911  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:52:19.624878  5307 solver.cpp:352] Iteration 29000 (1.65066 iter/s, 60.5817s/100 iter), 56.1/232ep, loss = 3.67674
-I0510 19:52:19.625249  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87256 (* 1 = 3.87256 loss)
-I0510 19:52:19.625259  5307 sgd_solver.cpp:172] Iteration 29000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:53:20.396816  5307 solver.cpp:352] Iteration 29100 (1.64553 iter/s, 60.7708s/100 iter), 56.3/232ep, loss = 3.99434
-I0510 19:53:20.396867  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.8691 (* 1 = 3.8691 loss)
-I0510 19:53:20.396876  5307 sgd_solver.cpp:172] Iteration 29100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:54:20.580611  5307 solver.cpp:352] Iteration 29200 (1.66161 iter/s, 60.1827s/100 iter), 56.5/232ep, loss = 3.78493
-I0510 19:54:20.580708  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06183 (* 1 = 4.06183 loss)
-I0510 19:54:20.580732  5307 sgd_solver.cpp:172] Iteration 29200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:55:20.472167  5307 solver.cpp:352] Iteration 29300 (1.66971 iter/s, 59.8905s/100 iter), 56.6/232ep, loss = 3.62764
-I0510 19:55:20.472227  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31053 (* 1 = 3.31053 loss)
-I0510 19:55:20.472235  5307 sgd_solver.cpp:172] Iteration 29300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:56:21.429445  5307 solver.cpp:352] Iteration 29400 (1.64052 iter/s, 60.9562s/100 iter), 56.8/232ep, loss = 3.77345
-I0510 19:56:21.429524  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61489 (* 1 = 3.61489 loss)
-I0510 19:56:21.429533  5307 sgd_solver.cpp:172] Iteration 29400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:56:59.462847  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:57:22.076934  5307 solver.cpp:352] Iteration 29500 (1.6489 iter/s, 60.6464s/100 iter), 57/232ep, loss = 3.6652
-I0510 19:57:22.076967  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40196 (* 1 = 3.40196 loss)
-I0510 19:57:22.076977  5307 sgd_solver.cpp:172] Iteration 29500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:58:22.610980  5307 solver.cpp:352] Iteration 29600 (1.65199 iter/s, 60.533s/100 iter), 57.2/232ep, loss = 3.70211
-I0510 19:58:22.611089  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43717 (* 1 = 3.43717 loss)
-I0510 19:58:22.611099  5307 sgd_solver.cpp:172] Iteration 29600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:59:22.832132  5307 solver.cpp:352] Iteration 29700 (1.66058 iter/s, 60.2201s/100 iter), 57.4/232ep, loss = 3.74542
-I0510 19:59:22.835464  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.23196 (* 1 = 4.23196 loss)
-I0510 19:59:22.835556  5307 sgd_solver.cpp:172] Iteration 29700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:00:23.247373  5307 solver.cpp:352] Iteration 29800 (1.65524 iter/s, 60.4142s/100 iter), 57.6/232ep, loss = 3.74278
-I0510 20:00:23.247465  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83845 (* 1 = 3.83845 loss)
-I0510 20:00:23.247474  5307 sgd_solver.cpp:172] Iteration 29800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:01:24.044986  5307 solver.cpp:352] Iteration 29900 (1.64483 iter/s, 60.7965s/100 iter), 57.8/232ep, loss = 3.6145
-I0510 20:01:24.045045  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74996 (* 1 = 2.74996 loss)
-I0510 20:01:24.045053  5307 sgd_solver.cpp:172] Iteration 29900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:02:12.929261  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:02:23.974081  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_30000.caffemodel
-I0510 20:02:23.993046  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_30000.solverstate
-I0510 20:02:23.999919  5307 solver.cpp:635] Iteration 30000, Testing net (#0)
-I0510 20:03:05.099125  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:03:05.335094  5307 solver.cpp:747] class AP 1: 0.49288
-I0510 20:03:05.335618  5307 solver.cpp:747] class AP 2: 0.572298
-I0510 20:03:05.351456  5307 solver.cpp:747] class AP 3: 0.411125
-I0510 20:03:05.354663  5307 solver.cpp:747] class AP 4: 0.283815
-I0510 20:03:05.369340  5307 solver.cpp:747] class AP 5: 0.159748
-I0510 20:03:05.369539  5307 solver.cpp:747] class AP 6: 0.57257
-I0510 20:03:05.377823  5307 solver.cpp:747] class AP 7: 0.55566
-I0510 20:03:05.378362  5307 solver.cpp:747] class AP 8: 0.604174
-I0510 20:03:05.393599  5307 solver.cpp:747] class AP 9: 0.217753
-I0510 20:03:05.394135  5307 solver.cpp:747] class AP 10: 0.400134
-I0510 20:03:05.394649  5307 solver.cpp:747] class AP 11: 0.429815
-I0510 20:03:05.396200  5307 solver.cpp:747] class AP 12: 0.544543
-I0510 20:03:05.396452  5307 solver.cpp:747] class AP 13: 0.672034
-I0510 20:03:05.396749  5307 solver.cpp:747] class AP 14: 0.587423
-I0510 20:03:05.454797  5307 solver.cpp:747] class AP 15: 0.603451
-I0510 20:03:05.464190  5307 solver.cpp:747] class AP 16: 0.160115
-I0510 20:03:05.465623  5307 solver.cpp:747] class AP 17: 0.407475
-I0510 20:03:05.465979  5307 solver.cpp:747] class AP 18: 0.364085
-I0510 20:03:05.466434  5307 solver.cpp:747] class AP 19: 0.563487
-I0510 20:03:05.467962  5307 solver.cpp:747] class AP 20: 0.370664
-I0510 20:03:05.467970  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.448662
-I0510 20:03:05.468106  5307 solver.cpp:283] Tests completed in 101.421s
-I0510 20:03:06.032670  5307 solver.cpp:352] Iteration 30000 (0.985986 iter/s, 101.421s/100 iter), 58/232ep, loss = 3.82731
-I0510 20:03:06.032719  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5366 (* 1 = 3.5366 loss)
-I0510 20:03:06.032733  5307 sgd_solver.cpp:172] Iteration 30000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:04:06.726922  5307 solver.cpp:352] Iteration 30100 (1.64763 iter/s, 60.6932s/100 iter), 58.2/232ep, loss = 3.74437
-I0510 20:04:06.726979  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78703 (* 1 = 3.78703 loss)
-I0510 20:04:06.726985  5307 sgd_solver.cpp:172] Iteration 30100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:05:07.274248  5307 solver.cpp:352] Iteration 30200 (1.65163 iter/s, 60.5462s/100 iter), 58.4/232ep, loss = 3.47742
-I0510 20:05:07.274332  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05092 (* 1 = 4.05092 loss)
-I0510 20:05:07.274341  5307 sgd_solver.cpp:172] Iteration 30200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:06:08.827862  5307 solver.cpp:352] Iteration 30300 (1.62463 iter/s, 61.5525s/100 iter), 58.6/232ep, loss = 3.77468
-I0510 20:06:08.827973  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50115 (* 1 = 3.50115 loss)
-I0510 20:06:08.827985  5307 sgd_solver.cpp:172] Iteration 30300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:07:10.170852  5307 solver.cpp:352] Iteration 30400 (1.63021 iter/s, 61.3419s/100 iter), 58.8/232ep, loss = 3.64959
-I0510 20:07:10.170904  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96388 (* 1 = 2.96388 loss)
-I0510 20:07:10.170913  5307 sgd_solver.cpp:172] Iteration 30400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:08:10.422246  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:08:12.163167  5307 solver.cpp:352] Iteration 30500 (1.61313 iter/s, 61.9912s/100 iter), 59/232ep, loss = 3.95137
-I0510 20:08:12.163193  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.71779 (* 1 = 4.71779 loss)
-I0510 20:08:12.163203  5307 sgd_solver.cpp:172] Iteration 30500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:09:13.321945  5307 solver.cpp:352] Iteration 30600 (1.63512 iter/s, 61.1576s/100 iter), 59.2/232ep, loss = 3.72914
-I0510 20:09:13.322137  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.10117 (* 1 = 4.10117 loss)
-I0510 20:09:13.322167  5307 sgd_solver.cpp:172] Iteration 30600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:10:14.789160  5307 solver.cpp:352] Iteration 30700 (1.62691 iter/s, 61.4662s/100 iter), 59.4/232ep, loss = 3.80969
-I0510 20:10:14.789242  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.44581 (* 1 = 4.44581 loss)
-I0510 20:10:14.789257  5307 sgd_solver.cpp:172] Iteration 30700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:11:16.550231  5307 solver.cpp:352] Iteration 30800 (1.61917 iter/s, 61.76s/100 iter), 59.5/232ep, loss = 3.63191
-I0510 20:11:16.551460  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.36055 (* 1 = 4.36055 loss)
-I0510 20:11:16.551486  5307 sgd_solver.cpp:172] Iteration 30800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:12:16.602501  5307 solver.cpp:352] Iteration 30900 (1.66524 iter/s, 60.0513s/100 iter), 59.7/232ep, loss = 3.7639
-I0510 20:12:16.602596  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01655 (* 1 = 3.01655 loss)
-I0510 20:12:16.602603  5307 sgd_solver.cpp:172] Iteration 30900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:13:16.543359  5307 solver.cpp:352] Iteration 31000 (1.66834 iter/s, 59.9398s/100 iter), 59.9/232ep, loss = 3.63295
-I0510 20:13:16.543452  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37379 (* 1 = 3.37379 loss)
-I0510 20:13:16.543471  5307 sgd_solver.cpp:172] Iteration 31000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:13:25.537050  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:14:16.204613  5307 solver.cpp:352] Iteration 31100 (1.67616 iter/s, 59.6602s/100 iter), 60.1/232ep, loss = 3.72176
-I0510 20:14:16.204711  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31073 (* 1 = 3.31073 loss)
-I0510 20:14:16.204720  5307 sgd_solver.cpp:172] Iteration 31100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:15:16.277683  5307 solver.cpp:352] Iteration 31200 (1.66467 iter/s, 60.072s/100 iter), 60.3/232ep, loss = 3.58337
-I0510 20:15:16.278057  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95243 (* 1 = 3.95243 loss)
-I0510 20:15:16.278071  5307 sgd_solver.cpp:172] Iteration 31200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:16:17.477808  5307 solver.cpp:352] Iteration 31300 (1.63401 iter/s, 61.1991s/100 iter), 60.5/232ep, loss = 3.7103
-I0510 20:16:17.477916  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.55529 (* 1 = 2.55529 loss)
-I0510 20:16:17.477927  5307 sgd_solver.cpp:172] Iteration 31300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:17:18.232285  5307 solver.cpp:352] Iteration 31400 (1.646 iter/s, 60.7534s/100 iter), 60.7/232ep, loss = 3.75925
-I0510 20:17:18.232393  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.36327 (* 1 = 4.36327 loss)
-I0510 20:17:18.232416  5307 sgd_solver.cpp:172] Iteration 31400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:18:19.069918  5307 solver.cpp:352] Iteration 31500 (1.64375 iter/s, 60.8366s/100 iter), 60.9/232ep, loss = 3.53607
-I0510 20:18:19.069981  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8967 (* 1 = 2.8967 loss)
-I0510 20:18:19.069990  5307 sgd_solver.cpp:172] Iteration 31500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:18:39.256943  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:19:19.638444  5307 solver.cpp:352] Iteration 31600 (1.65105 iter/s, 60.5675s/100 iter), 61.1/232ep, loss = 3.67042
-I0510 20:19:19.638500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.80708 (* 1 = 2.80708 loss)
-I0510 20:19:19.638509  5307 sgd_solver.cpp:172] Iteration 31600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:20:21.356631  5307 solver.cpp:352] Iteration 31700 (1.6203 iter/s, 61.7171s/100 iter), 61.3/232ep, loss = 3.81229
-I0510 20:20:21.357816  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15715 (* 1 = 4.15715 loss)
-I0510 20:20:21.357830  5307 sgd_solver.cpp:172] Iteration 31700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:21:22.677747  5307 solver.cpp:352] Iteration 31800 (1.63079 iter/s, 61.3201s/100 iter), 61.5/232ep, loss = 3.76929
-I0510 20:21:22.677806  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08326 (* 1 = 3.08326 loss)
-I0510 20:21:22.677814  5307 sgd_solver.cpp:172] Iteration 31800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:22:24.012138  5307 solver.cpp:352] Iteration 31900 (1.63043 iter/s, 61.3333s/100 iter), 61.7/232ep, loss = 3.64278
-I0510 20:22:24.012224  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.62073 (* 1 = 3.62073 loss)
-I0510 20:22:24.012233  5307 sgd_solver.cpp:172] Iteration 31900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:23:25.565407  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_32000.caffemodel
-I0510 20:23:25.587774  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_32000.solverstate
-I0510 20:23:25.595491  5307 solver.cpp:635] Iteration 32000, Testing net (#0)
-I0510 20:23:31.821794  5352 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0510 20:24:06.804874  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:24:07.037050  5307 solver.cpp:747] class AP 1: 0.526383
-I0510 20:24:07.037438  5307 solver.cpp:747] class AP 2: 0.635977
-I0510 20:24:07.048976  5307 solver.cpp:747] class AP 3: 0.399524
-I0510 20:24:07.051331  5307 solver.cpp:747] class AP 4: 0.347869
-I0510 20:24:07.067064  5307 solver.cpp:747] class AP 5: 0.256745
-I0510 20:24:07.067379  5307 solver.cpp:747] class AP 6: 0.649957
-I0510 20:24:07.072592  5307 solver.cpp:747] class AP 7: 0.617347
-I0510 20:24:07.073444  5307 solver.cpp:747] class AP 8: 0.690625
-I0510 20:24:07.097751  5307 solver.cpp:747] class AP 9: 0.335321
-I0510 20:24:07.098278  5307 solver.cpp:747] class AP 10: 0.517511
-I0510 20:24:07.099396  5307 solver.cpp:747] class AP 11: 0.472751
-I0510 20:24:07.100687  5307 solver.cpp:747] class AP 12: 0.596647
-I0510 20:24:07.100947  5307 solver.cpp:747] class AP 13: 0.676235
-I0510 20:24:07.101212  5307 solver.cpp:747] class AP 14: 0.649562
-I0510 20:24:07.157392  5307 solver.cpp:747] class AP 15: 0.64047
-I0510 20:24:07.162349  5307 solver.cpp:747] class AP 16: 0.223401
-I0510 20:24:07.165511  5307 solver.cpp:747] class AP 17: 0.496675
-I0510 20:24:07.166776  5307 solver.cpp:747] class AP 18: 0.510274
-I0510 20:24:07.167563  5307 solver.cpp:747] class AP 19: 0.621777
-I0510 20:24:07.168772  5307 solver.cpp:747] class AP 20: 0.474429
-I0510 20:24:07.168787  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.516974
-I0510 20:24:07.169006  5307 solver.cpp:283] Tests completed in 103.155s
-I0510 20:24:07.804672  5307 solver.cpp:352] Iteration 32000 (0.969414 iter/s, 103.155s/100 iter), 61.9/232ep, loss = 3.62977
-I0510 20:24:07.804797  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.35768 (* 1 = 3.35768 loss)
-I0510 20:24:07.804810  5307 sgd_solver.cpp:172] Iteration 32000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:24:38.469461  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:25:10.240434  5307 solver.cpp:352] Iteration 32100 (1.60168 iter/s, 62.4346s/100 iter), 62.1/232ep, loss = 3.66677
-I0510 20:25:10.240602  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87714 (* 1 = 3.87714 loss)
-I0510 20:25:10.240623  5307 sgd_solver.cpp:172] Iteration 32100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:26:11.415913  5307 solver.cpp:352] Iteration 32200 (1.63467 iter/s, 61.1744s/100 iter), 62.3/232ep, loss = 3.86129
-I0510 20:26:11.416028  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.7976 (* 1 = 3.7976 loss)
-I0510 20:26:11.416046  5307 sgd_solver.cpp:172] Iteration 32200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:27:13.032047  5307 solver.cpp:352] Iteration 32300 (1.62298 iter/s, 61.6151s/100 iter), 62.4/232ep, loss = 3.80358
-I0510 20:27:13.032133  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5296 (* 1 = 3.5296 loss)
-I0510 20:27:13.032150  5307 sgd_solver.cpp:172] Iteration 32300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:28:13.966925  5307 solver.cpp:352] Iteration 32400 (1.64113 iter/s, 60.9338s/100 iter), 62.6/232ep, loss = 3.76398
-I0510 20:28:13.967087  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.43466 (* 1 = 4.43466 loss)
-I0510 20:28:13.967106  5307 sgd_solver.cpp:172] Iteration 32400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:29:14.266544  5307 solver.cpp:352] Iteration 32500 (1.65841 iter/s, 60.2986s/100 iter), 62.8/232ep, loss = 3.84687
-I0510 20:29:14.267472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.96284 (* 1 = 3.96284 loss)
-I0510 20:29:14.267482  5307 sgd_solver.cpp:172] Iteration 32500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:29:55.900570  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:30:19.120484  5307 solver.cpp:352] Iteration 32600 (1.54195 iter/s, 64.8528s/100 iter), 63/232ep, loss = 3.61782
-I0510 20:30:19.120555  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3348 (* 1 = 3.3348 loss)
-I0510 20:30:19.120576  5307 sgd_solver.cpp:172] Iteration 32600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:31:27.233445  5307 solver.cpp:352] Iteration 32700 (1.46818 iter/s, 68.1118s/100 iter), 63.2/232ep, loss = 3.76131
-I0510 20:31:27.233536  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.97666 (* 1 = 3.97666 loss)
-I0510 20:31:27.233542  5307 sgd_solver.cpp:172] Iteration 32700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:32:27.301883  5307 solver.cpp:352] Iteration 32800 (1.6648 iter/s, 60.0674s/100 iter), 63.4/232ep, loss = 3.6275
-I0510 20:32:27.302006  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.93594 (* 1 = 2.93594 loss)
-I0510 20:32:27.302021  5307 sgd_solver.cpp:172] Iteration 32800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:33:28.381314  5307 solver.cpp:352] Iteration 32900 (1.63724 iter/s, 61.0784s/100 iter), 63.6/232ep, loss = 3.75429
-I0510 20:33:28.382957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.38282 (* 1 = 4.38282 loss)
-I0510 20:33:28.382968  5307 sgd_solver.cpp:172] Iteration 32900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:34:28.517973  5307 solver.cpp:352] Iteration 33000 (1.66291 iter/s, 60.1356s/100 iter), 63.8/232ep, loss = 3.79048
-I0510 20:34:28.518059  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.23225 (* 1 = 4.23225 loss)
-I0510 20:34:28.518067  5307 sgd_solver.cpp:172] Iteration 33000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:35:18.557407  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:35:28.267971  5307 solver.cpp:352] Iteration 33100 (1.67367 iter/s, 59.749s/100 iter), 64/232ep, loss = 3.6645
-I0510 20:35:28.267993  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03611 (* 1 = 3.03611 loss)
-I0510 20:35:28.267999  5307 sgd_solver.cpp:172] Iteration 33100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:36:29.240681  5307 solver.cpp:352] Iteration 33200 (1.64011 iter/s, 60.9717s/100 iter), 64.2/232ep, loss = 3.70925
-I0510 20:36:29.240780  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69101 (* 1 = 3.69101 loss)
-I0510 20:36:29.240792  5307 sgd_solver.cpp:172] Iteration 33200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:37:29.509500  5307 solver.cpp:352] Iteration 33300 (1.65926 iter/s, 60.2678s/100 iter), 64.4/232ep, loss = 3.64561
-I0510 20:37:29.512552  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32793 (* 1 = 3.32793 loss)
-I0510 20:37:29.512594  5307 sgd_solver.cpp:172] Iteration 33300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:38:30.920509  5307 solver.cpp:352] Iteration 33400 (1.6284 iter/s, 61.41s/100 iter), 64.6/232ep, loss = 3.73497
-I0510 20:38:30.920578  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.27622 (* 1 = 4.27622 loss)
-I0510 20:38:30.920588  5307 sgd_solver.cpp:172] Iteration 33400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:39:32.842433  5307 solver.cpp:352] Iteration 33500 (1.61496 iter/s, 61.9209s/100 iter), 64.8/232ep, loss = 3.82568
-I0510 20:39:32.842490  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.13622 (* 1 = 4.13622 loss)
-I0510 20:39:32.842499  5307 sgd_solver.cpp:172] Iteration 33500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:40:33.841985  5307 solver.cpp:352] Iteration 33600 (1.63938 iter/s, 60.9985s/100 iter), 65/232ep, loss = 3.69743
-I0510 20:40:33.842221  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.75096 (* 1 = 3.75096 loss)
-I0510 20:40:33.842247  5307 sgd_solver.cpp:172] Iteration 33600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:40:34.609417  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:41:35.916772  5307 solver.cpp:352] Iteration 33700 (1.61099 iter/s, 62.0737s/100 iter), 65.2/232ep, loss = 3.8023
-I0510 20:41:35.916874  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.88991 (* 1 = 3.88991 loss)
-I0510 20:41:35.916884  5307 sgd_solver.cpp:172] Iteration 33700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:42:36.419731  5307 solver.cpp:352] Iteration 33800 (1.65284 iter/s, 60.5019s/100 iter), 65.3/232ep, loss = 3.567
-I0510 20:42:36.419812  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4897 (* 1 = 3.4897 loss)
-I0510 20:42:36.419819  5307 sgd_solver.cpp:172] Iteration 33800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:43:36.926913  5307 solver.cpp:352] Iteration 33900 (1.65272 iter/s, 60.5061s/100 iter), 65.5/232ep, loss = 3.61852
-I0510 20:43:36.929528  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40645 (* 1 = 3.40645 loss)
-I0510 20:43:36.929539  5307 sgd_solver.cpp:172] Iteration 33900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:44:37.329893  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_34000.caffemodel
-I0510 20:44:37.345214  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_34000.solverstate
-I0510 20:44:37.350540  5307 solver.cpp:635] Iteration 34000, Testing net (#0)
-I0510 20:45:18.248383  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:45:18.483002  5307 solver.cpp:747] class AP 1: 0.468396
-I0510 20:45:18.484258  5307 solver.cpp:747] class AP 2: 0.505179
-I0510 20:45:18.489697  5307 solver.cpp:747] class AP 3: 0.354221
-I0510 20:45:18.493027  5307 solver.cpp:747] class AP 4: 0.355639
-I0510 20:45:18.514153  5307 solver.cpp:747] class AP 5: 0.19221
-I0510 20:45:18.514439  5307 solver.cpp:747] class AP 6: 0.58785
-I0510 20:45:18.519455  5307 solver.cpp:747] class AP 7: 0.56004
-I0510 20:45:18.519934  5307 solver.cpp:747] class AP 8: 0.604614
-I0510 20:45:18.549664  5307 solver.cpp:747] class AP 9: 0.315277
-I0510 20:45:18.549860  5307 solver.cpp:747] class AP 10: 0.427041
-I0510 20:45:18.550740  5307 solver.cpp:747] class AP 11: 0.436946
-I0510 20:45:18.551120  5307 solver.cpp:747] class AP 12: 0.507325
-I0510 20:45:18.551321  5307 solver.cpp:747] class AP 13: 0.552242
-I0510 20:45:18.551616  5307 solver.cpp:747] class AP 14: 0.531344
-I0510 20:45:18.596168  5307 solver.cpp:747] class AP 15: 0.593803
-I0510 20:45:18.613611  5307 solver.cpp:747] class AP 16: 0.182031
-I0510 20:45:18.614923  5307 solver.cpp:747] class AP 17: 0.416545
-I0510 20:45:18.615754  5307 solver.cpp:747] class AP 18: 0.478007
-I0510 20:45:18.616039  5307 solver.cpp:747] class AP 19: 0.576452
-I0510 20:45:18.617624  5307 solver.cpp:747] class AP 20: 0.367012
-I0510 20:45:18.617635  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.450609
-I0510 20:45:18.617774  5307 solver.cpp:283] Tests completed in 101.689s
-I0510 20:45:19.214574  5307 solver.cpp:352] Iteration 34000 (0.983389 iter/s, 101.689s/100 iter), 65.7/232ep, loss = 3.70767
-I0510 20:45:19.214648  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.55412 (* 1 = 4.55412 loss)
-I0510 20:45:19.214668  5307 sgd_solver.cpp:172] Iteration 34000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:46:19.771157  5307 solver.cpp:352] Iteration 34100 (1.65138 iter/s, 60.5555s/100 iter), 65.9/232ep, loss = 3.48196
-I0510 20:46:19.771966  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2801 (* 1 = 3.2801 loss)
-I0510 20:46:19.771975  5307 sgd_solver.cpp:172] Iteration 34100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:46:31.240007  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:47:20.672050  5307 solver.cpp:352] Iteration 34200 (1.64204 iter/s, 60.8998s/100 iter), 66.1/232ep, loss = 3.76233
-I0510 20:47:20.672143  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.77907 (* 1 = 3.77907 loss)
-I0510 20:47:20.672163  5307 sgd_solver.cpp:172] Iteration 34200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:48:21.350836  5307 solver.cpp:352] Iteration 34300 (1.64805 iter/s, 60.6777s/100 iter), 66.3/232ep, loss = 3.5743
-I0510 20:48:21.350909  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14103 (* 1 = 3.14103 loss)
-I0510 20:48:21.350927  5307 sgd_solver.cpp:172] Iteration 34300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:49:22.619603  5307 solver.cpp:352] Iteration 34400 (1.63218 iter/s, 61.2677s/100 iter), 66.5/232ep, loss = 3.59712
-I0510 20:49:22.620645  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3178 (* 1 = 3.3178 loss)
-I0510 20:49:22.620659  5307 sgd_solver.cpp:172] Iteration 34400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:50:24.179818  5307 solver.cpp:352] Iteration 34500 (1.62445 iter/s, 61.5592s/100 iter), 66.7/232ep, loss = 3.80377
-I0510 20:50:24.180825  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.96294 (* 1 = 3.96294 loss)
-I0510 20:50:24.180835  5307 sgd_solver.cpp:172] Iteration 34500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:51:24.903394  5307 solver.cpp:352] Iteration 34600 (1.64683 iter/s, 60.7225s/100 iter), 66.9/232ep, loss = 3.86259
-I0510 20:51:24.903481  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41186 (* 1 = 4.41186 loss)
-I0510 20:51:24.903538  5307 sgd_solver.cpp:172] Iteration 34600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:51:46.390770  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:52:25.481698  5307 solver.cpp:352] Iteration 34700 (1.65078 iter/s, 60.5773s/100 iter), 67.1/232ep, loss = 3.66415
-I0510 20:52:25.481909  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71425 (* 1 = 3.71425 loss)
-I0510 20:52:25.481936  5307 sgd_solver.cpp:172] Iteration 34700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:53:25.305434  5307 solver.cpp:352] Iteration 34800 (1.67161 iter/s, 59.8227s/100 iter), 67.3/232ep, loss = 3.60402
-I0510 20:53:25.305531  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56683 (* 1 = 3.56683 loss)
-I0510 20:53:25.305541  5307 sgd_solver.cpp:172] Iteration 34800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:54:25.806474  5307 solver.cpp:352] Iteration 34900 (1.65289 iter/s, 60.5s/100 iter), 67.5/232ep, loss = 3.95134
-I0510 20:54:25.806650  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80422 (* 1 = 3.80422 loss)
-I0510 20:54:25.806704  5307 sgd_solver.cpp:172] Iteration 34900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:55:26.613881  5307 solver.cpp:352] Iteration 35000 (1.64456 iter/s, 60.8064s/100 iter), 67.7/232ep, loss = 3.76141
-I0510 20:55:26.613971  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25462 (* 1 = 3.25462 loss)
-I0510 20:55:26.613988  5307 sgd_solver.cpp:172] Iteration 35000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:56:27.344899  5307 solver.cpp:352] Iteration 35100 (1.64663 iter/s, 60.73s/100 iter), 67.9/232ep, loss = 3.5772
-I0510 20:56:27.344980  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69115 (* 1 = 3.69115 loss)
-I0510 20:56:27.344990  5307 sgd_solver.cpp:172] Iteration 35100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:56:59.136808  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:57:27.278641  5307 solver.cpp:352] Iteration 35200 (1.66854 iter/s, 59.9327s/100 iter), 68.1/232ep, loss = 3.73241
-I0510 20:57:27.278709  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85551 (* 1 = 3.85551 loss)
-I0510 20:57:27.278722  5307 sgd_solver.cpp:172] Iteration 35200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:58:27.649441  5307 solver.cpp:352] Iteration 35300 (1.65646 iter/s, 60.3698s/100 iter), 68.2/232ep, loss = 3.69123
-I0510 20:58:27.649540  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00623 (* 1 = 4.00623 loss)
-I0510 20:58:27.649559  5307 sgd_solver.cpp:172] Iteration 35300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:59:28.589807  5307 solver.cpp:352] Iteration 35400 (1.64098 iter/s, 60.9393s/100 iter), 68.4/232ep, loss = 3.6245
-I0510 20:59:28.589917  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83925 (* 1 = 3.83925 loss)
-I0510 20:59:28.589929  5307 sgd_solver.cpp:172] Iteration 35400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:00:28.993971  5307 solver.cpp:352] Iteration 35500 (1.65554 iter/s, 60.4032s/100 iter), 68.6/232ep, loss = 3.68356
-I0510 21:00:28.994617  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54682 (* 1 = 3.54682 loss)
-I0510 21:00:28.994635  5307 sgd_solver.cpp:172] Iteration 35500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:01:29.870028  5307 solver.cpp:352] Iteration 35600 (1.64271 iter/s, 60.875s/100 iter), 68.8/232ep, loss = 3.76594
-I0510 21:01:29.870085  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28141 (* 1 = 3.28141 loss)
-I0510 21:01:29.870092  5307 sgd_solver.cpp:172] Iteration 35600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:02:11.876209  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:02:29.675426  5307 solver.cpp:352] Iteration 35700 (1.67212 iter/s, 59.8044s/100 iter), 69/232ep, loss = 3.60164
-I0510 21:02:29.675454  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.09273 (* 1 = 4.09273 loss)
-I0510 21:02:29.675460  5307 sgd_solver.cpp:172] Iteration 35700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:03:30.000664  5307 solver.cpp:352] Iteration 35800 (1.65771 iter/s, 60.3242s/100 iter), 69.2/232ep, loss = 3.59873
-I0510 21:03:30.000756  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.98077 (* 1 = 3.98077 loss)
-I0510 21:03:30.000772  5307 sgd_solver.cpp:172] Iteration 35800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:04:30.281559  5307 solver.cpp:352] Iteration 35900 (1.65893 iter/s, 60.2799s/100 iter), 69.4/232ep, loss = 3.67615
-I0510 21:04:30.281621  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51516 (* 1 = 3.51516 loss)
-I0510 21:04:30.281631  5307 sgd_solver.cpp:172] Iteration 35900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:05:30.561995  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_36000.caffemodel
-I0510 21:05:30.577775  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_36000.solverstate
-I0510 21:05:30.582509  5307 solver.cpp:635] Iteration 36000, Testing net (#0)
-I0510 21:06:11.008594  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:06:11.250401  5307 solver.cpp:747] class AP 1: 0.568783
-I0510 21:06:11.251291  5307 solver.cpp:747] class AP 2: 0.65916
-I0510 21:06:11.261994  5307 solver.cpp:747] class AP 3: 0.446317
-I0510 21:06:11.267140  5307 solver.cpp:747] class AP 4: 0.395777
-I0510 21:06:11.279081  5307 solver.cpp:747] class AP 5: 0.260131
-I0510 21:06:11.279667  5307 solver.cpp:747] class AP 6: 0.619327
-I0510 21:06:11.286386  5307 solver.cpp:747] class AP 7: 0.635646
-I0510 21:06:11.287024  5307 solver.cpp:747] class AP 8: 0.685365
-I0510 21:06:11.310312  5307 solver.cpp:747] class AP 9: 0.308565
-I0510 21:06:11.311499  5307 solver.cpp:747] class AP 10: 0.4708
-I0510 21:06:11.312520  5307 solver.cpp:747] class AP 11: 0.476802
-I0510 21:06:11.314118  5307 solver.cpp:747] class AP 12: 0.617592
-I0510 21:06:11.314607  5307 solver.cpp:747] class AP 13: 0.680942
-I0510 21:06:11.315171  5307 solver.cpp:747] class AP 14: 0.635709
-I0510 21:06:11.376093  5307 solver.cpp:747] class AP 15: 0.637665
-I0510 21:06:11.382761  5307 solver.cpp:747] class AP 16: 0.224308
-I0510 21:06:11.392376  5307 solver.cpp:747] class AP 17: 0.440435
-I0510 21:06:11.393535  5307 solver.cpp:747] class AP 18: 0.524649
-I0510 21:06:11.394313  5307 solver.cpp:747] class AP 19: 0.632256
-I0510 21:06:11.395380  5307 solver.cpp:747] class AP 20: 0.475234
-I0510 21:06:11.395386  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.519773
-I0510 21:06:11.395527  5307 solver.cpp:283] Tests completed in 101.112s
-I0510 21:06:11.943778  5307 solver.cpp:352] Iteration 36000 (0.989 iter/s, 101.112s/100 iter), 69.6/232ep, loss = 3.35457
-I0510 21:06:11.943830  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43099 (* 1 = 3.43099 loss)
-I0510 21:06:11.943842  5307 sgd_solver.cpp:172] Iteration 36000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:07:12.810127  5307 solver.cpp:352] Iteration 36100 (1.64297 iter/s, 60.8653s/100 iter), 69.8/232ep, loss = 3.67175
-I0510 21:07:12.810981  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53452 (* 1 = 3.53452 loss)
-I0510 21:07:12.811048  5307 sgd_solver.cpp:172] Iteration 36100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:08:05.406282  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:08:13.164630  5307 solver.cpp:352] Iteration 36200 (1.65691 iter/s, 60.3534s/100 iter), 70/232ep, loss = 3.62086
-I0510 21:08:13.164672  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.69297 (* 1 = 2.69297 loss)
-I0510 21:08:13.164682  5307 sgd_solver.cpp:172] Iteration 36200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:09:13.744716  5307 solver.cpp:352] Iteration 36300 (1.65074 iter/s, 60.579s/100 iter), 70.2/232ep, loss = 3.5315
-I0510 21:09:13.744881  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55787 (* 1 = 3.55787 loss)
-I0510 21:09:13.744909  5307 sgd_solver.cpp:172] Iteration 36300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:10:14.500439  5307 solver.cpp:352] Iteration 36400 (1.64596 iter/s, 60.7547s/100 iter), 70.4/232ep, loss = 3.63935
-I0510 21:10:14.500519  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89221 (* 1 = 3.89221 loss)
-I0510 21:10:14.500545  5307 sgd_solver.cpp:172] Iteration 36400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:11:14.099763  5307 solver.cpp:352] Iteration 36500 (1.6779 iter/s, 59.5983s/100 iter), 70.6/232ep, loss = 3.9966
-I0510 21:11:14.099948  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.81575 (* 1 = 3.81575 loss)
-I0510 21:11:14.099975  5307 sgd_solver.cpp:172] Iteration 36500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:12:14.474020  5307 solver.cpp:352] Iteration 36600 (1.65636 iter/s, 60.3732s/100 iter), 70.8/232ep, loss = 3.64754
-I0510 21:12:14.485167  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13334 (* 1 = 3.13334 loss)
-I0510 21:12:14.485191  5307 sgd_solver.cpp:172] Iteration 36600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:13:14.260732  5307 solver.cpp:352] Iteration 36700 (1.67264 iter/s, 59.7857s/100 iter), 71/232ep, loss = 3.69982
-I0510 21:13:14.260835  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.12445 (* 1 = 4.12445 loss)
-I0510 21:13:14.260859  5307 sgd_solver.cpp:172] Iteration 36700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:13:17.213470  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:14:13.801023  5307 solver.cpp:352] Iteration 36800 (1.67956 iter/s, 59.5393s/100 iter), 71.1/232ep, loss = 3.5667
-I0510 21:14:13.801134  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63345 (* 1 = 3.63345 loss)
-I0510 21:14:13.801147  5307 sgd_solver.cpp:172] Iteration 36800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:15:14.316159  5307 solver.cpp:352] Iteration 36900 (1.65251 iter/s, 60.5141s/100 iter), 71.3/232ep, loss = 3.71623
-I0510 21:15:14.316234  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73786 (* 1 = 2.73786 loss)
-I0510 21:15:14.316244  5307 sgd_solver.cpp:172] Iteration 36900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:16:14.722913  5307 solver.cpp:352] Iteration 37000 (1.65547 iter/s, 60.4057s/100 iter), 71.5/232ep, loss = 3.5448
-I0510 21:16:14.722980  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92331 (* 1 = 2.92331 loss)
-I0510 21:16:14.722988  5307 sgd_solver.cpp:172] Iteration 37000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:17:14.764508  5307 solver.cpp:352] Iteration 37100 (1.66554 iter/s, 60.0406s/100 iter), 71.7/232ep, loss = 3.59719
-I0510 21:17:14.764567  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05983 (* 1 = 4.05983 loss)
-I0510 21:17:14.764573  5307 sgd_solver.cpp:172] Iteration 37100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:18:14.917587  5307 solver.cpp:352] Iteration 37200 (1.66245 iter/s, 60.1521s/100 iter), 71.9/232ep, loss = 3.60382
-I0510 21:18:14.917676  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51662 (* 1 = 3.51662 loss)
-I0510 21:18:14.917697  5307 sgd_solver.cpp:172] Iteration 37200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:18:27.635392  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:19:15.886972  5307 solver.cpp:352] Iteration 37300 (1.6402 iter/s, 60.9683s/100 iter), 72.1/232ep, loss = 3.70657
-I0510 21:19:15.887038  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28576 (* 1 = 3.28576 loss)
-I0510 21:19:15.887046  5307 sgd_solver.cpp:172] Iteration 37300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:20:15.671473  5307 solver.cpp:352] Iteration 37400 (1.6727 iter/s, 59.7835s/100 iter), 72.3/232ep, loss = 3.46799
-I0510 21:20:15.671617  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.14536 (* 1 = 4.14536 loss)
-I0510 21:20:15.671633  5307 sgd_solver.cpp:172] Iteration 37400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:21:17.264648  5307 solver.cpp:352] Iteration 37500 (1.62358 iter/s, 61.5922s/100 iter), 72.5/232ep, loss = 3.59698
-I0510 21:21:17.264725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37801 (* 1 = 3.37801 loss)
-I0510 21:21:17.264735  5307 sgd_solver.cpp:172] Iteration 37500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:22:18.230902  5307 solver.cpp:352] Iteration 37600 (1.64028 iter/s, 60.9652s/100 iter), 72.7/232ep, loss = 3.59863
-I0510 21:22:18.231084  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41289 (* 1 = 3.41289 loss)
-I0510 21:22:18.231132  5307 sgd_solver.cpp:172] Iteration 37600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:23:19.303782  5307 solver.cpp:352] Iteration 37700 (1.63742 iter/s, 61.0719s/100 iter), 72.9/232ep, loss = 3.61308
-I0510 21:23:19.303894  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26588 (* 1 = 3.26588 loss)
-I0510 21:23:19.303903  5307 sgd_solver.cpp:172] Iteration 37700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:23:43.063323  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:24:19.149380  5307 solver.cpp:352] Iteration 37800 (1.67099 iter/s, 59.8446s/100 iter), 73.1/232ep, loss = 3.59578
-I0510 21:24:19.149605  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.75051 (* 1 = 3.75051 loss)
-I0510 21:24:19.149615  5307 sgd_solver.cpp:172] Iteration 37800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:25:19.356627  5307 solver.cpp:352] Iteration 37900 (1.66096 iter/s, 60.2062s/100 iter), 73.3/232ep, loss = 3.73517
-I0510 21:25:19.356943  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.43998 (* 1 = 4.43998 loss)
-I0510 21:25:19.356952  5307 sgd_solver.cpp:172] Iteration 37900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:26:19.011675  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_38000.caffemodel
-I0510 21:26:19.031734  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_38000.solverstate
-I0510 21:26:19.038130  5307 solver.cpp:635] Iteration 38000, Testing net (#0)
-I0510 21:26:59.776566  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:27:00.004941  5307 solver.cpp:747] class AP 1: 0.5052
-I0510 21:27:00.005132  5307 solver.cpp:747] class AP 2: 0.539033
-I0510 21:27:00.010339  5307 solver.cpp:747] class AP 3: 0.357168
-I0510 21:27:00.012910  5307 solver.cpp:747] class AP 4: 0.333069
-I0510 21:27:00.030097  5307 solver.cpp:747] class AP 5: 0.204389
-I0510 21:27:00.030365  5307 solver.cpp:747] class AP 6: 0.609031
-I0510 21:27:00.039222  5307 solver.cpp:747] class AP 7: 0.591758
-I0510 21:27:00.040027  5307 solver.cpp:747] class AP 8: 0.656491
-I0510 21:27:00.071101  5307 solver.cpp:747] class AP 9: 0.298
-I0510 21:27:00.071439  5307 solver.cpp:747] class AP 10: 0.475356
-I0510 21:27:00.071856  5307 solver.cpp:747] class AP 11: 0.50872
-I0510 21:27:00.072576  5307 solver.cpp:747] class AP 12: 0.538248
-I0510 21:27:00.072798  5307 solver.cpp:747] class AP 13: 0.651622
-I0510 21:27:00.073029  5307 solver.cpp:747] class AP 14: 0.562866
-I0510 21:27:00.128082  5307 solver.cpp:747] class AP 15: 0.606885
-I0510 21:27:00.130252  5307 solver.cpp:747] class AP 16: 0.222947
-I0510 21:27:00.132756  5307 solver.cpp:747] class AP 17: 0.437542
-I0510 21:27:00.134523  5307 solver.cpp:747] class AP 18: 0.413573
-I0510 21:27:00.134902  5307 solver.cpp:747] class AP 19: 0.619407
-I0510 21:27:00.136670  5307 solver.cpp:747] class AP 20: 0.461706
-I0510 21:27:00.136685  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.47965
-I0510 21:27:00.136886  5307 solver.cpp:283] Tests completed in 100.779s
-I0510 21:27:00.678278  5307 solver.cpp:352] Iteration 38000 (0.992274 iter/s, 100.779s/100 iter), 73.5/232ep, loss = 3.82641
-I0510 21:27:00.678313  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13177 (* 1 = 3.13177 loss)
-I0510 21:27:00.678320  5307 sgd_solver.cpp:172] Iteration 38000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:28:00.853718  5307 solver.cpp:352] Iteration 38100 (1.66184 iter/s, 60.1744s/100 iter), 73.7/232ep, loss = 3.62437
-I0510 21:28:00.853843  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30541 (* 1 = 3.30541 loss)
-I0510 21:28:00.853859  5307 sgd_solver.cpp:172] Iteration 38100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:29:01.346016  5307 solver.cpp:352] Iteration 38200 (1.65313 iter/s, 60.4912s/100 iter), 73.9/232ep, loss = 3.60155
-I0510 21:29:01.350435  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.7041 (* 1 = 3.7041 loss)
-I0510 21:29:01.350448  5307 sgd_solver.cpp:172] Iteration 38200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:29:35.598528  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:30:01.741117  5307 solver.cpp:352] Iteration 38300 (1.65579 iter/s, 60.3941s/100 iter), 74/232ep, loss = 3.58561
-I0510 21:30:01.741160  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.48464 (* 1 = 3.48464 loss)
-I0510 21:30:01.741169  5307 sgd_solver.cpp:172] Iteration 38300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:31:02.368338  5307 solver.cpp:352] Iteration 38400 (1.64945 iter/s, 60.6262s/100 iter), 74.2/232ep, loss = 3.65317
-I0510 21:31:02.368399  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03553 (* 1 = 4.03553 loss)
-I0510 21:31:02.368409  5307 sgd_solver.cpp:172] Iteration 38400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:32:03.428159  5307 solver.cpp:352] Iteration 38500 (1.63777 iter/s, 61.0588s/100 iter), 74.4/232ep, loss = 3.61148
-I0510 21:32:03.428247  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.8391 (* 1 = 3.8391 loss)
-I0510 21:32:03.428261  5307 sgd_solver.cpp:172] Iteration 38500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:33:03.708784  5307 solver.cpp:352] Iteration 38600 (1.65894 iter/s, 60.2796s/100 iter), 74.6/232ep, loss = 3.81464
-I0510 21:33:03.709264  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.7558 (* 1 = 3.7558 loss)
-I0510 21:33:03.709309  5307 sgd_solver.cpp:172] Iteration 38600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:34:04.382413  5307 solver.cpp:352] Iteration 38700 (1.64819 iter/s, 60.6726s/100 iter), 74.8/232ep, loss = 3.83513
-I0510 21:34:04.382488  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41642 (* 1 = 3.41642 loss)
-I0510 21:34:04.382498  5307 sgd_solver.cpp:172] Iteration 38700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:34:48.086021  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:35:04.040887  5307 solver.cpp:352] Iteration 38800 (1.67624 iter/s, 59.6575s/100 iter), 75/232ep, loss = 3.62916
-I0510 21:35:04.040923  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41938 (* 1 = 4.41938 loss)
-I0510 21:35:04.040931  5307 sgd_solver.cpp:172] Iteration 38800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:36:04.107892  5307 solver.cpp:352] Iteration 38900 (1.66484 iter/s, 60.066s/100 iter), 75.2/232ep, loss = 3.58486
-I0510 21:36:04.107978  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21385 (* 1 = 3.21385 loss)
-I0510 21:36:04.107995  5307 sgd_solver.cpp:172] Iteration 38900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:37:04.114724  5307 solver.cpp:352] Iteration 39000 (1.6665 iter/s, 60.0058s/100 iter), 75.4/232ep, loss = 3.52668
-I0510 21:37:04.115047  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.35119 (* 1 = 4.35119 loss)
-I0510 21:37:04.115056  5307 sgd_solver.cpp:172] Iteration 39000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:38:06.187549  5307 solver.cpp:352] Iteration 39100 (1.61104 iter/s, 62.0718s/100 iter), 75.6/232ep, loss = 3.52495
-I0510 21:38:06.187664  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.16989 (* 1 = 4.16989 loss)
-I0510 21:38:06.187674  5307 sgd_solver.cpp:172] Iteration 39100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:39:15.436691  5307 solver.cpp:352] Iteration 39200 (1.44409 iter/s, 69.248s/100 iter), 75.8/232ep, loss = 3.67819
-I0510 21:39:15.437286  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09562 (* 1 = 3.09562 loss)
-I0510 21:39:15.437294  5307 sgd_solver.cpp:172] Iteration 39200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:40:11.855397  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:40:17.215807  5307 solver.cpp:352] Iteration 39300 (1.6187 iter/s, 61.7781s/100 iter), 76/232ep, loss = 3.78971
-I0510 21:40:17.215832  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55306 (* 1 = 3.55306 loss)
-I0510 21:40:17.215840  5307 sgd_solver.cpp:172] Iteration 39300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:41:17.962391  5307 solver.cpp:352] Iteration 39400 (1.64621 iter/s, 60.7455s/100 iter), 76.2/232ep, loss = 3.89644
-I0510 21:41:17.962517  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11371 (* 1 = 4.11371 loss)
-I0510 21:41:17.962525  5307 sgd_solver.cpp:172] Iteration 39400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:42:18.468636  5307 solver.cpp:352] Iteration 39500 (1.65275 iter/s, 60.5052s/100 iter), 76.4/232ep, loss = 3.64194
-I0510 21:42:18.468721  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74449 (* 1 = 3.74449 loss)
-I0510 21:42:18.468731  5307 sgd_solver.cpp:172] Iteration 39500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:43:19.419124  5307 solver.cpp:352] Iteration 39600 (1.6407 iter/s, 60.9495s/100 iter), 76.6/232ep, loss = 3.63924
-I0510 21:43:19.419281  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61965 (* 1 = 3.61965 loss)
-I0510 21:43:19.419332  5307 sgd_solver.cpp:172] Iteration 39600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:44:20.567492  5307 solver.cpp:352] Iteration 39700 (1.63539 iter/s, 61.1473s/100 iter), 76.8/232ep, loss = 3.65378
-I0510 21:44:20.568058  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64097 (* 1 = 3.64097 loss)
-I0510 21:44:20.568075  5307 sgd_solver.cpp:172] Iteration 39700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:45:20.776649  5307 solver.cpp:352] Iteration 39800 (1.66091 iter/s, 60.2081s/100 iter), 77/232ep, loss = 3.61238
-I0510 21:45:20.776767  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.49909 (* 1 = 3.49909 loss)
-I0510 21:45:20.776785  5307 sgd_solver.cpp:172] Iteration 39800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:45:24.994469  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:46:20.611048  5307 solver.cpp:352] Iteration 39900 (1.67131 iter/s, 59.8334s/100 iter), 77.1/232ep, loss = 3.56136
-I0510 21:46:20.611136  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26811 (* 1 = 3.26811 loss)
-I0510 21:46:20.611156  5307 sgd_solver.cpp:172] Iteration 39900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:47:20.372117  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_40000.caffemodel
-I0510 21:47:20.389097  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_40000.solverstate
-I0510 21:47:20.394568  5307 solver.cpp:635] Iteration 40000, Testing net (#0)
-I0510 21:48:00.663660  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:48:00.872752  5307 solver.cpp:747] class AP 1: 0.520476
-I0510 21:48:00.873112  5307 solver.cpp:747] class AP 2: 0.577247
-I0510 21:48:00.878597  5307 solver.cpp:747] class AP 3: 0.314433
-I0510 21:48:00.879312  5307 solver.cpp:747] class AP 4: 0.335391
-I0510 21:48:00.899533  5307 solver.cpp:747] class AP 5: 0.227511
-I0510 21:48:00.899749  5307 solver.cpp:747] class AP 6: 0.573794
-I0510 21:48:00.905573  5307 solver.cpp:747] class AP 7: 0.569326
-I0510 21:48:00.907130  5307 solver.cpp:747] class AP 8: 0.655245
-I0510 21:48:00.917480  5307 solver.cpp:747] class AP 9: 0.261153
-I0510 21:48:00.918313  5307 solver.cpp:747] class AP 10: 0.416685
-I0510 21:48:00.918567  5307 solver.cpp:747] class AP 11: 0.489146
-I0510 21:48:00.921221  5307 solver.cpp:747] class AP 12: 0.578182
-I0510 21:48:00.921957  5307 solver.cpp:747] class AP 13: 0.706205
-I0510 21:48:00.922250  5307 solver.cpp:747] class AP 14: 0.591031
-I0510 21:48:01.001513  5307 solver.cpp:747] class AP 15: 0.615364
-I0510 21:48:01.005388  5307 solver.cpp:747] class AP 16: 0.207144
-I0510 21:48:01.006865  5307 solver.cpp:747] class AP 17: 0.43087
-I0510 21:48:01.007848  5307 solver.cpp:747] class AP 18: 0.419016
-I0510 21:48:01.008469  5307 solver.cpp:747] class AP 19: 0.614923
-I0510 21:48:01.009793  5307 solver.cpp:747] class AP 20: 0.450545
-I0510 21:48:01.009802  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.477684
-I0510 21:48:01.010001  5307 solver.cpp:283] Tests completed in 100.397s
-I0510 21:48:01.576629  5307 solver.cpp:352] Iteration 40000 (0.996043 iter/s, 100.397s/100 iter), 77.3/232ep, loss = 3.86338
-I0510 21:48:01.576654  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.65106 (* 1 = 4.65106 loss)
-I0510 21:48:01.576660  5307 sgd_solver.cpp:172] Iteration 40000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:49:01.632191  5307 solver.cpp:352] Iteration 40100 (1.66515 iter/s, 60.0545s/100 iter), 77.5/232ep, loss = 3.58973
-I0510 21:49:01.632961  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.6637 (* 1 = 3.6637 loss)
-I0510 21:49:01.632982  5307 sgd_solver.cpp:172] Iteration 40100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:50:02.186213  5307 solver.cpp:352] Iteration 40200 (1.65145 iter/s, 60.553s/100 iter), 77.7/232ep, loss = 3.734
-I0510 21:50:02.187319  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30205 (* 1 = 3.30205 loss)
-I0510 21:50:02.187347  5307 sgd_solver.cpp:172] Iteration 40200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:51:02.389930  5307 solver.cpp:352] Iteration 40300 (1.66106 iter/s, 60.2027s/100 iter), 77.9/232ep, loss = 3.55042
-I0510 21:51:02.389989  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4546 (* 1 = 3.4546 loss)
-I0510 21:51:02.389998  5307 sgd_solver.cpp:172] Iteration 40300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:51:17.505239  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:52:02.887758  5307 solver.cpp:352] Iteration 40400 (1.65298 iter/s, 60.4968s/100 iter), 78.1/232ep, loss = 3.61956
-I0510 21:52:02.887820  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15467 (* 1 = 4.15467 loss)
-I0510 21:52:02.887827  5307 sgd_solver.cpp:172] Iteration 40400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:53:03.079121  5307 solver.cpp:352] Iteration 40500 (1.6614 iter/s, 60.1904s/100 iter), 78.3/232ep, loss = 3.71012
-I0510 21:53:03.079205  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61716 (* 1 = 3.61716 loss)
-I0510 21:53:03.079222  5307 sgd_solver.cpp:172] Iteration 40500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:54:03.590065  5307 solver.cpp:352] Iteration 40600 (1.65262 iter/s, 60.5099s/100 iter), 78.5/232ep, loss = 3.5501
-I0510 21:54:03.590135  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.84851 (* 1 = 2.84851 loss)
-I0510 21:54:03.590147  5307 sgd_solver.cpp:172] Iteration 40600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:55:04.550119  5307 solver.cpp:352] Iteration 40700 (1.64045 iter/s, 60.959s/100 iter), 78.7/232ep, loss = 3.6139
-I0510 21:55:04.550245  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00362 (* 1 = 4.00362 loss)
-I0510 21:55:04.550262  5307 sgd_solver.cpp:172] Iteration 40700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:56:04.426820  5307 solver.cpp:352] Iteration 40800 (1.67013 iter/s, 59.8757s/100 iter), 78.9/232ep, loss = 3.45172
-I0510 21:56:04.426923  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41889 (* 1 = 3.41889 loss)
-I0510 21:56:04.426934  5307 sgd_solver.cpp:172] Iteration 40800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:56:30.006772  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:57:04.665575  5307 solver.cpp:352] Iteration 40900 (1.66009 iter/s, 60.2377s/100 iter), 79.1/232ep, loss = 3.62553
-I0510 21:57:04.665683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69357 (* 1 = 3.69357 loss)
-I0510 21:57:04.665704  5307 sgd_solver.cpp:172] Iteration 40900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:58:04.750860  5307 solver.cpp:352] Iteration 41000 (1.66433 iter/s, 60.0843s/100 iter), 79.3/232ep, loss = 3.74795
-I0510 21:58:04.750957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99367 (* 1 = 2.99367 loss)
-I0510 21:58:04.750977  5307 sgd_solver.cpp:172] Iteration 41000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:59:05.323962  5307 solver.cpp:352] Iteration 41100 (1.65093 iter/s, 60.5721s/100 iter), 79.5/232ep, loss = 3.56803
-I0510 21:59:05.324067  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03478 (* 1 = 4.03478 loss)
-I0510 21:59:05.324082  5307 sgd_solver.cpp:172] Iteration 41100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:00:05.307688  5307 solver.cpp:352] Iteration 41200 (1.66715 iter/s, 59.9827s/100 iter), 79.7/232ep, loss = 3.52172
-I0510 22:00:05.312608  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72247 (* 1 = 3.72247 loss)
-I0510 22:00:05.312623  5307 sgd_solver.cpp:172] Iteration 41200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:01:04.931408  5307 solver.cpp:352] Iteration 41300 (1.67721 iter/s, 59.6227s/100 iter), 79.9/232ep, loss = 3.77013
-I0510 22:01:04.931486  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.49615 (* 1 = 3.49615 loss)
-I0510 22:01:04.931495  5307 sgd_solver.cpp:172] Iteration 41300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:01:40.768656  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:02:05.374547  5307 solver.cpp:352] Iteration 41400 (1.65448 iter/s, 60.4421s/100 iter), 80/232ep, loss = 3.62685
-I0510 22:02:05.374572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10421 (* 1 = 3.10421 loss)
-I0510 22:02:05.374579  5307 sgd_solver.cpp:172] Iteration 41400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:03:06.852798  5307 solver.cpp:352] Iteration 41500 (1.62662 iter/s, 61.4772s/100 iter), 80.2/232ep, loss = 3.50893
-I0510 22:03:06.853668  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39475 (* 1 = 3.39475 loss)
-I0510 22:03:06.853682  5307 sgd_solver.cpp:172] Iteration 41500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:04:07.508661  5307 solver.cpp:352] Iteration 41600 (1.64867 iter/s, 60.6548s/100 iter), 80.4/232ep, loss = 3.59382
-I0510 22:04:07.509981  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.30832 (* 1 = 4.30832 loss)
-I0510 22:04:07.509997  5307 sgd_solver.cpp:172] Iteration 41600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:05:07.744612  5307 solver.cpp:352] Iteration 41700 (1.66017 iter/s, 60.235s/100 iter), 80.6/232ep, loss = 3.74398
-I0510 22:05:07.744665  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21229 (* 1 = 3.21229 loss)
-I0510 22:05:07.744671  5307 sgd_solver.cpp:172] Iteration 41700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:06:08.835930  5307 solver.cpp:352] Iteration 41800 (1.63692 iter/s, 61.0903s/100 iter), 80.8/232ep, loss = 3.61463
-I0510 22:06:08.836014  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87827 (* 1 = 3.87827 loss)
-I0510 22:06:08.836027  5307 sgd_solver.cpp:172] Iteration 41800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:06:55.344455  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:07:09.105779  5307 solver.cpp:352] Iteration 41900 (1.65923 iter/s, 60.2688s/100 iter), 81/232ep, loss = 3.66765
-I0510 22:07:09.105804  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.99514 (* 1 = 3.99514 loss)
-I0510 22:07:09.105813  5307 sgd_solver.cpp:172] Iteration 41900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:08:08.894412  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_42000.caffemodel
-I0510 22:08:08.913151  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_42000.solverstate
-I0510 22:08:08.920022  5307 solver.cpp:635] Iteration 42000, Testing net (#0)
-I0510 22:08:49.789216  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:08:50.003633  5307 solver.cpp:747] class AP 1: 0.534171
-I0510 22:08:50.004140  5307 solver.cpp:747] class AP 2: 0.628472
-I0510 22:08:50.010937  5307 solver.cpp:747] class AP 3: 0.418746
-I0510 22:08:50.014612  5307 solver.cpp:747] class AP 4: 0.364946
-I0510 22:08:50.031375  5307 solver.cpp:747] class AP 5: 0.213854
-I0510 22:08:50.031503  5307 solver.cpp:747] class AP 6: 0.627559
-I0510 22:08:50.041143  5307 solver.cpp:747] class AP 7: 0.620652
-I0510 22:08:50.042007  5307 solver.cpp:747] class AP 8: 0.710804
-I0510 22:08:50.061527  5307 solver.cpp:747] class AP 9: 0.330063
-I0510 22:08:50.061870  5307 solver.cpp:747] class AP 10: 0.504193
-I0510 22:08:50.062520  5307 solver.cpp:747] class AP 11: 0.534669
-I0510 22:08:50.063248  5307 solver.cpp:747] class AP 12: 0.633615
-I0510 22:08:50.063508  5307 solver.cpp:747] class AP 13: 0.705069
-I0510 22:08:50.063880  5307 solver.cpp:747] class AP 14: 0.632479
-I0510 22:08:50.124693  5307 solver.cpp:747] class AP 15: 0.632617
-I0510 22:08:50.129084  5307 solver.cpp:747] class AP 16: 0.246861
-I0510 22:08:50.130812  5307 solver.cpp:747] class AP 17: 0.470018
-I0510 22:08:50.131456  5307 solver.cpp:747] class AP 18: 0.51479
-I0510 22:08:50.131898  5307 solver.cpp:747] class AP 19: 0.688099
-I0510 22:08:50.132757  5307 solver.cpp:747] class AP 20: 0.523382
-I0510 22:08:50.132762  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.526753
-I0510 22:08:50.133000  5307 solver.cpp:283] Tests completed in 101.026s
-I0510 22:08:50.669611  5307 solver.cpp:352] Iteration 42000 (0.989849 iter/s, 101.026s/100 iter), 81.2/232ep, loss = 3.56295
-I0510 22:08:50.669718  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.17089 (* 1 = 3.17089 loss)
-I0510 22:08:50.669739  5307 sgd_solver.cpp:172] Iteration 42000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:09:50.111747  5307 solver.cpp:352] Iteration 42100 (1.68234 iter/s, 59.4411s/100 iter), 81.4/232ep, loss = 3.46262
-I0510 22:09:50.111821  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.23969 (* 1 = 4.23969 loss)
-I0510 22:09:50.111830  5307 sgd_solver.cpp:172] Iteration 42100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:10:50.060981  5307 solver.cpp:352] Iteration 42200 (1.66811 iter/s, 59.9482s/100 iter), 81.6/232ep, loss = 3.44918
-I0510 22:10:50.061062  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74013 (* 1 = 2.74013 loss)
-I0510 22:10:50.061074  5307 sgd_solver.cpp:172] Iteration 42200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:11:50.372360  5307 solver.cpp:352] Iteration 42300 (1.65809 iter/s, 60.3104s/100 iter), 81.8/232ep, loss = 3.7762
-I0510 22:11:50.372473  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85189 (* 1 = 3.85189 loss)
-I0510 22:11:50.372489  5307 sgd_solver.cpp:172] Iteration 42300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:12:46.130507  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:12:50.435878  5307 solver.cpp:352] Iteration 42400 (1.66493 iter/s, 60.0625s/100 iter), 82/232ep, loss = 3.733
-I0510 22:12:50.435904  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.80832 (* 1 = 4.80832 loss)
-I0510 22:12:50.435912  5307 sgd_solver.cpp:172] Iteration 42400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:13:51.216261  5307 solver.cpp:352] Iteration 42500 (1.6453 iter/s, 60.7794s/100 iter), 82.2/232ep, loss = 3.67476
-I0510 22:13:51.216312  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61387 (* 1 = 3.61387 loss)
-I0510 22:13:51.216320  5307 sgd_solver.cpp:172] Iteration 42500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:14:51.837419  5307 solver.cpp:352] Iteration 42600 (1.64962 iter/s, 60.6201s/100 iter), 82.4/232ep, loss = 3.84191
-I0510 22:14:51.837563  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19984 (* 1 = 3.19984 loss)
-I0510 22:14:51.837589  5307 sgd_solver.cpp:172] Iteration 42600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:15:52.448808  5307 solver.cpp:352] Iteration 42700 (1.64988 iter/s, 60.6104s/100 iter), 82.6/232ep, loss = 3.55317
-I0510 22:15:52.448926  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00699 (* 1 = 4.00699 loss)
-I0510 22:15:52.448948  5307 sgd_solver.cpp:172] Iteration 42700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:16:53.346068  5307 solver.cpp:352] Iteration 42800 (1.64214 iter/s, 60.8962s/100 iter), 82.8/232ep, loss = 3.53187
-I0510 22:16:53.346138  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.07234 (* 1 = 4.07234 loss)
-I0510 22:16:53.346146  5307 sgd_solver.cpp:172] Iteration 42800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:17:53.733168  5307 solver.cpp:352] Iteration 42900 (1.65601 iter/s, 60.3861s/100 iter), 82.9/232ep, loss = 3.60057
-I0510 22:17:53.733270  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.17121 (* 1 = 4.17121 loss)
-I0510 22:17:53.733295  5307 sgd_solver.cpp:172] Iteration 42900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:18:00.223826  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:18:54.359382  5307 solver.cpp:352] Iteration 43000 (1.64948 iter/s, 60.6252s/100 iter), 83.1/232ep, loss = 3.46198
-I0510 22:18:54.359463  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06771 (* 1 = 4.06771 loss)
-I0510 22:18:54.359474  5307 sgd_solver.cpp:172] Iteration 43000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:19:55.495054  5307 solver.cpp:352] Iteration 43100 (1.63573 iter/s, 61.1346s/100 iter), 83.3/232ep, loss = 3.58179
-I0510 22:19:55.495151  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99761 (* 1 = 2.99761 loss)
-I0510 22:19:55.495167  5307 sgd_solver.cpp:172] Iteration 43100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:20:57.084606  5307 solver.cpp:352] Iteration 43200 (1.62368 iter/s, 61.5885s/100 iter), 83.5/232ep, loss = 3.36912
-I0510 22:20:57.084743  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31 (* 1 = 3.31 loss)
-I0510 22:20:57.084753  5307 sgd_solver.cpp:172] Iteration 43200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:21:57.941856  5307 solver.cpp:352] Iteration 43300 (1.64322 iter/s, 60.8563s/100 iter), 83.7/232ep, loss = 3.66869
-I0510 22:21:57.941979  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89205 (* 1 = 3.89205 loss)
-I0510 22:21:57.942003  5307 sgd_solver.cpp:172] Iteration 43300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:22:59.763221  5307 solver.cpp:352] Iteration 43400 (1.61759 iter/s, 61.8203s/100 iter), 83.9/232ep, loss = 3.53433
-I0510 22:22:59.763306  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77005 (* 1 = 2.77005 loss)
-I0510 22:22:59.763316  5307 sgd_solver.cpp:172] Iteration 43400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:23:17.433843  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:24:00.845634  5307 solver.cpp:352] Iteration 43500 (1.63716 iter/s, 61.0814s/100 iter), 84.1/232ep, loss = 3.45022
-I0510 22:24:00.845722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95186 (* 1 = 3.95186 loss)
-I0510 22:24:00.845732  5307 sgd_solver.cpp:172] Iteration 43500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:25:00.274463  5307 solver.cpp:352] Iteration 43600 (1.68271 iter/s, 59.4278s/100 iter), 84.3/232ep, loss = 3.60126
-I0510 22:25:00.274605  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.79965 (* 1 = 2.79965 loss)
-I0510 22:25:00.274617  5307 sgd_solver.cpp:172] Iteration 43600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:26:00.962894  5307 solver.cpp:352] Iteration 43700 (1.64779 iter/s, 60.6874s/100 iter), 84.5/232ep, loss = 3.59502
-I0510 22:26:00.964380  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.55997 (* 1 = 2.55997 loss)
-I0510 22:26:00.964414  5307 sgd_solver.cpp:172] Iteration 43700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:27:01.428666  5307 solver.cpp:352] Iteration 43800 (1.65386 iter/s, 60.4647s/100 iter), 84.7/232ep, loss = 3.55229
-I0510 22:27:01.428730  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.97239 (* 1 = 3.97239 loss)
-I0510 22:27:01.428738  5307 sgd_solver.cpp:172] Iteration 43800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:28:02.477066  5307 solver.cpp:352] Iteration 43900 (1.63807 iter/s, 61.0474s/100 iter), 84.9/232ep, loss = 3.45262
-I0510 22:28:02.477171  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.79397 (* 1 = 3.79397 loss)
-I0510 22:28:02.477183  5307 sgd_solver.cpp:172] Iteration 43900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:28:30.984215  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:29:03.972008  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_44000.caffemodel
-I0510 22:29:03.986655  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_44000.solverstate
-I0510 22:29:03.990772  5307 solver.cpp:635] Iteration 44000, Testing net (#0)
-I0510 22:29:44.763483  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:29:45.015172  5307 solver.cpp:747] class AP 1: 0.537234
-I0510 22:29:45.015624  5307 solver.cpp:747] class AP 2: 0.566408
-I0510 22:29:45.019718  5307 solver.cpp:747] class AP 3: 0.411401
-I0510 22:29:45.022940  5307 solver.cpp:747] class AP 4: 0.364857
-I0510 22:29:45.038170  5307 solver.cpp:747] class AP 5: 0.233334
-I0510 22:29:45.038571  5307 solver.cpp:747] class AP 6: 0.629944
-I0510 22:29:45.042909  5307 solver.cpp:747] class AP 7: 0.613214
-I0510 22:29:45.043376  5307 solver.cpp:747] class AP 8: 0.656918
-I0510 22:29:45.063295  5307 solver.cpp:747] class AP 9: 0.338147
-I0510 22:29:45.063719  5307 solver.cpp:747] class AP 10: 0.461028
-I0510 22:29:45.064224  5307 solver.cpp:747] class AP 11: 0.43602
-I0510 22:29:45.064898  5307 solver.cpp:747] class AP 12: 0.606772
-I0510 22:29:45.065259  5307 solver.cpp:747] class AP 13: 0.686549
-I0510 22:29:45.065376  5307 solver.cpp:747] class AP 14: 0.586515
-I0510 22:29:45.134161  5307 solver.cpp:747] class AP 15: 0.635893
-I0510 22:29:45.143028  5307 solver.cpp:747] class AP 16: 0.177475
-I0510 22:29:45.144666  5307 solver.cpp:747] class AP 17: 0.391172
-I0510 22:29:45.145244  5307 solver.cpp:747] class AP 18: 0.434161
-I0510 22:29:45.145675  5307 solver.cpp:747] class AP 19: 0.618719
-I0510 22:29:45.146224  5307 solver.cpp:747] class AP 20: 0.446521
-I0510 22:29:45.146230  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.491614
-I0510 22:29:45.146399  5307 solver.cpp:283] Tests completed in 102.668s
-I0510 22:29:45.713840  5307 solver.cpp:352] Iteration 44000 (0.974017 iter/s, 102.668s/100 iter), 85.1/232ep, loss = 3.40872
-I0510 22:29:45.713865  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.29076 (* 1 = 3.29076 loss)
-I0510 22:29:45.713871  5307 sgd_solver.cpp:172] Iteration 44000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:30:45.584980  5307 solver.cpp:352] Iteration 44100 (1.67028 iter/s, 59.8701s/100 iter), 85.3/232ep, loss = 3.56606
-I0510 22:30:45.586292  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71579 (* 1 = 3.71579 loss)
-I0510 22:30:45.586303  5307 sgd_solver.cpp:172] Iteration 44100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:31:45.395543  5307 solver.cpp:352] Iteration 44200 (1.67197 iter/s, 59.8095s/100 iter), 85.5/232ep, loss = 3.64415
-I0510 22:31:45.395606  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41891 (* 1 = 4.41891 loss)
-I0510 22:31:45.395613  5307 sgd_solver.cpp:172] Iteration 44200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:32:46.211119  5307 solver.cpp:352] Iteration 44300 (1.64434 iter/s, 60.8145s/100 iter), 85.7/232ep, loss = 3.5561
-I0510 22:32:46.211210  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11668 (* 1 = 4.11668 loss)
-I0510 22:32:46.211227  5307 sgd_solver.cpp:172] Iteration 44300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:33:47.296813  5307 solver.cpp:352] Iteration 44400 (1.63707 iter/s, 61.0847s/100 iter), 85.8/232ep, loss = 3.65152
-I0510 22:33:47.296867  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.57339 (* 1 = 4.57339 loss)
-I0510 22:33:47.296875  5307 sgd_solver.cpp:172] Iteration 44400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:34:26.328572  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:34:48.634385  5307 solver.cpp:352] Iteration 44500 (1.63035 iter/s, 61.3365s/100 iter), 86/232ep, loss = 3.51682
-I0510 22:34:48.634536  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.79272 (* 1 = 3.79272 loss)
-I0510 22:34:48.634568  5307 sgd_solver.cpp:172] Iteration 44500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:35:49.449618  5307 solver.cpp:352] Iteration 44600 (1.64435 iter/s, 60.8142s/100 iter), 86.2/232ep, loss = 3.63962
-I0510 22:35:49.451788  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95575 (* 1 = 3.95575 loss)
-I0510 22:35:49.451802  5307 sgd_solver.cpp:172] Iteration 44600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:36:50.505905  5307 solver.cpp:352] Iteration 44700 (1.63786 iter/s, 61.0553s/100 iter), 86.4/232ep, loss = 3.55994
-I0510 22:36:50.506018  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28054 (* 1 = 3.28054 loss)
-I0510 22:36:50.506028  5307 sgd_solver.cpp:172] Iteration 44700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:37:51.268187  5307 solver.cpp:352] Iteration 44800 (1.64579 iter/s, 60.7613s/100 iter), 86.6/232ep, loss = 3.58286
-I0510 22:37:51.268245  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91869 (* 1 = 3.91869 loss)
-I0510 22:37:51.268254  5307 sgd_solver.cpp:172] Iteration 44800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:38:52.239480  5307 solver.cpp:352] Iteration 44900 (1.64014 iter/s, 60.9703s/100 iter), 86.8/232ep, loss = 3.62117
-I0510 22:38:52.241292  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73229 (* 1 = 2.73229 loss)
-I0510 22:38:52.241310  5307 sgd_solver.cpp:172] Iteration 44900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:39:40.497205  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:39:53.324957  5307 solver.cpp:352] Iteration 45000 (1.63708 iter/s, 61.0844s/100 iter), 87/232ep, loss = 3.54813
-I0510 22:39:53.325136  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.86743 (* 1 = 2.86743 loss)
-I0510 22:39:53.325163  5307 sgd_solver.cpp:172] Iteration 45000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:40:53.649266  5307 solver.cpp:352] Iteration 45100 (1.65773 iter/s, 60.3233s/100 iter), 87.2/232ep, loss = 3.34768
-I0510 22:40:53.649327  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63302 (* 1 = 3.63302 loss)
-I0510 22:40:53.649335  5307 sgd_solver.cpp:172] Iteration 45100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:41:53.778311  5307 solver.cpp:352] Iteration 45200 (1.66312 iter/s, 60.128s/100 iter), 87.4/232ep, loss = 3.61005
-I0510 22:41:53.778378  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56444 (* 1 = 3.56444 loss)
-I0510 22:41:53.778388  5307 sgd_solver.cpp:172] Iteration 45200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:42:54.838815  5307 solver.cpp:352] Iteration 45300 (1.63775 iter/s, 61.0595s/100 iter), 87.6/232ep, loss = 3.43124
-I0510 22:42:54.838886  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.88264 (* 1 = 3.88264 loss)
-I0510 22:42:54.838896  5307 sgd_solver.cpp:172] Iteration 45300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:43:55.382688  5307 solver.cpp:352] Iteration 45400 (1.65172 iter/s, 60.5428s/100 iter), 87.8/232ep, loss = 3.39923
-I0510 22:43:55.382769  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00722 (* 1 = 3.00722 loss)
-I0510 22:43:55.382781  5307 sgd_solver.cpp:172] Iteration 45400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:44:53.739300  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:44:55.335280  5307 solver.cpp:352] Iteration 45500 (1.66801 iter/s, 59.9516s/100 iter), 88/232ep, loss = 3.77631
-I0510 22:44:55.335304  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65193 (* 1 = 3.65193 loss)
-I0510 22:44:55.335312  5307 sgd_solver.cpp:172] Iteration 45500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:45:57.312166  5307 solver.cpp:352] Iteration 45600 (1.61353 iter/s, 61.9758s/100 iter), 88.2/232ep, loss = 3.60661
-I0510 22:45:57.312297  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44258 (* 1 = 3.44258 loss)
-I0510 22:45:57.312321  5307 sgd_solver.cpp:172] Iteration 45600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:47:06.872303  5307 solver.cpp:352] Iteration 45700 (1.43763 iter/s, 69.559s/100 iter), 88.4/232ep, loss = 3.70569
-I0510 22:47:06.872428  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80139 (* 1 = 3.80139 loss)
-I0510 22:47:06.872499  5307 sgd_solver.cpp:172] Iteration 45700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:48:08.359077  5307 solver.cpp:352] Iteration 45800 (1.62639 iter/s, 61.4857s/100 iter), 88.6/232ep, loss = 3.43112
-I0510 22:48:08.359217  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58173 (* 1 = 3.58173 loss)
-I0510 22:48:08.359228  5307 sgd_solver.cpp:172] Iteration 45800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:49:09.033349  5307 solver.cpp:352] Iteration 45900 (1.64817 iter/s, 60.6732s/100 iter), 88.7/232ep, loss = 3.56771
-I0510 22:49:09.033437  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74137 (* 1 = 3.74137 loss)
-I0510 22:49:09.033447  5307 sgd_solver.cpp:172] Iteration 45900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:50:08.859191  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_46000.caffemodel
-I0510 22:50:08.871475  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_46000.solverstate
-I0510 22:50:08.877465  5307 solver.cpp:635] Iteration 46000, Testing net (#0)
-I0510 22:50:49.766000  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:50:50.001467  5307 solver.cpp:747] class AP 1: 0.505791
-I0510 22:50:50.002292  5307 solver.cpp:747] class AP 2: 0.564018
-I0510 22:50:50.012104  5307 solver.cpp:747] class AP 3: 0.350009
-I0510 22:50:50.013630  5307 solver.cpp:747] class AP 4: 0.233533
-I0510 22:50:50.032207  5307 solver.cpp:747] class AP 5: 0.18993
-I0510 22:50:50.032379  5307 solver.cpp:747] class AP 6: 0.539161
-I0510 22:50:50.035763  5307 solver.cpp:747] class AP 7: 0.567182
-I0510 22:50:50.036207  5307 solver.cpp:747] class AP 8: 0.649454
-I0510 22:50:50.061702  5307 solver.cpp:747] class AP 9: 0.276798
-I0510 22:50:50.061992  5307 solver.cpp:747] class AP 10: 0.46867
-I0510 22:50:50.062243  5307 solver.cpp:747] class AP 11: 0.443067
-I0510 22:50:50.062950  5307 solver.cpp:747] class AP 12: 0.539027
-I0510 22:50:50.063304  5307 solver.cpp:747] class AP 13: 0.625951
-I0510 22:50:50.063649  5307 solver.cpp:747] class AP 14: 0.53717
-I0510 22:50:50.126659  5307 solver.cpp:747] class AP 15: 0.567079
-I0510 22:50:50.130455  5307 solver.cpp:747] class AP 16: 0.213157
-I0510 22:50:50.132161  5307 solver.cpp:747] class AP 17: 0.450719
-I0510 22:50:50.133276  5307 solver.cpp:747] class AP 18: 0.382244
-I0510 22:50:50.133790  5307 solver.cpp:747] class AP 19: 0.491094
-I0510 22:50:50.134387  5307 solver.cpp:747] class AP 20: 0.415519
-I0510 22:50:50.134392  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.450479
-I0510 22:50:50.134629  5307 solver.cpp:283] Tests completed in 101.1s
-I0510 22:50:50.690054  5307 solver.cpp:352] Iteration 46000 (0.989124 iter/s, 101.1s/100 iter), 88.9/232ep, loss = 3.5812
-I0510 22:50:50.690084  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04849 (* 1 = 3.04849 loss)
-I0510 22:50:50.690093  5307 sgd_solver.cpp:172] Iteration 46000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:50:59.990258  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:51:52.370064  5307 solver.cpp:352] Iteration 46100 (1.6213 iter/s, 61.6789s/100 iter), 89.1/232ep, loss = 3.6177
-I0510 22:51:52.375166  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14417 (* 1 = 3.14417 loss)
-I0510 22:51:52.375182  5307 sgd_solver.cpp:172] Iteration 46100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:52:52.779439  5307 solver.cpp:352] Iteration 46200 (1.6554 iter/s, 60.4083s/100 iter), 89.3/232ep, loss = 3.5219
-I0510 22:52:52.780040  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57021 (* 1 = 3.57021 loss)
-I0510 22:52:52.780048  5307 sgd_solver.cpp:172] Iteration 46200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:53:52.598860  5307 solver.cpp:352] Iteration 46300 (1.67173 iter/s, 59.8184s/100 iter), 89.5/232ep, loss = 3.51801
-I0510 22:53:52.598942  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.62599 (* 1 = 4.62599 loss)
-I0510 22:53:52.598951  5307 sgd_solver.cpp:172] Iteration 46300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:54:54.260977  5307 solver.cpp:352] Iteration 46400 (1.62177 iter/s, 61.6611s/100 iter), 89.7/232ep, loss = 3.51888
-I0510 22:54:54.261050  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83006 (* 1 = 3.83006 loss)
-I0510 22:54:54.261060  5307 sgd_solver.cpp:172] Iteration 46400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:55:55.168646  5307 solver.cpp:352] Iteration 46500 (1.64186 iter/s, 60.9066s/100 iter), 89.9/232ep, loss = 3.59075
-I0510 22:55:55.168771  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46868 (* 1 = 3.46868 loss)
-I0510 22:55:55.168786  5307 sgd_solver.cpp:172] Iteration 46500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:56:14.018493  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:56:55.430907  5307 solver.cpp:352] Iteration 46600 (1.65944 iter/s, 60.2613s/100 iter), 90.1/232ep, loss = 3.5544
-I0510 22:56:55.430966  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53938 (* 1 = 3.53938 loss)
-I0510 22:56:55.430976  5307 sgd_solver.cpp:172] Iteration 46600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:57:55.534490  5307 solver.cpp:352] Iteration 46700 (1.66382 iter/s, 60.1026s/100 iter), 90.3/232ep, loss = 3.58514
-I0510 22:57:55.534706  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84802 (* 1 = 3.84802 loss)
-I0510 22:57:55.534716  5307 sgd_solver.cpp:172] Iteration 46700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:58:56.183460  5307 solver.cpp:352] Iteration 46800 (1.64886 iter/s, 60.648s/100 iter), 90.5/232ep, loss = 3.73727
-I0510 22:58:56.183609  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74044 (* 1 = 3.74044 loss)
-I0510 22:58:56.183665  5307 sgd_solver.cpp:172] Iteration 46800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:59:55.746423  5307 solver.cpp:352] Iteration 46900 (1.67892 iter/s, 59.562s/100 iter), 90.7/232ep, loss = 3.45096
-I0510 22:59:55.747187  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21738 (* 1 = 3.21738 loss)
-I0510 22:59:55.747200  5307 sgd_solver.cpp:172] Iteration 46900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:00:56.605301  5307 solver.cpp:352] Iteration 47000 (1.64317 iter/s, 60.8579s/100 iter), 90.9/232ep, loss = 3.43792
-I0510 23:00:56.605358  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27902 (* 1 = 3.27902 loss)
-I0510 23:00:56.605366  5307 sgd_solver.cpp:172] Iteration 47000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:01:25.881090  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:01:56.549991  5307 solver.cpp:352] Iteration 47100 (1.66823 iter/s, 59.9437s/100 iter), 91.1/232ep, loss = 3.42707
-I0510 23:01:56.550885  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03025 (* 1 = 4.03025 loss)
-I0510 23:01:56.550915  5307 sgd_solver.cpp:172] Iteration 47100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:02:57.036665  5307 solver.cpp:352] Iteration 47200 (1.65328 iter/s, 60.4857s/100 iter), 91.3/232ep, loss = 3.7613
-I0510 23:02:57.036772  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40235 (* 1 = 3.40235 loss)
-I0510 23:02:57.036782  5307 sgd_solver.cpp:172] Iteration 47200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:03:56.531098  5307 solver.cpp:352] Iteration 47300 (1.68086 iter/s, 59.4934s/100 iter), 91.5/232ep, loss = 3.48968
-I0510 23:03:56.531193  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.02474 (* 1 = 3.02474 loss)
-I0510 23:03:56.531200  5307 sgd_solver.cpp:172] Iteration 47300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:04:57.948027  5307 solver.cpp:352] Iteration 47400 (1.62824 iter/s, 61.4159s/100 iter), 91.6/232ep, loss = 3.50518
-I0510 23:04:57.948096  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26962 (* 1 = 3.26962 loss)
-I0510 23:04:57.948105  5307 sgd_solver.cpp:172] Iteration 47400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:05:58.396701  5307 solver.cpp:352] Iteration 47500 (1.65432 iter/s, 60.4476s/100 iter), 91.8/232ep, loss = 3.48586
-I0510 23:05:58.397729  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72773 (* 1 = 3.72773 loss)
-I0510 23:05:58.397742  5307 sgd_solver.cpp:172] Iteration 47500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:06:38.718721  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:06:59.352711  5307 solver.cpp:352] Iteration 47600 (1.64055 iter/s, 60.955s/100 iter), 92/232ep, loss = 3.41207
-I0510 23:06:59.352737  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55819 (* 1 = 3.55819 loss)
-I0510 23:06:59.352746  5307 sgd_solver.cpp:172] Iteration 47600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:08:00.463523  5307 solver.cpp:352] Iteration 47700 (1.6364 iter/s, 61.1098s/100 iter), 92.2/232ep, loss = 3.60284
-I0510 23:08:00.463587  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78579 (* 1 = 3.78579 loss)
-I0510 23:08:00.463596  5307 sgd_solver.cpp:172] Iteration 47700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:09:01.200682  5307 solver.cpp:352] Iteration 47800 (1.64647 iter/s, 60.7361s/100 iter), 92.4/232ep, loss = 3.47811
-I0510 23:09:01.200820  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30471 (* 1 = 3.30471 loss)
-I0510 23:09:01.200846  5307 sgd_solver.cpp:172] Iteration 47800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:10:01.542644  5307 solver.cpp:352] Iteration 47900 (1.65725 iter/s, 60.341s/100 iter), 92.6/232ep, loss = 3.50561
-I0510 23:10:01.542717  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78229 (* 1 = 3.78229 loss)
-I0510 23:10:01.542724  5307 sgd_solver.cpp:172] Iteration 47900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:11:01.568513  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_48000.caffemodel
-I0510 23:11:01.588152  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_48000.solverstate
-I0510 23:11:01.593969  5307 solver.cpp:635] Iteration 48000, Testing net (#0)
-I0510 23:11:42.426506  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:11:42.629566  5307 solver.cpp:747] class AP 1: 0.561305
-I0510 23:11:42.630336  5307 solver.cpp:747] class AP 2: 0.631307
-I0510 23:11:42.641363  5307 solver.cpp:747] class AP 3: 0.430626
-I0510 23:11:42.645922  5307 solver.cpp:747] class AP 4: 0.414595
-I0510 23:11:42.659302  5307 solver.cpp:747] class AP 5: 0.252742
-I0510 23:11:42.659512  5307 solver.cpp:747] class AP 6: 0.633689
-I0510 23:11:42.666606  5307 solver.cpp:747] class AP 7: 0.623457
-I0510 23:11:42.667166  5307 solver.cpp:747] class AP 8: 0.719229
-I0510 23:11:42.683421  5307 solver.cpp:747] class AP 9: 0.326172
-I0510 23:11:42.683758  5307 solver.cpp:747] class AP 10: 0.497288
-I0510 23:11:42.684813  5307 solver.cpp:747] class AP 11: 0.421488
-I0510 23:11:42.685557  5307 solver.cpp:747] class AP 12: 0.630654
-I0510 23:11:42.685842  5307 solver.cpp:747] class AP 13: 0.69289
-I0510 23:11:42.686149  5307 solver.cpp:747] class AP 14: 0.646715
-I0510 23:11:42.750618  5307 solver.cpp:747] class AP 15: 0.665926
-I0510 23:11:42.756969  5307 solver.cpp:747] class AP 16: 0.265218
-I0510 23:11:42.757716  5307 solver.cpp:747] class AP 17: 0.466147
-I0510 23:11:42.758103  5307 solver.cpp:747] class AP 18: 0.448701
-I0510 23:11:42.758491  5307 solver.cpp:747] class AP 19: 0.658598
-I0510 23:11:42.759832  5307 solver.cpp:747] class AP 20: 0.479947
-I0510 23:11:42.759840  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.523335
-I0510 23:11:42.760054  5307 solver.cpp:283] Tests completed in 101.216s
-I0510 23:11:43.307546  5307 solver.cpp:352] Iteration 48000 (0.987989 iter/s, 101.216s/100 iter), 92.8/232ep, loss = 3.52073
-I0510 23:11:43.307855  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.35066 (* 1 = 3.35066 loss)
-I0510 23:11:43.307865  5307 sgd_solver.cpp:172] Iteration 48000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:12:33.688110  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:12:43.568645  5307 solver.cpp:352] Iteration 48100 (1.65947 iter/s, 60.26s/100 iter), 93/232ep, loss = 3.5282
-I0510 23:12:43.568722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78314 (* 1 = 3.78314 loss)
-I0510 23:12:43.568742  5307 sgd_solver.cpp:172] Iteration 48100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:13:43.754045  5307 solver.cpp:352] Iteration 48200 (1.66156 iter/s, 60.1844s/100 iter), 93.2/232ep, loss = 3.47301
-I0510 23:13:43.754109  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.12876 (* 1 = 4.12876 loss)
-I0510 23:13:43.754146  5307 sgd_solver.cpp:172] Iteration 48200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:14:43.993510  5307 solver.cpp:352] Iteration 48300 (1.66007 iter/s, 60.2384s/100 iter), 93.4/232ep, loss = 3.32308
-I0510 23:14:43.993574  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74263 (* 1 = 2.74263 loss)
-I0510 23:14:43.993583  5307 sgd_solver.cpp:172] Iteration 48300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:15:44.278393  5307 solver.cpp:352] Iteration 48400 (1.65882 iter/s, 60.2839s/100 iter), 93.6/232ep, loss = 3.54178
-I0510 23:15:44.278501  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.06438 (* 1 = 3.06438 loss)
-I0510 23:15:44.278522  5307 sgd_solver.cpp:172] Iteration 48400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:16:45.246727  5307 solver.cpp:352] Iteration 48500 (1.64022 iter/s, 60.9673s/100 iter), 93.8/232ep, loss = 3.41037
-I0510 23:16:45.247236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.66525 (* 1 = 2.66525 loss)
-I0510 23:16:45.247246  5307 sgd_solver.cpp:172] Iteration 48500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:17:46.222647  5307 solver.cpp:352] Iteration 48600 (1.64002 iter/s, 60.9749s/100 iter), 94/232ep, loss = 3.44866
-I0510 23:17:46.222743  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.40669 (* 1 = 4.40669 loss)
-I0510 23:17:46.222754  5307 sgd_solver.cpp:172] Iteration 48600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:17:46.884136  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:18:46.703645  5307 solver.cpp:352] Iteration 48700 (1.65344 iter/s, 60.48s/100 iter), 94.2/232ep, loss = 3.52651
-I0510 23:18:46.703832  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07363 (* 1 = 3.07363 loss)
-I0510 23:18:46.703843  5307 sgd_solver.cpp:172] Iteration 48700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:19:46.584103  5307 solver.cpp:352] Iteration 48800 (1.67002 iter/s, 59.8794s/100 iter), 94.4/232ep, loss = 3.60143
-I0510 23:19:46.584192  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.7301 (* 1 = 5.7301 loss)
-I0510 23:19:46.584203  5307 sgd_solver.cpp:172] Iteration 48800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:20:47.415668  5307 solver.cpp:352] Iteration 48900 (1.64391 iter/s, 60.8305s/100 iter), 94.5/232ep, loss = 3.5456
-I0510 23:20:47.415730  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.52771 (* 1 = 4.52771 loss)
-I0510 23:20:47.415740  5307 sgd_solver.cpp:172] Iteration 48900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:21:48.702627  5307 solver.cpp:352] Iteration 49000 (1.6317 iter/s, 61.2859s/100 iter), 94.7/232ep, loss = 3.63742
-I0510 23:21:48.702687  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15913 (* 1 = 3.15913 loss)
-I0510 23:21:48.702695  5307 sgd_solver.cpp:172] Iteration 49000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:22:49.551187  5307 solver.cpp:352] Iteration 49100 (1.64345 iter/s, 60.8475s/100 iter), 94.9/232ep, loss = 3.31566
-I0510 23:22:49.551270  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04667 (* 1 = 3.04667 loss)
-I0510 23:22:49.551278  5307 sgd_solver.cpp:172] Iteration 49100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:22:59.950218  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:23:49.574358  5307 solver.cpp:352] Iteration 49200 (1.66605 iter/s, 60.0222s/100 iter), 95.1/232ep, loss = 3.35315
-I0510 23:23:49.575289  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41286 (* 1 = 3.41286 loss)
-I0510 23:23:49.575297  5307 sgd_solver.cpp:172] Iteration 49200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:24:50.395352  5307 solver.cpp:352] Iteration 49300 (1.6442 iter/s, 60.82s/100 iter), 95.3/232ep, loss = 3.40763
-I0510 23:24:50.395437  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00214 (* 1 = 3.00214 loss)
-I0510 23:24:50.395447  5307 sgd_solver.cpp:172] Iteration 49300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:25:50.372149  5307 solver.cpp:352] Iteration 49400 (1.66734 iter/s, 59.9758s/100 iter), 95.5/232ep, loss = 3.49907
-I0510 23:25:50.372229  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41385 (* 1 = 4.41385 loss)
-I0510 23:25:50.372244  5307 sgd_solver.cpp:172] Iteration 49400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:26:50.997179  5307 solver.cpp:352] Iteration 49500 (1.64951 iter/s, 60.624s/100 iter), 95.7/232ep, loss = 3.59319
-I0510 23:26:50.997364  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9471 (* 1 = 2.9471 loss)
-I0510 23:26:50.997385  5307 sgd_solver.cpp:172] Iteration 49500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:27:51.858150  5307 solver.cpp:352] Iteration 49600 (1.64312 iter/s, 60.8599s/100 iter), 95.9/232ep, loss = 3.64598
-I0510 23:27:51.858709  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03478 (* 1 = 3.03478 loss)
-I0510 23:27:51.858719  5307 sgd_solver.cpp:172] Iteration 49600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:28:13.082340  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:28:52.739567  5307 solver.cpp:352] Iteration 49700 (1.64257 iter/s, 60.8804s/100 iter), 96.1/232ep, loss = 3.42936
-I0510 23:28:52.740306  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38264 (* 1 = 3.38264 loss)
-I0510 23:28:52.740326  5307 sgd_solver.cpp:172] Iteration 49700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:29:52.705199  5307 solver.cpp:352] Iteration 49800 (1.66765 iter/s, 59.9646s/100 iter), 96.3/232ep, loss = 3.6499
-I0510 23:29:52.705310  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.27572 (* 1 = 4.27572 loss)
-I0510 23:29:52.705402  5307 sgd_solver.cpp:172] Iteration 49800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:30:53.042645  5307 solver.cpp:352] Iteration 49900 (1.65737 iter/s, 60.3364s/100 iter), 96.5/232ep, loss = 3.74318
-I0510 23:30:53.042707  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.01434 (* 1 = 5.01434 loss)
-I0510 23:30:53.042718  5307 sgd_solver.cpp:172] Iteration 49900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:31:53.273087  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_50000.caffemodel
-I0510 23:31:53.290220  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_50000.solverstate
-I0510 23:31:53.295753  5307 solver.cpp:635] Iteration 50000, Testing net (#0)
-I0510 23:32:33.427985  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:32:33.640146  5307 solver.cpp:747] class AP 1: 0.498915
-I0510 23:32:33.640626  5307 solver.cpp:747] class AP 2: 0.585154
-I0510 23:32:33.648393  5307 solver.cpp:747] class AP 3: 0.417897
-I0510 23:32:33.664778  5307 solver.cpp:747] class AP 4: 0.337787
-I0510 23:32:33.674645  5307 solver.cpp:747] class AP 5: 0.251842
-I0510 23:32:33.676306  5307 solver.cpp:747] class AP 6: 0.628646
-I0510 23:32:33.684816  5307 solver.cpp:747] class AP 7: 0.572198
-I0510 23:32:33.685539  5307 solver.cpp:747] class AP 8: 0.663112
-I0510 23:32:33.709209  5307 solver.cpp:747] class AP 9: 0.282948
-I0510 23:32:33.710723  5307 solver.cpp:747] class AP 10: 0.427062
-I0510 23:32:33.711442  5307 solver.cpp:747] class AP 11: 0.48655
-I0510 23:32:33.712664  5307 solver.cpp:747] class AP 12: 0.581236
-I0510 23:32:33.713263  5307 solver.cpp:747] class AP 13: 0.654671
-I0510 23:32:33.713531  5307 solver.cpp:747] class AP 14: 0.589124
-I0510 23:32:33.759228  5307 solver.cpp:747] class AP 15: 0.633411
-I0510 23:32:33.766373  5307 solver.cpp:747] class AP 16: 0.243572
-I0510 23:32:33.774631  5307 solver.cpp:747] class AP 17: 0.457656
-I0510 23:32:33.775758  5307 solver.cpp:747] class AP 18: 0.471969
-I0510 23:32:33.776513  5307 solver.cpp:747] class AP 19: 0.627506
-I0510 23:32:33.778980  5307 solver.cpp:747] class AP 20: 0.464373
-I0510 23:32:33.778993  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.493781
-I0510 23:32:33.779156  5307 solver.cpp:283] Tests completed in 100.735s
-I0510 23:32:34.377696  5307 solver.cpp:352] Iteration 50000 (0.992705 iter/s, 100.735s/100 iter), 96.7/232ep, loss = 3.42507
-I0510 23:32:34.377723  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.44672 (* 1 = 4.44672 loss)
-I0510 23:32:34.377730  5307 sgd_solver.cpp:172] Iteration 50000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:33:35.872683  5307 solver.cpp:352] Iteration 50100 (1.62618 iter/s, 61.4939s/100 iter), 96.9/232ep, loss = 3.44612
-I0510 23:33:35.873013  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74043 (* 1 = 3.74043 loss)
-I0510 23:33:35.873035  5307 sgd_solver.cpp:172] Iteration 50100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:34:07.855278  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:34:36.364137  5307 solver.cpp:352] Iteration 50200 (1.65315 iter/s, 60.4904s/100 iter), 97.1/232ep, loss = 3.55674
-I0510 23:34:36.364169  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.44396 (* 1 = 4.44396 loss)
-I0510 23:34:36.364176  5307 sgd_solver.cpp:172] Iteration 50200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:35:35.969579  5307 solver.cpp:352] Iteration 50300 (1.67773 iter/s, 59.6044s/100 iter), 97.3/232ep, loss = 3.51906
-I0510 23:35:35.969683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.32653 (* 1 = 4.32653 loss)
-I0510 23:35:35.969761  5307 sgd_solver.cpp:172] Iteration 50300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:36:36.370111  5307 solver.cpp:352] Iteration 50400 (1.65564 iter/s, 60.3995s/100 iter), 97.4/232ep, loss = 3.47102
-I0510 23:36:36.370185  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71015 (* 1 = 3.71015 loss)
-I0510 23:36:36.370198  5307 sgd_solver.cpp:172] Iteration 50400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:37:37.328444  5307 solver.cpp:352] Iteration 50500 (1.64049 iter/s, 60.9573s/100 iter), 97.6/232ep, loss = 3.49171
-I0510 23:37:37.328510  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7692 (* 1 = 2.7692 loss)
-I0510 23:37:37.328521  5307 sgd_solver.cpp:172] Iteration 50500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:38:37.899471  5307 solver.cpp:352] Iteration 50600 (1.65098 iter/s, 60.57s/100 iter), 97.8/232ep, loss = 3.53187
-I0510 23:38:37.899546  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51964 (* 1 = 3.51964 loss)
-I0510 23:38:37.899555  5307 sgd_solver.cpp:172] Iteration 50600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:39:19.902827  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:39:38.853461  5307 solver.cpp:352] Iteration 50700 (1.64061 iter/s, 60.953s/100 iter), 98/232ep, loss = 3.48521
-I0510 23:39:38.853549  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83649 (* 1 = 3.83649 loss)
-I0510 23:39:38.853569  5307 sgd_solver.cpp:172] Iteration 50700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:40:39.750469  5307 solver.cpp:352] Iteration 50800 (1.64214 iter/s, 60.896s/100 iter), 98.2/232ep, loss = 3.33293
-I0510 23:40:39.750550  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.94241 (* 1 = 3.94241 loss)
-I0510 23:40:39.750560  5307 sgd_solver.cpp:172] Iteration 50800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:41:40.515030  5307 solver.cpp:352] Iteration 50900 (1.64572 iter/s, 60.7635s/100 iter), 98.4/232ep, loss = 3.48554
-I0510 23:41:40.515100  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14265 (* 1 = 3.14265 loss)
-I0510 23:41:40.515107  5307 sgd_solver.cpp:172] Iteration 50900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:42:41.899195  5307 solver.cpp:352] Iteration 51000 (1.62911 iter/s, 61.3831s/100 iter), 98.6/232ep, loss = 3.37388
-I0510 23:42:41.899366  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59194 (* 1 = 3.59194 loss)
-I0510 23:42:41.899385  5307 sgd_solver.cpp:172] Iteration 51000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:43:43.308969  5307 solver.cpp:352] Iteration 51100 (1.62843 iter/s, 61.4087s/100 iter), 98.8/232ep, loss = 3.53026
-I0510 23:43:43.309039  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1463 (* 1 = 3.1463 loss)
-I0510 23:43:43.309047  5307 sgd_solver.cpp:172] Iteration 51100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:44:37.293272  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:44:45.357547  5307 solver.cpp:352] Iteration 51200 (1.61167 iter/s, 62.0475s/100 iter), 99/232ep, loss = 3.4011
-I0510 23:44:45.357604  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56569 (* 1 = 3.56569 loss)
-I0510 23:44:45.357622  5307 sgd_solver.cpp:172] Iteration 51200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:45:47.347355  5307 solver.cpp:352] Iteration 51300 (1.6132 iter/s, 61.9888s/100 iter), 99.2/232ep, loss = 3.5833
-I0510 23:45:47.347461  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82223 (* 1 = 3.82223 loss)
-I0510 23:45:47.347473  5307 sgd_solver.cpp:172] Iteration 51300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:46:49.121846  5307 solver.cpp:352] Iteration 51400 (1.61882 iter/s, 61.7735s/100 iter), 99.4/232ep, loss = 3.3464
-I0510 23:46:49.122498  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88903 (* 1 = 2.88903 loss)
-I0510 23:46:49.122505  5307 sgd_solver.cpp:172] Iteration 51400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:47:50.326306  5307 solver.cpp:352] Iteration 51500 (1.6339 iter/s, 61.2034s/100 iter), 99.6/232ep, loss = 3.49587
-I0510 23:47:50.326407  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25812 (* 1 = 3.25812 loss)
-I0510 23:47:50.326422  5307 sgd_solver.cpp:172] Iteration 51500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:48:50.905516  5307 solver.cpp:352] Iteration 51600 (1.65076 iter/s, 60.5782s/100 iter), 99.8/232ep, loss = 3.49921
-I0510 23:48:50.905804  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91085 (* 1 = 2.91085 loss)
-I0510 23:48:50.905815  5307 sgd_solver.cpp:172] Iteration 51600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:49:52.094168  5307 solver.cpp:352] Iteration 51700 (1.63432 iter/s, 61.1876s/100 iter), 100/232ep, loss = 3.39004
-I0510 23:49:52.094250  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73419 (* 1 = 2.73419 loss)
-I0510 23:49:52.094262  5307 sgd_solver.cpp:172] Iteration 51700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:49:53.973093  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:50:52.856155  5307 solver.cpp:352] Iteration 51800 (1.64579 iter/s, 60.761s/100 iter), 100.2/232ep, loss = 3.36415
-I0510 23:50:52.856760  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68732 (* 1 = 3.68732 loss)
-I0510 23:50:52.856777  5307 sgd_solver.cpp:172] Iteration 51800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:51:54.498759  5307 solver.cpp:352] Iteration 51900 (1.62228 iter/s, 61.6416s/100 iter), 100.3/232ep, loss = 3.44527
-I0510 23:51:54.498867  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07261 (* 1 = 3.07261 loss)
-I0510 23:51:54.498878  5307 sgd_solver.cpp:172] Iteration 51900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:52:55.465734  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_52000.caffemodel
-I0510 23:52:55.483183  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_52000.solverstate
-I0510 23:52:55.490092  5307 solver.cpp:635] Iteration 52000, Testing net (#0)
-I0510 23:53:35.352563  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:53:35.534699  5307 solver.cpp:747] class AP 1: 0.518978
-I0510 23:53:35.535761  5307 solver.cpp:747] class AP 2: 0.636386
-I0510 23:53:35.548604  5307 solver.cpp:747] class AP 3: 0.366596
-I0510 23:53:35.551271  5307 solver.cpp:747] class AP 4: 0.37599
-I0510 23:53:35.572114  5307 solver.cpp:747] class AP 5: 0.227827
-I0510 23:53:35.572397  5307 solver.cpp:747] class AP 6: 0.615003
-I0510 23:53:35.578673  5307 solver.cpp:747] class AP 7: 0.608683
-I0510 23:53:35.579653  5307 solver.cpp:747] class AP 8: 0.675214
-I0510 23:53:35.606160  5307 solver.cpp:747] class AP 9: 0.318541
-I0510 23:53:35.606945  5307 solver.cpp:747] class AP 10: 0.467367
-I0510 23:53:35.607692  5307 solver.cpp:747] class AP 11: 0.484164
-I0510 23:53:35.608516  5307 solver.cpp:747] class AP 12: 0.578948
-I0510 23:53:35.608963  5307 solver.cpp:747] class AP 13: 0.713434
-I0510 23:53:35.609189  5307 solver.cpp:747] class AP 14: 0.620618
-I0510 23:53:35.680815  5307 solver.cpp:747] class AP 15: 0.642361
-I0510 23:53:35.699427  5307 solver.cpp:747] class AP 16: 0.23837
-I0510 23:53:35.703963  5307 solver.cpp:747] class AP 17: 0.460253
-I0510 23:53:35.705580  5307 solver.cpp:747] class AP 18: 0.542439
-I0510 23:53:35.706110  5307 solver.cpp:747] class AP 19: 0.657206
-I0510 23:53:35.707695  5307 solver.cpp:747] class AP 20: 0.473692
-I0510 23:53:35.707732  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.511103
-I0510 23:53:35.707897  5307 solver.cpp:283] Tests completed in 101.207s
-I0510 23:53:36.340836  5307 solver.cpp:352] Iteration 52000 (0.98807 iter/s, 101.207s/100 iter), 100.5/232ep, loss = 3.33154
-I0510 23:53:36.340910  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54616 (* 1 = 3.54616 loss)
-I0510 23:53:36.340932  5307 sgd_solver.cpp:172] Iteration 52000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:54:44.919634  5307 solver.cpp:352] Iteration 52100 (1.4582 iter/s, 68.5776s/100 iter), 100.7/232ep, loss = 3.29883
-I0510 23:54:44.922762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15171 (* 1 = 4.15171 loss)
-I0510 23:54:44.922811  5307 sgd_solver.cpp:172] Iteration 52100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:55:47.649695  5307 solver.cpp:352] Iteration 52200 (1.59416 iter/s, 62.729s/100 iter), 100.9/232ep, loss = 3.4715
-I0510 23:55:47.649773  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65583 (* 1 = 3.65583 loss)
-I0510 23:55:47.649786  5307 sgd_solver.cpp:172] Iteration 52200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:56:00.402654  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:56:47.282253  5307 solver.cpp:352] Iteration 52300 (1.67696 iter/s, 59.6315s/100 iter), 101.1/232ep, loss = 3.6139
-I0510 23:56:47.282346  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04672 (* 1 = 3.04672 loss)
-I0510 23:56:47.282354  5307 sgd_solver.cpp:172] Iteration 52300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:57:48.046723  5307 solver.cpp:352] Iteration 52400 (1.64573 iter/s, 60.7634s/100 iter), 101.3/232ep, loss = 3.62294
-I0510 23:57:48.046809  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25532 (* 1 = 3.25532 loss)
-I0510 23:57:48.046818  5307 sgd_solver.cpp:172] Iteration 52400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:58:48.641021  5307 solver.cpp:352] Iteration 52500 (1.65035 iter/s, 60.5933s/100 iter), 101.5/232ep, loss = 3.43837
-I0510 23:58:48.641079  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36506 (* 1 = 3.36506 loss)
-I0510 23:58:48.641089  5307 sgd_solver.cpp:172] Iteration 52500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:59:49.140475  5307 solver.cpp:352] Iteration 52600 (1.65294 iter/s, 60.4984s/100 iter), 101.7/232ep, loss = 3.55552
-I0510 23:59:49.140640  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.77614 (* 1 = 3.77614 loss)
-I0510 23:59:49.140661  5307 sgd_solver.cpp:172] Iteration 52600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:00:49.939690  5307 solver.cpp:352] Iteration 52700 (1.64479 iter/s, 60.7982s/100 iter), 101.9/232ep, loss = 3.40258
-I0511 00:00:49.939792  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.58967 (* 1 = 2.58967 loss)
-I0511 00:00:49.939841  5307 sgd_solver.cpp:172] Iteration 52700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:01:13.674773  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:01:51.234668  5307 solver.cpp:352] Iteration 52800 (1.63148 iter/s, 61.2939s/100 iter), 102.1/232ep, loss = 3.52778
-I0511 00:01:51.235667  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.6839 (* 1 = 3.6839 loss)
-I0511 00:01:51.235677  5307 sgd_solver.cpp:172] Iteration 52800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:02:52.080087  5307 solver.cpp:352] Iteration 52900 (1.64354 iter/s, 60.8444s/100 iter), 102.3/232ep, loss = 3.51606
-I0511 00:02:52.080184  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.61498 (* 1 = 2.61498 loss)
-I0511 00:02:52.080193  5307 sgd_solver.cpp:172] Iteration 52900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:03:51.713644  5307 solver.cpp:352] Iteration 53000 (1.67694 iter/s, 59.6325s/100 iter), 102.5/232ep, loss = 3.56518
-I0511 00:03:51.713754  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.98872 (* 1 = 2.98872 loss)
-I0511 00:03:51.713768  5307 sgd_solver.cpp:172] Iteration 53000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:04:51.912704  5307 solver.cpp:352] Iteration 53100 (1.66118 iter/s, 60.198s/100 iter), 102.7/232ep, loss = 3.60422
-I0511 00:04:51.912780  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.43261 (* 1 = 4.43261 loss)
-I0511 00:04:51.912791  5307 sgd_solver.cpp:172] Iteration 53100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:05:52.756698  5307 solver.cpp:352] Iteration 53200 (1.64358 iter/s, 60.843s/100 iter), 102.9/232ep, loss = 3.65099
-I0511 00:05:52.756784  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59315 (* 1 = 3.59315 loss)
-I0511 00:05:52.756800  5307 sgd_solver.cpp:172] Iteration 53200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:06:26.347018  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:06:53.908424  5307 solver.cpp:352] Iteration 53300 (1.6353 iter/s, 61.1507s/100 iter), 103.1/232ep, loss = 3.49781
-I0511 00:06:53.908447  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37101 (* 1 = 3.37101 loss)
-I0511 00:06:53.908455  5307 sgd_solver.cpp:172] Iteration 53300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:07:55.388799  5307 solver.cpp:352] Iteration 53400 (1.62656 iter/s, 61.4793s/100 iter), 103.2/232ep, loss = 3.4449
-I0511 00:07:55.388917  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.35449 (* 1 = 3.35449 loss)
-I0511 00:07:55.388942  5307 sgd_solver.cpp:172] Iteration 53400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:08:55.777259  5307 solver.cpp:352] Iteration 53500 (1.65597 iter/s, 60.3874s/100 iter), 103.4/232ep, loss = 3.47036
-I0511 00:08:55.777381  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.902 (* 1 = 3.902 loss)
-I0511 00:08:55.777406  5307 sgd_solver.cpp:172] Iteration 53500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:09:55.897388  5307 solver.cpp:352] Iteration 53600 (1.66336 iter/s, 60.1191s/100 iter), 103.6/232ep, loss = 3.55858
-I0511 00:09:55.897610  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.62222 (* 1 = 2.62222 loss)
-I0511 00:09:55.897622  5307 sgd_solver.cpp:172] Iteration 53600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:10:55.804698  5307 solver.cpp:352] Iteration 53700 (1.66927 iter/s, 59.9063s/100 iter), 103.8/232ep, loss = 3.53354
-I0511 00:10:55.804759  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07751 (* 1 = 3.07751 loss)
-I0511 00:10:55.804765  5307 sgd_solver.cpp:172] Iteration 53700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:11:39.663512  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:11:56.229519  5307 solver.cpp:352] Iteration 53800 (1.65498 iter/s, 60.4238s/100 iter), 104/232ep, loss = 3.35147
-I0511 00:11:56.229543  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7491 (* 1 = 2.7491 loss)
-I0511 00:11:56.229549  5307 sgd_solver.cpp:172] Iteration 53800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:12:56.770020  5307 solver.cpp:352] Iteration 53900 (1.65181 iter/s, 60.5395s/100 iter), 104.2/232ep, loss = 3.51365
-I0511 00:12:56.770087  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95267 (* 1 = 2.95267 loss)
-I0511 00:12:56.770093  5307 sgd_solver.cpp:172] Iteration 53900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:13:56.372295  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_54000.caffemodel
-I0511 00:13:56.389125  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_54000.solverstate
-I0511 00:13:56.394472  5307 solver.cpp:635] Iteration 54000, Testing net (#0)
-I0511 00:14:37.672940  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:14:37.919394  5307 solver.cpp:747] class AP 1: 0.525506
-I0511 00:14:37.919723  5307 solver.cpp:747] class AP 2: 0.623355
-I0511 00:14:37.921825  5307 solver.cpp:747] class AP 3: 0.432165
-I0511 00:14:37.923365  5307 solver.cpp:747] class AP 4: 0.382349
-I0511 00:14:37.949615  5307 solver.cpp:747] class AP 5: 0.247984
-I0511 00:14:37.949892  5307 solver.cpp:747] class AP 6: 0.653941
-I0511 00:14:37.955955  5307 solver.cpp:747] class AP 7: 0.630902
-I0511 00:14:37.956923  5307 solver.cpp:747] class AP 8: 0.71827
-I0511 00:14:37.979024  5307 solver.cpp:747] class AP 9: 0.326747
-I0511 00:14:37.979353  5307 solver.cpp:747] class AP 10: 0.480525
-I0511 00:14:37.980017  5307 solver.cpp:747] class AP 11: 0.530881
-I0511 00:14:37.980465  5307 solver.cpp:747] class AP 12: 0.623067
-I0511 00:14:37.980967  5307 solver.cpp:747] class AP 13: 0.69642
-I0511 00:14:37.981154  5307 solver.cpp:747] class AP 14: 0.665992
-I0511 00:14:38.042522  5307 solver.cpp:747] class AP 15: 0.670577
-I0511 00:14:38.047544  5307 solver.cpp:747] class AP 16: 0.282663
-I0511 00:14:38.048463  5307 solver.cpp:747] class AP 17: 0.492775
-I0511 00:14:38.049235  5307 solver.cpp:747] class AP 18: 0.524552
-I0511 00:14:38.050112  5307 solver.cpp:747] class AP 19: 0.65139
-I0511 00:14:38.052436  5307 solver.cpp:747] class AP 20: 0.517409
-I0511 00:14:38.052445  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.533873
-I0511 00:14:38.052774  5307 solver.cpp:283] Tests completed in 101.281s
-I0511 00:14:38.590441  5307 solver.cpp:352] Iteration 54000 (0.987352 iter/s, 101.281s/100 iter), 104.4/232ep, loss = 3.6458
-I0511 00:14:38.590467  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11997 (* 1 = 4.11997 loss)
-I0511 00:14:38.590474  5307 sgd_solver.cpp:172] Iteration 54000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:15:37.921257  5307 solver.cpp:352] Iteration 54100 (1.68549 iter/s, 59.3298s/100 iter), 104.6/232ep, loss = 3.58635
-I0511 00:15:37.921360  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27227 (* 1 = 3.27227 loss)
-I0511 00:15:37.921370  5307 sgd_solver.cpp:172] Iteration 54100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:16:37.701010  5307 solver.cpp:352] Iteration 54200 (1.67284 iter/s, 59.7787s/100 iter), 104.8/232ep, loss = 3.72543
-I0511 00:16:37.702693  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84609 (* 1 = 3.84609 loss)
-I0511 00:16:37.702716  5307 sgd_solver.cpp:172] Iteration 54200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:17:31.908587  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:17:38.575501  5307 solver.cpp:352] Iteration 54300 (1.64275 iter/s, 60.8734s/100 iter), 105/232ep, loss = 3.60018
-I0511 00:17:38.575531  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38112 (* 1 = 3.38112 loss)
-I0511 00:17:38.575538  5307 sgd_solver.cpp:172] Iteration 54300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:18:38.992295  5307 solver.cpp:352] Iteration 54400 (1.6552 iter/s, 60.4158s/100 iter), 105.2/232ep, loss = 3.65693
-I0511 00:18:38.992363  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51708 (* 1 = 2.51708 loss)
-I0511 00:18:38.992372  5307 sgd_solver.cpp:172] Iteration 54400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:19:39.192565  5307 solver.cpp:352] Iteration 54500 (1.66115 iter/s, 60.1992s/100 iter), 105.4/232ep, loss = 3.34804
-I0511 00:19:39.192680  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.07612 (* 1 = 4.07612 loss)
-I0511 00:19:39.192697  5307 sgd_solver.cpp:172] Iteration 54500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:20:39.840927  5307 solver.cpp:352] Iteration 54600 (1.64888 iter/s, 60.6473s/100 iter), 105.6/232ep, loss = 3.49878
-I0511 00:20:39.841084  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.6027 (* 1 = 4.6027 loss)
-I0511 00:20:39.841110  5307 sgd_solver.cpp:172] Iteration 54600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:21:40.356724  5307 solver.cpp:352] Iteration 54700 (1.65249 iter/s, 60.5148s/100 iter), 105.8/232ep, loss = 3.41457
-I0511 00:21:40.356827  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73008 (* 1 = 2.73008 loss)
-I0511 00:21:40.356837  5307 sgd_solver.cpp:172] Iteration 54700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:22:40.322903  5307 solver.cpp:352] Iteration 54800 (1.66763 iter/s, 59.9652s/100 iter), 106/232ep, loss = 3.46247
-I0511 00:22:40.324194  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.50552 (* 1 = 2.50552 loss)
-I0511 00:22:40.324211  5307 sgd_solver.cpp:172] Iteration 54800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:22:44.903548  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:23:40.294348  5307 solver.cpp:352] Iteration 54900 (1.66749 iter/s, 59.9704s/100 iter), 106.1/232ep, loss = 3.46535
-I0511 00:23:40.294414  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37254 (* 1 = 3.37254 loss)
-I0511 00:23:40.294423  5307 sgd_solver.cpp:172] Iteration 54900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:24:40.674048  5307 solver.cpp:352] Iteration 55000 (1.65621 iter/s, 60.3787s/100 iter), 106.3/232ep, loss = 3.60302
-I0511 00:24:40.674123  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72011 (* 1 = 3.72011 loss)
-I0511 00:24:40.674132  5307 sgd_solver.cpp:172] Iteration 55000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:25:42.052397  5307 solver.cpp:352] Iteration 55100 (1.62927 iter/s, 61.3773s/100 iter), 106.5/232ep, loss = 3.48589
-I0511 00:25:42.052486  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.69904 (* 1 = 2.69904 loss)
-I0511 00:25:42.052500  5307 sgd_solver.cpp:172] Iteration 55100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:26:41.886087  5307 solver.cpp:352] Iteration 55200 (1.67133 iter/s, 59.8327s/100 iter), 106.7/232ep, loss = 3.52104
-I0511 00:26:41.886149  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02414 (* 1 = 4.02414 loss)
-I0511 00:26:41.886157  5307 sgd_solver.cpp:172] Iteration 55200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:27:42.614260  5307 solver.cpp:352] Iteration 55300 (1.64671 iter/s, 60.7271s/100 iter), 106.9/232ep, loss = 3.50302
-I0511 00:27:42.614336  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99667 (* 1 = 2.99667 loss)
-I0511 00:27:42.614346  5307 sgd_solver.cpp:172] Iteration 55300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:27:57.643421  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:28:42.579155  5307 solver.cpp:352] Iteration 55400 (1.66767 iter/s, 59.9639s/100 iter), 107.1/232ep, loss = 3.60342
-I0511 00:28:42.579264  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53387 (* 1 = 3.53387 loss)
-I0511 00:28:42.579288  5307 sgd_solver.cpp:172] Iteration 55400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:29:43.274452  5307 solver.cpp:352] Iteration 55500 (1.6476 iter/s, 60.6943s/100 iter), 107.3/232ep, loss = 3.50229
-I0511 00:29:43.274533  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57112 (* 1 = 3.57112 loss)
-I0511 00:29:43.274541  5307 sgd_solver.cpp:172] Iteration 55500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:30:43.800295  5307 solver.cpp:352] Iteration 55600 (1.65222 iter/s, 60.5248s/100 iter), 107.5/232ep, loss = 3.44192
-I0511 00:30:43.804119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46049 (* 1 = 3.46049 loss)
-I0511 00:30:43.804157  5307 sgd_solver.cpp:172] Iteration 55600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:31:44.431244  5307 solver.cpp:352] Iteration 55700 (1.64935 iter/s, 60.6299s/100 iter), 107.7/232ep, loss = 3.45246
-I0511 00:31:44.431331  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.46113 (* 1 = 2.46113 loss)
-I0511 00:31:44.431356  5307 sgd_solver.cpp:172] Iteration 55700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:32:45.694702  5307 solver.cpp:352] Iteration 55800 (1.63232 iter/s, 61.2624s/100 iter), 107.9/232ep, loss = 3.40326
-I0511 00:32:45.694761  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.0129 (* 1 = 3.0129 loss)
-I0511 00:32:45.694770  5307 sgd_solver.cpp:172] Iteration 55800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:33:10.587299  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:33:46.352715  5307 solver.cpp:352] Iteration 55900 (1.64862 iter/s, 60.6569s/100 iter), 108.1/232ep, loss = 3.54755
-I0511 00:33:46.352850  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69712 (* 1 = 3.69712 loss)
-I0511 00:33:46.352869  5307 sgd_solver.cpp:172] Iteration 55900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:34:46.579649  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_56000.caffemodel
-I0511 00:34:46.599112  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_56000.solverstate
-I0511 00:34:46.605146  5307 solver.cpp:635] Iteration 56000, Testing net (#0)
-I0511 00:35:27.777395  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:35:28.025400  5307 solver.cpp:747] class AP 1: 0.535526
-I0511 00:35:28.026069  5307 solver.cpp:747] class AP 2: 0.638728
-I0511 00:35:28.036048  5307 solver.cpp:747] class AP 3: 0.429233
-I0511 00:35:28.038990  5307 solver.cpp:747] class AP 4: 0.333136
-I0511 00:35:28.053520  5307 solver.cpp:747] class AP 5: 0.211951
-I0511 00:35:28.053802  5307 solver.cpp:747] class AP 6: 0.661569
-I0511 00:35:28.064337  5307 solver.cpp:747] class AP 7: 0.616551
-I0511 00:35:28.064812  5307 solver.cpp:747] class AP 8: 0.672303
-I0511 00:35:28.090167  5307 solver.cpp:747] class AP 9: 0.349538
-I0511 00:35:28.090848  5307 solver.cpp:747] class AP 10: 0.511583
-I0511 00:35:28.091517  5307 solver.cpp:747] class AP 11: 0.503518
-I0511 00:35:28.092128  5307 solver.cpp:747] class AP 12: 0.58544
-I0511 00:35:28.092429  5307 solver.cpp:747] class AP 13: 0.694684
-I0511 00:35:28.092682  5307 solver.cpp:747] class AP 14: 0.630494
-I0511 00:35:28.145862  5307 solver.cpp:747] class AP 15: 0.655244
-I0511 00:35:28.150086  5307 solver.cpp:747] class AP 16: 0.245485
-I0511 00:35:28.153009  5307 solver.cpp:747] class AP 17: 0.516143
-I0511 00:35:28.153900  5307 solver.cpp:747] class AP 18: 0.465221
-I0511 00:35:28.154693  5307 solver.cpp:747] class AP 19: 0.633202
-I0511 00:35:28.155895  5307 solver.cpp:747] class AP 20: 0.515829
-I0511 00:35:28.155906  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.520269
-I0511 00:35:28.156122  5307 solver.cpp:283] Tests completed in 101.802s
-I0511 00:35:28.712455  5307 solver.cpp:352] Iteration 56000 (0.982302 iter/s, 101.802s/100 iter), 108.3/232ep, loss = 3.7071
-I0511 00:35:28.712481  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10523 (* 1 = 3.10523 loss)
-I0511 00:35:28.712489  5307 sgd_solver.cpp:172] Iteration 56000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:36:28.768484  5307 solver.cpp:352] Iteration 56100 (1.66514 iter/s, 60.055s/100 iter), 108.5/232ep, loss = 3.5618
-I0511 00:36:28.768560  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67482 (* 1 = 3.67482 loss)
-I0511 00:36:28.768570  5307 sgd_solver.cpp:172] Iteration 56100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:37:29.082165  5307 solver.cpp:352] Iteration 56200 (1.65803 iter/s, 60.3126s/100 iter), 108.7/232ep, loss = 3.36023
-I0511 00:37:29.083581  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33626 (* 1 = 3.33626 loss)
-I0511 00:37:29.083616  5307 sgd_solver.cpp:172] Iteration 56200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:38:30.046433  5307 solver.cpp:352] Iteration 56300 (1.64033 iter/s, 60.9632s/100 iter), 108.9/232ep, loss = 3.67072
-I0511 00:38:30.046625  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69164 (* 1 = 3.69164 loss)
-I0511 00:38:30.046633  5307 sgd_solver.cpp:172] Iteration 56300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:39:05.675428  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:39:29.936378  5307 solver.cpp:352] Iteration 56400 (1.66976 iter/s, 59.8889s/100 iter), 109/232ep, loss = 3.347
-I0511 00:39:29.936400  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32941 (* 1 = 3.32941 loss)
-I0511 00:39:29.936405  5307 sgd_solver.cpp:172] Iteration 56400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:40:30.386986  5307 solver.cpp:352] Iteration 56500 (1.65427 iter/s, 60.4496s/100 iter), 109.2/232ep, loss = 3.47285
-I0511 00:40:30.387064  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59983 (* 1 = 3.59983 loss)
-I0511 00:40:30.387073  5307 sgd_solver.cpp:172] Iteration 56500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:41:30.451970  5307 solver.cpp:352] Iteration 56600 (1.66489 iter/s, 60.064s/100 iter), 109.4/232ep, loss = 3.34361
-I0511 00:41:30.452033  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31377 (* 1 = 3.31377 loss)
-I0511 00:41:30.452042  5307 sgd_solver.cpp:172] Iteration 56600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:42:31.110832  5307 solver.cpp:352] Iteration 56700 (1.64859 iter/s, 60.6578s/100 iter), 109.6/232ep, loss = 3.63717
-I0511 00:42:31.110963  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51525 (* 1 = 3.51525 loss)
-I0511 00:42:31.110978  5307 sgd_solver.cpp:172] Iteration 56700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:43:31.553923  5307 solver.cpp:352] Iteration 56800 (1.65448 iter/s, 60.4421s/100 iter), 109.8/232ep, loss = 3.71151
-I0511 00:43:31.553988  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05874 (* 1 = 4.05874 loss)
-I0511 00:43:31.553997  5307 sgd_solver.cpp:172] Iteration 56800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:44:18.155795  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:44:32.454998  5307 solver.cpp:352] Iteration 56900 (1.64204 iter/s, 60.9s/100 iter), 110/232ep, loss = 3.56385
-I0511 00:44:32.455027  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38724 (* 1 = 3.38724 loss)
-I0511 00:44:32.455034  5307 sgd_solver.cpp:172] Iteration 56900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:45:32.628466  5307 solver.cpp:352] Iteration 57000 (1.66189 iter/s, 60.1725s/100 iter), 110.2/232ep, loss = 3.36299
-I0511 00:45:32.628590  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87368 (* 1 = 3.87368 loss)
-I0511 00:45:32.628612  5307 sgd_solver.cpp:172] Iteration 57000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:46:33.259104  5307 solver.cpp:352] Iteration 57100 (1.64936 iter/s, 60.6296s/100 iter), 110.4/232ep, loss = 3.57393
-I0511 00:46:33.259186  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.70297 (* 1 = 3.70297 loss)
-I0511 00:46:33.259202  5307 sgd_solver.cpp:172] Iteration 57100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:47:34.351581  5307 solver.cpp:352] Iteration 57200 (1.63689 iter/s, 61.0914s/100 iter), 110.6/232ep, loss = 3.46394
-I0511 00:47:34.351634  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81547 (* 1 = 2.81547 loss)
-I0511 00:47:34.351642  5307 sgd_solver.cpp:172] Iteration 57200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:48:34.817998  5307 solver.cpp:352] Iteration 57300 (1.65384 iter/s, 60.4654s/100 iter), 110.8/232ep, loss = 3.3979
-I0511 00:48:34.818073  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7929 (* 1 = 2.7929 loss)
-I0511 00:48:34.818079  5307 sgd_solver.cpp:172] Iteration 57300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:49:32.352228  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:49:36.503605  5307 solver.cpp:352] Iteration 57400 (1.62115 iter/s, 61.6846s/100 iter), 111/232ep, loss = 3.83276
-I0511 00:49:36.503638  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1509 (* 1 = 3.1509 loss)
-I0511 00:49:36.503646  5307 sgd_solver.cpp:172] Iteration 57400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:50:38.050436  5307 solver.cpp:352] Iteration 57500 (1.62481 iter/s, 61.5458s/100 iter), 111.2/232ep, loss = 3.42789
-I0511 00:50:38.050493  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65941 (* 1 = 3.65941 loss)
-I0511 00:50:38.050503  5307 sgd_solver.cpp:172] Iteration 57500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:51:40.025753  5307 solver.cpp:352] Iteration 57600 (1.61357 iter/s, 61.9743s/100 iter), 111.4/232ep, loss = 3.73921
-I0511 00:51:40.026000  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.20821 (* 1 = 4.20821 loss)
-I0511 00:51:40.026042  5307 sgd_solver.cpp:172] Iteration 57600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:52:41.653494  5307 solver.cpp:352] Iteration 57700 (1.62267 iter/s, 61.6267s/100 iter), 111.6/232ep, loss = 3.42248
-I0511 00:52:41.653587  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36359 (* 1 = 3.36359 loss)
-I0511 00:52:41.653602  5307 sgd_solver.cpp:172] Iteration 57700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:53:42.557371  5307 solver.cpp:352] Iteration 57800 (1.64196 iter/s, 60.9028s/100 iter), 111.8/232ep, loss = 3.44499
-I0511 00:53:42.557584  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.86643 (* 1 = 3.86643 loss)
-I0511 00:53:42.557593  5307 sgd_solver.cpp:172] Iteration 57800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:54:43.308697  5307 solver.cpp:352] Iteration 57900 (1.64608 iter/s, 60.7503s/100 iter), 111.9/232ep, loss = 3.27644
-I0511 00:54:43.308866  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.78733 (* 1 = 2.78733 loss)
-I0511 00:54:43.308876  5307 sgd_solver.cpp:172] Iteration 57900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:54:50.058835  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:55:43.244065  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_58000.caffemodel
-I0511 00:55:43.258394  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_58000.solverstate
-I0511 00:55:43.266721  5307 solver.cpp:635] Iteration 58000, Testing net (#0)
-I0511 00:56:24.250465  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:56:24.440966  5307 solver.cpp:747] class AP 1: 0.536921
-I0511 00:56:24.441691  5307 solver.cpp:747] class AP 2: 0.636741
-I0511 00:56:24.448153  5307 solver.cpp:747] class AP 3: 0.475505
-I0511 00:56:24.453078  5307 solver.cpp:747] class AP 4: 0.408649
-I0511 00:56:24.466481  5307 solver.cpp:747] class AP 5: 0.271112
-I0511 00:56:24.466751  5307 solver.cpp:747] class AP 6: 0.634191
-I0511 00:56:24.474997  5307 solver.cpp:747] class AP 7: 0.636721
-I0511 00:56:24.475579  5307 solver.cpp:747] class AP 8: 0.72689
-I0511 00:56:24.498325  5307 solver.cpp:747] class AP 9: 0.362138
-I0511 00:56:24.499078  5307 solver.cpp:747] class AP 10: 0.496736
-I0511 00:56:24.500514  5307 solver.cpp:747] class AP 11: 0.492416
-I0511 00:56:24.501749  5307 solver.cpp:747] class AP 12: 0.646025
-I0511 00:56:24.502315  5307 solver.cpp:747] class AP 13: 0.765683
-I0511 00:56:24.502632  5307 solver.cpp:747] class AP 14: 0.669449
-I0511 00:56:24.566150  5307 solver.cpp:747] class AP 15: 0.672423
-I0511 00:56:24.569351  5307 solver.cpp:747] class AP 16: 0.284018
-I0511 00:56:24.570860  5307 solver.cpp:747] class AP 17: 0.476287
-I0511 00:56:24.571535  5307 solver.cpp:747] class AP 18: 0.55905
-I0511 00:56:24.572093  5307 solver.cpp:747] class AP 19: 0.676947
-I0511 00:56:24.572917  5307 solver.cpp:747] class AP 20: 0.550362
-I0511 00:56:24.572924  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.548913
-I0511 00:56:24.573099  5307 solver.cpp:283] Tests completed in 101.263s
-I0511 00:56:25.165314  5307 solver.cpp:352] Iteration 58000 (0.98753 iter/s, 101.263s/100 iter), 112.1/232ep, loss = 3.30281
-I0511 00:56:25.165344  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47412 (* 1 = 3.47412 loss)
-I0511 00:56:25.165351  5307 sgd_solver.cpp:172] Iteration 58000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:57:25.432214  5307 solver.cpp:352] Iteration 58100 (1.65931 iter/s, 60.2658s/100 iter), 112.3/232ep, loss = 3.57495
-I0511 00:57:25.432303  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09301 (* 1 = 3.09301 loss)
-I0511 00:57:25.432313  5307 sgd_solver.cpp:172] Iteration 58100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:58:25.854038  5307 solver.cpp:352] Iteration 58200 (1.65506 iter/s, 60.4207s/100 iter), 112.5/232ep, loss = 3.37738
-I0511 00:58:25.854207  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47003 (* 1 = 3.47003 loss)
-I0511 00:58:25.854228  5307 sgd_solver.cpp:172] Iteration 58200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:59:25.874824  5307 solver.cpp:352] Iteration 58300 (1.66612 iter/s, 60.0198s/100 iter), 112.7/232ep, loss = 3.43581
-I0511 00:59:25.874918  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27225 (* 1 = 3.27225 loss)
-I0511 00:59:25.874928  5307 sgd_solver.cpp:172] Iteration 58300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:00:27.051739  5307 solver.cpp:352] Iteration 58400 (1.63463 iter/s, 61.1759s/100 iter), 112.9/232ep, loss = 3.4495
-I0511 01:00:27.051857  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92781 (* 1 = 2.92781 loss)
-I0511 01:00:27.051867  5307 sgd_solver.cpp:172] Iteration 58400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:00:43.793057  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:01:30.215191  5307 solver.cpp:352] Iteration 58500 (1.58322 iter/s, 63.1624s/100 iter), 113.1/232ep, loss = 3.54849
-I0511 01:01:30.217983  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15411 (* 1 = 3.15411 loss)
-I0511 01:01:30.218010  5307 sgd_solver.cpp:172] Iteration 58500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:02:39.419816  5307 solver.cpp:352] Iteration 58600 (1.44501 iter/s, 69.2034s/100 iter), 113.3/232ep, loss = 3.44474
-I0511 01:02:39.419972  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19437 (* 1 = 3.19437 loss)
-I0511 01:02:39.419981  5307 sgd_solver.cpp:172] Iteration 58600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:03:41.282872  5307 solver.cpp:352] Iteration 58700 (1.6165 iter/s, 61.862s/100 iter), 113.5/232ep, loss = 3.48314
-I0511 01:03:41.282948  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47422 (* 1 = 3.47422 loss)
-I0511 01:03:41.282958  5307 sgd_solver.cpp:172] Iteration 58700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:04:42.387756  5307 solver.cpp:352] Iteration 58800 (1.63656 iter/s, 61.1038s/100 iter), 113.7/232ep, loss = 3.30446
-I0511 01:04:42.387814  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03247 (* 1 = 4.03247 loss)
-I0511 01:04:42.387821  5307 sgd_solver.cpp:172] Iteration 58800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:05:42.568261  5307 solver.cpp:352] Iteration 58900 (1.6617 iter/s, 60.1795s/100 iter), 113.9/232ep, loss = 3.26982
-I0511 01:05:42.568331  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71852 (* 1 = 2.71852 loss)
-I0511 01:05:42.568341  5307 sgd_solver.cpp:172] Iteration 58900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:06:09.855984  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:06:43.287122  5307 solver.cpp:352] Iteration 59000 (1.64696 iter/s, 60.7178s/100 iter), 114.1/232ep, loss = 3.40579
-I0511 01:06:43.287201  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13 (* 1 = 3.13 loss)
-I0511 01:06:43.287211  5307 sgd_solver.cpp:172] Iteration 59000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:07:43.903594  5307 solver.cpp:352] Iteration 59100 (1.64974 iter/s, 60.6154s/100 iter), 114.3/232ep, loss = 3.52119
-I0511 01:07:43.903730  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2336 (* 1 = 3.2336 loss)
-I0511 01:07:43.903741  5307 sgd_solver.cpp:172] Iteration 59100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:08:44.515570  5307 solver.cpp:352] Iteration 59200 (1.64987 iter/s, 60.611s/100 iter), 114.5/232ep, loss = 3.51671
-I0511 01:08:44.515648  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63872 (* 1 = 3.63872 loss)
-I0511 01:08:44.515664  5307 sgd_solver.cpp:172] Iteration 59200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:09:44.930148  5307 solver.cpp:352] Iteration 59300 (1.65526 iter/s, 60.4136s/100 iter), 114.7/232ep, loss = 3.38098
-I0511 01:09:44.930215  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.86821 (* 1 = 3.86821 loss)
-I0511 01:09:44.930222  5307 sgd_solver.cpp:172] Iteration 59300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:10:44.699968  5307 solver.cpp:352] Iteration 59400 (1.67311 iter/s, 59.7688s/100 iter), 114.8/232ep, loss = 3.61522
-I0511 01:10:44.700042  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.49936 (* 1 = 3.49936 loss)
-I0511 01:10:44.700050  5307 sgd_solver.cpp:172] Iteration 59400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:11:22.176784  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:11:44.708138  5307 solver.cpp:352] Iteration 59500 (1.66647 iter/s, 60.0071s/100 iter), 115/232ep, loss = 3.24844
-I0511 01:11:44.708240  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.93217 (* 1 = 2.93217 loss)
-I0511 01:11:44.708266  5307 sgd_solver.cpp:172] Iteration 59500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:12:45.026967  5307 solver.cpp:352] Iteration 59600 (1.65788 iter/s, 60.3178s/100 iter), 115.2/232ep, loss = 3.47464
-I0511 01:12:45.027045  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0506 (* 1 = 4.0506 loss)
-I0511 01:12:45.027056  5307 sgd_solver.cpp:172] Iteration 59600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:13:45.293133  5307 solver.cpp:352] Iteration 59700 (1.65933 iter/s, 60.2651s/100 iter), 115.4/232ep, loss = 3.29606
-I0511 01:13:45.293268  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.21834 (* 1 = 2.21834 loss)
-I0511 01:13:45.293280  5307 sgd_solver.cpp:172] Iteration 59700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:14:45.865222  5307 solver.cpp:352] Iteration 59800 (1.65095 iter/s, 60.5711s/100 iter), 115.6/232ep, loss = 3.48137
-I0511 01:14:45.865280  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19146 (* 1 = 3.19146 loss)
-I0511 01:14:45.865288  5307 sgd_solver.cpp:172] Iteration 59800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:15:45.711884  5307 solver.cpp:352] Iteration 59900 (1.67097 iter/s, 59.8456s/100 iter), 115.8/232ep, loss = 3.47236
-I0511 01:15:45.711971  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.97808 (* 1 = 2.97808 loss)
-I0511 01:15:45.711985  5307 sgd_solver.cpp:172] Iteration 59900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:16:34.266850  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:16:46.247411  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_60000.caffemodel
-I0511 01:16:46.265805  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_60000.solverstate
-I0511 01:16:46.271970  5307 solver.cpp:635] Iteration 60000, Testing net (#0)
-I0511 01:17:26.765581  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:17:26.971472  5307 solver.cpp:747] class AP 1: 0.574086
-I0511 01:17:26.971858  5307 solver.cpp:747] class AP 2: 0.613003
-I0511 01:17:26.980267  5307 solver.cpp:747] class AP 3: 0.452021
-I0511 01:17:26.987545  5307 solver.cpp:747] class AP 4: 0.332015
-I0511 01:17:27.011425  5307 solver.cpp:747] class AP 5: 0.259983
-I0511 01:17:27.011533  5307 solver.cpp:747] class AP 6: 0.614489
-I0511 01:17:27.020190  5307 solver.cpp:747] class AP 7: 0.613133
-I0511 01:17:27.021162  5307 solver.cpp:747] class AP 8: 0.677218
-I0511 01:17:27.039156  5307 solver.cpp:747] class AP 9: 0.334882
-I0511 01:17:27.039464  5307 solver.cpp:747] class AP 10: 0.527755
-I0511 01:17:27.040042  5307 solver.cpp:747] class AP 11: 0.480282
-I0511 01:17:27.040508  5307 solver.cpp:747] class AP 12: 0.591494
-I0511 01:17:27.040783  5307 solver.cpp:747] class AP 13: 0.700473
-I0511 01:17:27.041205  5307 solver.cpp:747] class AP 14: 0.655316
-I0511 01:17:27.083600  5307 solver.cpp:747] class AP 15: 0.615903
-I0511 01:17:27.092900  5307 solver.cpp:747] class AP 16: 0.274368
-I0511 01:17:27.094329  5307 solver.cpp:747] class AP 17: 0.427949
-I0511 01:17:27.094879  5307 solver.cpp:747] class AP 18: 0.54173
-I0511 01:17:27.095206  5307 solver.cpp:747] class AP 19: 0.654811
-I0511 01:17:27.096396  5307 solver.cpp:747] class AP 20: 0.495851
-I0511 01:17:27.096405  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.521838
-I0511 01:17:27.096727  5307 solver.cpp:283] Tests completed in 101.383s
-I0511 01:17:27.445214  5355 sgd_solver.cpp:50] MultiStep Status: Iteration 60000, step = 1
-I0511 01:17:27.682260  5307 solver.cpp:352] Iteration 60000 (0.986357 iter/s, 101.383s/100 iter), 116/232ep, loss = 3.57575
-I0511 01:17:27.682317  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59007 (* 1 = 3.59007 loss)
-I0511 01:17:27.682333  5307 sgd_solver.cpp:172] Iteration 60000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:18:29.066782  5307 solver.cpp:352] Iteration 60100 (1.6291 iter/s, 61.3834s/100 iter), 116.2/232ep, loss = 3.33893
-I0511 01:18:29.066859  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36745 (* 1 = 3.36745 loss)
-I0511 01:18:29.066942  5307 sgd_solver.cpp:172] Iteration 60100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:19:30.656616  5307 solver.cpp:352] Iteration 60200 (1.62367 iter/s, 61.5887s/100 iter), 116.4/232ep, loss = 3.30766
-I0511 01:19:30.657325  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.66321 (* 1 = 3.66321 loss)
-I0511 01:19:30.657394  5307 sgd_solver.cpp:172] Iteration 60200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:20:32.139109  5307 solver.cpp:352] Iteration 60300 (1.62651 iter/s, 61.4814s/100 iter), 116.6/232ep, loss = 3.53453
-I0511 01:20:32.139199  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.27908 (* 1 = 4.27908 loss)
-I0511 01:20:32.139214  5307 sgd_solver.cpp:172] Iteration 60300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:21:33.893513  5307 solver.cpp:352] Iteration 60400 (1.61935 iter/s, 61.7534s/100 iter), 116.8/232ep, loss = 3.07137
-I0511 01:21:33.893599  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51694 (* 1 = 2.51694 loss)
-I0511 01:21:33.893795  5307 sgd_solver.cpp:172] Iteration 60400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:22:34.057631  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:22:35.990677  5307 solver.cpp:352] Iteration 60500 (1.61041 iter/s, 62.0961s/100 iter), 117/232ep, loss = 3.3171
-I0511 01:22:35.990705  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99441 (* 1 = 2.99441 loss)
-I0511 01:22:35.990715  5307 sgd_solver.cpp:172] Iteration 60500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:23:37.404093  5307 solver.cpp:352] Iteration 60600 (1.62834 iter/s, 61.4123s/100 iter), 117.2/232ep, loss = 3.38382
-I0511 01:23:37.404161  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96618 (* 1 = 2.96618 loss)
-I0511 01:23:37.404171  5307 sgd_solver.cpp:172] Iteration 60600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:24:39.115162  5307 solver.cpp:352] Iteration 60700 (1.62048 iter/s, 61.71s/100 iter), 117.4/232ep, loss = 3.29782
-I0511 01:24:39.115264  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73199 (* 1 = 2.73199 loss)
-I0511 01:24:39.115273  5307 sgd_solver.cpp:172] Iteration 60700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:25:40.255695  5307 solver.cpp:352] Iteration 60800 (1.6356 iter/s, 61.1395s/100 iter), 117.6/232ep, loss = 3.31946
-I0511 01:25:40.255801  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72749 (* 1 = 3.72749 loss)
-I0511 01:25:40.255810  5307 sgd_solver.cpp:172] Iteration 60800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:26:40.877454  5307 solver.cpp:352] Iteration 60900 (1.6496 iter/s, 60.6207s/100 iter), 117.7/232ep, loss = 3.24465
-I0511 01:26:40.877571  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59557 (* 1 = 3.59557 loss)
-I0511 01:26:40.877586  5307 sgd_solver.cpp:172] Iteration 60900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:27:42.193470  5307 solver.cpp:352] Iteration 61000 (1.63092 iter/s, 61.315s/100 iter), 117.9/232ep, loss = 2.96329
-I0511 01:27:42.195245  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5253 (* 1 = 2.5253 loss)
-I0511 01:27:42.195256  5307 sgd_solver.cpp:172] Iteration 61000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:27:50.109959  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:28:42.751310  5307 solver.cpp:352] Iteration 61100 (1.65134 iter/s, 60.5568s/100 iter), 118.1/232ep, loss = 3.174
-I0511 01:28:42.754483  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.70197 (* 1 = 2.70197 loss)
-I0511 01:28:42.754503  5307 sgd_solver.cpp:172] Iteration 61100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:29:44.676252  5307 solver.cpp:352] Iteration 61200 (1.61489 iter/s, 61.9239s/100 iter), 118.3/232ep, loss = 3.40893
-I0511 01:29:44.676367  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61415 (* 1 = 3.61415 loss)
-I0511 01:29:44.676388  5307 sgd_solver.cpp:172] Iteration 61200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:30:44.929544  5307 solver.cpp:352] Iteration 61300 (1.65969 iter/s, 60.2523s/100 iter), 118.5/232ep, loss = 3.03333
-I0511 01:30:44.930357  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07757 (* 1 = 3.07757 loss)
-I0511 01:30:44.930377  5307 sgd_solver.cpp:172] Iteration 61300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:31:45.904727  5307 solver.cpp:352] Iteration 61400 (1.64004 iter/s, 60.9742s/100 iter), 118.7/232ep, loss = 3.19597
-I0511 01:31:45.905048  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73004 (* 1 = 2.73004 loss)
-I0511 01:31:45.905057  5307 sgd_solver.cpp:172] Iteration 61400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:32:46.642874  5307 solver.cpp:352] Iteration 61500 (1.64644 iter/s, 60.7371s/100 iter), 118.9/232ep, loss = 3.19309
-I0511 01:32:46.642956  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14063 (* 1 = 3.14063 loss)
-I0511 01:32:46.642966  5307 sgd_solver.cpp:172] Iteration 61500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:33:05.857440  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:33:47.518443  5307 solver.cpp:352] Iteration 61600 (1.64272 iter/s, 60.8745s/100 iter), 119.1/232ep, loss = 3.33877
-I0511 01:33:47.518563  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71762 (* 1 = 3.71762 loss)
-I0511 01:33:47.518584  5307 sgd_solver.cpp:172] Iteration 61600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:34:47.873309  5307 solver.cpp:352] Iteration 61700 (1.6569 iter/s, 60.3538s/100 iter), 119.3/232ep, loss = 3.27758
-I0511 01:34:47.873818  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90094 (* 1 = 2.90094 loss)
-I0511 01:34:47.873839  5307 sgd_solver.cpp:172] Iteration 61700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:35:48.313613  5307 solver.cpp:352] Iteration 61800 (1.65455 iter/s, 60.4393s/100 iter), 119.5/232ep, loss = 3.40443
-I0511 01:35:48.313936  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3341 (* 1 = 3.3341 loss)
-I0511 01:35:48.313948  5307 sgd_solver.cpp:172] Iteration 61800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:36:49.063982  5307 solver.cpp:352] Iteration 61900 (1.64611 iter/s, 60.7493s/100 iter), 119.7/232ep, loss = 3.16417
-I0511 01:36:49.064105  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.94675 (* 1 = 3.94675 loss)
-I0511 01:36:49.064129  5307 sgd_solver.cpp:172] Iteration 61900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:37:49.609964  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_62000.caffemodel
-I0511 01:37:49.629725  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_62000.solverstate
-I0511 01:37:49.637205  5307 solver.cpp:635] Iteration 62000, Testing net (#0)
-I0511 01:38:30.271909  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:38:30.498445  5307 solver.cpp:747] class AP 1: 0.638976
-I0511 01:38:30.498889  5307 solver.cpp:747] class AP 2: 0.696391
-I0511 01:38:30.506206  5307 solver.cpp:747] class AP 3: 0.530722
-I0511 01:38:30.509886  5307 solver.cpp:747] class AP 4: 0.474306
-I0511 01:38:30.532281  5307 solver.cpp:747] class AP 5: 0.325235
-I0511 01:38:30.532739  5307 solver.cpp:747] class AP 6: 0.705911
-I0511 01:38:30.541038  5307 solver.cpp:747] class AP 7: 0.682504
-I0511 01:38:30.541545  5307 solver.cpp:747] class AP 8: 0.784299
-I0511 01:38:30.562366  5307 solver.cpp:747] class AP 9: 0.406171
-I0511 01:38:30.563141  5307 solver.cpp:747] class AP 10: 0.579289
-I0511 01:38:30.563907  5307 solver.cpp:747] class AP 11: 0.579477
-I0511 01:38:30.564935  5307 solver.cpp:747] class AP 12: 0.707274
-I0511 01:38:30.565356  5307 solver.cpp:747] class AP 13: 0.781847
-I0511 01:38:30.565732  5307 solver.cpp:747] class AP 14: 0.725835
-I0511 01:38:30.624557  5307 solver.cpp:747] class AP 15: 0.717883
-I0511 01:38:30.633199  5307 solver.cpp:747] class AP 16: 0.318442
-I0511 01:38:30.637576  5307 solver.cpp:747] class AP 17: 0.577362
-I0511 01:38:30.638466  5307 solver.cpp:747] class AP 18: 0.617153
-I0511 01:38:30.639308  5307 solver.cpp:747] class AP 19: 0.734592
-I0511 01:38:30.641549  5307 solver.cpp:747] class AP 20: 0.582975
-I0511 01:38:30.641572  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.608332
-I0511 01:38:30.641708  5307 solver.cpp:283] Tests completed in 101.576s
-I0511 01:38:31.202342  5307 solver.cpp:352] Iteration 62000 (0.984484 iter/s, 101.576s/100 iter), 119.9/232ep, loss = 3.18528
-I0511 01:38:31.202376  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26906 (* 1 = 3.26906 loss)
-I0511 01:38:31.202385  5307 sgd_solver.cpp:172] Iteration 62000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:39:00.942828  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:39:32.470726  5307 solver.cpp:352] Iteration 62100 (1.63219 iter/s, 61.2673s/100 iter), 120.1/232ep, loss = 3.32069
-I0511 01:39:32.470837  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25149 (* 1 = 3.25149 loss)
-I0511 01:39:32.470847  5307 sgd_solver.cpp:172] Iteration 62100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:40:32.866340  5307 solver.cpp:352] Iteration 62200 (1.65578 iter/s, 60.3946s/100 iter), 120.3/232ep, loss = 3.24012
-I0511 01:40:32.871697  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33285 (* 1 = 3.33285 loss)
-I0511 01:40:32.871791  5307 sgd_solver.cpp:172] Iteration 62200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:41:33.514859  5307 solver.cpp:352] Iteration 62300 (1.64887 iter/s, 60.6474s/100 iter), 120.5/232ep, loss = 3.14737
-I0511 01:41:33.517706  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.01378 (* 1 = 2.01378 loss)
-I0511 01:41:33.517721  5307 sgd_solver.cpp:172] Iteration 62300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:42:34.198036  5307 solver.cpp:352] Iteration 62400 (1.64793 iter/s, 60.6822s/100 iter), 120.6/232ep, loss = 3.04684
-I0511 01:42:34.198324  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95164 (* 1 = 2.95164 loss)
-I0511 01:42:34.198341  5307 sgd_solver.cpp:172] Iteration 62400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:43:35.042399  5307 solver.cpp:352] Iteration 62500 (1.64357 iter/s, 60.8433s/100 iter), 120.8/232ep, loss = 3.38942
-I0511 01:43:35.042520  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01356 (* 1 = 3.01356 loss)
-I0511 01:43:35.042529  5307 sgd_solver.cpp:172] Iteration 62500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:44:15.422554  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:44:36.124577  5307 solver.cpp:352] Iteration 62600 (1.63717 iter/s, 61.0811s/100 iter), 121/232ep, loss = 3.2401
-I0511 01:44:36.124794  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.23748 (* 1 = 3.23748 loss)
-I0511 01:44:36.124814  5307 sgd_solver.cpp:172] Iteration 62600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:45:36.969264  5307 solver.cpp:352] Iteration 62700 (1.64356 iter/s, 60.8437s/100 iter), 121.2/232ep, loss = 3.49287
-I0511 01:45:36.969357  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.75813 (* 1 = 3.75813 loss)
-I0511 01:45:36.969365  5307 sgd_solver.cpp:172] Iteration 62700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:46:37.442836  5307 solver.cpp:352] Iteration 62800 (1.65364 iter/s, 60.4725s/100 iter), 121.4/232ep, loss = 3.21464
-I0511 01:46:37.442962  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30845 (* 1 = 3.30845 loss)
-I0511 01:46:37.442970  5307 sgd_solver.cpp:172] Iteration 62800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:47:38.004196  5307 solver.cpp:352] Iteration 62900 (1.65125 iter/s, 60.5603s/100 iter), 121.6/232ep, loss = 3.15143
-I0511 01:47:38.004312  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25155 (* 1 = 3.25155 loss)
-I0511 01:47:38.004331  5307 sgd_solver.cpp:172] Iteration 62900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:48:38.915096  5307 solver.cpp:352] Iteration 63000 (1.64177 iter/s, 60.9099s/100 iter), 121.8/232ep, loss = 3.1154
-I0511 01:48:38.915282  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55979 (* 1 = 3.55979 loss)
-I0511 01:48:38.915294  5307 sgd_solver.cpp:172] Iteration 63000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:49:29.128574  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:49:39.204468  5307 solver.cpp:352] Iteration 63100 (1.65869 iter/s, 60.2884s/100 iter), 122/232ep, loss = 3.10442
-I0511 01:49:39.204491  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14016 (* 1 = 3.14016 loss)
-I0511 01:49:39.204499  5307 sgd_solver.cpp:172] Iteration 63100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:50:38.492687  5307 solver.cpp:352] Iteration 63200 (1.68671 iter/s, 59.2872s/100 iter), 122.2/232ep, loss = 3.15629
-I0511 01:50:38.492832  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.25644 (* 1 = 4.25644 loss)
-I0511 01:50:38.492857  5307 sgd_solver.cpp:172] Iteration 63200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:51:39.091516  5307 solver.cpp:352] Iteration 63300 (1.65022 iter/s, 60.5978s/100 iter), 122.4/232ep, loss = 3.01801
-I0511 01:51:39.091578  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67144 (* 1 = 3.67144 loss)
-I0511 01:51:39.091585  5307 sgd_solver.cpp:172] Iteration 63300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:52:39.720751  5307 solver.cpp:352] Iteration 63400 (1.6494 iter/s, 60.6282s/100 iter), 122.6/232ep, loss = 3.26002
-I0511 01:52:39.721735  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84441 (* 1 = 3.84441 loss)
-I0511 01:52:39.721746  5307 sgd_solver.cpp:172] Iteration 63400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:53:39.748903  5307 solver.cpp:352] Iteration 63500 (1.66591 iter/s, 60.0271s/100 iter), 122.8/232ep, loss = 3.11425
-I0511 01:53:39.749964  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13076 (* 1 = 3.13076 loss)
-I0511 01:53:39.749975  5307 sgd_solver.cpp:172] Iteration 63500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:54:39.551507  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:54:40.126468  5307 solver.cpp:352] Iteration 63600 (1.65627 iter/s, 60.3766s/100 iter), 123/232ep, loss = 3.36435
-I0511 01:54:40.126544  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82291 (* 1 = 3.82291 loss)
-I0511 01:54:40.126564  5307 sgd_solver.cpp:172] Iteration 63600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:55:41.248622  5307 solver.cpp:352] Iteration 63700 (1.6361 iter/s, 61.1211s/100 iter), 123.2/232ep, loss = 3.28457
-I0511 01:55:41.250053  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.92716 (* 1 = 3.92716 loss)
-I0511 01:55:41.250136  5307 sgd_solver.cpp:172] Iteration 63700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:56:41.808493  5307 solver.cpp:352] Iteration 63800 (1.65129 iter/s, 60.5588s/100 iter), 123.4/232ep, loss = 3.16873
-I0511 01:56:41.808573  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16457 (* 1 = 3.16457 loss)
-I0511 01:56:41.808583  5307 sgd_solver.cpp:172] Iteration 63800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:57:41.697094  5307 solver.cpp:352] Iteration 63900 (1.6698 iter/s, 59.8876s/100 iter), 123.5/232ep, loss = 3.09208
-I0511 01:57:41.697197  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.56341 (* 1 = 2.56341 loss)
-I0511 01:57:41.697211  5307 sgd_solver.cpp:172] Iteration 63900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:58:41.914530  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_64000.caffemodel
-I0511 01:58:41.936115  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_64000.solverstate
-I0511 01:58:41.942518  5307 solver.cpp:635] Iteration 64000, Testing net (#0)
-I0511 01:58:54.503506  5352 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0511 01:59:22.812211  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:59:23.034703  5307 solver.cpp:747] class AP 1: 0.633344
-I0511 01:59:23.035193  5307 solver.cpp:747] class AP 2: 0.71913
-I0511 01:59:23.041399  5307 solver.cpp:747] class AP 3: 0.523038
-I0511 01:59:23.044920  5307 solver.cpp:747] class AP 4: 0.487088
-I0511 01:59:23.065953  5307 solver.cpp:747] class AP 5: 0.323399
-I0511 01:59:23.066340  5307 solver.cpp:747] class AP 6: 0.712963
-I0511 01:59:23.073334  5307 solver.cpp:747] class AP 7: 0.678412
-I0511 01:59:23.073962  5307 solver.cpp:747] class AP 8: 0.791006
-I0511 01:59:23.093544  5307 solver.cpp:747] class AP 9: 0.418986
-I0511 01:59:23.094259  5307 solver.cpp:747] class AP 10: 0.613647
-I0511 01:59:23.094915  5307 solver.cpp:747] class AP 11: 0.564244
-I0511 01:59:23.095716  5307 solver.cpp:747] class AP 12: 0.6965
-I0511 01:59:23.096119  5307 solver.cpp:747] class AP 13: 0.777461
-I0511 01:59:23.096477  5307 solver.cpp:747] class AP 14: 0.733747
-I0511 01:59:23.148425  5307 solver.cpp:747] class AP 15: 0.713203
-I0511 01:59:23.154863  5307 solver.cpp:747] class AP 16: 0.343052
-I0511 01:59:23.157761  5307 solver.cpp:747] class AP 17: 0.584989
-I0511 01:59:23.158402  5307 solver.cpp:747] class AP 18: 0.589125
-I0511 01:59:23.158951  5307 solver.cpp:747] class AP 19: 0.73742
-I0511 01:59:23.160584  5307 solver.cpp:747] class AP 20: 0.592467
-I0511 01:59:23.160596  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.611661
-I0511 01:59:23.160784  5307 solver.cpp:283] Tests completed in 101.462s
-I0511 01:59:23.710171  5307 solver.cpp:352] Iteration 64000 (0.985591 iter/s, 101.462s/100 iter), 123.7/232ep, loss = 3.07692
-I0511 01:59:23.710196  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87853 (* 1 = 2.87853 loss)
-I0511 01:59:23.710201  5307 sgd_solver.cpp:172] Iteration 64000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:00:23.587422  5307 solver.cpp:352] Iteration 64100 (1.67011 iter/s, 59.8762s/100 iter), 123.9/232ep, loss = 3.19645
-I0511 02:00:23.587507  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44664 (* 1 = 3.44664 loss)
-I0511 02:00:23.587524  5307 sgd_solver.cpp:172] Iteration 64100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:00:34.106542  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:01:23.968485  5307 solver.cpp:352] Iteration 64200 (1.65618 iter/s, 60.38s/100 iter), 124.1/232ep, loss = 3.05154
-I0511 02:01:23.968683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59048 (* 1 = 3.59048 loss)
-I0511 02:01:23.968695  5307 sgd_solver.cpp:172] Iteration 64200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:02:24.219705  5307 solver.cpp:352] Iteration 64300 (1.65975 iter/s, 60.2502s/100 iter), 124.3/232ep, loss = 3.12734
-I0511 02:02:24.219782  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08787 (* 1 = 3.08787 loss)
-I0511 02:02:24.219791  5307 sgd_solver.cpp:172] Iteration 64300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:03:24.846391  5307 solver.cpp:352] Iteration 64400 (1.64947 iter/s, 60.6257s/100 iter), 124.5/232ep, loss = 3.0666
-I0511 02:03:24.846494  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15372 (* 1 = 3.15372 loss)
-I0511 02:03:24.846513  5307 sgd_solver.cpp:172] Iteration 64400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:04:25.418087  5307 solver.cpp:352] Iteration 64500 (1.65096 iter/s, 60.5707s/100 iter), 124.7/232ep, loss = 3.25712
-I0511 02:04:25.418170  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20735 (* 1 = 3.20735 loss)
-I0511 02:04:25.418179  5307 sgd_solver.cpp:172] Iteration 64500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:05:25.953708  5307 solver.cpp:352] Iteration 64600 (1.65195 iter/s, 60.5346s/100 iter), 124.9/232ep, loss = 3.072
-I0511 02:05:25.953817  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88575 (* 1 = 2.88575 loss)
-I0511 02:05:25.953832  5307 sgd_solver.cpp:172] Iteration 64600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:05:46.779067  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:06:26.804708  5307 solver.cpp:352] Iteration 64700 (1.64339 iter/s, 60.85s/100 iter), 125.1/232ep, loss = 3.16899
-I0511 02:06:26.805696  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.78591 (* 1 = 2.78591 loss)
-I0511 02:06:26.805712  5307 sgd_solver.cpp:172] Iteration 64700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:07:27.332586  5307 solver.cpp:352] Iteration 64800 (1.65216 iter/s, 60.5269s/100 iter), 125.3/232ep, loss = 3.11116
-I0511 02:07:27.332701  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53597 (* 1 = 3.53597 loss)
-I0511 02:07:27.332718  5307 sgd_solver.cpp:172] Iteration 64800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:08:27.384068  5307 solver.cpp:352] Iteration 64900 (1.66527 iter/s, 60.0505s/100 iter), 125.5/232ep, loss = 3.25568
-I0511 02:08:27.384121  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64235 (* 1 = 3.64235 loss)
-I0511 02:08:27.384130  5307 sgd_solver.cpp:172] Iteration 64900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:09:32.242856  5307 solver.cpp:352] Iteration 65000 (1.54184 iter/s, 64.8577s/100 iter), 125.7/232ep, loss = 3.19532
-I0511 02:09:32.245679  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05203 (* 1 = 3.05203 loss)
-I0511 02:09:32.245710  5307 sgd_solver.cpp:172] Iteration 65000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:10:40.086432  5307 solver.cpp:352] Iteration 65100 (1.474 iter/s, 67.8424s/100 iter), 125.9/232ep, loss = 3.23919
-I0511 02:10:40.086539  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31138 (* 1 = 3.31138 loss)
-I0511 02:10:40.086555  5307 sgd_solver.cpp:172] Iteration 65100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:11:11.076592  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:11:40.491904  5307 solver.cpp:352] Iteration 65200 (1.65551 iter/s, 60.4044s/100 iter), 126.1/232ep, loss = 3.29238
-I0511 02:11:40.491936  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03786 (* 1 = 3.03786 loss)
-I0511 02:11:40.491945  5307 sgd_solver.cpp:172] Iteration 65200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:12:41.340348  5307 solver.cpp:352] Iteration 65300 (1.64346 iter/s, 60.8474s/100 iter), 126.3/232ep, loss = 3.20961
-I0511 02:12:41.340802  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.39202 (* 1 = 4.39202 loss)
-I0511 02:12:41.340811  5307 sgd_solver.cpp:172] Iteration 65300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:13:40.918337  5307 solver.cpp:352] Iteration 65400 (1.6785 iter/s, 59.577s/100 iter), 126.4/232ep, loss = 3.12944
-I0511 02:13:40.918462  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88578 (* 1 = 2.88578 loss)
-I0511 02:13:40.918475  5307 sgd_solver.cpp:172] Iteration 65400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:14:41.663523  5307 solver.cpp:352] Iteration 65500 (1.64625 iter/s, 60.7442s/100 iter), 126.6/232ep, loss = 3.17585
-I0511 02:14:41.663591  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27108 (* 1 = 3.27108 loss)
-I0511 02:14:41.663600  5307 sgd_solver.cpp:172] Iteration 65500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:15:41.835770  5307 solver.cpp:352] Iteration 65600 (1.66192 iter/s, 60.1712s/100 iter), 126.8/232ep, loss = 3.22622
-I0511 02:15:41.835837  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64396 (* 1 = 3.64396 loss)
-I0511 02:15:41.835847  5307 sgd_solver.cpp:172] Iteration 65600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:16:23.883992  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:16:42.569505  5307 solver.cpp:352] Iteration 65700 (1.64656 iter/s, 60.7327s/100 iter), 127/232ep, loss = 3.21759
-I0511 02:16:42.569663  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.02444 (* 1 = 3.02444 loss)
-I0511 02:16:42.569728  5307 sgd_solver.cpp:172] Iteration 65700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:17:44.531523  5307 solver.cpp:352] Iteration 65800 (1.61392 iter/s, 61.961s/100 iter), 127.2/232ep, loss = 3.1564
-I0511 02:17:44.531584  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46917 (* 1 = 3.46917 loss)
-I0511 02:17:44.531592  5307 sgd_solver.cpp:172] Iteration 65800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:18:45.268631  5307 solver.cpp:352] Iteration 65900 (1.64647 iter/s, 60.7361s/100 iter), 127.4/232ep, loss = 3.09757
-I0511 02:18:45.268702  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.98101 (* 1 = 2.98101 loss)
-I0511 02:18:45.268712  5307 sgd_solver.cpp:172] Iteration 65900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:19:45.910188  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_66000.caffemodel
-I0511 02:19:45.926357  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_66000.solverstate
-I0511 02:19:45.931254  5307 solver.cpp:635] Iteration 66000, Testing net (#0)
-I0511 02:20:26.794226  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:20:27.040277  5307 solver.cpp:747] class AP 1: 0.64229
-I0511 02:20:27.040701  5307 solver.cpp:747] class AP 2: 0.706363
-I0511 02:20:27.047019  5307 solver.cpp:747] class AP 3: 0.531507
-I0511 02:20:27.050629  5307 solver.cpp:747] class AP 4: 0.49355
-I0511 02:20:27.070884  5307 solver.cpp:747] class AP 5: 0.323647
-I0511 02:20:27.071313  5307 solver.cpp:747] class AP 6: 0.704733
-I0511 02:20:27.079596  5307 solver.cpp:747] class AP 7: 0.697777
-I0511 02:20:27.080271  5307 solver.cpp:747] class AP 8: 0.798769
-I0511 02:20:27.099870  5307 solver.cpp:747] class AP 9: 0.412927
-I0511 02:20:27.100630  5307 solver.cpp:747] class AP 10: 0.632788
-I0511 02:20:27.101251  5307 solver.cpp:747] class AP 11: 0.571624
-I0511 02:20:27.102129  5307 solver.cpp:747] class AP 12: 0.718176
-I0511 02:20:27.102501  5307 solver.cpp:747] class AP 13: 0.786534
-I0511 02:20:27.102790  5307 solver.cpp:747] class AP 14: 0.73184
-I0511 02:20:27.153549  5307 solver.cpp:747] class AP 15: 0.714214
-I0511 02:20:27.160442  5307 solver.cpp:747] class AP 16: 0.342798
-I0511 02:20:27.163242  5307 solver.cpp:747] class AP 17: 0.582979
-I0511 02:20:27.163986  5307 solver.cpp:747] class AP 18: 0.620496
-I0511 02:20:27.164631  5307 solver.cpp:747] class AP 19: 0.743935
-I0511 02:20:27.166348  5307 solver.cpp:747] class AP 20: 0.586294
-I0511 02:20:27.166357  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.617162
-I0511 02:20:27.166574  5307 solver.cpp:283] Tests completed in 101.896s
-I0511 02:20:27.747750  5307 solver.cpp:352] Iteration 66000 (0.981391 iter/s, 101.896s/100 iter), 127.6/232ep, loss = 3.06323
-I0511 02:20:27.747782  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37556 (* 1 = 3.37556 loss)
-I0511 02:20:27.747792  5307 sgd_solver.cpp:172] Iteration 66000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:21:28.306773  5307 solver.cpp:352] Iteration 66100 (1.65131 iter/s, 60.558s/100 iter), 127.8/232ep, loss = 3.12489
-I0511 02:21:28.306880  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96524 (* 1 = 2.96524 loss)
-I0511 02:21:28.306896  5307 sgd_solver.cpp:172] Iteration 66100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:22:19.897558  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:22:28.833058  5307 solver.cpp:352] Iteration 66200 (1.6522 iter/s, 60.5252s/100 iter), 128/232ep, loss = 3.16999
-I0511 02:22:28.833091  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08489 (* 1 = 3.08489 loss)
-I0511 02:22:28.833099  5307 sgd_solver.cpp:172] Iteration 66200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:23:28.684754  5307 solver.cpp:352] Iteration 66300 (1.67083 iter/s, 59.8507s/100 iter), 128.2/232ep, loss = 3.05533
-I0511 02:23:28.684828  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32332 (* 1 = 3.32332 loss)
-I0511 02:23:28.684836  5307 sgd_solver.cpp:172] Iteration 66300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:24:29.196430  5307 solver.cpp:352] Iteration 66400 (1.6526 iter/s, 60.5106s/100 iter), 128.4/232ep, loss = 3.15909
-I0511 02:24:29.196501  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.45537 (* 1 = 2.45537 loss)
-I0511 02:24:29.196511  5307 sgd_solver.cpp:172] Iteration 66400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:25:29.284615  5307 solver.cpp:352] Iteration 66500 (1.66425 iter/s, 60.0871s/100 iter), 128.6/232ep, loss = 3.17891
-I0511 02:25:29.284759  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.80693 (* 1 = 2.80693 loss)
-I0511 02:25:29.284773  5307 sgd_solver.cpp:172] Iteration 66500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:26:29.177669  5307 solver.cpp:352] Iteration 66600 (1.66967 iter/s, 59.8921s/100 iter), 128.8/232ep, loss = 3.04129
-I0511 02:26:29.177758  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84487 (* 1 = 3.84487 loss)
-I0511 02:26:29.177778  5307 sgd_solver.cpp:172] Iteration 66600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:27:29.551985  5307 solver.cpp:352] Iteration 66700 (1.65636 iter/s, 60.3733s/100 iter), 129/232ep, loss = 3.10101
-I0511 02:27:29.552503  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.98461 (* 1 = 2.98461 loss)
-I0511 02:27:29.552539  5307 sgd_solver.cpp:172] Iteration 66700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:27:31.497298  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:28:29.639467  5307 solver.cpp:352] Iteration 66800 (1.66427 iter/s, 60.0865s/100 iter), 129.2/232ep, loss = 3.27425
-I0511 02:28:29.639585  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99742 (* 1 = 2.99742 loss)
-I0511 02:28:29.639600  5307 sgd_solver.cpp:172] Iteration 66800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:29:30.188894  5307 solver.cpp:352] Iteration 66900 (1.65157 iter/s, 60.5484s/100 iter), 129.3/232ep, loss = 3.07127
-I0511 02:29:30.189085  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.49614 (* 1 = 2.49614 loss)
-I0511 02:29:30.189118  5307 sgd_solver.cpp:172] Iteration 66900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:30:30.186563  5307 solver.cpp:352] Iteration 67000 (1.66676 iter/s, 59.9967s/100 iter), 129.5/232ep, loss = 3.04688
-I0511 02:30:30.186645  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31019 (* 1 = 3.31019 loss)
-I0511 02:30:30.186655  5307 sgd_solver.cpp:172] Iteration 67000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:31:30.200628  5307 solver.cpp:352] Iteration 67100 (1.6663 iter/s, 60.013s/100 iter), 129.7/232ep, loss = 3.24378
-I0511 02:31:30.200717  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95658 (* 1 = 2.95658 loss)
-I0511 02:31:30.200726  5307 sgd_solver.cpp:172] Iteration 67100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:32:30.827069  5307 solver.cpp:352] Iteration 67200 (1.64947 iter/s, 60.6254s/100 iter), 129.9/232ep, loss = 3.10399
-I0511 02:32:30.827136  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56074 (* 1 = 3.56074 loss)
-I0511 02:32:30.827142  5307 sgd_solver.cpp:172] Iteration 67200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:32:43.731626  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:33:30.801796  5307 solver.cpp:352] Iteration 67300 (1.6674 iter/s, 59.9737s/100 iter), 130.1/232ep, loss = 3.18025
-I0511 02:33:30.801970  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09506 (* 1 = 3.09506 loss)
-I0511 02:33:30.801990  5307 sgd_solver.cpp:172] Iteration 67300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:34:31.469436  5307 solver.cpp:352] Iteration 67400 (1.64835 iter/s, 60.6666s/100 iter), 130.3/232ep, loss = 3.25361
-I0511 02:34:31.469583  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88847 (* 1 = 2.88847 loss)
-I0511 02:34:31.469594  5307 sgd_solver.cpp:172] Iteration 67400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:35:31.926903  5307 solver.cpp:352] Iteration 67500 (1.65408 iter/s, 60.4565s/100 iter), 130.5/232ep, loss = 3.20026
-I0511 02:35:31.927027  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.99033 (* 1 = 3.99033 loss)
-I0511 02:35:31.927047  5307 sgd_solver.cpp:172] Iteration 67500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:36:32.995633  5307 solver.cpp:352] Iteration 67600 (1.63753 iter/s, 61.0677s/100 iter), 130.7/232ep, loss = 3.14645
-I0511 02:36:33.001457  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.64913 (* 1 = 2.64913 loss)
-I0511 02:36:33.001477  5307 sgd_solver.cpp:172] Iteration 67600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:37:34.313900  5307 solver.cpp:352] Iteration 67700 (1.63086 iter/s, 61.3172s/100 iter), 130.9/232ep, loss = 3.0593
-I0511 02:37:34.314021  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51218 (* 1 = 2.51218 loss)
-I0511 02:37:34.314043  5307 sgd_solver.cpp:172] Iteration 67700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:37:56.572094  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:38:34.731317  5307 solver.cpp:352] Iteration 67800 (1.65518 iter/s, 60.4164s/100 iter), 131.1/232ep, loss = 3.07228
-I0511 02:38:34.731390  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85683 (* 1 = 3.85683 loss)
-I0511 02:38:34.731400  5307 sgd_solver.cpp:172] Iteration 67800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:39:35.165295  5307 solver.cpp:352] Iteration 67900 (1.65473 iter/s, 60.4329s/100 iter), 131.3/232ep, loss = 3.21763
-I0511 02:39:35.168763  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.18548 (* 1 = 4.18548 loss)
-I0511 02:39:35.168782  5307 sgd_solver.cpp:172] Iteration 67900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:40:35.312610  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_68000.caffemodel
-I0511 02:40:35.335475  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_68000.solverstate
-I0511 02:40:35.341565  5307 solver.cpp:635] Iteration 68000, Testing net (#0)
-I0511 02:41:15.746647  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:41:15.956759  5307 solver.cpp:747] class AP 1: 0.659079
-I0511 02:41:15.957516  5307 solver.cpp:747] class AP 2: 0.732531
-I0511 02:41:15.964699  5307 solver.cpp:747] class AP 3: 0.534657
-I0511 02:41:15.968891  5307 solver.cpp:747] class AP 4: 0.510083
-I0511 02:41:15.988533  5307 solver.cpp:747] class AP 5: 0.312808
-I0511 02:41:15.988878  5307 solver.cpp:747] class AP 6: 0.711184
-I0511 02:41:15.996846  5307 solver.cpp:747] class AP 7: 0.695885
-I0511 02:41:15.997467  5307 solver.cpp:747] class AP 8: 0.791351
-I0511 02:41:16.014248  5307 solver.cpp:747] class AP 9: 0.415975
-I0511 02:41:16.014916  5307 solver.cpp:747] class AP 10: 0.608569
-I0511 02:41:16.015545  5307 solver.cpp:747] class AP 11: 0.562536
-I0511 02:41:16.016479  5307 solver.cpp:747] class AP 12: 0.72295
-I0511 02:41:16.016935  5307 solver.cpp:747] class AP 13: 0.788439
-I0511 02:41:16.017293  5307 solver.cpp:747] class AP 14: 0.726442
-I0511 02:41:16.068330  5307 solver.cpp:747] class AP 15: 0.720163
-I0511 02:41:16.074450  5307 solver.cpp:747] class AP 16: 0.357333
-I0511 02:41:16.076555  5307 solver.cpp:747] class AP 17: 0.573487
-I0511 02:41:16.077015  5307 solver.cpp:747] class AP 18: 0.621755
-I0511 02:41:16.077679  5307 solver.cpp:747] class AP 19: 0.750308
-I0511 02:41:16.078996  5307 solver.cpp:747] class AP 20: 0.58943
-I0511 02:41:16.079004  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.619248
-I0511 02:41:16.079181  5307 solver.cpp:283] Tests completed in 100.912s
-I0511 02:41:16.621726  5307 solver.cpp:352] Iteration 68000 (0.990961 iter/s, 100.912s/100 iter), 131.5/232ep, loss = 3.21332
-I0511 02:41:16.621757  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.426 (* 1 = 2.426 loss)
-I0511 02:41:16.621765  5307 sgd_solver.cpp:172] Iteration 68000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:42:17.548768  5307 solver.cpp:352] Iteration 68100 (1.64134 iter/s, 60.926s/100 iter), 131.7/232ep, loss = 3.23785
-I0511 02:42:17.548938  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05499 (* 1 = 3.05499 loss)
-I0511 02:42:17.548955  5307 sgd_solver.cpp:172] Iteration 68100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:43:18.543166  5307 solver.cpp:352] Iteration 68200 (1.63952 iter/s, 60.9933s/100 iter), 131.9/232ep, loss = 3.18542
-I0511 02:43:18.543371  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21433 (* 1 = 3.21433 loss)
-I0511 02:43:18.543467  5307 sgd_solver.cpp:172] Iteration 68200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:43:52.088322  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:44:19.328593  5307 solver.cpp:352] Iteration 68300 (1.64516 iter/s, 60.7844s/100 iter), 132.1/232ep, loss = 3.15519
-I0511 02:44:19.328624  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33395 (* 1 = 3.33395 loss)
-I0511 02:44:19.328634  5307 sgd_solver.cpp:172] Iteration 68300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:45:19.909802  5307 solver.cpp:352] Iteration 68400 (1.6507 iter/s, 60.5802s/100 iter), 132.2/232ep, loss = 3.1727
-I0511 02:45:19.909880  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32494 (* 1 = 3.32494 loss)
-I0511 02:45:19.909890  5307 sgd_solver.cpp:172] Iteration 68400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:46:21.203446  5307 solver.cpp:352] Iteration 68500 (1.63152 iter/s, 61.2926s/100 iter), 132.4/232ep, loss = 3.02053
-I0511 02:46:21.203536  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99906 (* 1 = 2.99906 loss)
-I0511 02:46:21.203547  5307 sgd_solver.cpp:172] Iteration 68500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:47:22.625470  5307 solver.cpp:352] Iteration 68600 (1.62811 iter/s, 61.421s/100 iter), 132.6/232ep, loss = 3.19481
-I0511 02:47:22.625568  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63442 (* 1 = 2.63442 loss)
-I0511 02:47:22.625591  5307 sgd_solver.cpp:172] Iteration 68600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:48:22.788887  5307 solver.cpp:352] Iteration 68700 (1.66217 iter/s, 60.1624s/100 iter), 132.8/232ep, loss = 3.31883
-I0511 02:48:22.788957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53685 (* 1 = 3.53685 loss)
-I0511 02:48:22.788977  5307 sgd_solver.cpp:172] Iteration 68700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:49:07.016917  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:49:23.496430  5307 solver.cpp:352] Iteration 68800 (1.64727 iter/s, 60.7065s/100 iter), 133/232ep, loss = 3.31059
-I0511 02:49:23.496461  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.60516 (* 1 = 4.60516 loss)
-I0511 02:49:23.496469  5307 sgd_solver.cpp:172] Iteration 68800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:50:23.810361  5307 solver.cpp:352] Iteration 68900 (1.65802 iter/s, 60.3129s/100 iter), 133.2/232ep, loss = 3.13913
-I0511 02:50:23.810559  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73763 (* 1 = 3.73763 loss)
-I0511 02:50:23.810570  5307 sgd_solver.cpp:172] Iteration 68900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:51:24.725180  5307 solver.cpp:352] Iteration 69000 (1.64167 iter/s, 60.9138s/100 iter), 133.4/232ep, loss = 3.34018
-I0511 02:51:24.725426  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06818 (* 1 = 4.06818 loss)
-I0511 02:51:24.725502  5307 sgd_solver.cpp:172] Iteration 69000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:52:25.565292  5307 solver.cpp:352] Iteration 69100 (1.64368 iter/s, 60.8391s/100 iter), 133.6/232ep, loss = 2.98946
-I0511 02:52:25.565399  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90528 (* 1 = 2.90528 loss)
-I0511 02:52:25.565416  5307 sgd_solver.cpp:172] Iteration 69100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:53:26.489583  5307 solver.cpp:352] Iteration 69200 (1.64141 iter/s, 60.9233s/100 iter), 133.8/232ep, loss = 3.04981
-I0511 02:53:26.489715  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.82091 (* 1 = 2.82091 loss)
-I0511 02:53:26.489738  5307 sgd_solver.cpp:172] Iteration 69200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:54:20.484907  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:54:26.980163  5307 solver.cpp:352] Iteration 69300 (1.65318 iter/s, 60.4896s/100 iter), 134/232ep, loss = 3.16001
-I0511 02:54:26.980187  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88092 (* 1 = 2.88092 loss)
-I0511 02:54:26.980195  5307 sgd_solver.cpp:172] Iteration 69300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:55:28.371501  5307 solver.cpp:352] Iteration 69400 (1.62892 iter/s, 61.3903s/100 iter), 134.2/232ep, loss = 3.13472
-I0511 02:55:28.372318  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85003 (* 1 = 2.85003 loss)
-I0511 02:55:28.372362  5307 sgd_solver.cpp:172] Iteration 69400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:56:28.697196  5307 solver.cpp:352] Iteration 69500 (1.6577 iter/s, 60.3247s/100 iter), 134.4/232ep, loss = 3.218
-I0511 02:56:28.697268  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.90315 (* 1 = 3.90315 loss)
-I0511 02:56:28.697279  5307 sgd_solver.cpp:172] Iteration 69500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:57:29.238632  5307 solver.cpp:352] Iteration 69600 (1.65179 iter/s, 60.5404s/100 iter), 134.6/232ep, loss = 3.18379
-I0511 02:57:29.238732  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.60102 (* 1 = 4.60102 loss)
-I0511 02:57:29.238746  5307 sgd_solver.cpp:172] Iteration 69600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:58:29.184934  5307 solver.cpp:352] Iteration 69700 (1.66819 iter/s, 59.9453s/100 iter), 134.8/232ep, loss = 3.2003
-I0511 02:58:29.185029  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8632 (* 1 = 2.8632 loss)
-I0511 02:58:29.185047  5307 sgd_solver.cpp:172] Iteration 69700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:59:30.345985  5307 solver.cpp:352] Iteration 69800 (1.63506 iter/s, 61.16s/100 iter), 135/232ep, loss = 3.04563
-I0511 02:59:30.347682  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74515 (* 1 = 2.74515 loss)
-I0511 02:59:30.347692  5307 sgd_solver.cpp:172] Iteration 69800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:59:34.952587  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:00:31.122530  5307 solver.cpp:352] Iteration 69900 (1.6454 iter/s, 60.7755s/100 iter), 135.1/232ep, loss = 2.95089
-I0511 03:00:31.124117  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21105 (* 1 = 3.21105 loss)
-I0511 03:00:31.124151  5307 sgd_solver.cpp:172] Iteration 69900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:01:31.175557  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_70000.caffemodel
-I0511 03:01:31.191851  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_70000.solverstate
-I0511 03:01:31.197576  5307 solver.cpp:635] Iteration 70000, Testing net (#0)
-I0511 03:02:11.462358  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:02:11.687438  5307 solver.cpp:747] class AP 1: 0.633928
-I0511 03:02:11.688009  5307 solver.cpp:747] class AP 2: 0.722257
-I0511 03:02:11.696943  5307 solver.cpp:747] class AP 3: 0.52554
-I0511 03:02:11.702378  5307 solver.cpp:747] class AP 4: 0.506187
-I0511 03:02:11.728567  5307 solver.cpp:747] class AP 5: 0.317221
-I0511 03:02:11.729123  5307 solver.cpp:747] class AP 6: 0.700389
-I0511 03:02:11.741091  5307 solver.cpp:747] class AP 7: 0.690578
-I0511 03:02:11.742168  5307 solver.cpp:747] class AP 8: 0.793709
-I0511 03:02:11.760407  5307 solver.cpp:747] class AP 9: 0.412928
-I0511 03:02:11.761131  5307 solver.cpp:747] class AP 10: 0.626752
-I0511 03:02:11.761754  5307 solver.cpp:747] class AP 11: 0.569649
-I0511 03:02:11.762750  5307 solver.cpp:747] class AP 12: 0.728977
-I0511 03:02:11.763142  5307 solver.cpp:747] class AP 13: 0.79404
-I0511 03:02:11.763547  5307 solver.cpp:747] class AP 14: 0.739371
-I0511 03:02:11.816392  5307 solver.cpp:747] class AP 15: 0.716036
-I0511 03:02:11.822613  5307 solver.cpp:747] class AP 16: 0.345662
-I0511 03:02:11.825171  5307 solver.cpp:747] class AP 17: 0.588648
-I0511 03:02:11.825748  5307 solver.cpp:747] class AP 18: 0.597739
-I0511 03:02:11.826503  5307 solver.cpp:747] class AP 19: 0.748818
-I0511 03:02:11.827986  5307 solver.cpp:747] class AP 20: 0.585734
-I0511 03:02:11.827993  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.617208
-I0511 03:02:11.828169  5307 solver.cpp:283] Tests completed in 100.704s
-I0511 03:02:12.381124  5307 solver.cpp:352] Iteration 70000 (0.99301 iter/s, 100.704s/100 iter), 135.3/232ep, loss = 3.35481
-I0511 03:02:12.381147  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59581 (* 1 = 3.59581 loss)
-I0511 03:02:12.381155  5307 sgd_solver.cpp:172] Iteration 70000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:03:12.412638  5307 solver.cpp:352] Iteration 70100 (1.66582 iter/s, 60.0305s/100 iter), 135.5/232ep, loss = 3.06649
-I0511 03:03:12.412716  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05734 (* 1 = 3.05734 loss)
-I0511 03:03:12.412726  5307 sgd_solver.cpp:172] Iteration 70100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:04:13.535756  5307 solver.cpp:352] Iteration 70200 (1.63607 iter/s, 61.1221s/100 iter), 135.7/232ep, loss = 3.11306
-I0511 03:04:13.535823  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.97389 (* 1 = 2.97389 loss)
-I0511 03:04:13.535832  5307 sgd_solver.cpp:172] Iteration 70200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:05:13.983336  5307 solver.cpp:352] Iteration 70300 (1.65435 iter/s, 60.4465s/100 iter), 135.9/232ep, loss = 3.06026
-I0511 03:05:13.983414  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.14835 (* 1 = 2.14835 loss)
-I0511 03:05:13.983424  5307 sgd_solver.cpp:172] Iteration 70300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:05:27.617794  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:06:14.169797  5307 solver.cpp:352] Iteration 70400 (1.66153 iter/s, 60.1854s/100 iter), 136.1/232ep, loss = 3.23885
-I0511 03:06:14.172082  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.23922 (* 1 = 3.23922 loss)
-I0511 03:06:14.172091  5307 sgd_solver.cpp:172] Iteration 70400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:07:14.290994  5307 solver.cpp:352] Iteration 70500 (1.66334 iter/s, 60.1202s/100 iter), 136.3/232ep, loss = 3.11523
-I0511 03:07:14.291625  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.43783 (* 1 = 2.43783 loss)
-I0511 03:07:14.291651  5307 sgd_solver.cpp:172] Iteration 70500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:08:15.169945  5307 solver.cpp:352] Iteration 70600 (1.64263 iter/s, 60.8779s/100 iter), 136.5/232ep, loss = 3.23688
-I0511 03:08:15.170079  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11832 (* 1 = 3.11832 loss)
-I0511 03:08:15.170087  5307 sgd_solver.cpp:172] Iteration 70600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:09:16.588992  5307 solver.cpp:352] Iteration 70700 (1.62819 iter/s, 61.418s/100 iter), 136.7/232ep, loss = 3.16966
-I0511 03:09:16.589047  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9083 (* 1 = 2.9083 loss)
-I0511 03:09:16.589054  5307 sgd_solver.cpp:172] Iteration 70700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:10:17.104252  5307 solver.cpp:352] Iteration 70800 (1.6525 iter/s, 60.5142s/100 iter), 136.9/232ep, loss = 2.9313
-I0511 03:10:17.104343  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13385 (* 1 = 3.13385 loss)
-I0511 03:10:17.104352  5307 sgd_solver.cpp:172] Iteration 70800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:10:42.343801  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:11:18.667933  5307 solver.cpp:352] Iteration 70900 (1.62436 iter/s, 61.5626s/100 iter), 137.1/232ep, loss = 3.02674
-I0511 03:11:18.668010  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.99819 (* 1 = 3.99819 loss)
-I0511 03:11:18.668016  5307 sgd_solver.cpp:172] Iteration 70900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:12:20.048511  5307 solver.cpp:352] Iteration 71000 (1.62921 iter/s, 61.3795s/100 iter), 137.3/232ep, loss = 3.13359
-I0511 03:12:20.051676  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.6327 (* 1 = 3.6327 loss)
-I0511 03:12:20.051697  5307 sgd_solver.cpp:172] Iteration 71000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:13:21.222898  5307 solver.cpp:352] Iteration 71100 (1.6347 iter/s, 61.1733s/100 iter), 137.5/232ep, loss = 3.08443
-I0511 03:13:21.225001  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2047 (* 1 = 3.2047 loss)
-I0511 03:13:21.225018  5307 sgd_solver.cpp:172] Iteration 71100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:14:21.752249  5307 solver.cpp:352] Iteration 71200 (1.65212 iter/s, 60.5283s/100 iter), 137.7/232ep, loss = 2.94043
-I0511 03:14:21.752353  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73582 (* 1 = 2.73582 loss)
-I0511 03:14:21.752368  5307 sgd_solver.cpp:172] Iteration 71200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:15:23.472234  5307 solver.cpp:352] Iteration 71300 (1.62025 iter/s, 61.7189s/100 iter), 137.9/232ep, loss = 3.25058
-I0511 03:15:23.476651  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54697 (* 1 = 3.54697 loss)
-I0511 03:15:23.476688  5307 sgd_solver.cpp:172] Iteration 71300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:15:59.221091  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:16:24.756625  5307 solver.cpp:352] Iteration 71400 (1.63176 iter/s, 61.2834s/100 iter), 138/232ep, loss = 3.00779
-I0511 03:16:24.756692  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.75285 (* 1 = 2.75285 loss)
-I0511 03:16:24.756788  5307 sgd_solver.cpp:172] Iteration 71400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:17:33.508616  5307 solver.cpp:352] Iteration 71500 (1.45453 iter/s, 68.7508s/100 iter), 138.2/232ep, loss = 3.13443
-I0511 03:17:33.508985  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40484 (* 1 = 3.40484 loss)
-I0511 03:17:33.508996  5307 sgd_solver.cpp:172] Iteration 71500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:18:36.579047  5307 solver.cpp:352] Iteration 71600 (1.58556 iter/s, 63.0693s/100 iter), 138.4/232ep, loss = 3.07886
-I0511 03:18:36.579121  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.34027 (* 1 = 3.34027 loss)
-I0511 03:18:36.579138  5307 sgd_solver.cpp:172] Iteration 71600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:19:37.170053  5307 solver.cpp:352] Iteration 71700 (1.65044 iter/s, 60.59s/100 iter), 138.6/232ep, loss = 3.27583
-I0511 03:19:37.170119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00287 (* 1 = 3.00287 loss)
-I0511 03:19:37.170125  5307 sgd_solver.cpp:172] Iteration 71700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:20:37.967916  5307 solver.cpp:352] Iteration 71800 (1.64482 iter/s, 60.7968s/100 iter), 138.8/232ep, loss = 3.22436
-I0511 03:20:37.967975  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.96683 (* 1 = 3.96683 loss)
-I0511 03:20:37.967983  5307 sgd_solver.cpp:172] Iteration 71800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:21:24.001253  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:21:39.559343  5307 solver.cpp:352] Iteration 71900 (1.62363 iter/s, 61.5904s/100 iter), 139/232ep, loss = 3.02662
-I0511 03:21:39.559372  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.47239 (* 1 = 2.47239 loss)
-I0511 03:21:39.559381  5307 sgd_solver.cpp:172] Iteration 71900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:22:39.245753  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_72000.caffemodel
-I0511 03:22:39.260543  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_72000.solverstate
-I0511 03:22:39.265848  5307 solver.cpp:635] Iteration 72000, Testing net (#0)
-I0511 03:23:19.926988  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:23:20.152026  5307 solver.cpp:747] class AP 1: 0.643178
-I0511 03:23:20.152619  5307 solver.cpp:747] class AP 2: 0.730592
-I0511 03:23:20.158911  5307 solver.cpp:747] class AP 3: 0.525441
-I0511 03:23:20.163348  5307 solver.cpp:747] class AP 4: 0.490848
-I0511 03:23:20.185232  5307 solver.cpp:747] class AP 5: 0.323959
-I0511 03:23:20.185839  5307 solver.cpp:747] class AP 6: 0.7124
-I0511 03:23:20.197413  5307 solver.cpp:747] class AP 7: 0.699418
-I0511 03:23:20.197970  5307 solver.cpp:747] class AP 8: 0.796918
-I0511 03:23:20.217874  5307 solver.cpp:747] class AP 9: 0.412358
-I0511 03:23:20.218621  5307 solver.cpp:747] class AP 10: 0.612703
-I0511 03:23:20.219408  5307 solver.cpp:747] class AP 11: 0.583159
-I0511 03:23:20.220283  5307 solver.cpp:747] class AP 12: 0.718245
-I0511 03:23:20.220710  5307 solver.cpp:747] class AP 13: 0.788613
-I0511 03:23:20.221154  5307 solver.cpp:747] class AP 14: 0.743379
-I0511 03:23:20.272939  5307 solver.cpp:747] class AP 15: 0.721877
-I0511 03:23:20.278545  5307 solver.cpp:747] class AP 16: 0.348866
-I0511 03:23:20.281221  5307 solver.cpp:747] class AP 17: 0.583127
-I0511 03:23:20.281805  5307 solver.cpp:747] class AP 18: 0.60061
-I0511 03:23:20.282523  5307 solver.cpp:747] class AP 19: 0.748297
-I0511 03:23:20.283898  5307 solver.cpp:747] class AP 20: 0.59774
-I0511 03:23:20.283905  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.619087
-I0511 03:23:20.284065  5307 solver.cpp:283] Tests completed in 100.723s
-I0511 03:23:20.840155  5307 solver.cpp:352] Iteration 72000 (0.992822 iter/s, 100.723s/100 iter), 139.2/232ep, loss = 3.05155
-I0511 03:23:20.840183  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95617 (* 1 = 2.95617 loss)
-I0511 03:23:20.840191  5307 sgd_solver.cpp:172] Iteration 72000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:24:21.332583  5307 solver.cpp:352] Iteration 72100 (1.65313 iter/s, 60.4914s/100 iter), 139.4/232ep, loss = 3.07664
-I0511 03:24:21.332656  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57719 (* 1 = 3.57719 loss)
-I0511 03:24:21.332665  5307 sgd_solver.cpp:172] Iteration 72100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:25:21.916609  5307 solver.cpp:352] Iteration 72200 (1.65063 iter/s, 60.583s/100 iter), 139.6/232ep, loss = 3.06678
-I0511 03:25:21.920967  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38199 (* 1 = 3.38199 loss)
-I0511 03:25:21.921028  5307 sgd_solver.cpp:172] Iteration 72200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:26:22.121351  5307 solver.cpp:352] Iteration 72300 (1.66103 iter/s, 60.2037s/100 iter), 139.8/232ep, loss = 3.00508
-I0511 03:26:22.121433  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74731 (* 1 = 2.74731 loss)
-I0511 03:26:22.121441  5307 sgd_solver.cpp:172] Iteration 72300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:27:18.519220  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:27:22.728324  5307 solver.cpp:352] Iteration 72400 (1.65 iter/s, 60.6059s/100 iter), 140/232ep, loss = 3.1278
-I0511 03:27:22.728421  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.64797 (* 1 = 2.64797 loss)
-I0511 03:27:22.728431  5307 sgd_solver.cpp:172] Iteration 72400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:28:23.054373  5307 solver.cpp:352] Iteration 72500 (1.65769 iter/s, 60.325s/100 iter), 140.2/232ep, loss = 3.01141
-I0511 03:28:23.054436  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71092 (* 1 = 2.71092 loss)
-I0511 03:28:23.054445  5307 sgd_solver.cpp:172] Iteration 72500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:29:23.481869  5307 solver.cpp:352] Iteration 72600 (1.6549 iter/s, 60.4265s/100 iter), 140.4/232ep, loss = 3.26152
-I0511 03:29:23.481925  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14742 (* 1 = 3.14742 loss)
-I0511 03:29:23.481932  5307 sgd_solver.cpp:172] Iteration 72600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:30:23.728221  5307 solver.cpp:352] Iteration 72700 (1.65988 iter/s, 60.2453s/100 iter), 140.6/232ep, loss = 3.17499
-I0511 03:30:23.728341  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.33493 (* 1 = 4.33493 loss)
-I0511 03:30:23.728349  5307 sgd_solver.cpp:172] Iteration 72700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:31:23.844614  5307 solver.cpp:352] Iteration 72800 (1.66347 iter/s, 60.1154s/100 iter), 140.8/232ep, loss = 3.15664
-I0511 03:31:23.844673  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.66648 (* 1 = 3.66648 loss)
-I0511 03:31:23.844682  5307 sgd_solver.cpp:172] Iteration 72800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:32:24.520457  5307 solver.cpp:352] Iteration 72900 (1.64813 iter/s, 60.6748s/100 iter), 140.9/232ep, loss = 2.99479
-I0511 03:32:24.520572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.53888 (* 1 = 2.53888 loss)
-I0511 03:32:24.520582  5307 sgd_solver.cpp:172] Iteration 72900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:32:30.003759  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:33:25.126344  5307 solver.cpp:352] Iteration 73000 (1.65003 iter/s, 60.6049s/100 iter), 141.1/232ep, loss = 2.92323
-I0511 03:33:25.126405  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.59324 (* 1 = 2.59324 loss)
-I0511 03:33:25.126415  5307 sgd_solver.cpp:172] Iteration 73000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:34:25.279366  5307 solver.cpp:352] Iteration 73100 (1.66246 iter/s, 60.152s/100 iter), 141.3/232ep, loss = 3.19742
-I0511 03:34:25.279520  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.23241 (* 1 = 3.23241 loss)
-I0511 03:34:25.279536  5307 sgd_solver.cpp:172] Iteration 73100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:35:25.761797  5307 solver.cpp:352] Iteration 73200 (1.6534 iter/s, 60.4814s/100 iter), 141.5/232ep, loss = 3.00938
-I0511 03:35:25.761957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9753 (* 1 = 2.9753 loss)
-I0511 03:35:25.761970  5307 sgd_solver.cpp:172] Iteration 73200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:36:26.001161  5307 solver.cpp:352] Iteration 73300 (1.66007 iter/s, 60.2383s/100 iter), 141.7/232ep, loss = 3.24271
-I0511 03:36:26.001288  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25406 (* 1 = 3.25406 loss)
-I0511 03:36:26.001312  5307 sgd_solver.cpp:172] Iteration 73300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:37:26.115409  5307 solver.cpp:352] Iteration 73400 (1.66353 iter/s, 60.1132s/100 iter), 141.9/232ep, loss = 2.95538
-I0511 03:37:26.115499  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.21927 (* 1 = 4.21927 loss)
-I0511 03:37:26.115511  5307 sgd_solver.cpp:172] Iteration 73400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:37:42.700953  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:38:27.965601  5307 solver.cpp:352] Iteration 73500 (1.61684 iter/s, 61.8491s/100 iter), 142.1/232ep, loss = 2.98142
-I0511 03:38:27.965658  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88538 (* 1 = 2.88538 loss)
-I0511 03:38:27.965667  5307 sgd_solver.cpp:172] Iteration 73500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:39:28.462384  5307 solver.cpp:352] Iteration 73600 (1.65301 iter/s, 60.4957s/100 iter), 142.3/232ep, loss = 3.18136
-I0511 03:39:28.462545  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7183 (* 1 = 2.7183 loss)
-I0511 03:39:28.462556  5307 sgd_solver.cpp:172] Iteration 73600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:40:29.701385  5307 solver.cpp:352] Iteration 73700 (1.63297 iter/s, 61.2379s/100 iter), 142.5/232ep, loss = 3.24209
-I0511 03:40:29.701820  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14435 (* 1 = 3.14435 loss)
-I0511 03:40:29.701833  5307 sgd_solver.cpp:172] Iteration 73700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:41:30.354627  5307 solver.cpp:352] Iteration 73800 (1.64874 iter/s, 60.6522s/100 iter), 142.7/232ep, loss = 3.10667
-I0511 03:41:30.360618  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50329 (* 1 = 3.50329 loss)
-I0511 03:41:30.360646  5307 sgd_solver.cpp:172] Iteration 73800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:42:30.918884  5307 solver.cpp:352] Iteration 73900 (1.65117 iter/s, 60.5632s/100 iter), 142.9/232ep, loss = 2.98285
-I0511 03:42:30.918987  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23428 (* 1 = 2.23428 loss)
-I0511 03:42:30.918998  5307 sgd_solver.cpp:172] Iteration 73900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:42:57.789077  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:43:30.908464  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_74000.caffemodel
-I0511 03:43:30.925472  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_74000.solverstate
-I0511 03:43:30.930797  5307 solver.cpp:635] Iteration 74000, Testing net (#0)
-I0511 03:44:11.253901  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:44:11.489528  5307 solver.cpp:747] class AP 1: 0.641228
-I0511 03:44:11.490033  5307 solver.cpp:747] class AP 2: 0.726448
-I0511 03:44:11.495765  5307 solver.cpp:747] class AP 3: 0.532019
-I0511 03:44:11.499542  5307 solver.cpp:747] class AP 4: 0.513854
-I0511 03:44:11.519951  5307 solver.cpp:747] class AP 5: 0.325712
-I0511 03:44:11.520368  5307 solver.cpp:747] class AP 6: 0.730229
-I0511 03:44:11.529734  5307 solver.cpp:747] class AP 7: 0.697817
-I0511 03:44:11.530369  5307 solver.cpp:747] class AP 8: 0.799968
-I0511 03:44:11.547799  5307 solver.cpp:747] class AP 9: 0.416313
-I0511 03:44:11.548456  5307 solver.cpp:747] class AP 10: 0.634536
-I0511 03:44:11.549134  5307 solver.cpp:747] class AP 11: 0.569721
-I0511 03:44:11.549952  5307 solver.cpp:747] class AP 12: 0.724131
-I0511 03:44:11.550333  5307 solver.cpp:747] class AP 13: 0.784362
-I0511 03:44:11.550717  5307 solver.cpp:747] class AP 14: 0.745329
-I0511 03:44:11.598302  5307 solver.cpp:747] class AP 15: 0.721109
-I0511 03:44:11.605280  5307 solver.cpp:747] class AP 16: 0.365057
-I0511 03:44:11.607946  5307 solver.cpp:747] class AP 17: 0.59138
-I0511 03:44:11.608561  5307 solver.cpp:747] class AP 18: 0.597681
-I0511 03:44:11.609176  5307 solver.cpp:747] class AP 19: 0.748637
-I0511 03:44:11.610620  5307 solver.cpp:747] class AP 20: 0.598941
-I0511 03:44:11.610625  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.623223
-I0511 03:44:11.610837  5307 solver.cpp:283] Tests completed in 100.69s
-I0511 03:44:12.156131  5307 solver.cpp:352] Iteration 74000 (0.993144 iter/s, 100.69s/100 iter), 143.1/232ep, loss = 3.17362
-I0511 03:44:12.156162  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.56647 (* 1 = 2.56647 loss)
-I0511 03:44:12.156170  5307 sgd_solver.cpp:172] Iteration 74000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:45:12.416200  5307 solver.cpp:352] Iteration 74100 (1.6595 iter/s, 60.259s/100 iter), 143.3/232ep, loss = 3.02609
-I0511 03:45:12.416337  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.72373 (* 1 = 2.72373 loss)
-I0511 03:45:12.416348  5307 sgd_solver.cpp:172] Iteration 74100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:46:12.726747  5307 solver.cpp:352] Iteration 74200 (1.65811 iter/s, 60.3095s/100 iter), 143.5/232ep, loss = 3.04684
-I0511 03:46:12.726939  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.64403 (* 1 = 2.64403 loss)
-I0511 03:46:12.726958  5307 sgd_solver.cpp:172] Iteration 74200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:47:13.618039  5307 solver.cpp:352] Iteration 74300 (1.6423 iter/s, 60.8902s/100 iter), 143.7/232ep, loss = 3.13517
-I0511 03:47:13.618142  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88684 (* 1 = 2.88684 loss)
-I0511 03:47:13.618157  5307 sgd_solver.cpp:172] Iteration 74300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:48:14.861030  5307 solver.cpp:352] Iteration 74400 (1.63287 iter/s, 61.242s/100 iter), 143.8/232ep, loss = 3.45337
-I0511 03:48:14.861167  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3419 (* 1 = 3.3419 loss)
-I0511 03:48:14.861178  5307 sgd_solver.cpp:172] Iteration 74400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:48:51.966392  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:49:15.283468  5307 solver.cpp:352] Iteration 74500 (1.65504 iter/s, 60.4214s/100 iter), 144/232ep, loss = 2.85047
-I0511 03:49:15.283495  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.93082 (* 1 = 2.93082 loss)
-I0511 03:49:15.283504  5307 sgd_solver.cpp:172] Iteration 74500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:50:15.385535  5307 solver.cpp:352] Iteration 74600 (1.66386 iter/s, 60.1011s/100 iter), 144.2/232ep, loss = 3.20432
-I0511 03:50:15.385777  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.67358 (* 1 = 2.67358 loss)
-I0511 03:50:15.385788  5307 sgd_solver.cpp:172] Iteration 74600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:51:15.879094  5307 solver.cpp:352] Iteration 74700 (1.6531 iter/s, 60.4925s/100 iter), 144.4/232ep, loss = 3.25151
-I0511 03:51:15.879184  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59463 (* 1 = 3.59463 loss)
-I0511 03:51:15.879199  5307 sgd_solver.cpp:172] Iteration 74700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:52:16.319046  5307 solver.cpp:352] Iteration 74800 (1.65456 iter/s, 60.4389s/100 iter), 144.6/232ep, loss = 3.18278
-I0511 03:52:16.319164  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4493 (* 1 = 3.4493 loss)
-I0511 03:52:16.319173  5307 sgd_solver.cpp:172] Iteration 74800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:53:17.035173  5307 solver.cpp:352] Iteration 74900 (1.64704 iter/s, 60.7151s/100 iter), 144.8/232ep, loss = 2.96317
-I0511 03:53:17.035262  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10215 (* 1 = 3.10215 loss)
-I0511 03:53:17.035274  5307 sgd_solver.cpp:172] Iteration 74900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:54:04.660311  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:54:17.287374  5307 solver.cpp:352] Iteration 75000 (1.65972 iter/s, 60.2512s/100 iter), 145/232ep, loss = 3.04642
-I0511 03:54:17.287405  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91731 (* 1 = 2.91731 loss)
-I0511 03:54:17.287411  5307 sgd_solver.cpp:172] Iteration 75000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:55:16.952937  5307 solver.cpp:352] Iteration 75100 (1.67604 iter/s, 59.6646s/100 iter), 145.2/232ep, loss = 3.07866
-I0511 03:55:16.953037  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96777 (* 1 = 2.96777 loss)
-I0511 03:55:16.953059  5307 sgd_solver.cpp:172] Iteration 75100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:56:17.980620  5307 solver.cpp:352] Iteration 75200 (1.63863 iter/s, 61.0266s/100 iter), 145.4/232ep, loss = 3.0594
-I0511 03:56:17.980721  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.35611 (* 1 = 3.35611 loss)
-I0511 03:56:17.980746  5307 sgd_solver.cpp:172] Iteration 75200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:57:19.051538  5307 solver.cpp:352] Iteration 75300 (1.63747 iter/s, 61.0699s/100 iter), 145.6/232ep, loss = 3.14592
-I0511 03:57:19.051651  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.43066 (* 1 = 2.43066 loss)
-I0511 03:57:19.051674  5307 sgd_solver.cpp:172] Iteration 75300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:58:20.779593  5307 solver.cpp:352] Iteration 75400 (1.62004 iter/s, 61.727s/100 iter), 145.8/232ep, loss = 2.98371
-I0511 03:58:20.780081  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68028 (* 1 = 3.68028 loss)
-I0511 03:58:20.780143  5307 sgd_solver.cpp:172] Iteration 75400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:59:19.123008  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:59:22.062898  5307 solver.cpp:352] Iteration 75500 (1.63179 iter/s, 61.2823s/100 iter), 146/232ep, loss = 3.34483
-I0511 03:59:22.062996  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.76846 (* 1 = 3.76846 loss)
-I0511 03:59:22.063019  5307 sgd_solver.cpp:172] Iteration 75500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:00:23.406405  5307 solver.cpp:352] Iteration 75600 (1.63019 iter/s, 61.3425s/100 iter), 146.2/232ep, loss = 2.99761
-I0511 04:00:23.406504  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74646 (* 1 = 2.74646 loss)
-I0511 04:00:23.406527  5307 sgd_solver.cpp:172] Iteration 75600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:01:25.636024  5307 solver.cpp:352] Iteration 75700 (1.60698 iter/s, 62.2285s/100 iter), 146.4/232ep, loss = 3.04397
-I0511 04:01:25.636116  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0651 (* 1 = 4.0651 loss)
-I0511 04:01:25.636124  5307 sgd_solver.cpp:172] Iteration 75700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:02:27.433805  5307 solver.cpp:352] Iteration 75800 (1.61821 iter/s, 61.7967s/100 iter), 146.6/232ep, loss = 3.0474
-I0511 04:02:27.433866  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96175 (* 1 = 2.96175 loss)
-I0511 04:02:27.433876  5307 sgd_solver.cpp:172] Iteration 75800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:03:28.920656  5307 solver.cpp:352] Iteration 75900 (1.62639 iter/s, 61.4858s/100 iter), 146.7/232ep, loss = 3.04129
-I0511 04:03:28.921588  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.01541 (* 1 = 2.01541 loss)
-I0511 04:03:28.921612  5307 sgd_solver.cpp:172] Iteration 75900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:04:29.593194  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_76000.caffemodel
-I0511 04:04:29.607446  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_76000.solverstate
-I0511 04:04:29.613701  5307 solver.cpp:635] Iteration 76000, Testing net (#0)
-I0511 04:05:10.383334  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:05:10.593204  5307 solver.cpp:747] class AP 1: 0.637343
-I0511 04:05:10.593714  5307 solver.cpp:747] class AP 2: 0.725514
-I0511 04:05:10.600751  5307 solver.cpp:747] class AP 3: 0.543728
-I0511 04:05:10.604346  5307 solver.cpp:747] class AP 4: 0.513556
-I0511 04:05:10.624176  5307 solver.cpp:747] class AP 5: 0.327433
-I0511 04:05:10.624552  5307 solver.cpp:747] class AP 6: 0.710337
-I0511 04:05:10.632586  5307 solver.cpp:747] class AP 7: 0.696507
-I0511 04:05:10.633287  5307 solver.cpp:747] class AP 8: 0.80158
-I0511 04:05:10.653848  5307 solver.cpp:747] class AP 9: 0.424203
-I0511 04:05:10.654513  5307 solver.cpp:747] class AP 10: 0.638241
-I0511 04:05:10.655176  5307 solver.cpp:747] class AP 11: 0.585361
-I0511 04:05:10.656023  5307 solver.cpp:747] class AP 12: 0.714094
-I0511 04:05:10.656427  5307 solver.cpp:747] class AP 13: 0.791293
-I0511 04:05:10.656805  5307 solver.cpp:747] class AP 14: 0.739938
-I0511 04:05:10.705305  5307 solver.cpp:747] class AP 15: 0.721612
-I0511 04:05:10.712443  5307 solver.cpp:747] class AP 16: 0.353075
-I0511 04:05:10.715252  5307 solver.cpp:747] class AP 17: 0.607122
-I0511 04:05:10.715829  5307 solver.cpp:747] class AP 18: 0.608899
-I0511 04:05:10.716554  5307 solver.cpp:747] class AP 19: 0.746024
-I0511 04:05:10.718053  5307 solver.cpp:747] class AP 20: 0.601709
-I0511 04:05:10.718061  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.624378
-I0511 04:05:10.718263  5307 solver.cpp:283] Tests completed in 101.796s
-I0511 04:05:11.252502  5307 solver.cpp:352] Iteration 76000 (0.982358 iter/s, 101.796s/100 iter), 146.9/232ep, loss = 2.94222
-I0511 04:05:11.252539  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.04738 (* 1 = 4.04738 loss)
-I0511 04:05:11.252548  5307 sgd_solver.cpp:172] Iteration 76000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:05:19.245709  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:06:11.964781  5307 solver.cpp:352] Iteration 76100 (1.64714 iter/s, 60.7112s/100 iter), 147.1/232ep, loss = 2.95309
-I0511 04:06:11.964931  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.86256 (* 1 = 2.86256 loss)
-I0511 04:06:11.964942  5307 sgd_solver.cpp:172] Iteration 76100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:07:12.802561  5307 solver.cpp:352] Iteration 76200 (1.64374 iter/s, 60.8367s/100 iter), 147.3/232ep, loss = 3.25318
-I0511 04:07:12.802662  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.17985 (* 1 = 4.17985 loss)
-I0511 04:07:12.802690  5307 sgd_solver.cpp:172] Iteration 76200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:08:14.762794  5307 solver.cpp:352] Iteration 76300 (1.61397 iter/s, 61.9592s/100 iter), 147.5/232ep, loss = 2.94757
-I0511 04:08:14.762857  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23976 (* 1 = 2.23976 loss)
-I0511 04:08:14.762864  5307 sgd_solver.cpp:172] Iteration 76300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:09:16.026989  5307 solver.cpp:352] Iteration 76400 (1.6323 iter/s, 61.2631s/100 iter), 147.7/232ep, loss = 3.11323
-I0511 04:09:16.027123  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.97677 (* 1 = 3.97677 loss)
-I0511 04:09:16.027142  5307 sgd_solver.cpp:172] Iteration 76400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:10:17.014519  5307 solver.cpp:352] Iteration 76500 (1.63971 iter/s, 60.9865s/100 iter), 147.9/232ep, loss = 3.02502
-I0511 04:10:17.014600  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14904 (* 1 = 3.14904 loss)
-I0511 04:10:17.014618  5307 sgd_solver.cpp:172] Iteration 76500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:10:36.196403  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:11:19.378612  5307 solver.cpp:352] Iteration 76600 (1.60351 iter/s, 62.363s/100 iter), 148.1/232ep, loss = 3.1812
-I0511 04:11:19.380671  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.34103 (* 1 = 3.34103 loss)
-I0511 04:11:19.380684  5307 sgd_solver.cpp:172] Iteration 76600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:12:21.259330  5307 solver.cpp:352] Iteration 76700 (1.61604 iter/s, 61.8797s/100 iter), 148.3/232ep, loss = 3.13056
-I0511 04:12:21.259500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73742 (* 1 = 2.73742 loss)
-I0511 04:12:21.259526  5307 sgd_solver.cpp:172] Iteration 76700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:13:23.125416  5307 solver.cpp:352] Iteration 76800 (1.61642 iter/s, 61.865s/100 iter), 148.5/232ep, loss = 3.21444
-I0511 04:13:23.125500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94929 (* 1 = 2.94929 loss)
-I0511 04:13:23.125511  5307 sgd_solver.cpp:172] Iteration 76800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:14:24.983587  5307 solver.cpp:352] Iteration 76900 (1.61663 iter/s, 61.8571s/100 iter), 148.7/232ep, loss = 2.99404
-I0511 04:14:24.983664  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85883 (* 1 = 2.85883 loss)
-I0511 04:14:24.983672  5307 sgd_solver.cpp:172] Iteration 76900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:15:26.783061  5307 solver.cpp:352] Iteration 77000 (1.61816 iter/s, 61.7984s/100 iter), 148.9/232ep, loss = 2.95391
-I0511 04:15:26.783149  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.34189 (* 1 = 2.34189 loss)
-I0511 04:15:26.783167  5307 sgd_solver.cpp:172] Iteration 77000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:15:55.960445  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:16:28.692605  5307 solver.cpp:352] Iteration 77100 (1.61529 iter/s, 61.9085s/100 iter), 149.1/232ep, loss = 3.08061
-I0511 04:16:28.693063  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6037 (* 1 = 2.6037 loss)
-I0511 04:16:28.693089  5307 sgd_solver.cpp:172] Iteration 77100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:17:30.074394  5307 solver.cpp:352] Iteration 77200 (1.62918 iter/s, 61.3808s/100 iter), 149.3/232ep, loss = 3.09659
-I0511 04:17:30.074466  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.57682 (* 1 = 2.57682 loss)
-I0511 04:17:30.074475  5307 sgd_solver.cpp:172] Iteration 77200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:18:31.458698  5307 solver.cpp:352] Iteration 77300 (1.62911 iter/s, 61.3832s/100 iter), 149.5/232ep, loss = 3.17427
-I0511 04:18:31.458783  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.77503 (* 1 = 3.77503 loss)
-I0511 04:18:31.458793  5307 sgd_solver.cpp:172] Iteration 77300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:19:33.653574  5307 solver.cpp:352] Iteration 77400 (1.60788 iter/s, 62.1938s/100 iter), 149.6/232ep, loss = 3.12145
-I0511 04:19:33.653671  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94468 (* 1 = 2.94468 loss)
-I0511 04:19:33.653678  5307 sgd_solver.cpp:172] Iteration 77400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:20:35.175375  5307 solver.cpp:352] Iteration 77500 (1.62547 iter/s, 61.5207s/100 iter), 149.8/232ep, loss = 3.29141
-I0511 04:20:35.175492  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.42403 (* 1 = 2.42403 loss)
-I0511 04:20:35.175504  5307 sgd_solver.cpp:172] Iteration 77500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:21:14.659782  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:21:35.705682  5307 solver.cpp:352] Iteration 77600 (1.65209 iter/s, 60.5293s/100 iter), 150/232ep, loss = 3.04855
-I0511 04:21:35.705739  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83429 (* 1 = 2.83429 loss)
-I0511 04:21:35.705750  5307 sgd_solver.cpp:172] Iteration 77600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:22:36.228951  5307 solver.cpp:352] Iteration 77700 (1.65228 iter/s, 60.5223s/100 iter), 150.2/232ep, loss = 3.05063
-I0511 04:22:36.229099  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.06361 (* 1 = 3.06361 loss)
-I0511 04:22:36.229125  5307 sgd_solver.cpp:172] Iteration 77700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:23:37.886205  5307 solver.cpp:352] Iteration 77800 (1.6219 iter/s, 61.6562s/100 iter), 150.4/232ep, loss = 3.20392
-I0511 04:23:37.886261  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.26003 (* 1 = 4.26003 loss)
-I0511 04:23:37.886270  5307 sgd_solver.cpp:172] Iteration 77800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:24:45.856096  5307 solver.cpp:352] Iteration 77900 (1.47126 iter/s, 67.9687s/100 iter), 150.6/232ep, loss = 3.197
-I0511 04:24:45.856202  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5935 (* 1 = 3.5935 loss)
-I0511 04:24:45.856223  5307 sgd_solver.cpp:172] Iteration 77900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:25:50.988086  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_78000.caffemodel
-I0511 04:25:51.005568  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_78000.solverstate
-I0511 04:25:51.010843  5307 solver.cpp:635] Iteration 78000, Testing net (#0)
-I0511 04:26:31.213625  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:26:31.416895  5307 solver.cpp:747] class AP 1: 0.632267
-I0511 04:26:31.417551  5307 solver.cpp:747] class AP 2: 0.7226
-I0511 04:26:31.424793  5307 solver.cpp:747] class AP 3: 0.54852
-I0511 04:26:31.428757  5307 solver.cpp:747] class AP 4: 0.509979
-I0511 04:26:31.444545  5307 solver.cpp:747] class AP 5: 0.316974
-I0511 04:26:31.444928  5307 solver.cpp:747] class AP 6: 0.724555
-I0511 04:26:31.455165  5307 solver.cpp:747] class AP 7: 0.705174
-I0511 04:26:31.455703  5307 solver.cpp:747] class AP 8: 0.798495
-I0511 04:26:31.472879  5307 solver.cpp:747] class AP 9: 0.411551
-I0511 04:26:31.473654  5307 solver.cpp:747] class AP 10: 0.616103
-I0511 04:26:31.474263  5307 solver.cpp:747] class AP 11: 0.570838
-I0511 04:26:31.475164  5307 solver.cpp:747] class AP 12: 0.724401
-I0511 04:26:31.475595  5307 solver.cpp:747] class AP 13: 0.79868
-I0511 04:26:31.476016  5307 solver.cpp:747] class AP 14: 0.739518
-I0511 04:26:31.527408  5307 solver.cpp:747] class AP 15: 0.72125
-I0511 04:26:31.532173  5307 solver.cpp:747] class AP 16: 0.356912
-I0511 04:26:31.535329  5307 solver.cpp:747] class AP 17: 0.57359
-I0511 04:26:31.535961  5307 solver.cpp:747] class AP 18: 0.596406
-I0511 04:26:31.536696  5307 solver.cpp:747] class AP 19: 0.74554
-I0511 04:26:31.538126  5307 solver.cpp:747] class AP 20: 0.598131
-I0511 04:26:31.538133  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.620574
-I0511 04:26:31.538298  5307 solver.cpp:283] Tests completed in 105.68s
-I0511 04:26:32.080586  5307 solver.cpp:352] Iteration 78000 (0.946249 iter/s, 105.68s/100 iter), 150.8/232ep, loss = 2.87031
-I0511 04:26:32.080616  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.55553 (* 1 = 2.55553 loss)
-I0511 04:26:32.080626  5307 sgd_solver.cpp:172] Iteration 78000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:27:21.375700  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:27:32.847172  5307 solver.cpp:352] Iteration 78100 (1.64567 iter/s, 60.7655s/100 iter), 151/232ep, loss = 3.09697
-I0511 04:27:32.847259  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.07398 (* 1 = 4.07398 loss)
-I0511 04:27:32.847275  5307 sgd_solver.cpp:172] Iteration 78100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:28:33.441352  5307 solver.cpp:352] Iteration 78200 (1.65035 iter/s, 60.5931s/100 iter), 151.2/232ep, loss = 2.97198
-I0511 04:28:33.441449  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01782 (* 1 = 3.01782 loss)
-I0511 04:28:33.441468  5307 sgd_solver.cpp:172] Iteration 78200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:29:34.452617  5307 solver.cpp:352] Iteration 78300 (1.63907 iter/s, 61.0102s/100 iter), 151.4/232ep, loss = 2.90562
-I0511 04:29:34.452863  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.22756 (* 1 = 2.22756 loss)
-I0511 04:29:34.452874  5307 sgd_solver.cpp:172] Iteration 78300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:30:34.917018  5307 solver.cpp:352] Iteration 78400 (1.65389 iter/s, 60.4634s/100 iter), 151.6/232ep, loss = 3.18169
-I0511 04:30:34.917094  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8036 (* 1 = 2.8036 loss)
-I0511 04:30:34.917109  5307 sgd_solver.cpp:172] Iteration 78400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:31:36.095175  5307 solver.cpp:352] Iteration 78500 (1.6346 iter/s, 61.1771s/100 iter), 151.8/232ep, loss = 3.01962
-I0511 04:31:36.095235  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8123 (* 1 = 2.8123 loss)
-I0511 04:31:36.095243  5307 sgd_solver.cpp:172] Iteration 78500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:32:35.911156  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:32:36.532106  5307 solver.cpp:352] Iteration 78600 (1.65465 iter/s, 60.4359s/100 iter), 152/232ep, loss = 3.21632
-I0511 04:32:36.532129  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63883 (* 1 = 3.63883 loss)
-I0511 04:32:36.532133  5307 sgd_solver.cpp:172] Iteration 78600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:33:38.368151  5307 solver.cpp:352] Iteration 78700 (1.61721 iter/s, 61.835s/100 iter), 152.2/232ep, loss = 3.0718
-I0511 04:33:38.368247  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00937 (* 1 = 3.00937 loss)
-I0511 04:33:38.368254  5307 sgd_solver.cpp:172] Iteration 78700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:34:39.152809  5307 solver.cpp:352] Iteration 78800 (1.64518 iter/s, 60.7836s/100 iter), 152.4/232ep, loss = 3.26289
-I0511 04:34:39.152863  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.34513 (* 1 = 2.34513 loss)
-I0511 04:34:39.152868  5307 sgd_solver.cpp:172] Iteration 78800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:35:39.979418  5307 solver.cpp:352] Iteration 78900 (1.64405 iter/s, 60.8256s/100 iter), 152.5/232ep, loss = 2.99703
-I0511 04:35:39.979521  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28211 (* 1 = 3.28211 loss)
-I0511 04:35:39.979542  5307 sgd_solver.cpp:172] Iteration 78900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:36:41.730059  5307 solver.cpp:352] Iteration 79000 (1.61944 iter/s, 61.7496s/100 iter), 152.7/232ep, loss = 3.15469
-I0511 04:36:41.730115  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83027 (* 1 = 2.83027 loss)
-I0511 04:36:41.730124  5307 sgd_solver.cpp:172] Iteration 79000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:37:43.383158  5307 solver.cpp:352] Iteration 79100 (1.62201 iter/s, 61.652s/100 iter), 152.9/232ep, loss = 3.03458
-I0511 04:37:43.383288  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40238 (* 1 = 3.40238 loss)
-I0511 04:37:43.383308  5307 sgd_solver.cpp:172] Iteration 79100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:37:54.007740  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:38:44.456564  5307 solver.cpp:352] Iteration 79200 (1.6374 iter/s, 61.0724s/100 iter), 153.1/232ep, loss = 3.09404
-I0511 04:38:44.456629  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.76522 (* 1 = 2.76522 loss)
-I0511 04:38:44.456636  5307 sgd_solver.cpp:172] Iteration 79200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:39:46.192864  5307 solver.cpp:352] Iteration 79300 (1.61982 iter/s, 61.7352s/100 iter), 153.3/232ep, loss = 3.07999
-I0511 04:39:46.192991  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25264 (* 1 = 3.25264 loss)
-I0511 04:39:46.193011  5307 sgd_solver.cpp:172] Iteration 79300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:40:47.734508  5307 solver.cpp:352] Iteration 79400 (1.62494 iter/s, 61.5406s/100 iter), 153.5/232ep, loss = 3.03022
-I0511 04:40:47.734652  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10661 (* 1 = 3.10661 loss)
-I0511 04:40:47.734671  5307 sgd_solver.cpp:172] Iteration 79400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:41:48.032901  5307 solver.cpp:352] Iteration 79500 (1.65845 iter/s, 60.2974s/100 iter), 153.7/232ep, loss = 3.18149
-I0511 04:41:48.032958  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.84987 (* 1 = 4.84987 loss)
-I0511 04:41:48.032968  5307 sgd_solver.cpp:172] Iteration 79500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:42:48.269826  5307 solver.cpp:352] Iteration 79600 (1.66014 iter/s, 60.2359s/100 iter), 153.9/232ep, loss = 3.0324
-I0511 04:42:48.269889  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51017 (* 1 = 3.51017 loss)
-I0511 04:42:48.269898  5307 sgd_solver.cpp:172] Iteration 79600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:43:08.215611  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:43:48.437150  5307 solver.cpp:352] Iteration 79700 (1.66206 iter/s, 60.1663s/100 iter), 154.1/232ep, loss = 3.10614
-I0511 04:43:48.437216  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.18151 (* 1 = 3.18151 loss)
-I0511 04:43:48.437223  5307 sgd_solver.cpp:172] Iteration 79700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:44:49.525799  5307 solver.cpp:352] Iteration 79800 (1.63699 iter/s, 61.0876s/100 iter), 154.3/232ep, loss = 2.98906
-I0511 04:44:49.525918  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.24818 (* 1 = 2.24818 loss)
-I0511 04:44:49.525928  5307 sgd_solver.cpp:172] Iteration 79800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:45:50.659781  5307 solver.cpp:352] Iteration 79900 (1.63578 iter/s, 61.133s/100 iter), 154.5/232ep, loss = 3.13227
-I0511 04:45:50.659904  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.23574 (* 1 = 3.23574 loss)
-I0511 04:45:50.659934  5307 sgd_solver.cpp:172] Iteration 79900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:46:51.066712  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_80000.caffemodel
-I0511 04:46:51.080826  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_80000.solverstate
-I0511 04:46:51.084496  5307 solver.cpp:635] Iteration 80000, Testing net (#0)
-I0511 04:47:31.970968  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:47:32.214776  5307 solver.cpp:747] class AP 1: 0.656922
-I0511 04:47:32.215538  5307 solver.cpp:747] class AP 2: 0.736532
-I0511 04:47:32.223600  5307 solver.cpp:747] class AP 3: 0.537648
-I0511 04:47:32.228229  5307 solver.cpp:747] class AP 4: 0.508865
-I0511 04:47:32.246457  5307 solver.cpp:747] class AP 5: 0.331343
-I0511 04:47:32.246815  5307 solver.cpp:747] class AP 6: 0.724548
-I0511 04:47:32.254050  5307 solver.cpp:747] class AP 7: 0.694589
-I0511 04:47:32.254701  5307 solver.cpp:747] class AP 8: 0.803459
-I0511 04:47:32.274544  5307 solver.cpp:747] class AP 9: 0.431811
-I0511 04:47:32.275423  5307 solver.cpp:747] class AP 10: 0.626501
-I0511 04:47:32.276293  5307 solver.cpp:747] class AP 11: 0.587636
-I0511 04:47:32.277295  5307 solver.cpp:747] class AP 12: 0.712719
-I0511 04:47:32.277781  5307 solver.cpp:747] class AP 13: 0.787989
-I0511 04:47:32.278138  5307 solver.cpp:747] class AP 14: 0.731135
-I0511 04:47:32.329286  5307 solver.cpp:747] class AP 15: 0.721379
-I0511 04:47:32.335880  5307 solver.cpp:747] class AP 16: 0.358117
-I0511 04:47:32.338951  5307 solver.cpp:747] class AP 17: 0.586319
-I0511 04:47:32.339478  5307 solver.cpp:747] class AP 18: 0.602769
-I0511 04:47:32.340133  5307 solver.cpp:747] class AP 19: 0.74245
-I0511 04:47:32.341581  5307 solver.cpp:747] class AP 20: 0.596077
-I0511 04:47:32.341706  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.62394
-I0511 04:47:32.341799  5307 solver.cpp:283] Tests completed in 101.68s
-I0511 04:47:32.905565  5307 solver.cpp:352] Iteration 80000 (0.983475 iter/s, 101.68s/100 iter), 154.7/232ep, loss = 2.99031
-I0511 04:47:32.905604  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96569 (* 1 = 2.96569 loss)
-I0511 04:47:32.905612  5307 sgd_solver.cpp:172] Iteration 80000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:48:34.126289  5307 solver.cpp:352] Iteration 80100 (1.63346 iter/s, 61.2196s/100 iter), 154.9/232ep, loss = 2.95308
-I0511 04:48:34.126351  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89951 (* 1 = 2.89951 loss)
-I0511 04:48:34.126360  5307 sgd_solver.cpp:172] Iteration 80100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:49:05.360407  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:49:35.240214  5307 solver.cpp:352] Iteration 80200 (1.63632 iter/s, 61.1129s/100 iter), 155.1/232ep, loss = 3.06651
-I0511 04:49:35.240325  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07834 (* 1 = 3.07834 loss)
-I0511 04:49:35.240341  5307 sgd_solver.cpp:172] Iteration 80200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:50:35.741667  5307 solver.cpp:352] Iteration 80300 (1.65288 iter/s, 60.5004s/100 iter), 155.3/232ep, loss = 3.06086
-I0511 04:50:35.741739  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36068 (* 1 = 3.36068 loss)
-I0511 04:50:35.741750  5307 sgd_solver.cpp:172] Iteration 80300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:51:37.026394  5307 solver.cpp:352] Iteration 80400 (1.63176 iter/s, 61.2837s/100 iter), 155.4/232ep, loss = 3.0957
-I0511 04:51:37.026475  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44752 (* 1 = 3.44752 loss)
-I0511 04:51:37.026511  5307 sgd_solver.cpp:172] Iteration 80400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:52:38.957073  5307 solver.cpp:352] Iteration 80500 (1.61474 iter/s, 61.9296s/100 iter), 155.6/232ep, loss = 3.05734
-I0511 04:52:38.957156  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89145 (* 1 = 2.89145 loss)
-I0511 04:52:38.957165  5307 sgd_solver.cpp:172] Iteration 80500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:53:40.124766  5307 solver.cpp:352] Iteration 80600 (1.63488 iter/s, 61.1666s/100 iter), 155.8/232ep, loss = 3.12808
-I0511 04:53:40.124861  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.12121 (* 1 = 4.12121 loss)
-I0511 04:53:40.124873  5307 sgd_solver.cpp:172] Iteration 80600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:54:22.535035  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:54:41.483376  5307 solver.cpp:352] Iteration 80700 (1.62979 iter/s, 61.3576s/100 iter), 156/232ep, loss = 3.07514
-I0511 04:54:41.483403  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65612 (* 1 = 2.65612 loss)
-I0511 04:54:41.483409  5307 sgd_solver.cpp:172] Iteration 80700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:55:43.258492  5307 solver.cpp:352] Iteration 80800 (1.6188 iter/s, 61.7741s/100 iter), 156.2/232ep, loss = 3.16967
-I0511 04:55:43.261402  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26641 (* 1 = 3.26641 loss)
-I0511 04:55:43.261415  5307 sgd_solver.cpp:172] Iteration 80800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:56:44.410297  5307 solver.cpp:352] Iteration 80900 (1.6353 iter/s, 61.1508s/100 iter), 156.4/232ep, loss = 2.97334
-I0511 04:56:44.410429  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81958 (* 1 = 2.81958 loss)
-I0511 04:56:44.410444  5307 sgd_solver.cpp:172] Iteration 80900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:57:45.559784  5307 solver.cpp:352] Iteration 81000 (1.63536 iter/s, 61.1484s/100 iter), 156.6/232ep, loss = 3.06272
-I0511 04:57:45.559870  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.07643 (* 1 = 4.07643 loss)
-I0511 04:57:45.559885  5307 sgd_solver.cpp:172] Iteration 81000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:58:47.035486  5307 solver.cpp:352] Iteration 81100 (1.62669 iter/s, 61.4747s/100 iter), 156.8/232ep, loss = 3.18442
-I0511 04:58:47.035533  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.86006 (* 1 = 1.86006 loss)
-I0511 04:58:47.035540  5307 sgd_solver.cpp:172] Iteration 81100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:59:39.381413  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:59:48.628669  5307 solver.cpp:352] Iteration 81200 (1.62358 iter/s, 61.5921s/100 iter), 157/232ep, loss = 2.97539
-I0511 04:59:48.628701  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.39648 (* 1 = 2.39648 loss)
-I0511 04:59:48.628711  5307 sgd_solver.cpp:172] Iteration 81200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:00:50.158447  5307 solver.cpp:352] Iteration 81300 (1.62526 iter/s, 61.5287s/100 iter), 157.2/232ep, loss = 3.16712
-I0511 05:00:50.158540  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19337 (* 1 = 3.19337 loss)
-I0511 05:00:50.158632  5307 sgd_solver.cpp:172] Iteration 81300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:01:50.419970  5307 solver.cpp:352] Iteration 81400 (1.65946 iter/s, 60.2605s/100 iter), 157.4/232ep, loss = 2.95731
-I0511 05:01:50.420078  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30601 (* 1 = 3.30601 loss)
-I0511 05:01:50.420086  5307 sgd_solver.cpp:172] Iteration 81400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:02:51.010126  5307 solver.cpp:352] Iteration 81500 (1.65046 iter/s, 60.5891s/100 iter), 157.6/232ep, loss = 3.17708
-I0511 05:02:51.012492  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81883 (* 1 = 2.81883 loss)
-I0511 05:02:51.012545  5307 sgd_solver.cpp:172] Iteration 81500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:03:51.385087  5307 solver.cpp:352] Iteration 81600 (1.65634 iter/s, 60.3739s/100 iter), 157.8/232ep, loss = 3.05348
-I0511 05:03:51.385354  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47478 (* 1 = 3.47478 loss)
-I0511 05:03:51.385385  5307 sgd_solver.cpp:172] Iteration 81600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:04:52.400323  5307 solver.cpp:352] Iteration 81700 (1.63896 iter/s, 61.0142s/100 iter), 158/232ep, loss = 3.07452
-I0511 05:04:52.401495  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68926 (* 1 = 3.68926 loss)
-I0511 05:04:52.401525  5307 sgd_solver.cpp:172] Iteration 81700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:04:54.259804  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:05:52.793665  5307 solver.cpp:352] Iteration 81800 (1.65584 iter/s, 60.3923s/100 iter), 158.2/232ep, loss = 3.01624
-I0511 05:05:52.793802  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.86283 (* 1 = 2.86283 loss)
-I0511 05:05:52.793817  5307 sgd_solver.cpp:172] Iteration 81800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:06:54.638144  5307 solver.cpp:352] Iteration 81900 (1.61699 iter/s, 61.8434s/100 iter), 158.3/232ep, loss = 3.15624
-I0511 05:06:54.638219  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.09845 (* 1 = 4.09845 loss)
-I0511 05:06:54.638228  5307 sgd_solver.cpp:172] Iteration 81900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:07:55.882076  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_82000.caffemodel
-I0511 05:07:55.897613  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_82000.solverstate
-I0511 05:07:55.919564  5307 solver.cpp:635] Iteration 82000, Testing net (#0)
-I0511 05:08:36.424590  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:08:36.650754  5307 solver.cpp:747] class AP 1: 0.655134
-I0511 05:08:36.651391  5307 solver.cpp:747] class AP 2: 0.733262
-I0511 05:08:36.658165  5307 solver.cpp:747] class AP 3: 0.534205
-I0511 05:08:36.661967  5307 solver.cpp:747] class AP 4: 0.499522
-I0511 05:08:36.679430  5307 solver.cpp:747] class AP 5: 0.335833
-I0511 05:08:36.679822  5307 solver.cpp:747] class AP 6: 0.722328
-I0511 05:08:36.688561  5307 solver.cpp:747] class AP 7: 0.701715
-I0511 05:08:36.689237  5307 solver.cpp:747] class AP 8: 0.803519
-I0511 05:08:36.707600  5307 solver.cpp:747] class AP 9: 0.419425
-I0511 05:08:36.708217  5307 solver.cpp:747] class AP 10: 0.598135
-I0511 05:08:36.708843  5307 solver.cpp:747] class AP 11: 0.574544
-I0511 05:08:36.709736  5307 solver.cpp:747] class AP 12: 0.72618
-I0511 05:08:36.710386  5307 solver.cpp:747] class AP 13: 0.787962
-I0511 05:08:36.710856  5307 solver.cpp:747] class AP 14: 0.746405
-I0511 05:08:36.762650  5307 solver.cpp:747] class AP 15: 0.723499
-I0511 05:08:36.768735  5307 solver.cpp:747] class AP 16: 0.363718
-I0511 05:08:36.771150  5307 solver.cpp:747] class AP 17: 0.580612
-I0511 05:08:36.771631  5307 solver.cpp:747] class AP 18: 0.586409
-I0511 05:08:36.772302  5307 solver.cpp:747] class AP 19: 0.74642
-I0511 05:08:36.773516  5307 solver.cpp:747] class AP 20: 0.599333
-I0511 05:08:36.773522  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.621908
-I0511 05:08:36.773705  5307 solver.cpp:283] Tests completed in 102.134s
-I0511 05:08:37.404319  5307 solver.cpp:352] Iteration 82000 (0.979107 iter/s, 102.134s/100 iter), 158.5/232ep, loss = 3.12407
-I0511 05:08:37.404367  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05297 (* 1 = 3.05297 loss)
-I0511 05:08:37.404381  5307 sgd_solver.cpp:172] Iteration 82000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:09:38.488523  5307 solver.cpp:352] Iteration 82100 (1.63711 iter/s, 61.0832s/100 iter), 158.7/232ep, loss = 3.17095
-I0511 05:09:38.489747  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8145 (* 1 = 2.8145 loss)
-I0511 05:09:38.489768  5307 sgd_solver.cpp:172] Iteration 82100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:10:40.255704  5307 solver.cpp:352] Iteration 82200 (1.61901 iter/s, 61.7661s/100 iter), 158.9/232ep, loss = 3.03422
-I0511 05:10:40.255859  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23898 (* 1 = 2.23898 loss)
-I0511 05:10:40.256000  5307 sgd_solver.cpp:172] Iteration 82200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:10:51.850184  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:11:40.704710  5307 solver.cpp:352] Iteration 82300 (1.65432 iter/s, 60.448s/100 iter), 159.1/232ep, loss = 3.07507
-I0511 05:11:40.704779  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08429 (* 1 = 3.08429 loss)
-I0511 05:11:40.704788  5307 sgd_solver.cpp:172] Iteration 82300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:12:41.458498  5307 solver.cpp:352] Iteration 82400 (1.64602 iter/s, 60.7528s/100 iter), 159.3/232ep, loss = 3.13112
-I0511 05:12:41.458572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09384 (* 1 = 3.09384 loss)
-I0511 05:12:41.458581  5307 sgd_solver.cpp:172] Iteration 82400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:13:42.341801  5307 solver.cpp:352] Iteration 82500 (1.64251 iter/s, 60.8823s/100 iter), 159.5/232ep, loss = 2.99072
-I0511 05:13:42.341908  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91019 (* 1 = 2.91019 loss)
-I0511 05:13:42.341918  5307 sgd_solver.cpp:172] Iteration 82500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:14:42.496304  5307 solver.cpp:352] Iteration 82600 (1.66241 iter/s, 60.1535s/100 iter), 159.7/232ep, loss = 3.11013
-I0511 05:14:42.496400  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.54618 (* 1 = 2.54618 loss)
-I0511 05:14:42.496408  5307 sgd_solver.cpp:172] Iteration 82600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:15:43.573561  5307 solver.cpp:352] Iteration 82700 (1.6373 iter/s, 61.0762s/100 iter), 159.9/232ep, loss = 3.14549
-I0511 05:15:43.573624  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.76109 (* 1 = 3.76109 loss)
-I0511 05:15:43.573633  5307 sgd_solver.cpp:172] Iteration 82700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:16:06.394397  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:16:43.689371  5307 solver.cpp:352] Iteration 82800 (1.66348 iter/s, 60.1148s/100 iter), 160.1/232ep, loss = 3.16714
-I0511 05:16:43.689472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.97011 (* 1 = 4.97011 loss)
-I0511 05:16:43.689481  5307 sgd_solver.cpp:172] Iteration 82800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:17:43.947782  5307 solver.cpp:352] Iteration 82900 (1.65955 iter/s, 60.2574s/100 iter), 160.3/232ep, loss = 3.14576
-I0511 05:17:43.947850  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03271 (* 1 = 3.03271 loss)
-I0511 05:17:43.947860  5307 sgd_solver.cpp:172] Iteration 82900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:18:44.860479  5307 solver.cpp:352] Iteration 83000 (1.64172 iter/s, 60.9117s/100 iter), 160.5/232ep, loss = 3.07304
-I0511 05:18:44.860572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.58383 (* 1 = 2.58383 loss)
-I0511 05:18:44.860581  5307 sgd_solver.cpp:172] Iteration 83000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:19:45.264725  5307 solver.cpp:352] Iteration 83100 (1.65554 iter/s, 60.4032s/100 iter), 160.7/232ep, loss = 3.1804
-I0511 05:19:45.264848  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89042 (* 1 = 2.89042 loss)
-I0511 05:19:45.264878  5307 sgd_solver.cpp:172] Iteration 83100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:20:46.261476  5307 solver.cpp:352] Iteration 83200 (1.63946 iter/s, 60.9957s/100 iter), 160.9/232ep, loss = 3.1519
-I0511 05:20:46.261567  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90517 (* 1 = 2.90517 loss)
-I0511 05:20:46.261579  5307 sgd_solver.cpp:172] Iteration 83200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:21:19.365172  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:21:47.061985  5307 solver.cpp:352] Iteration 83300 (1.64475 iter/s, 60.7995s/100 iter), 161.1/232ep, loss = 3.04006
-I0511 05:21:47.062106  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.31735 (* 1 = 2.31735 loss)
-I0511 05:21:47.062114  5307 sgd_solver.cpp:172] Iteration 83300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:22:48.098809  5307 solver.cpp:352] Iteration 83400 (1.63838 iter/s, 61.0358s/100 iter), 161.2/232ep, loss = 2.98619
-I0511 05:22:48.098963  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.46974 (* 1 = 2.46974 loss)
-I0511 05:22:48.098987  5307 sgd_solver.cpp:172] Iteration 83400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:23:48.358436  5307 solver.cpp:352] Iteration 83500 (1.65951 iter/s, 60.2586s/100 iter), 161.4/232ep, loss = 3.22008
-I0511 05:23:48.359045  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.2878 (* 1 = 4.2878 loss)
-I0511 05:23:48.359057  5307 sgd_solver.cpp:172] Iteration 83500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:24:48.559589  5307 solver.cpp:352] Iteration 83600 (1.66113 iter/s, 60.2001s/100 iter), 161.6/232ep, loss = 3.22677
-I0511 05:24:48.559682  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00922 (* 1 = 4.00922 loss)
-I0511 05:24:48.559692  5307 sgd_solver.cpp:172] Iteration 83600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:25:49.113479  5307 solver.cpp:352] Iteration 83700 (1.65145 iter/s, 60.5528s/100 iter), 161.8/232ep, loss = 3.1475
-I0511 05:25:49.113591  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92199 (* 1 = 2.92199 loss)
-I0511 05:25:49.113601  5307 sgd_solver.cpp:172] Iteration 83700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:26:32.403017  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:26:49.811486  5307 solver.cpp:352] Iteration 83800 (1.64753 iter/s, 60.697s/100 iter), 162/232ep, loss = 2.86257
-I0511 05:26:49.811573  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.61325 (* 1 = 2.61325 loss)
-I0511 05:26:49.811594  5307 sgd_solver.cpp:172] Iteration 83800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:27:51.098587  5307 solver.cpp:352] Iteration 83900 (1.63169 iter/s, 61.2861s/100 iter), 162.2/232ep, loss = 3.01158
-I0511 05:27:51.098793  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96056 (* 1 = 2.96056 loss)
-I0511 05:27:51.098819  5307 sgd_solver.cpp:172] Iteration 83900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:28:51.532718  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_84000.caffemodel
-I0511 05:28:51.545850  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_84000.solverstate
-I0511 05:28:51.549816  5307 solver.cpp:635] Iteration 84000, Testing net (#0)
-I0511 05:29:32.318837  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:29:32.539342  5307 solver.cpp:747] class AP 1: 0.657814
-I0511 05:29:32.539938  5307 solver.cpp:747] class AP 2: 0.710111
-I0511 05:29:32.546946  5307 solver.cpp:747] class AP 3: 0.538842
-I0511 05:29:32.551157  5307 solver.cpp:747] class AP 4: 0.516887
-I0511 05:29:32.570926  5307 solver.cpp:747] class AP 5: 0.332202
-I0511 05:29:32.571310  5307 solver.cpp:747] class AP 6: 0.720453
-I0511 05:29:32.581048  5307 solver.cpp:747] class AP 7: 0.69799
-I0511 05:29:32.581704  5307 solver.cpp:747] class AP 8: 0.808262
-I0511 05:29:32.599418  5307 solver.cpp:747] class AP 9: 0.417677
-I0511 05:29:32.600200  5307 solver.cpp:747] class AP 10: 0.610413
-I0511 05:29:32.600850  5307 solver.cpp:747] class AP 11: 0.601455
-I0511 05:29:32.601739  5307 solver.cpp:747] class AP 12: 0.726204
-I0511 05:29:32.602188  5307 solver.cpp:747] class AP 13: 0.7924
-I0511 05:29:32.602545  5307 solver.cpp:747] class AP 14: 0.737359
-I0511 05:29:32.656461  5307 solver.cpp:747] class AP 15: 0.727442
-I0511 05:29:32.663388  5307 solver.cpp:747] class AP 16: 0.360737
-I0511 05:29:32.666069  5307 solver.cpp:747] class AP 17: 0.601944
-I0511 05:29:32.666663  5307 solver.cpp:747] class AP 18: 0.595583
-I0511 05:29:32.667361  5307 solver.cpp:747] class AP 19: 0.750944
-I0511 05:29:32.668655  5307 solver.cpp:747] class AP 20: 0.604164
-I0511 05:29:32.668670  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.625444
-I0511 05:29:32.668895  5307 solver.cpp:283] Tests completed in 101.569s
-I0511 05:29:33.352635  5307 solver.cpp:352] Iteration 84000 (0.984556 iter/s, 101.569s/100 iter), 162.4/232ep, loss = 3.15069
-I0511 05:29:33.352704  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23146 (* 1 = 2.23146 loss)
-I0511 05:29:33.352723  5307 sgd_solver.cpp:172] Iteration 84000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:30:34.203102  5307 solver.cpp:352] Iteration 84100 (1.6434 iter/s, 60.8494s/100 iter), 162.6/232ep, loss = 3.1621
-I0511 05:30:34.203176  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85364 (* 1 = 3.85364 loss)
-I0511 05:30:34.203222  5307 sgd_solver.cpp:172] Iteration 84100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:31:38.800949  5307 solver.cpp:352] Iteration 84200 (1.54807 iter/s, 64.5967s/100 iter), 162.8/232ep, loss = 2.92466
-I0511 05:31:38.804613  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.49924 (* 1 = 2.49924 loss)
-I0511 05:31:38.804641  5307 sgd_solver.cpp:172] Iteration 84200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:32:40.326196  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:32:47.100292  5307 solver.cpp:352] Iteration 84300 (1.46417 iter/s, 68.2982s/100 iter), 163/232ep, loss = 3.00704
-I0511 05:32:47.100380  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16228 (* 1 = 3.16228 loss)
-I0511 05:32:47.100400  5307 sgd_solver.cpp:172] Iteration 84300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:33:48.171579  5307 solver.cpp:352] Iteration 84400 (1.63746 iter/s, 61.0702s/100 iter), 163.2/232ep, loss = 3.09693
-I0511 05:33:48.171639  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22999 (* 1 = 3.22999 loss)
-I0511 05:33:48.171648  5307 sgd_solver.cpp:172] Iteration 84400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:34:49.438040  5307 solver.cpp:352] Iteration 84500 (1.63224 iter/s, 61.2654s/100 iter), 163.4/232ep, loss = 3.14147
-I0511 05:34:49.438123  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30156 (* 1 = 3.30156 loss)
-I0511 05:34:49.438133  5307 sgd_solver.cpp:172] Iteration 84500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:35:50.558140  5307 solver.cpp:352] Iteration 84600 (1.63615 iter/s, 61.119s/100 iter), 163.6/232ep, loss = 3.1531
-I0511 05:35:50.558445  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08956 (* 1 = 3.08956 loss)
-I0511 05:35:50.558482  5307 sgd_solver.cpp:172] Iteration 84600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:36:51.441037  5307 solver.cpp:352] Iteration 84700 (1.64252 iter/s, 60.8819s/100 iter), 163.8/232ep, loss = 3.01361
-I0511 05:36:51.442643  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2958 (* 1 = 3.2958 loss)
-I0511 05:36:51.442658  5307 sgd_solver.cpp:172] Iteration 84700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:37:51.773715  5307 solver.cpp:352] Iteration 84800 (1.6575 iter/s, 60.3316s/100 iter), 164/232ep, loss = 3.08956
-I0511 05:37:51.773800  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61149 (* 1 = 3.61149 loss)
-I0511 05:37:51.773808  5307 sgd_solver.cpp:172] Iteration 84800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:37:54.923580  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:38:52.148077  5307 solver.cpp:352] Iteration 84900 (1.65636 iter/s, 60.3733s/100 iter), 164.1/232ep, loss = 2.88072
-I0511 05:38:52.148218  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33891 (* 1 = 3.33891 loss)
-I0511 05:38:52.148241  5307 sgd_solver.cpp:172] Iteration 84900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:39:52.873411  5307 solver.cpp:352] Iteration 85000 (1.64679 iter/s, 60.7243s/100 iter), 164.3/232ep, loss = 3.03843
-I0511 05:39:52.873515  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.0034 (* 1 = 3.0034 loss)
-I0511 05:39:52.873525  5307 sgd_solver.cpp:172] Iteration 85000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:40:53.578524  5307 solver.cpp:352] Iteration 85100 (1.64734 iter/s, 60.7041s/100 iter), 164.5/232ep, loss = 2.99282
-I0511 05:40:53.579010  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.06392 (* 1 = 3.06392 loss)
-I0511 05:40:53.579025  5307 sgd_solver.cpp:172] Iteration 85100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:41:54.347714  5307 solver.cpp:352] Iteration 85200 (1.6456 iter/s, 60.7682s/100 iter), 164.7/232ep, loss = 3.18014
-I0511 05:41:54.347831  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2297 (* 1 = 3.2297 loss)
-I0511 05:41:54.347851  5307 sgd_solver.cpp:172] Iteration 85200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:42:56.362783  5307 solver.cpp:352] Iteration 85300 (1.61254 iter/s, 62.014s/100 iter), 164.9/232ep, loss = 2.98081
-I0511 05:42:56.362850  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.67103 (* 1 = 2.67103 loss)
-I0511 05:42:56.362859  5307 sgd_solver.cpp:172] Iteration 85300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:43:10.316454  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:43:56.733450  5307 solver.cpp:352] Iteration 85400 (1.65646 iter/s, 60.3696s/100 iter), 165.1/232ep, loss = 3.11945
-I0511 05:43:56.733593  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08746 (* 1 = 3.08746 loss)
-I0511 05:43:56.733611  5307 sgd_solver.cpp:172] Iteration 85400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:44:58.045892  5307 solver.cpp:352] Iteration 85500 (1.63102 iter/s, 61.3114s/100 iter), 165.3/232ep, loss = 3.0195
-I0511 05:44:58.045987  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.69612 (* 1 = 2.69612 loss)
-I0511 05:44:58.046008  5307 sgd_solver.cpp:172] Iteration 85500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:45:58.778966  5307 solver.cpp:352] Iteration 85600 (1.64658 iter/s, 60.732s/100 iter), 165.5/232ep, loss = 2.96903
-I0511 05:45:58.781806  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53359 (* 1 = 3.53359 loss)
-I0511 05:45:58.781831  5307 sgd_solver.cpp:172] Iteration 85600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:46:59.483292  5307 solver.cpp:352] Iteration 85700 (1.64736 iter/s, 60.7033s/100 iter), 165.7/232ep, loss = 3.0415
-I0511 05:46:59.483381  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.60919 (* 1 = 2.60919 loss)
-I0511 05:46:59.483388  5307 sgd_solver.cpp:172] Iteration 85700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:47:59.298246  5307 solver.cpp:352] Iteration 85800 (1.67185 iter/s, 59.8139s/100 iter), 165.9/232ep, loss = 2.86475
-I0511 05:47:59.298338  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01744 (* 1 = 3.01744 loss)
-I0511 05:47:59.298348  5307 sgd_solver.cpp:172] Iteration 85800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:48:24.107800  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:48:59.673207  5307 solver.cpp:352] Iteration 85900 (1.65634 iter/s, 60.3739s/100 iter), 166.1/232ep, loss = 2.76809
-I0511 05:48:59.673928  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.84943 (* 1 = 2.84943 loss)
-I0511 05:48:59.674026  5307 sgd_solver.cpp:172] Iteration 85900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:50:00.043298  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_86000.caffemodel
-I0511 05:50:00.075486  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_86000.solverstate
-I0511 05:50:00.080802  5307 solver.cpp:635] Iteration 86000, Testing net (#0)
-I0511 05:50:40.533110  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:50:40.757798  5307 solver.cpp:747] class AP 1: 0.644248
-I0511 05:50:40.758245  5307 solver.cpp:747] class AP 2: 0.7234
-I0511 05:50:40.767001  5307 solver.cpp:747] class AP 3: 0.546652
-I0511 05:50:40.770838  5307 solver.cpp:747] class AP 4: 0.505063
-I0511 05:50:40.789113  5307 solver.cpp:747] class AP 5: 0.336162
-I0511 05:50:40.789417  5307 solver.cpp:747] class AP 6: 0.731788
-I0511 05:50:40.798163  5307 solver.cpp:747] class AP 7: 0.704465
-I0511 05:50:40.798924  5307 solver.cpp:747] class AP 8: 0.799013
-I0511 05:50:40.818701  5307 solver.cpp:747] class AP 9: 0.418467
-I0511 05:50:40.819725  5307 solver.cpp:747] class AP 10: 0.618901
-I0511 05:50:40.820538  5307 solver.cpp:747] class AP 11: 0.581964
-I0511 05:50:40.821631  5307 solver.cpp:747] class AP 12: 0.724035
-I0511 05:50:40.822109  5307 solver.cpp:747] class AP 13: 0.787672
-I0511 05:50:40.822438  5307 solver.cpp:747] class AP 14: 0.737262
-I0511 05:50:40.870316  5307 solver.cpp:747] class AP 15: 0.724478
-I0511 05:50:40.876652  5307 solver.cpp:747] class AP 16: 0.359236
-I0511 05:50:40.879967  5307 solver.cpp:747] class AP 17: 0.581703
-I0511 05:50:40.880720  5307 solver.cpp:747] class AP 18: 0.595236
-I0511 05:50:40.881427  5307 solver.cpp:747] class AP 19: 0.748551
-I0511 05:50:40.882745  5307 solver.cpp:747] class AP 20: 0.608915
-I0511 05:50:40.882756  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.62386
-I0511 05:50:40.882899  5307 solver.cpp:283] Tests completed in 101.208s
-I0511 05:50:41.464840  5307 solver.cpp:352] Iteration 86000 (0.988064 iter/s, 101.208s/100 iter), 166.3/232ep, loss = 2.9692
-I0511 05:50:41.464874  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43173 (* 1 = 3.43173 loss)
-I0511 05:50:41.464881  5307 sgd_solver.cpp:172] Iteration 86000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:51:42.045100  5307 solver.cpp:352] Iteration 86100 (1.65073 iter/s, 60.5792s/100 iter), 166.5/232ep, loss = 3.0519
-I0511 05:51:42.045164  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30511 (* 1 = 3.30511 loss)
-I0511 05:51:42.045173  5307 sgd_solver.cpp:172] Iteration 86100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:52:42.345363  5307 solver.cpp:352] Iteration 86200 (1.6584 iter/s, 60.2992s/100 iter), 166.7/232ep, loss = 3.13449
-I0511 05:52:42.345502  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16417 (* 1 = 3.16417 loss)
-I0511 05:52:42.345513  5307 sgd_solver.cpp:172] Iteration 86200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:53:44.037740  5307 solver.cpp:352] Iteration 86300 (1.62097 iter/s, 61.6913s/100 iter), 166.9/232ep, loss = 3.16945
-I0511 05:53:44.037837  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6172 (* 1 = 2.6172 loss)
-I0511 05:53:44.037858  5307 sgd_solver.cpp:172] Iteration 86300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:54:18.505733  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:54:44.654685  5307 solver.cpp:352] Iteration 86400 (1.64973 iter/s, 60.6159s/100 iter), 167/232ep, loss = 2.95208
-I0511 05:54:44.654716  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.17169 (* 1 = 3.17169 loss)
-I0511 05:54:44.654723  5307 sgd_solver.cpp:172] Iteration 86400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:55:45.467463  5307 solver.cpp:352] Iteration 86500 (1.64442 iter/s, 60.8117s/100 iter), 167.2/232ep, loss = 3.02727
-I0511 05:55:45.467547  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26439 (* 1 = 3.26439 loss)
-I0511 05:55:45.467557  5307 sgd_solver.cpp:172] Iteration 86500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:56:45.926738  5307 solver.cpp:352] Iteration 86600 (1.65403 iter/s, 60.4583s/100 iter), 167.4/232ep, loss = 3.08285
-I0511 05:56:45.926811  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81787 (* 1 = 2.81787 loss)
-I0511 05:56:45.926820  5307 sgd_solver.cpp:172] Iteration 86600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:57:46.451650  5307 solver.cpp:352] Iteration 86700 (1.65224 iter/s, 60.5239s/100 iter), 167.6/232ep, loss = 3.07502
-I0511 05:57:46.451722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93777 (* 1 = 3.93777 loss)
-I0511 05:57:46.451735  5307 sgd_solver.cpp:172] Iteration 86700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:58:47.215143  5307 solver.cpp:352] Iteration 86800 (1.64575 iter/s, 60.7625s/100 iter), 167.8/232ep, loss = 3.04614
-I0511 05:58:47.215207  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41199 (* 1 = 3.41199 loss)
-I0511 05:58:47.215215  5307 sgd_solver.cpp:172] Iteration 86800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:59:32.973482  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:59:48.104275  5307 solver.cpp:352] Iteration 86900 (1.64236 iter/s, 60.8881s/100 iter), 168/232ep, loss = 3.05184
-I0511 05:59:48.104303  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73959 (* 1 = 2.73959 loss)
-I0511 05:59:48.104311  5307 sgd_solver.cpp:172] Iteration 86900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:00:48.318265  5307 solver.cpp:352] Iteration 87000 (1.66077 iter/s, 60.213s/100 iter), 168.2/232ep, loss = 2.91989
-I0511 06:00:48.318336  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71483 (* 1 = 2.71483 loss)
-I0511 06:00:48.318347  5307 sgd_solver.cpp:172] Iteration 87000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:01:48.634670  5307 solver.cpp:352] Iteration 87100 (1.65795 iter/s, 60.3154s/100 iter), 168.4/232ep, loss = 2.80193
-I0511 06:01:48.635248  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.13481 (* 1 = 2.13481 loss)
-I0511 06:01:48.635268  5307 sgd_solver.cpp:172] Iteration 87100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:02:48.851761  5307 solver.cpp:352] Iteration 87200 (1.66069 iter/s, 60.2161s/100 iter), 168.6/232ep, loss = 3.02473
-I0511 06:02:48.851871  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85324 (* 1 = 2.85324 loss)
-I0511 06:02:48.851884  5307 sgd_solver.cpp:172] Iteration 87200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:03:50.542805  5307 solver.cpp:352] Iteration 87300 (1.62101 iter/s, 61.69s/100 iter), 168.8/232ep, loss = 3.01181
-I0511 06:03:50.542874  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.18435 (* 1 = 3.18435 loss)
-I0511 06:03:50.542882  5307 sgd_solver.cpp:172] Iteration 87300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:04:46.543390  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:04:52.260768  5307 solver.cpp:352] Iteration 87400 (1.6203 iter/s, 61.7169s/100 iter), 169/232ep, loss = 3.18492
-I0511 06:04:52.261236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20891 (* 1 = 3.20891 loss)
-I0511 06:04:52.261292  5307 sgd_solver.cpp:172] Iteration 87400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:05:54.376600  5307 solver.cpp:352] Iteration 87500 (1.60992 iter/s, 62.1148s/100 iter), 169.2/232ep, loss = 2.98092
-I0511 06:05:54.376689  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77034 (* 1 = 2.77034 loss)
-I0511 06:05:54.376699  5307 sgd_solver.cpp:172] Iteration 87500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:06:56.324757  5307 solver.cpp:352] Iteration 87600 (1.61428 iter/s, 61.9471s/100 iter), 169.4/232ep, loss = 3.09123
-I0511 06:06:56.324951  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.59935 (* 1 = 2.59935 loss)
-I0511 06:06:56.324972  5307 sgd_solver.cpp:172] Iteration 87600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:07:58.232978  5307 solver.cpp:352] Iteration 87700 (1.61532 iter/s, 61.9072s/100 iter), 169.6/232ep, loss = 2.86781
-I0511 06:07:58.233054  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15377 (* 1 = 3.15377 loss)
-I0511 06:07:58.233119  5307 sgd_solver.cpp:172] Iteration 87700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:09:00.459904  5307 solver.cpp:352] Iteration 87800 (1.60705 iter/s, 62.2258s/100 iter), 169.8/232ep, loss = 3.03055
-I0511 06:09:00.460453  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51731 (* 1 = 2.51731 loss)
-I0511 06:09:00.460474  5307 sgd_solver.cpp:172] Iteration 87800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:10:01.098047  5307 solver.cpp:352] Iteration 87900 (1.64916 iter/s, 60.6371s/100 iter), 169.9/232ep, loss = 2.96504
-I0511 06:10:01.098119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.47514 (* 1 = 2.47514 loss)
-I0511 06:10:01.098127  5307 sgd_solver.cpp:172] Iteration 87900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:10:06.589433  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:11:01.903599  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_88000.caffemodel
-I0511 06:11:01.921385  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_88000.solverstate
-I0511 06:11:01.929335  5307 solver.cpp:635] Iteration 88000, Testing net (#0)
-I0511 06:11:42.505491  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:11:42.742010  5307 solver.cpp:747] class AP 1: 0.660187
-I0511 06:11:42.742581  5307 solver.cpp:747] class AP 2: 0.72923
-I0511 06:11:42.749033  5307 solver.cpp:747] class AP 3: 0.554101
-I0511 06:11:42.752707  5307 solver.cpp:747] class AP 4: 0.490957
-I0511 06:11:42.773998  5307 solver.cpp:747] class AP 5: 0.331025
-I0511 06:11:42.774334  5307 solver.cpp:747] class AP 6: 0.724311
-I0511 06:11:42.783169  5307 solver.cpp:747] class AP 7: 0.705649
-I0511 06:11:42.783768  5307 solver.cpp:747] class AP 8: 0.79094
-I0511 06:11:42.803867  5307 solver.cpp:747] class AP 9: 0.44045
-I0511 06:11:42.804479  5307 solver.cpp:747] class AP 10: 0.621599
-I0511 06:11:42.805268  5307 solver.cpp:747] class AP 11: 0.60273
-I0511 06:11:42.806205  5307 solver.cpp:747] class AP 12: 0.717561
-I0511 06:11:42.806623  5307 solver.cpp:747] class AP 13: 0.788349
-I0511 06:11:42.806979  5307 solver.cpp:747] class AP 14: 0.743536
-I0511 06:11:42.860196  5307 solver.cpp:747] class AP 15: 0.724921
-I0511 06:11:42.868512  5307 solver.cpp:747] class AP 16: 0.353575
-I0511 06:11:42.871130  5307 solver.cpp:747] class AP 17: 0.587968
-I0511 06:11:42.871780  5307 solver.cpp:747] class AP 18: 0.601266
-I0511 06:11:42.872375  5307 solver.cpp:747] class AP 19: 0.739207
-I0511 06:11:42.873889  5307 solver.cpp:747] class AP 20: 0.605896
-I0511 06:11:42.873899  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.625673
-I0511 06:11:42.874081  5307 solver.cpp:283] Tests completed in 101.774s
-I0511 06:11:43.418345  5307 solver.cpp:352] Iteration 88000 (0.982566 iter/s, 101.774s/100 iter), 170.1/232ep, loss = 3.05336
-I0511 06:11:43.418370  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2318 (* 1 = 3.2318 loss)
-I0511 06:11:43.418378  5307 sgd_solver.cpp:172] Iteration 88000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:12:44.214612  5307 solver.cpp:352] Iteration 88100 (1.64487 iter/s, 60.7952s/100 iter), 170.3/232ep, loss = 3.18775
-I0511 06:12:44.214668  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04814 (* 1 = 3.04814 loss)
-I0511 06:12:44.214675  5307 sgd_solver.cpp:172] Iteration 88100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:13:45.426923  5307 solver.cpp:352] Iteration 88200 (1.63369 iter/s, 61.2112s/100 iter), 170.5/232ep, loss = 2.93526
-I0511 06:13:45.427034  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69837 (* 1 = 3.69837 loss)
-I0511 06:13:45.427053  5307 sgd_solver.cpp:172] Iteration 88200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:14:47.090023  5307 solver.cpp:352] Iteration 88300 (1.62174 iter/s, 61.662s/100 iter), 170.7/232ep, loss = 3.13437
-I0511 06:14:47.090090  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11089 (* 1 = 3.11089 loss)
-I0511 06:14:47.090100  5307 sgd_solver.cpp:172] Iteration 88300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:15:48.794766  5307 solver.cpp:352] Iteration 88400 (1.62065 iter/s, 61.7037s/100 iter), 170.9/232ep, loss = 3.03478
-I0511 06:15:48.795208  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87982 (* 1 = 3.87982 loss)
-I0511 06:15:48.795225  5307 sgd_solver.cpp:172] Iteration 88400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:16:05.361198  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:16:50.024565  5307 solver.cpp:352] Iteration 88500 (1.63322 iter/s, 61.2287s/100 iter), 171.1/232ep, loss = 2.96032
-I0511 06:16:50.024686  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.97389 (* 1 = 2.97389 loss)
-I0511 06:16:50.024703  5307 sgd_solver.cpp:172] Iteration 88500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:17:52.224668  5307 solver.cpp:352] Iteration 88600 (1.60774 iter/s, 62.1991s/100 iter), 171.3/232ep, loss = 3.26774
-I0511 06:17:52.225001  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02001 (* 1 = 4.02001 loss)
-I0511 06:17:52.225014  5307 sgd_solver.cpp:172] Iteration 88600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:18:54.006628  5307 solver.cpp:352] Iteration 88700 (1.61862 iter/s, 61.7809s/100 iter), 171.5/232ep, loss = 2.90802
-I0511 06:18:54.006784  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11486 (* 1 = 3.11486 loss)
-I0511 06:18:54.006793  5307 sgd_solver.cpp:172] Iteration 88700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:19:56.394021  5307 solver.cpp:352] Iteration 88800 (1.60292 iter/s, 62.3863s/100 iter), 171.7/232ep, loss = 3.09054
-I0511 06:19:56.394305  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.78126 (* 1 = 2.78126 loss)
-I0511 06:19:56.394325  5307 sgd_solver.cpp:172] Iteration 88800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:20:57.952348  5307 solver.cpp:352] Iteration 88900 (1.6245 iter/s, 61.5573s/100 iter), 171.9/232ep, loss = 2.90461
-I0511 06:20:57.960649  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8149 (* 1 = 2.8149 loss)
-I0511 06:20:57.960680  5307 sgd_solver.cpp:172] Iteration 88900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:21:24.568037  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:21:59.451285  5307 solver.cpp:352] Iteration 89000 (1.62607 iter/s, 61.4979s/100 iter), 172.1/232ep, loss = 2.94432
-I0511 06:21:59.451416  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15219 (* 1 = 3.15219 loss)
-I0511 06:21:59.451439  5307 sgd_solver.cpp:172] Iteration 89000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:23:01.246716  5307 solver.cpp:352] Iteration 89100 (1.61827 iter/s, 61.7944s/100 iter), 172.3/232ep, loss = 3.05031
-I0511 06:23:01.248620  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08868 (* 1 = 3.08868 loss)
-I0511 06:23:01.248646  5307 sgd_solver.cpp:172] Iteration 89100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:24:03.109206  5307 solver.cpp:352] Iteration 89200 (1.61652 iter/s, 61.8614s/100 iter), 172.5/232ep, loss = 2.96362
-I0511 06:24:03.109306  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3566 (* 1 = 3.3566 loss)
-I0511 06:24:03.109318  5307 sgd_solver.cpp:172] Iteration 89200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:25:04.702862  5307 solver.cpp:352] Iteration 89300 (1.62357 iter/s, 61.5926s/100 iter), 172.7/232ep, loss = 3.08537
-I0511 06:25:04.706243  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38645 (* 1 = 3.38645 loss)
-I0511 06:25:04.706276  5307 sgd_solver.cpp:172] Iteration 89300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:26:04.479785  5307 solver.cpp:352] Iteration 89400 (1.67292 iter/s, 59.7759s/100 iter), 172.8/232ep, loss = 3.3297
-I0511 06:26:04.480430  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.15903 (* 1 = 2.15903 loss)
-I0511 06:26:04.482417  5307 sgd_solver.cpp:172] Iteration 89400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:26:41.524902  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:27:05.238521  5307 solver.cpp:352] Iteration 89500 (1.64588 iter/s, 60.7577s/100 iter), 173/232ep, loss = 2.87615
-I0511 06:27:05.238606  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73996 (* 1 = 2.73996 loss)
-I0511 06:27:05.238634  5307 sgd_solver.cpp:172] Iteration 89500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:28:05.023437  5307 solver.cpp:352] Iteration 89600 (1.67269 iter/s, 59.7839s/100 iter), 173.2/232ep, loss = 3.24382
-I0511 06:28:05.023519  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9831 (* 1 = 2.9831 loss)
-I0511 06:28:05.023528  5307 sgd_solver.cpp:172] Iteration 89600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:29:06.104635  5307 solver.cpp:352] Iteration 89700 (1.63719 iter/s, 61.0802s/100 iter), 173.4/232ep, loss = 2.88581
-I0511 06:29:06.104703  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50106 (* 1 = 3.50106 loss)
-I0511 06:29:06.104714  5307 sgd_solver.cpp:172] Iteration 89700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:30:05.908205  5307 solver.cpp:352] Iteration 89800 (1.67217 iter/s, 59.8026s/100 iter), 173.6/232ep, loss = 3.19147
-I0511 06:30:05.908301  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82678 (* 1 = 3.82678 loss)
-I0511 06:30:05.908309  5307 sgd_solver.cpp:172] Iteration 89800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:31:06.240638  5307 solver.cpp:352] Iteration 89900 (1.65751 iter/s, 60.3314s/100 iter), 173.8/232ep, loss = 2.92829
-I0511 06:31:06.244410  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.11302 (* 1 = 2.11302 loss)
-I0511 06:31:06.244437  5307 sgd_solver.cpp:172] Iteration 89900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:31:54.437822  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:32:06.440652  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_90000.caffemodel
-I0511 06:32:06.464042  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_90000.solverstate
-I0511 06:32:06.470664  5307 solver.cpp:635] Iteration 90000, Testing net (#0)
-I0511 06:32:46.600402  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:32:46.823004  5307 solver.cpp:747] class AP 1: 0.652784
-I0511 06:32:46.823493  5307 solver.cpp:747] class AP 2: 0.729538
-I0511 06:32:46.831249  5307 solver.cpp:747] class AP 3: 0.55649
-I0511 06:32:46.834486  5307 solver.cpp:747] class AP 4: 0.508623
-I0511 06:32:46.852995  5307 solver.cpp:747] class AP 5: 0.329417
-I0511 06:32:46.853309  5307 solver.cpp:747] class AP 6: 0.730925
-I0511 06:32:46.861941  5307 solver.cpp:747] class AP 7: 0.694457
-I0511 06:32:46.862560  5307 solver.cpp:747] class AP 8: 0.807829
-I0511 06:32:46.881888  5307 solver.cpp:747] class AP 9: 0.420227
-I0511 06:32:46.882714  5307 solver.cpp:747] class AP 10: 0.632828
-I0511 06:32:46.883391  5307 solver.cpp:747] class AP 11: 0.577087
-I0511 06:32:46.884311  5307 solver.cpp:747] class AP 12: 0.722598
-I0511 06:32:46.884766  5307 solver.cpp:747] class AP 13: 0.793949
-I0511 06:32:46.885109  5307 solver.cpp:747] class AP 14: 0.735033
-I0511 06:32:46.930568  5307 solver.cpp:747] class AP 15: 0.723676
-I0511 06:32:46.937418  5307 solver.cpp:747] class AP 16: 0.361499
-I0511 06:32:46.940719  5307 solver.cpp:747] class AP 17: 0.601625
-I0511 06:32:46.941234  5307 solver.cpp:747] class AP 18: 0.612741
-I0511 06:32:46.941953  5307 solver.cpp:747] class AP 19: 0.744411
-I0511 06:32:46.943197  5307 solver.cpp:747] class AP 20: 0.607792
-I0511 06:32:46.943202  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.627176
-I0511 06:32:46.943362  5307 solver.cpp:283] Tests completed in 100.701s
-I0511 06:32:47.283601  5355 sgd_solver.cpp:50] MultiStep Status: Iteration 90000, step = 2
-I0511 06:32:47.528645  5307 solver.cpp:352] Iteration 90000 (0.993038 iter/s, 100.701s/100 iter), 174/232ep, loss = 3.06175
-I0511 06:32:47.528715  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.88285 (* 1 = 3.88285 loss)
-I0511 06:32:47.528735  5307 sgd_solver.cpp:172] Iteration 90000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:33:48.304985  5307 solver.cpp:352] Iteration 90100 (1.64541 iter/s, 60.7753s/100 iter), 174.2/232ep, loss = 2.96418
-I0511 06:33:48.305083  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5118 (* 1 = 2.5118 loss)
-I0511 06:33:48.305094  5307 sgd_solver.cpp:172] Iteration 90100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:34:49.420004  5307 solver.cpp:352] Iteration 90200 (1.63629 iter/s, 61.114s/100 iter), 174.4/232ep, loss = 2.87708
-I0511 06:34:49.420078  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.96865 (* 1 = 1.96865 loss)
-I0511 06:34:49.420086  5307 sgd_solver.cpp:172] Iteration 90200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:35:50.142431  5307 solver.cpp:352] Iteration 90300 (1.64687 iter/s, 60.7214s/100 iter), 174.6/232ep, loss = 3.06197
-I0511 06:35:50.142529  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.39679 (* 1 = 2.39679 loss)
-I0511 06:35:50.142539  5307 sgd_solver.cpp:172] Iteration 90300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:36:50.662226  5307 solver.cpp:352] Iteration 90400 (1.65238 iter/s, 60.5188s/100 iter), 174.8/232ep, loss = 2.87284
-I0511 06:36:50.662303  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83573 (* 1 = 2.83573 loss)
-I0511 06:36:50.662312  5307 sgd_solver.cpp:172] Iteration 90400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:37:48.705770  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:37:51.686559  5307 solver.cpp:352] Iteration 90500 (1.63872 iter/s, 61.0233s/100 iter), 175/232ep, loss = 3.05013
-I0511 06:37:51.686622  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23287 (* 1 = 2.23287 loss)
-I0511 06:37:51.686633  5307 sgd_solver.cpp:172] Iteration 90500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:38:55.799005  5307 solver.cpp:352] Iteration 90600 (1.55979 iter/s, 64.1114s/100 iter), 175.2/232ep, loss = 3.02569
-I0511 06:38:55.804631  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77855 (* 1 = 2.77855 loss)
-I0511 06:38:55.804669  5307 sgd_solver.cpp:172] Iteration 90600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:40:04.341732  5307 solver.cpp:352] Iteration 90700 (1.45897 iter/s, 68.5415s/100 iter), 175.4/232ep, loss = 3.20002
-I0511 06:40:04.341799  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9114 (* 1 = 2.9114 loss)
-I0511 06:40:04.341811  5307 sgd_solver.cpp:172] Iteration 90700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:41:06.142693  5307 solver.cpp:352] Iteration 90800 (1.61813 iter/s, 61.7999s/100 iter), 175.6/232ep, loss = 2.92238
-I0511 06:41:06.142745  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.49991 (* 1 = 2.49991 loss)
-I0511 06:41:06.142753  5307 sgd_solver.cpp:172] Iteration 90800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:42:06.225172  5307 solver.cpp:352] Iteration 90900 (1.66441 iter/s, 60.0814s/100 iter), 175.7/232ep, loss = 3.06205
-I0511 06:42:06.225240  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38434 (* 1 = 3.38434 loss)
-I0511 06:42:06.225250  5307 sgd_solver.cpp:172] Iteration 90900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:43:06.774168  5307 solver.cpp:352] Iteration 91000 (1.65158 iter/s, 60.548s/100 iter), 175.9/232ep, loss = 2.8425
-I0511 06:43:06.774284  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09239 (* 1 = 3.09239 loss)
-I0511 06:43:06.774297  5307 sgd_solver.cpp:172] Iteration 91000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:43:14.753564  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:44:06.892729  5307 solver.cpp:352] Iteration 91100 (1.66341 iter/s, 60.1176s/100 iter), 176.1/232ep, loss = 2.96822
-I0511 06:44:06.892796  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7695 (* 1 = 2.7695 loss)
-I0511 06:44:06.892803  5307 sgd_solver.cpp:172] Iteration 91100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:45:07.706563  5307 solver.cpp:352] Iteration 91200 (1.64439 iter/s, 60.8128s/100 iter), 176.3/232ep, loss = 3.08933
-I0511 06:45:07.706674  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11674 (* 1 = 3.11674 loss)
-I0511 06:45:07.706684  5307 sgd_solver.cpp:172] Iteration 91200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:46:08.655390  5307 solver.cpp:352] Iteration 91300 (1.64075 iter/s, 60.9478s/100 iter), 176.5/232ep, loss = 2.94552
-I0511 06:46:08.655488  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26752 (* 1 = 3.26752 loss)
-I0511 06:46:08.655509  5307 sgd_solver.cpp:172] Iteration 91300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:47:09.975742  5307 solver.cpp:352] Iteration 91400 (1.63081 iter/s, 61.3193s/100 iter), 176.7/232ep, loss = 2.98143
-I0511 06:47:09.975798  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4964 (* 1 = 3.4964 loss)
-I0511 06:47:09.975806  5307 sgd_solver.cpp:172] Iteration 91400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:48:10.877688  5307 solver.cpp:352] Iteration 91500 (1.64201 iter/s, 60.9009s/100 iter), 176.9/232ep, loss = 2.77348
-I0511 06:48:10.877744  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87046 (* 1 = 2.87046 loss)
-I0511 06:48:10.877751  5307 sgd_solver.cpp:172] Iteration 91500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:48:28.336748  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:49:11.077268  5307 solver.cpp:352] Iteration 91600 (1.66117 iter/s, 60.1986s/100 iter), 177.1/232ep, loss = 2.87366
-I0511 06:49:11.077348  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23284 (* 1 = 2.23284 loss)
-I0511 06:49:11.077368  5307 sgd_solver.cpp:172] Iteration 91600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:50:12.198155  5307 solver.cpp:352] Iteration 91700 (1.63613 iter/s, 61.1199s/100 iter), 177.3/232ep, loss = 3.02639
-I0511 06:50:12.198213  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30429 (* 1 = 3.30429 loss)
-I0511 06:50:12.198221  5307 sgd_solver.cpp:172] Iteration 91700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:51:12.915246  5307 solver.cpp:352] Iteration 91800 (1.64701 iter/s, 60.7161s/100 iter), 177.5/232ep, loss = 3.15878
-I0511 06:51:12.916009  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44774 (* 1 = 3.44774 loss)
-I0511 06:51:12.916018  5307 sgd_solver.cpp:172] Iteration 91800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:52:13.195530  5307 solver.cpp:352] Iteration 91900 (1.65895 iter/s, 60.2793s/100 iter), 177.7/232ep, loss = 2.94377
-I0511 06:52:13.195955  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51839 (* 1 = 2.51839 loss)
-I0511 06:52:13.195963  5307 sgd_solver.cpp:172] Iteration 91900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:53:13.970113  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_92000.caffemodel
-I0511 06:53:13.984675  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_92000.solverstate
-I0511 06:53:13.989930  5307 solver.cpp:635] Iteration 92000, Testing net (#0)
-I0511 06:53:54.539722  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:53:54.751148  5307 solver.cpp:747] class AP 1: 0.6524
-I0511 06:53:54.751955  5307 solver.cpp:747] class AP 2: 0.72956
-I0511 06:53:54.760458  5307 solver.cpp:747] class AP 3: 0.558785
-I0511 06:53:54.765637  5307 solver.cpp:747] class AP 4: 0.518879
-I0511 06:53:54.789904  5307 solver.cpp:747] class AP 5: 0.337961
-I0511 06:53:54.790262  5307 solver.cpp:747] class AP 6: 0.732748
-I0511 06:53:54.799666  5307 solver.cpp:747] class AP 7: 0.701902
-I0511 06:53:54.800206  5307 solver.cpp:747] class AP 8: 0.804724
-I0511 06:53:54.820778  5307 solver.cpp:747] class AP 9: 0.430797
-I0511 06:53:54.821504  5307 solver.cpp:747] class AP 10: 0.621646
-I0511 06:53:54.822299  5307 solver.cpp:747] class AP 11: 0.589305
-I0511 06:53:54.823139  5307 solver.cpp:747] class AP 12: 0.718752
-I0511 06:53:54.823617  5307 solver.cpp:747] class AP 13: 0.795582
-I0511 06:53:54.823979  5307 solver.cpp:747] class AP 14: 0.749374
-I0511 06:53:54.879411  5307 solver.cpp:747] class AP 15: 0.726554
-I0511 06:53:54.886247  5307 solver.cpp:747] class AP 16: 0.357537
-I0511 06:53:54.888780  5307 solver.cpp:747] class AP 17: 0.593442
-I0511 06:53:54.889374  5307 solver.cpp:747] class AP 18: 0.619407
-I0511 06:53:54.890004  5307 solver.cpp:747] class AP 19: 0.7472
-I0511 06:53:54.891474  5307 solver.cpp:747] class AP 20: 0.609963
-I0511 06:53:54.891482  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.629826
-I0511 06:53:54.891830  5307 solver.cpp:283] Tests completed in 101.695s
-I0511 06:53:55.485334  5307 solver.cpp:352] Iteration 92000 (0.983336 iter/s, 101.695s/100 iter), 177.9/232ep, loss = 2.87393
-I0511 06:53:55.485361  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63063 (* 1 = 2.63063 loss)
-I0511 06:53:55.485369  5307 sgd_solver.cpp:172] Iteration 92000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:54:23.681706  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:54:55.911607  5307 solver.cpp:352] Iteration 92100 (1.65494 iter/s, 60.4252s/100 iter), 178.1/232ep, loss = 2.93419
-I0511 06:54:55.911684  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47136 (* 1 = 3.47136 loss)
-I0511 06:54:55.911695  5307 sgd_solver.cpp:172] Iteration 92100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:55:56.659097  5307 solver.cpp:352] Iteration 92200 (1.64619 iter/s, 60.7464s/100 iter), 178.3/232ep, loss = 3.30948
-I0511 06:55:56.659168  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.13782 (* 1 = 4.13782 loss)
-I0511 06:55:56.659178  5307 sgd_solver.cpp:172] Iteration 92200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:56:56.856077  5307 solver.cpp:352] Iteration 92300 (1.66124 iter/s, 60.1959s/100 iter), 178.5/232ep, loss = 2.98758
-I0511 06:56:56.856153  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08614 (* 1 = 3.08614 loss)
-I0511 06:56:56.856160  5307 sgd_solver.cpp:172] Iteration 92300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:57:57.516736  5307 solver.cpp:352] Iteration 92400 (1.64854 iter/s, 60.6596s/100 iter), 178.6/232ep, loss = 3.00875
-I0511 06:57:57.516957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.93811 (* 1 = 2.93811 loss)
-I0511 06:57:57.516968  5307 sgd_solver.cpp:172] Iteration 92400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:58:58.128021  5307 solver.cpp:352] Iteration 92500 (1.64989 iter/s, 60.6103s/100 iter), 178.8/232ep, loss = 3.06919
-I0511 06:58:58.128134  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.60397 (* 1 = 3.60397 loss)
-I0511 06:58:58.128156  5307 sgd_solver.cpp:172] Iteration 92500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:59:37.560575  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:59:58.865466  5307 solver.cpp:352] Iteration 92600 (1.64646 iter/s, 60.7364s/100 iter), 179/232ep, loss = 2.9328
-I0511 06:59:58.865562  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.717 (* 1 = 2.717 loss)
-I0511 06:59:58.865584  5307 sgd_solver.cpp:172] Iteration 92600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:00:59.504809  5307 solver.cpp:352] Iteration 92700 (1.64912 iter/s, 60.6383s/100 iter), 179.2/232ep, loss = 3.177
-I0511 07:00:59.504895  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27882 (* 1 = 3.27882 loss)
-I0511 07:00:59.504904  5307 sgd_solver.cpp:172] Iteration 92700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:01:59.805862  5307 solver.cpp:352] Iteration 92800 (1.65837 iter/s, 60.3s/100 iter), 179.4/232ep, loss = 3.05714
-I0511 07:01:59.805963  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5165 (* 1 = 2.5165 loss)
-I0511 07:01:59.806018  5307 sgd_solver.cpp:172] Iteration 92800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:03:00.626083  5307 solver.cpp:352] Iteration 92900 (1.64422 iter/s, 60.8192s/100 iter), 179.6/232ep, loss = 2.963
-I0511 07:03:00.626170  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00387 (* 1 = 3.00387 loss)
-I0511 07:03:00.626179  5307 sgd_solver.cpp:172] Iteration 92900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:04:01.318279  5307 solver.cpp:352] Iteration 93000 (1.64769 iter/s, 60.6912s/100 iter), 179.8/232ep, loss = 2.90055
-I0511 07:04:01.320188  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65029 (* 1 = 2.65029 loss)
-I0511 07:04:01.320212  5307 sgd_solver.cpp:172] Iteration 93000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:04:50.817641  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:05:02.257743  5307 solver.cpp:352] Iteration 93100 (1.641 iter/s, 60.9384s/100 iter), 180/232ep, loss = 3.23961
-I0511 07:05:02.257766  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14786 (* 1 = 3.14786 loss)
-I0511 07:05:02.257772  5307 sgd_solver.cpp:172] Iteration 93100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:06:03.299690  5307 solver.cpp:352] Iteration 93200 (1.63825 iter/s, 61.0409s/100 iter), 180.2/232ep, loss = 2.91292
-I0511 07:06:03.299780  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25663 (* 1 = 3.25663 loss)
-I0511 07:06:03.299795  5307 sgd_solver.cpp:172] Iteration 93200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:07:04.007691  5307 solver.cpp:352] Iteration 93300 (1.64726 iter/s, 60.7069s/100 iter), 180.4/232ep, loss = 2.8366
-I0511 07:07:04.007822  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.76125 (* 1 = 2.76125 loss)
-I0511 07:07:04.007833  5307 sgd_solver.cpp:172] Iteration 93300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:08:05.674250  5307 solver.cpp:352] Iteration 93400 (1.62165 iter/s, 61.6655s/100 iter), 180.6/232ep, loss = 2.9875
-I0511 07:08:05.674376  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00216 (* 1 = 3.00216 loss)
-I0511 07:08:05.674407  5307 sgd_solver.cpp:172] Iteration 93400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:09:06.510345  5307 solver.cpp:352] Iteration 93500 (1.64379 iter/s, 60.835s/100 iter), 180.8/232ep, loss = 2.91242
-I0511 07:09:06.510448  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26614 (* 1 = 3.26614 loss)
-I0511 07:09:06.510457  5307 sgd_solver.cpp:172] Iteration 93500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:10:07.199136  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:10:07.692203  5307 solver.cpp:352] Iteration 93600 (1.6345 iter/s, 61.1808s/100 iter), 181/232ep, loss = 2.92701
-I0511 07:10:07.692236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92543 (* 1 = 2.92543 loss)
-I0511 07:10:07.692245  5307 sgd_solver.cpp:172] Iteration 93600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:11:08.276374  5307 solver.cpp:352] Iteration 93700 (1.65063 iter/s, 60.5831s/100 iter), 181.2/232ep, loss = 2.97391
-I0511 07:11:08.276445  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.84651 (* 1 = 2.84651 loss)
-I0511 07:11:08.276464  5307 sgd_solver.cpp:172] Iteration 93700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:12:09.098157  5307 solver.cpp:352] Iteration 93800 (1.64418 iter/s, 60.8207s/100 iter), 181.4/232ep, loss = 3.05575
-I0511 07:12:09.098242  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10997 (* 1 = 3.10997 loss)
-I0511 07:12:09.098258  5307 sgd_solver.cpp:172] Iteration 93800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:13:09.135836  5307 solver.cpp:352] Iteration 93900 (1.66565 iter/s, 60.0366s/100 iter), 181.5/232ep, loss = 2.79365
-I0511 07:13:09.135907  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.80829 (* 1 = 2.80829 loss)
-I0511 07:13:09.135917  5307 sgd_solver.cpp:172] Iteration 93900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:14:09.049873  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_94000.caffemodel
-I0511 07:14:09.067451  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_94000.solverstate
-I0511 07:14:09.073073  5307 solver.cpp:635] Iteration 94000, Testing net (#0)
-I0511 07:14:49.386508  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:14:49.603636  5307 solver.cpp:747] class AP 1: 0.653359
-I0511 07:14:49.604197  5307 solver.cpp:747] class AP 2: 0.73238
-I0511 07:14:49.610410  5307 solver.cpp:747] class AP 3: 0.551173
-I0511 07:14:49.614192  5307 solver.cpp:747] class AP 4: 0.511015
-I0511 07:14:49.632762  5307 solver.cpp:747] class AP 5: 0.343197
-I0511 07:14:49.633168  5307 solver.cpp:747] class AP 6: 0.732664
-I0511 07:14:49.642177  5307 solver.cpp:747] class AP 7: 0.703703
-I0511 07:14:49.642736  5307 solver.cpp:747] class AP 8: 0.806241
-I0511 07:14:49.660897  5307 solver.cpp:747] class AP 9: 0.430877
-I0511 07:14:49.661641  5307 solver.cpp:747] class AP 10: 0.626487
-I0511 07:14:49.662276  5307 solver.cpp:747] class AP 11: 0.582946
-I0511 07:14:49.663098  5307 solver.cpp:747] class AP 12: 0.72
-I0511 07:14:49.663549  5307 solver.cpp:747] class AP 13: 0.795215
-I0511 07:14:49.663914  5307 solver.cpp:747] class AP 14: 0.756727
-I0511 07:14:49.716935  5307 solver.cpp:747] class AP 15: 0.725841
-I0511 07:14:49.723117  5307 solver.cpp:747] class AP 16: 0.352762
-I0511 07:14:49.725605  5307 solver.cpp:747] class AP 17: 0.594063
-I0511 07:14:49.726192  5307 solver.cpp:747] class AP 18: 0.607985
-I0511 07:14:49.726879  5307 solver.cpp:747] class AP 19: 0.752284
-I0511 07:14:49.728354  5307 solver.cpp:747] class AP 20: 0.612051
-I0511 07:14:49.728365  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.629548
-I0511 07:14:49.728660  5307 solver.cpp:283] Tests completed in 100.591s
-I0511 07:14:50.404428  5307 solver.cpp:352] Iteration 94000 (0.994125 iter/s, 100.591s/100 iter), 181.7/232ep, loss = 3.00078
-I0511 07:14:50.404458  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03151 (* 1 = 3.03151 loss)
-I0511 07:14:50.404465  5307 sgd_solver.cpp:172] Iteration 94000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:15:51.333745  5307 solver.cpp:352] Iteration 94100 (1.64128 iter/s, 60.9282s/100 iter), 181.9/232ep, loss = 3.00365
-I0511 07:15:51.333849  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.65699 (* 1 = 1.65699 loss)
-I0511 07:15:51.333858  5307 sgd_solver.cpp:172] Iteration 94100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:16:00.422384  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:16:52.949550  5307 solver.cpp:352] Iteration 94200 (1.62299 iter/s, 61.6147s/100 iter), 182.1/232ep, loss = 2.99714
-I0511 07:16:52.949631  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91074 (* 1 = 2.91074 loss)
-I0511 07:16:52.949641  5307 sgd_solver.cpp:172] Iteration 94200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:17:53.041024  5307 solver.cpp:352] Iteration 94300 (1.66416 iter/s, 60.0903s/100 iter), 182.3/232ep, loss = 2.97779
-I0511 07:17:53.041158  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01335 (* 1 = 3.01335 loss)
-I0511 07:17:53.041172  5307 sgd_solver.cpp:172] Iteration 94300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:18:53.639108  5307 solver.cpp:352] Iteration 94400 (1.65025 iter/s, 60.597s/100 iter), 182.5/232ep, loss = 2.9533
-I0511 07:18:53.639197  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15735 (* 1 = 3.15735 loss)
-I0511 07:18:53.639212  5307 sgd_solver.cpp:172] Iteration 94400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:19:54.755478  5307 solver.cpp:352] Iteration 94500 (1.63625 iter/s, 61.1153s/100 iter), 182.7/232ep, loss = 3.05215
-I0511 07:19:54.755560  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.78547 (* 1 = 1.78547 loss)
-I0511 07:19:54.755575  5307 sgd_solver.cpp:172] Iteration 94500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:20:55.250944  5307 solver.cpp:352] Iteration 94600 (1.65305 iter/s, 60.4943s/100 iter), 182.9/232ep, loss = 2.91921
-I0511 07:20:55.251121  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6026 (* 1 = 2.6026 loss)
-I0511 07:20:55.251130  5307 sgd_solver.cpp:172] Iteration 94600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:21:15.316819  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:21:55.952729  5307 solver.cpp:352] Iteration 94700 (1.64743 iter/s, 60.7007s/100 iter), 183.1/232ep, loss = 2.97533
-I0511 07:21:55.958325  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.53738 (* 1 = 2.53738 loss)
-I0511 07:21:55.958407  5307 sgd_solver.cpp:172] Iteration 94700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:22:56.539149  5307 solver.cpp:352] Iteration 94800 (1.65056 iter/s, 60.5853s/100 iter), 183.3/232ep, loss = 2.88534
-I0511 07:22:56.551717  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51739 (* 1 = 2.51739 loss)
-I0511 07:22:56.551738  5307 sgd_solver.cpp:172] Iteration 94800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:23:57.239343  5307 solver.cpp:352] Iteration 94900 (1.64747 iter/s, 60.6991s/100 iter), 183.5/232ep, loss = 3.07979
-I0511 07:23:57.239454  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.56482 (* 1 = 2.56482 loss)
-I0511 07:23:57.239470  5307 sgd_solver.cpp:172] Iteration 94900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:24:57.647054  5307 solver.cpp:352] Iteration 95000 (1.65545 iter/s, 60.4066s/100 iter), 183.7/232ep, loss = 2.9111
-I0511 07:24:57.647584  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51917 (* 1 = 2.51917 loss)
-I0511 07:24:57.647593  5307 sgd_solver.cpp:172] Iteration 95000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:25:58.006286  5307 solver.cpp:352] Iteration 95100 (1.65678 iter/s, 60.3581s/100 iter), 183.9/232ep, loss = 2.91394
-I0511 07:25:58.006376  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.16777 (* 1 = 2.16777 loss)
-I0511 07:25:58.006386  5307 sgd_solver.cpp:172] Iteration 95100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:26:29.239646  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:26:58.534366  5307 solver.cpp:352] Iteration 95200 (1.65216 iter/s, 60.527s/100 iter), 184.1/232ep, loss = 2.99329
-I0511 07:26:58.534436  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.20944 (* 1 = 4.20944 loss)
-I0511 07:26:58.534467  5307 sgd_solver.cpp:172] Iteration 95200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:28:00.180697  5307 solver.cpp:352] Iteration 95300 (1.62219 iter/s, 61.6452s/100 iter), 184.3/232ep, loss = 3.05895
-I0511 07:28:00.180809  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.2327 (* 1 = 2.2327 loss)
-I0511 07:28:00.180820  5307 sgd_solver.cpp:172] Iteration 95300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:29:01.828652  5307 solver.cpp:352] Iteration 95400 (1.62214 iter/s, 61.6468s/100 iter), 184.4/232ep, loss = 3.03341
-I0511 07:29:01.828793  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.27634 (* 1 = 2.27634 loss)
-I0511 07:29:01.828820  5307 sgd_solver.cpp:172] Iteration 95400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:30:02.710813  5307 solver.cpp:352] Iteration 95500 (1.64255 iter/s, 60.881s/100 iter), 184.6/232ep, loss = 2.95368
-I0511 07:30:02.710907  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.47872 (* 1 = 2.47872 loss)
-I0511 07:30:02.710917  5307 sgd_solver.cpp:172] Iteration 95500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:31:03.373091  5307 solver.cpp:352] Iteration 95600 (1.6485 iter/s, 60.6612s/100 iter), 184.8/232ep, loss = 3.00084
-I0511 07:31:03.373272  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63916 (* 1 = 2.63916 loss)
-I0511 07:31:03.373291  5307 sgd_solver.cpp:172] Iteration 95600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:31:44.715602  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:32:04.248646  5307 solver.cpp:352] Iteration 95700 (1.64273 iter/s, 60.8744s/100 iter), 185/232ep, loss = 3.05273
-I0511 07:32:04.248762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04961 (* 1 = 3.04961 loss)
-I0511 07:32:04.248780  5307 sgd_solver.cpp:172] Iteration 95700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:33:04.989846  5307 solver.cpp:352] Iteration 95800 (1.64636 iter/s, 60.7401s/100 iter), 185.2/232ep, loss = 3.06251
-I0511 07:33:04.989917  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85397 (* 1 = 2.85397 loss)
-I0511 07:33:04.989924  5307 sgd_solver.cpp:172] Iteration 95800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:34:04.922678  5307 solver.cpp:352] Iteration 95900 (1.66857 iter/s, 59.9317s/100 iter), 185.4/232ep, loss = 3.11436
-I0511 07:34:04.922744  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51926 (* 1 = 2.51926 loss)
-I0511 07:34:04.922751  5307 sgd_solver.cpp:172] Iteration 95900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:35:04.914889  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_96000.caffemodel
-I0511 07:35:04.936225  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_96000.solverstate
-I0511 07:35:04.941499  5307 solver.cpp:635] Iteration 96000, Testing net (#0)
-I0511 07:35:23.672327  5352 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0511 07:35:45.077711  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:35:45.308502  5307 solver.cpp:747] class AP 1: 0.650321
-I0511 07:35:45.309023  5307 solver.cpp:747] class AP 2: 0.734017
-I0511 07:35:45.315362  5307 solver.cpp:747] class AP 3: 0.555505
-I0511 07:35:45.319352  5307 solver.cpp:747] class AP 4: 0.501021
-I0511 07:35:45.337565  5307 solver.cpp:747] class AP 5: 0.344569
-I0511 07:35:45.337915  5307 solver.cpp:747] class AP 6: 0.733044
-I0511 07:35:45.346527  5307 solver.cpp:747] class AP 7: 0.704343
-I0511 07:35:45.347060  5307 solver.cpp:747] class AP 8: 0.813259
-I0511 07:35:45.364531  5307 solver.cpp:747] class AP 9: 0.425829
-I0511 07:35:45.365254  5307 solver.cpp:747] class AP 10: 0.624562
-I0511 07:35:45.365865  5307 solver.cpp:747] class AP 11: 0.58426
-I0511 07:35:45.366700  5307 solver.cpp:747] class AP 12: 0.722605
-I0511 07:35:45.367126  5307 solver.cpp:747] class AP 13: 0.789451
-I0511 07:35:45.367465  5307 solver.cpp:747] class AP 14: 0.745061
-I0511 07:35:45.415539  5307 solver.cpp:747] class AP 15: 0.725725
-I0511 07:35:45.421653  5307 solver.cpp:747] class AP 16: 0.354737
-I0511 07:35:45.424113  5307 solver.cpp:747] class AP 17: 0.597748
-I0511 07:35:45.424669  5307 solver.cpp:747] class AP 18: 0.618047
-I0511 07:35:45.425331  5307 solver.cpp:747] class AP 19: 0.744493
-I0511 07:35:45.426846  5307 solver.cpp:747] class AP 20: 0.608665
-I0511 07:35:45.426854  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.628863
-I0511 07:35:45.427047  5307 solver.cpp:283] Tests completed in 100.503s
-I0511 07:35:45.994454  5307 solver.cpp:352] Iteration 96000 (0.995 iter/s, 100.503s/100 iter), 185.6/232ep, loss = 2.9123
-I0511 07:35:45.994532  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39141 (* 1 = 3.39141 loss)
-I0511 07:35:45.994559  5307 sgd_solver.cpp:172] Iteration 96000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:36:46.702077  5307 solver.cpp:352] Iteration 96100 (1.64727 iter/s, 60.7065s/100 iter), 185.8/232ep, loss = 3.05719
-I0511 07:36:46.702152  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16969 (* 1 = 3.16969 loss)
-I0511 07:36:46.702162  5307 sgd_solver.cpp:172] Iteration 96100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:37:38.127743  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:37:47.506345  5307 solver.cpp:352] Iteration 96200 (1.64465 iter/s, 60.8031s/100 iter), 186/232ep, loss = 2.96958
-I0511 07:37:47.506371  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.18929 (* 1 = 3.18929 loss)
-I0511 07:37:47.506381  5307 sgd_solver.cpp:172] Iteration 96200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:38:47.357182  5307 solver.cpp:352] Iteration 96300 (1.67085 iter/s, 59.8498s/100 iter), 186.2/232ep, loss = 3.00744
-I0511 07:38:47.357235  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.54607 (* 1 = 2.54607 loss)
-I0511 07:38:47.357244  5307 sgd_solver.cpp:172] Iteration 96300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:39:46.934804  5307 solver.cpp:352] Iteration 96400 (1.67851 iter/s, 59.5765s/100 iter), 186.4/232ep, loss = 2.90113
-I0511 07:39:46.934885  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7434 (* 1 = 2.7434 loss)
-I0511 07:39:46.934895  5307 sgd_solver.cpp:172] Iteration 96400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:40:46.563388  5307 solver.cpp:352] Iteration 96500 (1.67708 iter/s, 59.6275s/100 iter), 186.6/232ep, loss = 3.30584
-I0511 07:40:46.563503  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.42639 (* 1 = 3.42639 loss)
-I0511 07:40:46.563514  5307 sgd_solver.cpp:172] Iteration 96500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:41:46.848609  5307 solver.cpp:352] Iteration 96600 (1.65881 iter/s, 60.2841s/100 iter), 186.8/232ep, loss = 2.93792
-I0511 07:41:46.848676  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63076 (* 1 = 2.63076 loss)
-I0511 07:41:46.848685  5307 sgd_solver.cpp:172] Iteration 96600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:42:47.210800  5307 solver.cpp:352] Iteration 96700 (1.6567 iter/s, 60.3611s/100 iter), 187/232ep, loss = 3.05603
-I0511 07:42:47.212236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73215 (* 1 = 3.73215 loss)
-I0511 07:42:47.212250  5307 sgd_solver.cpp:172] Iteration 96700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:42:47.932543  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:43:47.787328  5307 solver.cpp:352] Iteration 96800 (1.65083 iter/s, 60.5754s/100 iter), 187.2/232ep, loss = 3.03419
-I0511 07:43:47.787413  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96915 (* 1 = 2.96915 loss)
-I0511 07:43:47.787425  5307 sgd_solver.cpp:172] Iteration 96800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:44:49.099545  5307 solver.cpp:352] Iteration 96900 (1.63103 iter/s, 61.3111s/100 iter), 187.3/232ep, loss = 3.09535
-I0511 07:44:49.099644  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93823 (* 1 = 3.93823 loss)
-I0511 07:44:49.099663  5307 sgd_solver.cpp:172] Iteration 96900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:45:52.576695  5307 solver.cpp:352] Iteration 97000 (1.5754 iter/s, 63.476s/100 iter), 187.5/232ep, loss = 2.80578
-I0511 07:45:52.578472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.33847 (* 1 = 2.33847 loss)
-I0511 07:45:52.578514  5307 sgd_solver.cpp:172] Iteration 97000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:47:00.539968  5307 solver.cpp:352] Iteration 97100 (1.47141 iter/s, 67.962s/100 iter), 187.7/232ep, loss = 2.9538
-I0511 07:47:00.540072  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27623 (* 1 = 3.27623 loss)
-I0511 07:47:00.540093  5307 sgd_solver.cpp:172] Iteration 97100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:48:01.684559  5307 solver.cpp:352] Iteration 97200 (1.6355 iter/s, 61.1434s/100 iter), 187.9/232ep, loss = 2.9581
-I0511 07:48:01.684702  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46043 (* 1 = 3.46043 loss)
-I0511 07:48:01.684712  5307 sgd_solver.cpp:172] Iteration 97200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:48:13.198102  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:49:01.896059  5307 solver.cpp:352] Iteration 97300 (1.66084 iter/s, 60.2104s/100 iter), 188.1/232ep, loss = 3.00296
-I0511 07:49:01.899176  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.27139 (* 1 = 2.27139 loss)
-I0511 07:49:01.899194  5307 sgd_solver.cpp:172] Iteration 97300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:50:02.053539  5307 solver.cpp:352] Iteration 97400 (1.66234 iter/s, 60.1563s/100 iter), 188.3/232ep, loss = 2.91776
-I0511 07:50:02.054003  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90872 (* 1 = 2.90872 loss)
-I0511 07:50:02.054015  5307 sgd_solver.cpp:172] Iteration 97400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:51:02.951967  5307 solver.cpp:352] Iteration 97500 (1.64211 iter/s, 60.8973s/100 iter), 188.5/232ep, loss = 2.875
-I0511 07:51:02.952033  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22074 (* 1 = 3.22074 loss)
-I0511 07:51:02.952041  5307 sgd_solver.cpp:172] Iteration 97500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:52:04.163118  5307 solver.cpp:352] Iteration 97600 (1.63372 iter/s, 61.21s/100 iter), 188.7/232ep, loss = 2.90709
-I0511 07:52:04.163497  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.6202 (* 1 = 3.6202 loss)
-I0511 07:52:04.163509  5307 sgd_solver.cpp:172] Iteration 97600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:53:05.139300  5307 solver.cpp:352] Iteration 97700 (1.64001 iter/s, 60.9751s/100 iter), 188.9/232ep, loss = 3.0651
-I0511 07:53:05.139398  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82895 (* 1 = 3.82895 loss)
-I0511 07:53:05.139415  5307 sgd_solver.cpp:172] Iteration 97700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:53:27.015391  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:54:05.430426  5307 solver.cpp:352] Iteration 97800 (1.65865 iter/s, 60.29s/100 iter), 189.1/232ep, loss = 2.91936
-I0511 07:54:05.430500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72138 (* 1 = 3.72138 loss)
-I0511 07:54:05.430510  5307 sgd_solver.cpp:172] Iteration 97800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:55:06.594501  5307 solver.cpp:352] Iteration 97900 (1.63498 iter/s, 61.163s/100 iter), 189.3/232ep, loss = 3.04614
-I0511 07:55:06.594552  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.68441 (* 1 = 2.68441 loss)
-I0511 07:55:06.594559  5307 sgd_solver.cpp:172] Iteration 97900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:56:06.258683  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_98000.caffemodel
-I0511 07:56:06.280103  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_98000.solverstate
-I0511 07:56:06.286790  5307 solver.cpp:635] Iteration 98000, Testing net (#0)
-I0511 07:56:46.613548  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:56:46.815506  5307 solver.cpp:747] class AP 1: 0.654648
-I0511 07:56:46.816174  5307 solver.cpp:747] class AP 2: 0.729718
-I0511 07:56:46.824645  5307 solver.cpp:747] class AP 3: 0.556767
-I0511 07:56:46.830163  5307 solver.cpp:747] class AP 4: 0.509277
-I0511 07:56:46.853922  5307 solver.cpp:747] class AP 5: 0.343129
-I0511 07:56:46.854557  5307 solver.cpp:747] class AP 6: 0.733831
-I0511 07:56:46.863710  5307 solver.cpp:747] class AP 7: 0.699716
-I0511 07:56:46.864267  5307 solver.cpp:747] class AP 8: 0.818443
-I0511 07:56:46.883057  5307 solver.cpp:747] class AP 9: 0.426093
-I0511 07:56:46.883762  5307 solver.cpp:747] class AP 10: 0.628663
-I0511 07:56:46.884393  5307 solver.cpp:747] class AP 11: 0.58388
-I0511 07:56:46.885224  5307 solver.cpp:747] class AP 12: 0.71764
-I0511 07:56:46.885659  5307 solver.cpp:747] class AP 13: 0.794358
-I0511 07:56:46.885994  5307 solver.cpp:747] class AP 14: 0.74868
-I0511 07:56:46.938817  5307 solver.cpp:747] class AP 15: 0.724842
-I0511 07:56:46.946049  5307 solver.cpp:747] class AP 16: 0.359878
-I0511 07:56:46.948588  5307 solver.cpp:747] class AP 17: 0.593851
-I0511 07:56:46.949234  5307 solver.cpp:747] class AP 18: 0.609637
-I0511 07:56:46.950158  5307 solver.cpp:747] class AP 19: 0.747296
-I0511 07:56:46.951679  5307 solver.cpp:747] class AP 20: 0.611734
-I0511 07:56:46.951694  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.629604
-I0511 07:56:46.951939  5307 solver.cpp:283] Tests completed in 100.356s
-I0511 07:56:47.491531  5307 solver.cpp:352] Iteration 98000 (0.996456 iter/s, 100.356s/100 iter), 189.5/232ep, loss = 3.20631
-I0511 07:56:47.491556  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01891 (* 1 = 3.01891 loss)
-I0511 07:56:47.491564  5307 sgd_solver.cpp:172] Iteration 98000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:57:47.971768  5307 solver.cpp:352] Iteration 98100 (1.65346 iter/s, 60.4791s/100 iter), 189.7/232ep, loss = 3.06749
-I0511 07:57:47.972045  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03684 (* 1 = 3.03684 loss)
-I0511 07:57:47.972064  5307 sgd_solver.cpp:172] Iteration 98100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:58:50.075870  5307 solver.cpp:352] Iteration 98200 (1.61023 iter/s, 62.103s/100 iter), 189.9/232ep, loss = 2.9852
-I0511 07:58:50.076016  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37209 (* 1 = 3.37209 loss)
-I0511 07:58:50.076025  5307 sgd_solver.cpp:172] Iteration 98200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:59:22.351446  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:59:50.813318  5307 solver.cpp:352] Iteration 98300 (1.64646 iter/s, 60.7363s/100 iter), 190.1/232ep, loss = 2.70888
-I0511 07:59:50.813359  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.57383 (* 1 = 2.57383 loss)
-I0511 07:59:50.813371  5307 sgd_solver.cpp:172] Iteration 98300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:00:51.706754  5307 solver.cpp:352] Iteration 98400 (1.64224 iter/s, 60.8923s/100 iter), 190.2/232ep, loss = 3.08315
-I0511 08:00:51.706881  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.79268 (* 1 = 2.79268 loss)
-I0511 08:00:51.706892  5307 sgd_solver.cpp:172] Iteration 98400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:01:52.966831  5307 solver.cpp:352] Iteration 98500 (1.63241 iter/s, 61.259s/100 iter), 190.4/232ep, loss = 3.01733
-I0511 08:01:52.966913  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21688 (* 1 = 3.21688 loss)
-I0511 08:01:52.966922  5307 sgd_solver.cpp:172] Iteration 98500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:02:53.233733  5307 solver.cpp:352] Iteration 98600 (1.65932 iter/s, 60.2658s/100 iter), 190.6/232ep, loss = 3.05306
-I0511 08:02:53.233789  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07683 (* 1 = 3.07683 loss)
-I0511 08:02:53.233798  5307 sgd_solver.cpp:172] Iteration 98600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:03:54.616510  5307 solver.cpp:352] Iteration 98700 (1.62915 iter/s, 61.3816s/100 iter), 190.8/232ep, loss = 3.10036
-I0511 08:03:54.616595  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22673 (* 1 = 3.22673 loss)
-I0511 08:03:54.616603  5307 sgd_solver.cpp:172] Iteration 98700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:04:38.339814  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:04:55.744252  5307 solver.cpp:352] Iteration 98800 (1.63595 iter/s, 61.1266s/100 iter), 191/232ep, loss = 2.97291
-I0511 08:04:55.744356  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05587 (* 1 = 3.05587 loss)
-I0511 08:04:55.744379  5307 sgd_solver.cpp:172] Iteration 98800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:05:56.503899  5307 solver.cpp:352] Iteration 98900 (1.64586 iter/s, 60.7585s/100 iter), 191.2/232ep, loss = 2.95962
-I0511 08:05:56.503983  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.0435 (* 1 = 3.0435 loss)
-I0511 08:05:56.503996  5307 sgd_solver.cpp:172] Iteration 98900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:06:58.032640  5307 solver.cpp:352] Iteration 99000 (1.62529 iter/s, 61.5276s/100 iter), 191.4/232ep, loss = 3.08671
-I0511 08:06:58.032723  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94509 (* 1 = 2.94509 loss)
-I0511 08:06:58.032732  5307 sgd_solver.cpp:172] Iteration 99000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:07:59.002532  5307 solver.cpp:352] Iteration 99100 (1.64018 iter/s, 60.9688s/100 iter), 191.6/232ep, loss = 3.02594
-I0511 08:07:59.002626  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53134 (* 1 = 3.53134 loss)
-I0511 08:07:59.002635  5307 sgd_solver.cpp:172] Iteration 99100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:09:00.493904  5307 solver.cpp:352] Iteration 99200 (1.62627 iter/s, 61.4902s/100 iter), 191.8/232ep, loss = 3.0374
-I0511 08:09:00.494019  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.23447 (* 1 = 4.23447 loss)
-I0511 08:09:00.494030  5307 sgd_solver.cpp:172] Iteration 99200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:09:53.119544  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:10:01.056978  5307 solver.cpp:352] Iteration 99300 (1.6512 iter/s, 60.5619s/100 iter), 192/232ep, loss = 3.03007
-I0511 08:10:01.057054  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11184 (* 1 = 3.11184 loss)
-I0511 08:10:01.057076  5307 sgd_solver.cpp:172] Iteration 99300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:11:02.474581  5307 solver.cpp:352] Iteration 99400 (1.62823 iter/s, 61.4164s/100 iter), 192.2/232ep, loss = 3.02644
-I0511 08:11:02.474658  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58186 (* 1 = 3.58186 loss)
-I0511 08:11:02.474666  5307 sgd_solver.cpp:172] Iteration 99400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:12:03.639566  5307 solver.cpp:352] Iteration 99500 (1.63495 iter/s, 61.1639s/100 iter), 192.4/232ep, loss = 3.0477
-I0511 08:12:03.639678  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54568 (* 1 = 3.54568 loss)
-I0511 08:12:03.639699  5307 sgd_solver.cpp:172] Iteration 99500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:13:04.248728  5307 solver.cpp:352] Iteration 99600 (1.64995 iter/s, 60.608s/100 iter), 192.6/232ep, loss = 3.26572
-I0511 08:13:04.248836  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.48364 (* 1 = 3.48364 loss)
-I0511 08:13:04.248863  5307 sgd_solver.cpp:172] Iteration 99600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:14:04.842027  5307 solver.cpp:352] Iteration 99700 (1.65038 iter/s, 60.5922s/100 iter), 192.8/232ep, loss = 2.9188
-I0511 08:14:04.842499  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09875 (* 1 = 3.09875 loss)
-I0511 08:14:04.842510  5307 sgd_solver.cpp:172] Iteration 99700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:15:05.169956  5307 solver.cpp:352] Iteration 99800 (1.65764 iter/s, 60.3268s/100 iter), 193/232ep, loss = 2.89835
-I0511 08:15:05.170317  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.32569 (* 1 = 4.32569 loss)
-I0511 08:15:05.170327  5307 sgd_solver.cpp:172] Iteration 99800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:15:08.292088  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:16:06.441372  5307 solver.cpp:352] Iteration 99900 (1.63211 iter/s, 61.2703s/100 iter), 193.1/232ep, loss = 3.01729
-I0511 08:16:06.441478  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73704 (* 1 = 3.73704 loss)
-I0511 08:16:06.441498  5307 sgd_solver.cpp:172] Iteration 99900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:17:08.110452  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_100000.caffemodel
-I0511 08:17:08.130551  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_100000.solverstate
-I0511 08:17:08.136447  5307 solver.cpp:635] Iteration 100000, Testing net (#0)
-I0511 08:17:48.875803  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:17:49.103816  5307 solver.cpp:747] class AP 1: 0.665005
-I0511 08:17:49.104339  5307 solver.cpp:747] class AP 2: 0.730937
-I0511 08:17:49.110823  5307 solver.cpp:747] class AP 3: 0.558327
-I0511 08:17:49.114506  5307 solver.cpp:747] class AP 4: 0.507206
-I0511 08:17:49.132952  5307 solver.cpp:747] class AP 5: 0.34404
-I0511 08:17:49.133280  5307 solver.cpp:747] class AP 6: 0.735807
-I0511 08:17:49.141923  5307 solver.cpp:747] class AP 7: 0.701335
-I0511 08:17:49.142475  5307 solver.cpp:747] class AP 8: 0.815496
-I0511 08:17:49.160322  5307 solver.cpp:747] class AP 9: 0.425556
-I0511 08:17:49.161043  5307 solver.cpp:747] class AP 10: 0.626299
-I0511 08:17:49.161677  5307 solver.cpp:747] class AP 11: 0.592111
-I0511 08:17:49.162549  5307 solver.cpp:747] class AP 12: 0.718074
-I0511 08:17:49.162979  5307 solver.cpp:747] class AP 13: 0.792086
-I0511 08:17:49.163327  5307 solver.cpp:747] class AP 14: 0.756043
-I0511 08:17:49.222995  5307 solver.cpp:747] class AP 15: 0.725033
-I0511 08:17:49.231612  5307 solver.cpp:747] class AP 16: 0.357034
-I0511 08:17:49.234997  5307 solver.cpp:747] class AP 17: 0.597503
-I0511 08:17:49.235782  5307 solver.cpp:747] class AP 18: 0.606173
-I0511 08:17:49.236677  5307 solver.cpp:747] class AP 19: 0.749204
-I0511 08:17:49.238603  5307 solver.cpp:747] class AP 20: 0.617463
-I0511 08:17:49.238801  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631037
-I0511 08:17:49.238991  5307 solver.cpp:283] Tests completed in 102.796s
-I0511 08:17:49.832324  5307 solver.cpp:352] Iteration 100000 (0.972803 iter/s, 102.796s/100 iter), 193.3/232ep, loss = 3.0267
-I0511 08:17:49.832352  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.33654 (* 1 = 2.33654 loss)
-I0511 08:17:49.832360  5307 sgd_solver.cpp:172] Iteration 100000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:18:51.388283  5307 solver.cpp:352] Iteration 100100 (1.62457 iter/s, 61.5548s/100 iter), 193.5/232ep, loss = 2.84996
-I0511 08:18:51.388463  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.45932 (* 1 = 2.45932 loss)
-I0511 08:18:51.388489  5307 sgd_solver.cpp:172] Iteration 100100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:19:53.190773  5307 solver.cpp:352] Iteration 100200 (1.61809 iter/s, 61.8014s/100 iter), 193.7/232ep, loss = 3.15988
-I0511 08:19:53.190889  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08743 (* 1 = 3.08743 loss)
-I0511 08:19:53.190897  5307 sgd_solver.cpp:172] Iteration 100200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:20:54.608816  5307 solver.cpp:352] Iteration 100300 (1.62822 iter/s, 61.4169s/100 iter), 193.9/232ep, loss = 2.97717
-I0511 08:20:54.608924  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59103 (* 1 = 3.59103 loss)
-I0511 08:20:54.608954  5307 sgd_solver.cpp:172] Iteration 100300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:21:08.816452  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:21:55.471817  5307 solver.cpp:352] Iteration 100400 (1.64306 iter/s, 60.8619s/100 iter), 194.1/232ep, loss = 2.97832
-I0511 08:21:55.471938  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.36064 (* 1 = 2.36064 loss)
-I0511 08:21:55.471957  5307 sgd_solver.cpp:172] Iteration 100400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:22:56.358227  5307 solver.cpp:352] Iteration 100500 (1.64243 iter/s, 60.8853s/100 iter), 194.3/232ep, loss = 2.98626
-I0511 08:22:56.358577  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.43856 (* 1 = 2.43856 loss)
-I0511 08:22:56.358593  5307 sgd_solver.cpp:172] Iteration 100500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:23:57.579596  5307 solver.cpp:352] Iteration 100600 (1.63345 iter/s, 61.2203s/100 iter), 194.5/232ep, loss = 3.05359
-I0511 08:23:57.582028  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.41592 (* 1 = 2.41592 loss)
-I0511 08:23:57.582038  5307 sgd_solver.cpp:172] Iteration 100600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:24:58.344626  5307 solver.cpp:352] Iteration 100700 (1.64571 iter/s, 60.7639s/100 iter), 194.7/232ep, loss = 2.91428
-I0511 08:24:58.344753  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1572 (* 1 = 3.1572 loss)
-I0511 08:24:58.344775  5307 sgd_solver.cpp:172] Iteration 100700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:25:59.356418  5307 solver.cpp:352] Iteration 100800 (1.63906 iter/s, 61.0107s/100 iter), 194.9/232ep, loss = 3.0662
-I0511 08:25:59.356564  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50593 (* 1 = 3.50593 loss)
-I0511 08:25:59.356577  5307 sgd_solver.cpp:172] Iteration 100800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:26:23.589988  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:27:00.902576  5307 solver.cpp:352] Iteration 100900 (1.62483 iter/s, 61.5451s/100 iter), 195.1/232ep, loss = 2.96019
-I0511 08:27:00.902674  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.54178 (* 1 = 2.54178 loss)
-I0511 08:27:00.902681  5307 sgd_solver.cpp:172] Iteration 100900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:28:02.828667  5307 solver.cpp:352] Iteration 101000 (1.61486 iter/s, 61.9249s/100 iter), 195.3/232ep, loss = 2.93848
-I0511 08:28:02.828826  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.41082 (* 1 = 2.41082 loss)
-I0511 08:28:02.828871  5307 sgd_solver.cpp:172] Iteration 101000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:29:04.057327  5307 solver.cpp:352] Iteration 101100 (1.63325 iter/s, 61.2275s/100 iter), 195.5/232ep, loss = 3.148
-I0511 08:29:04.057379  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57206 (* 1 = 3.57206 loss)
-I0511 08:29:04.057386  5307 sgd_solver.cpp:172] Iteration 101100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:30:05.313616  5307 solver.cpp:352] Iteration 101200 (1.63252 iter/s, 61.2551s/100 iter), 195.7/232ep, loss = 3.03246
-I0511 08:30:05.313746  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61708 (* 1 = 3.61708 loss)
-I0511 08:30:05.313758  5307 sgd_solver.cpp:172] Iteration 101200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:31:07.408694  5307 solver.cpp:352] Iteration 101300 (1.61046 iter/s, 62.0939s/100 iter), 195.9/232ep, loss = 3.11302
-I0511 08:31:07.408802  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83745 (* 1 = 2.83745 loss)
-I0511 08:31:07.408816  5307 sgd_solver.cpp:172] Iteration 101300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:31:42.815610  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:32:09.252004  5307 solver.cpp:352] Iteration 101400 (1.61702 iter/s, 61.8422s/100 iter), 196/232ep, loss = 2.79151
-I0511 08:32:09.252032  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.39979 (* 1 = 2.39979 loss)
-I0511 08:32:09.252040  5307 sgd_solver.cpp:172] Iteration 101400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:33:10.985529  5307 solver.cpp:352] Iteration 101500 (1.6199 iter/s, 61.7324s/100 iter), 196.2/232ep, loss = 2.91793
-I0511 08:33:10.985631  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04143 (* 1 = 3.04143 loss)
-I0511 08:33:10.985642  5307 sgd_solver.cpp:172] Iteration 101500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:34:12.504964  5307 solver.cpp:352] Iteration 101600 (1.62553 iter/s, 61.5183s/100 iter), 196.4/232ep, loss = 2.99502
-I0511 08:34:12.505041  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.19517 (* 1 = 2.19517 loss)
-I0511 08:34:12.505050  5307 sgd_solver.cpp:172] Iteration 101600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:35:13.790604  5307 solver.cpp:352] Iteration 101700 (1.63173 iter/s, 61.2845s/100 iter), 196.6/232ep, loss = 3.06827
-I0511 08:35:13.790659  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38886 (* 1 = 3.38886 loss)
-I0511 08:35:13.790666  5307 sgd_solver.cpp:172] Iteration 101700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:36:15.784857  5307 solver.cpp:352] Iteration 101800 (1.61308 iter/s, 61.9931s/100 iter), 196.8/232ep, loss = 3.18449
-I0511 08:36:15.784955  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28257 (* 1 = 3.28257 loss)
-I0511 08:36:15.784977  5307 sgd_solver.cpp:172] Iteration 101800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:37:01.141197  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:37:16.739065  5307 solver.cpp:352] Iteration 101900 (1.64061 iter/s, 60.9531s/100 iter), 197/232ep, loss = 3.02052
-I0511 08:37:16.739158  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.42314 (* 1 = 3.42314 loss)
-I0511 08:37:16.739177  5307 sgd_solver.cpp:172] Iteration 101900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:38:16.737043  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_102000.caffemodel
-I0511 08:38:16.749049  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_102000.solverstate
-I0511 08:38:16.753746  5307 solver.cpp:635] Iteration 102000, Testing net (#0)
-I0511 08:38:57.167840  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:38:57.375763  5307 solver.cpp:747] class AP 1: 0.662877
-I0511 08:38:57.376477  5307 solver.cpp:747] class AP 2: 0.729423
-I0511 08:38:57.385727  5307 solver.cpp:747] class AP 3: 0.558048
-I0511 08:38:57.391151  5307 solver.cpp:747] class AP 4: 0.501808
-I0511 08:38:57.416709  5307 solver.cpp:747] class AP 5: 0.339622
-I0511 08:38:57.417057  5307 solver.cpp:747] class AP 6: 0.734243
-I0511 08:38:57.425725  5307 solver.cpp:747] class AP 7: 0.703979
-I0511 08:38:57.426270  5307 solver.cpp:747] class AP 8: 0.820063
-I0511 08:38:57.444169  5307 solver.cpp:747] class AP 9: 0.430973
-I0511 08:38:57.444890  5307 solver.cpp:747] class AP 10: 0.627212
-I0511 08:38:57.445516  5307 solver.cpp:747] class AP 11: 0.598763
-I0511 08:38:57.446367  5307 solver.cpp:747] class AP 12: 0.727264
-I0511 08:38:57.446800  5307 solver.cpp:747] class AP 13: 0.795383
-I0511 08:38:57.447157  5307 solver.cpp:747] class AP 14: 0.742447
-I0511 08:38:57.496114  5307 solver.cpp:747] class AP 15: 0.724216
-I0511 08:38:57.502737  5307 solver.cpp:747] class AP 16: 0.360335
-I0511 08:38:57.505149  5307 solver.cpp:747] class AP 17: 0.59934
-I0511 08:38:57.505834  5307 solver.cpp:747] class AP 18: 0.609809
-I0511 08:38:57.506490  5307 solver.cpp:747] class AP 19: 0.750395
-I0511 08:38:57.507906  5307 solver.cpp:747] class AP 20: 0.613732
-I0511 08:38:57.507915  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631497
-I0511 08:38:57.508059  5307 solver.cpp:283] Tests completed in 100.767s
-I0511 08:38:58.034000  5307 solver.cpp:352] Iteration 102000 (0.992386 iter/s, 100.767s/100 iter), 197.2/232ep, loss = 2.96189
-I0511 08:38:58.034025  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47859 (* 1 = 3.47859 loss)
-I0511 08:38:58.034032  5307 sgd_solver.cpp:172] Iteration 102000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:39:59.308593  5307 solver.cpp:352] Iteration 102100 (1.63203 iter/s, 61.2734s/100 iter), 197.4/232ep, loss = 3.01728
-I0511 08:39:59.308722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22398 (* 1 = 3.22398 loss)
-I0511 08:39:59.308735  5307 sgd_solver.cpp:172] Iteration 102100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:40:59.338691  5307 solver.cpp:352] Iteration 102200 (1.66586 iter/s, 60.0291s/100 iter), 197.6/232ep, loss = 2.97617
-I0511 08:40:59.338783  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.49093 (* 1 = 2.49093 loss)
-I0511 08:40:59.338793  5307 sgd_solver.cpp:172] Iteration 102200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:42:01.744545  5307 solver.cpp:352] Iteration 102300 (1.60244 iter/s, 62.4047s/100 iter), 197.8/232ep, loss = 3.03357
-I0511 08:42:01.744637  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25867 (* 1 = 3.25867 loss)
-I0511 08:42:01.744647  5307 sgd_solver.cpp:172] Iteration 102300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:42:57.391222  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:43:02.803563  5307 solver.cpp:352] Iteration 102400 (1.63779 iter/s, 61.058s/100 iter), 198/232ep, loss = 3.22251
-I0511 08:43:02.803596  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6136 (* 1 = 2.6136 loss)
-I0511 08:43:02.803603  5307 sgd_solver.cpp:172] Iteration 102400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:44:04.976128  5307 solver.cpp:352] Iteration 102500 (1.60845 iter/s, 62.1715s/100 iter), 198.2/232ep, loss = 3.14362
-I0511 08:44:04.976188  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.12992 (* 1 = 3.12992 loss)
-I0511 08:44:04.976194  5307 sgd_solver.cpp:172] Iteration 102500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:45:06.639672  5307 solver.cpp:352] Iteration 102600 (1.62173 iter/s, 61.6625s/100 iter), 198.4/232ep, loss = 3.05518
-I0511 08:45:06.640053  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95388 (* 1 = 2.95388 loss)
-I0511 08:45:06.640072  5307 sgd_solver.cpp:172] Iteration 102600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:46:07.664664  5307 solver.cpp:352] Iteration 102700 (1.6387 iter/s, 61.0239s/100 iter), 198.6/232ep, loss = 2.99007
-I0511 08:46:07.667974  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39835 (* 1 = 3.39835 loss)
-I0511 08:46:07.668041  5307 sgd_solver.cpp:172] Iteration 102700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:47:09.222339  5307 solver.cpp:352] Iteration 102800 (1.62452 iter/s, 61.5566s/100 iter), 198.8/232ep, loss = 2.92772
-I0511 08:47:09.222436  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.22916 (* 1 = 2.22916 loss)
-I0511 08:47:09.222455  5307 sgd_solver.cpp:172] Iteration 102800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:48:10.972451  5307 solver.cpp:352] Iteration 102900 (1.61946 iter/s, 61.749s/100 iter), 198.9/232ep, loss = 2.97089
-I0511 08:48:10.972628  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5179 (* 1 = 3.5179 loss)
-I0511 08:48:10.972647  5307 sgd_solver.cpp:172] Iteration 102900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:48:16.512580  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:49:12.852767  5307 solver.cpp:352] Iteration 103000 (1.61605 iter/s, 61.8792s/100 iter), 199.1/232ep, loss = 2.86671
-I0511 08:49:12.853016  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73384 (* 1 = 3.73384 loss)
-I0511 08:49:12.853035  5307 sgd_solver.cpp:172] Iteration 103000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:50:14.537976  5307 solver.cpp:352] Iteration 103100 (1.62116 iter/s, 61.6841s/100 iter), 199.3/232ep, loss = 3.3114
-I0511 08:50:14.538293  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01035 (* 1 = 3.01035 loss)
-I0511 08:50:14.538347  5307 sgd_solver.cpp:172] Iteration 103100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:51:16.029994  5307 solver.cpp:352] Iteration 103200 (1.62626 iter/s, 61.4909s/100 iter), 199.5/232ep, loss = 3.06903
-I0511 08:51:16.036649  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0684 (* 1 = 4.0684 loss)
-I0511 08:51:16.036679  5307 sgd_solver.cpp:172] Iteration 103200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:52:17.581897  5307 solver.cpp:352] Iteration 103300 (1.62468 iter/s, 61.5508s/100 iter), 199.7/232ep, loss = 3.08515
-I0511 08:52:17.582022  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87733 (* 1 = 2.87733 loss)
-I0511 08:52:17.582093  5307 sgd_solver.cpp:172] Iteration 103300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:53:25.213412  5307 solver.cpp:352] Iteration 103400 (1.47863 iter/s, 67.6302s/100 iter), 199.9/232ep, loss = 2.89853
-I0511 08:53:25.213524  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3616 (* 1 = 3.3616 loss)
-I0511 08:53:25.213547  5307 sgd_solver.cpp:172] Iteration 103400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:53:42.453626  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:54:30.902637  5307 solver.cpp:352] Iteration 103500 (1.52235 iter/s, 65.688s/100 iter), 200.1/232ep, loss = 2.97316
-I0511 08:54:30.902704  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.48358 (* 1 = 2.48358 loss)
-I0511 08:54:30.902714  5307 sgd_solver.cpp:172] Iteration 103500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:55:32.001219  5307 solver.cpp:352] Iteration 103600 (1.63673 iter/s, 61.0974s/100 iter), 200.3/232ep, loss = 3.12863
-I0511 08:55:32.001878  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65934 (* 1 = 2.65934 loss)
-I0511 08:55:32.001896  5307 sgd_solver.cpp:172] Iteration 103600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:56:32.925688  5307 solver.cpp:352] Iteration 103700 (1.64141 iter/s, 60.9234s/100 iter), 200.5/232ep, loss = 3.02484
-I0511 08:56:32.930019  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6127 (* 1 = 2.6127 loss)
-I0511 08:56:32.930043  5307 sgd_solver.cpp:172] Iteration 103700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:57:34.563419  5307 solver.cpp:352] Iteration 103800 (1.62241 iter/s, 61.6366s/100 iter), 200.7/232ep, loss = 3.00477
-I0511 08:57:34.564416  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82427 (* 1 = 3.82427 loss)
-I0511 08:57:34.564426  5307 sgd_solver.cpp:172] Iteration 103800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:58:35.047950  5307 solver.cpp:352] Iteration 103900 (1.65335 iter/s, 60.4834s/100 iter), 200.9/232ep, loss = 2.86798
-I0511 08:58:35.048068  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92458 (* 1 = 2.92458 loss)
-I0511 08:58:35.048089  5307 sgd_solver.cpp:172] Iteration 103900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:59:01.674793  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:59:35.537987  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_104000.caffemodel
-I0511 08:59:35.552865  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_104000.solverstate
-I0511 08:59:35.557982  5307 solver.cpp:635] Iteration 104000, Testing net (#0)
-I0511 09:00:15.941030  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:00:16.171171  5307 solver.cpp:747] class AP 1: 0.658912
-I0511 09:00:16.171667  5307 solver.cpp:747] class AP 2: 0.733622
-I0511 09:00:16.178172  5307 solver.cpp:747] class AP 3: 0.560076
-I0511 09:00:16.181856  5307 solver.cpp:747] class AP 4: 0.507364
-I0511 09:00:16.200403  5307 solver.cpp:747] class AP 5: 0.342464
-I0511 09:00:16.200734  5307 solver.cpp:747] class AP 6: 0.737497
-I0511 09:00:16.209339  5307 solver.cpp:747] class AP 7: 0.704001
-I0511 09:00:16.209879  5307 solver.cpp:747] class AP 8: 0.816034
-I0511 09:00:16.228055  5307 solver.cpp:747] class AP 9: 0.434627
-I0511 09:00:16.228770  5307 solver.cpp:747] class AP 10: 0.626055
-I0511 09:00:16.229395  5307 solver.cpp:747] class AP 11: 0.601497
-I0511 09:00:16.230235  5307 solver.cpp:747] class AP 12: 0.720504
-I0511 09:00:16.230667  5307 solver.cpp:747] class AP 13: 0.798838
-I0511 09:00:16.231020  5307 solver.cpp:747] class AP 14: 0.741948
-I0511 09:00:16.281016  5307 solver.cpp:747] class AP 15: 0.727061
-I0511 09:00:16.287535  5307 solver.cpp:747] class AP 16: 0.36246
-I0511 09:00:16.290091  5307 solver.cpp:747] class AP 17: 0.598146
-I0511 09:00:16.290707  5307 solver.cpp:747] class AP 18: 0.609144
-I0511 09:00:16.291417  5307 solver.cpp:747] class AP 19: 0.747257
-I0511 09:00:16.292925  5307 solver.cpp:747] class AP 20: 0.609945
-I0511 09:00:16.292943  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631873
-I0511 09:00:16.293195  5307 solver.cpp:283] Tests completed in 101.243s
-I0511 09:00:16.893482  5307 solver.cpp:352] Iteration 104000 (0.987718 iter/s, 101.243s/100 iter), 201.1/232ep, loss = 2.84492
-I0511 09:00:16.893506  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.13108 (* 1 = 2.13108 loss)
-I0511 09:00:16.893512  5307 sgd_solver.cpp:172] Iteration 104000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:01:18.301661  5307 solver.cpp:352] Iteration 104100 (1.62848 iter/s, 61.4071s/100 iter), 201.3/232ep, loss = 3.17149
-I0511 09:01:18.301719  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.66412 (* 1 = 2.66412 loss)
-I0511 09:01:18.301728  5307 sgd_solver.cpp:172] Iteration 104100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:02:19.057096  5307 solver.cpp:352] Iteration 104200 (1.64597 iter/s, 60.7543s/100 iter), 201.5/232ep, loss = 2.97307
-I0511 09:02:19.057158  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.79797 (* 1 = 2.79797 loss)
-I0511 09:02:19.057164  5307 sgd_solver.cpp:172] Iteration 104200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:03:19.339989  5307 solver.cpp:352] Iteration 104300 (1.65888 iter/s, 60.2818s/100 iter), 201.7/232ep, loss = 2.97009
-I0511 09:03:19.340106  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71737 (* 1 = 2.71737 loss)
-I0511 09:03:19.340113  5307 sgd_solver.cpp:172] Iteration 104300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:04:19.700664  5307 solver.cpp:352] Iteration 104400 (1.65674 iter/s, 60.3596s/100 iter), 201.8/232ep, loss = 3.18266
-I0511 09:04:19.700740  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.75174 (* 1 = 2.75174 loss)
-I0511 09:04:19.700747  5307 sgd_solver.cpp:172] Iteration 104400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:04:55.972400  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:05:19.960947  5307 solver.cpp:352] Iteration 104500 (1.6595 iter/s, 60.2592s/100 iter), 202/232ep, loss = 3.00151
-I0511 09:05:19.960974  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.33216 (* 1 = 4.33216 loss)
-I0511 09:05:19.960983  5307 sgd_solver.cpp:172] Iteration 104500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:06:21.572664  5307 solver.cpp:352] Iteration 104600 (1.6231 iter/s, 61.6106s/100 iter), 202.2/232ep, loss = 2.96726
-I0511 09:06:21.574237  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63491 (* 1 = 2.63491 loss)
-I0511 09:06:21.574266  5307 sgd_solver.cpp:172] Iteration 104600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:07:22.228152  5307 solver.cpp:352] Iteration 104700 (1.64868 iter/s, 60.6544s/100 iter), 202.4/232ep, loss = 2.94288
-I0511 09:07:22.228384  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.29353 (* 1 = 2.29353 loss)
-I0511 09:07:22.228392  5307 sgd_solver.cpp:172] Iteration 104700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:08:22.898113  5307 solver.cpp:352] Iteration 104800 (1.64829 iter/s, 60.6688s/100 iter), 202.6/232ep, loss = 2.97853
-I0511 09:08:22.899556  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.0337 (* 1 = 2.0337 loss)
-I0511 09:08:22.899595  5307 sgd_solver.cpp:172] Iteration 104800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:09:23.892618  5307 solver.cpp:352] Iteration 104900 (1.63952 iter/s, 60.9934s/100 iter), 202.8/232ep, loss = 2.9735
-I0511 09:09:23.892762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.52497 (* 1 = 3.52497 loss)
-I0511 09:09:23.892772  5307 sgd_solver.cpp:172] Iteration 104900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:10:10.349397  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:10:24.394165  5307 solver.cpp:352] Iteration 105000 (1.65288 iter/s, 60.5004s/100 iter), 203/232ep, loss = 3.00669
-I0511 09:10:24.394269  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04437 (* 1 = 3.04437 loss)
-I0511 09:10:24.394306  5307 sgd_solver.cpp:172] Iteration 105000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:11:26.353379  5307 solver.cpp:352] Iteration 105100 (1.61399 iter/s, 61.9581s/100 iter), 203.2/232ep, loss = 2.88185
-I0511 09:11:26.353467  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6082 (* 1 = 2.6082 loss)
-I0511 09:11:26.353478  5307 sgd_solver.cpp:172] Iteration 105100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:12:27.174247  5307 solver.cpp:352] Iteration 105200 (1.6442 iter/s, 60.8197s/100 iter), 203.4/232ep, loss = 2.87346
-I0511 09:12:27.174407  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02363 (* 1 = 4.02363 loss)
-I0511 09:12:27.174417  5307 sgd_solver.cpp:172] Iteration 105200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:13:28.831068  5307 solver.cpp:352] Iteration 105300 (1.62191 iter/s, 61.6557s/100 iter), 203.6/232ep, loss = 3.00454
-I0511 09:13:28.831135  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.38076 (* 1 = 4.38076 loss)
-I0511 09:13:28.831141  5307 sgd_solver.cpp:172] Iteration 105300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:14:30.143863  5307 solver.cpp:352] Iteration 105400 (1.63101 iter/s, 61.3116s/100 iter), 203.8/232ep, loss = 2.85613
-I0511 09:14:30.144198  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83625 (* 1 = 2.83625 loss)
-I0511 09:14:30.144227  5307 sgd_solver.cpp:172] Iteration 105400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:15:28.410624  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:15:31.289784  5307 solver.cpp:352] Iteration 105500 (1.63546 iter/s, 61.1448s/100 iter), 204/232ep, loss = 3.07666
-I0511 09:15:31.289810  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81599 (* 1 = 2.81599 loss)
-I0511 09:15:31.289819  5307 sgd_solver.cpp:172] Iteration 105500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:16:31.947705  5307 solver.cpp:352] Iteration 105600 (1.64862 iter/s, 60.6568s/100 iter), 204.2/232ep, loss = 2.84988
-I0511 09:16:31.947778  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81488 (* 1 = 2.81488 loss)
-I0511 09:16:31.947788  5307 sgd_solver.cpp:172] Iteration 105600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:17:32.886667  5307 solver.cpp:352] Iteration 105700 (1.64102 iter/s, 60.9379s/100 iter), 204.4/232ep, loss = 3.18043
-I0511 09:17:32.886966  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.54316 (* 1 = 2.54316 loss)
-I0511 09:17:32.886976  5307 sgd_solver.cpp:172] Iteration 105700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:18:34.355509  5307 solver.cpp:352] Iteration 105800 (1.62687 iter/s, 61.4677s/100 iter), 204.6/232ep, loss = 3.05276
-I0511 09:18:34.355572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07529 (* 1 = 3.07529 loss)
-I0511 09:18:34.355579  5307 sgd_solver.cpp:172] Iteration 105800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:19:35.041429  5307 solver.cpp:352] Iteration 105900 (1.64786 iter/s, 60.6848s/100 iter), 204.7/232ep, loss = 2.9841
-I0511 09:19:35.041501  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95786 (* 1 = 2.95786 loss)
-I0511 09:19:35.041512  5307 sgd_solver.cpp:172] Iteration 105900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:20:35.229087  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_106000.caffemodel
-I0511 09:20:35.249084  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_106000.solverstate
-I0511 09:20:35.255237  5307 solver.cpp:635] Iteration 106000, Testing net (#0)
-I0511 09:21:15.721871  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:21:15.931792  5307 solver.cpp:747] class AP 1: 0.660411
-I0511 09:21:15.932317  5307 solver.cpp:747] class AP 2: 0.730086
-I0511 09:21:15.938953  5307 solver.cpp:747] class AP 3: 0.557565
-I0511 09:21:15.942739  5307 solver.cpp:747] class AP 4: 0.505904
-I0511 09:21:15.962241  5307 solver.cpp:747] class AP 5: 0.345831
-I0511 09:21:15.962599  5307 solver.cpp:747] class AP 6: 0.736774
-I0511 09:21:15.971547  5307 solver.cpp:747] class AP 7: 0.705488
-I0511 09:21:15.972134  5307 solver.cpp:747] class AP 8: 0.819378
-I0511 09:21:15.990371  5307 solver.cpp:747] class AP 9: 0.429442
-I0511 09:21:15.991097  5307 solver.cpp:747] class AP 10: 0.633304
-I0511 09:21:15.991744  5307 solver.cpp:747] class AP 11: 0.595445
-I0511 09:21:15.992588  5307 solver.cpp:747] class AP 12: 0.721519
-I0511 09:21:15.993032  5307 solver.cpp:747] class AP 13: 0.796779
-I0511 09:21:15.993393  5307 solver.cpp:747] class AP 14: 0.748903
-I0511 09:21:16.041465  5307 solver.cpp:747] class AP 15: 0.725762
-I0511 09:21:16.047837  5307 solver.cpp:747] class AP 16: 0.364806
-I0511 09:21:16.050380  5307 solver.cpp:747] class AP 17: 0.598963
-I0511 09:21:16.050945  5307 solver.cpp:747] class AP 18: 0.604041
-I0511 09:21:16.051612  5307 solver.cpp:747] class AP 19: 0.749612
-I0511 09:21:16.053093  5307 solver.cpp:747] class AP 20: 0.610039
-I0511 09:21:16.053099  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.632003
-I0511 09:21:16.053356  5307 solver.cpp:283] Tests completed in 101.01s
-I0511 09:21:16.605718  5307 solver.cpp:352] Iteration 106000 (0.99 iter/s, 101.01s/100 iter), 204.9/232ep, loss = 2.97081
-I0511 09:21:16.605746  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91581 (* 1 = 2.91581 loss)
-I0511 09:21:16.605754  5307 sgd_solver.cpp:172] Iteration 106000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:21:23.239075  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:22:16.511878  5307 solver.cpp:352] Iteration 106100 (1.66931 iter/s, 59.9051s/100 iter), 205.1/232ep, loss = 2.79096
-I0511 09:22:16.511988  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9052 (* 1 = 2.9052 loss)
-I0511 09:22:16.512006  5307 sgd_solver.cpp:172] Iteration 106100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:23:17.654028  5307 solver.cpp:352] Iteration 106200 (1.63556 iter/s, 61.141s/100 iter), 205.3/232ep, loss = 2.99165
-I0511 09:23:17.654165  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20889 (* 1 = 3.20889 loss)
-I0511 09:23:17.654181  5307 sgd_solver.cpp:172] Iteration 106200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:24:18.296691  5307 solver.cpp:352] Iteration 106300 (1.64903 iter/s, 60.6416s/100 iter), 205.5/232ep, loss = 3.0056
-I0511 09:24:18.296780  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80644 (* 1 = 3.80644 loss)
-I0511 09:24:18.296798  5307 sgd_solver.cpp:172] Iteration 106300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:25:18.281538  5307 solver.cpp:352] Iteration 106400 (1.66712 iter/s, 59.9838s/100 iter), 205.7/232ep, loss = 2.94822
-I0511 09:25:18.281648  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.13342 (* 1 = 2.13342 loss)
-I0511 09:25:18.281662  5307 sgd_solver.cpp:172] Iteration 106400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:26:18.623312  5307 solver.cpp:352] Iteration 106500 (1.65726 iter/s, 60.3407s/100 iter), 205.9/232ep, loss = 2.91705
-I0511 09:26:18.623702  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31356 (* 1 = 3.31356 loss)
-I0511 09:26:18.623710  5307 sgd_solver.cpp:172] Iteration 106500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:26:36.457285  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:27:19.887410  5307 solver.cpp:352] Iteration 106600 (1.63231 iter/s, 61.263s/100 iter), 206.1/232ep, loss = 3.00814
-I0511 09:27:19.889544  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25941 (* 1 = 3.25941 loss)
-I0511 09:27:19.889564  5307 sgd_solver.cpp:172] Iteration 106600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:28:21.581161  5307 solver.cpp:352] Iteration 106700 (1.62094 iter/s, 61.6927s/100 iter), 206.3/232ep, loss = 3.08816
-I0511 09:28:21.581254  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27414 (* 1 = 3.27414 loss)
-I0511 09:28:21.581272  5307 sgd_solver.cpp:172] Iteration 106700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:29:24.353520  5307 solver.cpp:352] Iteration 106800 (1.59309 iter/s, 62.7713s/100 iter), 206.5/232ep, loss = 2.97322
-I0511 09:29:24.353602  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.45352 (* 1 = 3.45352 loss)
-I0511 09:29:24.353622  5307 sgd_solver.cpp:172] Iteration 106800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:30:25.825932  5307 solver.cpp:352] Iteration 106900 (1.62678 iter/s, 61.4713s/100 iter), 206.7/232ep, loss = 2.96496
-I0511 09:30:25.826134  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6223 (* 1 = 2.6223 loss)
-I0511 09:30:25.826148  5307 sgd_solver.cpp:172] Iteration 106900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:31:27.199806  5307 solver.cpp:352] Iteration 107000 (1.62939 iter/s, 61.3728s/100 iter), 206.9/232ep, loss = 2.87001
-I0511 09:31:27.199870  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64079 (* 1 = 3.64079 loss)
-I0511 09:31:27.199879  5307 sgd_solver.cpp:172] Iteration 107000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:31:55.909417  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:32:28.962905  5307 solver.cpp:352] Iteration 107100 (1.61912 iter/s, 61.762s/100 iter), 207.1/232ep, loss = 3.00419
-I0511 09:32:28.963433  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91865 (* 1 = 2.91865 loss)
-I0511 09:32:28.963446  5307 sgd_solver.cpp:172] Iteration 107100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:33:30.509364  5307 solver.cpp:352] Iteration 107200 (1.62482 iter/s, 61.5453s/100 iter), 207.3/232ep, loss = 3.30159
-I0511 09:33:30.511792  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6854 (* 1 = 2.6854 loss)
-I0511 09:33:30.511801  5307 sgd_solver.cpp:172] Iteration 107200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:34:31.048547  5307 solver.cpp:352] Iteration 107300 (1.65185 iter/s, 60.5381s/100 iter), 207.5/232ep, loss = 3.02911
-I0511 09:34:31.048740  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.60675 (* 1 = 3.60675 loss)
-I0511 09:34:31.048806  5307 sgd_solver.cpp:172] Iteration 107300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:35:32.531407  5307 solver.cpp:352] Iteration 107400 (1.6265 iter/s, 61.4817s/100 iter), 207.6/232ep, loss = 2.8751
-I0511 09:35:32.532121  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31164 (* 1 = 3.31164 loss)
-I0511 09:35:32.532130  5307 sgd_solver.cpp:172] Iteration 107400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:36:33.544476  5307 solver.cpp:352] Iteration 107500 (1.63902 iter/s, 61.0119s/100 iter), 207.8/232ep, loss = 3.05105
-I0511 09:36:33.544617  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65433 (* 1 = 2.65433 loss)
-I0511 09:36:33.544636  5307 sgd_solver.cpp:172] Iteration 107500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:37:11.896042  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:37:34.432308  5307 solver.cpp:352] Iteration 107600 (1.64239 iter/s, 60.8867s/100 iter), 208/232ep, loss = 2.922
-I0511 09:37:34.432337  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.57429 (* 1 = 2.57429 loss)
-I0511 09:37:34.432345  5307 sgd_solver.cpp:172] Iteration 107600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:38:36.154429  5307 solver.cpp:352] Iteration 107700 (1.62019 iter/s, 61.721s/100 iter), 208.2/232ep, loss = 2.95121
-I0511 09:38:36.156332  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.72509 (* 1 = 2.72509 loss)
-I0511 09:38:36.156342  5307 sgd_solver.cpp:172] Iteration 107700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:39:37.661792  5307 solver.cpp:352] Iteration 107800 (1.62585 iter/s, 61.5062s/100 iter), 208.4/232ep, loss = 2.9885
-I0511 09:39:37.662276  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4115 (* 1 = 3.4115 loss)
-I0511 09:39:37.662286  5307 sgd_solver.cpp:172] Iteration 107800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:40:38.793115  5307 solver.cpp:352] Iteration 107900 (1.63585 iter/s, 61.1302s/100 iter), 208.6/232ep, loss = 3.15024
-I0511 09:40:38.794373  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.24121 (* 1 = 3.24121 loss)
-I0511 09:40:38.794384  5307 sgd_solver.cpp:172] Iteration 107900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:41:39.421762  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_108000.caffemodel
-I0511 09:41:39.435892  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_108000.solverstate
-I0511 09:41:39.441318  5307 solver.cpp:635] Iteration 108000, Testing net (#0)
-I0511 09:42:19.909317  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:42:20.142171  5307 solver.cpp:747] class AP 1: 0.656404
-I0511 09:42:20.142681  5307 solver.cpp:747] class AP 2: 0.728707
-I0511 09:42:20.149108  5307 solver.cpp:747] class AP 3: 0.554245
-I0511 09:42:20.152906  5307 solver.cpp:747] class AP 4: 0.51111
-I0511 09:42:20.172255  5307 solver.cpp:747] class AP 5: 0.346773
-I0511 09:42:20.172605  5307 solver.cpp:747] class AP 6: 0.744805
-I0511 09:42:20.181558  5307 solver.cpp:747] class AP 7: 0.703511
-I0511 09:42:20.182119  5307 solver.cpp:747] class AP 8: 0.818978
-I0511 09:42:20.200107  5307 solver.cpp:747] class AP 9: 0.432783
-I0511 09:42:20.200898  5307 solver.cpp:747] class AP 10: 0.628323
-I0511 09:42:20.201720  5307 solver.cpp:747] class AP 11: 0.588869
-I0511 09:42:20.202574  5307 solver.cpp:747] class AP 12: 0.720254
-I0511 09:42:20.203035  5307 solver.cpp:747] class AP 13: 0.798658
-I0511 09:42:20.203418  5307 solver.cpp:747] class AP 14: 0.747712
-I0511 09:42:20.259835  5307 solver.cpp:747] class AP 15: 0.726384
-I0511 09:42:20.266482  5307 solver.cpp:747] class AP 16: 0.356199
-I0511 09:42:20.269019  5307 solver.cpp:747] class AP 17: 0.598237
-I0511 09:42:20.269618  5307 solver.cpp:747] class AP 18: 0.603476
-I0511 09:42:20.270298  5307 solver.cpp:747] class AP 19: 0.759944
-I0511 09:42:20.271759  5307 solver.cpp:747] class AP 20: 0.615325
-I0511 09:42:20.271777  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.632035
-I0511 09:42:20.272122  5307 solver.cpp:283] Tests completed in 101.477s
-I0511 09:42:20.826761  5307 solver.cpp:352] Iteration 108000 (0.985443 iter/s, 101.477s/100 iter), 208.8/232ep, loss = 2.9927
-I0511 09:42:20.827028  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90072 (* 1 = 2.90072 loss)
-I0511 09:42:20.827039  5307 sgd_solver.cpp:172] Iteration 108000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:43:10.224517  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:43:22.015218  5307 solver.cpp:352] Iteration 108100 (1.63432 iter/s, 61.1873s/100 iter), 209/232ep, loss = 3.04481
-I0511 09:43:22.015246  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63587 (* 1 = 2.63587 loss)
-I0511 09:43:22.015254  5307 sgd_solver.cpp:172] Iteration 108100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:44:23.599179  5307 solver.cpp:352] Iteration 108200 (1.62383 iter/s, 61.5828s/100 iter), 209.2/232ep, loss = 2.92217
-I0511 09:44:23.600044  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.41159 (* 1 = 2.41159 loss)
-I0511 09:44:23.600061  5307 sgd_solver.cpp:172] Iteration 108200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:45:25.352929  5307 solver.cpp:352] Iteration 108300 (1.61936 iter/s, 61.7527s/100 iter), 209.4/232ep, loss = 2.88494
-I0511 09:45:25.352996  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46943 (* 1 = 3.46943 loss)
-I0511 09:45:25.353006  5307 sgd_solver.cpp:172] Iteration 108300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:46:27.529007  5307 solver.cpp:352] Iteration 108400 (1.60836 iter/s, 62.1749s/100 iter), 209.6/232ep, loss = 3.15808
-I0511 09:46:27.531289  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.35382 (* 1 = 2.35382 loss)
-I0511 09:46:27.531325  5307 sgd_solver.cpp:172] Iteration 108400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:47:28.979347  5307 solver.cpp:352] Iteration 108500 (1.62736 iter/s, 61.4493s/100 iter), 209.8/232ep, loss = 3.06685
-I0511 09:47:28.979426  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.57391 (* 1 = 2.57391 loss)
-I0511 09:47:28.979434  5307 sgd_solver.cpp:172] Iteration 108500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:48:29.157548  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:48:30.958716  5307 solver.cpp:352] Iteration 108600 (1.61347 iter/s, 61.9783s/100 iter), 210/232ep, loss = 3.16514
-I0511 09:48:30.958742  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32524 (* 1 = 3.32524 loss)
-I0511 09:48:30.958748  5307 sgd_solver.cpp:172] Iteration 108600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:49:31.946439  5307 solver.cpp:352] Iteration 108700 (1.6397 iter/s, 60.9866s/100 iter), 210.2/232ep, loss = 3.11442
-I0511 09:49:31.946703  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58374 (* 1 = 3.58374 loss)
-I0511 09:49:31.946714  5307 sgd_solver.cpp:172] Iteration 108700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:50:33.278905  5307 solver.cpp:352] Iteration 108800 (1.63049 iter/s, 61.3314s/100 iter), 210.4/232ep, loss = 3.11977
-I0511 09:50:33.279023  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.24816 (* 1 = 3.24816 loss)
-I0511 09:50:33.279034  5307 sgd_solver.cpp:172] Iteration 108800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:51:35.136703  5307 solver.cpp:352] Iteration 108900 (1.61664 iter/s, 61.8567s/100 iter), 210.5/232ep, loss = 2.79067
-I0511 09:51:35.138720  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31322 (* 1 = 3.31322 loss)
-I0511 09:51:35.138751  5307 sgd_solver.cpp:172] Iteration 108900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:52:36.540758  5307 solver.cpp:352] Iteration 109000 (1.62859 iter/s, 61.403s/100 iter), 210.7/232ep, loss = 3.03206
-I0511 09:52:36.543386  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.53034 (* 1 = 2.53034 loss)
-I0511 09:52:36.543408  5307 sgd_solver.cpp:172] Iteration 109000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:53:36.958336  5307 solver.cpp:352] Iteration 109100 (1.65518 iter/s, 60.4165s/100 iter), 210.9/232ep, loss = 2.81642
-I0511 09:53:36.958397  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55472 (* 1 = 3.55472 loss)
-I0511 09:53:36.958406  5307 sgd_solver.cpp:172] Iteration 109100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:53:46.445642  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:54:39.186568  5307 solver.cpp:352] Iteration 109200 (1.60702 iter/s, 62.2271s/100 iter), 211.1/232ep, loss = 2.96823
-I0511 09:54:39.186671  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5983 (* 1 = 2.5983 loss)
-I0511 09:54:39.186682  5307 sgd_solver.cpp:172] Iteration 109200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:55:41.894292  5307 solver.cpp:352] Iteration 109300 (1.59473 iter/s, 62.7066s/100 iter), 211.3/232ep, loss = 3.0341
-I0511 09:55:41.894351  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.34157 (* 1 = 3.34157 loss)
-I0511 09:55:41.894359  5307 sgd_solver.cpp:172] Iteration 109300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:56:43.293130  5307 solver.cpp:352] Iteration 109400 (1.62873 iter/s, 61.3977s/100 iter), 211.5/232ep, loss = 2.94719
-I0511 09:56:43.293259  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5932 (* 1 = 2.5932 loss)
-I0511 09:56:43.293289  5307 sgd_solver.cpp:172] Iteration 109400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:57:44.943948  5307 solver.cpp:352] Iteration 109500 (1.62207 iter/s, 61.6497s/100 iter), 211.7/232ep, loss = 3.04132
-I0511 09:57:44.944041  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.2802 (* 1 = 2.2802 loss)
-I0511 09:57:44.944051  5307 sgd_solver.cpp:172] Iteration 109500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:58:46.472889  5307 solver.cpp:352] Iteration 109600 (1.62528 iter/s, 61.5278s/100 iter), 211.9/232ep, loss = 3.05654
-I0511 09:58:46.476739  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87819 (* 1 = 2.87819 loss)
-I0511 09:58:46.476758  5307 sgd_solver.cpp:172] Iteration 109600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:59:07.274627  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:59:48.034642  5307 solver.cpp:352] Iteration 109700 (1.62442 iter/s, 61.5606s/100 iter), 212.1/232ep, loss = 3.04314
-I0511 09:59:48.034703  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15212 (* 1 = 3.15212 loss)
-I0511 09:59:48.034711  5307 sgd_solver.cpp:172] Iteration 109700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:00:57.823367  5307 solver.cpp:352] Iteration 109800 (1.43292 iter/s, 69.7874s/100 iter), 212.3/232ep, loss = 3.09853
-I0511 10:00:57.823479  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.29951 (* 1 = 3.29951 loss)
-I0511 10:00:57.823501  5307 sgd_solver.cpp:172] Iteration 109800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:02:03.153767  5307 solver.cpp:352] Iteration 109900 (1.53071 iter/s, 65.3292s/100 iter), 212.5/232ep, loss = 3.13834
-I0511 10:02:03.153846  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69669 (* 1 = 3.69669 loss)
-I0511 10:02:03.153853  5307 sgd_solver.cpp:172] Iteration 109900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:03:03.416615  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_110000.caffemodel
-I0511 10:03:03.433248  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_110000.solverstate
-I0511 10:03:03.438459  5307 solver.cpp:635] Iteration 110000, Testing net (#0)
-I0511 10:03:25.448328  5354 blocking_queue.cpp:40] Waiting for data
-I0511 10:03:43.845228  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:03:44.052278  5307 solver.cpp:747] class AP 1: 0.65293
-I0511 10:03:44.052799  5307 solver.cpp:747] class AP 2: 0.733623
-I0511 10:03:44.059448  5307 solver.cpp:747] class AP 3: 0.557503
-I0511 10:03:44.063221  5307 solver.cpp:747] class AP 4: 0.512509
-I0511 10:03:44.082121  5307 solver.cpp:747] class AP 5: 0.345366
-I0511 10:03:44.082494  5307 solver.cpp:747] class AP 6: 0.739828
-I0511 10:03:44.091215  5307 solver.cpp:747] class AP 7: 0.703411
-I0511 10:03:44.091783  5307 solver.cpp:747] class AP 8: 0.816873
-I0511 10:03:44.110553  5307 solver.cpp:747] class AP 9: 0.43649
-I0511 10:03:44.111286  5307 solver.cpp:747] class AP 10: 0.631253
-I0511 10:03:44.112057  5307 solver.cpp:747] class AP 11: 0.589722
-I0511 10:03:44.113168  5307 solver.cpp:747] class AP 12: 0.720832
-I0511 10:03:44.113615  5307 solver.cpp:747] class AP 13: 0.79909
-I0511 10:03:44.113967  5307 solver.cpp:747] class AP 14: 0.74729
-I0511 10:03:44.163322  5307 solver.cpp:747] class AP 15: 0.725755
-I0511 10:03:44.169760  5307 solver.cpp:747] class AP 16: 0.358302
-I0511 10:03:44.172224  5307 solver.cpp:747] class AP 17: 0.598111
-I0511 10:03:44.172845  5307 solver.cpp:747] class AP 18: 0.601112
-I0511 10:03:44.173518  5307 solver.cpp:747] class AP 19: 0.752073
-I0511 10:03:44.175300  5307 solver.cpp:747] class AP 20: 0.609423
-I0511 10:03:44.175433  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631575
-I0511 10:03:44.175595  5307 solver.cpp:283] Tests completed in 101.02s
-I0511 10:03:44.715556  5307 solver.cpp:352] Iteration 110000 (0.989903 iter/s, 101.02s/100 iter), 212.7/232ep, loss = 2.89916
-I0511 10:03:44.715628  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63487 (* 1 = 2.63487 loss)
-I0511 10:03:44.715646  5307 sgd_solver.cpp:172] Iteration 110000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:04:45.138458  5307 solver.cpp:352] Iteration 110100 (1.65503 iter/s, 60.4218s/100 iter), 212.9/232ep, loss = 3.00876
-I0511 10:04:45.138525  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1163 (* 1 = 3.1163 loss)
-I0511 10:04:45.138535  5307 sgd_solver.cpp:172] Iteration 110100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:05:14.963007  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:05:46.285318  5307 solver.cpp:352] Iteration 110200 (1.63544 iter/s, 61.1457s/100 iter), 213.1/232ep, loss = 3.04647
-I0511 10:05:46.285425  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90314 (* 1 = 2.90314 loss)
-I0511 10:05:46.285439  5307 sgd_solver.cpp:172] Iteration 110200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:06:46.456821  5307 solver.cpp:352] Iteration 110300 (1.66195 iter/s, 60.1704s/100 iter), 213.3/232ep, loss = 3.11642
-I0511 10:06:46.456908  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.70813 (* 1 = 2.70813 loss)
-I0511 10:06:46.456918  5307 sgd_solver.cpp:172] Iteration 110300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:07:47.811429  5307 solver.cpp:352] Iteration 110400 (1.6299 iter/s, 61.3535s/100 iter), 213.4/232ep, loss = 3.08903
-I0511 10:07:47.811530  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.70512 (* 1 = 2.70512 loss)
-I0511 10:07:47.811553  5307 sgd_solver.cpp:172] Iteration 110400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:08:48.071257  5307 solver.cpp:352] Iteration 110500 (1.65951 iter/s, 60.2587s/100 iter), 213.6/232ep, loss = 2.86229
-I0511 10:08:48.071324  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.34643 (* 1 = 3.34643 loss)
-I0511 10:08:48.071367  5307 sgd_solver.cpp:172] Iteration 110500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:09:49.470010  5307 solver.cpp:352] Iteration 110600 (1.62872 iter/s, 61.3977s/100 iter), 213.8/232ep, loss = 3.12379
-I0511 10:09:49.470111  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.75619 (* 1 = 2.75619 loss)
-I0511 10:09:49.470121  5307 sgd_solver.cpp:172] Iteration 110600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:10:30.507227  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:10:50.539381  5307 solver.cpp:352] Iteration 110700 (1.63751 iter/s, 61.0683s/100 iter), 214/232ep, loss = 2.99424
-I0511 10:10:50.539412  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89221 (* 1 = 2.89221 loss)
-I0511 10:10:50.539420  5307 sgd_solver.cpp:172] Iteration 110700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:11:52.147364  5307 solver.cpp:352] Iteration 110800 (1.62319 iter/s, 61.6069s/100 iter), 214.2/232ep, loss = 3.14237
-I0511 10:11:52.147531  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.78656 (* 1 = 2.78656 loss)
-I0511 10:11:52.147547  5307 sgd_solver.cpp:172] Iteration 110800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:12:52.570505  5307 solver.cpp:352] Iteration 110900 (1.65502 iter/s, 60.4221s/100 iter), 214.4/232ep, loss = 3.02799
-I0511 10:12:52.570567  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.16478 (* 1 = 2.16478 loss)
-I0511 10:12:52.570576  5307 sgd_solver.cpp:172] Iteration 110900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:13:53.284628  5307 solver.cpp:352] Iteration 111000 (1.64709 iter/s, 60.7131s/100 iter), 214.6/232ep, loss = 2.94168
-I0511 10:13:53.284693  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99242 (* 1 = 2.99242 loss)
-I0511 10:13:53.284700  5307 sgd_solver.cpp:172] Iteration 111000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:14:53.858494  5307 solver.cpp:352] Iteration 111100 (1.65091 iter/s, 60.5728s/100 iter), 214.8/232ep, loss = 2.93955
-I0511 10:14:53.858589  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.69679 (* 1 = 2.69679 loss)
-I0511 10:14:53.858608  5307 sgd_solver.cpp:172] Iteration 111100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:15:44.839627  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:15:55.098361  5307 solver.cpp:352] Iteration 111200 (1.63295 iter/s, 61.2388s/100 iter), 215/232ep, loss = 2.86403
-I0511 10:15:55.098414  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10467 (* 1 = 3.10467 loss)
-I0511 10:15:55.098424  5307 sgd_solver.cpp:172] Iteration 111200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:16:55.731014  5307 solver.cpp:352] Iteration 111300 (1.6493 iter/s, 60.6316s/100 iter), 215.2/232ep, loss = 3.04527
-I0511 10:16:55.731109  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95204 (* 1 = 2.95204 loss)
-I0511 10:16:55.731127  5307 sgd_solver.cpp:172] Iteration 111300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:17:56.691306  5307 solver.cpp:352] Iteration 111400 (1.64044 iter/s, 60.9592s/100 iter), 215.4/232ep, loss = 2.94958
-I0511 10:17:56.691378  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11284 (* 1 = 3.11284 loss)
-I0511 10:17:56.691396  5307 sgd_solver.cpp:172] Iteration 111400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:18:57.145282  5307 solver.cpp:352] Iteration 111500 (1.65418 iter/s, 60.4529s/100 iter), 215.6/232ep, loss = 3.01524
-I0511 10:18:57.145421  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94067 (* 1 = 2.94067 loss)
-I0511 10:18:57.145431  5307 sgd_solver.cpp:172] Iteration 111500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:19:58.131446  5307 solver.cpp:352] Iteration 111600 (1.63975 iter/s, 60.9851s/100 iter), 215.8/232ep, loss = 2.99065
-I0511 10:19:58.131516  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92307 (* 1 = 2.92307 loss)
-I0511 10:19:58.131525  5307 sgd_solver.cpp:172] Iteration 111600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:20:59.895972  5307 solver.cpp:352] Iteration 111700 (1.61908 iter/s, 61.7634s/100 iter), 216/232ep, loss = 2.88708
-I0511 10:20:59.896270  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.31386 (* 1 = 2.31386 loss)
-I0511 10:20:59.896335  5307 sgd_solver.cpp:172] Iteration 111700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:21:00.557533  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:22:00.743355  5307 solver.cpp:352] Iteration 111800 (1.64349 iter/s, 60.8463s/100 iter), 216.2/232ep, loss = 3.08605
-I0511 10:22:00.746047  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7764 (* 1 = 2.7764 loss)
-I0511 10:22:00.746073  5307 sgd_solver.cpp:172] Iteration 111800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:23:01.987576  5307 solver.cpp:352] Iteration 111900 (1.63284 iter/s, 61.2431s/100 iter), 216.3/232ep, loss = 3.08897
-I0511 10:23:01.987634  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6799 (* 1 = 2.6799 loss)
-I0511 10:23:01.987643  5307 sgd_solver.cpp:172] Iteration 111900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:24:03.145884  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_112000.caffemodel
-I0511 10:24:03.165766  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_112000.solverstate
-I0511 10:24:03.171766  5307 solver.cpp:635] Iteration 112000, Testing net (#0)
-I0511 10:24:43.817241  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:24:44.021019  5307 solver.cpp:747] class AP 1: 0.652025
-I0511 10:24:44.021556  5307 solver.cpp:747] class AP 2: 0.735424
-I0511 10:24:44.027999  5307 solver.cpp:747] class AP 3: 0.562478
-I0511 10:24:44.031703  5307 solver.cpp:747] class AP 4: 0.510381
-I0511 10:24:44.049821  5307 solver.cpp:747] class AP 5: 0.346569
-I0511 10:24:44.050158  5307 solver.cpp:747] class AP 6: 0.736914
-I0511 10:24:44.058876  5307 solver.cpp:747] class AP 7: 0.704268
-I0511 10:24:44.059409  5307 solver.cpp:747] class AP 8: 0.818155
-I0511 10:24:44.077251  5307 solver.cpp:747] class AP 9: 0.431948
-I0511 10:24:44.078028  5307 solver.cpp:747] class AP 10: 0.627871
-I0511 10:24:44.078682  5307 solver.cpp:747] class AP 11: 0.593541
-I0511 10:24:44.079497  5307 solver.cpp:747] class AP 12: 0.724921
-I0511 10:24:44.079932  5307 solver.cpp:747] class AP 13: 0.804708
-I0511 10:24:44.080291  5307 solver.cpp:747] class AP 14: 0.748014
-I0511 10:24:44.131726  5307 solver.cpp:747] class AP 15: 0.726007
-I0511 10:24:44.138413  5307 solver.cpp:747] class AP 16: 0.365348
-I0511 10:24:44.140985  5307 solver.cpp:747] class AP 17: 0.598858
-I0511 10:24:44.141667  5307 solver.cpp:747] class AP 18: 0.608303
-I0511 10:24:44.142585  5307 solver.cpp:747] class AP 19: 0.754497
-I0511 10:24:44.144356  5307 solver.cpp:747] class AP 20: 0.611097
-I0511 10:24:44.144549  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.633066
-I0511 10:24:44.144703  5307 solver.cpp:283] Tests completed in 102.155s
-I0511 10:24:44.779572  5307 solver.cpp:352] Iteration 112000 (0.978902 iter/s, 102.155s/100 iter), 216.5/232ep, loss = 2.84662
-I0511 10:24:44.779598  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99714 (* 1 = 2.99714 loss)
-I0511 10:24:44.779605  5307 sgd_solver.cpp:172] Iteration 112000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:25:45.657253  5307 solver.cpp:352] Iteration 112100 (1.64267 iter/s, 60.8766s/100 iter), 216.7/232ep, loss = 2.94875
-I0511 10:25:45.657313  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73282 (* 1 = 3.73282 loss)
-I0511 10:25:45.657322  5307 sgd_solver.cpp:172] Iteration 112100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:26:47.189956  5307 solver.cpp:352] Iteration 112200 (1.62518 iter/s, 61.5316s/100 iter), 216.9/232ep, loss = 2.94758
-I0511 10:26:47.190044  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77857 (* 1 = 2.77857 loss)
-I0511 10:26:47.190053  5307 sgd_solver.cpp:172] Iteration 112200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:26:58.774957  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:27:48.748471  5307 solver.cpp:352] Iteration 112300 (1.6245 iter/s, 61.5574s/100 iter), 217.1/232ep, loss = 3.19982
-I0511 10:27:48.748627  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.7726 (* 1 = 3.7726 loss)
-I0511 10:27:48.748638  5307 sgd_solver.cpp:172] Iteration 112300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:28:51.163944  5307 solver.cpp:352] Iteration 112400 (1.60219 iter/s, 62.4144s/100 iter), 217.3/232ep, loss = 3.03614
-I0511 10:28:51.166050  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94561 (* 1 = 2.94561 loss)
-I0511 10:28:51.166059  5307 sgd_solver.cpp:172] Iteration 112400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:29:52.775889  5307 solver.cpp:352] Iteration 112500 (1.62309 iter/s, 61.6109s/100 iter), 217.5/232ep, loss = 3.00284
-I0511 10:29:52.775948  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1787 (* 1 = 3.1787 loss)
-I0511 10:29:52.775956  5307 sgd_solver.cpp:172] Iteration 112500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:30:53.999619  5307 solver.cpp:352] Iteration 112600 (1.63338 iter/s, 61.2226s/100 iter), 217.7/232ep, loss = 3.09079
-I0511 10:30:53.999730  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16119 (* 1 = 3.16119 loss)
-I0511 10:30:53.999747  5307 sgd_solver.cpp:172] Iteration 112600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:31:55.897014  5307 solver.cpp:352] Iteration 112700 (1.61561 iter/s, 61.8963s/100 iter), 217.9/232ep, loss = 3.09488
-I0511 10:31:55.899727  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09322 (* 1 = 3.09322 loss)
-I0511 10:31:55.899747  5307 sgd_solver.cpp:172] Iteration 112700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:32:17.061614  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:32:56.688714  5307 solver.cpp:352] Iteration 112800 (1.64499 iter/s, 60.7906s/100 iter), 218.1/232ep, loss = 2.89371
-I0511 10:32:56.688843  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51754 (* 1 = 2.51754 loss)
-I0511 10:32:56.688855  5307 sgd_solver.cpp:172] Iteration 112800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:33:57.503278  5307 solver.cpp:352] Iteration 112900 (1.64437 iter/s, 60.8135s/100 iter), 218.3/232ep, loss = 3.04521
-I0511 10:33:57.503353  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81041 (* 1 = 2.81041 loss)
-I0511 10:33:57.503362  5307 sgd_solver.cpp:172] Iteration 112900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:34:58.744582  5307 solver.cpp:352] Iteration 113000 (1.63291 iter/s, 61.2402s/100 iter), 218.5/232ep, loss = 3.17241
-I0511 10:34:58.744669  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21981 (* 1 = 3.21981 loss)
-I0511 10:34:58.744678  5307 sgd_solver.cpp:172] Iteration 113000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:35:59.644662  5307 solver.cpp:352] Iteration 113100 (1.64206 iter/s, 60.899s/100 iter), 218.7/232ep, loss = 2.95082
-I0511 10:35:59.644762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39512 (* 1 = 3.39512 loss)
-I0511 10:35:59.644781  5307 sgd_solver.cpp:172] Iteration 113100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:37:00.493922  5307 solver.cpp:352] Iteration 113200 (1.64343 iter/s, 60.8482s/100 iter), 218.9/232ep, loss = 2.90385
-I0511 10:37:00.494029  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05948 (* 1 = 3.05948 loss)
-I0511 10:37:00.494048  5307 sgd_solver.cpp:172] Iteration 113200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:37:33.207693  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:38:01.939122  5307 solver.cpp:352] Iteration 113300 (1.6275 iter/s, 61.4441s/100 iter), 219.1/232ep, loss = 2.96832
-I0511 10:38:01.939155  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38524 (* 1 = 3.38524 loss)
-I0511 10:38:01.939164  5307 sgd_solver.cpp:172] Iteration 113300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:39:02.934594  5307 solver.cpp:352] Iteration 113400 (1.6395 iter/s, 60.9944s/100 iter), 219.2/232ep, loss = 2.95074
-I0511 10:39:02.934692  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87529 (* 1 = 2.87529 loss)
-I0511 10:39:02.934710  5307 sgd_solver.cpp:172] Iteration 113400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:40:03.528507  5307 solver.cpp:352] Iteration 113500 (1.65036 iter/s, 60.5928s/100 iter), 219.4/232ep, loss = 3.19723
-I0511 10:40:03.533421  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77092 (* 1 = 2.77092 loss)
-I0511 10:40:03.533440  5307 sgd_solver.cpp:172] Iteration 113500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:41:03.971828  5307 solver.cpp:352] Iteration 113600 (1.65447 iter/s, 60.4422s/100 iter), 219.6/232ep, loss = 2.86982
-I0511 10:41:03.972090  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33419 (* 1 = 3.33419 loss)
-I0511 10:41:03.972113  5307 sgd_solver.cpp:172] Iteration 113600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:42:05.621686  5307 solver.cpp:352] Iteration 113700 (1.62209 iter/s, 61.6487s/100 iter), 219.8/232ep, loss = 3.13368
-I0511 10:42:05.621779  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.27146 (* 1 = 2.27146 loss)
-I0511 10:42:05.621790  5307 sgd_solver.cpp:172] Iteration 113700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:42:48.676345  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:43:06.615356  5307 solver.cpp:352] Iteration 113800 (1.63955 iter/s, 60.9925s/100 iter), 220/232ep, loss = 2.8886
-I0511 10:43:06.615412  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03967 (* 1 = 3.03967 loss)
-I0511 10:43:06.615424  5307 sgd_solver.cpp:172] Iteration 113800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:44:08.389992  5307 solver.cpp:352] Iteration 113900 (1.61882 iter/s, 61.7735s/100 iter), 220.2/232ep, loss = 2.9446
-I0511 10:44:08.390053  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37132 (* 1 = 3.37132 loss)
-I0511 10:44:08.390061  5307 sgd_solver.cpp:172] Iteration 113900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:45:08.962965  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_114000.caffemodel
-I0511 10:45:08.976925  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_114000.solverstate
-I0511 10:45:08.981122  5307 solver.cpp:635] Iteration 114000, Testing net (#0)
-I0511 10:45:49.198523  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:45:49.415805  5307 solver.cpp:747] class AP 1: 0.662198
-I0511 10:45:49.416313  5307 solver.cpp:747] class AP 2: 0.729406
-I0511 10:45:49.422883  5307 solver.cpp:747] class AP 3: 0.557192
-I0511 10:45:49.426580  5307 solver.cpp:747] class AP 4: 0.507719
-I0511 10:45:49.445612  5307 solver.cpp:747] class AP 5: 0.345573
-I0511 10:45:49.445950  5307 solver.cpp:747] class AP 6: 0.74042
-I0511 10:45:49.454557  5307 solver.cpp:747] class AP 7: 0.705059
-I0511 10:45:49.455088  5307 solver.cpp:747] class AP 8: 0.816973
-I0511 10:45:49.473081  5307 solver.cpp:747] class AP 9: 0.431518
-I0511 10:45:49.473772  5307 solver.cpp:747] class AP 10: 0.628521
-I0511 10:45:49.474426  5307 solver.cpp:747] class AP 11: 0.587503
-I0511 10:45:49.475253  5307 solver.cpp:747] class AP 12: 0.720823
-I0511 10:45:49.475683  5307 solver.cpp:747] class AP 13: 0.790295
-I0511 10:45:49.476042  5307 solver.cpp:747] class AP 14: 0.743502
-I0511 10:45:49.524214  5307 solver.cpp:747] class AP 15: 0.723762
-I0511 10:45:49.530274  5307 solver.cpp:747] class AP 16: 0.361899
-I0511 10:45:49.532704  5307 solver.cpp:747] class AP 17: 0.596467
-I0511 10:45:49.533264  5307 solver.cpp:747] class AP 18: 0.607036
-I0511 10:45:49.533893  5307 solver.cpp:747] class AP 19: 0.745844
-I0511 10:45:49.535290  5307 solver.cpp:747] class AP 20: 0.614507
-I0511 10:45:49.535298  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.630811
-I0511 10:45:49.535538  5307 solver.cpp:283] Tests completed in 101.144s
-I0511 10:45:50.078846  5307 solver.cpp:352] Iteration 114000 (0.988692 iter/s, 101.144s/100 iter), 220.4/232ep, loss = 3.01824
-I0511 10:45:50.078913  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92418 (* 1 = 2.92418 loss)
-I0511 10:45:50.079262  5307 sgd_solver.cpp:172] Iteration 114000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:46:51.070911  5307 solver.cpp:352] Iteration 114100 (1.63959 iter/s, 60.9909s/100 iter), 220.6/232ep, loss = 2.88598
-I0511 10:46:51.071024  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1741 (* 1 = 3.1741 loss)
-I0511 10:46:51.071035  5307 sgd_solver.cpp:172] Iteration 114100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:47:52.394845  5307 solver.cpp:352] Iteration 114200 (1.63071 iter/s, 61.3228s/100 iter), 220.8/232ep, loss = 2.99809
-I0511 10:47:52.394902  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.29741 (* 1 = 3.29741 loss)
-I0511 10:47:52.394942  5307 sgd_solver.cpp:172] Iteration 114200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:48:46.215500  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:48:53.950975  5307 solver.cpp:352] Iteration 114300 (1.62456 iter/s, 61.555s/100 iter), 221/232ep, loss = 2.97063
-I0511 10:48:53.951047  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.24911 (* 1 = 3.24911 loss)
-I0511 10:48:53.951067  5307 sgd_solver.cpp:172] Iteration 114300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:49:54.352638  5307 solver.cpp:352] Iteration 114400 (1.65561 iter/s, 60.4006s/100 iter), 221.2/232ep, loss = 2.91539
-I0511 10:49:54.353127  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65132 (* 1 = 3.65132 loss)
-I0511 10:49:54.353137  5307 sgd_solver.cpp:172] Iteration 114400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:50:55.012678  5307 solver.cpp:352] Iteration 114500 (1.64856 iter/s, 60.659s/100 iter), 221.4/232ep, loss = 2.86124
-I0511 10:50:55.012753  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.58102 (* 1 = 2.58102 loss)
-I0511 10:50:55.012768  5307 sgd_solver.cpp:172] Iteration 114500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:51:56.122793  5307 solver.cpp:352] Iteration 114600 (1.63642 iter/s, 61.109s/100 iter), 221.6/232ep, loss = 3.12296
-I0511 10:51:56.122936  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54923 (* 1 = 3.54923 loss)
-I0511 10:51:56.122951  5307 sgd_solver.cpp:172] Iteration 114600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:52:58.023329  5307 solver.cpp:352] Iteration 114700 (1.61552 iter/s, 61.8994s/100 iter), 221.8/232ep, loss = 2.80427
-I0511 10:52:58.023398  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63464 (* 1 = 2.63464 loss)
-I0511 10:52:58.023407  5307 sgd_solver.cpp:172] Iteration 114700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:53:59.532196  5307 solver.cpp:352] Iteration 114800 (1.62581 iter/s, 61.5078s/100 iter), 222/232ep, loss = 2.89953
-I0511 10:53:59.532305  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07735 (* 1 = 3.07735 loss)
-I0511 10:53:59.532322  5307 sgd_solver.cpp:172] Iteration 114800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:54:02.501703  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:55:02.028355  5307 solver.cpp:352] Iteration 114900 (1.60013 iter/s, 62.4951s/100 iter), 222.1/232ep, loss = 2.98781
-I0511 10:55:02.028434  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15999 (* 1 = 3.15999 loss)
-I0511 10:55:02.028443  5307 sgd_solver.cpp:172] Iteration 114900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:56:03.357002  5307 solver.cpp:352] Iteration 115000 (1.63059 iter/s, 61.3276s/100 iter), 222.3/232ep, loss = 3.05279
-I0511 10:56:03.364600  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.97168 (* 1 = 1.97168 loss)
-I0511 10:56:03.364627  5307 sgd_solver.cpp:172] Iteration 115000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:57:05.293462  5307 solver.cpp:352] Iteration 115100 (1.61459 iter/s, 61.9354s/100 iter), 222.5/232ep, loss = 2.94648
-I0511 10:57:05.293543  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89315 (* 1 = 2.89315 loss)
-I0511 10:57:05.293552  5307 sgd_solver.cpp:172] Iteration 115100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:58:06.643431  5307 solver.cpp:352] Iteration 115200 (1.63002 iter/s, 61.3489s/100 iter), 222.7/232ep, loss = 2.99899
-I0511 10:58:06.643540  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.02968 (* 1 = 3.02968 loss)
-I0511 10:58:06.643551  5307 sgd_solver.cpp:172] Iteration 115200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:59:08.695617  5307 solver.cpp:352] Iteration 115300 (1.61158 iter/s, 62.0511s/100 iter), 222.9/232ep, loss = 3.02161
-I0511 10:59:08.695713  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39698 (* 1 = 3.39698 loss)
-I0511 10:59:08.695724  5307 sgd_solver.cpp:172] Iteration 115300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:59:21.704402  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:00:09.808604  5307 solver.cpp:352] Iteration 115400 (1.63634 iter/s, 61.1119s/100 iter), 223.1/232ep, loss = 2.98201
-I0511 11:00:09.808735  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65728 (* 1 = 2.65728 loss)
-I0511 11:00:09.808758  5307 sgd_solver.cpp:172] Iteration 115400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:01:10.817817  5307 solver.cpp:352] Iteration 115500 (1.63913 iter/s, 61.0081s/100 iter), 223.3/232ep, loss = 2.86876
-I0511 11:01:10.817908  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74372 (* 1 = 3.74372 loss)
-I0511 11:01:10.817925  5307 sgd_solver.cpp:172] Iteration 115500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:02:12.303939  5307 solver.cpp:352] Iteration 115600 (1.62641 iter/s, 61.485s/100 iter), 223.5/232ep, loss = 2.99374
-I0511 11:02:12.307034  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.66607 (* 1 = 2.66607 loss)
-I0511 11:02:12.307056  5307 sgd_solver.cpp:172] Iteration 115600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:03:12.455924  5307 solver.cpp:352] Iteration 115700 (1.66249 iter/s, 60.1509s/100 iter), 223.7/232ep, loss = 3.09511
-I0511 11:03:12.455989  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1523 (* 1 = 3.1523 loss)
-I0511 11:03:12.455998  5307 sgd_solver.cpp:172] Iteration 115700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:04:13.109742  5307 solver.cpp:352] Iteration 115800 (1.64873 iter/s, 60.6527s/100 iter), 223.9/232ep, loss = 2.8967
-I0511 11:04:13.109834  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7674 (* 1 = 2.7674 loss)
-I0511 11:04:13.109855  5307 sgd_solver.cpp:172] Iteration 115800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:04:37.028450  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:05:14.281826  5307 solver.cpp:352] Iteration 115900 (1.63476 iter/s, 61.171s/100 iter), 224.1/232ep, loss = 2.95257
-I0511 11:05:14.281886  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.62779 (* 1 = 2.62779 loss)
-I0511 11:05:14.281895  5307 sgd_solver.cpp:172] Iteration 115900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:06:14.788892  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_116000.caffemodel
-I0511 11:06:14.807366  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_116000.solverstate
-I0511 11:06:14.813482  5307 solver.cpp:635] Iteration 116000, Testing net (#0)
-I0511 11:06:55.290019  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:06:55.517653  5307 solver.cpp:747] class AP 1: 0.650297
-I0511 11:06:55.518486  5307 solver.cpp:747] class AP 2: 0.731171
-I0511 11:06:55.527159  5307 solver.cpp:747] class AP 3: 0.55694
-I0511 11:06:55.532552  5307 solver.cpp:747] class AP 4: 0.516235
-I0511 11:06:55.556718  5307 solver.cpp:747] class AP 5: 0.347945
-I0511 11:06:55.557184  5307 solver.cpp:747] class AP 6: 0.737584
-I0511 11:06:55.568270  5307 solver.cpp:747] class AP 7: 0.704858
-I0511 11:06:55.569039  5307 solver.cpp:747] class AP 8: 0.81655
-I0511 11:06:55.593116  5307 solver.cpp:747] class AP 9: 0.433403
-I0511 11:06:55.593871  5307 solver.cpp:747] class AP 10: 0.627933
-I0511 11:06:55.594524  5307 solver.cpp:747] class AP 11: 0.592362
-I0511 11:06:55.595378  5307 solver.cpp:747] class AP 12: 0.722884
-I0511 11:06:55.595813  5307 solver.cpp:747] class AP 13: 0.802147
-I0511 11:06:55.596138  5307 solver.cpp:747] class AP 14: 0.744025
-I0511 11:06:55.643785  5307 solver.cpp:747] class AP 15: 0.726057
-I0511 11:06:55.650180  5307 solver.cpp:747] class AP 16: 0.359646
-I0511 11:06:55.652637  5307 solver.cpp:747] class AP 17: 0.594529
-I0511 11:06:55.653204  5307 solver.cpp:747] class AP 18: 0.609831
-I0511 11:06:55.653875  5307 solver.cpp:747] class AP 19: 0.743373
-I0511 11:06:55.655283  5307 solver.cpp:747] class AP 20: 0.619952
-I0511 11:06:55.655295  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631886
-I0511 11:06:55.655506  5307 solver.cpp:283] Tests completed in 101.372s
-I0511 11:06:56.292500  5307 solver.cpp:352] Iteration 116000 (0.986467 iter/s, 101.372s/100 iter), 224.3/232ep, loss = 3.11957
-I0511 11:06:56.292546  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71054 (* 1 = 2.71054 loss)
-I0511 11:06:56.292552  5307 sgd_solver.cpp:172] Iteration 116000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:08:02.647570  5307 solver.cpp:352] Iteration 116100 (1.50707 iter/s, 66.3538s/100 iter), 224.5/232ep, loss = 3.17559
-I0511 11:08:02.647683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4876 (* 1 = 3.4876 loss)
-I0511 11:08:02.647696  5307 sgd_solver.cpp:172] Iteration 116100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:09:08.393443  5307 solver.cpp:352] Iteration 116200 (1.52104 iter/s, 65.7447s/100 iter), 224.7/232ep, loss = 2.99814
-I0511 11:09:08.396077  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22462 (* 1 = 3.22462 loss)
-I0511 11:09:08.396090  5307 sgd_solver.cpp:172] Iteration 116200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:10:09.231055  5307 solver.cpp:352] Iteration 116300 (1.64375 iter/s, 60.8365s/100 iter), 224.9/232ep, loss = 3.04884
-I0511 11:10:09.231128  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.9264 (* 1 = 3.9264 loss)
-I0511 11:10:09.231138  5307 sgd_solver.cpp:172] Iteration 116300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:10:43.547654  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:11:09.930076  5307 solver.cpp:352] Iteration 116400 (1.6475 iter/s, 60.6979s/100 iter), 225/232ep, loss = 3.0008
-I0511 11:11:09.930106  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90725 (* 1 = 2.90725 loss)
-I0511 11:11:09.930115  5307 sgd_solver.cpp:172] Iteration 116400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:12:09.585803  5307 solver.cpp:352] Iteration 116500 (1.67631 iter/s, 59.6547s/100 iter), 225.2/232ep, loss = 3.17016
-I0511 11:12:09.585994  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.0389 (* 1 = 3.0389 loss)
-I0511 11:12:09.586025  5307 sgd_solver.cpp:172] Iteration 116500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:13:10.186215  5307 solver.cpp:352] Iteration 116600 (1.65018 iter/s, 60.5993s/100 iter), 225.4/232ep, loss = 2.88852
-I0511 11:13:10.186285  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.17429 (* 1 = 3.17429 loss)
-I0511 11:13:10.186295  5307 sgd_solver.cpp:172] Iteration 116600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:14:09.787925  5307 solver.cpp:352] Iteration 116700 (1.67783 iter/s, 59.6007s/100 iter), 225.6/232ep, loss = 3.10487
-I0511 11:14:09.788018  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28151 (* 1 = 3.28151 loss)
-I0511 11:14:09.788035  5307 sgd_solver.cpp:172] Iteration 116700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:15:11.139684  5307 solver.cpp:352] Iteration 116800 (1.62997 iter/s, 61.3507s/100 iter), 225.8/232ep, loss = 3.23564
-I0511 11:15:11.139751  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.45886 (* 1 = 3.45886 loss)
-I0511 11:15:11.139758  5307 sgd_solver.cpp:172] Iteration 116800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:15:55.356794  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:16:11.635367  5307 solver.cpp:352] Iteration 116900 (1.65304 iter/s, 60.4946s/100 iter), 226/232ep, loss = 3.05684
-I0511 11:16:11.635630  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91783 (* 1 = 2.91783 loss)
-I0511 11:16:11.635658  5307 sgd_solver.cpp:172] Iteration 116900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:17:12.995401  5307 solver.cpp:352] Iteration 117000 (1.62975 iter/s, 61.359s/100 iter), 226.2/232ep, loss = 2.99461
-I0511 11:17:12.995496  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50326 (* 1 = 3.50326 loss)
-I0511 11:17:12.995514  5307 sgd_solver.cpp:172] Iteration 117000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:18:13.218389  5307 solver.cpp:352] Iteration 117100 (1.66052 iter/s, 60.2219s/100 iter), 226.4/232ep, loss = 3.03247
-I0511 11:18:13.218454  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68845 (* 1 = 3.68845 loss)
-I0511 11:18:13.218463  5307 sgd_solver.cpp:172] Iteration 117100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:19:13.291749  5307 solver.cpp:352] Iteration 117200 (1.66466 iter/s, 60.0723s/100 iter), 226.6/232ep, loss = 2.87023
-I0511 11:19:13.291846  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85732 (* 1 = 2.85732 loss)
-I0511 11:19:13.291857  5307 sgd_solver.cpp:172] Iteration 117200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:20:13.224674  5307 solver.cpp:352] Iteration 117300 (1.66856 iter/s, 59.9319s/100 iter), 226.8/232ep, loss = 2.96887
-I0511 11:20:13.225811  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.86509 (* 1 = 1.86509 loss)
-I0511 11:20:13.225838  5307 sgd_solver.cpp:172] Iteration 117300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:21:08.103113  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:21:13.299240  5307 solver.cpp:352] Iteration 117400 (1.66463 iter/s, 60.0735s/100 iter), 227/232ep, loss = 3.09113
-I0511 11:21:13.299270  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.52411 (* 1 = 2.52411 loss)
-I0511 11:21:13.299278  5307 sgd_solver.cpp:172] Iteration 117400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:22:13.700301  5307 solver.cpp:352] Iteration 117500 (1.65563 iter/s, 60.4s/100 iter), 227.2/232ep, loss = 3.03423
-I0511 11:22:13.700546  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85504 (* 1 = 3.85504 loss)
-I0511 11:22:13.700562  5307 sgd_solver.cpp:172] Iteration 117500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:23:14.520663  5307 solver.cpp:352] Iteration 117600 (1.64422 iter/s, 60.8193s/100 iter), 227.4/232ep, loss = 2.91665
-I0511 11:23:14.520825  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.40878 (* 1 = 2.40878 loss)
-I0511 11:23:14.520834  5307 sgd_solver.cpp:172] Iteration 117600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:24:15.486469  5307 solver.cpp:352] Iteration 117700 (1.64029 iter/s, 60.9647s/100 iter), 227.6/232ep, loss = 3.19194
-I0511 11:24:15.486999  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.24722 (* 1 = 3.24722 loss)
-I0511 11:24:15.487007  5307 sgd_solver.cpp:172] Iteration 117700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:25:16.517316  5307 solver.cpp:352] Iteration 117800 (1.63855 iter/s, 61.0297s/100 iter), 227.8/232ep, loss = 2.87382
-I0511 11:25:16.517437  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81489 (* 1 = 2.81489 loss)
-I0511 11:25:16.517447  5307 sgd_solver.cpp:172] Iteration 117800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:26:16.765038  5307 solver.cpp:352] Iteration 117900 (1.65984 iter/s, 60.2466s/100 iter), 227.9/232ep, loss = 2.99439
-I0511 11:26:16.765139  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.282 (* 1 = 2.282 loss)
-I0511 11:26:16.765159  5307 sgd_solver.cpp:172] Iteration 117900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:26:21.159152  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:27:17.238680  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_118000.caffemodel
-I0511 11:27:17.257541  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_118000.solverstate
-I0511 11:27:17.263979  5307 solver.cpp:635] Iteration 118000, Testing net (#0)
-I0511 11:27:57.641331  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:27:57.861429  5307 solver.cpp:747] class AP 1: 0.654472
-I0511 11:27:57.861944  5307 solver.cpp:747] class AP 2: 0.731609
-I0511 11:27:57.868554  5307 solver.cpp:747] class AP 3: 0.557668
-I0511 11:27:57.872315  5307 solver.cpp:747] class AP 4: 0.517042
-I0511 11:27:57.891069  5307 solver.cpp:747] class AP 5: 0.345227
-I0511 11:27:57.891412  5307 solver.cpp:747] class AP 6: 0.738804
-I0511 11:27:57.900190  5307 solver.cpp:747] class AP 7: 0.703705
-I0511 11:27:57.900959  5307 solver.cpp:747] class AP 8: 0.817978
-I0511 11:27:57.920097  5307 solver.cpp:747] class AP 9: 0.430764
-I0511 11:27:57.920806  5307 solver.cpp:747] class AP 10: 0.635427
-I0511 11:27:57.921437  5307 solver.cpp:747] class AP 11: 0.594552
-I0511 11:27:57.922281  5307 solver.cpp:747] class AP 12: 0.719994
-I0511 11:27:57.922788  5307 solver.cpp:747] class AP 13: 0.788424
-I0511 11:27:57.923264  5307 solver.cpp:747] class AP 14: 0.745163
-I0511 11:27:57.972834  5307 solver.cpp:747] class AP 15: 0.725318
-I0511 11:27:57.979189  5307 solver.cpp:747] class AP 16: 0.368298
-I0511 11:27:57.981844  5307 solver.cpp:747] class AP 17: 0.596233
-I0511 11:27:57.982441  5307 solver.cpp:747] class AP 18: 0.610433
-I0511 11:27:57.983145  5307 solver.cpp:747] class AP 19: 0.751794
-I0511 11:27:57.984674  5307 solver.cpp:747] class AP 20: 0.617365
-I0511 11:27:57.984683  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.632513
-I0511 11:27:57.984807  5307 solver.cpp:283] Tests completed in 101.218s
-I0511 11:27:58.641021  5307 solver.cpp:352] Iteration 118000 (0.987967 iter/s, 101.218s/100 iter), 228.1/232ep, loss = 2.9497
-I0511 11:27:58.641055  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.12983 (* 1 = 3.12983 loss)
-I0511 11:27:58.641063  5307 sgd_solver.cpp:172] Iteration 118000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:28:58.839681  5307 solver.cpp:352] Iteration 118100 (1.6612 iter/s, 60.1975s/100 iter), 228.3/232ep, loss = 3.24715
-I0511 11:28:58.839756  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65285 (* 1 = 3.65285 loss)
-I0511 11:28:58.839774  5307 sgd_solver.cpp:172] Iteration 118100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:30:00.189913  5307 solver.cpp:352] Iteration 118200 (1.63002 iter/s, 61.3491s/100 iter), 228.5/232ep, loss = 2.8064
-I0511 11:30:00.191293  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91214 (* 1 = 2.91214 loss)
-I0511 11:30:00.191314  5307 sgd_solver.cpp:172] Iteration 118200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:31:00.269927  5307 solver.cpp:352] Iteration 118300 (1.66448 iter/s, 60.0789s/100 iter), 228.7/232ep, loss = 3.06632
-I0511 11:31:00.270061  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44544 (* 1 = 3.44544 loss)
-I0511 11:31:00.270086  5307 sgd_solver.cpp:172] Iteration 118300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:32:01.229151  5307 solver.cpp:352] Iteration 118400 (1.64047 iter/s, 60.9581s/100 iter), 228.9/232ep, loss = 2.92896
-I0511 11:32:01.229290  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68048 (* 1 = 3.68048 loss)
-I0511 11:32:01.229305  5307 sgd_solver.cpp:172] Iteration 118400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:32:16.214731  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:33:01.567019  5307 solver.cpp:352] Iteration 118500 (1.65736 iter/s, 60.3368s/100 iter), 229.1/232ep, loss = 3.13304
-I0511 11:33:01.567117  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15197 (* 1 = 3.15197 loss)
-I0511 11:33:01.567138  5307 sgd_solver.cpp:172] Iteration 118500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:34:01.775032  5307 solver.cpp:352] Iteration 118600 (1.66094 iter/s, 60.207s/100 iter), 229.3/232ep, loss = 3.0296
-I0511 11:34:01.775141  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71965 (* 1 = 2.71965 loss)
-I0511 11:34:01.775158  5307 sgd_solver.cpp:172] Iteration 118600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:35:02.408643  5307 solver.cpp:352] Iteration 118700 (1.64928 iter/s, 60.6325s/100 iter), 229.5/232ep, loss = 2.91601
-I0511 11:35:02.408749  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7621 (* 1 = 2.7621 loss)
-I0511 11:35:02.408767  5307 sgd_solver.cpp:172] Iteration 118700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:36:03.211777  5307 solver.cpp:352] Iteration 118800 (1.64468 iter/s, 60.8021s/100 iter), 229.7/232ep, loss = 3.03007
-I0511 11:36:03.211851  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71402 (* 1 = 3.71402 loss)
-I0511 11:36:03.211863  5307 sgd_solver.cpp:172] Iteration 118800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:37:03.776070  5307 solver.cpp:352] Iteration 118900 (1.65117 iter/s, 60.5632s/100 iter), 229.9/232ep, loss = 2.9015
-I0511 11:37:03.776235  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77313 (* 1 = 2.77313 loss)
-I0511 11:37:03.776248  5307 sgd_solver.cpp:172] Iteration 118900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:37:29.550253  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:38:03.689391  5307 solver.cpp:352] Iteration 119000 (1.66911 iter/s, 59.9123s/100 iter), 230.1/232ep, loss = 2.88679
-I0511 11:38:03.689962  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22293 (* 1 = 3.22293 loss)
-I0511 11:38:03.690055  5307 sgd_solver.cpp:172] Iteration 119000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:39:03.612455  5307 solver.cpp:352] Iteration 119100 (1.66884 iter/s, 59.922s/100 iter), 230.3/232ep, loss = 3.19493
-I0511 11:39:03.612581  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.60366 (* 1 = 2.60366 loss)
-I0511 11:39:03.612608  5307 sgd_solver.cpp:172] Iteration 119100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:40:04.584720  5307 solver.cpp:352] Iteration 119200 (1.64012 iter/s, 60.9712s/100 iter), 230.5/232ep, loss = 3.04357
-I0511 11:40:04.584801  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.52593 (* 1 = 3.52593 loss)
-I0511 11:40:04.584810  5307 sgd_solver.cpp:172] Iteration 119200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:41:06.064980  5307 solver.cpp:352] Iteration 119300 (1.62657 iter/s, 61.4792s/100 iter), 230.7/232ep, loss = 2.91227
-I0511 11:41:06.065052  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.61844 (* 1 = 2.61844 loss)
-I0511 11:41:06.065062  5307 sgd_solver.cpp:172] Iteration 119300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:42:06.932260  5307 solver.cpp:352] Iteration 119400 (1.64295 iter/s, 60.8662s/100 iter), 230.9/232ep, loss = 3.17262
-I0511 11:42:06.932314  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95531 (* 1 = 2.95531 loss)
-I0511 11:42:06.932320  5307 sgd_solver.cpp:172] Iteration 119400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:42:42.828730  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:43:07.304044  5307 solver.cpp:352] Iteration 119500 (1.65643 iter/s, 60.3707s/100 iter), 231/232ep, loss = 2.80561
-I0511 11:43:07.304111  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30471 (* 1 = 3.30471 loss)
-I0511 11:43:07.304133  5307 sgd_solver.cpp:172] Iteration 119500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:44:08.021536  5307 solver.cpp:352] Iteration 119600 (1.647 iter/s, 60.7164s/100 iter), 231.2/232ep, loss = 2.93156
-I0511 11:44:08.021646  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.35993 (* 1 = 2.35993 loss)
-I0511 11:44:08.021667  5307 sgd_solver.cpp:172] Iteration 119600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:45:08.781613  5307 solver.cpp:352] Iteration 119700 (1.64585 iter/s, 60.759s/100 iter), 231.4/232ep, loss = 3.03697
-I0511 11:45:08.781715  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44033 (* 1 = 3.44033 loss)
-I0511 11:45:08.781733  5307 sgd_solver.cpp:172] Iteration 119700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:46:10.104699  5307 solver.cpp:352] Iteration 119800 (1.63074 iter/s, 61.322s/100 iter), 231.6/232ep, loss = 3.10778
-I0511 11:46:10.104800  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.60798 (* 1 = 2.60798 loss)
-I0511 11:46:10.104815  5307 sgd_solver.cpp:172] Iteration 119800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:47:10.143796  5307 solver.cpp:352] Iteration 119900 (1.66561 iter/s, 60.038s/100 iter), 231.8/232ep, loss = 2.83629
-I0511 11:47:10.143863  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14731 (* 1 = 3.14731 loss)
-I0511 11:47:10.143874  5307 sgd_solver.cpp:172] Iteration 119900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:47:56.251756  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:48:09.220212  5307 solver.cpp:352] Iteration 119999 (1.67583 iter/s, 59.0753s/99 iter), 232/232ep, loss = 3.15551
-I0511 11:48:09.220237  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67871 (* 1 = 3.67871 loss)
-I0511 11:48:09.220245  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel
-I0511 11:48:09.232520  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.solverstate
-I0511 11:48:09.280829  5307 solver.cpp:501] Iteration 120000, loss = 3.15029
-I0511 11:48:09.280858  5307 solver.cpp:635] Iteration 120000, Testing net (#0)
-I0511 11:48:49.480348  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:48:49.715391  5307 solver.cpp:747] class AP 1: 0.651863
-I0511 11:48:49.715903  5307 solver.cpp:747] class AP 2: 0.731042
-I0511 11:48:49.722532  5307 solver.cpp:747] class AP 3: 0.56037
-I0511 11:48:49.726208  5307 solver.cpp:747] class AP 4: 0.508346
-I0511 11:48:49.744891  5307 solver.cpp:747] class AP 5: 0.337747
-I0511 11:48:49.745234  5307 solver.cpp:747] class AP 6: 0.737946
-I0511 11:48:49.753764  5307 solver.cpp:747] class AP 7: 0.703266
-I0511 11:48:49.754317  5307 solver.cpp:747] class AP 8: 0.816119
-I0511 11:48:49.772083  5307 solver.cpp:747] class AP 9: 0.429319
-I0511 11:48:49.772775  5307 solver.cpp:747] class AP 10: 0.63832
-I0511 11:48:49.773403  5307 solver.cpp:747] class AP 11: 0.596956
-I0511 11:48:49.774240  5307 solver.cpp:747] class AP 12: 0.725066
-I0511 11:48:49.774662  5307 solver.cpp:747] class AP 13: 0.799125
-I0511 11:48:49.775009  5307 solver.cpp:747] class AP 14: 0.745774
-I0511 11:48:49.823776  5307 solver.cpp:747] class AP 15: 0.727146
-I0511 11:48:49.830077  5307 solver.cpp:747] class AP 16: 0.366462
-I0511 11:48:49.832449  5307 solver.cpp:747] class AP 17: 0.600338
-I0511 11:48:49.833067  5307 solver.cpp:747] class AP 18: 0.609607
-I0511 11:48:49.833757  5307 solver.cpp:747] class AP 19: 0.750236
-I0511 11:48:49.835151  5307 solver.cpp:747] class AP 20: 0.617223
-I0511 11:48:49.835160  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.632614
-I0511 11:48:49.835372  5307 caffe.cpp:268] Solver performance on device 0: 1.589 * 16 = 50.85 img/sec (120000 itr in 7.551e+04 sec)
-I0511 11:48:49.835388  5307 caffe.cpp:271] Optimization Done in 21h 0m 20s

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/run.sh b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/run.sh
deleted file mode 100755 (executable)
index beede8d..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/run.sh
+++ /dev/null
@@ -1,4 +0,0 @@
-/user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin train \
---solver="training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/solver.prototxt" \
---weights="../trained/image_classification/imagenet_mobilenet-0.5/initial/imagenet_mobilenet-0.5_iter_320000.caffemodel" \
---gpu "0" 2>&1 | tee training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/run.log

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/solver.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/solver.prototxt
deleted file mode 100755 (executable)
index 4674ecd..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/solver.prototxt
+++ /dev/null
@@ -1,30 +0,0 @@
-train_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/train.prototxt"
-test_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/test.prototxt"
-test_iter: 619
-test_interval: 2000
-base_lr: 0.01
-display: 100
-max_iter: 120000
-lr_policy: "multistep"
-gamma: 0.1
-power: 1.0
-momentum: 0.9
-weight_decay: 0.0001
-snapshot: 2000
-snapshot_prefix: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5"
-solver_mode: GPU
-device_id: 0
-random_seed: 33
-debug_info: false
-snapshot_after_train: true
-test_initialization: true
-average_loss: 10
-stepvalue: 60000
-stepvalue: 90000
-stepvalue: 300000
-iter_size: 2
-type: "SGD"
-eval_type: "detection"
-ap_version: "11point"
-show_per_class_result: true
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/test.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/test.prototxt
deleted file mode 100755 (executable)
index dfdd513..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/test.prototxt
+++ /dev/null
@@ -1,2419 +0,0 @@
-name: "mobiledetnet-0.5_test"
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 8
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
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-      type: "msra"
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
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-  type: "Scale"
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-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
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-layer {
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-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
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-  }
-  convolution_param {
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-    pad: 0
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-    stride: 1
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-layer {
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-  top: "conv2_1/sep"
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-layer {
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-  top: "conv2_1/sep"
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-layer {
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-  param {
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-    decay_mult: 0.01
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-    weight_filler {
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-layer {
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-layer {
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-layer {
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-  top: "conv2_2/sep"
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-layer {
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-  type: "ReLU"
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-}
-layer {
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-layer {
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-    bias_term: false
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-layer {
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-  top: "conv3_1/sep"
-}
-layer {
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-  param {
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-  }
-  convolution_param {
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-    pad: 1
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-    stride: 2
-    weight_filler {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-  convolution_param {
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-layer {
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-  }
-  convolution_param {
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-layer {
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-layer {
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-  }
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-layer {
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-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
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-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    pad: 1
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-    group: 512
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-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
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-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    pad: 0
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
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-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
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-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
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-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
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-    decay_mult: 0
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-layer {
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-  top: "ctx_output1/1x1"
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-}
-layer {
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-}
-layer {
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-  top: "ctx_output1"
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-  param {
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-layer {
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-layer {
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-layer {
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-  top: "ctx_output2/1x1"
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-layer {
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-layer {
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-layer {
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-  top: "ctx_output2"
-  param {
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-layer {
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-layer {
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-layer {
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-  top: "ctx_output3/1x1"
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-layer {
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-layer {
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-layer {
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-  top: "ctx_output3"
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-layer {
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-layer {
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-  top: "ctx_output4/1x1"
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-layer {
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-  top: "ctx_output4/1x1"
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-layer {
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-  top: "ctx_output4/1x1"
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-layer {
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-  top: "ctx_output4"
-  param {
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-layer {
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-  top: "ctx_output4"
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-layer {
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-  top: "ctx_output5/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-layer {
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-  top: "ctx_output5/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
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-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19.0
-    max_size: 88.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output2"
-  bottom: "data"
-  top: "ctx_output2/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 88.0
-    max_size: 157.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_loc"
-  top: "ctx_output3/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_loc_perm"
-  top: "ctx_output3/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_conf"
-  top: "ctx_output3/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_conf_perm"
-  top: "ctx_output3/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output3"
-  bottom: "data"
-  top: "ctx_output3/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 157.0
-    max_size: 226.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_loc"
-  top: "ctx_output4/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_loc_perm"
-  top: "ctx_output4/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_conf"
-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_conf_perm"
-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output4"
-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 226.0
-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_reshape"
-  type: "Reshape"
-  bottom: "mbox_conf"
-  top: "mbox_conf_reshape"
-  reshape_param {
-    shape {
-      dim: 0
-      dim: -1
-      dim: 21
-    }
-  }
-}
-layer {
-  name: "mbox_conf_softmax"
-  type: "Softmax"
-  bottom: "mbox_conf_reshape"
-  top: "mbox_conf_softmax"
-  softmax_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_flatten"
-  type: "Flatten"
-  bottom: "mbox_conf_softmax"
-  top: "mbox_conf_flatten"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "detection_out"
-  type: "DetectionOutput"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf_flatten"
-  bottom: "mbox_priorbox"
-  top: "detection_out"
-  include {
-    phase: TEST
-  }
-  detection_output_param {
-    num_classes: 21
-    share_location: true
-    background_label_id: 0
-    nms_param {
-      nms_threshold: 0.45
-      top_k: 400
-    }
-    save_output_param {
-      output_directory: ""
-      output_name_prefix: "comp4_det_test_"
-      output_format: "VOC"
-      label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-      name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-      num_test_image: 4952
-    }
-    code_type: CENTER_SIZE
-    keep_top_k: 200
-    confidence_threshold: 0.01
-  }
-}
-layer {
-  name: "detection_eval"
-  type: "DetectionEvaluate"
-  bottom: "detection_out"
-  bottom: "label"
-  top: "detection_eval"
-  include {
-    phase: TEST
-  }
-  detection_evaluate_param {
-    num_classes: 21
-    background_label_id: 0
-    overlap_threshold: 0.5
-    evaluate_difficult_gt: false
-    name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/train.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/train.prototxt
deleted file mode 100755 (executable)
index 63b33c1..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/train.prototxt
+++ /dev/null
@@ -1,2482 +0,0 @@
-name: "mobiledetnet-0.5"
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TRAIN
-  }
-  transform_param {
-    mirror: true
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-      interp_mode: AREA
-      interp_mode: NEAREST
-      interp_mode: CUBIC
-      interp_mode: LANCZOS4
-    }
-    emit_constraint {
-      emit_type: CENTER
-    }
-    crop_h: 256
-    crop_w: 512
-    distort_param {
-      brightness_prob: 0.5
-      brightness_delta: 32
-      contrast_prob: 0.5
-      contrast_lower: 0.5
-      contrast_upper: 1.5
-      hue_prob: 0.5
-      hue_delta: 18
-      saturation_prob: 0.5
-      saturation_lower: 0.5
-      saturation_upper: 1.5
-      random_order_prob: 0.0
-    }
-    expand_param {
-      prob: 0.5
-      max_expand_ratio: 4.0
-    }
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb"
-    batch_size: 16
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-      max_sample: 1
-      max_trials: 1
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.1
-      }
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-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
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-    }
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-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/dw/scale"
-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
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-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
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-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    weight_filler {
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-    }
-    bias_filler {
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-    dilation: 1
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    kernel_size: 3
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-    weight_filler {
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-    }
-    bias_filler {
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-layer {
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-  bottom: "ctx_output1"
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-}
-layer {
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-  top: "ctx_output1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
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-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
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-    eps: 0.0001
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-  }
-}
-layer {
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-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    }
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-layer {
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-layer {
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-  top: "ctx_output2"
-}
-layer {
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-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-layer {
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-  top: "ctx_output3/1x1"
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-  }
-}
-layer {
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-  top: "ctx_output3/1x1"
-}
-layer {
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-  top: "ctx_output3"
-  param {
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-  }
-  param {
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-    decay_mult: 0
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-  convolution_param {
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-layer {
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-  top: "ctx_output3"
-  batch_norm_param {
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-}
-layer {
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-  top: "ctx_output3"
-}
-layer {
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-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-layer {
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-  top: "ctx_output4/1x1"
-  batch_norm_param {
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-  }
-}
-layer {
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-  top: "ctx_output4/1x1"
-}
-layer {
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-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    }
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-layer {
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-  top: "ctx_output4"
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-  }
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-layer {
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-  top: "ctx_output4"
-}
-layer {
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-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 0
-    kernel_size: 1
-    group: 1
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-    weight_filler {
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-    }
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-      value: 0
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-    dilation: 1
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-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
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-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-    decay_mult: 0
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-layer {
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-  bottom: "ctx_output5"
-  top: "ctx_output5"
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-    scale_bias: true
-  }
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-layer {
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-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
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-    decay_mult: 1
-  }
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-    }
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
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-    weight_filler {
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-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19.0
-    max_size: 88.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output2"
-  bottom: "data"
-  top: "ctx_output2/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 88.0
-    max_size: 157.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_loc"
-  top: "ctx_output3/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_loc_perm"
-  top: "ctx_output3/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_conf"
-  top: "ctx_output3/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_conf_perm"
-  top: "ctx_output3/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output3"
-  bottom: "data"
-  top: "ctx_output3/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 157.0
-    max_size: 226.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_loc"
-  top: "ctx_output4/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_loc_perm"
-  top: "ctx_output4/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_conf"
-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_conf_perm"
-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output4"
-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 226.0
-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_loss"
-  type: "MultiBoxLoss"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf"
-  bottom: "mbox_priorbox"
-  bottom: "label"
-  top: "mbox_loss"
-  include {
-    phase: TRAIN
-  }
-  propagate_down: true
-  propagate_down: true
-  propagate_down: false
-  propagate_down: false
-  loss_param {
-    normalization: VALID
-  }
-  multibox_loss_param {
-    loc_loss_type: SMOOTH_L1
-    conf_loss_type: SOFTMAX
-    loc_weight: 1.0
-    num_classes: 21
-    share_location: true
-    match_type: PER_PREDICTION
-    overlap_threshold: 0.5
-    use_prior_for_matching: true
-    background_label_id: 0
-    use_difficult_gt: true
-    neg_pos_ratio: 3.0
-    neg_overlap: 0.5
-    code_type: CENTER_SIZE
-    ignore_cross_boundary_bbox: false
-    mining_type: MAX_NEGATIVE
-    ignore_difficult_gt: false
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/train_image_object_detection.sh b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/train_image_object_detection.sh
deleted file mode 100755 (executable)
index c08e0b4..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/train_image_object_detection.sh
+++ /dev/null
@@ -1,360 +0,0 @@
-#!/bin/bash
-
-#-------------------------------------------------------
-DATE_TIME=`date +'%Y%m%d_%H-%M'`
-#-------------------------------------------------------
-
-#------------------------------------------------
-gpus="0" #"0,1" #"0,1,2"   #IMPORTANT: change this to "0" if you have only one GPU and adjust batch_size (below) accordingly
-
-#-------------------------------------------------------
-model_name=ssdJacintoNetV2       #ssdJacintoNetV2  #mobiledetnet-0.5     
-dataset=voc0712                  #voc0712,ti-custom-cfg1,ti-custom-cfg2
-#------------------------------------------------
-
-#Download the pretrained weights
-weights_dst="../trained/image_classification/imagenet_jacintonet11v2/initial/imagenet_jacintonet11v2_iter_320000.caffemodel"
-
-#------------------------------------------------
-#ssd-size:'512x512', '300x300','256x256'
-ssd_size='512x512'
-
-#0:[1,2,1/2] for each reg head, 1:like orig SSD
-aspect_ratios_type=1
-
-#max donwsampling factor: 16,32
-ds_fac=32
-
-#down sampling type: 'DFLT', 'PSP'
-ds_type='PSP'
-
-#regression head at downsamling 8 layer: 0,1 
-reg_head_at_ds8=1
-
-#use concat layers for regression heads
-concat_reg_head=0
-
-#kernel size for mbox_loc, mbox_conf conv
-ker_mbox_loc_conf=3
-
-#if unintialized value: Average of W,H will be used as min dim
-min_dim=-1
-
-#1:model tuned for small objects, 0:model tuned for moderate size object like PASCAL VOC
-small_objs=0
-
-#"step", "multistep", "poly"
-lr_policy="multistep"
-
-#needed for coco training for gray scale images
-force_color=0
-stepvalue3=300000 
-
-#num op ch for mbox layers = num_intermediate/2
-num_intermediate=512
-rhead_name_non_linear=0
-
-#1: difficult GT will be used for eval, 0: difficult GT will not be used for evaluation
-evaluate_difficult_gt=0
-
-#:Experimntal option. Does not have  any effect now.
-ignore_difficult_gt=0
-
-#set to True for VOC0712
-use_difficult_gt=1
-
-#"poly","multistep"
-lr_policy="multistep"
-
-#set it to 4.0 for poly
-power=1.0
-
-#0.0005 (orignal SSD), 0.0001
-weight_decay_L2=0.0001
-
-#0:linear,1:log,2:like original SSD (min/max ratio will be recomputed)
-log_space_steps=2
-min_ratio=10
-max_ratio=90
-
-#1:FC layer like originalk SSD, 0: no FC layer
-fully_conv_at_end=0
-
-#1: connect 3 head in base n/w. Experimental. set it to 0
-base_nw_3_head=0
-
-#1:first head num of op channel same as other layers, 0: first hd double the number of op channel
-first_hd_same_op_ch=1
-
-#To chop of last few heads. It will make max/min size computed based on original number of heads
-chop_num_heads=0
-
-#known issue - use_image_list=0 && shuffle=1 => hang.
-use_image_list=0 
-
-#Note shuffle is used only in training
-shuffle=0        
-
-#sparsity will be induced gradually starting from this value
-sparsity_start_factor=0.5
-#-------------------------------------------------------
-if [ $dataset = "voc0712" ]
-then
-
-  train_data="../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
- 
-  num_test_image=4952
-  num_classes=21
-
-  min_dim=512
-  
-  resize_width=512
-  resize_height=512
-  crop_width=512
-  crop_height=512
-  batch_size=16    #32    #16
-
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=120000    #120000  #64000   #32000
-  stepvalue1=60000   #60000   #32000   #16000
-  stepvalue2=90000   #90000   #48000   #24000
-  base_lr=1e-2       #1e-2    #1e-4    #1e-3
-  
-  #use batch norm ofr mbox layer1:enable,0:disable
-  use_batchnorm_mbox=1
-
-  sparsity_start_factor=0.25 
-
-elif [ $dataset = "ti-custom-cfg1" ]
-then
-  #In V2 removed V153,154(part of TI Demo) and V002(anno has been corrected so no need to use VGG generated)     
- 
-  train_data="../../caffe-jacinto/examples/ti-custom-cfg1/ti-custom-cfg1_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/ti-custom-cfg1/ti-custom-cfg1_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/ti-custom-cfg1/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/ti-custom-cfg1/labelmap.prototxt"
- 
-  num_test_image=3609
-  num_classes=4
-
-  min_dim=368
- 
-  resize_width=720
-  resize_height=368
-  crop_width=720
-  crop_height=368
-  use_difficult_gt=0
-  small_objs=1
-  ker_mbox_loc_conf=1
-  batch_size=16      #32    #16
-
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=120000    #120000  #64000   #32000
-  stepvalue1=30000   #60000   #32000   #16000
-  stepvalue2=45000   #90000   #48000   #24000
-  base_lr=1e-3       #1e-2    #1e-4    #1e-3
-  lr_policy="poly"
-  #set it to 4.0 for poly
-  power=4.0
-
-  #0.0005 (orignal SSD), 0.0001
-  weight_decay_L2=0.0005
-  use_batchnorm_mbox=0
-elif [ $dataset = "ti-custom-cfg2" ]
-then
-  train_data="../../caffe-jacinto/examples/ti-custom-cfg2/ti-custom-cfg2_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/ti-custom-cfg2/ti-custom-cfg2_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/ti-custom-cfg2/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/ti-custom-cfg2/labelmap.prototxt"
-
-  num_test_image=294
-  num_classes=3 
-
-  min_dim=256
-  ssd_size='512x512'
- 
-  resize_width=512
-  resize_height=256
-  crop_width=512
-  crop_height=256
-  small_objs=0
-  ker_mbox_loc_conf=1
-  batch_size=16      #32    #16
-
-  #ignore lables are marked as diff in TI dataset 
-  use_difficult_gt=1
-  
-  #solver params
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=50000     #120000  #64000   #32000
-  stepvalue1=30000   #60000   #32000   #16000
-  stepvalue2=40000   #90000   #48000   #24000
-  base_lr=1e-2       #1e-2    #1e-4    #1e-3
-  #set it to 4.0 for poly
-  power=1.0
-
-  #0.0005 (orignal SSD), 0.0001
-  weight_decay_L2=0.0001
-  use_batchnorm_mbox=1
-else
-  echo "Invalid dataset name"
-  exit
-fi
-
-model_name_to_print=$model_name 
-if [ $model_name = 'ssdJacintoNetV2' ]
-then
-  model_name_to_print="JDetNet" 
-fi  
-
-folder_name=training/"$dataset"/"$model_name_to_print"/"$DATE_TIME"_"ds_PSP_dsFac_32_hdDS8_1";mkdir training/"$dataset";mkdir training/"$dataset"/"$model_name_to_print";mkdir $folder_name
-
-#------------------------------------------------
-LOG=$folder_name/train-log_"$DATE_TIME".txt
-exec &> >(tee -a "$LOG")
-echo Logging output to "$LOG"
-
-#-------------------------------------------------------
-#Initial training
-stage="initial"
-weights=$weights_dst
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],'weight_decay':$weight_decay_L2}"
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,\
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,\
-'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type',\
-'rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,\
-'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#l1 regularized training before sparsification
-stage="l1reg"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_"$max_iter".caffemodel
-
-max_iter=60000
-stepvalue1=30000
-stepvalue2=45000
-base_lr=1e-3       #1e-2    #1e-4    #1e-3
-l1reg_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$l1reg_solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#incremental sparsification and finetuning
-stage="sparse"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-#Using more than one GPU for this step gives strange results. Imbalanced accuracy between the GPUs.
-gpus="0" #"0,1,2"
-batch_size=8
-lr_policy="poly"
-#set it to 4.0 for poly
-power=4.0
-base_lr=1e-3       #1e-2    #1e-4    #1e-3
-sparse_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':2000,\
-'sparsity_target':0.70,'sparsity_start_iter':0,'sparsity_start_factor':$sparsity_start_factor,\
-'sparsity_step_iter':2000,'sparsity_step_factor':0.05,'sparsity_itr_increment_bfr_applying':1,'sparsity_threshold_maxratio':0.2,\
-'sparsity_threshold_value_max':0.2}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox, 'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$sparse_solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#test
-stage="test"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-test_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':1000}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'test_batch_size':10,'caffe_cmd':'test_detection','display_sparsity':1,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$test_solver_param
-#config_name_prev=$config_name
-
-#-------------------------------------------------------
-#test_quantize
-stage="test_quantize"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-test_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':1000}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'test_batch_size':10,'caffe_cmd':'test_detection',\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,\
-'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,\
-'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$test_solver_param
-
-echo "quantize: true" > $config_name/deploy_new.prototxt
-cat $config_name/deploy.prototxt >> $config_name/deploy_new.prototxt
-mv --force $config_name/deploy_new.prototxt $config_name/deploy.prototxt
-
-echo "quantize: true" > $config_name/test_new.prototxt
-cat $config_name/test.prototxt >> $config_name/test_new.prototxt
-mv --force $config_name/test_new.prototxt $config_name/test.prototxt
-
-#-------------------------------------------------------
-#run
-list_dirs=`command ls -d1 "$folder_name"/*/ | command cut -f5 -d/`
-for f in $list_dirs; do "$folder_name"/$f/run.sh; done

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel
deleted file mode 100755 (executable)
index 14ed76b..0000000
Binary files a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel and /dev/null differ

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/deploy.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/deploy.prototxt
deleted file mode 100755 (executable)
index 941284d..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/deploy.prototxt
+++ /dev/null
@@ -1,2373 +0,0 @@
-name: "mobiledetnet-0.5_deploy"
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 256
-  dim: 512
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_1/sep/scale"
-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/dw/scale"
-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  top: "ctx_output4/relu_mbox_loc_perm"
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-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_conf"
-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_conf_perm"
-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output4"
-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 226.0
-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_reshape"
-  type: "Reshape"
-  bottom: "mbox_conf"
-  top: "mbox_conf_reshape"
-  reshape_param {
-    shape {
-      dim: 0
-      dim: -1
-      dim: 21
-    }
-  }
-}
-layer {
-  name: "mbox_conf_softmax"
-  type: "Softmax"
-  bottom: "mbox_conf_reshape"
-  top: "mbox_conf_softmax"
-  softmax_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_flatten"
-  type: "Flatten"
-  bottom: "mbox_conf_softmax"
-  top: "mbox_conf_flatten"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "detection_out"
-  type: "DetectionOutput"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf_flatten"
-  bottom: "mbox_priorbox"
-  top: "detection_out"
-  include {
-    phase: TEST
-  }
-  detection_output_param {
-    num_classes: 21
-    share_location: true
-    background_label_id: 0
-    nms_param {
-      nms_threshold: 0.45
-      top_k: 400
-    }
-    save_output_param {
-      output_directory: ""
-      output_name_prefix: "comp4_det_test_"
-      output_format: "VOC"
-      label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-      name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-      num_test_image: 4952
-    }
-    code_type: CENTER_SIZE
-    keep_top_k: 200
-    confidence_threshold: 0.01
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/image_object_detection.py b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/image_object_detection.py
deleted file mode 100755 (executable)
index 88b0dae..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/image_object_detection.py
+++ /dev/null
@@ -1,986 +0,0 @@
-from __future__ import print_function
-import caffe
-from google.protobuf import text_format
-import ast
-from models.model_libs import *
-import models.jacintonet_v2
-import models.mobilenet
-import numpy as np
-import math
-import os
-import shutil
-import stat
-import subprocess
-import sys
-import argparse
-from collections import OrderedDict
-
-
-def set_min_max_sizes(config_param):
-  # in percent %
-  min_ratio = 15
-  if config_param.ssd_size == '512x512':
-    min_ratio = 15
-  elif (config_param.ssd_size == '300x300') or(config_param.ssd_size == '256x256'):
-    min_ratio = 20
-  
-  if config_param.small_objs: 
-    min_ratio = min_ratio - 5
-   
-  max_ratio = 90
-  step = int(math.floor((max_ratio - min_ratio) / (config_param.num_steps - 2)))
-
-  min_sizes = []
-  max_sizes = []
-
-  for ratio in xrange(min_ratio, max_ratio + 1, step):
-    min_sizes.append(config_param.min_dim * ratio / 100.)
-    max_sizes.append(config_param.min_dim * (ratio + step) / 100.)
-
-  print('ratio_step_size:', step)   
-  
-  min_size_mul = 7
-  max_size_mul = 15
-  if config_param.ssd_size == '512x512':
-    if config_param.small_objs:
-      min_size_mul = 4 
-      max_size_mul = 10
-    else:  
-      min_size_mul = 7
-      max_size_mul = 15 
-  elif (config_param.ssd_size == '300x300') or (config_param.ssd_size == '256x256'):
-    if config_param.small_objs:
-      min_size_mul = 7
-      max_size_mul = 15 
-    else:
-      min_size_mul = 10
-      max_size_mul = 20
-  
-  min_sizes = [config_param.min_dim * min_size_mul / 100.] + min_sizes
-  max_sizes = [config_param.min_dim * max_size_mul / 100.] + max_sizes
-  
-  #print('min_sizes:', min_sizes)   
-  #print('max_sizes:', max_sizes)  
-
-  return min_sizes, max_sizes  
-
-def CreateAnnotatedDataLayer(source, batch_size=32, backend=P.Data.LMDB,
-        output_label=True, train=True, label_map_file='', anno_type=None,
-        transform_param={}, batch_sampler=[{}], threads=1):
-    if train:
-        kwargs = {
-                'include': dict(phase=caffe_pb2.Phase.Value('TRAIN')),
-                'transform_param': transform_param,
-                }
-    else:
-        kwargs = {
-                'include': dict(phase=caffe_pb2.Phase.Value('TEST')),
-                'transform_param': transform_param,
-                }
-    ntop = 1
-    if output_label:
-        ntop = 2
-    annotated_data_param = {
-        'label_map_file': label_map_file,
-        'batch_sampler': batch_sampler,
-        }
-    if anno_type is not None:
-        annotated_data_param.update({'anno_type': anno_type})
-    return L.AnnotatedData(name="data", annotated_data_param=annotated_data_param,
-        data_param=dict(batch_size=batch_size, backend=backend, source=source, parser_threads=threads, threads=threads),
-        ntop=ntop, **kwargs)
-        
-def CreateMultiBoxHead(net, data_layer="data", num_classes=[], from_layers=[],
-        use_objectness=False, normalizations=[], use_batchnorm=True, lr_mult=1,
-        use_scale=True, min_sizes=[], max_sizes=[], prior_variance = [0.1],
-        aspect_ratios=[], steps=[], img_height=0, img_width=0, share_location=True,
-        flip=True, clip=True, offset=0.5, inter_layer_depth=[], kernel_size=1, pad=0,
-        conf_postfix='', loc_postfix='', **bn_param):
-    assert num_classes, "must provide num_classes"
-    assert num_classes > 0, "num_classes must be positive number"
-    if normalizations:
-        assert len(from_layers) == len(normalizations), "from_layers and normalizations should have same length"
-    assert len(from_layers) == len(min_sizes), "from_layers and min_sizes should have same length"
-    if max_sizes:
-        assert len(from_layers) == len(max_sizes), "from_layers and max_sizes should have same length"
-    if aspect_ratios:
-        assert len(from_layers) == len(aspect_ratios), "from_layers and aspect_ratios should have same length"
-    if steps:
-        assert len(from_layers) == len(steps), "from_layers and steps should have same length"
-    net_layers = net.keys()
-    assert data_layer in net_layers, "data_layer is not in net's layers"
-    if inter_layer_depth:
-        assert len(from_layers) == len(inter_layer_depth), "from_layers and inter_layer_depth should have same length"
-
-    num = len(from_layers)
-    priorbox_layers = []
-    loc_layers = []
-    conf_layers = []
-    objectness_layers = []
-    for i in range(0, num):
-        from_layer = from_layers[i]
-
-        # Get the normalize value.
-        if normalizations:
-            if normalizations[i] != -1:
-                norm_name = "{}_norm".format(from_layer)
-                net[norm_name] = L.Normalize(net[from_layer], scale_filler=dict(type="constant", value=normalizations[i]),
-                    across_spatial=False, channel_shared=False)
-                from_layer = norm_name
-
-        # Add intermediate layers.
-        if inter_layer_depth:
-            if inter_layer_depth[i] > 0:
-                inter_name = "{}_inter".format(from_layer)
-                ConvBNLayerSSD(net, from_layer, inter_name, use_bn=use_batchnorm, use_relu=True, lr_mult=lr_mult,
-                      num_output=inter_layer_depth[i], kernel_size=3, pad=1, stride=1, use_scale=use_scale, **bn_param)
-                from_layer = inter_name
-
-        # Estimate number of priors per location given provided parameters.
-        min_size = min_sizes[i]
-        if type(min_size) is not list:
-            min_size = [min_size]
-        aspect_ratio = []
-        if len(aspect_ratios) > i:
-            aspect_ratio = aspect_ratios[i]
-            if type(aspect_ratio) is not list:
-                aspect_ratio = [aspect_ratio]
-        max_size = []
-        if len(max_sizes) > i:
-            max_size = max_sizes[i]
-            if type(max_size) is not list:
-                max_size = [max_size]
-            if max_size:
-                assert len(max_size) == len(min_size), "max_size and min_size should have same length."
-        if max_size:
-            num_priors_per_location = (2 + len(aspect_ratio)) * len(min_size)
-        else:
-            num_priors_per_location = (1 + len(aspect_ratio)) * len(min_size)
-        if flip:
-            num_priors_per_location += len(aspect_ratio) * len(min_size)
-        step = []
-        if len(steps) > i:
-            step = steps[i]
-
-        # Create location prediction layer.
-        name = "{}_mbox_loc{}".format(from_layer, loc_postfix)
-        num_loc_output = num_priors_per_location * 4;
-        if not share_location:
-            num_loc_output *= num_classes
-       
-        dilation=1
-        pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-        ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-            num_output=num_loc_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-        permute_name = "{}_perm".format(name)
-        net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-        flatten_name = "{}_flat".format(name)
-        net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-        loc_layers.append(net[flatten_name])
-
-        # Create confidence prediction layer.
-        name = "{}_mbox_conf{}".format(from_layer, conf_postfix)
-        num_conf_output = num_priors_per_location * num_classes;
-
-        dilation=1
-        pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-        ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-            num_output=num_conf_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-        permute_name = "{}_perm".format(name)
-        net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-        flatten_name = "{}_flat".format(name)
-        net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-        conf_layers.append(net[flatten_name])
-
-        # Create prior generation layer.
-        name = "{}_mbox_priorbox".format(from_layer)
-        net[name] = L.PriorBox(net[from_layer], net[data_layer], min_size=min_size,
-                clip=clip, variance=prior_variance, offset=offset)
-        if max_size:
-            net.update(name, {'max_size': max_size})
-        if aspect_ratio:
-            net.update(name, {'aspect_ratio': aspect_ratio, 'flip': flip})
-        if step:
-            net.update(name, {'step': step})
-        if img_height != 0 and img_width != 0:
-            if img_height == img_width:
-                net.update(name, {'img_size': img_height})
-            else:
-                net.update(name, {'img_h': img_height, 'img_w': img_width})
-        priorbox_layers.append(net[name])
-
-        # Create objectness prediction layer.
-        if use_objectness:
-            name = "{}_mbox_objectness".format(from_layer)
-            num_obj_output = num_priors_per_location * 2;
-            dilation=1
-            pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-            ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-                num_output=num_obj_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-            permute_name = "{}_perm".format(name)
-            net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-            flatten_name = "{}_flat".format(name)
-            net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-            objectness_layers.append(net[flatten_name])
-
-    # Concatenate priorbox, loc, and conf layers.
-    mbox_layers = []
-    name = "mbox_loc"
-    net[name] = L.Concat(*loc_layers, axis=1)
-    mbox_layers.append(net[name])
-    name = "mbox_conf"
-    net[name] = L.Concat(*conf_layers, axis=1)
-    mbox_layers.append(net[name])
-    name = "mbox_priorbox"
-    net[name] = L.Concat(*priorbox_layers, axis=2)
-    mbox_layers.append(net[name])
-    if use_objectness:
-        name = "mbox_objectness"
-        net[name] = L.Concat(*objectness_layers, axis=1)
-        mbox_layers.append(net[name])
-
-    return mbox_layers
-
-
-def CoreNetwork(config_param, net, from_layer):
-    if config_param.model_name == 'jdetnet21v2':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)
-    elif config_param.model_name == 'jdetnet21v2-s8':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21_s8(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)              
-    elif config_param.model_name == 'jdetnet21v2-fpn':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21_fpn(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)
-    elif config_param.model_name == 'ssdJacintoNetV2':
-        out_layer, out_layer_names = models.jacintonet_v2.ssdJacintoNetV2(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,\
-          dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride,\
-          ds_type=config_param.ds_type, use_batchnorm_mbox=config_param.use_batchnorm_mbox,fully_conv_at_end=config_param.fully_conv_at_end, 
-          reg_head_at_ds8=config_param.reg_head_at_ds8, concat_reg_head=config_param.concat_reg_head,
-          base_nw_3_head=config_param.base_nw_3_head, first_hd_same_op_ch=config_param.first_hd_same_op_ch,
-          num_intermediate=config_param.num_intermediate, rhead_name_non_linear=config_param.rhead_name_non_linear,
-          chop_num_heads=config_param.chop_num_heads)
-    elif 'mobiledetnet' in config_param.model_name:
-        #out_layer = models.mobilenet.mobiledetnet(net, from_layer=from_layer,\
-        #  num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-        #  freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride, wide_factor=wide_factor)
-        wide_factor = float(config_param.model_name.split('-')[1])
-        out_layer, out_layer_names = models.mobilenet.mobiledetnet(net, from_layer=from_layer, wide_factor=wide_factor, num_intermediate=config_param.num_intermediate)
-    else:
-        ValueError("Invalid model name")
-
-    return net, out_layer, out_layer_names
-
-
-def get_arguments():
-    parser = argparse.ArgumentParser()   
-    parser.add_argument('--config_param', type=str, default=None, help='Extra config parameters')      
-    parser.add_argument('--solver_param', type=str, default=None, help='Extra solver parameters')        
-    return parser.parse_args()
-      
-def main(): 
-    args = get_arguments()
-   
-    if args.solver_param != None:
-      print(args.solver_param)
-      args.solver_param = ast.literal_eval(args.solver_param) 
-            
-    if args.config_param != None:
-      print(args.config_param)
-      args.config_param = ast.literal_eval(args.config_param) 
-            
-    #Start populating config_param
-    config_param = OrderedDict()
-  
-    #Names
-    config_param.config_name = 'image-objdet'
-    config_param.model_name = "jacintonet11"
-    config_param.dataset = "nodataset"       
-    config_param.pretrain_model = None
-                          
-    ### Modify the following parameters accordingly ###
-    # The directory which contains the caffe code.
-    # We assume you are running the script at the CAFFE_ROOT.
-    config_param.caffe_root = os.environ['CAFFE_ROOT'] if 'CAFFE_ROOT' in os.environ else None
-    if config_param.caffe_root == None:
-      config_param.caffe_root = os.environ['CAFFE_HOME'] if 'CAFFE_HOME' in os.environ else None
-    if config_param.caffe_root != None:
-      config_param.caffe_root = config_param.caffe_root + '/build/tools/caffe.bin'
-    config_param.caffe_cmd = 'train'
-
-    print("caffe_root = : ",  config_param.caffe_root)
-
-    # Set true if you want to start training right after generating all files.
-    config_param.run_soon = False
-    # Set true if you want to load from most recently saved snapshot.
-    # Otherwise, we will load from the pretrain_model defined below.
-    config_param.resume_training = True
-    # If true, Remove old model files.
-    config_param.remove_old_models = False
-    config_param.display_sparsity = False
-    
-    # Specify the batch sampler.
-    config_param.resize_width = 512
-    config_param.resize_height = 512
-    config_param.crop_width = config_param.resize_width
-    config_param.crop_height = config_param.resize_height
-
-    #feature stride can be 16, 32. 32 provides the best radeoff
-    config_param.feature_stride = 32
-    config_param.num_feature = 512 #number of feature channels
-    config_param.threads = 4
-    # The database file for training data. Created by data/VOC0712/create_data.sh
-    config_param.train_data = "/data/hdd/datasets/object-detect/other/pascal-voc/VOCdevkit/VOC0712/lmdb/VOC0712_trainval_lmdb"
-    # The database file for testing data. Created by data/VOC0712/create_data.sh
-    config_param.test_data = "/data/hdd/datasets/object-detect/other/pascal-voc/VOCdevkit/VOC0712/lmdb/VOC0712_test_lmdb"
-
-    config_param.stride_list = None
-    config_param.dilation_list = None
-
-    config_param.mean_value = 128 #used in a bias layer in the net.
-
-    
-    # If true, use batch norm for all newly added layers.
-    # Currently only the non batch norm version has been tested.
-    config_param.use_batchnorm = False
-    config_param.use_scale = False
-    
-    config_param.lr_mult = 1
-
-    # Which layers to freeze (no backward) during training.
-    config_param.freeze_layers = []
-    # Defining which GPUs to use.
-    config_param.gpus = "0,1" #gpus = "0"  
-
-    config_param.batch_size = 32
-    config_param.accum_batch_size = 32
-
-    # Evaluate on whole test set.
-    config_param.num_test_image = 4952
-    config_param.test_batch_size = 8
-    
-    # Stores the test image names and sizes. Created by data/VOC0712/create_list.sh
-    config_param.name_size_file = "/user/a0393608/files/work/code/vision/github/weiliu89_ssd/caffe/data/VOC0712/test_name_size.txt"
-    # Stores LabelMapItem.
-    config_param.label_map_file = "/user/a0393608/files/work/code/vision/github/weiliu89_ssd/caffe/data/VOC0712/labelmap_voc.prototxt"
-
-    # minimum dimension of input image
-    config_param.log_space_steps = False #True
-    config_param.min_ratio = 10 #5 #20     # in percent %
-    config_param.max_ratio = 90            # in percent %
-    config_param.num_classes = 21
-    
-    # MultiBoxLoss parameters initialization.
-    config_param.share_location = True
-    config_param.background_label_id=0
-    config_param.use_difficult_gt = True
-    config_param.ignore_difficult_gt = False
-    config_param.evaluate_difficult_gt = False
-    config_param.normalization_mode = P.Loss.VALID
-    config_param.code_type = P.PriorBox.CENTER_SIZE
-    config_param.ignore_cross_boundary_bbox = False
-    config_param.mining_type = P.MultiBoxLoss.MAX_NEGATIVE
-    config_param.neg_pos_ratio = 3.
-    config_param.loc_weight = (config_param.neg_pos_ratio + 1.) / 4.
-    config_param.min_dim = -1
-    config_param.aspect_ratios_type=0
-    #need it for COCO which may have gray scale image
-    config_param.force_color = 0 
-
-    #Update from params given from outside
-    #if args.config_param != None:
-    #  config_param.update(args.config_param)   
-    if args.config_param != None: 
-      for k in args.config_param.keys():
-        config_param.__setattr__(k,args.config_param[k])
-        config_param.__setitem__(k,args.config_param[k])
-
-    if config_param.min_dim == -1:
-      config_param.min_dim = int((config_param.crop_width + config_param.crop_height)/2)
-
-    if config_param.ds_fac == 16: 
-      config_param.stride_list = [2,2,2,2,1]
-      config_param.dilation_list = [1,1,1,1,2]
-      config_param.feature_stride = 16
-    elif config_param.ds_fac == 32: 
-      config_param.stride_list = [2,2,2,2,2]
-      config_param.dilation_list = [1,1,1,1,1]
-      config_param.feature_stride = 32
-   
-    print("config_param.ds_fac :", config_param.ds_fac)
-    print("config_param.stride_list :", config_param.stride_list)
-    resize = "{}x{}".format(config_param.resize_width, config_param.resize_height)
-    config_param.batch_sampler = [
-            {
-                    'sampler': {
-                            },
-                    'max_trials': 1,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.1,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.3,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.5,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.7,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.9,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'max_jaccard_overlap': 1.0,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            ]
-    config_param.train_transform_param = {
-            'mirror': True,
-            'mean_value': [0, 0, 0],
-            'force_color':config_param.force_color,
-            'resize_param': {
-                    'prob': 1,
-                    'resize_mode': P.Resize.WARP,
-                    'height': config_param.resize_height,
-                    'width': config_param.resize_width,
-                    'interp_mode': [
-                            P.Resize.LINEAR,
-                            P.Resize.AREA,
-                            P.Resize.NEAREST,
-                            P.Resize.CUBIC,
-                            P.Resize.LANCZOS4,
-                            ],
-                    },
-            'distort_param': {
-                    'brightness_prob': 0.5,
-                    'brightness_delta': 32,
-                    'contrast_prob': 0.5,
-                    'contrast_lower': 0.5,
-                    'contrast_upper': 1.5,
-                    'hue_prob': 0.5,
-                    'hue_delta': 18,
-                    'saturation_prob': 0.5,
-                    'saturation_lower': 0.5,
-                    'saturation_upper': 1.5,
-                    'random_order_prob': 0.0,
-                    },
-            'expand_param': {
-                    'prob': 0.5,
-                    'max_expand_ratio': 4.0,
-                    },
-            'emit_constraint': {
-                'emit_type': caffe_pb2.EmitConstraint.CENTER,
-                },
-      'crop_h': config_param.crop_height,
-      'crop_w': config_param.crop_width
-            }
-    config_param.test_transform_param = {
-            'mean_value': [0, 0, 0],
-            'force_color':config_param.force_color,
-            'resize_param': {
-                    'prob': 1,
-                    'resize_mode': P.Resize.WARP,
-                    'height': config_param.resize_height,
-                    'width': config_param.resize_width,
-                    'interp_mode': [P.Resize.LINEAR],
-                    },
-      'crop_h': config_param.crop_height,
-      'crop_w': config_param.crop_width          
-            }
-
-        
-    # Modify the job name if you want.
-    #print("config_name is {}".format(config_param.config_name))
-    config_param.base_name = config_param.config_name
-    config_param.job_name = config_param.base_name
-
-    # Base dir
-    config_param.base_dir = config_param.job_name
-    # Directory which stores the model .prototxt file.
-    config_param.save_dir = config_param.job_name
-    # Directory which stores the snapshot of models.
-    config_param.snapshot_dir = config_param.job_name
-    # Directory which stores the job script and log file.
-    config_param.job_dir = config_param.job_name
-    # Directory which stores the detection results.
-    config_param.output_result_dir = "" #"{}/results".format(config_param.job_name)
-        
-    # model definition files.
-    config_param.train_net_file = "{}/train.prototxt".format(config_param.save_dir)
-    config_param.test_net_file = "{}/test.prototxt".format(config_param.save_dir)
-    config_param.deploy_net_file = "{}/deploy.prototxt".format(config_param.save_dir)
-    config_param.solver_file = "{}/solver.prototxt".format(config_param.save_dir)
-    # snapshot prefix.
-    config_param.snapshot_prefix = "{}/{}_{}".format(config_param.snapshot_dir, config_param.dataset, config_param.model_name)
-    # job script path.
-    job_file_base_name = 'run' 
-    config_param.job_file_base = "{}/{}".format(config_param.job_dir, job_file_base_name)
-    config_param.log_file = "{}.log".format(config_param.job_file_base)    
-    config_param.job_file = "{}.sh".format(config_param.job_file_base)
-   
-    # MultiBoxLoss parameters.
-    multibox_loss_param = {
-        'loc_loss_type': P.MultiBoxLoss.SMOOTH_L1,
-        'conf_loss_type': P.MultiBoxLoss.SOFTMAX,
-        'loc_weight': config_param.loc_weight,
-        'num_classes': config_param.num_classes,
-        'share_location': config_param.share_location,
-        'match_type': P.MultiBoxLoss.PER_PREDICTION,
-        'overlap_threshold': 0.5,
-        'use_prior_for_matching': True,
-        'background_label_id': config_param.background_label_id,
-        'use_difficult_gt': config_param.use_difficult_gt,
-        'ignore_difficult_gt': config_param.ignore_difficult_gt,
-        'mining_type': config_param.mining_type,
-        'neg_pos_ratio': config_param.neg_pos_ratio,
-        'neg_overlap': 0.5,
-        'code_type': config_param.code_type,
-        'ignore_cross_boundary_bbox': config_param.ignore_cross_boundary_bbox,
-        }
-    loss_param = {
-        'normalization': config_param.normalization_mode,
-        }
-
-    if config_param.feature_stride != 16 and config_param.feature_stride != 32:
-        ValueError("config_param.feature_stride {} is incorrect".format(config_param.feature_stride))
-    
-
-    config_param.flip = True
-    config_param.clip = False
-
-    # Solver parameters.
-    # Defining which GPUs to use.
-    config_param.gpulist = config_param.gpus.split(",")
-    config_param.num_gpus = len(config_param.gpulist)
-   
-    # Divide the mini-batch to different GPUs.
-    iter_size = int(math.ceil(config_param.accum_batch_size/config_param.batch_size))
-    solver_mode = P.Solver.CPU
-    device_id = 0
-    batch_size_per_device = config_param.batch_size
-    if config_param.num_gpus > 0:
-      batch_size_per_device = int(math.ceil(float(config_param.batch_size) / config_param.num_gpus))
-      iter_size = int(math.ceil(float(config_param.accum_batch_size) / (batch_size_per_device * config_param.num_gpus)))
-      solver_mode = P.Solver.GPU
-      device_id = int(config_param.gpulist[0])
-
-    # Ideally test_batch_size should be divisible by num_test_image,
-    # otherwise mAP will be slightly off the true value.
-    test_iter = int(math.ceil(float(config_param.num_test_image) / config_param.test_batch_size))
-
-    solver_param = {
-        # Train parameters
-        'type': "SGD",
-        'base_lr': 1e-3,
-        'max_iter': 32000, 
-        'weight_decay': 0.0005,
-        'lr_policy': "multistep",
-        'power': 1.0,
-        'stepvalue': [24000, 30000, 32000],
-        'gamma': 0.1,
-        'momentum': 0.9,
-        'iter_size': iter_size,
-        'snapshot': 2000,
-        'display': 100,
-        'average_loss': 10,
-        'type': "SGD",
-        'solver_mode': solver_mode,
-        'device_id': device_id,
-        'debug_info': False,
-        'snapshot_after_train': True,
-        # Test parameters
-        'test_iter': [test_iter],
-        'test_interval': 2000,
-        'eval_type': "detection",
-        'ap_version': "11point",
-        'test_initialization': True,
-        'random_seed': 33,
-        'show_per_class_result': True,
-        }
-
-    #if args.solver_param != None:
-    #  solver_param.update(args.solver_param)       
-    if args.solver_param != None: 
-      for k in args.solver_param.keys():
-        solver_param.__setitem__(k,args.solver_param[k])    
-        #solver_param.__setattr__(k,args.solver_param[k])
-    
-    # parameters for generating detection output.
-    det_out_param = {
-        'num_classes': config_param.num_classes,
-        'share_location': config_param.share_location,
-        'background_label_id': config_param.background_label_id,
-        'nms_param': {'nms_threshold': 0.45, 'top_k': 400},
-        'save_output_param': {
-            'output_directory': config_param.output_result_dir,
-            'output_name_prefix': "comp4_det_test_",
-            'output_format': "VOC",
-            'label_map_file': config_param.label_map_file,
-            'name_size_file': config_param.name_size_file,
-            'num_test_image': config_param.num_test_image,
-            },
-        'keep_top_k': 200,
-        'confidence_threshold': 0.01,
-        'code_type': config_param.code_type,
-        }
-
-    # parameters for evaluating detection results.
-    det_eval_param = {
-        'num_classes': config_param.num_classes,
-        'background_label_id': config_param.background_label_id,
-        'overlap_threshold': 0.5,
-        'evaluate_difficult_gt': config_param.evaluate_difficult_gt,
-        'name_size_file': config_param.name_size_file,
-        }
-
-    ### Hopefully you don't need to change the following ###
-    # Check file.
-    check_if_exist(config_param.train_data)
-    check_if_exist(config_param.test_data)
-    check_if_exist(config_param.label_map_file)
-    if config_param.pretrain_model != None:    
-      check_if_exist(config_param.pretrain_model)
-    make_if_not_exist(config_param.base_dir)  
-    make_if_not_exist(config_param.save_dir)
-    make_if_not_exist(config_param.job_dir)
-    make_if_not_exist(config_param.snapshot_dir)
-
-    # Create train net.
-    net = caffe.NetSpec()
-    net.data, net.label = CreateAnnotatedDataLayer(config_param.train_data, batch_size=config_param.batch_size,
-            train=True, output_label=True, label_map_file=config_param.label_map_file,
-            transform_param=config_param.train_transform_param, batch_sampler=config_param.batch_sampler, 
-            threads=config_param.threads)
-
-    out_layer = 'data'
-    bias_kwargs = { #fixed value with lr_mult=0
-        'param': [dict(lr_mult=0, decay_mult=0)],
-        'filler': dict(type='constant', value=(-config_param.mean_value)),
-        }       
-    net['data/bias'] = L.Bias(net[out_layer], in_place=False, **bias_kwargs)
-    out_layer = 'data/bias'           
-
-    net, out_layer, out_layer_names = CoreNetwork(config_param, net, out_layer)
-
-    if (config_param.model_name == 'jdetnet21v2'):
-        config_param.steps = [] #[16, 32, 64, 128]
-        config_param.mbox_source_layers = out_layer_names
-    elif (config_param.model_name == 'jdetnet21v2-s8'):
-        config_param.steps = [] #[8, 16, 32, 64, 128, 256]
-        config_param.mbox_source_layers = out_layer_names
-    elif (config_param.model_name == 'jdetnet21v2-fpn'):
-        config_param.steps = [] #[16, 16, 32, 64, 128, 256]
-        config_param.mbox_source_layers = out_layer_names
-    if (config_param.model_name == 'ssdJacintoNetV2'):
-      config_param.mbox_source_layers = out_layer_names
-      config_param.steps = []
-      if config_param.ds_type == 'DFLT':
-        #config_param.mbox_source_layers = ['res3a_branch2b/relu', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2', 'conv10_2']
-        config_param.mbox_source_layers = out_layer_names
-        if config_param.base_nw_3_head:
-          config_param.mbox_source_layers.append('ctx_output{}/relu'.format(len(config_param.mbox_source_layers)+1))
-    elif config_param.model_name == 'vgg16':
-        # conv4_3 ==> 38 x 38
-        # fc7 ==> 19 x 19
-        # conv6_2 ==> 10 x 10
-        # conv7_2 ==> 5 x 5
-        # conv8_2 ==> 3 x 3
-        # conv9_2 ==> 1 x 1
-        config_param.mbox_source_layers = ['conv4_3', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2']
-        config_param.steps = [8, 16, 32, 64, 100, 300]
-    elif 'mobiledetnet' in config_param.model_name:
-        config_param.mbox_source_layers = out_layer_names
-        config_param.steps = [] #[16, 32, 64, 128, 256] #[8, 16, 32, 64, 128, 256]
-    else:
-        print("Unknown detection network. Assuming default step sizes")
-        config_param.steps = []
-        config_param.mbox_source_layers = out_layer_names
-    
-    #-------------------------------------------------------------------
-    # parameters for generating priors.
-    config_param.num_steps = len(config_param.mbox_source_layers)  
-    config_param.step = int(math.floor((config_param.max_ratio - config_param.min_ratio) / config_param.num_steps))
-    config_param.min_sizes = []
-    config_param.max_sizes = []
-      
-    print("min_dim = {}".format(config_param.min_dim))
-    min_dim_to_use = config_param.min_ratio*config_param.min_dim/100
-    max_dim_to_use = config_param.max_ratio*config_param.min_dim/100
-    if config_param.log_space_steps == 1:
-      #log
-      min_max_sizes = np.logspace(np.log2(min_dim_to_use), np.log2(max_dim_to_use), num=config_param.num_steps+1, base=2)
-      config_param.min_sizes = list(min_max_sizes[0:config_param.num_steps])
-      config_param.max_sizes = list(min_max_sizes[1:config_param.num_steps+1])
-    elif config_param.log_space_steps == 0:
-      #linear
-      min_max_sizes = np.linspace(min_dim_to_use, max_dim_to_use, num=config_param.num_steps+1)
-      config_param.min_sizes = list(min_max_sizes[0:config_param.num_steps])
-      config_param.max_sizes = list(min_max_sizes[1:config_param.num_steps+1])
-    else:
-      #like original SSD
-      config_param.min_sizes, config_param.max_sizes = set_min_max_sizes(config_param)
-  
-    print("minsizes = {}".format(config_param.min_sizes))
-    print("maxsizes = {}".format(config_param.max_sizes))
-   
-    if config_param.aspect_ratios_type == 0:
-      config_param.aspect_ratios = [[2]]*config_param.num_steps 
-    else:
-      #like original SSD
-      config_param.aspect_ratios = [[2,3]]*config_param.num_steps
-      config_param.aspect_ratios[0] = [2]
-      config_param.aspect_ratios[-1] = [2]
-      config_param.aspect_ratios[-2] = [2]
-           
-    print("ARs:",config_param.aspect_ratios)
-    # L2 normalize conv4_3.
-    config_param.normalizations = [-1]*config_param.num_steps #[20, -1, -1, -1, -1, -1]
-    # variance used to encode/decode prior bboxes.
-    if config_param.code_type == P.PriorBox.CENTER_SIZE:
-      config_param.prior_variance = [0.1, 0.1, 0.2, 0.2]
-    else:
-      config_param.prior_variance = [0.1]
-
-    if config_param.chop_num_heads > 0:
-      print("Chopping heads")
-      del config_param.min_sizes[-config_param.chop_num_heads:]
-      del config_param.max_sizes[-config_param.chop_num_heads:]
-      del config_param.aspect_ratios[-config_param.chop_num_heads:]
-      del config_param.normalizations[-config_param.chop_num_heads:]
-      del config_param.mbox_source_layers[-config_param.chop_num_heads:]
-
-      print("minsizes = {}".format(config_param.min_sizes))
-      print("maxsizes = {}".format(config_param.max_sizes))
-      print("aspect_ratios = {}".format(config_param.aspect_ratios))
-      print(config_param.mbox_source_layers)
-    
-    
-    mbox_layers = CreateMultiBoxHead(net, data_layer='data', from_layers=config_param.mbox_source_layers,
-            use_batchnorm=config_param.use_batchnorm, use_scale=config_param.use_scale, min_sizes=config_param.min_sizes, max_sizes=config_param.max_sizes,
-            aspect_ratios=config_param.aspect_ratios, steps=config_param.steps, normalizations=config_param.normalizations,
-            num_classes=config_param.num_classes, share_location=config_param.share_location, flip=config_param.flip, clip=config_param.clip,
-            prior_variance=config_param.prior_variance, kernel_size=config_param.ker_mbox_loc_conf, pad=1, lr_mult=config_param.lr_mult)
-
-    # Create the MultiBoxLossLayer.
-    name = "mbox_loss"
-    mbox_layers.append(net.label)
-    net[name] = L.MultiBoxLoss(*mbox_layers, multibox_loss_param=multibox_loss_param,
-            loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')),
-            propagate_down=[True, True, False, False])
-
-    with open(config_param.train_net_file, 'w') as f:
-        print(config_param.train_net_file)
-        print('name: "{}"'.format(config_param.model_name), file=f)
-        print(net.to_proto(), file=f)
-    #shutil.copy(train_net_file, job_dir)
-
-
-    #-------------------------------------------------------------------
-    # Create test net.
-    net = caffe.NetSpec()
-    net.data, net.label = CreateAnnotatedDataLayer(config_param.test_data, batch_size=config_param.test_batch_size,
-            train=False, output_label=True, label_map_file=config_param.label_map_file,
-            transform_param=config_param.test_transform_param, threads=config_param.threads)
-
-    out_layer = 'data'
-    bias_kwargs = { #fixed value with lr_mult=0
-        'param': [dict(lr_mult=0, decay_mult=0)],
-        'filler': dict(type='constant', value=(-config_param.mean_value)),
-        }       
-    net['data/bias'] = L.Bias(net[out_layer], in_place=False, **bias_kwargs)
-    out_layer = 'data/bias'    
-    
-    net, out_layer, out_layer_names = CoreNetwork(config_param, net, out_layer)
-    
-    mbox_layers = CreateMultiBoxHead(net, data_layer='data', from_layers=config_param.mbox_source_layers,
-            use_batchnorm=config_param.use_batchnorm, use_scale=config_param.use_scale, min_sizes=config_param.min_sizes, max_sizes=config_param.max_sizes,
-            aspect_ratios=config_param.aspect_ratios, steps=config_param.steps, normalizations=config_param.normalizations,
-            num_classes=config_param.num_classes, share_location=config_param.share_location, flip=config_param.flip, clip=config_param.clip,
-            prior_variance=config_param.prior_variance, kernel_size=config_param.ker_mbox_loc_conf, pad=1, lr_mult=config_param.lr_mult)
-
-    conf_name = "mbox_conf"
-    if multibox_loss_param["conf_loss_type"] == P.MultiBoxLoss.SOFTMAX:
-      reshape_name = "{}_reshape".format(conf_name)
-      net[reshape_name] = L.Reshape(net[conf_name], shape=dict(dim=[0, -1, config_param.num_classes]))
-      softmax_name = "{}_softmax".format(conf_name)
-      net[softmax_name] = L.Softmax(net[reshape_name], axis=2)
-      flatten_name = "{}_flatten".format(conf_name)
-      net[flatten_name] = L.Flatten(net[softmax_name], axis=1)
-      mbox_layers[1] = net[flatten_name]
-    elif multibox_loss_param["conf_loss_type"] == P.MultiBoxLoss.LOGISTIC:
-      sigmoid_name = "{}_sigmoid".format(conf_name)
-      net[sigmoid_name] = L.Sigmoid(net[conf_name])
-      mbox_layers[1] = net[sigmoid_name]
-
-    net.detection_out = L.DetectionOutput(*mbox_layers,
-        detection_output_param=det_out_param,
-        include=dict(phase=caffe_pb2.Phase.Value('TEST')))
-    net.detection_eval = L.DetectionEvaluate(net.detection_out, net.label,
-        detection_evaluate_param=det_eval_param,
-        include=dict(phase=caffe_pb2.Phase.Value('TEST')))
-
-    with open(config_param.test_net_file, 'w') as f:
-        print('name: "{}_test"'.format(config_param.model_name), file=f)
-        print(net.to_proto(verbose=False), file=f)
-    if config_param.save_dir!=config_param.job_dir:
-      shutil.copy(config_param.test_net_file, config_param.job_dir)
-
-    # Create deploy net.
-    # Remove the first and last layer from test net.
-    deploy_net = net
-    with open(config_param.deploy_net_file, 'w') as f:
-        net_param = deploy_net.to_proto()
-        # Remove the first (AnnotatedData) and last (DetectionEvaluate) layer from test net.
-        del net_param.layer[0]
-        del net_param.layer[-1]
-        net_param.name = '{}_deploy'.format(config_param.model_name)
-        net_param.input.extend(['data'])
-        net_param.input_shape.extend([
-            caffe_pb2.BlobShape(dim=[1, 3, config_param.resize_height, config_param.resize_width])])
-        print(net_param, file=f)
-    if config_param.save_dir!=config_param.job_dir:        
-      shutil.copy(config_param.deploy_net_file, config_param.job_dir)
-
-    # Create solver.
-    solver = caffe_pb2.SolverParameter(
-            train_net=config_param.train_net_file,
-            test_net=[config_param.test_net_file],
-            snapshot_prefix=config_param.snapshot_prefix,
-            **solver_param)
-            
-    with open(config_param.solver_file, 'w') as f:
-        print(solver, file=f)
-    if config_param.save_dir!=config_param.job_dir:        
-      shutil.copy(solver_file, job_dir)
-
-    max_iter = 0
-    # Find most recent snapshot.
-    for file in os.listdir(config_param.snapshot_dir):
-      if file.endswith(".solverstate"):
-        basename = os.path.splitext(file)[0]
-        iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-        if iter > max_iter:
-          max_iter = iter
-
-    train_src_param = None
-    if config_param.pretrain_model != None:
-      train_src_param = '--weights="{}" \\\n'.format(config_param.pretrain_model)
-    if config_param.resume_training:
-      if max_iter > 0:
-        train_src_param = '--snapshot="{}_iter_{}.solverstate" \\\n'.format(config_param.snapshot_prefix, max_iter)
-
-    if config_param.remove_old_models:
-      # Remove any snapshots smaller than max_iter.
-      for file in os.listdir(config_param.snapshot_dir):
-        if file.endswith(".solverstate"):
-          basename = os.path.splitext(file)[0]
-          iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-          if max_iter > iter:
-            os.remove("{}/{}".format(config_param.snapshot_dir, file))
-        if file.endswith(".caffemodel"):
-          basename = os.path.splitext(file)[0]
-          iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-          if max_iter > iter:
-            os.remove("{}/{}".format(config_param.snapshot_dir, file))
-
-    # Create job file.
-    with open(config_param.job_file, 'w') as f:
-      #f.write('cd {}\n'.format(config_param.caffe_root))
-      f.write('{} {} \\\n'.format(config_param.caffe_root, config_param.caffe_cmd))    
-      if(config_param.caffe_cmd == 'test' or config_param.caffe_cmd == 'test_detection'):
-        f.write('--model="{}" \\\n'.format(config_param.test_net_file))
-        f.write('--iterations="{}" \\\n'.format(solver_param['test_iter'][0]))       
-        if config_param.display_sparsity:
-          f.write('--display_sparsity=1 \\\n')
-      else:
-        f.write('--solver="{}" \\\n'.format(config_param.solver_file))      
-      if train_src_param != None:
-        f.write(train_src_param)
-      if solver_param['solver_mode'] == P.Solver.GPU:
-        f.write('--gpu "{}" 2>&1 | tee {}\n'.format(config_param.gpus, config_param.log_file))
-      else:
-        f.write('2>&1 | tee {}\n'.format(config_param.log_file))
-
-    # Copy the python script to job_dir.
-    py_file = os.path.abspath(__file__)
-    shutil.copy(py_file, config_param.job_dir)
-    
-    #copy some other utils scripts
-    shutil.copy(os.getcwd() + '/train_image_object_detection.sh', config_param.job_dir)
-    shutil.copy(os.getcwd() + '/models/jacintonet_v2.py', config_param.job_dir)
-
-    # Run the job.
-    os.chmod(config_param.job_file, stat.S_IRWXU)
-    if config_param.run_soon:
-      subprocess.call(config_param.job_file, shell=True)
-  
-  
-if __name__ == "__main__":
-  main()  

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/jacintonet_v2.py b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/jacintonet_v2.py
deleted file mode 100755 (executable)
index a19b4d4..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/jacintonet_v2.py
+++ /dev/null
@@ -1,703 +0,0 @@
-from __future__ import print_function
-import caffe
-from models.model_libs import *
-
-def jacintonet11_base(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=1000, stride_list=None, dilation_list=None, freeze_layers=None, in_place=True):  
-   #Top and Bottom blobs must be different for NVCaffe BN caffe-0.15 (in_place=False), but no such constraint for caffe-0.16
-   
-   #--     
-   stage=0
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]   
-   
-   out_layer = 'conv1a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=32, kernel_size=[5,5], pad=2*dilation, stride=stride, group=1, dilation=dilation, in_place=in_place)  
-   
-   from_layer = out_layer
-   out_layer = 'conv1b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=32, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)       
-   
-   #--     
-   stage=1
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]   
-        
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool1'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)       
-      
-   from_layer = out_layer
-   out_layer = 'res2a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res2a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)     
-     
-   #--     
-   stage=2
-   stride=stride_list[stage]
-   dilation=dilation_list[stage] 
-        
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}       
-   from_layer = out_layer
-   out_layer = 'pool2'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)     
-         
-   from_layer = out_layer
-   out_layer = 'res3a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=128, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res3a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=128, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)    
-   
-   #--       
-   stage=3
-   stride=stride_list[stage]
-   dilation=dilation_list[stage] 
-      
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool3'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)         
-         
-   from_layer = out_layer
-   out_layer = 'res4a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer 
-   out_layer = 'res4a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)        
-      
-   #--      
-   stage=4
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]         
-   
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool4'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)     
-
-   from_layer = out_layer
-   out_layer = 'res5a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=512, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res5a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=512, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place) 
-   
-   return out_layer
-  
-  
-def jacintonet11(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=1000, stride_list=None, dilation_list=None, freeze_layers=None):  
-   if stride_list == None:
-     stride_list = [2,2,2,2,2]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1]
-   
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #--   
-   # Add global pooling layer.
-   from_layer = out_layer
-   out_layer = 'pool5'
-   net[out_layer] = L.Pooling(net[from_layer], pool=P.Pooling.AVE, global_pooling=True)
-       
-   from_layer = out_layer 
-   out_layer = 'fc'+str(num_output)
-   kwargs = { 'num_output': num_output, 
-     'param': [{'lr_mult': 1, 'decay_mult': 1}, {'lr_mult': 2, 'decay_mult': 0}], 
-     'inner_product_param': { 
-         'weight_filler': { 'type': 'msra' }, 
-         'bias_filler': { 'type': 'constant', 'value': 0 }   
-     },
-   }
-   net[out_layer] = L.InnerProduct(net[from_layer], **kwargs)    
-   
-   return out_layer
-   
-   
-def jsegnet21(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=True): 
-   in_place = True
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #--   
-   from_layer = out_layer
-   out_layer = 'out5a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=2, dilation=4) 
-   
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'out5a_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 64, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 64, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)    
-   
-   from_layer = 'res3a_branch2b' if in_place else 'res3a_branch2b/bn'
-   out_layer = 'out3a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=1, stride=1, group=2, dilation=1) 
-   
-   from_layer = out_layer   
-   out_layer = 'out3_out5_combined'
-   net[out_layer] = L.Eltwise(net['out5a_up2'], net[from_layer])
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv1'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1) 
-      
-   from_layer = out_layer
-   out_layer = 'ctx_conv2'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv3'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv4'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-       
-   from_layer = out_layer
-   out_layer = 'ctx_final'
-   conv_kwargs = {
-        'param': [dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)],
-        'weight_filler': dict(type='msra'),
-        'bias_term': True, 
-        'bias_filler': dict(type='constant', value=0) }   
-   net[out_layer] = L.Convolution(net[from_layer], num_output=num_output, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, **conv_kwargs) 
-         
-   from_layer = out_layer
-   out_layer = 'ctx_final/relu'
-   net[out_layer] = L.ReLU(net[from_layer], in_place=True) 
-               
-   #frozen upsampling layer   
-   if upsample:      
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up2'   
-       deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-           'convolution_param': { 'num_output': num_output, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': num_output, 'stride': 2, 
-           'weight_filler': { 'type': 'bilinear' } } }       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-               
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up4'       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs) 
-       
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up8'       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)     
-                            
-   return out_layer    
-
-
-def jdetnet21(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-      
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   
-   #---------------------------        
-   out_layer_names = []
-  
-   from_layer = 'res5a_branch2b/relu'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7'
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-
-def jdetnet21_s8(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,2] #[2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1] #[1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-
-   from_layer = 'res5a_branch2b/relu'
-   out_layer = 'conv6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=1024, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1)
-      
-   from_layer = out_layer
-   out_layer = 'conv7'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=1024, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)
-
-   #---------------------------       
-   out_layer = 'res3a_branch2b/concat'    
-   net[out_layer] = L.Concat(net['res3a_branch2a/relu'], net['res3a_branch2b/relu'])  
-         
-   out_layer = 'res4a_branch2b/concat'    
-   net[out_layer] = L.Concat(net['res4a_branch2a/relu'], net['res4a_branch2b/relu'])  
-            
-   #out_layer = 'res5a_branch2b/concat'    
-   #net[out_layer] = L.Concat(net['res5a_branch2a/relu'], net['res5a_branch2b/relu'])  
-               
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = 'conv7/relu' #'res5a_branch2b/concat' #
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':1, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   #---------------------------       
-   out_layer_names = []
-   
-   from_layer = 'res3a_branch2b/concat'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)  
-   out_layer_names += [out_layer]
-   
-   from_layer = 'res4a_branch2b/concat'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1) 
-   out_layer_names += [out_layer]
-   
-   from_layer = 'conv7/relu' #'res5a_branch2b/concat' #
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7'
-   out_layer = 'ctx_output5'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-
-#To match configuration used by original SSD script
-def ssdJacintoNetV2(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32, use_batchnorm_mbox=True, ds_type='PSP', fully_conv_at_end=True, reg_head_at_ds8=True, 
-   concat_reg_head=False, base_nw_3_head=False, first_hd_same_op_ch=False,
-   rhead_name_non_linear=False, chop_num_heads=0): 
-   
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-
-   last_base_layer_name = out_layer
-
-   if concat_reg_head:
-     out_layer = 'res4a_branch2b/concat'    
-     net[out_layer] = L.Concat(net['res4a_branch2a/relu'], net['res4a_branch2b/relu']) 
-                           
-     out_layer = 'res5a_branch2b/concat'    
-     net[out_layer] = L.Concat(net['res5a_branch2a/relu'], net['res5a_branch2b/relu'])  
-     last_base_layer_name = out_layer
-
-   if fully_conv_at_end:
-     from_layer = last_base_layer_name 
-     out_layer = 'fc6'
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=1024, kernel_size=[3,3], pad=6, stride=1, group=1, dilation=6)
-        
-     from_layer = out_layer
-     out_layer = 'fc7'
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=1024, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)
-     last_base_layer_name = out_layer
-      
-   #---------------------------     
-   out_layer_names = []
-  
-   #PSP style pool down
-   if ds_type == 'PSP':
-     if chop_num_heads < 4:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool6'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-     
-     #--
-     if chop_num_heads < 3:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool7'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if chop_num_heads < 2:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool8'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if chop_num_heads < 1:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool9'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if stride_list[4] == 1:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':1, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool10'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   
-     #mbox_source_layers = ['res3a_branch2b_relu', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2','conv10_2']
-     if rhead_name_non_linear:
-       reg_head_idx=6
-     else:
-       reg_head_idx=1
-
-     if reg_head_at_ds8:
-       from_layer = 'res3a_branch2b/relu'
-     else: 
-       if concat_reg_head:
-         from_layer = 'res4a_branch2b/concat'
-       else:  
-         from_layer = 'res4a_branch2b/relu'
-
-     out_layer = 'ctx_output{}'.format(reg_head_idx)
-
-     if rhead_name_non_linear:
-       reg_head_idx=0
-
-     reg_head_idx += 1
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>first_hd_same_op_ch, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-     out_layer_names += [out_layer]
-     
-     from_layer = last_base_layer_name 
-     out_layer = 'ctx_output{}'.format(reg_head_idx)
-     reg_head_idx += 1
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-     out_layer_names += [out_layer]
-    
-     if chop_num_heads < 4:
-       from_layer = 'pool6'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 3:
-       from_layer = 'pool7'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 2:
-       from_layer = 'pool8'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 1:
-       from_layer = 'pool9'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if stride_list[4] == 1:
-       from_layer = 'pool10'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if base_nw_3_head:
-       #by default 2 heads are connected in base n/w are at res3a and res5a (at the end of base n/w)
-       from_layer = 'res4a_branch2b/relu'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     return out_layer, out_layer_names
-   else:
-     out_layer_names += ['res3a_branch2b/relu']
-     if fully_conv_at_end:
-       out_layer_names += ['fc7']
-     
-     ssd_size = '512x512'
-     training_type = 'SSD'
-     if (ssd_size == '512x512') and (training_type == 'SSD'):
-                       #32x32    #16x16    #8x8      #4x4      #2x2
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,   1,   4,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,   1,   1,]
-     elif (ssd_size == '300x300') and (training_type == 'SSD'):
-                      #19x19     #10x10    #5x5      #3x3
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   0,   0,   0,]
-       strides=       [  1,   2,   1,   2,   1,   1,   1,   1,]
-     elif (ssd_size == '256x256') and (training_type == 'SSD'):
-                      #16x16     #8x8    #8x8      #4x4
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   0,   0,   0,]
-       strides=       [  1,   2,   1,   1,   1,   1,   1,   1,]
-     elif (ssd_size == '512x512') and (training_type == 'IMGNET'):
-                       #16x16    #8x8      #4x4      #2x2
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,]
-     elif (ssd_size == '300x300') and (training_type == 'IMGNET'):
-                       #10x10    #5x5      #3x3       #2x2   
-       num_outputs =  [256, 512, 128, 256, 128, 256,  64, 128,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,]
-
-     # index of first additional layer after base network
-     first_idx = 6
-     from_layer = net.keys()[-1]
-     blk_idx = first_idx
-     lr_mult = 1 
-     bn_postfix='/bn'
-     scale_postfix='/scale'
-     print("num_outputs: ", num_outputs) 
-     for idx in range (0, len(num_outputs)):
-       print("blk_index: ", blk_idx)
-       # TODO(weiliu89): Construct the name using the last layer to avoid duplication.
-       one_or_two = (idx%2) + 1
-       out_layer = "conv{}_{}".format(blk_idx, one_or_two)
-       ConvBNLayer(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_outputs[idx],
-           kernel_sizes[idx], pads[idx], strides[idx], lr_mult=lr_mult, bn_postfix=bn_postfix,
-           scale_postfix=scale_postfix)
-       out_layer_names += [out_layer]
-       from_layer = out_layer
-       if one_or_two == 2:
-         blk_idx = blk_idx + 1
-
-     return out_layer, out_layer_names
-   #---------------------------       
-
-   
-   
-def jdetnet21_fpn(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   in_place = True   
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,2]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-   from_layer = out_layer
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':1, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   #---------------------------   
-   #FPN layers start here  
-   #---------------------------  512->256  
-   from_layer = out_layer
-   out_layer = 'pool8_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-   
-   out_layer_1x1 = 'pool7_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'pool7', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)    
-            
-   from_layer = out_layer   
-   out_layer = 'pool7_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-              
-   #---------------------------  512->256  
-   from_layer = out_layer
-   out_layer = 'pool7_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'pool7_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-            
-   out_layer_1x1 = 'pool6_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'pool6', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)     
-            
-   from_layer = out_layer   
-   out_layer = 'pool6_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-          
-   #---------------------------  512->256   
-   from_layer = out_layer
-   out_layer = 'pool6_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'pool6_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-            
-   out_layer_1x1 = 'res5a_branch2b_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res5a_branch2b/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)         
-        
-   from_layer = out_layer   
-   out_layer = 'res5a_branch2b_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-              
-   #---------------------------   256->256 
-   from_layer = out_layer
-   out_layer = 'res5a_branch2b_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'res5a_branch2a_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-       
-   out_layer_1x1 = 'res4a_branch2b_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res4a_branch2b/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)  
-                         
-   from_layer = out_layer   
-   out_layer = 'res4a_branch2b_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-          
-   #---------------------------   256->256 
-   from_layer = out_layer
-   out_layer = 'res4a_branch2b_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place)    
-       
-   out_layer_1x1 = 'res4a_branch2a_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res4a_branch2a/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)   
-                      
-   from_layer = out_layer   
-   out_layer = 'res4a_branch2a_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-                              
-   #---------------------------  
-   out_layer_names = []
-   
-   #SSD heads start here
-   from_layer = 'res4a_branch2a_plus'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)   
-   out_layer_names += [out_layer]
-
-   from_layer = 'res4a_branch2b_plus'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)          
-   out_layer_names += [out_layer]
-   
-   from_layer = 'res5a_branch2b_plus'
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6_plus'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7_plus'
-   out_layer = 'ctx_output5'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/run.log b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/run.log
deleted file mode 100755 (executable)
index bc2c726..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/run.log
+++ /dev/null
@@ -1,13744 +0,0 @@
-I0511 11:48:50.933817  4597 caffe.cpp:902] This is NVCaffe 0.17.0 started at Fri May 11 11:48:50 2018
-I0511 11:48:50.933930  4597 caffe.cpp:904] CuDNN version: 7003
-I0511 11:48:50.933935  4597 caffe.cpp:905] CuBLAS version: 9000
-I0511 11:48:50.933938  4597 caffe.cpp:906] CUDA version: 9000
-I0511 11:48:50.933940  4597 caffe.cpp:907] CUDA driver version: 9000
-I0511 11:48:50.933944  4597 caffe.cpp:908] Arguments: 
-[0]: /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-[1]: test_detection
-[2]: --model=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test/test.prototxt
-[3]: --iterations=496
-[4]: --display_sparsity=1
-[5]: --weights=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel
-[6]: --gpu
-[7]: 0
-I0511 11:48:51.207144  4597 gpu_memory.cpp:105] GPUMemory::Manager initialized
-I0511 11:48:51.207890  4597 gpu_memory.cpp:107] Total memory: 11713708032, Free: 11223957504, dev_info[0]: total=11713708032 free=11223957504
-I0511 11:48:51.207895  4597 caffe.cpp:406] Use GPU with device ID 0
-I0511 11:48:51.208423  4597 caffe.cpp:409] GPU device name: GeForce GTX 1080 Ti
-I0511 11:48:51.235842  4597 net.cpp:80] Initializing net from parameters: 
-name: "mobiledetnet-0.5_test"
-state {
-  phase: TEST
-  level: 0
-}
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 10
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
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-  top: "conv5_1/sep"
-}
-layer {
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-layer {
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-  top: "conv5_1/sep"
-}
-layer {
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-  top: "conv5_2/dw"
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-layer {
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-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
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-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
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-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
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-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
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-    decay_mult: 1
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-  convolution_param {
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-layer {
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-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
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-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
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-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
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-layer {
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-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
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-    decay_mult: 0.01
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-layer {
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-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
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-layer {
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-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
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-layer {
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-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
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-  top: "conv5_3/sep"
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-layer {
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-layer {
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-layer {
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-  top: "conv5_3/sep"
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-layer {
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-layer {
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-  top: "conv5_4/dw"
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-layer {
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-  top: "conv5_4/dw"
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-layer {
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-  top: "conv5_4/dw"
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-layer {
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-layer {
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-  top: "conv5_4/sep"
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-layer {
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-layer {
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-  top: "conv5_4/sep"
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-layer {
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-  top: "conv5_5/dw"
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-layer {
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-layer {
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-layer {
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-  top: "conv5_5/dw"
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-  top: "conv5_6/dw"
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19
-    max_size: 88
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx
-I0511 11:48:51.236408  4597 net.cpp:110] Using FLOAT as default forward math type
-I0511 11:48:51.236418  4597 net.cpp:116] Using FLOAT as default backward math type
-I0511 11:48:51.236423  4597 layer_factory.hpp:172] Creating layer 'data' of type 'AnnotatedData'
-I0511 11:48:51.236428  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.236750  4597 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:48:51.238076  4637 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0511 11:48:51.238101  4597 net.cpp:200] Created Layer data (0)
-I0511 11:48:51.238112  4597 net.cpp:542] data -> data
-I0511 11:48:51.238126  4597 net.cpp:542] data -> label
-I0511 11:48:51.238138  4597 data_reader.cpp:58] Data Reader threads: 1, out queues: 1, depth: 10
-I0511 11:48:51.238150  4597 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:48:51.319651  4638 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb
-I0511 11:48:51.321449  4597 annotated_data_layer.cpp:105] output data size: 10,3,256,512
-I0511 11:48:51.321525  4597 annotated_data_layer.cpp:150] (0) Output data size: 10, 3, 256, 512
-I0511 11:48:51.321573  4597 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:48:51.321605  4597 net.cpp:260] Setting up data
-I0511 11:48:51.322369  4643 data_layer.cpp:105] (0) Parser threads: 1
-I0511 11:48:51.322378  4643 data_layer.cpp:107] (0) Transformer threads: 1
-I0511 11:48:51.322372  4597 net.cpp:267] TEST Top shape for layer 0 'data' 10 3 256 512 (3932160)
-I0511 11:48:51.322409  4597 net.cpp:267] TEST Top shape for layer 0 'data' 1 1 2 8 (16)
-I0511 11:48:51.322435  4597 layer_factory.hpp:172] Creating layer 'data_data_0_split' of type 'Split'
-I0511 11:48:51.322450  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.322470  4597 net.cpp:200] Created Layer data_data_0_split (1)
-I0511 11:48:51.322485  4597 net.cpp:572] data_data_0_split <- data
-I0511 11:48:51.322504  4597 net.cpp:542] data_data_0_split -> data_data_0_split_0
-I0511 11:48:51.322520  4597 net.cpp:542] data_data_0_split -> data_data_0_split_1
-I0511 11:48:51.322532  4597 net.cpp:542] data_data_0_split -> data_data_0_split_2
-I0511 11:48:51.322547  4597 net.cpp:542] data_data_0_split -> data_data_0_split_3
-I0511 11:48:51.322561  4597 net.cpp:542] data_data_0_split -> data_data_0_split_4
-I0511 11:48:51.322572  4597 net.cpp:542] data_data_0_split -> data_data_0_split_5
-I0511 11:48:51.322645  4597 net.cpp:260] Setting up data_data_0_split
-I0511 11:48:51.322661  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322674  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322687  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322700  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322715  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322727  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322739  4597 layer_factory.hpp:172] Creating layer 'data/bias' of type 'Bias'
-I0511 11:48:51.322751  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.322769  4597 net.cpp:200] Created Layer data/bias (2)
-I0511 11:48:51.322782  4597 net.cpp:572] data/bias <- data_data_0_split_0
-I0511 11:48:51.322794  4597 net.cpp:542] data/bias -> data/bias
-I0511 11:48:51.323726  4597 net.cpp:260] Setting up data/bias
-I0511 11:48:51.323755  4597 net.cpp:267] TEST Top shape for layer 2 'data/bias' 10 3 256 512 (3932160)
-I0511 11:48:51.323776  4597 layer_factory.hpp:172] Creating layer 'conv1' of type 'Convolution'
-I0511 11:48:51.323792  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.323827  4597 net.cpp:200] Created Layer conv1 (3)
-I0511 11:48:51.323849  4597 net.cpp:572] conv1 <- data/bias
-I0511 11:48:51.323865  4597 net.cpp:542] conv1 -> conv1
-I0511 11:48:51.908941  4597 net.cpp:260] Setting up conv1
-I0511 11:48:51.908967  4597 net.cpp:267] TEST Top shape for layer 3 'conv1' 10 16 128 256 (5242880)
-I0511 11:48:51.908978  4597 layer_factory.hpp:172] Creating layer 'conv1/bn' of type 'BatchNorm'
-I0511 11:48:51.908983  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.908998  4597 net.cpp:200] Created Layer conv1/bn (4)
-I0511 11:48:51.909003  4597 net.cpp:572] conv1/bn <- conv1
-I0511 11:48:51.909006  4597 net.cpp:527] conv1/bn -> conv1 (in-place)
-I0511 11:48:51.909968  4597 net.cpp:260] Setting up conv1/bn
-I0511 11:48:51.909979  4597 net.cpp:267] TEST Top shape for layer 4 'conv1/bn' 10 16 128 256 (5242880)
-I0511 11:48:51.909987  4597 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Scale'
-I0511 11:48:51.909991  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.909998  4597 net.cpp:200] Created Layer conv1/scale (5)
-I0511 11:48:51.910001  4597 net.cpp:572] conv1/scale <- conv1
-I0511 11:48:51.910006  4597 net.cpp:527] conv1/scale -> conv1 (in-place)
-I0511 11:48:51.910037  4597 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Bias'
-I0511 11:48:51.910043  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.910143  4597 net.cpp:260] Setting up conv1/scale
-I0511 11:48:51.910148  4597 net.cpp:267] TEST Top shape for layer 5 'conv1/scale' 10 16 128 256 (5242880)
-I0511 11:48:51.910163  4597 layer_factory.hpp:172] Creating layer 'relu1' of type 'ReLU'
-I0511 11:48:51.910167  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.910171  4597 net.cpp:200] Created Layer relu1 (6)
-I0511 11:48:51.910173  4597 net.cpp:572] relu1 <- conv1
-I0511 11:48:51.910176  4597 net.cpp:527] relu1 -> conv1 (in-place)
-I0511 11:48:51.910190  4597 net.cpp:260] Setting up relu1
-I0511 11:48:51.910195  4597 net.cpp:267] TEST Top shape for layer 6 'relu1' 10 16 128 256 (5242880)
-I0511 11:48:51.910198  4597 layer_factory.hpp:172] Creating layer 'conv2_1/dw' of type 'Convolution'
-I0511 11:48:51.910202  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.910209  4597 net.cpp:200] Created Layer conv2_1/dw (7)
-I0511 11:48:51.910212  4597 net.cpp:572] conv2_1/dw <- conv1
-I0511 11:48:51.910215  4597 net.cpp:542] conv2_1/dw -> conv2_1/dw
-I0511 11:48:51.911314  4597 net.cpp:260] Setting up conv2_1/dw
-I0511 11:48:51.911322  4597 net.cpp:267] TEST Top shape for layer 7 'conv2_1/dw' 10 16 128 256 (5242880)
-I0511 11:48:51.911327  4597 layer_factory.hpp:172] Creating layer 'conv2_1/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.911330  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911335  4597 net.cpp:200] Created Layer conv2_1/dw/bn (8)
-I0511 11:48:51.911337  4597 net.cpp:572] conv2_1/dw/bn <- conv2_1/dw
-I0511 11:48:51.911340  4597 net.cpp:527] conv2_1/dw/bn -> conv2_1/dw (in-place)
-I0511 11:48:51.911597  4597 net.cpp:260] Setting up conv2_1/dw/bn
-I0511 11:48:51.911607  4597 net.cpp:267] TEST Top shape for layer 8 'conv2_1/dw/bn' 10 16 128 256 (5242880)
-I0511 11:48:51.911615  4597 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Scale'
-I0511 11:48:51.911619  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911624  4597 net.cpp:200] Created Layer conv2_1/dw/scale (9)
-I0511 11:48:51.911628  4597 net.cpp:572] conv2_1/dw/scale <- conv2_1/dw
-I0511 11:48:51.911631  4597 net.cpp:527] conv2_1/dw/scale -> conv2_1/dw (in-place)
-I0511 11:48:51.911661  4597 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Bias'
-I0511 11:48:51.911667  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911798  4597 net.cpp:260] Setting up conv2_1/dw/scale
-I0511 11:48:51.911806  4597 net.cpp:267] TEST Top shape for layer 9 'conv2_1/dw/scale' 10 16 128 256 (5242880)
-I0511 11:48:51.911813  4597 layer_factory.hpp:172] Creating layer 'relu2_1/dw' of type 'ReLU'
-I0511 11:48:51.911816  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911821  4597 net.cpp:200] Created Layer relu2_1/dw (10)
-I0511 11:48:51.911825  4597 net.cpp:572] relu2_1/dw <- conv2_1/dw
-I0511 11:48:51.911829  4597 net.cpp:527] relu2_1/dw -> conv2_1/dw (in-place)
-I0511 11:48:51.911835  4597 net.cpp:260] Setting up relu2_1/dw
-I0511 11:48:51.911841  4597 net.cpp:267] TEST Top shape for layer 10 'relu2_1/dw' 10 16 128 256 (5242880)
-I0511 11:48:51.911846  4597 layer_factory.hpp:172] Creating layer 'conv2_1/sep' of type 'Convolution'
-I0511 11:48:51.911850  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911860  4597 net.cpp:200] Created Layer conv2_1/sep (11)
-I0511 11:48:51.911865  4597 net.cpp:572] conv2_1/sep <- conv2_1/dw
-I0511 11:48:51.911870  4597 net.cpp:542] conv2_1/sep -> conv2_1/sep
-I0511 11:48:51.912060  4597 net.cpp:260] Setting up conv2_1/sep
-I0511 11:48:51.912070  4597 net.cpp:267] TEST Top shape for layer 11 'conv2_1/sep' 10 32 128 256 (10485760)
-I0511 11:48:51.912076  4597 layer_factory.hpp:172] Creating layer 'conv2_1/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.912081  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912088  4597 net.cpp:200] Created Layer conv2_1/sep/bn (12)
-I0511 11:48:51.912103  4597 net.cpp:572] conv2_1/sep/bn <- conv2_1/sep
-I0511 11:48:51.912108  4597 net.cpp:527] conv2_1/sep/bn -> conv2_1/sep (in-place)
-I0511 11:48:51.912474  4597 net.cpp:260] Setting up conv2_1/sep/bn
-I0511 11:48:51.912482  4597 net.cpp:267] TEST Top shape for layer 12 'conv2_1/sep/bn' 10 32 128 256 (10485760)
-I0511 11:48:51.912493  4597 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Scale'
-I0511 11:48:51.912498  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912505  4597 net.cpp:200] Created Layer conv2_1/sep/scale (13)
-I0511 11:48:51.912510  4597 net.cpp:572] conv2_1/sep/scale <- conv2_1/sep
-I0511 11:48:51.912515  4597 net.cpp:527] conv2_1/sep/scale -> conv2_1/sep (in-place)
-I0511 11:48:51.912554  4597 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Bias'
-I0511 11:48:51.912559  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912694  4597 net.cpp:260] Setting up conv2_1/sep/scale
-I0511 11:48:51.912701  4597 net.cpp:267] TEST Top shape for layer 13 'conv2_1/sep/scale' 10 32 128 256 (10485760)
-I0511 11:48:51.912708  4597 layer_factory.hpp:172] Creating layer 'relu2_1/sep' of type 'ReLU'
-I0511 11:48:51.912714  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912719  4597 net.cpp:200] Created Layer relu2_1/sep (14)
-I0511 11:48:51.912722  4597 net.cpp:572] relu2_1/sep <- conv2_1/sep
-I0511 11:48:51.912727  4597 net.cpp:527] relu2_1/sep -> conv2_1/sep (in-place)
-I0511 11:48:51.912734  4597 net.cpp:260] Setting up relu2_1/sep
-I0511 11:48:51.912739  4597 net.cpp:267] TEST Top shape for layer 14 'relu2_1/sep' 10 32 128 256 (10485760)
-I0511 11:48:51.912744  4597 layer_factory.hpp:172] Creating layer 'conv2_2/dw' of type 'Convolution'
-I0511 11:48:51.912747  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912756  4597 net.cpp:200] Created Layer conv2_2/dw (15)
-I0511 11:48:51.912761  4597 net.cpp:572] conv2_2/dw <- conv2_1/sep
-I0511 11:48:51.912766  4597 net.cpp:542] conv2_2/dw -> conv2_2/dw
-I0511 11:48:51.912925  4597 net.cpp:260] Setting up conv2_2/dw
-I0511 11:48:51.912931  4597 net.cpp:267] TEST Top shape for layer 15 'conv2_2/dw' 10 32 64 128 (2621440)
-I0511 11:48:51.912936  4597 layer_factory.hpp:172] Creating layer 'conv2_2/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.912940  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912945  4597 net.cpp:200] Created Layer conv2_2/dw/bn (16)
-I0511 11:48:51.912948  4597 net.cpp:572] conv2_2/dw/bn <- conv2_2/dw
-I0511 11:48:51.912950  4597 net.cpp:527] conv2_2/dw/bn -> conv2_2/dw (in-place)
-I0511 11:48:51.913966  4597 net.cpp:260] Setting up conv2_2/dw/bn
-I0511 11:48:51.913981  4597 net.cpp:267] TEST Top shape for layer 16 'conv2_2/dw/bn' 10 32 64 128 (2621440)
-I0511 11:48:51.913990  4597 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Scale'
-I0511 11:48:51.913993  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.914002  4597 net.cpp:200] Created Layer conv2_2/dw/scale (17)
-I0511 11:48:51.914006  4597 net.cpp:572] conv2_2/dw/scale <- conv2_2/dw
-I0511 11:48:51.914011  4597 net.cpp:527] conv2_2/dw/scale -> conv2_2/dw (in-place)
-I0511 11:48:51.914037  4597 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Bias'
-I0511 11:48:51.914041  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.914115  4597 net.cpp:260] Setting up conv2_2/dw/scale
-I0511 11:48:51.914120  4597 net.cpp:267] TEST Top shape for layer 17 'conv2_2/dw/scale' 10 32 64 128 (2621440)
-I0511 11:48:51.914125  4597 layer_factory.hpp:172] Creating layer 'relu2_2/dw' of type 'ReLU'
-I0511 11:48:51.914129  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.914132  4597 net.cpp:200] Created Layer relu2_2/dw (18)
-I0511 11:48:51.914149  4597 net.cpp:572] relu2_2/dw <- conv2_2/dw
-I0511 11:48:51.914152  4597 net.cpp:527] relu2_2/dw -> conv2_2/dw (in-place)
-I0511 11:48:51.914157  4597 net.cpp:260] Setting up relu2_2/dw
-I0511 11:48:51.914162  4597 net.cpp:267] TEST Top shape for layer 18 'relu2_2/dw' 10 32 64 128 (2621440)
-I0511 11:48:51.914166  4597 layer_factory.hpp:172] Creating layer 'conv2_2/sep' of type 'Convolution'
-I0511 11:48:51.914170  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.914180  4597 net.cpp:200] Created Layer conv2_2/sep (19)
-I0511 11:48:51.914191  4597 net.cpp:572] conv2_2/sep <- conv2_2/dw
-I0511 11:48:51.914196  4597 net.cpp:542] conv2_2/sep -> conv2_2/sep
-I0511 11:48:51.915102  4597 net.cpp:260] Setting up conv2_2/sep
-I0511 11:48:51.915114  4597 net.cpp:267] TEST Top shape for layer 19 'conv2_2/sep' 10 64 64 128 (5242880)
-I0511 11:48:51.915120  4597 layer_factory.hpp:172] Creating layer 'conv2_2/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.915127  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915134  4597 net.cpp:200] Created Layer conv2_2/sep/bn (20)
-I0511 11:48:51.915139  4597 net.cpp:572] conv2_2/sep/bn <- conv2_2/sep
-I0511 11:48:51.915143  4597 net.cpp:527] conv2_2/sep/bn -> conv2_2/sep (in-place)
-I0511 11:48:51.915386  4597 net.cpp:260] Setting up conv2_2/sep/bn
-I0511 11:48:51.915393  4597 net.cpp:267] TEST Top shape for layer 20 'conv2_2/sep/bn' 10 64 64 128 (5242880)
-I0511 11:48:51.915401  4597 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Scale'
-I0511 11:48:51.915406  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915412  4597 net.cpp:200] Created Layer conv2_2/sep/scale (21)
-I0511 11:48:51.915416  4597 net.cpp:572] conv2_2/sep/scale <- conv2_2/sep
-I0511 11:48:51.915421  4597 net.cpp:527] conv2_2/sep/scale -> conv2_2/sep (in-place)
-I0511 11:48:51.915449  4597 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Bias'
-I0511 11:48:51.915454  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915532  4597 net.cpp:260] Setting up conv2_2/sep/scale
-I0511 11:48:51.915539  4597 net.cpp:267] TEST Top shape for layer 21 'conv2_2/sep/scale' 10 64 64 128 (5242880)
-I0511 11:48:51.915545  4597 layer_factory.hpp:172] Creating layer 'relu2_2/sep' of type 'ReLU'
-I0511 11:48:51.915549  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915555  4597 net.cpp:200] Created Layer relu2_2/sep (22)
-I0511 11:48:51.915560  4597 net.cpp:572] relu2_2/sep <- conv2_2/sep
-I0511 11:48:51.915563  4597 net.cpp:527] relu2_2/sep -> conv2_2/sep (in-place)
-I0511 11:48:51.915570  4597 net.cpp:260] Setting up relu2_2/sep
-I0511 11:48:51.915575  4597 net.cpp:267] TEST Top shape for layer 22 'relu2_2/sep' 10 64 64 128 (5242880)
-I0511 11:48:51.915580  4597 layer_factory.hpp:172] Creating layer 'conv3_1/dw' of type 'Convolution'
-I0511 11:48:51.915585  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915596  4597 net.cpp:200] Created Layer conv3_1/dw (23)
-I0511 11:48:51.915598  4597 net.cpp:572] conv3_1/dw <- conv2_2/sep
-I0511 11:48:51.915603  4597 net.cpp:542] conv3_1/dw -> conv3_1/dw
-I0511 11:48:51.916445  4597 net.cpp:260] Setting up conv3_1/dw
-I0511 11:48:51.916452  4597 net.cpp:267] TEST Top shape for layer 23 'conv3_1/dw' 10 64 64 128 (5242880)
-I0511 11:48:51.916460  4597 layer_factory.hpp:172] Creating layer 'conv3_1/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.916463  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916471  4597 net.cpp:200] Created Layer conv3_1/dw/bn (24)
-I0511 11:48:51.916474  4597 net.cpp:572] conv3_1/dw/bn <- conv3_1/dw
-I0511 11:48:51.916479  4597 net.cpp:527] conv3_1/dw/bn -> conv3_1/dw (in-place)
-I0511 11:48:51.916718  4597 net.cpp:260] Setting up conv3_1/dw/bn
-I0511 11:48:51.916731  4597 net.cpp:267] TEST Top shape for layer 24 'conv3_1/dw/bn' 10 64 64 128 (5242880)
-I0511 11:48:51.916745  4597 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Scale'
-I0511 11:48:51.916750  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916756  4597 net.cpp:200] Created Layer conv3_1/dw/scale (25)
-I0511 11:48:51.916761  4597 net.cpp:572] conv3_1/dw/scale <- conv3_1/dw
-I0511 11:48:51.916765  4597 net.cpp:527] conv3_1/dw/scale -> conv3_1/dw (in-place)
-I0511 11:48:51.916792  4597 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Bias'
-I0511 11:48:51.916797  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916874  4597 net.cpp:260] Setting up conv3_1/dw/scale
-I0511 11:48:51.916882  4597 net.cpp:267] TEST Top shape for layer 25 'conv3_1/dw/scale' 10 64 64 128 (5242880)
-I0511 11:48:51.916888  4597 layer_factory.hpp:172] Creating layer 'relu3_1/dw' of type 'ReLU'
-I0511 11:48:51.916893  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916898  4597 net.cpp:200] Created Layer relu3_1/dw (26)
-I0511 11:48:51.916901  4597 net.cpp:572] relu3_1/dw <- conv3_1/dw
-I0511 11:48:51.916906  4597 net.cpp:527] relu3_1/dw -> conv3_1/dw (in-place)
-I0511 11:48:51.916913  4597 net.cpp:260] Setting up relu3_1/dw
-I0511 11:48:51.916918  4597 net.cpp:267] TEST Top shape for layer 26 'relu3_1/dw' 10 64 64 128 (5242880)
-I0511 11:48:51.916923  4597 layer_factory.hpp:172] Creating layer 'conv3_1/sep' of type 'Convolution'
-I0511 11:48:51.916926  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916937  4597 net.cpp:200] Created Layer conv3_1/sep (27)
-I0511 11:48:51.916941  4597 net.cpp:572] conv3_1/sep <- conv3_1/dw
-I0511 11:48:51.916945  4597 net.cpp:542] conv3_1/sep -> conv3_1/sep
-I0511 11:48:51.917141  4597 net.cpp:260] Setting up conv3_1/sep
-I0511 11:48:51.917148  4597 net.cpp:267] TEST Top shape for layer 27 'conv3_1/sep' 10 64 64 128 (5242880)
-I0511 11:48:51.917155  4597 layer_factory.hpp:172] Creating layer 'conv3_1/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.917160  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917165  4597 net.cpp:200] Created Layer conv3_1/sep/bn (28)
-I0511 11:48:51.917170  4597 net.cpp:572] conv3_1/sep/bn <- conv3_1/sep
-I0511 11:48:51.917174  4597 net.cpp:527] conv3_1/sep/bn -> conv3_1/sep (in-place)
-I0511 11:48:51.917400  4597 net.cpp:260] Setting up conv3_1/sep/bn
-I0511 11:48:51.917407  4597 net.cpp:267] TEST Top shape for layer 28 'conv3_1/sep/bn' 10 64 64 128 (5242880)
-I0511 11:48:51.917414  4597 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Scale'
-I0511 11:48:51.917418  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917425  4597 net.cpp:200] Created Layer conv3_1/sep/scale (29)
-I0511 11:48:51.917429  4597 net.cpp:572] conv3_1/sep/scale <- conv3_1/sep
-I0511 11:48:51.917433  4597 net.cpp:527] conv3_1/sep/scale -> conv3_1/sep (in-place)
-I0511 11:48:51.917460  4597 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Bias'
-I0511 11:48:51.917465  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917541  4597 net.cpp:260] Setting up conv3_1/sep/scale
-I0511 11:48:51.917547  4597 net.cpp:267] TEST Top shape for layer 29 'conv3_1/sep/scale' 10 64 64 128 (5242880)
-I0511 11:48:51.917554  4597 layer_factory.hpp:172] Creating layer 'relu3_1/sep' of type 'ReLU'
-I0511 11:48:51.917558  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917563  4597 net.cpp:200] Created Layer relu3_1/sep (30)
-I0511 11:48:51.917567  4597 net.cpp:572] relu3_1/sep <- conv3_1/sep
-I0511 11:48:51.917572  4597 net.cpp:527] relu3_1/sep -> conv3_1/sep (in-place)
-I0511 11:48:51.917583  4597 net.cpp:260] Setting up relu3_1/sep
-I0511 11:48:51.917589  4597 net.cpp:267] TEST Top shape for layer 30 'relu3_1/sep' 10 64 64 128 (5242880)
-I0511 11:48:51.917593  4597 layer_factory.hpp:172] Creating layer 'conv3_2/dw' of type 'Convolution'
-I0511 11:48:51.917598  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917606  4597 net.cpp:200] Created Layer conv3_2/dw (31)
-I0511 11:48:51.917610  4597 net.cpp:572] conv3_2/dw <- conv3_1/sep
-I0511 11:48:51.917614  4597 net.cpp:542] conv3_2/dw -> conv3_2/dw
-I0511 11:48:51.917747  4597 net.cpp:260] Setting up conv3_2/dw
-I0511 11:48:51.917753  4597 net.cpp:267] TEST Top shape for layer 31 'conv3_2/dw' 10 64 32 64 (1310720)
-I0511 11:48:51.917759  4597 layer_factory.hpp:172] Creating layer 'conv3_2/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.917764  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917770  4597 net.cpp:200] Created Layer conv3_2/dw/bn (32)
-I0511 11:48:51.917774  4597 net.cpp:572] conv3_2/dw/bn <- conv3_2/dw
-I0511 11:48:51.917779  4597 net.cpp:527] conv3_2/dw/bn -> conv3_2/dw (in-place)
-I0511 11:48:51.918004  4597 net.cpp:260] Setting up conv3_2/dw/bn
-I0511 11:48:51.918011  4597 net.cpp:267] TEST Top shape for layer 32 'conv3_2/dw/bn' 10 64 32 64 (1310720)
-I0511 11:48:51.918018  4597 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Scale'
-I0511 11:48:51.918022  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918028  4597 net.cpp:200] Created Layer conv3_2/dw/scale (33)
-I0511 11:48:51.918033  4597 net.cpp:572] conv3_2/dw/scale <- conv3_2/dw
-I0511 11:48:51.918037  4597 net.cpp:527] conv3_2/dw/scale -> conv3_2/dw (in-place)
-I0511 11:48:51.918066  4597 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Bias'
-I0511 11:48:51.918071  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918138  4597 net.cpp:260] Setting up conv3_2/dw/scale
-I0511 11:48:51.918144  4597 net.cpp:267] TEST Top shape for layer 33 'conv3_2/dw/scale' 10 64 32 64 (1310720)
-I0511 11:48:51.918150  4597 layer_factory.hpp:172] Creating layer 'relu3_2/dw' of type 'ReLU'
-I0511 11:48:51.918155  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918160  4597 net.cpp:200] Created Layer relu3_2/dw (34)
-I0511 11:48:51.918164  4597 net.cpp:572] relu3_2/dw <- conv3_2/dw
-I0511 11:48:51.918169  4597 net.cpp:527] relu3_2/dw -> conv3_2/dw (in-place)
-I0511 11:48:51.918175  4597 net.cpp:260] Setting up relu3_2/dw
-I0511 11:48:51.918180  4597 net.cpp:267] TEST Top shape for layer 34 'relu3_2/dw' 10 64 32 64 (1310720)
-I0511 11:48:51.918184  4597 layer_factory.hpp:172] Creating layer 'conv3_2/sep' of type 'Convolution'
-I0511 11:48:51.918190  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918197  4597 net.cpp:200] Created Layer conv3_2/sep (35)
-I0511 11:48:51.918200  4597 net.cpp:572] conv3_2/sep <- conv3_2/dw
-I0511 11:48:51.918205  4597 net.cpp:542] conv3_2/sep -> conv3_2/sep
-I0511 11:48:51.918478  4597 net.cpp:260] Setting up conv3_2/sep
-I0511 11:48:51.918483  4597 net.cpp:267] TEST Top shape for layer 35 'conv3_2/sep' 10 128 32 64 (2621440)
-I0511 11:48:51.918490  4597 layer_factory.hpp:172] Creating layer 'conv3_2/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.918494  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918500  4597 net.cpp:200] Created Layer conv3_2/sep/bn (36)
-I0511 11:48:51.918505  4597 net.cpp:572] conv3_2/sep/bn <- conv3_2/sep
-I0511 11:48:51.918509  4597 net.cpp:527] conv3_2/sep/bn -> conv3_2/sep (in-place)
-I0511 11:48:51.918715  4597 net.cpp:260] Setting up conv3_2/sep/bn
-I0511 11:48:51.918721  4597 net.cpp:267] TEST Top shape for layer 36 'conv3_2/sep/bn' 10 128 32 64 (2621440)
-I0511 11:48:51.918728  4597 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Scale'
-I0511 11:48:51.918737  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918746  4597 net.cpp:200] Created Layer conv3_2/sep/scale (37)
-I0511 11:48:51.918751  4597 net.cpp:572] conv3_2/sep/scale <- conv3_2/sep
-I0511 11:48:51.918756  4597 net.cpp:527] conv3_2/sep/scale -> conv3_2/sep (in-place)
-I0511 11:48:51.918781  4597 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Bias'
-I0511 11:48:51.918787  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918850  4597 net.cpp:260] Setting up conv3_2/sep/scale
-I0511 11:48:51.918856  4597 net.cpp:267] TEST Top shape for layer 37 'conv3_2/sep/scale' 10 128 32 64 (2621440)
-I0511 11:48:51.918864  4597 layer_factory.hpp:172] Creating layer 'relu3_2/sep' of type 'ReLU'
-I0511 11:48:51.918867  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918874  4597 net.cpp:200] Created Layer relu3_2/sep (38)
-I0511 11:48:51.918877  4597 net.cpp:572] relu3_2/sep <- conv3_2/sep
-I0511 11:48:51.918882  4597 net.cpp:527] relu3_2/sep -> conv3_2/sep (in-place)
-I0511 11:48:51.918887  4597 net.cpp:260] Setting up relu3_2/sep
-I0511 11:48:51.918893  4597 net.cpp:267] TEST Top shape for layer 38 'relu3_2/sep' 10 128 32 64 (2621440)
-I0511 11:48:51.918897  4597 layer_factory.hpp:172] Creating layer 'conv4_1/dw' of type 'Convolution'
-I0511 11:48:51.918902  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918910  4597 net.cpp:200] Created Layer conv4_1/dw (39)
-I0511 11:48:51.918913  4597 net.cpp:572] conv4_1/dw <- conv3_2/sep
-I0511 11:48:51.918918  4597 net.cpp:542] conv4_1/dw -> conv4_1/dw
-I0511 11:48:51.919057  4597 net.cpp:260] Setting up conv4_1/dw
-I0511 11:48:51.919064  4597 net.cpp:267] TEST Top shape for layer 39 'conv4_1/dw' 10 128 32 64 (2621440)
-I0511 11:48:51.919070  4597 layer_factory.hpp:172] Creating layer 'conv4_1/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.919075  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919081  4597 net.cpp:200] Created Layer conv4_1/dw/bn (40)
-I0511 11:48:51.919085  4597 net.cpp:572] conv4_1/dw/bn <- conv4_1/dw
-I0511 11:48:51.919090  4597 net.cpp:527] conv4_1/dw/bn -> conv4_1/dw (in-place)
-I0511 11:48:51.919296  4597 net.cpp:260] Setting up conv4_1/dw/bn
-I0511 11:48:51.919301  4597 net.cpp:267] TEST Top shape for layer 40 'conv4_1/dw/bn' 10 128 32 64 (2621440)
-I0511 11:48:51.919309  4597 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Scale'
-I0511 11:48:51.919313  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919318  4597 net.cpp:200] Created Layer conv4_1/dw/scale (41)
-I0511 11:48:51.919323  4597 net.cpp:572] conv4_1/dw/scale <- conv4_1/dw
-I0511 11:48:51.919327  4597 net.cpp:527] conv4_1/dw/scale -> conv4_1/dw (in-place)
-I0511 11:48:51.919354  4597 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Bias'
-I0511 11:48:51.919359  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919420  4597 net.cpp:260] Setting up conv4_1/dw/scale
-I0511 11:48:51.919425  4597 net.cpp:267] TEST Top shape for layer 41 'conv4_1/dw/scale' 10 128 32 64 (2621440)
-I0511 11:48:51.919432  4597 layer_factory.hpp:172] Creating layer 'relu4_1/dw' of type 'ReLU'
-I0511 11:48:51.919436  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919441  4597 net.cpp:200] Created Layer relu4_1/dw (42)
-I0511 11:48:51.919446  4597 net.cpp:572] relu4_1/dw <- conv4_1/dw
-I0511 11:48:51.919450  4597 net.cpp:527] relu4_1/dw -> conv4_1/dw (in-place)
-I0511 11:48:51.919456  4597 net.cpp:260] Setting up relu4_1/dw
-I0511 11:48:51.919461  4597 net.cpp:267] TEST Top shape for layer 42 'relu4_1/dw' 10 128 32 64 (2621440)
-I0511 11:48:51.919466  4597 layer_factory.hpp:172] Creating layer 'conv4_1/sep' of type 'Convolution'
-I0511 11:48:51.919474  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919483  4597 net.cpp:200] Created Layer conv4_1/sep (43)
-I0511 11:48:51.919486  4597 net.cpp:572] conv4_1/sep <- conv4_1/dw
-I0511 11:48:51.919492  4597 net.cpp:542] conv4_1/sep -> conv4_1/sep
-I0511 11:48:51.919926  4597 net.cpp:260] Setting up conv4_1/sep
-I0511 11:48:51.919934  4597 net.cpp:267] TEST Top shape for layer 43 'conv4_1/sep' 10 128 32 64 (2621440)
-I0511 11:48:51.919939  4597 layer_factory.hpp:172] Creating layer 'conv4_1/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.919944  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919950  4597 net.cpp:200] Created Layer conv4_1/sep/bn (44)
-I0511 11:48:51.919955  4597 net.cpp:572] conv4_1/sep/bn <- conv4_1/sep
-I0511 11:48:51.919958  4597 net.cpp:527] conv4_1/sep/bn -> conv4_1/sep (in-place)
-I0511 11:48:51.920169  4597 net.cpp:260] Setting up conv4_1/sep/bn
-I0511 11:48:51.920176  4597 net.cpp:267] TEST Top shape for layer 44 'conv4_1/sep/bn' 10 128 32 64 (2621440)
-I0511 11:48:51.920186  4597 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Scale'
-I0511 11:48:51.920192  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920197  4597 net.cpp:200] Created Layer conv4_1/sep/scale (45)
-I0511 11:48:51.920202  4597 net.cpp:572] conv4_1/sep/scale <- conv4_1/sep
-I0511 11:48:51.920207  4597 net.cpp:527] conv4_1/sep/scale -> conv4_1/sep (in-place)
-I0511 11:48:51.920234  4597 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Bias'
-I0511 11:48:51.920239  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920303  4597 net.cpp:260] Setting up conv4_1/sep/scale
-I0511 11:48:51.920310  4597 net.cpp:267] TEST Top shape for layer 45 'conv4_1/sep/scale' 10 128 32 64 (2621440)
-I0511 11:48:51.920316  4597 layer_factory.hpp:172] Creating layer 'relu4_1/sep' of type 'ReLU'
-I0511 11:48:51.920320  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920325  4597 net.cpp:200] Created Layer relu4_1/sep (46)
-I0511 11:48:51.920331  4597 net.cpp:572] relu4_1/sep <- conv4_1/sep
-I0511 11:48:51.920334  4597 net.cpp:527] relu4_1/sep -> conv4_1/sep (in-place)
-I0511 11:48:51.920341  4597 net.cpp:260] Setting up relu4_1/sep
-I0511 11:48:51.920346  4597 net.cpp:267] TEST Top shape for layer 46 'relu4_1/sep' 10 128 32 64 (2621440)
-I0511 11:48:51.920351  4597 layer_factory.hpp:172] Creating layer 'conv4_2/dw' of type 'Convolution'
-I0511 11:48:51.920356  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920367  4597 net.cpp:200] Created Layer conv4_2/dw (47)
-I0511 11:48:51.920369  4597 net.cpp:572] conv4_2/dw <- conv4_1/sep
-I0511 11:48:51.920375  4597 net.cpp:542] conv4_2/dw -> conv4_2/dw
-I0511 11:48:51.920519  4597 net.cpp:260] Setting up conv4_2/dw
-I0511 11:48:51.920532  4597 net.cpp:267] TEST Top shape for layer 47 'conv4_2/dw' 10 128 16 32 (655360)
-I0511 11:48:51.920552  4597 layer_factory.hpp:172] Creating layer 'conv4_2/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.920557  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920562  4597 net.cpp:200] Created Layer conv4_2/dw/bn (48)
-I0511 11:48:51.920567  4597 net.cpp:572] conv4_2/dw/bn <- conv4_2/dw
-I0511 11:48:51.920572  4597 net.cpp:527] conv4_2/dw/bn -> conv4_2/dw (in-place)
-I0511 11:48:51.920794  4597 net.cpp:260] Setting up conv4_2/dw/bn
-I0511 11:48:51.920800  4597 net.cpp:267] TEST Top shape for layer 48 'conv4_2/dw/bn' 10 128 16 32 (655360)
-I0511 11:48:51.920809  4597 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Scale'
-I0511 11:48:51.920814  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920819  4597 net.cpp:200] Created Layer conv4_2/dw/scale (49)
-I0511 11:48:51.920831  4597 net.cpp:572] conv4_2/dw/scale <- conv4_2/dw
-I0511 11:48:51.920836  4597 net.cpp:527] conv4_2/dw/scale -> conv4_2/dw (in-place)
-I0511 11:48:51.920866  4597 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Bias'
-I0511 11:48:51.920871  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920940  4597 net.cpp:260] Setting up conv4_2/dw/scale
-I0511 11:48:51.920946  4597 net.cpp:267] TEST Top shape for layer 49 'conv4_2/dw/scale' 10 128 16 32 (655360)
-I0511 11:48:51.920953  4597 layer_factory.hpp:172] Creating layer 'relu4_2/dw' of type 'ReLU'
-I0511 11:48:51.920958  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920964  4597 net.cpp:200] Created Layer relu4_2/dw (50)
-I0511 11:48:51.920969  4597 net.cpp:572] relu4_2/dw <- conv4_2/dw
-I0511 11:48:51.920974  4597 net.cpp:527] relu4_2/dw -> conv4_2/dw (in-place)
-I0511 11:48:51.920980  4597 net.cpp:260] Setting up relu4_2/dw
-I0511 11:48:51.920986  4597 net.cpp:267] TEST Top shape for layer 50 'relu4_2/dw' 10 128 16 32 (655360)
-I0511 11:48:51.920991  4597 layer_factory.hpp:172] Creating layer 'conv4_2/sep' of type 'Convolution'
-I0511 11:48:51.920996  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.921006  4597 net.cpp:200] Created Layer conv4_2/sep (51)
-I0511 11:48:51.921010  4597 net.cpp:572] conv4_2/sep <- conv4_2/dw
-I0511 11:48:51.921015  4597 net.cpp:542] conv4_2/sep -> conv4_2/sep
-I0511 11:48:51.921761  4597 net.cpp:260] Setting up conv4_2/sep
-I0511 11:48:51.921768  4597 net.cpp:267] TEST Top shape for layer 51 'conv4_2/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.921774  4597 layer_factory.hpp:172] Creating layer 'conv4_2/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.921779  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.921787  4597 net.cpp:200] Created Layer conv4_2/sep/bn (52)
-I0511 11:48:51.921792  4597 net.cpp:572] conv4_2/sep/bn <- conv4_2/sep
-I0511 11:48:51.921797  4597 net.cpp:527] conv4_2/sep/bn -> conv4_2/sep (in-place)
-I0511 11:48:51.922013  4597 net.cpp:260] Setting up conv4_2/sep/bn
-I0511 11:48:51.922019  4597 net.cpp:267] TEST Top shape for layer 52 'conv4_2/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.922026  4597 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Scale'
-I0511 11:48:51.922031  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922037  4597 net.cpp:200] Created Layer conv4_2/sep/scale (53)
-I0511 11:48:51.922042  4597 net.cpp:572] conv4_2/sep/scale <- conv4_2/sep
-I0511 11:48:51.922047  4597 net.cpp:527] conv4_2/sep/scale -> conv4_2/sep (in-place)
-I0511 11:48:51.922075  4597 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Bias'
-I0511 11:48:51.922080  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922147  4597 net.cpp:260] Setting up conv4_2/sep/scale
-I0511 11:48:51.922152  4597 net.cpp:267] TEST Top shape for layer 53 'conv4_2/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.922159  4597 layer_factory.hpp:172] Creating layer 'relu4_2/sep' of type 'ReLU'
-I0511 11:48:51.922164  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922170  4597 net.cpp:200] Created Layer relu4_2/sep (54)
-I0511 11:48:51.922175  4597 net.cpp:572] relu4_2/sep <- conv4_2/sep
-I0511 11:48:51.922180  4597 net.cpp:527] relu4_2/sep -> conv4_2/sep (in-place)
-I0511 11:48:51.922186  4597 net.cpp:260] Setting up relu4_2/sep
-I0511 11:48:51.922192  4597 net.cpp:267] TEST Top shape for layer 54 'relu4_2/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.922197  4597 layer_factory.hpp:172] Creating layer 'conv5_1/dw' of type 'Convolution'
-I0511 11:48:51.922202  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922216  4597 net.cpp:200] Created Layer conv5_1/dw (55)
-I0511 11:48:51.922225  4597 net.cpp:572] conv5_1/dw <- conv4_2/sep
-I0511 11:48:51.922230  4597 net.cpp:542] conv5_1/dw -> conv5_1/dw
-I0511 11:48:51.922397  4597 net.cpp:260] Setting up conv5_1/dw
-I0511 11:48:51.922405  4597 net.cpp:267] TEST Top shape for layer 55 'conv5_1/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.922410  4597 layer_factory.hpp:172] Creating layer 'conv5_1/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.922415  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922421  4597 net.cpp:200] Created Layer conv5_1/dw/bn (56)
-I0511 11:48:51.922426  4597 net.cpp:572] conv5_1/dw/bn <- conv5_1/dw
-I0511 11:48:51.922431  4597 net.cpp:527] conv5_1/dw/bn -> conv5_1/dw (in-place)
-I0511 11:48:51.922638  4597 net.cpp:260] Setting up conv5_1/dw/bn
-I0511 11:48:51.922644  4597 net.cpp:267] TEST Top shape for layer 56 'conv5_1/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.922652  4597 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Scale'
-I0511 11:48:51.922657  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922662  4597 net.cpp:200] Created Layer conv5_1/dw/scale (57)
-I0511 11:48:51.922667  4597 net.cpp:572] conv5_1/dw/scale <- conv5_1/dw
-I0511 11:48:51.922672  4597 net.cpp:527] conv5_1/dw/scale -> conv5_1/dw (in-place)
-I0511 11:48:51.922701  4597 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Bias'
-I0511 11:48:51.922705  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922770  4597 net.cpp:260] Setting up conv5_1/dw/scale
-I0511 11:48:51.922775  4597 net.cpp:267] TEST Top shape for layer 57 'conv5_1/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.922782  4597 layer_factory.hpp:172] Creating layer 'relu5_1/dw' of type 'ReLU'
-I0511 11:48:51.922786  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922792  4597 net.cpp:200] Created Layer relu5_1/dw (58)
-I0511 11:48:51.922796  4597 net.cpp:572] relu5_1/dw <- conv5_1/dw
-I0511 11:48:51.922801  4597 net.cpp:527] relu5_1/dw -> conv5_1/dw (in-place)
-I0511 11:48:51.922808  4597 net.cpp:260] Setting up relu5_1/dw
-I0511 11:48:51.922813  4597 net.cpp:267] TEST Top shape for layer 58 'relu5_1/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.922818  4597 layer_factory.hpp:172] Creating layer 'conv5_1/sep' of type 'Convolution'
-I0511 11:48:51.922823  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922832  4597 net.cpp:200] Created Layer conv5_1/sep (59)
-I0511 11:48:51.922837  4597 net.cpp:572] conv5_1/sep <- conv5_1/dw
-I0511 11:48:51.922842  4597 net.cpp:542] conv5_1/sep -> conv5_1/sep
-I0511 11:48:51.924191  4597 net.cpp:260] Setting up conv5_1/sep
-I0511 11:48:51.924198  4597 net.cpp:267] TEST Top shape for layer 59 'conv5_1/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.924204  4597 layer_factory.hpp:172] Creating layer 'conv5_1/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.924209  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924216  4597 net.cpp:200] Created Layer conv5_1/sep/bn (60)
-I0511 11:48:51.924221  4597 net.cpp:572] conv5_1/sep/bn <- conv5_1/sep
-I0511 11:48:51.924226  4597 net.cpp:527] conv5_1/sep/bn -> conv5_1/sep (in-place)
-I0511 11:48:51.924439  4597 net.cpp:260] Setting up conv5_1/sep/bn
-I0511 11:48:51.924445  4597 net.cpp:267] TEST Top shape for layer 60 'conv5_1/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.924453  4597 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Scale'
-I0511 11:48:51.924458  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924468  4597 net.cpp:200] Created Layer conv5_1/sep/scale (61)
-I0511 11:48:51.924473  4597 net.cpp:572] conv5_1/sep/scale <- conv5_1/sep
-I0511 11:48:51.924476  4597 net.cpp:527] conv5_1/sep/scale -> conv5_1/sep (in-place)
-I0511 11:48:51.924505  4597 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Bias'
-I0511 11:48:51.924516  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924602  4597 net.cpp:260] Setting up conv5_1/sep/scale
-I0511 11:48:51.924609  4597 net.cpp:267] TEST Top shape for layer 61 'conv5_1/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.924615  4597 layer_factory.hpp:172] Creating layer 'relu5_1/sep' of type 'ReLU'
-I0511 11:48:51.924620  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924625  4597 net.cpp:200] Created Layer relu5_1/sep (62)
-I0511 11:48:51.924630  4597 net.cpp:572] relu5_1/sep <- conv5_1/sep
-I0511 11:48:51.924634  4597 net.cpp:527] relu5_1/sep -> conv5_1/sep (in-place)
-I0511 11:48:51.924641  4597 net.cpp:260] Setting up relu5_1/sep
-I0511 11:48:51.924648  4597 net.cpp:267] TEST Top shape for layer 62 'relu5_1/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.924652  4597 layer_factory.hpp:172] Creating layer 'conv5_2/dw' of type 'Convolution'
-I0511 11:48:51.924656  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924669  4597 net.cpp:200] Created Layer conv5_2/dw (63)
-I0511 11:48:51.924674  4597 net.cpp:572] conv5_2/dw <- conv5_1/sep
-I0511 11:48:51.924677  4597 net.cpp:542] conv5_2/dw -> conv5_2/dw
-I0511 11:48:51.924844  4597 net.cpp:260] Setting up conv5_2/dw
-I0511 11:48:51.924850  4597 net.cpp:267] TEST Top shape for layer 63 'conv5_2/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.924856  4597 layer_factory.hpp:172] Creating layer 'conv5_2/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.924861  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924870  4597 net.cpp:200] Created Layer conv5_2/dw/bn (64)
-I0511 11:48:51.924875  4597 net.cpp:572] conv5_2/dw/bn <- conv5_2/dw
-I0511 11:48:51.924880  4597 net.cpp:527] conv5_2/dw/bn -> conv5_2/dw (in-place)
-I0511 11:48:51.925089  4597 net.cpp:260] Setting up conv5_2/dw/bn
-I0511 11:48:51.925096  4597 net.cpp:267] TEST Top shape for layer 64 'conv5_2/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.925103  4597 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Scale'
-I0511 11:48:51.925107  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.925113  4597 net.cpp:200] Created Layer conv5_2/dw/scale (65)
-I0511 11:48:51.925118  4597 net.cpp:572] conv5_2/dw/scale <- conv5_2/dw
-I0511 11:48:51.925123  4597 net.cpp:527] conv5_2/dw/scale -> conv5_2/dw (in-place)
-I0511 11:48:51.925153  4597 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Bias'
-I0511 11:48:51.925158  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.925225  4597 net.cpp:260] Setting up conv5_2/dw/scale
-I0511 11:48:51.925231  4597 net.cpp:267] TEST Top shape for layer 65 'conv5_2/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.925238  4597 layer_factory.hpp:172] Creating layer 'relu5_2/dw' of type 'ReLU'
-I0511 11:48:51.925242  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.925249  4597 net.cpp:200] Created Layer relu5_2/dw (66)
-I0511 11:48:51.925254  4597 net.cpp:572] relu5_2/dw <- conv5_2/dw
-I0511 11:48:51.925258  4597 net.cpp:527] relu5_2/dw -> conv5_2/dw (in-place)
-I0511 11:48:51.925266  4597 net.cpp:260] Setting up relu5_2/dw
-I0511 11:48:51.925271  4597 net.cpp:267] TEST Top shape for layer 66 'relu5_2/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.925277  4597 layer_factory.hpp:172] Creating layer 'conv5_2/sep' of type 'Convolution'
-I0511 11:48:51.925282  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.925292  4597 net.cpp:200] Created Layer conv5_2/sep (67)
-I0511 11:48:51.925297  4597 net.cpp:572] conv5_2/sep <- conv5_2/dw
-I0511 11:48:51.925302  4597 net.cpp:542] conv5_2/sep -> conv5_2/sep
-I0511 11:48:51.926657  4597 net.cpp:260] Setting up conv5_2/sep
-I0511 11:48:51.926679  4597 net.cpp:267] TEST Top shape for layer 67 'conv5_2/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.926686  4597 layer_factory.hpp:172] Creating layer 'conv5_2/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.926692  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.926698  4597 net.cpp:200] Created Layer conv5_2/sep/bn (68)
-I0511 11:48:51.926703  4597 net.cpp:572] conv5_2/sep/bn <- conv5_2/sep
-I0511 11:48:51.926708  4597 net.cpp:527] conv5_2/sep/bn -> conv5_2/sep (in-place)
-I0511 11:48:51.926934  4597 net.cpp:260] Setting up conv5_2/sep/bn
-I0511 11:48:51.926939  4597 net.cpp:267] TEST Top shape for layer 68 'conv5_2/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.926959  4597 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Scale'
-I0511 11:48:51.926965  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.926978  4597 net.cpp:200] Created Layer conv5_2/sep/scale (69)
-I0511 11:48:51.926982  4597 net.cpp:572] conv5_2/sep/scale <- conv5_2/sep
-I0511 11:48:51.926987  4597 net.cpp:527] conv5_2/sep/scale -> conv5_2/sep (in-place)
-I0511 11:48:51.927028  4597 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Bias'
-I0511 11:48:51.927033  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927104  4597 net.cpp:260] Setting up conv5_2/sep/scale
-I0511 11:48:51.927110  4597 net.cpp:267] TEST Top shape for layer 69 'conv5_2/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.927129  4597 layer_factory.hpp:172] Creating layer 'relu5_2/sep' of type 'ReLU'
-I0511 11:48:51.927134  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927139  4597 net.cpp:200] Created Layer relu5_2/sep (70)
-I0511 11:48:51.927145  4597 net.cpp:572] relu5_2/sep <- conv5_2/sep
-I0511 11:48:51.927155  4597 net.cpp:527] relu5_2/sep -> conv5_2/sep (in-place)
-I0511 11:48:51.927161  4597 net.cpp:260] Setting up relu5_2/sep
-I0511 11:48:51.927167  4597 net.cpp:267] TEST Top shape for layer 70 'relu5_2/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.927173  4597 layer_factory.hpp:172] Creating layer 'conv5_3/dw' of type 'Convolution'
-I0511 11:48:51.927183  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927196  4597 net.cpp:200] Created Layer conv5_3/dw (71)
-I0511 11:48:51.927199  4597 net.cpp:572] conv5_3/dw <- conv5_2/sep
-I0511 11:48:51.927204  4597 net.cpp:542] conv5_3/dw -> conv5_3/dw
-I0511 11:48:51.927382  4597 net.cpp:260] Setting up conv5_3/dw
-I0511 11:48:51.927389  4597 net.cpp:267] TEST Top shape for layer 71 'conv5_3/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.927397  4597 layer_factory.hpp:172] Creating layer 'conv5_3/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.927402  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927414  4597 net.cpp:200] Created Layer conv5_3/dw/bn (72)
-I0511 11:48:51.927418  4597 net.cpp:572] conv5_3/dw/bn <- conv5_3/dw
-I0511 11:48:51.927423  4597 net.cpp:527] conv5_3/dw/bn -> conv5_3/dw (in-place)
-I0511 11:48:51.927647  4597 net.cpp:260] Setting up conv5_3/dw/bn
-I0511 11:48:51.927654  4597 net.cpp:267] TEST Top shape for layer 72 'conv5_3/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.927669  4597 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Scale'
-I0511 11:48:51.927672  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927678  4597 net.cpp:200] Created Layer conv5_3/dw/scale (73)
-I0511 11:48:51.927683  4597 net.cpp:572] conv5_3/dw/scale <- conv5_3/dw
-I0511 11:48:51.927695  4597 net.cpp:527] conv5_3/dw/scale -> conv5_3/dw (in-place)
-I0511 11:48:51.927726  4597 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Bias'
-I0511 11:48:51.927731  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927804  4597 net.cpp:260] Setting up conv5_3/dw/scale
-I0511 11:48:51.927816  4597 net.cpp:267] TEST Top shape for layer 73 'conv5_3/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.927829  4597 layer_factory.hpp:172] Creating layer 'relu5_3/dw' of type 'ReLU'
-I0511 11:48:51.927834  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927839  4597 net.cpp:200] Created Layer relu5_3/dw (74)
-I0511 11:48:51.927845  4597 net.cpp:572] relu5_3/dw <- conv5_3/dw
-I0511 11:48:51.927850  4597 net.cpp:527] relu5_3/dw -> conv5_3/dw (in-place)
-I0511 11:48:51.927860  4597 net.cpp:260] Setting up relu5_3/dw
-I0511 11:48:51.927865  4597 net.cpp:267] TEST Top shape for layer 74 'relu5_3/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.927870  4597 layer_factory.hpp:172] Creating layer 'conv5_3/sep' of type 'Convolution'
-I0511 11:48:51.927873  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927882  4597 net.cpp:200] Created Layer conv5_3/sep (75)
-I0511 11:48:51.927887  4597 net.cpp:572] conv5_3/sep <- conv5_3/dw
-I0511 11:48:51.927891  4597 net.cpp:542] conv5_3/sep -> conv5_3/sep
-I0511 11:48:51.929265  4597 net.cpp:260] Setting up conv5_3/sep
-I0511 11:48:51.929272  4597 net.cpp:267] TEST Top shape for layer 75 'conv5_3/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.929286  4597 layer_factory.hpp:172] Creating layer 'conv5_3/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.929291  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929297  4597 net.cpp:200] Created Layer conv5_3/sep/bn (76)
-I0511 11:48:51.929302  4597 net.cpp:572] conv5_3/sep/bn <- conv5_3/sep
-I0511 11:48:51.929312  4597 net.cpp:527] conv5_3/sep/bn -> conv5_3/sep (in-place)
-I0511 11:48:51.929533  4597 net.cpp:260] Setting up conv5_3/sep/bn
-I0511 11:48:51.929539  4597 net.cpp:267] TEST Top shape for layer 76 'conv5_3/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.929548  4597 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Scale'
-I0511 11:48:51.929553  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929558  4597 net.cpp:200] Created Layer conv5_3/sep/scale (77)
-I0511 11:48:51.929563  4597 net.cpp:572] conv5_3/sep/scale <- conv5_3/sep
-I0511 11:48:51.929569  4597 net.cpp:527] conv5_3/sep/scale -> conv5_3/sep (in-place)
-I0511 11:48:51.929597  4597 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Bias'
-I0511 11:48:51.929602  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929668  4597 net.cpp:260] Setting up conv5_3/sep/scale
-I0511 11:48:51.929674  4597 net.cpp:267] TEST Top shape for layer 77 'conv5_3/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.929682  4597 layer_factory.hpp:172] Creating layer 'relu5_3/sep' of type 'ReLU'
-I0511 11:48:51.929687  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929692  4597 net.cpp:200] Created Layer relu5_3/sep (78)
-I0511 11:48:51.929697  4597 net.cpp:572] relu5_3/sep <- conv5_3/sep
-I0511 11:48:51.929702  4597 net.cpp:527] relu5_3/sep -> conv5_3/sep (in-place)
-I0511 11:48:51.929708  4597 net.cpp:260] Setting up relu5_3/sep
-I0511 11:48:51.929713  4597 net.cpp:267] TEST Top shape for layer 78 'relu5_3/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.929718  4597 layer_factory.hpp:172] Creating layer 'conv5_4/dw' of type 'Convolution'
-I0511 11:48:51.929723  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929731  4597 net.cpp:200] Created Layer conv5_4/dw (79)
-I0511 11:48:51.929736  4597 net.cpp:572] conv5_4/dw <- conv5_3/sep
-I0511 11:48:51.929740  4597 net.cpp:542] conv5_4/dw -> conv5_4/dw
-I0511 11:48:51.929903  4597 net.cpp:260] Setting up conv5_4/dw
-I0511 11:48:51.929910  4597 net.cpp:267] TEST Top shape for layer 79 'conv5_4/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.929916  4597 layer_factory.hpp:172] Creating layer 'conv5_4/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.929926  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929934  4597 net.cpp:200] Created Layer conv5_4/dw/bn (80)
-I0511 11:48:51.929939  4597 net.cpp:572] conv5_4/dw/bn <- conv5_4/dw
-I0511 11:48:51.929944  4597 net.cpp:527] conv5_4/dw/bn -> conv5_4/dw (in-place)
-I0511 11:48:51.930160  4597 net.cpp:260] Setting up conv5_4/dw/bn
-I0511 11:48:51.930166  4597 net.cpp:267] TEST Top shape for layer 80 'conv5_4/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.930174  4597 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Scale'
-I0511 11:48:51.930178  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.930184  4597 net.cpp:200] Created Layer conv5_4/dw/scale (81)
-I0511 11:48:51.930189  4597 net.cpp:572] conv5_4/dw/scale <- conv5_4/dw
-I0511 11:48:51.930194  4597 net.cpp:527] conv5_4/dw/scale -> conv5_4/dw (in-place)
-I0511 11:48:51.930224  4597 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Bias'
-I0511 11:48:51.930229  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.930294  4597 net.cpp:260] Setting up conv5_4/dw/scale
-I0511 11:48:51.930299  4597 net.cpp:267] TEST Top shape for layer 81 'conv5_4/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.930306  4597 layer_factory.hpp:172] Creating layer 'relu5_4/dw' of type 'ReLU'
-I0511 11:48:51.930311  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.930316  4597 net.cpp:200] Created Layer relu5_4/dw (82)
-I0511 11:48:51.930321  4597 net.cpp:572] relu5_4/dw <- conv5_4/dw
-I0511 11:48:51.930325  4597 net.cpp:527] relu5_4/dw -> conv5_4/dw (in-place)
-I0511 11:48:51.930332  4597 net.cpp:260] Setting up relu5_4/dw
-I0511 11:48:51.930337  4597 net.cpp:267] TEST Top shape for layer 82 'relu5_4/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.930342  4597 layer_factory.hpp:172] Creating layer 'conv5_4/sep' of type 'Convolution'
-I0511 11:48:51.930347  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.930356  4597 net.cpp:200] Created Layer conv5_4/sep (83)
-I0511 11:48:51.930361  4597 net.cpp:572] conv5_4/sep <- conv5_4/dw
-I0511 11:48:51.930366  4597 net.cpp:542] conv5_4/sep -> conv5_4/sep
-I0511 11:48:51.932469  4597 net.cpp:260] Setting up conv5_4/sep
-I0511 11:48:51.932483  4597 net.cpp:267] TEST Top shape for layer 83 'conv5_4/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.932492  4597 layer_factory.hpp:172] Creating layer 'conv5_4/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.932497  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932505  4597 net.cpp:200] Created Layer conv5_4/sep/bn (84)
-I0511 11:48:51.932512  4597 net.cpp:572] conv5_4/sep/bn <- conv5_4/sep
-I0511 11:48:51.932518  4597 net.cpp:527] conv5_4/sep/bn -> conv5_4/sep (in-place)
-I0511 11:48:51.932780  4597 net.cpp:260] Setting up conv5_4/sep/bn
-I0511 11:48:51.932786  4597 net.cpp:267] TEST Top shape for layer 84 'conv5_4/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.932795  4597 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Scale'
-I0511 11:48:51.932801  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932807  4597 net.cpp:200] Created Layer conv5_4/sep/scale (85)
-I0511 11:48:51.932812  4597 net.cpp:572] conv5_4/sep/scale <- conv5_4/sep
-I0511 11:48:51.932817  4597 net.cpp:527] conv5_4/sep/scale -> conv5_4/sep (in-place)
-I0511 11:48:51.932848  4597 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Bias'
-I0511 11:48:51.932853  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932924  4597 net.cpp:260] Setting up conv5_4/sep/scale
-I0511 11:48:51.932930  4597 net.cpp:267] TEST Top shape for layer 85 'conv5_4/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.932937  4597 layer_factory.hpp:172] Creating layer 'relu5_4/sep' of type 'ReLU'
-I0511 11:48:51.932948  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932955  4597 net.cpp:200] Created Layer relu5_4/sep (86)
-I0511 11:48:51.932960  4597 net.cpp:572] relu5_4/sep <- conv5_4/sep
-I0511 11:48:51.932965  4597 net.cpp:527] relu5_4/sep -> conv5_4/sep (in-place)
-I0511 11:48:51.932972  4597 net.cpp:260] Setting up relu5_4/sep
-I0511 11:48:51.932977  4597 net.cpp:267] TEST Top shape for layer 86 'relu5_4/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.932982  4597 layer_factory.hpp:172] Creating layer 'conv5_5/dw' of type 'Convolution'
-I0511 11:48:51.932987  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932997  4597 net.cpp:200] Created Layer conv5_5/dw (87)
-I0511 11:48:51.933001  4597 net.cpp:572] conv5_5/dw <- conv5_4/sep
-I0511 11:48:51.933006  4597 net.cpp:542] conv5_5/dw -> conv5_5/dw
-I0511 11:48:51.933207  4597 net.cpp:260] Setting up conv5_5/dw
-I0511 11:48:51.933217  4597 net.cpp:267] TEST Top shape for layer 87 'conv5_5/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.933223  4597 layer_factory.hpp:172] Creating layer 'conv5_5/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.933228  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933235  4597 net.cpp:200] Created Layer conv5_5/dw/bn (88)
-I0511 11:48:51.933240  4597 net.cpp:572] conv5_5/dw/bn <- conv5_5/dw
-I0511 11:48:51.933245  4597 net.cpp:527] conv5_5/dw/bn -> conv5_5/dw (in-place)
-I0511 11:48:51.933557  4597 net.cpp:260] Setting up conv5_5/dw/bn
-I0511 11:48:51.933564  4597 net.cpp:267] TEST Top shape for layer 88 'conv5_5/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.933581  4597 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Scale'
-I0511 11:48:51.933586  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933593  4597 net.cpp:200] Created Layer conv5_5/dw/scale (89)
-I0511 11:48:51.933598  4597 net.cpp:572] conv5_5/dw/scale <- conv5_5/dw
-I0511 11:48:51.933603  4597 net.cpp:527] conv5_5/dw/scale -> conv5_5/dw (in-place)
-I0511 11:48:51.933639  4597 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Bias'
-I0511 11:48:51.933645  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933737  4597 net.cpp:260] Setting up conv5_5/dw/scale
-I0511 11:48:51.933744  4597 net.cpp:267] TEST Top shape for layer 89 'conv5_5/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.933751  4597 layer_factory.hpp:172] Creating layer 'relu5_5/dw' of type 'ReLU'
-I0511 11:48:51.933756  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933761  4597 net.cpp:200] Created Layer relu5_5/dw (90)
-I0511 11:48:51.933766  4597 net.cpp:572] relu5_5/dw <- conv5_5/dw
-I0511 11:48:51.933770  4597 net.cpp:527] relu5_5/dw -> conv5_5/dw (in-place)
-I0511 11:48:51.933776  4597 net.cpp:260] Setting up relu5_5/dw
-I0511 11:48:51.933782  4597 net.cpp:267] TEST Top shape for layer 90 'relu5_5/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.933786  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep' of type 'Convolution'
-I0511 11:48:51.933791  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933801  4597 net.cpp:200] Created Layer conv5_5/sep (91)
-I0511 11:48:51.933805  4597 net.cpp:572] conv5_5/sep <- conv5_5/dw
-I0511 11:48:51.933811  4597 net.cpp:542] conv5_5/sep -> conv5_5/sep
-I0511 11:48:51.935364  4597 net.cpp:260] Setting up conv5_5/sep
-I0511 11:48:51.935371  4597 net.cpp:267] TEST Top shape for layer 91 'conv5_5/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.935379  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.935385  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935391  4597 net.cpp:200] Created Layer conv5_5/sep/bn (92)
-I0511 11:48:51.935402  4597 net.cpp:572] conv5_5/sep/bn <- conv5_5/sep
-I0511 11:48:51.935408  4597 net.cpp:527] conv5_5/sep/bn -> conv5_5/sep (in-place)
-I0511 11:48:51.935642  4597 net.cpp:260] Setting up conv5_5/sep/bn
-I0511 11:48:51.935647  4597 net.cpp:267] TEST Top shape for layer 92 'conv5_5/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.935655  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Scale'
-I0511 11:48:51.935660  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935667  4597 net.cpp:200] Created Layer conv5_5/sep/scale (93)
-I0511 11:48:51.935672  4597 net.cpp:572] conv5_5/sep/scale <- conv5_5/sep
-I0511 11:48:51.935678  4597 net.cpp:527] conv5_5/sep/scale -> conv5_5/sep (in-place)
-I0511 11:48:51.935708  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Bias'
-I0511 11:48:51.935711  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935781  4597 net.cpp:260] Setting up conv5_5/sep/scale
-I0511 11:48:51.935786  4597 net.cpp:267] TEST Top shape for layer 93 'conv5_5/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.935792  4597 layer_factory.hpp:172] Creating layer 'relu5_5/sep' of type 'ReLU'
-I0511 11:48:51.935797  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935803  4597 net.cpp:200] Created Layer relu5_5/sep (94)
-I0511 11:48:51.935808  4597 net.cpp:572] relu5_5/sep <- conv5_5/sep
-I0511 11:48:51.935813  4597 net.cpp:527] relu5_5/sep -> conv5_5/sep (in-place)
-I0511 11:48:51.935819  4597 net.cpp:260] Setting up relu5_5/sep
-I0511 11:48:51.935825  4597 net.cpp:267] TEST Top shape for layer 94 'relu5_5/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.935830  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep_relu5_5/sep_0_split' of type 'Split'
-I0511 11:48:51.935835  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935842  4597 net.cpp:200] Created Layer conv5_5/sep_relu5_5/sep_0_split (95)
-I0511 11:48:51.935847  4597 net.cpp:572] conv5_5/sep_relu5_5/sep_0_split <- conv5_5/sep
-I0511 11:48:51.935851  4597 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_0
-I0511 11:48:51.935859  4597 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_1
-I0511 11:48:51.935889  4597 net.cpp:260] Setting up conv5_5/sep_relu5_5/sep_0_split
-I0511 11:48:51.935894  4597 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 10 256 16 32 (1310720)
-I0511 11:48:51.935900  4597 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 10 256 16 32 (1310720)
-I0511 11:48:51.935905  4597 layer_factory.hpp:172] Creating layer 'conv5_6/dw' of type 'Convolution'
-I0511 11:48:51.935910  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935925  4597 net.cpp:200] Created Layer conv5_6/dw (96)
-I0511 11:48:51.935930  4597 net.cpp:572] conv5_6/dw <- conv5_5/sep_relu5_5/sep_0_split_0
-I0511 11:48:51.935935  4597 net.cpp:542] conv5_6/dw -> conv5_6/dw
-I0511 11:48:51.940685  4597 net.cpp:260] Setting up conv5_6/dw
-I0511 11:48:51.940699  4597 net.cpp:267] TEST Top shape for layer 96 'conv5_6/dw' 10 256 8 16 (327680)
-I0511 11:48:51.940706  4597 layer_factory.hpp:172] Creating layer 'conv5_6/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.940711  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.940719  4597 net.cpp:200] Created Layer conv5_6/dw/bn (97)
-I0511 11:48:51.940726  4597 net.cpp:572] conv5_6/dw/bn <- conv5_6/dw
-I0511 11:48:51.940731  4597 net.cpp:527] conv5_6/dw/bn -> conv5_6/dw (in-place)
-I0511 11:48:51.940969  4597 net.cpp:260] Setting up conv5_6/dw/bn
-I0511 11:48:51.940975  4597 net.cpp:267] TEST Top shape for layer 97 'conv5_6/dw/bn' 10 256 8 16 (327680)
-I0511 11:48:51.940984  4597 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Scale'
-I0511 11:48:51.940995  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.941002  4597 net.cpp:200] Created Layer conv5_6/dw/scale (98)
-I0511 11:48:51.941007  4597 net.cpp:572] conv5_6/dw/scale <- conv5_6/dw
-I0511 11:48:51.941012  4597 net.cpp:527] conv5_6/dw/scale -> conv5_6/dw (in-place)
-I0511 11:48:51.941043  4597 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Bias'
-I0511 11:48:51.941047  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.941123  4597 net.cpp:260] Setting up conv5_6/dw/scale
-I0511 11:48:51.941128  4597 net.cpp:267] TEST Top shape for layer 98 'conv5_6/dw/scale' 10 256 8 16 (327680)
-I0511 11:48:51.941135  4597 layer_factory.hpp:172] Creating layer 'relu5_6/dw' of type 'ReLU'
-I0511 11:48:51.941140  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.941145  4597 net.cpp:200] Created Layer relu5_6/dw (99)
-I0511 11:48:51.941150  4597 net.cpp:572] relu5_6/dw <- conv5_6/dw
-I0511 11:48:51.941155  4597 net.cpp:527] relu5_6/dw -> conv5_6/dw (in-place)
-I0511 11:48:51.941162  4597 net.cpp:260] Setting up relu5_6/dw
-I0511 11:48:51.941169  4597 net.cpp:267] TEST Top shape for layer 99 'relu5_6/dw' 10 256 8 16 (327680)
-I0511 11:48:51.941174  4597 layer_factory.hpp:172] Creating layer 'conv5_6/sep' of type 'Convolution'
-I0511 11:48:51.941177  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.941192  4597 net.cpp:200] Created Layer conv5_6/sep (100)
-I0511 11:48:51.941196  4597 net.cpp:572] conv5_6/sep <- conv5_6/dw
-I0511 11:48:51.941200  4597 net.cpp:542] conv5_6/sep -> conv5_6/sep
-I0511 11:48:51.943786  4597 net.cpp:260] Setting up conv5_6/sep
-I0511 11:48:51.943795  4597 net.cpp:267] TEST Top shape for layer 100 'conv5_6/sep' 10 512 8 16 (655360)
-I0511 11:48:51.943801  4597 layer_factory.hpp:172] Creating layer 'conv5_6/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.943806  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.943814  4597 net.cpp:200] Created Layer conv5_6/sep/bn (101)
-I0511 11:48:51.943819  4597 net.cpp:572] conv5_6/sep/bn <- conv5_6/sep
-I0511 11:48:51.943825  4597 net.cpp:527] conv5_6/sep/bn -> conv5_6/sep (in-place)
-I0511 11:48:51.944082  4597 net.cpp:260] Setting up conv5_6/sep/bn
-I0511 11:48:51.944088  4597 net.cpp:267] TEST Top shape for layer 101 'conv5_6/sep/bn' 10 512 8 16 (655360)
-I0511 11:48:51.944095  4597 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Scale'
-I0511 11:48:51.944102  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944108  4597 net.cpp:200] Created Layer conv5_6/sep/scale (102)
-I0511 11:48:51.944113  4597 net.cpp:572] conv5_6/sep/scale <- conv5_6/sep
-I0511 11:48:51.944119  4597 net.cpp:527] conv5_6/sep/scale -> conv5_6/sep (in-place)
-I0511 11:48:51.944154  4597 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Bias'
-I0511 11:48:51.944159  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944239  4597 net.cpp:260] Setting up conv5_6/sep/scale
-I0511 11:48:51.944245  4597 net.cpp:267] TEST Top shape for layer 102 'conv5_6/sep/scale' 10 512 8 16 (655360)
-I0511 11:48:51.944252  4597 layer_factory.hpp:172] Creating layer 'relu5_6/sep' of type 'ReLU'
-I0511 11:48:51.944258  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944263  4597 net.cpp:200] Created Layer relu5_6/sep (103)
-I0511 11:48:51.944268  4597 net.cpp:572] relu5_6/sep <- conv5_6/sep
-I0511 11:48:51.944273  4597 net.cpp:527] relu5_6/sep -> conv5_6/sep (in-place)
-I0511 11:48:51.944279  4597 net.cpp:260] Setting up relu5_6/sep
-I0511 11:48:51.944285  4597 net.cpp:267] TEST Top shape for layer 103 'relu5_6/sep' 10 512 8 16 (655360)
-I0511 11:48:51.944290  4597 layer_factory.hpp:172] Creating layer 'conv6/dw' of type 'Convolution'
-I0511 11:48:51.944303  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944311  4597 net.cpp:200] Created Layer conv6/dw (104)
-I0511 11:48:51.944315  4597 net.cpp:572] conv6/dw <- conv5_6/sep
-I0511 11:48:51.944320  4597 net.cpp:542] conv6/dw -> conv6/dw
-I0511 11:48:51.944545  4597 net.cpp:260] Setting up conv6/dw
-I0511 11:48:51.944552  4597 net.cpp:267] TEST Top shape for layer 104 'conv6/dw' 10 512 8 16 (655360)
-I0511 11:48:51.944559  4597 layer_factory.hpp:172] Creating layer 'conv6/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.944564  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944571  4597 net.cpp:200] Created Layer conv6/dw/bn (105)
-I0511 11:48:51.944576  4597 net.cpp:572] conv6/dw/bn <- conv6/dw
-I0511 11:48:51.944581  4597 net.cpp:527] conv6/dw/bn -> conv6/dw (in-place)
-I0511 11:48:51.944815  4597 net.cpp:260] Setting up conv6/dw/bn
-I0511 11:48:51.944821  4597 net.cpp:267] TEST Top shape for layer 105 'conv6/dw/bn' 10 512 8 16 (655360)
-I0511 11:48:51.944829  4597 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Scale'
-I0511 11:48:51.944834  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944849  4597 net.cpp:200] Created Layer conv6/dw/scale (106)
-I0511 11:48:51.944852  4597 net.cpp:572] conv6/dw/scale <- conv6/dw
-I0511 11:48:51.944856  4597 net.cpp:527] conv6/dw/scale -> conv6/dw (in-place)
-I0511 11:48:51.944886  4597 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Bias'
-I0511 11:48:51.944891  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944967  4597 net.cpp:260] Setting up conv6/dw/scale
-I0511 11:48:51.944973  4597 net.cpp:267] TEST Top shape for layer 106 'conv6/dw/scale' 10 512 8 16 (655360)
-I0511 11:48:51.944979  4597 layer_factory.hpp:172] Creating layer 'relu6/dw' of type 'ReLU'
-I0511 11:48:51.944984  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944990  4597 net.cpp:200] Created Layer relu6/dw (107)
-I0511 11:48:51.944995  4597 net.cpp:572] relu6/dw <- conv6/dw
-I0511 11:48:51.945000  4597 net.cpp:527] relu6/dw -> conv6/dw (in-place)
-I0511 11:48:51.945008  4597 net.cpp:260] Setting up relu6/dw
-I0511 11:48:51.945013  4597 net.cpp:267] TEST Top shape for layer 107 'relu6/dw' 10 512 8 16 (655360)
-I0511 11:48:51.945017  4597 layer_factory.hpp:172] Creating layer 'conv6/sep' of type 'Convolution'
-I0511 11:48:51.945022  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.945031  4597 net.cpp:200] Created Layer conv6/sep (108)
-I0511 11:48:51.945035  4597 net.cpp:572] conv6/sep <- conv6/dw
-I0511 11:48:51.945040  4597 net.cpp:542] conv6/sep -> conv6/sep
-I0511 11:48:51.950122  4597 net.cpp:260] Setting up conv6/sep
-I0511 11:48:51.950141  4597 net.cpp:267] TEST Top shape for layer 108 'conv6/sep' 10 512 8 16 (655360)
-I0511 11:48:51.950148  4597 layer_factory.hpp:172] Creating layer 'conv6/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.950155  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950165  4597 net.cpp:200] Created Layer conv6/sep/bn (109)
-I0511 11:48:51.950170  4597 net.cpp:572] conv6/sep/bn <- conv6/sep
-I0511 11:48:51.950176  4597 net.cpp:527] conv6/sep/bn -> conv6/sep (in-place)
-I0511 11:48:51.950459  4597 net.cpp:260] Setting up conv6/sep/bn
-I0511 11:48:51.950464  4597 net.cpp:267] TEST Top shape for layer 109 'conv6/sep/bn' 10 512 8 16 (655360)
-I0511 11:48:51.950474  4597 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Scale'
-I0511 11:48:51.950477  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950484  4597 net.cpp:200] Created Layer conv6/sep/scale (110)
-I0511 11:48:51.950489  4597 net.cpp:572] conv6/sep/scale <- conv6/sep
-I0511 11:48:51.950495  4597 net.cpp:527] conv6/sep/scale -> conv6/sep (in-place)
-I0511 11:48:51.950534  4597 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Bias'
-I0511 11:48:51.950539  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950619  4597 net.cpp:260] Setting up conv6/sep/scale
-I0511 11:48:51.950626  4597 net.cpp:267] TEST Top shape for layer 110 'conv6/sep/scale' 10 512 8 16 (655360)
-I0511 11:48:51.950633  4597 layer_factory.hpp:172] Creating layer 'relu6/sep' of type 'ReLU'
-I0511 11:48:51.950637  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950644  4597 net.cpp:200] Created Layer relu6/sep (111)
-I0511 11:48:51.950647  4597 net.cpp:572] relu6/sep <- conv6/sep
-I0511 11:48:51.950652  4597 net.cpp:527] relu6/sep -> conv6/sep (in-place)
-I0511 11:48:51.950660  4597 net.cpp:260] Setting up relu6/sep
-I0511 11:48:51.950666  4597 net.cpp:267] TEST Top shape for layer 111 'relu6/sep' 10 512 8 16 (655360)
-I0511 11:48:51.950671  4597 layer_factory.hpp:172] Creating layer 'conv6/sep_relu6/sep_0_split' of type 'Split'
-I0511 11:48:51.950676  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950683  4597 net.cpp:200] Created Layer conv6/sep_relu6/sep_0_split (112)
-I0511 11:48:51.950688  4597 net.cpp:572] conv6/sep_relu6/sep_0_split <- conv6/sep
-I0511 11:48:51.950693  4597 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_0
-I0511 11:48:51.950700  4597 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_1
-I0511 11:48:51.950736  4597 net.cpp:260] Setting up conv6/sep_relu6/sep_0_split
-I0511 11:48:51.950742  4597 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.950747  4597 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.950752  4597 layer_factory.hpp:172] Creating layer 'pool6' of type 'Pooling'
-I0511 11:48:51.950757  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950768  4597 net.cpp:200] Created Layer pool6 (113)
-I0511 11:48:51.950773  4597 net.cpp:572] pool6 <- conv6/sep_relu6/sep_0_split_0
-I0511 11:48:51.950778  4597 net.cpp:542] pool6 -> pool6
-I0511 11:48:51.950829  4597 net.cpp:260] Setting up pool6
-I0511 11:48:51.950834  4597 net.cpp:267] TEST Top shape for layer 113 'pool6' 10 512 5 9 (230400)
-I0511 11:48:51.950839  4597 layer_factory.hpp:172] Creating layer 'pool6_pool6_0_split' of type 'Split'
-I0511 11:48:51.950844  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950850  4597 net.cpp:200] Created Layer pool6_pool6_0_split (114)
-I0511 11:48:51.950855  4597 net.cpp:572] pool6_pool6_0_split <- pool6
-I0511 11:48:51.950860  4597 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_0
-I0511 11:48:51.950866  4597 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_1
-I0511 11:48:51.950892  4597 net.cpp:260] Setting up pool6_pool6_0_split
-I0511 11:48:51.950898  4597 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.950903  4597 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.950908  4597 layer_factory.hpp:172] Creating layer 'pool7' of type 'Pooling'
-I0511 11:48:51.950913  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950919  4597 net.cpp:200] Created Layer pool7 (115)
-I0511 11:48:51.950925  4597 net.cpp:572] pool7 <- pool6_pool6_0_split_0
-I0511 11:48:51.950930  4597 net.cpp:542] pool7 -> pool7
-I0511 11:48:51.950965  4597 net.cpp:260] Setting up pool7
-I0511 11:48:51.950970  4597 net.cpp:267] TEST Top shape for layer 115 'pool7' 10 512 3 5 (76800)
-I0511 11:48:51.950975  4597 layer_factory.hpp:172] Creating layer 'pool7_pool7_0_split' of type 'Split'
-I0511 11:48:51.950980  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950991  4597 net.cpp:200] Created Layer pool7_pool7_0_split (116)
-I0511 11:48:51.950996  4597 net.cpp:572] pool7_pool7_0_split <- pool7
-I0511 11:48:51.951001  4597 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_0
-I0511 11:48:51.951007  4597 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_1
-I0511 11:48:51.951033  4597 net.cpp:260] Setting up pool7_pool7_0_split
-I0511 11:48:51.951038  4597 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.951045  4597 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.951050  4597 layer_factory.hpp:172] Creating layer 'pool8' of type 'Pooling'
-I0511 11:48:51.951055  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.951061  4597 net.cpp:200] Created Layer pool8 (117)
-I0511 11:48:51.951066  4597 net.cpp:572] pool8 <- pool7_pool7_0_split_0
-I0511 11:48:51.951071  4597 net.cpp:542] pool8 -> pool8
-I0511 11:48:51.951110  4597 net.cpp:260] Setting up pool8
-I0511 11:48:51.951122  4597 net.cpp:267] TEST Top shape for layer 117 'pool8' 10 512 3 5 (76800)
-I0511 11:48:51.951126  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1' of type 'Convolution'
-I0511 11:48:51.951131  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.951143  4597 net.cpp:200] Created Layer ctx_output1/1x1 (118)
-I0511 11:48:51.951148  4597 net.cpp:572] ctx_output1/1x1 <- conv5_5/sep_relu5_5/sep_0_split_1
-I0511 11:48:51.951153  4597 net.cpp:542] ctx_output1/1x1 -> ctx_output1/1x1
-I0511 11:48:51.955041  4597 net.cpp:260] Setting up ctx_output1/1x1
-I0511 11:48:51.955075  4597 net.cpp:267] TEST Top shape for layer 118 'ctx_output1/1x1' 10 512 16 32 (2621440)
-I0511 11:48:51.955086  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.955096  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.955118  4597 net.cpp:200] Created Layer ctx_output1/1x1/bn (119)
-I0511 11:48:51.955126  4597 net.cpp:572] ctx_output1/1x1/bn <- ctx_output1/1x1
-I0511 11:48:51.955133  4597 net.cpp:527] ctx_output1/1x1/bn -> ctx_output1/1x1 (in-place)
-I0511 11:48:51.955387  4597 net.cpp:260] Setting up ctx_output1/1x1/bn
-I0511 11:48:51.955394  4597 net.cpp:267] TEST Top shape for layer 119 'ctx_output1/1x1/bn' 10 512 16 32 (2621440)
-I0511 11:48:51.955404  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/relu' of type 'ReLU'
-I0511 11:48:51.955409  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.955415  4597 net.cpp:200] Created Layer ctx_output1/1x1/relu (120)
-I0511 11:48:51.955420  4597 net.cpp:572] ctx_output1/1x1/relu <- ctx_output1/1x1
-I0511 11:48:51.955425  4597 net.cpp:527] ctx_output1/1x1/relu -> ctx_output1/1x1 (in-place)
-I0511 11:48:51.955432  4597 net.cpp:260] Setting up ctx_output1/1x1/relu
-I0511 11:48:51.955438  4597 net.cpp:267] TEST Top shape for layer 120 'ctx_output1/1x1/relu' 10 512 16 32 (2621440)
-I0511 11:48:51.955442  4597 layer_factory.hpp:172] Creating layer 'ctx_output1' of type 'Convolution'
-I0511 11:48:51.955447  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.955459  4597 net.cpp:200] Created Layer ctx_output1 (121)
-I0511 11:48:51.955463  4597 net.cpp:572] ctx_output1 <- ctx_output1/1x1
-I0511 11:48:51.955468  4597 net.cpp:542] ctx_output1 -> ctx_output1
-I0511 11:48:51.955727  4597 net.cpp:260] Setting up ctx_output1
-I0511 11:48:51.955734  4597 net.cpp:267] TEST Top shape for layer 121 'ctx_output1' 10 512 16 32 (2621440)
-I0511 11:48:51.955741  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/bn' of type 'BatchNorm'
-I0511 11:48:51.955746  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.955754  4597 net.cpp:200] Created Layer ctx_output1/bn (122)
-I0511 11:48:51.955757  4597 net.cpp:572] ctx_output1/bn <- ctx_output1
-I0511 11:48:51.955773  4597 net.cpp:527] ctx_output1/bn -> ctx_output1 (in-place)
-I0511 11:48:51.956012  4597 net.cpp:260] Setting up ctx_output1/bn
-I0511 11:48:51.956018  4597 net.cpp:267] TEST Top shape for layer 122 'ctx_output1/bn' 10 512 16 32 (2621440)
-I0511 11:48:51.956028  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu' of type 'ReLU'
-I0511 11:48:51.956032  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.956037  4597 net.cpp:200] Created Layer ctx_output1/relu (123)
-I0511 11:48:51.956043  4597 net.cpp:572] ctx_output1/relu <- ctx_output1
-I0511 11:48:51.956048  4597 net.cpp:527] ctx_output1/relu -> ctx_output1 (in-place)
-I0511 11:48:51.956053  4597 net.cpp:260] Setting up ctx_output1/relu
-I0511 11:48:51.956059  4597 net.cpp:267] TEST Top shape for layer 123 'ctx_output1/relu' 10 512 16 32 (2621440)
-I0511 11:48:51.956064  4597 layer_factory.hpp:172] Creating layer 'ctx_output1_ctx_output1/relu_0_split' of type 'Split'
-I0511 11:48:51.956069  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.956075  4597 net.cpp:200] Created Layer ctx_output1_ctx_output1/relu_0_split (124)
-I0511 11:48:51.956080  4597 net.cpp:572] ctx_output1_ctx_output1/relu_0_split <- ctx_output1
-I0511 11:48:51.956085  4597 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_0
-I0511 11:48:51.956092  4597 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_1
-I0511 11:48:51.956099  4597 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_2
-I0511 11:48:51.956133  4597 net.cpp:260] Setting up ctx_output1_ctx_output1/relu_0_split
-I0511 11:48:51.956140  4597 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:48:51.956145  4597 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:48:51.956151  4597 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:48:51.956156  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1' of type 'Convolution'
-I0511 11:48:51.956161  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.956173  4597 net.cpp:200] Created Layer ctx_output2/1x1 (125)
-I0511 11:48:51.956177  4597 net.cpp:572] ctx_output2/1x1 <- conv6/sep_relu6/sep_0_split_1
-I0511 11:48:51.956183  4597 net.cpp:542] ctx_output2/1x1 -> ctx_output2/1x1
-I0511 11:48:51.961294  4597 net.cpp:260] Setting up ctx_output2/1x1
-I0511 11:48:51.961310  4597 net.cpp:267] TEST Top shape for layer 125 'ctx_output2/1x1' 10 512 8 16 (655360)
-I0511 11:48:51.961318  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.961324  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.961341  4597 net.cpp:200] Created Layer ctx_output2/1x1/bn (126)
-I0511 11:48:51.961345  4597 net.cpp:572] ctx_output2/1x1/bn <- ctx_output2/1x1
-I0511 11:48:51.961351  4597 net.cpp:527] ctx_output2/1x1/bn -> ctx_output2/1x1 (in-place)
-I0511 11:48:51.961596  4597 net.cpp:260] Setting up ctx_output2/1x1/bn
-I0511 11:48:51.961601  4597 net.cpp:267] TEST Top shape for layer 126 'ctx_output2/1x1/bn' 10 512 8 16 (655360)
-I0511 11:48:51.961611  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/relu' of type 'ReLU'
-I0511 11:48:51.961614  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.961621  4597 net.cpp:200] Created Layer ctx_output2/1x1/relu (127)
-I0511 11:48:51.961625  4597 net.cpp:572] ctx_output2/1x1/relu <- ctx_output2/1x1
-I0511 11:48:51.961630  4597 net.cpp:527] ctx_output2/1x1/relu -> ctx_output2/1x1 (in-place)
-I0511 11:48:51.961637  4597 net.cpp:260] Setting up ctx_output2/1x1/relu
-I0511 11:48:51.961642  4597 net.cpp:267] TEST Top shape for layer 127 'ctx_output2/1x1/relu' 10 512 8 16 (655360)
-I0511 11:48:51.961654  4597 layer_factory.hpp:172] Creating layer 'ctx_output2' of type 'Convolution'
-I0511 11:48:51.961659  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.961673  4597 net.cpp:200] Created Layer ctx_output2 (128)
-I0511 11:48:51.961678  4597 net.cpp:572] ctx_output2 <- ctx_output2/1x1
-I0511 11:48:51.961681  4597 net.cpp:542] ctx_output2 -> ctx_output2
-I0511 11:48:51.961938  4597 net.cpp:260] Setting up ctx_output2
-I0511 11:48:51.961946  4597 net.cpp:267] TEST Top shape for layer 128 'ctx_output2' 10 512 8 16 (655360)
-I0511 11:48:51.961952  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/bn' of type 'BatchNorm'
-I0511 11:48:51.961957  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.961963  4597 net.cpp:200] Created Layer ctx_output2/bn (129)
-I0511 11:48:51.961968  4597 net.cpp:572] ctx_output2/bn <- ctx_output2
-I0511 11:48:51.961973  4597 net.cpp:527] ctx_output2/bn -> ctx_output2 (in-place)
-I0511 11:48:51.962201  4597 net.cpp:260] Setting up ctx_output2/bn
-I0511 11:48:51.962208  4597 net.cpp:267] TEST Top shape for layer 129 'ctx_output2/bn' 10 512 8 16 (655360)
-I0511 11:48:51.962218  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu' of type 'ReLU'
-I0511 11:48:51.962221  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.962226  4597 net.cpp:200] Created Layer ctx_output2/relu (130)
-I0511 11:48:51.962231  4597 net.cpp:572] ctx_output2/relu <- ctx_output2
-I0511 11:48:51.962236  4597 net.cpp:527] ctx_output2/relu -> ctx_output2 (in-place)
-I0511 11:48:51.962242  4597 net.cpp:260] Setting up ctx_output2/relu
-I0511 11:48:51.962249  4597 net.cpp:267] TEST Top shape for layer 130 'ctx_output2/relu' 10 512 8 16 (655360)
-I0511 11:48:51.962254  4597 layer_factory.hpp:172] Creating layer 'ctx_output2_ctx_output2/relu_0_split' of type 'Split'
-I0511 11:48:51.962258  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.962265  4597 net.cpp:200] Created Layer ctx_output2_ctx_output2/relu_0_split (131)
-I0511 11:48:51.962270  4597 net.cpp:572] ctx_output2_ctx_output2/relu_0_split <- ctx_output2
-I0511 11:48:51.962275  4597 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_0
-I0511 11:48:51.962280  4597 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_1
-I0511 11:48:51.962286  4597 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_2
-I0511 11:48:51.962332  4597 net.cpp:260] Setting up ctx_output2_ctx_output2/relu_0_split
-I0511 11:48:51.962337  4597 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.962342  4597 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.962347  4597 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.962352  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1' of type 'Convolution'
-I0511 11:48:51.962357  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.962366  4597 net.cpp:200] Created Layer ctx_output3/1x1 (132)
-I0511 11:48:51.962371  4597 net.cpp:572] ctx_output3/1x1 <- pool6_pool6_0_split_1
-I0511 11:48:51.962378  4597 net.cpp:542] ctx_output3/1x1 -> ctx_output3/1x1
-I0511 11:48:51.968237  4597 net.cpp:260] Setting up ctx_output3/1x1
-I0511 11:48:51.968262  4597 net.cpp:267] TEST Top shape for layer 132 'ctx_output3/1x1' 10 512 5 9 (230400)
-I0511 11:48:51.968271  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.968276  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.968287  4597 net.cpp:200] Created Layer ctx_output3/1x1/bn (133)
-I0511 11:48:51.968305  4597 net.cpp:572] ctx_output3/1x1/bn <- ctx_output3/1x1
-I0511 11:48:51.968313  4597 net.cpp:527] ctx_output3/1x1/bn -> ctx_output3/1x1 (in-place)
-I0511 11:48:51.968598  4597 net.cpp:260] Setting up ctx_output3/1x1/bn
-I0511 11:48:51.968605  4597 net.cpp:267] TEST Top shape for layer 133 'ctx_output3/1x1/bn' 10 512 5 9 (230400)
-I0511 11:48:51.968616  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/relu' of type 'ReLU'
-I0511 11:48:51.968621  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.968627  4597 net.cpp:200] Created Layer ctx_output3/1x1/relu (134)
-I0511 11:48:51.968632  4597 net.cpp:572] ctx_output3/1x1/relu <- ctx_output3/1x1
-I0511 11:48:51.968637  4597 net.cpp:527] ctx_output3/1x1/relu -> ctx_output3/1x1 (in-place)
-I0511 11:48:51.968644  4597 net.cpp:260] Setting up ctx_output3/1x1/relu
-I0511 11:48:51.968650  4597 net.cpp:267] TEST Top shape for layer 134 'ctx_output3/1x1/relu' 10 512 5 9 (230400)
-I0511 11:48:51.968655  4597 layer_factory.hpp:172] Creating layer 'ctx_output3' of type 'Convolution'
-I0511 11:48:51.968659  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.968670  4597 net.cpp:200] Created Layer ctx_output3 (135)
-I0511 11:48:51.968675  4597 net.cpp:572] ctx_output3 <- ctx_output3/1x1
-I0511 11:48:51.968679  4597 net.cpp:542] ctx_output3 -> ctx_output3
-I0511 11:48:51.979056  4597 net.cpp:260] Setting up ctx_output3
-I0511 11:48:51.979081  4597 net.cpp:267] TEST Top shape for layer 135 'ctx_output3' 10 512 5 9 (230400)
-I0511 11:48:51.979090  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/bn' of type 'BatchNorm'
-I0511 11:48:51.979096  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.979120  4597 net.cpp:200] Created Layer ctx_output3/bn (136)
-I0511 11:48:51.979126  4597 net.cpp:572] ctx_output3/bn <- ctx_output3
-I0511 11:48:51.979130  4597 net.cpp:527] ctx_output3/bn -> ctx_output3 (in-place)
-I0511 11:48:51.979403  4597 net.cpp:260] Setting up ctx_output3/bn
-I0511 11:48:51.979410  4597 net.cpp:267] TEST Top shape for layer 136 'ctx_output3/bn' 10 512 5 9 (230400)
-I0511 11:48:51.979416  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu' of type 'ReLU'
-I0511 11:48:51.979418  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.979425  4597 net.cpp:200] Created Layer ctx_output3/relu (137)
-I0511 11:48:51.979429  4597 net.cpp:572] ctx_output3/relu <- ctx_output3
-I0511 11:48:51.979431  4597 net.cpp:527] ctx_output3/relu -> ctx_output3 (in-place)
-I0511 11:48:51.979435  4597 net.cpp:260] Setting up ctx_output3/relu
-I0511 11:48:51.979439  4597 net.cpp:267] TEST Top shape for layer 137 'ctx_output3/relu' 10 512 5 9 (230400)
-I0511 11:48:51.979441  4597 layer_factory.hpp:172] Creating layer 'ctx_output3_ctx_output3/relu_0_split' of type 'Split'
-I0511 11:48:51.979445  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.979451  4597 net.cpp:200] Created Layer ctx_output3_ctx_output3/relu_0_split (138)
-I0511 11:48:51.979457  4597 net.cpp:572] ctx_output3_ctx_output3/relu_0_split <- ctx_output3
-I0511 11:48:51.979463  4597 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_0
-I0511 11:48:51.979471  4597 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_1
-I0511 11:48:51.979476  4597 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_2
-I0511 11:48:51.979514  4597 net.cpp:260] Setting up ctx_output3_ctx_output3/relu_0_split
-I0511 11:48:51.979521  4597 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.979524  4597 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.979529  4597 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.979543  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1' of type 'Convolution'
-I0511 11:48:51.979548  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.979558  4597 net.cpp:200] Created Layer ctx_output4/1x1 (139)
-I0511 11:48:51.979563  4597 net.cpp:572] ctx_output4/1x1 <- pool7_pool7_0_split_1
-I0511 11:48:51.979568  4597 net.cpp:542] ctx_output4/1x1 -> ctx_output4/1x1
-I0511 11:48:51.984747  4597 net.cpp:260] Setting up ctx_output4/1x1
-I0511 11:48:51.984766  4597 net.cpp:267] TEST Top shape for layer 139 'ctx_output4/1x1' 10 512 3 5 (76800)
-I0511 11:48:51.984771  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.984776  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.984782  4597 net.cpp:200] Created Layer ctx_output4/1x1/bn (140)
-I0511 11:48:51.984786  4597 net.cpp:572] ctx_output4/1x1/bn <- ctx_output4/1x1
-I0511 11:48:51.984791  4597 net.cpp:527] ctx_output4/1x1/bn -> ctx_output4/1x1 (in-place)
-I0511 11:48:51.985059  4597 net.cpp:260] Setting up ctx_output4/1x1/bn
-I0511 11:48:51.985064  4597 net.cpp:267] TEST Top shape for layer 140 'ctx_output4/1x1/bn' 10 512 3 5 (76800)
-I0511 11:48:51.985070  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/relu' of type 'ReLU'
-I0511 11:48:51.985074  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985076  4597 net.cpp:200] Created Layer ctx_output4/1x1/relu (141)
-I0511 11:48:51.985079  4597 net.cpp:572] ctx_output4/1x1/relu <- ctx_output4/1x1
-I0511 11:48:51.985081  4597 net.cpp:527] ctx_output4/1x1/relu -> ctx_output4/1x1 (in-place)
-I0511 11:48:51.985085  4597 net.cpp:260] Setting up ctx_output4/1x1/relu
-I0511 11:48:51.985088  4597 net.cpp:267] TEST Top shape for layer 141 'ctx_output4/1x1/relu' 10 512 3 5 (76800)
-I0511 11:48:51.985091  4597 layer_factory.hpp:172] Creating layer 'ctx_output4' of type 'Convolution'
-I0511 11:48:51.985093  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985102  4597 net.cpp:200] Created Layer ctx_output4 (142)
-I0511 11:48:51.985117  4597 net.cpp:572] ctx_output4 <- ctx_output4/1x1
-I0511 11:48:51.985124  4597 net.cpp:542] ctx_output4 -> ctx_output4
-I0511 11:48:51.985402  4597 net.cpp:260] Setting up ctx_output4
-I0511 11:48:51.985409  4597 net.cpp:267] TEST Top shape for layer 142 'ctx_output4' 10 512 3 5 (76800)
-I0511 11:48:51.985414  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/bn' of type 'BatchNorm'
-I0511 11:48:51.985416  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985420  4597 net.cpp:200] Created Layer ctx_output4/bn (143)
-I0511 11:48:51.985424  4597 net.cpp:572] ctx_output4/bn <- ctx_output4
-I0511 11:48:51.985425  4597 net.cpp:527] ctx_output4/bn -> ctx_output4 (in-place)
-I0511 11:48:51.985668  4597 net.cpp:260] Setting up ctx_output4/bn
-I0511 11:48:51.985675  4597 net.cpp:267] TEST Top shape for layer 143 'ctx_output4/bn' 10 512 3 5 (76800)
-I0511 11:48:51.985683  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu' of type 'ReLU'
-I0511 11:48:51.985688  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985692  4597 net.cpp:200] Created Layer ctx_output4/relu (144)
-I0511 11:48:51.985697  4597 net.cpp:572] ctx_output4/relu <- ctx_output4
-I0511 11:48:51.985702  4597 net.cpp:527] ctx_output4/relu -> ctx_output4 (in-place)
-I0511 11:48:51.985707  4597 net.cpp:260] Setting up ctx_output4/relu
-I0511 11:48:51.985713  4597 net.cpp:267] TEST Top shape for layer 144 'ctx_output4/relu' 10 512 3 5 (76800)
-I0511 11:48:51.985718  4597 layer_factory.hpp:172] Creating layer 'ctx_output4_ctx_output4/relu_0_split' of type 'Split'
-I0511 11:48:51.985723  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985735  4597 net.cpp:200] Created Layer ctx_output4_ctx_output4/relu_0_split (145)
-I0511 11:48:51.985740  4597 net.cpp:572] ctx_output4_ctx_output4/relu_0_split <- ctx_output4
-I0511 11:48:51.985746  4597 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_0
-I0511 11:48:51.985754  4597 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_1
-I0511 11:48:51.985759  4597 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_2
-I0511 11:48:51.985796  4597 net.cpp:260] Setting up ctx_output4_ctx_output4/relu_0_split
-I0511 11:48:51.985801  4597 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.985806  4597 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.985812  4597 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.985817  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1' of type 'Convolution'
-I0511 11:48:51.985822  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985836  4597 net.cpp:200] Created Layer ctx_output5/1x1 (146)
-I0511 11:48:51.985841  4597 net.cpp:572] ctx_output5/1x1 <- pool8
-I0511 11:48:51.985846  4597 net.cpp:542] ctx_output5/1x1 -> ctx_output5/1x1
-I0511 11:48:51.992885  4597 net.cpp:260] Setting up ctx_output5/1x1
-I0511 11:48:51.992913  4597 net.cpp:267] TEST Top shape for layer 146 'ctx_output5/1x1' 10 512 3 5 (76800)
-I0511 11:48:51.992920  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.992925  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.992934  4597 net.cpp:200] Created Layer ctx_output5/1x1/bn (147)
-I0511 11:48:51.992940  4597 net.cpp:572] ctx_output5/1x1/bn <- ctx_output5/1x1
-I0511 11:48:51.992944  4597 net.cpp:527] ctx_output5/1x1/bn -> ctx_output5/1x1 (in-place)
-I0511 11:48:51.993245  4597 net.cpp:260] Setting up ctx_output5/1x1/bn
-I0511 11:48:51.993252  4597 net.cpp:267] TEST Top shape for layer 147 'ctx_output5/1x1/bn' 10 512 3 5 (76800)
-I0511 11:48:51.993258  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/relu' of type 'ReLU'
-I0511 11:48:51.993261  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993265  4597 net.cpp:200] Created Layer ctx_output5/1x1/relu (148)
-I0511 11:48:51.993268  4597 net.cpp:572] ctx_output5/1x1/relu <- ctx_output5/1x1
-I0511 11:48:51.993270  4597 net.cpp:527] ctx_output5/1x1/relu -> ctx_output5/1x1 (in-place)
-I0511 11:48:51.993279  4597 net.cpp:260] Setting up ctx_output5/1x1/relu
-I0511 11:48:51.993283  4597 net.cpp:267] TEST Top shape for layer 148 'ctx_output5/1x1/relu' 10 512 3 5 (76800)
-I0511 11:48:51.993289  4597 layer_factory.hpp:172] Creating layer 'ctx_output5' of type 'Convolution'
-I0511 11:48:51.993294  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993304  4597 net.cpp:200] Created Layer ctx_output5 (149)
-I0511 11:48:51.993309  4597 net.cpp:572] ctx_output5 <- ctx_output5/1x1
-I0511 11:48:51.993314  4597 net.cpp:542] ctx_output5 -> ctx_output5
-I0511 11:48:51.993585  4597 net.cpp:260] Setting up ctx_output5
-I0511 11:48:51.993592  4597 net.cpp:267] TEST Top shape for layer 149 'ctx_output5' 10 512 3 5 (76800)
-I0511 11:48:51.993597  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/bn' of type 'BatchNorm'
-I0511 11:48:51.993599  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993603  4597 net.cpp:200] Created Layer ctx_output5/bn (150)
-I0511 11:48:51.993607  4597 net.cpp:572] ctx_output5/bn <- ctx_output5
-I0511 11:48:51.993609  4597 net.cpp:527] ctx_output5/bn -> ctx_output5 (in-place)
-I0511 11:48:51.993860  4597 net.cpp:260] Setting up ctx_output5/bn
-I0511 11:48:51.993875  4597 net.cpp:267] TEST Top shape for layer 150 'ctx_output5/bn' 10 512 3 5 (76800)
-I0511 11:48:51.993880  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu' of type 'ReLU'
-I0511 11:48:51.993883  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993886  4597 net.cpp:200] Created Layer ctx_output5/relu (151)
-I0511 11:48:51.993888  4597 net.cpp:572] ctx_output5/relu <- ctx_output5
-I0511 11:48:51.993891  4597 net.cpp:527] ctx_output5/relu -> ctx_output5 (in-place)
-I0511 11:48:51.993894  4597 net.cpp:260] Setting up ctx_output5/relu
-I0511 11:48:51.993897  4597 net.cpp:267] TEST Top shape for layer 151 'ctx_output5/relu' 10 512 3 5 (76800)
-I0511 11:48:51.993899  4597 layer_factory.hpp:172] Creating layer 'ctx_output5_ctx_output5/relu_0_split' of type 'Split'
-I0511 11:48:51.993902  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993906  4597 net.cpp:200] Created Layer ctx_output5_ctx_output5/relu_0_split (152)
-I0511 11:48:51.993908  4597 net.cpp:572] ctx_output5_ctx_output5/relu_0_split <- ctx_output5
-I0511 11:48:51.993911  4597 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_0
-I0511 11:48:51.993916  4597 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_1
-I0511 11:48:51.993922  4597 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_2
-I0511 11:48:51.993968  4597 net.cpp:260] Setting up ctx_output5_ctx_output5/relu_0_split
-I0511 11:48:51.993973  4597 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.993978  4597 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.993983  4597 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.993988  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:51.993993  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.994004  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc (153)
-I0511 11:48:51.994009  4597 net.cpp:572] ctx_output1/relu_mbox_loc <- ctx_output1_ctx_output1/relu_0_split_0
-I0511 11:48:51.994014  4597 net.cpp:542] ctx_output1/relu_mbox_loc -> ctx_output1/relu_mbox_loc
-I0511 11:48:51.994343  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_loc
-I0511 11:48:51.994350  4597 net.cpp:267] TEST Top shape for layer 153 'ctx_output1/relu_mbox_loc' 10 16 16 32 (81920)
-I0511 11:48:51.994359  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:51.994364  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.994374  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_perm (154)
-I0511 11:48:51.994380  4597 net.cpp:572] ctx_output1/relu_mbox_loc_perm <- ctx_output1/relu_mbox_loc
-I0511 11:48:51.994385  4597 net.cpp:542] ctx_output1/relu_mbox_loc_perm -> ctx_output1/relu_mbox_loc_perm
-I0511 11:48:51.994464  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_perm
-I0511 11:48:51.994470  4597 net.cpp:267] TEST Top shape for layer 154 'ctx_output1/relu_mbox_loc_perm' 10 16 32 16 (81920)
-I0511 11:48:51.994475  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:51.994480  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.994488  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_flat (155)
-I0511 11:48:51.994493  4597 net.cpp:572] ctx_output1/relu_mbox_loc_flat <- ctx_output1/relu_mbox_loc_perm
-I0511 11:48:51.994498  4597 net.cpp:542] ctx_output1/relu_mbox_loc_flat -> ctx_output1/relu_mbox_loc_flat
-I0511 11:48:51.994599  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_flat
-I0511 11:48:51.994606  4597 net.cpp:267] TEST Top shape for layer 155 'ctx_output1/relu_mbox_loc_flat' 10 8192 (81920)
-I0511 11:48:51.994617  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:51.994622  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.994632  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf (156)
-I0511 11:48:51.994637  4597 net.cpp:572] ctx_output1/relu_mbox_conf <- ctx_output1_ctx_output1/relu_0_split_1
-I0511 11:48:51.994642  4597 net.cpp:542] ctx_output1/relu_mbox_conf -> ctx_output1/relu_mbox_conf
-I0511 11:48:51.995640  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_conf
-I0511 11:48:51.995647  4597 net.cpp:267] TEST Top shape for layer 156 'ctx_output1/relu_mbox_conf' 10 84 16 32 (430080)
-I0511 11:48:51.995656  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:51.995661  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.995667  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_perm (157)
-I0511 11:48:51.995673  4597 net.cpp:572] ctx_output1/relu_mbox_conf_perm <- ctx_output1/relu_mbox_conf
-I0511 11:48:51.995678  4597 net.cpp:542] ctx_output1/relu_mbox_conf_perm -> ctx_output1/relu_mbox_conf_perm
-I0511 11:48:51.995750  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_perm
-I0511 11:48:51.995756  4597 net.cpp:267] TEST Top shape for layer 157 'ctx_output1/relu_mbox_conf_perm' 10 16 32 84 (430080)
-I0511 11:48:51.995762  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:51.995766  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.995774  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_flat (158)
-I0511 11:48:51.995779  4597 net.cpp:572] ctx_output1/relu_mbox_conf_flat <- ctx_output1/relu_mbox_conf_perm
-I0511 11:48:51.995784  4597 net.cpp:542] ctx_output1/relu_mbox_conf_flat -> ctx_output1/relu_mbox_conf_flat
-I0511 11:48:51.997581  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_flat
-I0511 11:48:51.997593  4597 net.cpp:267] TEST Top shape for layer 158 'ctx_output1/relu_mbox_conf_flat' 10 43008 (430080)
-I0511 11:48:51.997599  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:51.997606  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.997628  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_priorbox (159)
-I0511 11:48:51.997633  4597 net.cpp:572] ctx_output1/relu_mbox_priorbox <- ctx_output1_ctx_output1/relu_0_split_2
-I0511 11:48:51.997640  4597 net.cpp:572] ctx_output1/relu_mbox_priorbox <- data_data_0_split_1
-I0511 11:48:51.997648  4597 net.cpp:542] ctx_output1/relu_mbox_priorbox -> ctx_output1/relu_mbox_priorbox
-I0511 11:48:51.997680  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_priorbox
-I0511 11:48:51.997687  4597 net.cpp:267] TEST Top shape for layer 159 'ctx_output1/relu_mbox_priorbox' 1 2 8192 (16384)
-I0511 11:48:51.997694  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:51.997697  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.997716  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc (160)
-I0511 11:48:51.997721  4597 net.cpp:572] ctx_output2/relu_mbox_loc <- ctx_output2_ctx_output2/relu_0_split_0
-I0511 11:48:51.997732  4597 net.cpp:542] ctx_output2/relu_mbox_loc -> ctx_output2/relu_mbox_loc
-I0511 11:48:51.998186  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_loc
-I0511 11:48:51.998195  4597 net.cpp:267] TEST Top shape for layer 160 'ctx_output2/relu_mbox_loc' 10 24 8 16 (30720)
-I0511 11:48:51.998203  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:51.998217  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.998236  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_perm (161)
-I0511 11:48:51.998241  4597 net.cpp:572] ctx_output2/relu_mbox_loc_perm <- ctx_output2/relu_mbox_loc
-I0511 11:48:51.998251  4597 net.cpp:542] ctx_output2/relu_mbox_loc_perm -> ctx_output2/relu_mbox_loc_perm
-I0511 11:48:51.998319  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_perm
-I0511 11:48:51.998325  4597 net.cpp:267] TEST Top shape for layer 161 'ctx_output2/relu_mbox_loc_perm' 10 8 16 24 (30720)
-I0511 11:48:51.998330  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:51.998340  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.998351  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_flat (162)
-I0511 11:48:51.998356  4597 net.cpp:572] ctx_output2/relu_mbox_loc_flat <- ctx_output2/relu_mbox_loc_perm
-I0511 11:48:51.998366  4597 net.cpp:542] ctx_output2/relu_mbox_loc_flat -> ctx_output2/relu_mbox_loc_flat
-I0511 11:48:51.998435  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_flat
-I0511 11:48:51.998442  4597 net.cpp:267] TEST Top shape for layer 162 'ctx_output2/relu_mbox_loc_flat' 10 3072 (30720)
-I0511 11:48:51.998447  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:51.998451  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.998466  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf (163)
-I0511 11:48:51.998471  4597 net.cpp:572] ctx_output2/relu_mbox_conf <- ctx_output2_ctx_output2/relu_0_split_1
-I0511 11:48:51.998481  4597 net.cpp:542] ctx_output2/relu_mbox_conf -> ctx_output2/relu_mbox_conf
-I0511 11:48:51.999861  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_conf
-I0511 11:48:51.999869  4597 net.cpp:267] TEST Top shape for layer 163 'ctx_output2/relu_mbox_conf' 10 126 8 16 (161280)
-I0511 11:48:51.999877  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:51.999882  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.999888  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_perm (164)
-I0511 11:48:51.999892  4597 net.cpp:572] ctx_output2/relu_mbox_conf_perm <- ctx_output2/relu_mbox_conf
-I0511 11:48:51.999898  4597 net.cpp:542] ctx_output2/relu_mbox_conf_perm -> ctx_output2/relu_mbox_conf_perm
-I0511 11:48:51.999964  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_perm
-I0511 11:48:51.999971  4597 net.cpp:267] TEST Top shape for layer 164 'ctx_output2/relu_mbox_conf_perm' 10 8 16 126 (161280)
-I0511 11:48:51.999976  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:51.999981  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.999986  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_flat (165)
-I0511 11:48:51.999991  4597 net.cpp:572] ctx_output2/relu_mbox_conf_flat <- ctx_output2/relu_mbox_conf_perm
-I0511 11:48:51.999997  4597 net.cpp:542] ctx_output2/relu_mbox_conf_flat -> ctx_output2/relu_mbox_conf_flat
-I0511 11:48:52.001277  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_flat
-I0511 11:48:52.001291  4597 net.cpp:267] TEST Top shape for layer 165 'ctx_output2/relu_mbox_conf_flat' 10 16128 (161280)
-I0511 11:48:52.001296  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:52.001302  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.001309  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_priorbox (166)
-I0511 11:48:52.001314  4597 net.cpp:572] ctx_output2/relu_mbox_priorbox <- ctx_output2_ctx_output2/relu_0_split_2
-I0511 11:48:52.001322  4597 net.cpp:572] ctx_output2/relu_mbox_priorbox <- data_data_0_split_2
-I0511 11:48:52.001327  4597 net.cpp:542] ctx_output2/relu_mbox_priorbox -> ctx_output2/relu_mbox_priorbox
-I0511 11:48:52.001364  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_priorbox
-I0511 11:48:52.001370  4597 net.cpp:267] TEST Top shape for layer 166 'ctx_output2/relu_mbox_priorbox' 1 2 3072 (6144)
-I0511 11:48:52.001375  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:52.001380  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.001397  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc (167)
-I0511 11:48:52.001401  4597 net.cpp:572] ctx_output3/relu_mbox_loc <- ctx_output3_ctx_output3/relu_0_split_0
-I0511 11:48:52.001407  4597 net.cpp:542] ctx_output3/relu_mbox_loc -> ctx_output3/relu_mbox_loc
-I0511 11:48:52.001842  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_loc
-I0511 11:48:52.001850  4597 net.cpp:267] TEST Top shape for layer 167 'ctx_output3/relu_mbox_loc' 10 24 5 9 (10800)
-I0511 11:48:52.001858  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:52.001863  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.001870  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_perm (168)
-I0511 11:48:52.001874  4597 net.cpp:572] ctx_output3/relu_mbox_loc_perm <- ctx_output3/relu_mbox_loc
-I0511 11:48:52.001880  4597 net.cpp:542] ctx_output3/relu_mbox_loc_perm -> ctx_output3/relu_mbox_loc_perm
-I0511 11:48:52.001947  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_perm
-I0511 11:48:52.001953  4597 net.cpp:267] TEST Top shape for layer 168 'ctx_output3/relu_mbox_loc_perm' 10 5 9 24 (10800)
-I0511 11:48:52.001958  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:52.001962  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.001969  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_flat (169)
-I0511 11:48:52.001973  4597 net.cpp:572] ctx_output3/relu_mbox_loc_flat <- ctx_output3/relu_mbox_loc_perm
-I0511 11:48:52.001979  4597 net.cpp:542] ctx_output3/relu_mbox_loc_flat -> ctx_output3/relu_mbox_loc_flat
-I0511 11:48:52.002033  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_flat
-I0511 11:48:52.002039  4597 net.cpp:267] TEST Top shape for layer 169 'ctx_output3/relu_mbox_loc_flat' 10 1080 (10800)
-I0511 11:48:52.002044  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:52.002049  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.002058  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf (170)
-I0511 11:48:52.002063  4597 net.cpp:572] ctx_output3/relu_mbox_conf <- ctx_output3_ctx_output3/relu_0_split_1
-I0511 11:48:52.002068  4597 net.cpp:542] ctx_output3/relu_mbox_conf -> ctx_output3/relu_mbox_conf
-I0511 11:48:52.003453  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_conf
-I0511 11:48:52.003460  4597 net.cpp:267] TEST Top shape for layer 170 'ctx_output3/relu_mbox_conf' 10 126 5 9 (56700)
-I0511 11:48:52.003468  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:52.003471  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.003485  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_perm (171)
-I0511 11:48:52.003491  4597 net.cpp:572] ctx_output3/relu_mbox_conf_perm <- ctx_output3/relu_mbox_conf
-I0511 11:48:52.003505  4597 net.cpp:542] ctx_output3/relu_mbox_conf_perm -> ctx_output3/relu_mbox_conf_perm
-I0511 11:48:52.003578  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_perm
-I0511 11:48:52.003585  4597 net.cpp:267] TEST Top shape for layer 171 'ctx_output3/relu_mbox_conf_perm' 10 5 9 126 (56700)
-I0511 11:48:52.003595  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:52.003600  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.003617  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_flat (172)
-I0511 11:48:52.003623  4597 net.cpp:572] ctx_output3/relu_mbox_conf_flat <- ctx_output3/relu_mbox_conf_perm
-I0511 11:48:52.003631  4597 net.cpp:542] ctx_output3/relu_mbox_conf_flat -> ctx_output3/relu_mbox_conf_flat
-I0511 11:48:52.003716  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_flat
-I0511 11:48:52.003723  4597 net.cpp:267] TEST Top shape for layer 172 'ctx_output3/relu_mbox_conf_flat' 10 5670 (56700)
-I0511 11:48:52.003732  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:52.003737  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.003747  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_priorbox (173)
-I0511 11:48:52.003752  4597 net.cpp:572] ctx_output3/relu_mbox_priorbox <- ctx_output3_ctx_output3/relu_0_split_2
-I0511 11:48:52.003762  4597 net.cpp:572] ctx_output3/relu_mbox_priorbox <- data_data_0_split_3
-I0511 11:48:52.003768  4597 net.cpp:542] ctx_output3/relu_mbox_priorbox -> ctx_output3/relu_mbox_priorbox
-I0511 11:48:52.003793  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_priorbox
-I0511 11:48:52.003799  4597 net.cpp:267] TEST Top shape for layer 173 'ctx_output3/relu_mbox_priorbox' 1 2 1080 (2160)
-I0511 11:48:52.003808  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:52.003813  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.003829  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc (174)
-I0511 11:48:52.003834  4597 net.cpp:572] ctx_output4/relu_mbox_loc <- ctx_output4_ctx_output4/relu_0_split_0
-I0511 11:48:52.003844  4597 net.cpp:542] ctx_output4/relu_mbox_loc -> ctx_output4/relu_mbox_loc
-I0511 11:48:52.004180  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_loc
-I0511 11:48:52.004187  4597 net.cpp:267] TEST Top shape for layer 174 'ctx_output4/relu_mbox_loc' 10 16 3 5 (2400)
-I0511 11:48:52.004200  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:52.004205  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.004216  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_perm (175)
-I0511 11:48:52.004220  4597 net.cpp:572] ctx_output4/relu_mbox_loc_perm <- ctx_output4/relu_mbox_loc
-I0511 11:48:52.004230  4597 net.cpp:542] ctx_output4/relu_mbox_loc_perm -> ctx_output4/relu_mbox_loc_perm
-I0511 11:48:52.004302  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_perm
-I0511 11:48:52.004309  4597 net.cpp:267] TEST Top shape for layer 175 'ctx_output4/relu_mbox_loc_perm' 10 3 5 16 (2400)
-I0511 11:48:52.004319  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:52.004323  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.004333  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_flat (176)
-I0511 11:48:52.004338  4597 net.cpp:572] ctx_output4/relu_mbox_loc_flat <- ctx_output4/relu_mbox_loc_perm
-I0511 11:48:52.004348  4597 net.cpp:542] ctx_output4/relu_mbox_loc_flat -> ctx_output4/relu_mbox_loc_flat
-I0511 11:48:52.004396  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_flat
-I0511 11:48:52.004403  4597 net.cpp:267] TEST Top shape for layer 176 'ctx_output4/relu_mbox_loc_flat' 10 240 (2400)
-I0511 11:48:52.004413  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:52.004417  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.004431  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf (177)
-I0511 11:48:52.004434  4597 net.cpp:572] ctx_output4/relu_mbox_conf <- ctx_output4_ctx_output4/relu_0_split_1
-I0511 11:48:52.004446  4597 net.cpp:542] ctx_output4/relu_mbox_conf -> ctx_output4/relu_mbox_conf
-I0511 11:48:52.005472  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_conf
-I0511 11:48:52.005484  4597 net.cpp:267] TEST Top shape for layer 177 'ctx_output4/relu_mbox_conf' 10 84 3 5 (12600)
-I0511 11:48:52.005498  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:52.005503  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.005515  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_perm (178)
-I0511 11:48:52.005520  4597 net.cpp:572] ctx_output4/relu_mbox_conf_perm <- ctx_output4/relu_mbox_conf
-I0511 11:48:52.005530  4597 net.cpp:542] ctx_output4/relu_mbox_conf_perm -> ctx_output4/relu_mbox_conf_perm
-I0511 11:48:52.005607  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_perm
-I0511 11:48:52.005614  4597 net.cpp:267] TEST Top shape for layer 178 'ctx_output4/relu_mbox_conf_perm' 10 3 5 84 (12600)
-I0511 11:48:52.005625  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:52.005630  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.005635  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_flat (179)
-I0511 11:48:52.005640  4597 net.cpp:572] ctx_output4/relu_mbox_conf_flat <- ctx_output4/relu_mbox_conf_perm
-I0511 11:48:52.005645  4597 net.cpp:542] ctx_output4/relu_mbox_conf_flat -> ctx_output4/relu_mbox_conf_flat
-I0511 11:48:52.005698  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_flat
-I0511 11:48:52.005704  4597 net.cpp:267] TEST Top shape for layer 179 'ctx_output4/relu_mbox_conf_flat' 10 1260 (12600)
-I0511 11:48:52.005709  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:52.005714  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.005722  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_priorbox (180)
-I0511 11:48:52.005728  4597 net.cpp:572] ctx_output4/relu_mbox_priorbox <- ctx_output4_ctx_output4/relu_0_split_2
-I0511 11:48:52.005734  4597 net.cpp:572] ctx_output4/relu_mbox_priorbox <- data_data_0_split_4
-I0511 11:48:52.005740  4597 net.cpp:542] ctx_output4/relu_mbox_priorbox -> ctx_output4/relu_mbox_priorbox
-I0511 11:48:52.005762  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_priorbox
-I0511 11:48:52.005767  4597 net.cpp:267] TEST Top shape for layer 180 'ctx_output4/relu_mbox_priorbox' 1 2 240 (480)
-I0511 11:48:52.005770  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:52.005776  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.005862  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc (181)
-I0511 11:48:52.005868  4597 net.cpp:572] ctx_output5/relu_mbox_loc <- ctx_output5_ctx_output5/relu_0_split_0
-I0511 11:48:52.005872  4597 net.cpp:542] ctx_output5/relu_mbox_loc -> ctx_output5/relu_mbox_loc
-I0511 11:48:52.006203  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_loc
-I0511 11:48:52.006211  4597 net.cpp:267] TEST Top shape for layer 181 'ctx_output5/relu_mbox_loc' 10 16 3 5 (2400)
-I0511 11:48:52.006217  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:52.006222  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.006228  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_perm (182)
-I0511 11:48:52.006234  4597 net.cpp:572] ctx_output5/relu_mbox_loc_perm <- ctx_output5/relu_mbox_loc
-I0511 11:48:52.006240  4597 net.cpp:542] ctx_output5/relu_mbox_loc_perm -> ctx_output5/relu_mbox_loc_perm
-I0511 11:48:52.006319  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_perm
-I0511 11:48:52.006323  4597 net.cpp:267] TEST Top shape for layer 182 'ctx_output5/relu_mbox_loc_perm' 10 3 5 16 (2400)
-I0511 11:48:52.006327  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:52.006340  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.006346  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_flat (183)
-I0511 11:48:52.006351  4597 net.cpp:572] ctx_output5/relu_mbox_loc_flat <- ctx_output5/relu_mbox_loc_perm
-I0511 11:48:52.006357  4597 net.cpp:542] ctx_output5/relu_mbox_loc_flat -> ctx_output5/relu_mbox_loc_flat
-I0511 11:48:52.006407  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_flat
-I0511 11:48:52.006413  4597 net.cpp:267] TEST Top shape for layer 183 'ctx_output5/relu_mbox_loc_flat' 10 240 (2400)
-I0511 11:48:52.006418  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:52.006423  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.006434  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf (184)
-I0511 11:48:52.006438  4597 net.cpp:572] ctx_output5/relu_mbox_conf <- ctx_output5_ctx_output5/relu_0_split_1
-I0511 11:48:52.006443  4597 net.cpp:542] ctx_output5/relu_mbox_conf -> ctx_output5/relu_mbox_conf
-I0511 11:48:52.007438  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_conf
-I0511 11:48:52.007445  4597 net.cpp:267] TEST Top shape for layer 184 'ctx_output5/relu_mbox_conf' 10 84 3 5 (12600)
-I0511 11:48:52.007452  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:52.007457  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007464  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_perm (185)
-I0511 11:48:52.007469  4597 net.cpp:572] ctx_output5/relu_mbox_conf_perm <- ctx_output5/relu_mbox_conf
-I0511 11:48:52.007475  4597 net.cpp:542] ctx_output5/relu_mbox_conf_perm -> ctx_output5/relu_mbox_conf_perm
-I0511 11:48:52.007549  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_perm
-I0511 11:48:52.007555  4597 net.cpp:267] TEST Top shape for layer 185 'ctx_output5/relu_mbox_conf_perm' 10 3 5 84 (12600)
-I0511 11:48:52.007560  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:52.007565  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007570  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_flat (186)
-I0511 11:48:52.007576  4597 net.cpp:572] ctx_output5/relu_mbox_conf_flat <- ctx_output5/relu_mbox_conf_perm
-I0511 11:48:52.007582  4597 net.cpp:542] ctx_output5/relu_mbox_conf_flat -> ctx_output5/relu_mbox_conf_flat
-I0511 11:48:52.007635  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_flat
-I0511 11:48:52.007642  4597 net.cpp:267] TEST Top shape for layer 186 'ctx_output5/relu_mbox_conf_flat' 10 1260 (12600)
-I0511 11:48:52.007647  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:52.007652  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007663  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_priorbox (187)
-I0511 11:48:52.007666  4597 net.cpp:572] ctx_output5/relu_mbox_priorbox <- ctx_output5_ctx_output5/relu_0_split_2
-I0511 11:48:52.007671  4597 net.cpp:572] ctx_output5/relu_mbox_priorbox <- data_data_0_split_5
-I0511 11:48:52.007678  4597 net.cpp:542] ctx_output5/relu_mbox_priorbox -> ctx_output5/relu_mbox_priorbox
-I0511 11:48:52.007699  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_priorbox
-I0511 11:48:52.007704  4597 net.cpp:267] TEST Top shape for layer 187 'ctx_output5/relu_mbox_priorbox' 1 2 240 (480)
-I0511 11:48:52.007709  4597 layer_factory.hpp:172] Creating layer 'mbox_loc' of type 'Concat'
-I0511 11:48:52.007714  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007722  4597 net.cpp:200] Created Layer mbox_loc (188)
-I0511 11:48:52.007726  4597 net.cpp:572] mbox_loc <- ctx_output1/relu_mbox_loc_flat
-I0511 11:48:52.007737  4597 net.cpp:572] mbox_loc <- ctx_output2/relu_mbox_loc_flat
-I0511 11:48:52.007743  4597 net.cpp:572] mbox_loc <- ctx_output3/relu_mbox_loc_flat
-I0511 11:48:52.007750  4597 net.cpp:572] mbox_loc <- ctx_output4/relu_mbox_loc_flat
-I0511 11:48:52.007755  4597 net.cpp:572] mbox_loc <- ctx_output5/relu_mbox_loc_flat
-I0511 11:48:52.007761  4597 net.cpp:542] mbox_loc -> mbox_loc
-I0511 11:48:52.007786  4597 net.cpp:260] Setting up mbox_loc
-I0511 11:48:52.007792  4597 net.cpp:267] TEST Top shape for layer 188 'mbox_loc' 10 12824 (128240)
-I0511 11:48:52.007797  4597 layer_factory.hpp:172] Creating layer 'mbox_conf' of type 'Concat'
-I0511 11:48:52.007802  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007808  4597 net.cpp:200] Created Layer mbox_conf (189)
-I0511 11:48:52.007814  4597 net.cpp:572] mbox_conf <- ctx_output1/relu_mbox_conf_flat
-I0511 11:48:52.007820  4597 net.cpp:572] mbox_conf <- ctx_output2/relu_mbox_conf_flat
-I0511 11:48:52.007827  4597 net.cpp:572] mbox_conf <- ctx_output3/relu_mbox_conf_flat
-I0511 11:48:52.007833  4597 net.cpp:572] mbox_conf <- ctx_output4/relu_mbox_conf_flat
-I0511 11:48:52.007838  4597 net.cpp:572] mbox_conf <- ctx_output5/relu_mbox_conf_flat
-I0511 11:48:52.007843  4597 net.cpp:542] mbox_conf -> mbox_conf
-I0511 11:48:52.007863  4597 net.cpp:260] Setting up mbox_conf
-I0511 11:48:52.007867  4597 net.cpp:267] TEST Top shape for layer 189 'mbox_conf' 10 67326 (673260)
-I0511 11:48:52.007872  4597 layer_factory.hpp:172] Creating layer 'mbox_priorbox' of type 'Concat'
-I0511 11:48:52.007877  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007884  4597 net.cpp:200] Created Layer mbox_priorbox (190)
-I0511 11:48:52.007889  4597 net.cpp:572] mbox_priorbox <- ctx_output1/relu_mbox_priorbox
-I0511 11:48:52.007894  4597 net.cpp:572] mbox_priorbox <- ctx_output2/relu_mbox_priorbox
-I0511 11:48:52.007900  4597 net.cpp:572] mbox_priorbox <- ctx_output3/relu_mbox_priorbox
-I0511 11:48:52.007905  4597 net.cpp:572] mbox_priorbox <- ctx_output4/relu_mbox_priorbox
-I0511 11:48:52.007910  4597 net.cpp:572] mbox_priorbox <- ctx_output5/relu_mbox_priorbox
-I0511 11:48:52.007916  4597 net.cpp:542] mbox_priorbox -> mbox_priorbox
-I0511 11:48:52.007941  4597 net.cpp:260] Setting up mbox_priorbox
-I0511 11:48:52.007946  4597 net.cpp:267] TEST Top shape for layer 190 'mbox_priorbox' 1 2 12824 (25648)
-I0511 11:48:52.007951  4597 layer_factory.hpp:172] Creating layer 'mbox_conf_reshape' of type 'Reshape'
-I0511 11:48:52.007956  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007964  4597 net.cpp:200] Created Layer mbox_conf_reshape (191)
-I0511 11:48:52.007969  4597 net.cpp:572] mbox_conf_reshape <- mbox_conf
-I0511 11:48:52.007973  4597 net.cpp:542] mbox_conf_reshape -> mbox_conf_reshape
-I0511 11:48:52.007993  4597 net.cpp:260] Setting up mbox_conf_reshape
-I0511 11:48:52.007998  4597 net.cpp:267] TEST Top shape for layer 191 'mbox_conf_reshape' 10 3206 21 (673260)
-I0511 11:48:52.008003  4597 layer_factory.hpp:172] Creating layer 'mbox_conf_softmax' of type 'Softmax'
-I0511 11:48:52.008008  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.008021  4597 net.cpp:200] Created Layer mbox_conf_softmax (192)
-I0511 11:48:52.008025  4597 net.cpp:572] mbox_conf_softmax <- mbox_conf_reshape
-I0511 11:48:52.008029  4597 net.cpp:542] mbox_conf_softmax -> mbox_conf_softmax
-I0511 11:48:52.008078  4597 net.cpp:260] Setting up mbox_conf_softmax
-I0511 11:48:52.008083  4597 net.cpp:267] TEST Top shape for layer 192 'mbox_conf_softmax' 10 3206 21 (673260)
-I0511 11:48:52.008090  4597 layer_factory.hpp:172] Creating layer 'mbox_conf_flatten' of type 'Flatten'
-I0511 11:48:52.008095  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.008098  4597 net.cpp:200] Created Layer mbox_conf_flatten (193)
-I0511 11:48:52.008101  4597 net.cpp:572] mbox_conf_flatten <- mbox_conf_softmax
-I0511 11:48:52.008108  4597 net.cpp:542] mbox_conf_flatten -> mbox_conf_flatten
-I0511 11:48:52.011179  4597 net.cpp:260] Setting up mbox_conf_flatten
-I0511 11:48:52.011201  4597 net.cpp:267] TEST Top shape for layer 193 'mbox_conf_flatten' 10 67326 (673260)
-I0511 11:48:52.011207  4597 layer_factory.hpp:172] Creating layer 'detection_out' of type 'DetectionOutput'
-I0511 11:48:52.011212  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.011232  4597 net.cpp:200] Created Layer detection_out (194)
-I0511 11:48:52.011236  4597 net.cpp:572] detection_out <- mbox_loc
-I0511 11:48:52.011241  4597 net.cpp:572] detection_out <- mbox_conf_flatten
-I0511 11:48:52.011245  4597 net.cpp:572] detection_out <- mbox_priorbox
-I0511 11:48:52.011247  4597 net.cpp:542] detection_out -> detection_out
-I0511 11:48:52.037533  4597 net.cpp:260] Setting up detection_out
-I0511 11:48:52.037564  4597 net.cpp:267] TEST Top shape for layer 194 'detection_out' 1 1 1 7 (7)
-I0511 11:48:52.037573  4597 layer_factory.hpp:172] Creating layer 'detection_eval' of type 'DetectionEvaluate'
-I0511 11:48:52.037580  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.037603  4597 net.cpp:200] Created Layer detection_eval (195)
-I0511 11:48:52.037611  4597 net.cpp:572] detection_eval <- detection_out
-I0511 11:48:52.037619  4597 net.cpp:572] detection_eval <- label
-I0511 11:48:52.037627  4597 net.cpp:542] detection_eval -> detection_eval
-I0511 11:48:52.038914  4597 net.cpp:260] Setting up detection_eval
-I0511 11:48:52.038928  4597 net.cpp:267] TEST Top shape for layer 195 'detection_eval' 1 1 21 5 (105)
-I0511 11:48:52.038936  4597 net.cpp:338] detection_eval does not need backward computation.
-I0511 11:48:52.038940  4597 net.cpp:338] detection_out does not need backward computation.
-I0511 11:48:52.038944  4597 net.cpp:338] mbox_conf_flatten does not need backward computation.
-I0511 11:48:52.038949  4597 net.cpp:338] mbox_conf_softmax does not need backward computation.
-I0511 11:48:52.038951  4597 net.cpp:338] mbox_conf_reshape does not need backward computation.
-I0511 11:48:52.038954  4597 net.cpp:338] mbox_priorbox does not need backward computation.
-I0511 11:48:52.038960  4597 net.cpp:338] mbox_conf does not need backward computation.
-I0511 11:48:52.038974  4597 net.cpp:338] mbox_loc does not need backward computation.
-I0511 11:48:52.038980  4597 net.cpp:338] ctx_output5/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.038986  4597 net.cpp:338] ctx_output5/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.038991  4597 net.cpp:338] ctx_output5/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.038996  4597 net.cpp:338] ctx_output5/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039001  4597 net.cpp:338] ctx_output5/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039006  4597 net.cpp:338] ctx_output5/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039011  4597 net.cpp:338] ctx_output5/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039016  4597 net.cpp:338] ctx_output4/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.039021  4597 net.cpp:338] ctx_output4/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.039026  4597 net.cpp:338] ctx_output4/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.039032  4597 net.cpp:338] ctx_output4/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039037  4597 net.cpp:338] ctx_output4/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039042  4597 net.cpp:338] ctx_output4/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039047  4597 net.cpp:338] ctx_output4/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039052  4597 net.cpp:338] ctx_output3/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.039057  4597 net.cpp:338] ctx_output3/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.039075  4597 net.cpp:338] ctx_output3/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.039080  4597 net.cpp:338] ctx_output3/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039085  4597 net.cpp:338] ctx_output3/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039090  4597 net.cpp:338] ctx_output3/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039095  4597 net.cpp:338] ctx_output3/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039100  4597 net.cpp:338] ctx_output2/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.039104  4597 net.cpp:338] ctx_output2/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.039109  4597 net.cpp:338] ctx_output2/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.039114  4597 net.cpp:338] ctx_output2/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039119  4597 net.cpp:338] ctx_output2/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039124  4597 net.cpp:338] ctx_output2/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039129  4597 net.cpp:338] ctx_output2/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039134  4597 net.cpp:338] ctx_output1/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.039139  4597 net.cpp:338] ctx_output1/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.039144  4597 net.cpp:338] ctx_output1/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.039149  4597 net.cpp:338] ctx_output1/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039153  4597 net.cpp:338] ctx_output1/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039157  4597 net.cpp:338] ctx_output1/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039162  4597 net.cpp:338] ctx_output1/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039168  4597 net.cpp:338] ctx_output5_ctx_output5/relu_0_split does not need backward computation.
-I0511 11:48:52.039173  4597 net.cpp:338] ctx_output5/relu does not need backward computation.
-I0511 11:48:52.039178  4597 net.cpp:338] ctx_output5/bn does not need backward computation.
-I0511 11:48:52.039182  4597 net.cpp:338] ctx_output5 does not need backward computation.
-I0511 11:48:52.039187  4597 net.cpp:338] ctx_output5/1x1/relu does not need backward computation.
-I0511 11:48:52.039192  4597 net.cpp:338] ctx_output5/1x1/bn does not need backward computation.
-I0511 11:48:52.039197  4597 net.cpp:338] ctx_output5/1x1 does not need backward computation.
-I0511 11:48:52.039202  4597 net.cpp:338] ctx_output4_ctx_output4/relu_0_split does not need backward computation.
-I0511 11:48:52.039207  4597 net.cpp:338] ctx_output4/relu does not need backward computation.
-I0511 11:48:52.039212  4597 net.cpp:338] ctx_output4/bn does not need backward computation.
-I0511 11:48:52.039216  4597 net.cpp:338] ctx_output4 does not need backward computation.
-I0511 11:48:52.039222  4597 net.cpp:338] ctx_output4/1x1/relu does not need backward computation.
-I0511 11:48:52.039227  4597 net.cpp:338] ctx_output4/1x1/bn does not need backward computation.
-I0511 11:48:52.039230  4597 net.cpp:338] ctx_output4/1x1 does not need backward computation.
-I0511 11:48:52.039237  4597 net.cpp:338] ctx_output3_ctx_output3/relu_0_split does not need backward computation.
-I0511 11:48:52.039242  4597 net.cpp:338] ctx_output3/relu does not need backward computation.
-I0511 11:48:52.039247  4597 net.cpp:338] ctx_output3/bn does not need backward computation.
-I0511 11:48:52.039252  4597 net.cpp:338] ctx_output3 does not need backward computation.
-I0511 11:48:52.039257  4597 net.cpp:338] ctx_output3/1x1/relu does not need backward computation.
-I0511 11:48:52.039261  4597 net.cpp:338] ctx_output3/1x1/bn does not need backward computation.
-I0511 11:48:52.039266  4597 net.cpp:338] ctx_output3/1x1 does not need backward computation.
-I0511 11:48:52.039278  4597 net.cpp:338] ctx_output2_ctx_output2/relu_0_split does not need backward computation.
-I0511 11:48:52.039283  4597 net.cpp:338] ctx_output2/relu does not need backward computation.
-I0511 11:48:52.039288  4597 net.cpp:338] ctx_output2/bn does not need backward computation.
-I0511 11:48:52.039291  4597 net.cpp:338] ctx_output2 does not need backward computation.
-I0511 11:48:52.039296  4597 net.cpp:338] ctx_output2/1x1/relu does not need backward computation.
-I0511 11:48:52.039301  4597 net.cpp:338] ctx_output2/1x1/bn does not need backward computation.
-I0511 11:48:52.039305  4597 net.cpp:338] ctx_output2/1x1 does not need backward computation.
-I0511 11:48:52.039311  4597 net.cpp:338] ctx_output1_ctx_output1/relu_0_split does not need backward computation.
-I0511 11:48:52.039316  4597 net.cpp:338] ctx_output1/relu does not need backward computation.
-I0511 11:48:52.039321  4597 net.cpp:338] ctx_output1/bn does not need backward computation.
-I0511 11:48:52.039325  4597 net.cpp:338] ctx_output1 does not need backward computation.
-I0511 11:48:52.039330  4597 net.cpp:338] ctx_output1/1x1/relu does not need backward computation.
-I0511 11:48:52.039335  4597 net.cpp:338] ctx_output1/1x1/bn does not need backward computation.
-I0511 11:48:52.039340  4597 net.cpp:338] ctx_output1/1x1 does not need backward computation.
-I0511 11:48:52.039345  4597 net.cpp:338] pool8 does not need backward computation.
-I0511 11:48:52.039351  4597 net.cpp:338] pool7_pool7_0_split does not need backward computation.
-I0511 11:48:52.039356  4597 net.cpp:338] pool7 does not need backward computation.
-I0511 11:48:52.039361  4597 net.cpp:338] pool6_pool6_0_split does not need backward computation.
-I0511 11:48:52.039366  4597 net.cpp:338] pool6 does not need backward computation.
-I0511 11:48:52.039371  4597 net.cpp:338] conv6/sep_relu6/sep_0_split does not need backward computation.
-I0511 11:48:52.039376  4597 net.cpp:338] relu6/sep does not need backward computation.
-I0511 11:48:52.039381  4597 net.cpp:338] conv6/sep/scale does not need backward computation.
-I0511 11:48:52.039386  4597 net.cpp:338] conv6/sep/bn does not need backward computation.
-I0511 11:48:52.039389  4597 net.cpp:338] conv6/sep does not need backward computation.
-I0511 11:48:52.039394  4597 net.cpp:338] relu6/dw does not need backward computation.
-I0511 11:48:52.039399  4597 net.cpp:338] conv6/dw/scale does not need backward computation.
-I0511 11:48:52.039404  4597 net.cpp:338] conv6/dw/bn does not need backward computation.
-I0511 11:48:52.039408  4597 net.cpp:338] conv6/dw does not need backward computation.
-I0511 11:48:52.039413  4597 net.cpp:338] relu5_6/sep does not need backward computation.
-I0511 11:48:52.039418  4597 net.cpp:338] conv5_6/sep/scale does not need backward computation.
-I0511 11:48:52.039422  4597 net.cpp:338] conv5_6/sep/bn does not need backward computation.
-I0511 11:48:52.039427  4597 net.cpp:338] conv5_6/sep does not need backward computation.
-I0511 11:48:52.039433  4597 net.cpp:338] relu5_6/dw does not need backward computation.
-I0511 11:48:52.039436  4597 net.cpp:338] conv5_6/dw/scale does not need backward computation.
-I0511 11:48:52.039441  4597 net.cpp:338] conv5_6/dw/bn does not need backward computation.
-I0511 11:48:52.039446  4597 net.cpp:338] conv5_6/dw does not need backward computation.
-I0511 11:48:52.039451  4597 net.cpp:338] conv5_5/sep_relu5_5/sep_0_split does not need backward computation.
-I0511 11:48:52.039456  4597 net.cpp:338] relu5_5/sep does not need backward computation.
-I0511 11:48:52.039461  4597 net.cpp:338] conv5_5/sep/scale does not need backward computation.
-I0511 11:48:52.039465  4597 net.cpp:338] conv5_5/sep/bn does not need backward computation.
-I0511 11:48:52.039470  4597 net.cpp:338] conv5_5/sep does not need backward computation.
-I0511 11:48:52.039475  4597 net.cpp:338] relu5_5/dw does not need backward computation.
-I0511 11:48:52.039480  4597 net.cpp:338] conv5_5/dw/scale does not need backward computation.
-I0511 11:48:52.039484  4597 net.cpp:338] conv5_5/dw/bn does not need backward computation.
-I0511 11:48:52.039492  4597 net.cpp:338] conv5_5/dw does not need backward computation.
-I0511 11:48:52.039499  4597 net.cpp:338] relu5_4/sep does not need backward computation.
-I0511 11:48:52.039502  4597 net.cpp:338] conv5_4/sep/scale does not need backward computation.
-I0511 11:48:52.039507  4597 net.cpp:338] conv5_4/sep/bn does not need backward computation.
-I0511 11:48:52.039511  4597 net.cpp:338] conv5_4/sep does not need backward computation.
-I0511 11:48:52.039516  4597 net.cpp:338] relu5_4/dw does not need backward computation.
-I0511 11:48:52.039521  4597 net.cpp:338] conv5_4/dw/scale does not need backward computation.
-I0511 11:48:52.039525  4597 net.cpp:338] conv5_4/dw/bn does not need backward computation.
-I0511 11:48:52.039530  4597 net.cpp:338] conv5_4/dw does not need backward computation.
-I0511 11:48:52.039535  4597 net.cpp:338] relu5_3/sep does not need backward computation.
-I0511 11:48:52.039539  4597 net.cpp:338] conv5_3/sep/scale does not need backward computation.
-I0511 11:48:52.039544  4597 net.cpp:338] conv5_3/sep/bn does not need backward computation.
-I0511 11:48:52.039548  4597 net.cpp:338] conv5_3/sep does not need backward computation.
-I0511 11:48:52.039553  4597 net.cpp:338] relu5_3/dw does not need backward computation.
-I0511 11:48:52.039558  4597 net.cpp:338] conv5_3/dw/scale does not need backward computation.
-I0511 11:48:52.039562  4597 net.cpp:338] conv5_3/dw/bn does not need backward computation.
-I0511 11:48:52.039567  4597 net.cpp:338] conv5_3/dw does not need backward computation.
-I0511 11:48:52.039572  4597 net.cpp:338] relu5_2/sep does not need backward computation.
-I0511 11:48:52.039577  4597 net.cpp:338] conv5_2/sep/scale does not need backward computation.
-I0511 11:48:52.039582  4597 net.cpp:338] conv5_2/sep/bn does not need backward computation.
-I0511 11:48:52.039585  4597 net.cpp:338] conv5_2/sep does not need backward computation.
-I0511 11:48:52.039590  4597 net.cpp:338] relu5_2/dw does not need backward computation.
-I0511 11:48:52.039594  4597 net.cpp:338] conv5_2/dw/scale does not need backward computation.
-I0511 11:48:52.039599  4597 net.cpp:338] conv5_2/dw/bn does not need backward computation.
-I0511 11:48:52.039603  4597 net.cpp:338] conv5_2/dw does not need backward computation.
-I0511 11:48:52.039609  4597 net.cpp:338] relu5_1/sep does not need backward computation.
-I0511 11:48:52.039613  4597 net.cpp:338] conv5_1/sep/scale does not need backward computation.
-I0511 11:48:52.039618  4597 net.cpp:338] conv5_1/sep/bn does not need backward computation.
-I0511 11:48:52.039623  4597 net.cpp:338] conv5_1/sep does not need backward computation.
-I0511 11:48:52.039628  4597 net.cpp:338] relu5_1/dw does not need backward computation.
-I0511 11:48:52.039633  4597 net.cpp:338] conv5_1/dw/scale does not need backward computation.
-I0511 11:48:52.039638  4597 net.cpp:338] conv5_1/dw/bn does not need backward computation.
-I0511 11:48:52.039641  4597 net.cpp:338] conv5_1/dw does not need backward computation.
-I0511 11:48:52.039646  4597 net.cpp:338] relu4_2/sep does not need backward computation.
-I0511 11:48:52.039650  4597 net.cpp:338] conv4_2/sep/scale does not need backward computation.
-I0511 11:48:52.039655  4597 net.cpp:338] conv4_2/sep/bn does not need backward computation.
-I0511 11:48:52.039660  4597 net.cpp:338] conv4_2/sep does not need backward computation.
-I0511 11:48:52.039665  4597 net.cpp:338] relu4_2/dw does not need backward computation.
-I0511 11:48:52.039669  4597 net.cpp:338] conv4_2/dw/scale does not need backward computation.
-I0511 11:48:52.039674  4597 net.cpp:338] conv4_2/dw/bn does not need backward computation.
-I0511 11:48:52.039678  4597 net.cpp:338] conv4_2/dw does not need backward computation.
-I0511 11:48:52.039683  4597 net.cpp:338] relu4_1/sep does not need backward computation.
-I0511 11:48:52.039687  4597 net.cpp:338] conv4_1/sep/scale does not need backward computation.
-I0511 11:48:52.039692  4597 net.cpp:338] conv4_1/sep/bn does not need backward computation.
-I0511 11:48:52.039697  4597 net.cpp:338] conv4_1/sep does not need backward computation.
-I0511 11:48:52.039705  4597 net.cpp:338] relu4_1/dw does not need backward computation.
-I0511 11:48:52.039710  4597 net.cpp:338] conv4_1/dw/scale does not need backward computation.
-I0511 11:48:52.039716  4597 net.cpp:338] conv4_1/dw/bn does not need backward computation.
-I0511 11:48:52.039719  4597 net.cpp:338] conv4_1/dw does not need backward computation.
-I0511 11:48:52.039724  4597 net.cpp:338] relu3_2/sep does not need backward computation.
-I0511 11:48:52.039728  4597 net.cpp:338] conv3_2/sep/scale does not need backward computation.
-I0511 11:48:52.039733  4597 net.cpp:338] conv3_2/sep/bn does not need backward computation.
-I0511 11:48:52.039738  4597 net.cpp:338] conv3_2/sep does not need backward computation.
-I0511 11:48:52.039743  4597 net.cpp:338] relu3_2/dw does not need backward computation.
-I0511 11:48:52.039747  4597 net.cpp:338] conv3_2/dw/scale does not need backward computation.
-I0511 11:48:52.039752  4597 net.cpp:338] conv3_2/dw/bn does not need backward computation.
-I0511 11:48:52.039757  4597 net.cpp:338] conv3_2/dw does not need backward computation.
-I0511 11:48:52.039762  4597 net.cpp:338] relu3_1/sep does not need backward computation.
-I0511 11:48:52.039765  4597 net.cpp:338] conv3_1/sep/scale does not need backward computation.
-I0511 11:48:52.039769  4597 net.cpp:338] conv3_1/sep/bn does not need backward computation.
-I0511 11:48:52.039774  4597 net.cpp:338] conv3_1/sep does not need backward computation.
-I0511 11:48:52.039778  4597 net.cpp:338] relu3_1/dw does not need backward computation.
-I0511 11:48:52.039783  4597 net.cpp:338] conv3_1/dw/scale does not need backward computation.
-I0511 11:48:52.039788  4597 net.cpp:338] conv3_1/dw/bn does not need backward computation.
-I0511 11:48:52.039793  4597 net.cpp:338] conv3_1/dw does not need backward computation.
-I0511 11:48:52.039796  4597 net.cpp:338] relu2_2/sep does not need backward computation.
-I0511 11:48:52.039801  4597 net.cpp:338] conv2_2/sep/scale does not need backward computation.
-I0511 11:48:52.039806  4597 net.cpp:338] conv2_2/sep/bn does not need backward computation.
-I0511 11:48:52.039810  4597 net.cpp:338] conv2_2/sep does not need backward computation.
-I0511 11:48:52.039815  4597 net.cpp:338] relu2_2/dw does not need backward computation.
-I0511 11:48:52.039819  4597 net.cpp:338] conv2_2/dw/scale does not need backward computation.
-I0511 11:48:52.039824  4597 net.cpp:338] conv2_2/dw/bn does not need backward computation.
-I0511 11:48:52.039829  4597 net.cpp:338] conv2_2/dw does not need backward computation.
-I0511 11:48:52.039834  4597 net.cpp:338] relu2_1/sep does not need backward computation.
-I0511 11:48:52.039839  4597 net.cpp:338] conv2_1/sep/scale does not need backward computation.
-I0511 11:48:52.039842  4597 net.cpp:338] conv2_1/sep/bn does not need backward computation.
-I0511 11:48:52.039847  4597 net.cpp:338] conv2_1/sep does not need backward computation.
-I0511 11:48:52.039851  4597 net.cpp:338] relu2_1/dw does not need backward computation.
-I0511 11:48:52.039855  4597 net.cpp:338] conv2_1/dw/scale does not need backward computation.
-I0511 11:48:52.039860  4597 net.cpp:338] conv2_1/dw/bn does not need backward computation.
-I0511 11:48:52.039863  4597 net.cpp:338] conv2_1/dw does not need backward computation.
-I0511 11:48:52.039867  4597 net.cpp:338] relu1 does not need backward computation.
-I0511 11:48:52.039871  4597 net.cpp:338] conv1/scale does not need backward computation.
-I0511 11:48:52.039875  4597 net.cpp:338] conv1/bn does not need backward computation.
-I0511 11:48:52.039880  4597 net.cpp:338] conv1 does not need backward computation.
-I0511 11:48:52.039883  4597 net.cpp:338] data/bias does not need backward computation.
-I0511 11:48:52.039888  4597 net.cpp:338] data_data_0_split does not need backward computation.
-I0511 11:48:52.039893  4597 net.cpp:338] data does not need backward computation.
-I0511 11:48:52.039897  4597 net.cpp:380] This network produces output detection_eval
-I0511 11:48:52.040083  4597 net.cpp:403] Top memory (TEST) required for data: 1352267864 diff: 1352267864
-I0511 11:48:52.040091  4597 net.cpp:406] Bottom memory (TEST) required for data: 1352267440 diff: 1352267440
-I0511 11:48:52.040100  4597 net.cpp:409] Shared (in-place) memory (TEST) by data: 848936960 diff: 848936960
-I0511 11:48:52.040104  4597 net.cpp:412] Parameters memory (TEST) required for data: 9462808 diff: 9462808
-I0511 11:48:52.040108  4597 net.cpp:415] Parameters shared memory (TEST) by data: 0 diff: 0
-I0511 11:48:52.040112  4597 net.cpp:421] Network initialization done.
-I0511 11:48:52.047904  4597 net.cpp:1144] Copying source layer data Type:AnnotatedData #blobs=0
-I0511 11:48:52.047925  4597 net.cpp:1144] Copying source layer data_data_0_split Type:Split #blobs=0
-I0511 11:48:52.047929  4597 net.cpp:1144] Copying source layer data/bias Type:Bias #blobs=1
-I0511 11:48:52.047973  4597 net.cpp:1144] Copying source layer conv1 Type:Convolution #blobs=1
-I0511 11:48:52.047991  4597 net.cpp:1144] Copying source layer conv1/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048012  4597 net.cpp:1144] Copying source layer conv1/scale Type:Scale #blobs=2
-I0511 11:48:52.048028  4597 net.cpp:1144] Copying source layer relu1 Type:ReLU #blobs=0
-I0511 11:48:52.048033  4597 net.cpp:1144] Copying source layer conv2_1/dw Type:Convolution #blobs=1
-I0511 11:48:52.048043  4597 net.cpp:1144] Copying source layer conv2_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048063  4597 net.cpp:1144] Copying source layer conv2_1/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048079  4597 net.cpp:1144] Copying source layer relu2_1/dw Type:ReLU #blobs=0
-I0511 11:48:52.048084  4597 net.cpp:1144] Copying source layer conv2_1/sep Type:Convolution #blobs=1
-I0511 11:48:52.048094  4597 net.cpp:1144] Copying source layer conv2_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048113  4597 net.cpp:1144] Copying source layer conv2_1/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048128  4597 net.cpp:1144] Copying source layer relu2_1/sep Type:ReLU #blobs=0
-I0511 11:48:52.048132  4597 net.cpp:1144] Copying source layer conv2_2/dw Type:Convolution #blobs=1
-I0511 11:48:52.048141  4597 net.cpp:1144] Copying source layer conv2_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048158  4597 net.cpp:1144] Copying source layer conv2_2/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048174  4597 net.cpp:1144] Copying source layer relu2_2/dw Type:ReLU #blobs=0
-I0511 11:48:52.048179  4597 net.cpp:1144] Copying source layer conv2_2/sep Type:Convolution #blobs=1
-I0511 11:48:52.048192  4597 net.cpp:1144] Copying source layer conv2_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048211  4597 net.cpp:1144] Copying source layer conv2_2/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048229  4597 net.cpp:1144] Copying source layer relu2_2/sep Type:ReLU #blobs=0
-I0511 11:48:52.048234  4597 net.cpp:1144] Copying source layer conv3_1/dw Type:Convolution #blobs=1
-I0511 11:48:52.048244  4597 net.cpp:1144] Copying source layer conv3_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048264  4597 net.cpp:1144] Copying source layer conv3_1/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048280  4597 net.cpp:1144] Copying source layer relu3_1/dw Type:ReLU #blobs=0
-I0511 11:48:52.048285  4597 net.cpp:1144] Copying source layer conv3_1/sep Type:Convolution #blobs=1
-I0511 11:48:52.048300  4597 net.cpp:1144] Copying source layer conv3_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048338  4597 net.cpp:1144] Copying source layer conv3_1/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048365  4597 net.cpp:1144] Copying source layer relu3_1/sep Type:ReLU #blobs=0
-I0511 11:48:52.048377  4597 net.cpp:1144] Copying source layer conv3_2/dw Type:Convolution #blobs=1
-I0511 11:48:52.048394  4597 net.cpp:1144] Copying source layer conv3_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048420  4597 net.cpp:1144] Copying source layer conv3_2/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048441  4597 net.cpp:1144] Copying source layer relu3_2/dw Type:ReLU #blobs=0
-I0511 11:48:52.048452  4597 net.cpp:1144] Copying source layer conv3_2/sep Type:Convolution #blobs=1
-I0511 11:48:52.048477  4597 net.cpp:1144] Copying source layer conv3_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048512  4597 net.cpp:1144] Copying source layer conv3_2/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048576  4597 net.cpp:1144] Copying source layer relu3_2/sep Type:ReLU #blobs=0
-I0511 11:48:52.048589  4597 net.cpp:1144] Copying source layer conv4_1/dw Type:Convolution #blobs=1
-I0511 11:48:52.048606  4597 net.cpp:1144] Copying source layer conv4_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048631  4597 net.cpp:1144] Copying source layer conv4_1/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048655  4597 net.cpp:1144] Copying source layer relu4_1/dw Type:ReLU #blobs=0
-I0511 11:48:52.048666  4597 net.cpp:1144] Copying source layer conv4_1/sep Type:Convolution #blobs=1
-I0511 11:48:52.048691  4597 net.cpp:1144] Copying source layer conv4_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048717  4597 net.cpp:1144] Copying source layer conv4_1/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048740  4597 net.cpp:1144] Copying source layer relu4_1/sep Type:ReLU #blobs=0
-I0511 11:48:52.048750  4597 net.cpp:1144] Copying source layer conv4_2/dw Type:Convolution #blobs=1
-I0511 11:48:52.048768  4597 net.cpp:1144] Copying source layer conv4_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048794  4597 net.cpp:1144] Copying source layer conv4_2/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048815  4597 net.cpp:1144] Copying source layer relu4_2/dw Type:ReLU #blobs=0
-I0511 11:48:52.048827  4597 net.cpp:1144] Copying source layer conv4_2/sep Type:Convolution #blobs=1
-I0511 11:48:52.048866  4597 net.cpp:1144] Copying source layer conv4_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048892  4597 net.cpp:1144] Copying source layer conv4_2/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048921  4597 net.cpp:1144] Copying source layer relu4_2/sep Type:ReLU #blobs=0
-I0511 11:48:52.048933  4597 net.cpp:1144] Copying source layer conv5_1/dw Type:Convolution #blobs=1
-I0511 11:48:52.048951  4597 net.cpp:1144] Copying source layer conv5_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048977  4597 net.cpp:1144] Copying source layer conv5_1/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049000  4597 net.cpp:1144] Copying source layer relu5_1/dw Type:ReLU #blobs=0
-I0511 11:48:52.049012  4597 net.cpp:1144] Copying source layer conv5_1/sep Type:Convolution #blobs=1
-I0511 11:48:52.049068  4597 net.cpp:1144] Copying source layer conv5_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049089  4597 net.cpp:1144] Copying source layer conv5_1/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049105  4597 net.cpp:1144] Copying source layer relu5_1/sep Type:ReLU #blobs=0
-I0511 11:48:52.049111  4597 net.cpp:1144] Copying source layer conv5_2/dw Type:Convolution #blobs=1
-I0511 11:48:52.049123  4597 net.cpp:1144] Copying source layer conv5_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049142  4597 net.cpp:1144] Copying source layer conv5_2/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049157  4597 net.cpp:1144] Copying source layer relu5_2/dw Type:ReLU #blobs=0
-I0511 11:48:52.049162  4597 net.cpp:1144] Copying source layer conv5_2/sep Type:Convolution #blobs=1
-I0511 11:48:52.049208  4597 net.cpp:1144] Copying source layer conv5_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049229  4597 net.cpp:1144] Copying source layer conv5_2/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049244  4597 net.cpp:1144] Copying source layer relu5_2/sep Type:ReLU #blobs=0
-I0511 11:48:52.049250  4597 net.cpp:1144] Copying source layer conv5_3/dw Type:Convolution #blobs=1
-I0511 11:48:52.049262  4597 net.cpp:1144] Copying source layer conv5_3/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049280  4597 net.cpp:1144] Copying source layer conv5_3/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049298  4597 net.cpp:1144] Copying source layer relu5_3/dw Type:ReLU #blobs=0
-I0511 11:48:52.049302  4597 net.cpp:1144] Copying source layer conv5_3/sep Type:Convolution #blobs=1
-I0511 11:48:52.049358  4597 net.cpp:1144] Copying source layer conv5_3/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049381  4597 net.cpp:1144] Copying source layer conv5_3/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049397  4597 net.cpp:1144] Copying source layer relu5_3/sep Type:ReLU #blobs=0
-I0511 11:48:52.049412  4597 net.cpp:1144] Copying source layer conv5_4/dw Type:Convolution #blobs=1
-I0511 11:48:52.049424  4597 net.cpp:1144] Copying source layer conv5_4/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049444  4597 net.cpp:1144] Copying source layer conv5_4/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049460  4597 net.cpp:1144] Copying source layer relu5_4/dw Type:ReLU #blobs=0
-I0511 11:48:52.049466  4597 net.cpp:1144] Copying source layer conv5_4/sep Type:Convolution #blobs=1
-I0511 11:48:52.049511  4597 net.cpp:1144] Copying source layer conv5_4/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049535  4597 net.cpp:1144] Copying source layer conv5_4/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049551  4597 net.cpp:1144] Copying source layer relu5_4/sep Type:ReLU #blobs=0
-I0511 11:48:52.049556  4597 net.cpp:1144] Copying source layer conv5_5/dw Type:Convolution #blobs=1
-I0511 11:48:52.049567  4597 net.cpp:1144] Copying source layer conv5_5/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049588  4597 net.cpp:1144] Copying source layer conv5_5/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049605  4597 net.cpp:1144] Copying source layer relu5_5/dw Type:ReLU #blobs=0
-I0511 11:48:52.049612  4597 net.cpp:1144] Copying source layer conv5_5/sep Type:Convolution #blobs=1
-I0511 11:48:52.049654  4597 net.cpp:1144] Copying source layer conv5_5/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049676  4597 net.cpp:1144] Copying source layer conv5_5/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049693  4597 net.cpp:1144] Copying source layer relu5_5/sep Type:ReLU #blobs=0
-I0511 11:48:52.049700  4597 net.cpp:1144] Copying source layer conv5_5/sep_relu5_5/sep_0_split Type:Split #blobs=0
-I0511 11:48:52.049705  4597 net.cpp:1144] Copying source layer conv5_6/dw Type:Convolution #blobs=1
-I0511 11:48:52.049717  4597 net.cpp:1144] Copying source layer conv5_6/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049738  4597 net.cpp:1144] Copying source layer conv5_6/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049756  4597 net.cpp:1144] Copying source layer relu5_6/dw Type:ReLU #blobs=0
-I0511 11:48:52.049762  4597 net.cpp:1144] Copying source layer conv5_6/sep Type:Convolution #blobs=1
-I0511 11:48:52.049834  4597 net.cpp:1144] Copying source layer conv5_6/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049860  4597 net.cpp:1144] Copying source layer conv5_6/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049876  4597 net.cpp:1144] Copying source layer relu5_6/sep Type:ReLU #blobs=0
-I0511 11:48:52.049882  4597 net.cpp:1144] Copying source layer conv6/dw Type:Convolution #blobs=1
-I0511 11:48:52.049896  4597 net.cpp:1144] Copying source layer conv6/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049916  4597 net.cpp:1144] Copying source layer conv6/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049933  4597 net.cpp:1144] Copying source layer relu6/dw Type:ReLU #blobs=0
-I0511 11:48:52.049939  4597 net.cpp:1144] Copying source layer conv6/sep Type:Convolution #blobs=1
-I0511 11:48:52.050068  4597 net.cpp:1144] Copying source layer conv6/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.050092  4597 net.cpp:1144] Copying source layer conv6/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.050107  4597 net.cpp:1144] Copying source layer relu6/sep Type:ReLU #blobs=0
-I0511 11:48:52.050113  4597 net.cpp:1144] Copying source layer conv6/sep_relu6/sep_0_split Type:Split #blobs=0
-I0511 11:48:52.050117  4597 net.cpp:1144] Copying source layer pool6 Type:Pooling #blobs=0
-I0511 11:48:52.050122  4597 net.cpp:1144] Copying source layer pool6_pool6_0_split Type:Split #blobs=0
-I0511 11:48:52.050127  4597 net.cpp:1144] Copying source layer pool7 Type:Pooling #blobs=0
-I0511 11:48:52.050130  4597 net.cpp:1144] Copying source layer pool7_pool7_0_split Type:Split #blobs=0
-I0511 11:48:52.050135  4597 net.cpp:1144] Copying source layer pool8 Type:Pooling #blobs=0
-I0511 11:48:52.050139  4597 net.cpp:1144] Copying source layer ctx_output1/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.050209  4597 net.cpp:1144] Copying source layer ctx_output1/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050246  4597 net.cpp:1144] Copying source layer ctx_output1/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050253  4597 net.cpp:1144] Copying source layer ctx_output1 Type:Convolution #blobs=2
-I0511 11:48:52.050271  4597 net.cpp:1144] Copying source layer ctx_output1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050297  4597 net.cpp:1144] Copying source layer ctx_output1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050302  4597 net.cpp:1144] Copying source layer ctx_output1_ctx_output1/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.050307  4597 net.cpp:1144] Copying source layer ctx_output2/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.050436  4597 net.cpp:1144] Copying source layer ctx_output2/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050464  4597 net.cpp:1144] Copying source layer ctx_output2/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050470  4597 net.cpp:1144] Copying source layer ctx_output2 Type:Convolution #blobs=2
-I0511 11:48:52.050487  4597 net.cpp:1144] Copying source layer ctx_output2/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050514  4597 net.cpp:1144] Copying source layer ctx_output2/relu Type:ReLU #blobs=0
-I0511 11:48:52.050520  4597 net.cpp:1144] Copying source layer ctx_output2_ctx_output2/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.050525  4597 net.cpp:1144] Copying source layer ctx_output3/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.050652  4597 net.cpp:1144] Copying source layer ctx_output3/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050681  4597 net.cpp:1144] Copying source layer ctx_output3/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050688  4597 net.cpp:1144] Copying source layer ctx_output3 Type:Convolution #blobs=2
-I0511 11:48:52.050704  4597 net.cpp:1144] Copying source layer ctx_output3/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050730  4597 net.cpp:1144] Copying source layer ctx_output3/relu Type:ReLU #blobs=0
-I0511 11:48:52.050736  4597 net.cpp:1144] Copying source layer ctx_output3_ctx_output3/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.050740  4597 net.cpp:1144] Copying source layer ctx_output4/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.050871  4597 net.cpp:1144] Copying source layer ctx_output4/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050900  4597 net.cpp:1144] Copying source layer ctx_output4/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050906  4597 net.cpp:1144] Copying source layer ctx_output4 Type:Convolution #blobs=2
-I0511 11:48:52.050922  4597 net.cpp:1144] Copying source layer ctx_output4/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050951  4597 net.cpp:1144] Copying source layer ctx_output4/relu Type:ReLU #blobs=0
-I0511 11:48:52.050956  4597 net.cpp:1144] Copying source layer ctx_output4_ctx_output4/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.050961  4597 net.cpp:1144] Copying source layer ctx_output5/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.051087  4597 net.cpp:1144] Copying source layer ctx_output5/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.051113  4597 net.cpp:1144] Copying source layer ctx_output5/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.051120  4597 net.cpp:1144] Copying source layer ctx_output5 Type:Convolution #blobs=2
-I0511 11:48:52.051138  4597 net.cpp:1144] Copying source layer ctx_output5/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.051167  4597 net.cpp:1144] Copying source layer ctx_output5/relu Type:ReLU #blobs=0
-I0511 11:48:52.051172  4597 net.cpp:1144] Copying source layer ctx_output5_ctx_output5/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.051177  4597 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:48:52.051195  4597 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:48:52.051201  4597 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:48:52.051206  4597 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:48:52.051239  4597 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:48:52.051245  4597 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:48:52.051255  4597 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:48:52.051260  4597 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_loc Type:Convolution #blobs=2
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-I0511 11:48:52.051607  4597 net.cpp:1136] Ignoring source layer mbox_loss
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-I0511 11:49:27.126497  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126513  4597 caffe.cpp:501] detection_eval = 1
-I0511 11:49:27.126528  4597 caffe.cpp:501] detection_eval = 0.574597
-I0511 11:49:27.126543  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126557  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126571  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126586  4597 caffe.cpp:501] detection_eval = 2
-I0511 11:49:27.126600  4597 caffe.cpp:501] detection_eval = 0.679435
-I0511 11:49:27.126616  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126629  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126643  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126657  4597 caffe.cpp:501] detection_eval = 3
-I0511 11:49:27.126672  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.126687  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126700  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126721  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126736  4597 caffe.cpp:501] detection_eval = 4
-I0511 11:49:27.126750  4597 caffe.cpp:501] detection_eval = 0.530242
-I0511 11:49:27.126765  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126780  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126793  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126807  4597 caffe.cpp:501] detection_eval = 5
-I0511 11:49:27.126821  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.126835  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126849  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126863  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126878  4597 caffe.cpp:501] detection_eval = 6
-I0511 11:49:27.126893  4597 caffe.cpp:501] detection_eval = 0.429435
-I0511 11:49:27.126906  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126920  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126935  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126948  4597 caffe.cpp:501] detection_eval = 7
-I0511 11:49:27.126962  4597 caffe.cpp:501] detection_eval = 2.43548
-I0511 11:49:27.126976  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126991  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127004  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127018  4597 caffe.cpp:501] detection_eval = 8
-I0511 11:49:27.127033  4597 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:49:27.127048  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127065  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127079  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127094  4597 caffe.cpp:501] detection_eval = 9
-I0511 11:49:27.127108  4597 caffe.cpp:501] detection_eval = 1.53226
-I0511 11:49:27.127122  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127136  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127151  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127164  4597 caffe.cpp:501] detection_eval = 10
-I0511 11:49:27.127179  4597 caffe.cpp:501] detection_eval = 0.491935
-I0511 11:49:27.127193  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127208  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127223  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127236  4597 caffe.cpp:501] detection_eval = 11
-I0511 11:49:27.127250  4597 caffe.cpp:501] detection_eval = 0.417339
-I0511 11:49:27.127264  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127287  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127301  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127315  4597 caffe.cpp:501] detection_eval = 12
-I0511 11:49:27.127331  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.127344  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127358  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127372  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127387  4597 caffe.cpp:501] detection_eval = 13
-I0511 11:49:27.127400  4597 caffe.cpp:501] detection_eval = 0.703629
-I0511 11:49:27.127414  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127429  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127442  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127457  4597 caffe.cpp:501] detection_eval = 14
-I0511 11:49:27.127471  4597 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:49:27.127485  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127499  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127513  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127526  4597 caffe.cpp:501] detection_eval = 15
-I0511 11:49:27.127542  4597 caffe.cpp:501] detection_eval = 9.13306
-I0511 11:49:27.127555  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127569  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127583  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127598  4597 caffe.cpp:501] detection_eval = 16
-I0511 11:49:27.127612  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.127626  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127645  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127658  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127672  4597 caffe.cpp:501] detection_eval = 17
-I0511 11:49:27.127686  4597 caffe.cpp:501] detection_eval = 0.487903
-I0511 11:49:27.127701  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127714  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127728  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127743  4597 caffe.cpp:501] detection_eval = 18
-I0511 11:49:27.127758  4597 caffe.cpp:501] detection_eval = 0.483871
-I0511 11:49:27.127771  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127785  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127799  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127813  4597 caffe.cpp:501] detection_eval = 19
-I0511 11:49:27.127827  4597 caffe.cpp:501] detection_eval = 0.570565
-I0511 11:49:27.127841  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127856  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127869  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127883  4597 caffe.cpp:501] detection_eval = 20
-I0511 11:49:27.127897  4597 caffe.cpp:501] detection_eval = 0.620968
-I0511 11:49:27.127912  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127925  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127939  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.127954  4597 caffe.cpp:501] detection_eval = 3.19556
-I0511 11:49:27.127967  4597 caffe.cpp:501] detection_eval = 0.155836
-I0511 11:49:27.127985  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.128000  4597 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:49:27.128013  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128027  4597 caffe.cpp:501] detection_eval = 3.58871
-I0511 11:49:27.128041  4597 caffe.cpp:501] detection_eval = 0.100137
-I0511 11:49:27.128056  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.128069  4597 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:49:27.128083  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128098  4597 caffe.cpp:501] detection_eval = 3.79637
-I0511 11:49:27.128111  4597 caffe.cpp:501] detection_eval = 0.0758775
-I0511 11:49:27.128126  4597 caffe.cpp:501] detection_eval = 0.0403226
-I0511 11:49:27.128140  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.128154  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128168  4597 caffe.cpp:501] detection_eval = 3.92339
-I0511 11:49:27.128187  4597 caffe.cpp:501] detection_eval = 0.0664227
-I0511 11:49:27.128201  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.128216  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.128231  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128244  4597 caffe.cpp:501] detection_eval = 4.0746
-I0511 11:49:27.128258  4597 caffe.cpp:501] detection_eval = 0.0578036
-I0511 11:49:27.128273  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.128286  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.128300  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128314  4597 caffe.cpp:501] detection_eval = 4.1875
-I0511 11:49:27.128329  4597 caffe.cpp:501] detection_eval = 0.0488079
-I0511 11:49:27.128343  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.128357  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.128371  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128386  4597 caffe.cpp:501] detection_eval = 4.26411
-I0511 11:49:27.128401  4597 caffe.cpp:501] detection_eval = 0.0514011
-I0511 11:49:27.128414  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.128428  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.128443  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128458  4597 caffe.cpp:501] detection_eval = 4.375
-I0511 11:49:27.128470  4597 caffe.cpp:501] detection_eval = 0.0565917
-I0511 11:49:27.128484  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.128499  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.128516  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128537  4597 caffe.cpp:501] detection_eval = 4.4375
-I0511 11:49:27.128553  4597 caffe.cpp:501] detection_eval = 0.0425472
-I0511 11:49:27.128567  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.128582  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.128595  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128609  4597 caffe.cpp:501] detection_eval = 4.49798
-I0511 11:49:27.128623  4597 caffe.cpp:501] detection_eval = 0.0395933
-I0511 11:49:27.128638  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.128653  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.128666  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128680  4597 caffe.cpp:501] detection_eval = 4.54637
-I0511 11:49:27.128695  4597 caffe.cpp:501] detection_eval = 0.0453336
-I0511 11:49:27.128708  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.128722  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.128736  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128751  4597 caffe.cpp:501] detection_eval = 4.65323
-I0511 11:49:27.128765  4597 caffe.cpp:501] detection_eval = 0.0416205
-I0511 11:49:27.128778  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.128793  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.128806  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128820  4597 caffe.cpp:501] detection_eval = 4.77016
-I0511 11:49:27.128837  4597 caffe.cpp:501] detection_eval = 0.0486904
-I0511 11:49:27.128852  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.128866  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.128880  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.128895  4597 caffe.cpp:501] detection_eval = 4.80444
-I0511 11:49:27.128908  4597 caffe.cpp:501] detection_eval = 0.0418979
-I0511 11:49:27.128922  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.128937  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.128950  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.128964  4597 caffe.cpp:501] detection_eval = 4.85685
-I0511 11:49:27.128978  4597 caffe.cpp:501] detection_eval = 0.042125
-I0511 11:49:27.128993  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.129006  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.129021  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129035  4597 caffe.cpp:501] detection_eval = 4.87702
-I0511 11:49:27.129055  4597 caffe.cpp:501] detection_eval = 0.0416501
-I0511 11:49:27.129070  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.129083  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.129097  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129112  4597 caffe.cpp:501] detection_eval = 4.95968
-I0511 11:49:27.129124  4597 caffe.cpp:501] detection_eval = 0.037758
-I0511 11:49:27.129137  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129148  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.129159  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129171  4597 caffe.cpp:501] detection_eval = 5.02218
-I0511 11:49:27.129184  4597 caffe.cpp:501] detection_eval = 0.0439259
-I0511 11:49:27.129195  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.129207  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.129218  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129230  4597 caffe.cpp:501] detection_eval = 5.09073
-I0511 11:49:27.129242  4597 caffe.cpp:501] detection_eval = 0.0430185
-I0511 11:49:27.129254  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.129266  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.129277  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129289  4597 caffe.cpp:501] detection_eval = 5.18548
-I0511 11:49:27.129302  4597 caffe.cpp:501] detection_eval = 0.0427662
-I0511 11:49:27.129312  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.129326  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.129338  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129350  4597 caffe.cpp:501] detection_eval = 5.26008
-I0511 11:49:27.129362  4597 caffe.cpp:501] detection_eval = 0.0448038
-I0511 11:49:27.129374  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129387  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.129400  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129413  4597 caffe.cpp:501] detection_eval = 5.33669
-I0511 11:49:27.129426  4597 caffe.cpp:501] detection_eval = 0.0424197
-I0511 11:49:27.129439  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.129452  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.129465  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.129478  4597 caffe.cpp:501] detection_eval = 5.39718
-I0511 11:49:27.129490  4597 caffe.cpp:501] detection_eval = 0.0494331
-I0511 11:49:27.129503  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.129516  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.129528  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.129541  4597 caffe.cpp:501] detection_eval = 5.44153
-I0511 11:49:27.129554  4597 caffe.cpp:501] detection_eval = 0.0412754
-I0511 11:49:27.129567  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129580  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.129592  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.129609  4597 caffe.cpp:501] detection_eval = 5.50202
-I0511 11:49:27.129622  4597 caffe.cpp:501] detection_eval = 0.0410487
-I0511 11:49:27.129636  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129648  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.129662  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.129673  4597 caffe.cpp:501] detection_eval = 5.56452
-I0511 11:49:27.129686  4597 caffe.cpp:501] detection_eval = 0.0476251
-I0511 11:49:27.129699  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.129714  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.129726  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.129739  4597 caffe.cpp:501] detection_eval = 5.61694
-I0511 11:49:27.129752  4597 caffe.cpp:501] detection_eval = 0.0399715
-I0511 11:49:27.129765  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129778  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.129791  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.129809  4597 caffe.cpp:501] detection_eval = 5.65726
-I0511 11:49:27.129823  4597 caffe.cpp:501] detection_eval = 0.0359377
-I0511 11:49:27.129837  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129850  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.129864  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.129878  4597 caffe.cpp:501] detection_eval = 5.71976
-I0511 11:49:27.129892  4597 caffe.cpp:501] detection_eval = 0.0411324
-I0511 11:49:27.129906  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129921  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.129935  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.129951  4597 caffe.cpp:501] detection_eval = 5.80242
-I0511 11:49:27.129963  4597 caffe.cpp:501] detection_eval = 0.0412029
-I0511 11:49:27.129977  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.129992  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.130005  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130019  4597 caffe.cpp:501] detection_eval = 5.89315
-I0511 11:49:27.130033  4597 caffe.cpp:501] detection_eval = 0.0388007
-I0511 11:49:27.130048  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.130062  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.130076  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130090  4597 caffe.cpp:501] detection_eval = 5.94556
-I0511 11:49:27.130103  4597 caffe.cpp:501] detection_eval = 0.0353795
-I0511 11:49:27.130120  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.130136  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.130149  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130163  4597 caffe.cpp:501] detection_eval = 6.04637
-I0511 11:49:27.130177  4597 caffe.cpp:501] detection_eval = 0.0426654
-I0511 11:49:27.130192  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.130205  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.130219  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130231  4597 caffe.cpp:501] detection_eval = 6.15121
-I0511 11:49:27.130242  4597 caffe.cpp:501] detection_eval = 0.038799
-I0511 11:49:27.130254  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.130264  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.130276  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.130290  4597 caffe.cpp:501] detection_eval = 6.18347
-I0511 11:49:27.130303  4597 caffe.cpp:501] detection_eval = 0.0411229
-I0511 11:49:27.130316  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.130331  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.130343  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.130357  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.130372  4597 caffe.cpp:501] detection_eval = 0.0462864
-I0511 11:49:27.130385  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.130399  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.130414  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.130425  4597 caffe.cpp:501] detection_eval = 6.36089
-I0511 11:49:27.130436  4597 caffe.cpp:501] detection_eval = 0.0456047
-I0511 11:49:27.130447  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.130460  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.130475  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130486  4597 caffe.cpp:501] detection_eval = 6.39718
-I0511 11:49:27.130501  4597 caffe.cpp:501] detection_eval = 0.0444649
-I0511 11:49:27.130514  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130527  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.130542  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130555  4597 caffe.cpp:501] detection_eval = 6.45968
-I0511 11:49:27.130569  4597 caffe.cpp:501] detection_eval = 0.03753
-I0511 11:49:27.130584  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.130597  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.130616  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130631  4597 caffe.cpp:501] detection_eval = 6.52823
-I0511 11:49:27.130645  4597 caffe.cpp:501] detection_eval = 0.0426885
-I0511 11:49:27.130659  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.130673  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.130687  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130702  4597 caffe.cpp:501] detection_eval = 6.62903
-I0511 11:49:27.130715  4597 caffe.cpp:501] detection_eval = 0.0381812
-I0511 11:49:27.130729  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.130744  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.130758  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130771  4597 caffe.cpp:501] detection_eval = 6.72984
-I0511 11:49:27.130785  4597 caffe.cpp:501] detection_eval = 0.0387956
-I0511 11:49:27.130800  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.130813  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.130827  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130841  4597 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:49:27.130856  4597 caffe.cpp:501] detection_eval = 0.040319
-I0511 11:49:27.130869  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.130883  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.130897  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130911  4597 caffe.cpp:501] detection_eval = 6.85484
-I0511 11:49:27.130928  4597 caffe.cpp:501] detection_eval = 0.0379203
-I0511 11:49:27.130941  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.130956  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.130971  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130985  4597 caffe.cpp:501] detection_eval = 6.93145
-I0511 11:49:27.131000  4597 caffe.cpp:501] detection_eval = 0.0380551
-I0511 11:49:27.131014  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.131028  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.131042  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.131057  4597 caffe.cpp:501] detection_eval = 7.07056
-I0511 11:49:27.131072  4597 caffe.cpp:501] detection_eval = 0.0413856
-I0511 11:49:27.131085  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.131099  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131114  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.131127  4597 caffe.cpp:501] detection_eval = 7.19556
-I0511 11:49:27.131141  4597 caffe.cpp:501] detection_eval = 0.0445879
-I0511 11:49:27.131155  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.131170  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.131183  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131198  4597 caffe.cpp:501] detection_eval = 7.21169
-I0511 11:49:27.131212  4597 caffe.cpp:501] detection_eval = 0.0456281
-I0511 11:49:27.131227  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.131244  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131258  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131273  4597 caffe.cpp:501] detection_eval = 7.26411
-I0511 11:49:27.131287  4597 caffe.cpp:501] detection_eval = 0.0398665
-I0511 11:49:27.131301  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.131316  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.131330  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131345  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.131358  4597 caffe.cpp:501] detection_eval = 0.0426693
-I0511 11:49:27.131372  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.131387  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.131402  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131415  4597 caffe.cpp:501] detection_eval = 7.49194
-I0511 11:49:27.131429  4597 caffe.cpp:501] detection_eval = 0.0411533
-I0511 11:49:27.131443  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.131464  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.131479  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131491  4597 caffe.cpp:501] detection_eval = 7.58669
-I0511 11:49:27.131505  4597 caffe.cpp:501] detection_eval = 0.0420787
-I0511 11:49:27.131520  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.131533  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.131547  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131561  4597 caffe.cpp:501] detection_eval = 7.73185
-I0511 11:49:27.131575  4597 caffe.cpp:501] detection_eval = 0.0470093
-I0511 11:49:27.131589  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.131603  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131618  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131631  4597 caffe.cpp:501] detection_eval = 7.78427
-I0511 11:49:27.131645  4597 caffe.cpp:501] detection_eval = 0.0409579
-I0511 11:49:27.131659  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.131673  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.131687  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131701  4597 caffe.cpp:501] detection_eval = 7.89516
-I0511 11:49:27.131716  4597 caffe.cpp:501] detection_eval = 0.0434188
-I0511 11:49:27.131729  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.131743  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.131757  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131774  4597 caffe.cpp:501] detection_eval = 7.92944
-I0511 11:49:27.131788  4597 caffe.cpp:501] detection_eval = 0.0427699
-I0511 11:49:27.131803  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.131817  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131831  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131845  4597 caffe.cpp:501] detection_eval = 7.97177
-I0511 11:49:27.131860  4597 caffe.cpp:501] detection_eval = 0.0375143
-I0511 11:49:27.131872  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.131887  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.131901  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131916  4597 caffe.cpp:501] detection_eval = 8.08266
-I0511 11:49:27.131929  4597 caffe.cpp:501] detection_eval = 0.0442452
-I0511 11:49:27.131943  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.131958  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131971  4597 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:49:27.131985  4597 caffe.cpp:501] detection_eval = 8.16129
-I0511 11:49:27.131999  4597 caffe.cpp:501] detection_eval = 0.0438716
-I0511 11:49:27.132014  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.132027  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.132041  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132055  4597 caffe.cpp:501] detection_eval = 8.19556
-I0511 11:49:27.132069  4597 caffe.cpp:501] detection_eval = 0.0454496
-I0511 11:49:27.132086  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.132102  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.132115  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132129  4597 caffe.cpp:501] detection_eval = 8.25806
-I0511 11:49:27.132143  4597 caffe.cpp:501] detection_eval = 0.0422392
-I0511 11:49:27.132158  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.132171  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.132185  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132200  4597 caffe.cpp:501] detection_eval = 8.37903
-I0511 11:49:27.132213  4597 caffe.cpp:501] detection_eval = 0.0462827
-I0511 11:49:27.132226  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.132241  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.132254  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132268  4597 caffe.cpp:501] detection_eval = 8.44556
-I0511 11:49:27.132282  4597 caffe.cpp:501] detection_eval = 0.0395954
-I0511 11:49:27.132302  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.132318  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.132331  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132345  4597 caffe.cpp:501] detection_eval = 8.55847
-I0511 11:49:27.132359  4597 caffe.cpp:501] detection_eval = 0.04636
-I0511 11:49:27.132374  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.132387  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.132401  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132416  4597 caffe.cpp:501] detection_eval = 8.63508
-I0511 11:49:27.132429  4597 caffe.cpp:501] detection_eval = 0.0432603
-I0511 11:49:27.132443  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.132457  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.132472  4597 caffe.cpp:501] detection_eval = 0.0342742
-I0511 11:49:27.132485  4597 caffe.cpp:501] detection_eval = 8.68548
-I0511 11:49:27.132499  4597 caffe.cpp:501] detection_eval = 0.0452855
-I0511 11:49:27.132513  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.132535  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.132550  4597 caffe.cpp:501] detection_eval = 0.0342742
-I0511 11:49:27.132562  4597 caffe.cpp:501] detection_eval = 8.75605
-I0511 11:49:27.132575  4597 caffe.cpp:501] detection_eval = 0.0379097
-I0511 11:49:27.132588  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.132602  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.132619  4597 caffe.cpp:501] detection_eval = 0.0362903
-I0511 11:49:27.132634  4597 caffe.cpp:501] detection_eval = 8.79435
-I0511 11:49:27.132647  4597 caffe.cpp:501] detection_eval = 0.0433688
-I0511 11:49:27.132661  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.132675  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.132689  4597 caffe.cpp:501] detection_eval = 0.0362903
-I0511 11:49:27.132704  4597 caffe.cpp:501] detection_eval = 8.89919
-I0511 11:49:27.132719  4597 caffe.cpp:501] detection_eval = 0.0470879
-I0511 11:49:27.132732  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.132746  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.132761  4597 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:49:27.132774  4597 caffe.cpp:501] detection_eval = 8.91935
-I0511 11:49:27.132788  4597 caffe.cpp:501] detection_eval = 0.0427316
-I0511 11:49:27.132802  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.132817  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.132830  4597 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:49:27.132845  4597 caffe.cpp:501] detection_eval = 9.03427
-I0511 11:49:27.132858  4597 caffe.cpp:501] detection_eval = 0.0459964
-I0511 11:49:27.132872  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.132886  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.132900  4597 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:49:27.132915  4597 caffe.cpp:501] detection_eval = 9.08468
-I0511 11:49:27.132930  4597 caffe.cpp:501] detection_eval = 0.0470074
-I0511 11:49:27.132946  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.132959  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.132973  4597 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:49:27.132987  4597 caffe.cpp:501] detection_eval = 9.16734
-I0511 11:49:27.133002  4597 caffe.cpp:501] detection_eval = 0.0436674
-I0511 11:49:27.133015  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.133029  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.133042  4597 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:49:27.133057  4597 caffe.cpp:501] detection_eval = 9.19153
-I0511 11:49:27.133070  4597 caffe.cpp:501] detection_eval = 0.0432862
-I0511 11:49:27.133085  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.133100  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.133113  4597 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:49:27.133127  4597 caffe.cpp:501] detection_eval = 9.25806
-I0511 11:49:27.133149  4597 caffe.cpp:501] detection_eval = 0.041063
-I0511 11:49:27.133163  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.133177  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133191  4597 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:49:27.133205  4597 caffe.cpp:501] detection_eval = 9.35484
-I0511 11:49:27.133219  4597 caffe.cpp:501] detection_eval = 0.0500139
-I0511 11:49:27.133234  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.133247  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.133261  4597 caffe.cpp:501] detection_eval = 0.0443548
-I0511 11:49:27.133275  4597 caffe.cpp:501] detection_eval = 9.36895
-I0511 11:49:27.133289  4597 caffe.cpp:501] detection_eval = 0.0411816
-I0511 11:49:27.133303  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.133317  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133332  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.133345  4597 caffe.cpp:501] detection_eval = 9.39315
-I0511 11:49:27.133359  4597 caffe.cpp:501] detection_eval = 0.0391489
-I0511 11:49:27.133373  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.133388  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.133401  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.133415  4597 caffe.cpp:501] detection_eval = 9.47379
-I0511 11:49:27.133428  4597 caffe.cpp:501] detection_eval = 0.0395449
-I0511 11:49:27.133442  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.133460  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133473  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.133487  4597 caffe.cpp:501] detection_eval = 9.55847
-I0511 11:49:27.133502  4597 caffe.cpp:501] detection_eval = 0.0414796
-I0511 11:49:27.133515  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.133529  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133543  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.133558  4597 caffe.cpp:501] detection_eval = 9.64919
-I0511 11:49:27.133571  4597 caffe.cpp:501] detection_eval = 0.041218
-I0511 11:49:27.133585  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.133599  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.133612  4597 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:49:27.133626  4597 caffe.cpp:501] detection_eval = 9.69153
-I0511 11:49:27.133641  4597 caffe.cpp:501] detection_eval = 0.0393077
-I0511 11:49:27.133654  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.133668  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.133682  4597 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:49:27.133697  4597 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:49:27.133710  4597 caffe.cpp:501] detection_eval = 0.0442791
-I0511 11:49:27.133724  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.133738  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133752  4597 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:49:27.133769  4597 caffe.cpp:501] detection_eval = 9.875
-I0511 11:49:27.133783  4597 caffe.cpp:501] detection_eval = 0.0439502
-I0511 11:49:27.133797  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.133811  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.133826  4597 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:49:27.133839  4597 caffe.cpp:501] detection_eval = 9.90726
-I0511 11:49:27.133853  4597 caffe.cpp:501] detection_eval = 0.0385435
-I0511 11:49:27.133867  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.133882  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.133895  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.133909  4597 caffe.cpp:501] detection_eval = 9.96371
-I0511 11:49:27.133924  4597 caffe.cpp:501] detection_eval = 0.0408335
-I0511 11:49:27.133937  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.133951  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.133965  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.133985  4597 caffe.cpp:501] detection_eval = 10.0383
-I0511 11:49:27.133999  4597 caffe.cpp:501] detection_eval = 0.0407894
-I0511 11:49:27.134013  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.134027  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.134042  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.134055  4597 caffe.cpp:501] detection_eval = 10.1149
-I0511 11:49:27.134069  4597 caffe.cpp:501] detection_eval = 0.0367908
-I0511 11:49:27.134083  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.134099  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.134112  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.134126  4597 caffe.cpp:501] detection_eval = 10.1956
-I0511 11:49:27.134140  4597 caffe.cpp:501] detection_eval = 0.0403792
-I0511 11:49:27.134155  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.134168  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.134182  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.134196  4597 caffe.cpp:501] detection_eval = 10.2419
-I0511 11:49:27.134210  4597 caffe.cpp:501] detection_eval = 0.0411727
-I0511 11:49:27.134225  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.134239  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.134253  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.134268  4597 caffe.cpp:501] detection_eval = 10.2843
-I0511 11:49:27.134281  4597 caffe.cpp:501] detection_eval = 0.0438232
-I0511 11:49:27.134297  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.134312  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.134326  4597 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:49:27.134341  4597 caffe.cpp:501] detection_eval = 10.3105
-I0511 11:49:27.134354  4597 caffe.cpp:501] detection_eval = 0.0407584
-I0511 11:49:27.134368  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.134382  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.134397  4597 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:49:27.134410  4597 caffe.cpp:501] detection_eval = 10.4194
-I0511 11:49:27.134424  4597 caffe.cpp:501] detection_eval = 0.0432809
-I0511 11:49:27.134438  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.134452  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.134466  4597 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:49:27.134480  4597 caffe.cpp:501] detection_eval = 10.5161
-I0511 11:49:27.134495  4597 caffe.cpp:501] detection_eval = 0.0394205
-I0511 11:49:27.134508  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.134522  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.134536  4597 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:49:27.134551  4597 caffe.cpp:501] detection_eval = 10.6169
-I0511 11:49:27.134564  4597 caffe.cpp:501] detection_eval = 0.0418179
-I0511 11:49:27.134578  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.134593  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.134610  4597 caffe.cpp:501] detection_eval = 0.0564516
-I0511 11:49:27.134624  4597 caffe.cpp:501] detection_eval = 10.6673
-I0511 11:49:27.134639  4597 caffe.cpp:501] detection_eval = 0.0497172
-I0511 11:49:27.134654  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.134667  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.134681  4597 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:49:27.134696  4597 caffe.cpp:501] detection_eval = 10.7198
-I0511 11:49:27.134709  4597 caffe.cpp:501] detection_eval = 0.0484078
-I0511 11:49:27.134723  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.134737  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.134752  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.134764  4597 caffe.cpp:501] detection_eval = 10.8065
-I0511 11:49:27.134779  4597 caffe.cpp:501] detection_eval = 0.0451504
-I0511 11:49:27.134793  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.134807  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.134825  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.134840  4597 caffe.cpp:501] detection_eval = 10.9375
-I0511 11:49:27.134855  4597 caffe.cpp:501] detection_eval = 0.0483512
-I0511 11:49:27.134868  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.134882  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.134896  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.134910  4597 caffe.cpp:501] detection_eval = 11.0181
-I0511 11:49:27.134924  4597 caffe.cpp:501] detection_eval = 0.0471296
-I0511 11:49:27.134938  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.134953  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.134966  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.134980  4597 caffe.cpp:501] detection_eval = 11.0706
-I0511 11:49:27.134994  4597 caffe.cpp:501] detection_eval = 0.046401
-I0511 11:49:27.135008  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.135022  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.135036  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.135051  4597 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:49:27.135064  4597 caffe.cpp:501] detection_eval = 0.0402911
-I0511 11:49:27.135078  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.135092  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.135107  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.135120  4597 caffe.cpp:501] detection_eval = 11.2077
-I0511 11:49:27.135138  4597 caffe.cpp:501] detection_eval = 0.0443586
-I0511 11:49:27.135151  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.135166  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.135180  4597 caffe.cpp:501] detection_eval = 0.0625
-I0511 11:49:27.135195  4597 caffe.cpp:501] detection_eval = 11.2742
-I0511 11:49:27.135208  4597 caffe.cpp:501] detection_eval = 0.0453521
-I0511 11:49:27.135222  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.135236  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.135251  4597 caffe.cpp:501] detection_eval = 0.0625
-I0511 11:49:27.135264  4597 caffe.cpp:501] detection_eval = 11.3387
-I0511 11:49:27.135279  4597 caffe.cpp:501] detection_eval = 0.0460164
-I0511 11:49:27.135293  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.135308  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.135320  4597 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:49:27.135335  4597 caffe.cpp:501] detection_eval = 11.3831
-I0511 11:49:27.135349  4597 caffe.cpp:501] detection_eval = 0.0495264
-I0511 11:49:27.135363  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.135377  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.135390  4597 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:49:27.135404  4597 caffe.cpp:501] detection_eval = 11.506
-I0511 11:49:27.135419  4597 caffe.cpp:501] detection_eval = 0.0499466
-I0511 11:49:27.135432  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.135449  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.135464  4597 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:49:27.135478  4597 caffe.cpp:501] detection_eval = 11.5202
-I0511 11:49:27.135493  4597 caffe.cpp:501] detection_eval = 0.0448316
-I0511 11:49:27.135506  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.135520  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.135535  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135547  4597 caffe.cpp:501] detection_eval = 11.5363
-I0511 11:49:27.135562  4597 caffe.cpp:501] detection_eval = 0.0465377
-I0511 11:49:27.135576  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.135591  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.135603  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135617  4597 caffe.cpp:501] detection_eval = 11.6028
-I0511 11:49:27.135632  4597 caffe.cpp:501] detection_eval = 0.0402731
-I0511 11:49:27.135645  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.135664  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.135679  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135692  4597 caffe.cpp:501] detection_eval = 11.6351
-I0511 11:49:27.135707  4597 caffe.cpp:501] detection_eval = 0.0384965
-I0511 11:49:27.135721  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.135735  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.135749  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135763  4597 caffe.cpp:501] detection_eval = 11.6996
-I0511 11:49:27.135777  4597 caffe.cpp:501] detection_eval = 0.035633
-I0511 11:49:27.135792  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.135805  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.135819  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135833  4597 caffe.cpp:501] detection_eval = 11.746
-I0511 11:49:27.135848  4597 caffe.cpp:501] detection_eval = 0.0382949
-I0511 11:49:27.135861  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.135875  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.135890  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135903  4597 caffe.cpp:501] detection_eval = 11.7823
-I0511 11:49:27.135917  4597 caffe.cpp:501] detection_eval = 0.0356282
-I0511 11:49:27.135931  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.135946  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.135959  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135975  4597 caffe.cpp:501] detection_eval = 11.8629
-I0511 11:49:27.135990  4597 caffe.cpp:501] detection_eval = 0.0370107
-I0511 11:49:27.136004  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.136019  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.136034  4597 caffe.cpp:501] detection_eval = 0.0745968
-I0511 11:49:27.136046  4597 caffe.cpp:501] detection_eval = 11.9234
-I0511 11:49:27.136061  4597 caffe.cpp:501] detection_eval = 0.0394983
-I0511 11:49:27.136075  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.136090  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.136103  4597 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:49:27.136117  4597 caffe.cpp:501] detection_eval = 11.9738
-I0511 11:49:27.136132  4597 caffe.cpp:501] detection_eval = 0.0436015
-I0511 11:49:27.136145  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.136159  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.136173  4597 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:49:27.136188  4597 caffe.cpp:501] detection_eval = 11.996
-I0511 11:49:27.136201  4597 caffe.cpp:501] detection_eval = 0.0392789
-I0511 11:49:27.136215  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.136229  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.136243  4597 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:49:27.136257  4597 caffe.cpp:501] detection_eval = 12.0524
-I0511 11:49:27.136271  4597 caffe.cpp:501] detection_eval = 0.0396812
-I0511 11:49:27.136287  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.136302  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.136317  4597 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:49:27.136330  4597 caffe.cpp:501] detection_eval = 12.127
-I0511 11:49:27.136344  4597 caffe.cpp:501] detection_eval = 0.0433486
-I0511 11:49:27.136358  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.136373  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.136386  4597 caffe.cpp:501] detection_eval = 0.0806452
-I0511 11:49:27.136400  4597 caffe.cpp:501] detection_eval = 12.1653
-I0511 11:49:27.136415  4597 caffe.cpp:501] detection_eval = 0.044022
-I0511 11:49:27.136428  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.136442  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.136456  4597 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:49:27.136471  4597 caffe.cpp:501] detection_eval = 12.1976
-I0511 11:49:27.136484  4597 caffe.cpp:501] detection_eval = 0.0452797
-I0511 11:49:27.136502  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.136518  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.136536  4597 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:49:27.136553  4597 caffe.cpp:501] detection_eval = 12.254
-I0511 11:49:27.136566  4597 caffe.cpp:501] detection_eval = 0.0420392
-I0511 11:49:27.136580  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.136595  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.136608  4597 caffe.cpp:501] detection_eval = 0.0866935
-I0511 11:49:27.136622  4597 caffe.cpp:501] detection_eval = 12.2984
-I0511 11:49:27.136634  4597 caffe.cpp:501] detection_eval = 0.0416046
-I0511 11:49:27.136646  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.136657  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.136669  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136680  4597 caffe.cpp:501] detection_eval = 12.3448
-I0511 11:49:27.136693  4597 caffe.cpp:501] detection_eval = 0.0415534
-I0511 11:49:27.136703  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.136715  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.136726  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136739  4597 caffe.cpp:501] detection_eval = 12.4234
-I0511 11:49:27.136750  4597 caffe.cpp:501] detection_eval = 0.0421341
-I0511 11:49:27.136761  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.136773  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.136785  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136798  4597 caffe.cpp:501] detection_eval = 12.4919
-I0511 11:49:27.136811  4597 caffe.cpp:501] detection_eval = 0.0411038
-I0511 11:49:27.136821  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.136833  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.136845  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136857  4597 caffe.cpp:501] detection_eval = 12.5847
-I0511 11:49:27.136868  4597 caffe.cpp:501] detection_eval = 0.0455635
-I0511 11:49:27.136879  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.136890  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.136903  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136914  4597 caffe.cpp:501] detection_eval = 12.6653
-I0511 11:49:27.136926  4597 caffe.cpp:501] detection_eval = 0.0447624
-I0511 11:49:27.136937  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.136950  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.136960  4597 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:49:27.136972  4597 caffe.cpp:501] detection_eval = 12.7298
-I0511 11:49:27.136983  4597 caffe.cpp:501] detection_eval = 0.0437253
-I0511 11:49:27.136994  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.137006  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.137015  4597 caffe.cpp:501] detection_eval = 0.0927419
-I0511 11:49:27.137025  4597 caffe.cpp:501] detection_eval = 12.8266
-I0511 11:49:27.137035  4597 caffe.cpp:501] detection_eval = 0.0534464
-I0511 11:49:27.137049  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.137060  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.137071  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137081  4597 caffe.cpp:501] detection_eval = 12.871
-I0511 11:49:27.137091  4597 caffe.cpp:501] detection_eval = 0.0465589
-I0511 11:49:27.137101  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137114  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.137125  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137136  4597 caffe.cpp:501] detection_eval = 12.9435
-I0511 11:49:27.137148  4597 caffe.cpp:501] detection_eval = 0.0445296
-I0511 11:49:27.137159  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.137171  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.137182  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137193  4597 caffe.cpp:501] detection_eval = 13.0262
-I0511 11:49:27.137209  4597 caffe.cpp:501] detection_eval = 0.0512573
-I0511 11:49:27.137221  4597 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:49:27.137233  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.137244  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137256  4597 caffe.cpp:501] detection_eval = 13.1169
-I0511 11:49:27.137267  4597 caffe.cpp:501] detection_eval = 0.04829
-I0511 11:49:27.137279  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.137290  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.137301  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137312  4597 caffe.cpp:501] detection_eval = 13.1472
-I0511 11:49:27.137325  4597 caffe.cpp:501] detection_eval = 0.0414065
-I0511 11:49:27.137336  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.137346  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.137357  4597 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:49:27.137368  4597 caffe.cpp:501] detection_eval = 13.1613
-I0511 11:49:27.137380  4597 caffe.cpp:501] detection_eval = 0.0442636
-I0511 11:49:27.137392  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137403  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.137414  4597 caffe.cpp:501] detection_eval = 0.0987903
-I0511 11:49:27.137425  4597 caffe.cpp:501] detection_eval = 13.1935
-I0511 11:49:27.137437  4597 caffe.cpp:501] detection_eval = 0.0424333
-I0511 11:49:27.137449  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.137459  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.137473  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137485  4597 caffe.cpp:501] detection_eval = 13.1855
-I0511 11:49:27.137496  4597 caffe.cpp:501] detection_eval = 0.0424543
-I0511 11:49:27.137507  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137518  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.137529  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137542  4597 caffe.cpp:501] detection_eval = 13.2379
-I0511 11:49:27.137552  4597 caffe.cpp:501] detection_eval = 0.0420954
-I0511 11:49:27.137563  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.137575  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.137588  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137598  4597 caffe.cpp:501] detection_eval = 13.2923
-I0511 11:49:27.137609  4597 caffe.cpp:501] detection_eval = 0.0400218
-I0511 11:49:27.137620  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137632  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.137643  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137655  4597 caffe.cpp:501] detection_eval = 13.3448
-I0511 11:49:27.137666  4597 caffe.cpp:501] detection_eval = 0.0361185
-I0511 11:49:27.137677  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.137688  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.137699  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137711  4597 caffe.cpp:501] detection_eval = 13.4214
-I0511 11:49:27.137724  4597 caffe.cpp:501] detection_eval = 0.0387783
-I0511 11:49:27.137737  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.137748  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.137759  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137770  4597 caffe.cpp:501] detection_eval = 13.4677
-I0511 11:49:27.137782  4597 caffe.cpp:501] detection_eval = 0.0393879
-I0511 11:49:27.137794  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.137806  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.137821  4597 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:49:27.137835  4597 caffe.cpp:501] detection_eval = 13.5101
-I0511 11:49:27.137848  4597 caffe.cpp:501] detection_eval = 0.0445567
-I0511 11:49:27.137861  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137873  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.137887  4597 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:49:27.137904  4597 caffe.cpp:501] detection_eval = 13.5504
-I0511 11:49:27.137917  4597 caffe.cpp:501] detection_eval = 0.0398496
-I0511 11:49:27.137930  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.137943  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.137955  4597 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:49:27.137969  4597 caffe.cpp:501] detection_eval = 13.5786
-I0511 11:49:27.137981  4597 caffe.cpp:501] detection_eval = 0.0361707
-I0511 11:49:27.137995  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138007  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.138020  4597 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:49:27.138032  4597 caffe.cpp:501] detection_eval = 13.5968
-I0511 11:49:27.138046  4597 caffe.cpp:501] detection_eval = 0.0382904
-I0511 11:49:27.138057  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138070  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.138083  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138095  4597 caffe.cpp:501] detection_eval = 13.627
-I0511 11:49:27.138108  4597 caffe.cpp:501] detection_eval = 0.0435423
-I0511 11:49:27.138121  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.138134  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.138146  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138159  4597 caffe.cpp:501] detection_eval = 13.6976
-I0511 11:49:27.138171  4597 caffe.cpp:501] detection_eval = 0.0371483
-I0511 11:49:27.138185  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138200  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.138213  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138226  4597 caffe.cpp:501] detection_eval = 13.7581
-I0511 11:49:27.138238  4597 caffe.cpp:501] detection_eval = 0.0372349
-I0511 11:49:27.138252  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.138265  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.138278  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138290  4597 caffe.cpp:501] detection_eval = 13.8185
-I0511 11:49:27.138303  4597 caffe.cpp:501] detection_eval = 0.0346949
-I0511 11:49:27.138316  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.138329  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.138341  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138355  4597 caffe.cpp:501] detection_eval = 13.8347
-I0511 11:49:27.138367  4597 caffe.cpp:501] detection_eval = 0.036285
-I0511 11:49:27.138381  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138393  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.138406  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138419  4597 caffe.cpp:501] detection_eval = 13.8649
-I0511 11:49:27.138432  4597 caffe.cpp:501] detection_eval = 0.034692
-I0511 11:49:27.138444  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138458  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.138470  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138486  4597 caffe.cpp:501] detection_eval = 13.9113
-I0511 11:49:27.138499  4597 caffe.cpp:501] detection_eval = 0.0342626
-I0511 11:49:27.138512  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.138525  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.138538  4597 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:49:27.138551  4597 caffe.cpp:501] detection_eval = 13.9556
-I0511 11:49:27.138564  4597 caffe.cpp:501] detection_eval = 0.0420291
-I0511 11:49:27.138577  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.138590  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.138603  4597 caffe.cpp:501] detection_eval = 0.116935
-I0511 11:49:27.138617  4597 caffe.cpp:501] detection_eval = 13.9899
-I0511 11:49:27.138629  4597 caffe.cpp:501] detection_eval = 0.0428096
-I0511 11:49:27.138643  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.138655  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.138672  4597 caffe.cpp:501] detection_eval = 0.116935
-I0511 11:49:27.138686  4597 caffe.cpp:501] detection_eval = 14.0504
-I0511 11:49:27.138700  4597 caffe.cpp:501] detection_eval = 0.0409506
-I0511 11:49:27.138711  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.138725  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.138737  4597 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:49:27.138751  4597 caffe.cpp:501] detection_eval = 14.0645
-I0511 11:49:27.138763  4597 caffe.cpp:501] detection_eval = 0.0405591
-I0511 11:49:27.138777  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.138789  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.138801  4597 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:49:27.138814  4597 caffe.cpp:501] detection_eval = 14.0927
-I0511 11:49:27.138828  4597 caffe.cpp:501] detection_eval = 0.0365014
-I0511 11:49:27.138840  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.138854  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.138866  4597 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:49:27.138878  4597 caffe.cpp:501] detection_eval = 14.1351
-I0511 11:49:27.138891  4597 caffe.cpp:501] detection_eval = 0.0343148
-I0511 11:49:27.138903  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.138916  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.138929  4597 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:49:27.138942  4597 caffe.cpp:501] detection_eval = 14.1593
-I0511 11:49:27.138955  4597 caffe.cpp:501] detection_eval = 0.0369762
-I0511 11:49:27.138972  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.138986  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.138999  4597 caffe.cpp:501] detection_eval = 0.120968
-I0511 11:49:27.139015  4597 caffe.cpp:501] detection_eval = 14.1573
-I0511 11:49:27.139029  4597 caffe.cpp:501] detection_eval = 0.035061
-I0511 11:49:27.139042  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139055  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.139070  4597 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:49:27.139083  4597 caffe.cpp:501] detection_eval = 14.1512
-I0511 11:49:27.139096  4597 caffe.cpp:501] detection_eval = 0.035864
-I0511 11:49:27.139109  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139123  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.139140  4597 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:49:27.139153  4597 caffe.cpp:501] detection_eval = 14.1855
-I0511 11:49:27.139166  4597 caffe.cpp:501] detection_eval = 0.0329432
-I0511 11:49:27.139179  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139192  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139205  4597 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:49:27.139219  4597 caffe.cpp:501] detection_eval = 14.1694
-I0511 11:49:27.139231  4597 caffe.cpp:501] detection_eval = 0.0330096
-I0511 11:49:27.139245  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139257  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139272  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139286  4597 caffe.cpp:501] detection_eval = 14.252
-I0511 11:49:27.139299  4597 caffe.cpp:501] detection_eval = 0.0325234
-I0511 11:49:27.139312  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.139325  4597 caffe.cpp:501] detection_eval = 1
-I0511 11:49:27.139338  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139350  4597 caffe.cpp:501] detection_eval = 14.2742
-I0511 11:49:27.139364  4597 caffe.cpp:501] detection_eval = 0.0301755
-I0511 11:49:27.139376  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.139389  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.139401  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139415  4597 caffe.cpp:501] detection_eval = 14.3004
-I0511 11:49:27.139428  4597 caffe.cpp:501] detection_eval = 0.0304516
-I0511 11:49:27.139441  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139453  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.139472  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139484  4597 caffe.cpp:501] detection_eval = 14.3226
-I0511 11:49:27.139497  4597 caffe.cpp:501] detection_eval = 0.0326873
-I0511 11:49:27.139510  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139523  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.139536  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139549  4597 caffe.cpp:501] detection_eval = 14.373
-I0511 11:49:27.139561  4597 caffe.cpp:501] detection_eval = 0.0322298
-I0511 11:49:27.139575  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139588  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139601  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139614  4597 caffe.cpp:501] detection_eval = 14.4375
-I0511 11:49:27.139627  4597 caffe.cpp:501] detection_eval = 0.0339324
-I0511 11:49:27.139641  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.139653  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.139667  4597 caffe.cpp:501] detection_eval = 0.131048
-I0511 11:49:27.139678  4597 caffe.cpp:501] detection_eval = 14.4435
-I0511 11:49:27.139691  4597 caffe.cpp:501] detection_eval = 0.0360259
-I0511 11:49:27.139704  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.139717  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.139730  4597 caffe.cpp:501] detection_eval = 0.131048
-I0511 11:49:27.139744  4597 caffe.cpp:501] detection_eval = 14.4819
-I0511 11:49:27.139758  4597 caffe.cpp:501] detection_eval = 0.0316306
-I0511 11:49:27.139771  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139784  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139797  4597 caffe.cpp:501] detection_eval = 0.131048
-I0511 11:49:27.139809  4597 caffe.cpp:501] detection_eval = 14.5484
-I0511 11:49:27.139822  4597 caffe.cpp:501] detection_eval = 0.0332233
-I0511 11:49:27.139835  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139848  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139861  4597 caffe.cpp:501] detection_eval = 0.133065
-I0511 11:49:27.139874  4597 caffe.cpp:501] detection_eval = 14.5786
-I0511 11:49:27.139888  4597 caffe.cpp:501] detection_eval = 0.0363158
-I0511 11:49:27.139899  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.139912  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.139925  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.139938  4597 caffe.cpp:501] detection_eval = 14.5847
-I0511 11:49:27.139951  4597 caffe.cpp:501] detection_eval = 0.0350456
-I0511 11:49:27.139964  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139976  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139989  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140002  4597 caffe.cpp:501] detection_eval = 14.623
-I0511 11:49:27.140015  4597 caffe.cpp:501] detection_eval = 0.0356263
-I0511 11:49:27.140028  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140043  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140056  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140069  4597 caffe.cpp:501] detection_eval = 14.6431
-I0511 11:49:27.140082  4597 caffe.cpp:501] detection_eval = 0.0318447
-I0511 11:49:27.140095  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.140108  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140121  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140135  4597 caffe.cpp:501] detection_eval = 14.6935
-I0511 11:49:27.140147  4597 caffe.cpp:501] detection_eval = 0.03345
-I0511 11:49:27.140161  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.140173  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.140187  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140200  4597 caffe.cpp:501] detection_eval = 14.7399
-I0511 11:49:27.140213  4597 caffe.cpp:501] detection_eval = 0.0338787
-I0511 11:49:27.140226  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140244  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140257  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140270  4597 caffe.cpp:501] detection_eval = 14.7903
-I0511 11:49:27.140283  4597 caffe.cpp:501] detection_eval = 0.0337207
-I0511 11:49:27.140295  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.140308  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.140321  4597 caffe.cpp:501] detection_eval = 0.143145
-I0511 11:49:27.140333  4597 caffe.cpp:501] detection_eval = 14.75
-I0511 11:49:27.140347  4597 caffe.cpp:501] detection_eval = 0.036413
-I0511 11:49:27.140359  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.140372  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140385  4597 caffe.cpp:501] detection_eval = 0.143145
-I0511 11:49:27.140398  4597 caffe.cpp:501] detection_eval = 14.8105
-I0511 11:49:27.140410  4597 caffe.cpp:501] detection_eval = 0.0325231
-I0511 11:49:27.140424  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.140436  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140450  4597 caffe.cpp:501] detection_eval = 0.145161
-I0511 11:49:27.140461  4597 caffe.cpp:501] detection_eval = 14.8266
-I0511 11:49:27.140475  4597 caffe.cpp:501] detection_eval = 0.0326505
-I0511 11:49:27.140487  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140501  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140512  4597 caffe.cpp:501] detection_eval = 0.147177
-I0511 11:49:27.140534  4597 caffe.cpp:501] detection_eval = 14.8851
-I0511 11:49:27.140550  4597 caffe.cpp:501] detection_eval = 0.0387736
-I0511 11:49:27.140563  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140576  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140589  4597 caffe.cpp:501] detection_eval = 0.15121
-I0511 11:49:27.140602  4597 caffe.cpp:501] detection_eval = 14.8831
-I0511 11:49:27.140615  4597 caffe.cpp:501] detection_eval = 0.0343417
-I0511 11:49:27.140628  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.140641  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140655  4597 caffe.cpp:501] detection_eval = 0.155242
-I0511 11:49:27.140666  4597 caffe.cpp:501] detection_eval = 14.9315
-I0511 11:49:27.140681  4597 caffe.cpp:501] detection_eval = 0.0331358
-I0511 11:49:27.140692  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140705  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.140718  4597 caffe.cpp:501] detection_eval = 0.157258
-I0511 11:49:27.140732  4597 caffe.cpp:501] detection_eval = 14.9718
-I0511 11:49:27.140745  4597 caffe.cpp:501] detection_eval = 0.0350309
-I0511 11:49:27.140758  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.140771  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140784  4597 caffe.cpp:501] detection_eval = 0.159274
-I0511 11:49:27.140796  4597 caffe.cpp:501] detection_eval = 14.9879
-I0511 11:49:27.140810  4597 caffe.cpp:501] detection_eval = 0.0314733
-I0511 11:49:27.140825  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.140838  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.140851  4597 caffe.cpp:501] detection_eval = 0.159274
-I0511 11:49:27.140863  4597 caffe.cpp:501] detection_eval = 15.0565
-I0511 11:49:27.140877  4597 caffe.cpp:501] detection_eval = 0.0325432
-I0511 11:49:27.140889  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140902  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140915  4597 caffe.cpp:501] detection_eval = 0.159274
-I0511 11:49:27.140928  4597 caffe.cpp:501] detection_eval = 15.2016
-I0511 11:49:27.140941  4597 caffe.cpp:501] detection_eval = 0.0410111
-I0511 11:49:27.140954  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.140966  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.140980  4597 caffe.cpp:501] detection_eval = 0.159274
-I0511 11:49:27.140992  4597 caffe.cpp:501] detection_eval = 15.3327
-I0511 11:49:27.141005  4597 caffe.cpp:501] detection_eval = 0.0373448
-I0511 11:49:27.141023  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.141036  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.141049  4597 caffe.cpp:501] detection_eval = 0.167339
-I0511 11:49:27.141062  4597 caffe.cpp:501] detection_eval = 15.3649
-I0511 11:49:27.141075  4597 caffe.cpp:501] detection_eval = 0.0424123
-I0511 11:49:27.141088  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.141101  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.141113  4597 caffe.cpp:501] detection_eval = 0.167339
-I0511 11:49:27.141126  4597 caffe.cpp:501] detection_eval = 15.4859
-I0511 11:49:27.141139  4597 caffe.cpp:501] detection_eval = 0.0360478
-I0511 11:49:27.141153  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.141166  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.141180  4597 caffe.cpp:501] detection_eval = 0.167339
-I0511 11:49:27.141192  4597 caffe.cpp:501] detection_eval = 15.6391
-I0511 11:49:27.141206  4597 caffe.cpp:501] detection_eval = 0.0404236
-I0511 11:49:27.141218  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.141230  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.141243  4597 caffe.cpp:501] detection_eval = 0.169355
-I0511 11:49:27.141257  4597 caffe.cpp:501] detection_eval = 15.8105
-I0511 11:49:27.141269  4597 caffe.cpp:501] detection_eval = 0.03665
-I0511 11:49:27.141283  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.141294  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.141310  4597 caffe.cpp:501] detection_eval = 0.173387
-I0511 11:49:27.141324  4597 caffe.cpp:501] detection_eval = 15.9738
-I0511 11:49:27.141336  4597 caffe.cpp:501] detection_eval = 0.0364727
-I0511 11:49:27.141350  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.141362  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.141376  4597 caffe.cpp:501] detection_eval = 0.173387
-I0511 11:49:27.141387  4597 caffe.cpp:501] detection_eval = 16.3206
-I0511 11:49:27.141402  4597 caffe.cpp:501] detection_eval = 0.0422899
-I0511 11:49:27.141413  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.141427  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.141439  4597 caffe.cpp:501] detection_eval = 0.175403
-I0511 11:49:27.141450  4597 caffe.cpp:501] detection_eval = 16.7742
-I0511 11:49:27.141463  4597 caffe.cpp:501] detection_eval = 0.0304554
-I0511 11:49:27.141476  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.141489  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.141502  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141515  4597 caffe.cpp:501] detection_eval = 4.12702
-I0511 11:49:27.141528  4597 caffe.cpp:501] detection_eval = 0.149664
-I0511 11:49:27.141541  4597 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:49:27.141556  4597 caffe.cpp:501] detection_eval = 0.875
-I0511 11:49:27.141567  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141580  4597 caffe.cpp:501] detection_eval = 4.40726
-I0511 11:49:27.141593  4597 caffe.cpp:501] detection_eval = 0.0784179
-I0511 11:49:27.141608  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.141623  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.141635  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141649  4597 caffe.cpp:501] detection_eval = 4.62298
-I0511 11:49:27.141661  4597 caffe.cpp:501] detection_eval = 0.0701486
-I0511 11:49:27.141674  4597 caffe.cpp:501] detection_eval = 0.0443548
-I0511 11:49:27.141688  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.141701  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141715  4597 caffe.cpp:501] detection_eval = 4.79234
-I0511 11:49:27.141726  4597 caffe.cpp:501] detection_eval = 0.0624976
-I0511 11:49:27.141739  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.141752  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.141765  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141778  4597 caffe.cpp:501] detection_eval = 4.95565
-I0511 11:49:27.141795  4597 caffe.cpp:501] detection_eval = 0.0622305
-I0511 11:49:27.141809  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.141821  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.141834  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141847  4597 caffe.cpp:501] detection_eval = 5.0746
-I0511 11:49:27.141861  4597 caffe.cpp:501] detection_eval = 0.0590016
-I0511 11:49:27.141875  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.141887  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.141901  4597 caffe.cpp:501] detection_eval = 1.01411
-I0511 11:49:27.141912  4597 caffe.cpp:501] detection_eval = 5.16734
-I0511 11:49:27.141925  4597 caffe.cpp:501] detection_eval = 0.0508263
-I0511 11:49:27.141938  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.141952  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.141964  4597 caffe.cpp:501] detection_eval = 1.01613
-I0511 11:49:27.141976  4597 caffe.cpp:501] detection_eval = 5.27016
-I0511 11:49:27.141989  4597 caffe.cpp:501] detection_eval = 0.0498147
-I0511 11:49:27.142002  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.142014  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.142027  4597 caffe.cpp:501] detection_eval = 1.01815
-I0511 11:49:27.142040  4597 caffe.cpp:501] detection_eval = 5.30645
-I0511 11:49:27.142053  4597 caffe.cpp:501] detection_eval = 0.045917
-I0511 11:49:27.142066  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142078  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.142093  4597 caffe.cpp:501] detection_eval = 1.01815
-I0511 11:49:27.142107  4597 caffe.cpp:501] detection_eval = 5.39516
-I0511 11:49:27.142119  4597 caffe.cpp:501] detection_eval = 0.045753
-I0511 11:49:27.142132  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142146  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.142159  4597 caffe.cpp:501] detection_eval = 1.01815
-I0511 11:49:27.142172  4597 caffe.cpp:501] detection_eval = 5.4496
-I0511 11:49:27.142185  4597 caffe.cpp:501] detection_eval = 0.0404288
-I0511 11:49:27.142199  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.142211  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.142225  4597 caffe.cpp:501] detection_eval = 1.02016
-I0511 11:49:27.142237  4597 caffe.cpp:501] detection_eval = 5.47177
-I0511 11:49:27.142249  4597 caffe.cpp:501] detection_eval = 0.0440242
-I0511 11:49:27.142262  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.142276  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.142288  4597 caffe.cpp:501] detection_eval = 1.02016
-I0511 11:49:27.142300  4597 caffe.cpp:501] detection_eval = 5.56855
-I0511 11:49:27.142313  4597 caffe.cpp:501] detection_eval = 0.0451199
-I0511 11:49:27.142326  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142339  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.142351  4597 caffe.cpp:501] detection_eval = 1.02218
-I0511 11:49:27.142364  4597 caffe.cpp:501] detection_eval = 5.59879
-I0511 11:49:27.142380  4597 caffe.cpp:501] detection_eval = 0.0448299
-I0511 11:49:27.142395  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.142407  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.142419  4597 caffe.cpp:501] detection_eval = 1.02419
-I0511 11:49:27.142432  4597 caffe.cpp:501] detection_eval = 5.63508
-I0511 11:49:27.142446  4597 caffe.cpp:501] detection_eval = 0.0521873
-I0511 11:49:27.142458  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.142470  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.142483  4597 caffe.cpp:501] detection_eval = 1.02621
-I0511 11:49:27.142496  4597 caffe.cpp:501] detection_eval = 5.66935
-I0511 11:49:27.142509  4597 caffe.cpp:501] detection_eval = 0.0443965
-I0511 11:49:27.142521  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.142534  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.142547  4597 caffe.cpp:501] detection_eval = 1.02621
-I0511 11:49:27.142560  4597 caffe.cpp:501] detection_eval = 5.76411
-I0511 11:49:27.142577  4597 caffe.cpp:501] detection_eval = 0.0405536
-I0511 11:49:27.142591  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142603  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.142616  4597 caffe.cpp:501] detection_eval = 1.02621
-I0511 11:49:27.142633  4597 caffe.cpp:501] detection_eval = 5.85081
-I0511 11:49:27.142647  4597 caffe.cpp:501] detection_eval = 0.042654
-I0511 11:49:27.142663  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142676  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.142691  4597 caffe.cpp:501] detection_eval = 1.03024
-I0511 11:49:27.142705  4597 caffe.cpp:501] detection_eval = 5.90121
-I0511 11:49:27.142719  4597 caffe.cpp:501] detection_eval = 0.0400547
-I0511 11:49:27.142732  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.142745  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.142758  4597 caffe.cpp:501] detection_eval = 1.03024
-I0511 11:49:27.142771  4597 caffe.cpp:501] detection_eval = 5.98589
-I0511 11:49:27.142786  4597 caffe.cpp:501] detection_eval = 0.0409764
-I0511 11:49:27.142798  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.142812  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.142825  4597 caffe.cpp:501] detection_eval = 1.03226
-I0511 11:49:27.142838  4597 caffe.cpp:501] detection_eval = 6.02823
-I0511 11:49:27.142851  4597 caffe.cpp:501] detection_eval = 0.0386796
-I0511 11:49:27.142864  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.142880  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.142894  4597 caffe.cpp:501] detection_eval = 1.03226
-I0511 11:49:27.142907  4597 caffe.cpp:501] detection_eval = 6.09879
-I0511 11:49:27.142921  4597 caffe.cpp:501] detection_eval = 0.0445525
-I0511 11:49:27.142935  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.142949  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.142963  4597 caffe.cpp:501] detection_eval = 1.03629
-I0511 11:49:27.142977  4597 caffe.cpp:501] detection_eval = 6.12097
-I0511 11:49:27.142990  4597 caffe.cpp:501] detection_eval = 0.0419441
-I0511 11:49:27.143004  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.143018  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.143030  4597 caffe.cpp:501] detection_eval = 1.03831
-I0511 11:49:27.143044  4597 caffe.cpp:501] detection_eval = 6.19758
-I0511 11:49:27.143057  4597 caffe.cpp:501] detection_eval = 0.0432385
-I0511 11:49:27.143071  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.143085  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.143097  4597 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:49:27.143111  4597 caffe.cpp:501] detection_eval = 6.23185
-I0511 11:49:27.143126  4597 caffe.cpp:501] detection_eval = 0.0413859
-I0511 11:49:27.143142  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143157  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.143172  4597 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:49:27.143190  4597 caffe.cpp:501] detection_eval = 6.30847
-I0511 11:49:27.143204  4597 caffe.cpp:501] detection_eval = 0.0380197
-I0511 11:49:27.143219  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.143234  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.143249  4597 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:49:27.143263  4597 caffe.cpp:501] detection_eval = 6.40323
-I0511 11:49:27.143277  4597 caffe.cpp:501] detection_eval = 0.0423985
-I0511 11:49:27.143292  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.143306  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.143321  4597 caffe.cpp:501] detection_eval = 1.04234
-I0511 11:49:27.143335  4597 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:49:27.143349  4597 caffe.cpp:501] detection_eval = 0.0383202
-I0511 11:49:27.143364  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.143379  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.143393  4597 caffe.cpp:501] detection_eval = 1.04637
-I0511 11:49:27.143412  4597 caffe.cpp:501] detection_eval = 6.45363
-I0511 11:49:27.143427  4597 caffe.cpp:501] detection_eval = 0.0365058
-I0511 11:49:27.143441  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143457  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.143472  4597 caffe.cpp:501] detection_eval = 1.04637
-I0511 11:49:27.143486  4597 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:49:27.143501  4597 caffe.cpp:501] detection_eval = 0.0359437
-I0511 11:49:27.143515  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143529  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.143544  4597 caffe.cpp:501] detection_eval = 1.04637
-I0511 11:49:27.143558  4597 caffe.cpp:501] detection_eval = 6.6371
-I0511 11:49:27.143574  4597 caffe.cpp:501] detection_eval = 0.0397337
-I0511 11:49:27.143590  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.143604  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.143620  4597 caffe.cpp:501] detection_eval = 1.04839
-I0511 11:49:27.143635  4597 caffe.cpp:501] detection_eval = 6.70161
-I0511 11:49:27.143649  4597 caffe.cpp:501] detection_eval = 0.0413847
-I0511 11:49:27.143666  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143682  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.143697  4597 caffe.cpp:501] detection_eval = 1.04839
-I0511 11:49:27.143728  4597 caffe.cpp:501] detection_eval = 6.77016
-I0511 11:49:27.143749  4597 caffe.cpp:501] detection_eval = 0.0406304
-I0511 11:49:27.143764  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.143781  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.143796  4597 caffe.cpp:501] detection_eval = 1.04839
-I0511 11:49:27.143810  4597 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:49:27.143824  4597 caffe.cpp:501] detection_eval = 0.0351328
-I0511 11:49:27.143837  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.143852  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.143867  4597 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:49:27.143879  4597 caffe.cpp:501] detection_eval = 6.88105
-I0511 11:49:27.143893  4597 caffe.cpp:501] detection_eval = 0.0374926
-I0511 11:49:27.143908  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.143921  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.143936  4597 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:49:27.143950  4597 caffe.cpp:501] detection_eval = 6.99798
-I0511 11:49:27.143963  4597 caffe.cpp:501] detection_eval = 0.0416074
-I0511 11:49:27.143977  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143992  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.144006  4597 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:49:27.144019  4597 caffe.cpp:501] detection_eval = 7.14516
-I0511 11:49:27.144033  4597 caffe.cpp:501] detection_eval = 0.0420148
-I0511 11:49:27.144048  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.144062  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144075  4597 caffe.cpp:501] detection_eval = 1.05444
-I0511 11:49:27.144093  4597 caffe.cpp:501] detection_eval = 7.15323
-I0511 11:49:27.144109  4597 caffe.cpp:501] detection_eval = 0.0411047
-I0511 11:49:27.144122  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144137  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.144151  4597 caffe.cpp:501] detection_eval = 1.05645
-I0511 11:49:27.144165  4597 caffe.cpp:501] detection_eval = 7.22581
-I0511 11:49:27.144179  4597 caffe.cpp:501] detection_eval = 0.0394439
-I0511 11:49:27.144193  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144207  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144220  4597 caffe.cpp:501] detection_eval = 1.05645
-I0511 11:49:27.144234  4597 caffe.cpp:501] detection_eval = 7.31048
-I0511 11:49:27.144248  4597 caffe.cpp:501] detection_eval = 0.0354345
-I0511 11:49:27.144263  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144276  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144292  4597 caffe.cpp:501] detection_eval = 1.05645
-I0511 11:49:27.144304  4597 caffe.cpp:501] detection_eval = 7.40927
-I0511 11:49:27.144313  4597 caffe.cpp:501] detection_eval = 0.0408727
-I0511 11:49:27.144322  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144331  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.144341  4597 caffe.cpp:501] detection_eval = 1.05847
-I0511 11:49:27.144351  4597 caffe.cpp:501] detection_eval = 7.48589
-I0511 11:49:27.144358  4597 caffe.cpp:501] detection_eval = 0.0395751
-I0511 11:49:27.144367  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.144377  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144387  4597 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:49:27.144394  4597 caffe.cpp:501] detection_eval = 7.53831
-I0511 11:49:27.144402  4597 caffe.cpp:501] detection_eval = 0.0404673
-I0511 11:49:27.144412  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144423  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.144431  4597 caffe.cpp:501] detection_eval = 1.0625
-I0511 11:49:27.144439  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.144448  4597 caffe.cpp:501] detection_eval = 0.0437643
-I0511 11:49:27.144456  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144466  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.144476  4597 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:49:27.144484  4597 caffe.cpp:501] detection_eval = 7.66331
-I0511 11:49:27.144492  4597 caffe.cpp:501] detection_eval = 0.0436936
-I0511 11:49:27.144501  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.144510  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.144518  4597 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:49:27.144536  4597 caffe.cpp:501] detection_eval = 7.75605
-I0511 11:49:27.144546  4597 caffe.cpp:501] detection_eval = 0.0451707
-I0511 11:49:27.144556  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144564  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.144573  4597 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:49:27.144582  4597 caffe.cpp:501] detection_eval = 7.85685
-I0511 11:49:27.144589  4597 caffe.cpp:501] detection_eval = 0.0391205
-I0511 11:49:27.144598  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144605  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.144614  4597 caffe.cpp:501] detection_eval = 1.06855
-I0511 11:49:27.144624  4597 caffe.cpp:501] detection_eval = 7.90323
-I0511 11:49:27.144634  4597 caffe.cpp:501] detection_eval = 0.0425444
-I0511 11:49:27.144641  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.144649  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.144657  4597 caffe.cpp:501] detection_eval = 1.07056
-I0511 11:49:27.144666  4597 caffe.cpp:501] detection_eval = 7.93347
-I0511 11:49:27.144675  4597 caffe.cpp:501] detection_eval = 0.0481662
-I0511 11:49:27.144683  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144692  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.144706  4597 caffe.cpp:501] detection_eval = 1.07056
-I0511 11:49:27.144714  4597 caffe.cpp:501] detection_eval = 8.01411
-I0511 11:49:27.144723  4597 caffe.cpp:501] detection_eval = 0.0398225
-I0511 11:49:27.144731  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.144740  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.144748  4597 caffe.cpp:501] detection_eval = 1.07661
-I0511 11:49:27.144757  4597 caffe.cpp:501] detection_eval = 7.99395
-I0511 11:49:27.144764  4597 caffe.cpp:501] detection_eval = 0.0411763
-I0511 11:49:27.144774  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144783  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144793  4597 caffe.cpp:501] detection_eval = 1.07661
-I0511 11:49:27.144801  4597 caffe.cpp:501] detection_eval = 8.03226
-I0511 11:49:27.144809  4597 caffe.cpp:501] detection_eval = 0.0390111
-I0511 11:49:27.144817  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.144825  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144840  4597 caffe.cpp:501] detection_eval = 1.07863
-I0511 11:49:27.144847  4597 caffe.cpp:501] detection_eval = 8.10282
-I0511 11:49:27.144857  4597 caffe.cpp:501] detection_eval = 0.0432689
-I0511 11:49:27.144867  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144876  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.144884  4597 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:49:27.144893  4597 caffe.cpp:501] detection_eval = 8.11492
-I0511 11:49:27.144901  4597 caffe.cpp:501] detection_eval = 0.0395303
-I0511 11:49:27.144909  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.144918  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144927  4597 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:49:27.144934  4597 caffe.cpp:501] detection_eval = 8.16331
-I0511 11:49:27.144944  4597 caffe.cpp:501] detection_eval = 0.0367415
-I0511 11:49:27.144953  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144963  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.144970  4597 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:49:27.144979  4597 caffe.cpp:501] detection_eval = 8.22379
-I0511 11:49:27.144984  4597 caffe.cpp:501] detection_eval = 0.0368785
-I0511 11:49:27.144989  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.144992  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144997  4597 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:49:27.145001  4597 caffe.cpp:501] detection_eval = 8.31048
-I0511 11:49:27.145006  4597 caffe.cpp:501] detection_eval = 0.039801
-I0511 11:49:27.145011  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145016  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145020  4597 caffe.cpp:501] detection_eval = 1.08266
-I0511 11:49:27.145023  4597 caffe.cpp:501] detection_eval = 8.38105
-I0511 11:49:27.145028  4597 caffe.cpp:501] detection_eval = 0.0395155
-I0511 11:49:27.145033  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145043  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145050  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145054  4597 caffe.cpp:501] detection_eval = 8.41935
-I0511 11:49:27.145064  4597 caffe.cpp:501] detection_eval = 0.0432269
-I0511 11:49:27.145069  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145073  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145078  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145082  4597 caffe.cpp:501] detection_eval = 8.5121
-I0511 11:49:27.145087  4597 caffe.cpp:501] detection_eval = 0.0442923
-I0511 11:49:27.145092  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145095  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145100  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145104  4597 caffe.cpp:501] detection_eval = 8.60484
-I0511 11:49:27.145109  4597 caffe.cpp:501] detection_eval = 0.0466011
-I0511 11:49:27.145114  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145118  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145123  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145126  4597 caffe.cpp:501] detection_eval = 8.6754
-I0511 11:49:27.145130  4597 caffe.cpp:501] detection_eval = 0.0382274
-I0511 11:49:27.145135  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145139  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.145144  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145148  4597 caffe.cpp:501] detection_eval = 8.76411
-I0511 11:49:27.145153  4597 caffe.cpp:501] detection_eval = 0.0373927
-I0511 11:49:27.145157  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145162  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145166  4597 caffe.cpp:501] detection_eval = 1.08871
-I0511 11:49:27.145171  4597 caffe.cpp:501] detection_eval = 8.79032
-I0511 11:49:27.145176  4597 caffe.cpp:501] detection_eval = 0.0388855
-I0511 11:49:27.145180  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145190  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145195  4597 caffe.cpp:501] detection_eval = 1.08871
-I0511 11:49:27.145198  4597 caffe.cpp:501] detection_eval = 8.91734
-I0511 11:49:27.145203  4597 caffe.cpp:501] detection_eval = 0.0389421
-I0511 11:49:27.145207  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.145211  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.145215  4597 caffe.cpp:501] detection_eval = 1.09476
-I0511 11:49:27.145220  4597 caffe.cpp:501] detection_eval = 8.90524
-I0511 11:49:27.145225  4597 caffe.cpp:501] detection_eval = 0.0407377
-I0511 11:49:27.145226  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145229  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145231  4597 caffe.cpp:501] detection_eval = 1.09476
-I0511 11:49:27.145233  4597 caffe.cpp:501] detection_eval = 9.02016
-I0511 11:49:27.145236  4597 caffe.cpp:501] detection_eval = 0.0462407
-I0511 11:49:27.145238  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145241  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145244  4597 caffe.cpp:501] detection_eval = 1.09476
-I0511 11:49:27.145247  4597 caffe.cpp:501] detection_eval = 9.08669
-I0511 11:49:27.145249  4597 caffe.cpp:501] detection_eval = 0.0400719
-I0511 11:49:27.145252  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145254  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145257  4597 caffe.cpp:501] detection_eval = 1.09677
-I0511 11:49:27.145259  4597 caffe.cpp:501] detection_eval = 9.23992
-I0511 11:49:27.145262  4597 caffe.cpp:501] detection_eval = 0.0503495
-I0511 11:49:27.145264  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.145267  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.145269  4597 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:49:27.145272  4597 caffe.cpp:501] detection_eval = 9.27823
-I0511 11:49:27.145274  4597 caffe.cpp:501] detection_eval = 0.0405731
-I0511 11:49:27.145277  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145278  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145282  4597 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:49:27.145283  4597 caffe.cpp:501] detection_eval = 9.36694
-I0511 11:49:27.145287  4597 caffe.cpp:501] detection_eval = 0.040862
-I0511 11:49:27.145288  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145292  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145293  4597 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:49:27.145296  4597 caffe.cpp:501] detection_eval = 9.48185
-I0511 11:49:27.145298  4597 caffe.cpp:501] detection_eval = 0.0391158
-I0511 11:49:27.145301  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145303  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145306  4597 caffe.cpp:501] detection_eval = 1.10282
-I0511 11:49:27.145308  4597 caffe.cpp:501] detection_eval = 9.56048
-I0511 11:49:27.145310  4597 caffe.cpp:501] detection_eval = 0.039909
-I0511 11:49:27.145313  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145315  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145318  4597 caffe.cpp:501] detection_eval = 1.10685
-I0511 11:49:27.145320  4597 caffe.cpp:501] detection_eval = 9.59073
-I0511 11:49:27.145323  4597 caffe.cpp:501] detection_eval = 0.0405835
-I0511 11:49:27.145325  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.145328  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.145329  4597 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:49:27.145332  4597 caffe.cpp:501] detection_eval = 9.72984
-I0511 11:49:27.145334  4597 caffe.cpp:501] detection_eval = 0.0489761
-I0511 11:49:27.145337  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145339  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145342  4597 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:49:27.145344  4597 caffe.cpp:501] detection_eval = 9.80444
-I0511 11:49:27.145347  4597 caffe.cpp:501] detection_eval = 0.0469686
-I0511 11:49:27.145354  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145356  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145359  4597 caffe.cpp:501] detection_eval = 1.1129
-I0511 11:49:27.145361  4597 caffe.cpp:501] detection_eval = 9.87298
-I0511 11:49:27.145364  4597 caffe.cpp:501] detection_eval = 0.0530507
-I0511 11:49:27.145365  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.145368  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.145370  4597 caffe.cpp:501] detection_eval = 1.11694
-I0511 11:49:27.145372  4597 caffe.cpp:501] detection_eval = 9.94556
-I0511 11:49:27.145375  4597 caffe.cpp:501] detection_eval = 0.0506045
-I0511 11:49:27.145377  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145380  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.145382  4597 caffe.cpp:501] detection_eval = 1.11895
-I0511 11:49:27.145385  4597 caffe.cpp:501] detection_eval = 9.96774
-I0511 11:49:27.145387  4597 caffe.cpp:501] detection_eval = 0.0446408
-I0511 11:49:27.145390  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145392  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145395  4597 caffe.cpp:501] detection_eval = 1.12298
-I0511 11:49:27.145397  4597 caffe.cpp:501] detection_eval = 10.0181
-I0511 11:49:27.145401  4597 caffe.cpp:501] detection_eval = 0.0450307
-I0511 11:49:27.145402  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145406  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145407  4597 caffe.cpp:501] detection_eval = 1.12298
-I0511 11:49:27.145411  4597 caffe.cpp:501] detection_eval = 10.123
-I0511 11:49:27.145413  4597 caffe.cpp:501] detection_eval = 0.0510043
-I0511 11:49:27.145416  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.145418  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.145421  4597 caffe.cpp:501] detection_eval = 1.12903
-I0511 11:49:27.145423  4597 caffe.cpp:501] detection_eval = 10.0806
-I0511 11:49:27.145426  4597 caffe.cpp:501] detection_eval = 0.0439102
-I0511 11:49:27.145428  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145431  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145433  4597 caffe.cpp:501] detection_eval = 1.13105
-I0511 11:49:27.145437  4597 caffe.cpp:501] detection_eval = 10.1411
-I0511 11:49:27.145438  4597 caffe.cpp:501] detection_eval = 0.0428833
-I0511 11:49:27.145442  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145443  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145447  4597 caffe.cpp:501] detection_eval = 1.13105
-I0511 11:49:27.145448  4597 caffe.cpp:501] detection_eval = 10.246
-I0511 11:49:27.145452  4597 caffe.cpp:501] detection_eval = 0.0500312
-I0511 11:49:27.145453  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145455  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145458  4597 caffe.cpp:501] detection_eval = 1.13306
-I0511 11:49:27.145460  4597 caffe.cpp:501] detection_eval = 10.2681
-I0511 11:49:27.145463  4597 caffe.cpp:501] detection_eval = 0.0444223
-I0511 11:49:27.145465  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145467  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145470  4597 caffe.cpp:501] detection_eval = 1.13508
-I0511 11:49:27.145473  4597 caffe.cpp:501] detection_eval = 10.3004
-I0511 11:49:27.145475  4597 caffe.cpp:501] detection_eval = 0.0467727
-I0511 11:49:27.145478  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145480  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.145483  4597 caffe.cpp:501] detection_eval = 1.1371
-I0511 11:49:27.145484  4597 caffe.cpp:501] detection_eval = 10.3972
-I0511 11:49:27.145488  4597 caffe.cpp:501] detection_eval = 0.047602
-I0511 11:49:27.145490  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145493  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145495  4597 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:49:27.145498  4597 caffe.cpp:501] detection_eval = 10.4214
-I0511 11:49:27.145501  4597 caffe.cpp:501] detection_eval = 0.0430616
-I0511 11:49:27.145506  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145509  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145512  4597 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:49:27.145514  4597 caffe.cpp:501] detection_eval = 10.4516
-I0511 11:49:27.145517  4597 caffe.cpp:501] detection_eval = 0.040741
-I0511 11:49:27.145519  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145522  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145524  4597 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:49:27.145526  4597 caffe.cpp:501] detection_eval = 10.5323
-I0511 11:49:27.145529  4597 caffe.cpp:501] detection_eval = 0.0401114
-I0511 11:49:27.145532  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145534  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145536  4597 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:49:27.145539  4597 caffe.cpp:501] detection_eval = 10.6028
-I0511 11:49:27.145542  4597 caffe.cpp:501] detection_eval = 0.0464177
-I0511 11:49:27.145545  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145546  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.145550  4597 caffe.cpp:501] detection_eval = 1.14315
-I0511 11:49:27.145551  4597 caffe.cpp:501] detection_eval = 10.6552
-I0511 11:49:27.145555  4597 caffe.cpp:501] detection_eval = 0.0518352
-I0511 11:49:27.145556  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145560  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145561  4597 caffe.cpp:501] detection_eval = 1.14315
-I0511 11:49:27.145565  4597 caffe.cpp:501] detection_eval = 10.7379
-I0511 11:49:27.145566  4597 caffe.cpp:501] detection_eval = 0.0485364
-I0511 11:49:27.145570  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145571  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145575  4597 caffe.cpp:501] detection_eval = 1.14516
-I0511 11:49:27.145576  4597 caffe.cpp:501] detection_eval = 10.7823
-I0511 11:49:27.145579  4597 caffe.cpp:501] detection_eval = 0.0425106
-I0511 11:49:27.145581  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145584  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145586  4597 caffe.cpp:501] detection_eval = 1.14516
-I0511 11:49:27.145588  4597 caffe.cpp:501] detection_eval = 10.8851
-I0511 11:49:27.145592  4597 caffe.cpp:501] detection_eval = 0.0433279
-I0511 11:49:27.145594  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145597  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.145599  4597 caffe.cpp:501] detection_eval = 1.14718
-I0511 11:49:27.145602  4597 caffe.cpp:501] detection_eval = 10.9294
-I0511 11:49:27.145604  4597 caffe.cpp:501] detection_eval = 0.0416914
-I0511 11:49:27.145607  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145611  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145612  4597 caffe.cpp:501] detection_eval = 1.14919
-I0511 11:49:27.145615  4597 caffe.cpp:501] detection_eval = 11
-I0511 11:49:27.145618  4597 caffe.cpp:501] detection_eval = 0.0450898
-I0511 11:49:27.145620  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145623  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145625  4597 caffe.cpp:501] detection_eval = 1.15121
-I0511 11:49:27.145628  4597 caffe.cpp:501] detection_eval = 11.1048
-I0511 11:49:27.145630  4597 caffe.cpp:501] detection_eval = 0.0448681
-I0511 11:49:27.145633  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145635  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145638  4597 caffe.cpp:501] detection_eval = 1.15121
-I0511 11:49:27.145640  4597 caffe.cpp:501] detection_eval = 11.1915
-I0511 11:49:27.145643  4597 caffe.cpp:501] detection_eval = 0.0498553
-I0511 11:49:27.145645  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145648  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.145650  4597 caffe.cpp:501] detection_eval = 1.15121
-I0511 11:49:27.145653  4597 caffe.cpp:501] detection_eval = 11.2379
-I0511 11:49:27.145658  4597 caffe.cpp:501] detection_eval = 0.0413096
-I0511 11:49:27.145661  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145663  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145666  4597 caffe.cpp:501] detection_eval = 1.15121
-I0511 11:49:27.145669  4597 caffe.cpp:501] detection_eval = 11.3387
-I0511 11:49:27.145671  4597 caffe.cpp:501] detection_eval = 0.0436923
-I0511 11:49:27.145674  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145678  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145679  4597 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:49:27.145682  4597 caffe.cpp:501] detection_eval = 11.3569
-I0511 11:49:27.145684  4597 caffe.cpp:501] detection_eval = 0.0404503
-I0511 11:49:27.145687  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145689  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145691  4597 caffe.cpp:501] detection_eval = 1.15726
-I0511 11:49:27.145694  4597 caffe.cpp:501] detection_eval = 11.3125
-I0511 11:49:27.145696  4597 caffe.cpp:501] detection_eval = 0.042096
-I0511 11:49:27.145699  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145701  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145704  4597 caffe.cpp:501] detection_eval = 1.16129
-I0511 11:49:27.145706  4597 caffe.cpp:501] detection_eval = 11.3024
-I0511 11:49:27.145709  4597 caffe.cpp:501] detection_eval = 0.0446841
-I0511 11:49:27.145711  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145714  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145716  4597 caffe.cpp:501] detection_eval = 1.16331
-I0511 11:49:27.145720  4597 caffe.cpp:501] detection_eval = 11.3387
-I0511 11:49:27.145722  4597 caffe.cpp:501] detection_eval = 0.0416956
-I0511 11:49:27.145725  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145727  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145730  4597 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:49:27.145731  4597 caffe.cpp:501] detection_eval = 11.3851
-I0511 11:49:27.145735  4597 caffe.cpp:501] detection_eval = 0.043156
-I0511 11:49:27.145736  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145738  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145741  4597 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:49:27.145743  4597 caffe.cpp:501] detection_eval = 11.4758
-I0511 11:49:27.145746  4597 caffe.cpp:501] detection_eval = 0.0440364
-I0511 11:49:27.145748  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145750  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145753  4597 caffe.cpp:501] detection_eval = 1.16935
-I0511 11:49:27.145756  4597 caffe.cpp:501] detection_eval = 11.5081
-I0511 11:49:27.145758  4597 caffe.cpp:501] detection_eval = 0.0416945
-I0511 11:49:27.145761  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145763  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.145766  4597 caffe.cpp:501] detection_eval = 1.17339
-I0511 11:49:27.145768  4597 caffe.cpp:501] detection_eval = 11.5282
-I0511 11:49:27.145771  4597 caffe.cpp:501] detection_eval = 0.0406592
-I0511 11:49:27.145774  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145776  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145778  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145781  4597 caffe.cpp:501] detection_eval = 11.5847
-I0511 11:49:27.145783  4597 caffe.cpp:501] detection_eval = 0.041443
-I0511 11:49:27.145787  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145788  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145792  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145793  4597 caffe.cpp:501] detection_eval = 11.6573
-I0511 11:49:27.145797  4597 caffe.cpp:501] detection_eval = 0.0402786
-I0511 11:49:27.145798  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145802  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145803  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145805  4597 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:49:27.145812  4597 caffe.cpp:501] detection_eval = 0.0423552
-I0511 11:49:27.145817  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145819  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145822  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145824  4597 caffe.cpp:501] detection_eval = 11.8145
-I0511 11:49:27.145826  4597 caffe.cpp:501] detection_eval = 0.0458264
-I0511 11:49:27.145829  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145831  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.145834  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145836  4597 caffe.cpp:501] detection_eval = 11.8609
-I0511 11:49:27.145839  4597 caffe.cpp:501] detection_eval = 0.0438705
-I0511 11:49:27.145841  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145843  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145846  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145848  4597 caffe.cpp:501] detection_eval = 11.9577
-I0511 11:49:27.145851  4597 caffe.cpp:501] detection_eval = 0.0431666
-I0511 11:49:27.145853  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145855  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145859  4597 caffe.cpp:501] detection_eval = 1.17944
-I0511 11:49:27.145860  4597 caffe.cpp:501] detection_eval = 11.9738
-I0511 11:49:27.145864  4597 caffe.cpp:501] detection_eval = 0.0449846
-I0511 11:49:27.145865  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145869  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145870  4597 caffe.cpp:501] detection_eval = 1.18145
-I0511 11:49:27.145874  4597 caffe.cpp:501] detection_eval = 12.0323
-I0511 11:49:27.145875  4597 caffe.cpp:501] detection_eval = 0.0450107
-I0511 11:49:27.145879  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145880  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145884  4597 caffe.cpp:501] detection_eval = 1.18145
-I0511 11:49:27.145885  4597 caffe.cpp:501] detection_eval = 12.119
-I0511 11:49:27.145889  4597 caffe.cpp:501] detection_eval = 0.0485021
-I0511 11:49:27.145890  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145893  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145895  4597 caffe.cpp:501] detection_eval = 1.18145
-I0511 11:49:27.145897  4597 caffe.cpp:501] detection_eval = 12.1774
-I0511 11:49:27.145900  4597 caffe.cpp:501] detection_eval = 0.0465926
-I0511 11:49:27.145902  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145905  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.145907  4597 caffe.cpp:501] detection_eval = 1.18347
-I0511 11:49:27.145910  4597 caffe.cpp:501] detection_eval = 12.244
-I0511 11:49:27.145912  4597 caffe.cpp:501] detection_eval = 0.0446817
-I0511 11:49:27.145915  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145917  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145920  4597 caffe.cpp:501] detection_eval = 1.18548
-I0511 11:49:27.145922  4597 caffe.cpp:501] detection_eval = 12.3206
-I0511 11:49:27.145925  4597 caffe.cpp:501] detection_eval = 0.0488514
-I0511 11:49:27.145926  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145929  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145931  4597 caffe.cpp:501] detection_eval = 1.1875
-I0511 11:49:27.145934  4597 caffe.cpp:501] detection_eval = 12.3589
-I0511 11:49:27.145936  4597 caffe.cpp:501] detection_eval = 0.0448765
-I0511 11:49:27.145939  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145941  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145944  4597 caffe.cpp:501] detection_eval = 1.18952
-I0511 11:49:27.145946  4597 caffe.cpp:501] detection_eval = 12.3972
-I0511 11:49:27.145951  4597 caffe.cpp:501] detection_eval = 0.0514622
-I0511 11:49:27.145952  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.145956  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.145957  4597 caffe.cpp:501] detection_eval = 1.19355
-I0511 11:49:27.145962  4597 caffe.cpp:501] detection_eval = 12.4032
-I0511 11:49:27.145965  4597 caffe.cpp:501] detection_eval = 0.0471194
-I0511 11:49:27.145968  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145970  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145973  4597 caffe.cpp:501] detection_eval = 1.19556
-I0511 11:49:27.145975  4597 caffe.cpp:501] detection_eval = 12.4335
-I0511 11:49:27.145978  4597 caffe.cpp:501] detection_eval = 0.0434861
-I0511 11:49:27.145980  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145983  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145985  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.145988  4597 caffe.cpp:501] detection_eval = 12.4395
-I0511 11:49:27.145990  4597 caffe.cpp:501] detection_eval = 0.0407979
-I0511 11:49:27.145993  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145995  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145998  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.146000  4597 caffe.cpp:501] detection_eval = 12.498
-I0511 11:49:27.146003  4597 caffe.cpp:501] detection_eval = 0.0435581
-I0511 11:49:27.146005  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.146008  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.146010  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.146013  4597 caffe.cpp:501] detection_eval = 12.5827
-I0511 11:49:27.146016  4597 caffe.cpp:501] detection_eval = 0.0457352
-I0511 11:49:27.146018  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146021  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146023  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.146025  4597 caffe.cpp:501] detection_eval = 12.6613
-I0511 11:49:27.146028  4597 caffe.cpp:501] detection_eval = 0.0438167
-I0511 11:49:27.146030  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146034  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146035  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.146039  4597 caffe.cpp:501] detection_eval = 12.7238
-I0511 11:49:27.146040  4597 caffe.cpp:501] detection_eval = 0.0418078
-I0511 11:49:27.146042  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146045  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146047  4597 caffe.cpp:501] detection_eval = 1.20766
-I0511 11:49:27.146050  4597 caffe.cpp:501] detection_eval = 12.6895
-I0511 11:49:27.146052  4597 caffe.cpp:501] detection_eval = 0.0447596
-I0511 11:49:27.146055  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146057  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146060  4597 caffe.cpp:501] detection_eval = 1.20766
-I0511 11:49:27.146062  4597 caffe.cpp:501] detection_eval = 12.756
-I0511 11:49:27.146065  4597 caffe.cpp:501] detection_eval = 0.0435381
-I0511 11:49:27.146067  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146070  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146072  4597 caffe.cpp:501] detection_eval = 1.20968
-I0511 11:49:27.146075  4597 caffe.cpp:501] detection_eval = 12.7802
-I0511 11:49:27.146077  4597 caffe.cpp:501] detection_eval = 0.0456512
-I0511 11:49:27.146080  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146081  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146085  4597 caffe.cpp:501] detection_eval = 1.21169
-I0511 11:49:27.146086  4597 caffe.cpp:501] detection_eval = 12.8266
-I0511 11:49:27.146090  4597 caffe.cpp:501] detection_eval = 0.0449135
-I0511 11:49:27.146092  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.146095  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.146097  4597 caffe.cpp:501] detection_eval = 1.21573
-I0511 11:49:27.146100  4597 caffe.cpp:501] detection_eval = 12.8347
-I0511 11:49:27.146102  4597 caffe.cpp:501] detection_eval = 0.04379
-I0511 11:49:27.146106  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146107  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146111  4597 caffe.cpp:501] detection_eval = 1.21573
-I0511 11:49:27.146116  4597 caffe.cpp:501] detection_eval = 12.9073
-I0511 11:49:27.146118  4597 caffe.cpp:501] detection_eval = 0.0412596
-I0511 11:49:27.146121  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146123  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146126  4597 caffe.cpp:501] detection_eval = 1.22177
-I0511 11:49:27.146128  4597 caffe.cpp:501] detection_eval = 12.8831
-I0511 11:49:27.146131  4597 caffe.cpp:501] detection_eval = 0.0390567
-I0511 11:49:27.146133  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146136  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146138  4597 caffe.cpp:501] detection_eval = 1.22581
-I0511 11:49:27.146142  4597 caffe.cpp:501] detection_eval = 12.875
-I0511 11:49:27.146143  4597 caffe.cpp:501] detection_eval = 0.0453133
-I0511 11:49:27.146147  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146148  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146152  4597 caffe.cpp:501] detection_eval = 1.23185
-I0511 11:49:27.146153  4597 caffe.cpp:501] detection_eval = 12.8468
-I0511 11:49:27.146157  4597 caffe.cpp:501] detection_eval = 0.041157
-I0511 11:49:27.146158  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146162  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146163  4597 caffe.cpp:501] detection_eval = 1.23387
-I0511 11:49:27.146167  4597 caffe.cpp:501] detection_eval = 12.877
-I0511 11:49:27.146169  4597 caffe.cpp:501] detection_eval = 0.0393585
-I0511 11:49:27.146172  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146173  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146176  4597 caffe.cpp:501] detection_eval = 1.23589
-I0511 11:49:27.146178  4597 caffe.cpp:501] detection_eval = 12.9315
-I0511 11:49:27.146181  4597 caffe.cpp:501] detection_eval = 0.0382644
-I0511 11:49:27.146184  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146186  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146189  4597 caffe.cpp:501] detection_eval = 1.23589
-I0511 11:49:27.146193  4597 caffe.cpp:501] detection_eval = 12.9738
-I0511 11:49:27.146194  4597 caffe.cpp:501] detection_eval = 0.0372697
-I0511 11:49:27.146198  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146199  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146201  4597 caffe.cpp:501] detection_eval = 1.23589
-I0511 11:49:27.146204  4597 caffe.cpp:501] detection_eval = 13.0645
-I0511 11:49:27.146206  4597 caffe.cpp:501] detection_eval = 0.0392381
-I0511 11:49:27.146209  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146211  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146214  4597 caffe.cpp:501] detection_eval = 1.23992
-I0511 11:49:27.146216  4597 caffe.cpp:501] detection_eval = 13.0706
-I0511 11:49:27.146219  4597 caffe.cpp:501] detection_eval = 0.0395565
-I0511 11:49:27.146221  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146224  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146226  4597 caffe.cpp:501] detection_eval = 1.24395
-I0511 11:49:27.146229  4597 caffe.cpp:501] detection_eval = 13.0484
-I0511 11:49:27.146231  4597 caffe.cpp:501] detection_eval = 0.0409841
-I0511 11:49:27.146234  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146236  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146239  4597 caffe.cpp:501] detection_eval = 1.24597
-I0511 11:49:27.146241  4597 caffe.cpp:501] detection_eval = 13.0927
-I0511 11:49:27.146245  4597 caffe.cpp:501] detection_eval = 0.0409264
-I0511 11:49:27.146246  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.146250  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.146251  4597 caffe.cpp:501] detection_eval = 1.24597
-I0511 11:49:27.146255  4597 caffe.cpp:501] detection_eval = 13.1613
-I0511 11:49:27.146257  4597 caffe.cpp:501] detection_eval = 0.0407683
-I0511 11:49:27.146260  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146262  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146267  4597 caffe.cpp:501] detection_eval = 1.25
-I0511 11:49:27.146270  4597 caffe.cpp:501] detection_eval = 13.1532
-I0511 11:49:27.146272  4597 caffe.cpp:501] detection_eval = 0.0435359
-I0511 11:49:27.146275  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.146277  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.146281  4597 caffe.cpp:501] detection_eval = 1.25202
-I0511 11:49:27.146282  4597 caffe.cpp:501] detection_eval = 13.1714
-I0511 11:49:27.146286  4597 caffe.cpp:501] detection_eval = 0.0407399
-I0511 11:49:27.146287  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146291  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146292  4597 caffe.cpp:501] detection_eval = 1.25202
-I0511 11:49:27.146294  4597 caffe.cpp:501] detection_eval = 13.2077
-I0511 11:49:27.146297  4597 caffe.cpp:501] detection_eval = 0.0377397
-I0511 11:49:27.146301  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146302  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146304  4597 caffe.cpp:501] detection_eval = 1.25202
-I0511 11:49:27.146307  4597 caffe.cpp:501] detection_eval = 13.2641
-I0511 11:49:27.146309  4597 caffe.cpp:501] detection_eval = 0.0362508
-I0511 11:49:27.146312  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146314  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146317  4597 caffe.cpp:501] detection_eval = 1.25605
-I0511 11:49:27.146319  4597 caffe.cpp:501] detection_eval = 13.2984
-I0511 11:49:27.146322  4597 caffe.cpp:501] detection_eval = 0.0408606
-I0511 11:49:27.146324  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146327  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146329  4597 caffe.cpp:501] detection_eval = 1.25806
-I0511 11:49:27.146332  4597 caffe.cpp:501] detection_eval = 13.3004
-I0511 11:49:27.146335  4597 caffe.cpp:501] detection_eval = 0.0369961
-I0511 11:49:27.146337  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146340  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146342  4597 caffe.cpp:501] detection_eval = 1.25806
-I0511 11:49:27.146345  4597 caffe.cpp:501] detection_eval = 13.3427
-I0511 11:49:27.146348  4597 caffe.cpp:501] detection_eval = 0.0363474
-I0511 11:49:27.146350  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146353  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146356  4597 caffe.cpp:501] detection_eval = 1.25806
-I0511 11:49:27.146358  4597 caffe.cpp:501] detection_eval = 13.3911
-I0511 11:49:27.146361  4597 caffe.cpp:501] detection_eval = 0.0379257
-I0511 11:49:27.146363  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146366  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146368  4597 caffe.cpp:501] detection_eval = 1.2621
-I0511 11:49:27.146371  4597 caffe.cpp:501] detection_eval = 13.377
-I0511 11:49:27.146374  4597 caffe.cpp:501] detection_eval = 0.0377221
-I0511 11:49:27.146376  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146378  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146381  4597 caffe.cpp:501] detection_eval = 1.26613
-I0511 11:49:27.146384  4597 caffe.cpp:501] detection_eval = 13.375
-I0511 11:49:27.146385  4597 caffe.cpp:501] detection_eval = 0.0383149
-I0511 11:49:27.146387  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146390  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146392  4597 caffe.cpp:501] detection_eval = 1.26613
-I0511 11:49:27.146395  4597 caffe.cpp:501] detection_eval = 13.4355
-I0511 11:49:27.146397  4597 caffe.cpp:501] detection_eval = 0.040566
-I0511 11:49:27.146400  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146402  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146405  4597 caffe.cpp:501] detection_eval = 1.26613
-I0511 11:49:27.146407  4597 caffe.cpp:501] detection_eval = 13.4637
-I0511 11:49:27.146410  4597 caffe.cpp:501] detection_eval = 0.0353715
-I0511 11:49:27.146412  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146417  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146420  4597 caffe.cpp:501] detection_eval = 1.26815
-I0511 11:49:27.146423  4597 caffe.cpp:501] detection_eval = 13.4758
-I0511 11:49:27.146425  4597 caffe.cpp:501] detection_eval = 0.0362634
-I0511 11:49:27.146428  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146430  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146432  4597 caffe.cpp:501] detection_eval = 1.26815
-I0511 11:49:27.146435  4597 caffe.cpp:501] detection_eval = 13.5101
-I0511 11:49:27.146438  4597 caffe.cpp:501] detection_eval = 0.0366599
-I0511 11:49:27.146440  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146442  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146445  4597 caffe.cpp:501] detection_eval = 1.27218
-I0511 11:49:27.146447  4597 caffe.cpp:501] detection_eval = 13.5101
-I0511 11:49:27.146450  4597 caffe.cpp:501] detection_eval = 0.0381063
-I0511 11:49:27.146452  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146455  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146456  4597 caffe.cpp:501] detection_eval = 1.27823
-I0511 11:49:27.146459  4597 caffe.cpp:501] detection_eval = 13.4637
-I0511 11:49:27.146462  4597 caffe.cpp:501] detection_eval = 0.0346172
-I0511 11:49:27.146464  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146467  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146469  4597 caffe.cpp:501] detection_eval = 1.28226
-I0511 11:49:27.146472  4597 caffe.cpp:501] detection_eval = 13.4456
-I0511 11:49:27.146476  4597 caffe.cpp:501] detection_eval = 0.0336624
-I0511 11:49:27.146477  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146481  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146482  4597 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:49:27.146486  4597 caffe.cpp:501] detection_eval = 13.4194
-I0511 11:49:27.146488  4597 caffe.cpp:501] detection_eval = 0.0336696
-I0511 11:49:27.146490  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146493  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146495  4597 caffe.cpp:501] detection_eval = 1.28831
-I0511 11:49:27.146498  4597 caffe.cpp:501] detection_eval = 13.4375
-I0511 11:49:27.146500  4597 caffe.cpp:501] detection_eval = 0.037632
-I0511 11:49:27.146503  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146505  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146508  4597 caffe.cpp:501] detection_eval = 1.29032
-I0511 11:49:27.146510  4597 caffe.cpp:501] detection_eval = 13.4355
-I0511 11:49:27.146513  4597 caffe.cpp:501] detection_eval = 0.0397644
-I0511 11:49:27.146515  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146517  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146520  4597 caffe.cpp:501] detection_eval = 1.29032
-I0511 11:49:27.146522  4597 caffe.cpp:501] detection_eval = 13.4839
-I0511 11:49:27.146525  4597 caffe.cpp:501] detection_eval = 0.0340828
-I0511 11:49:27.146528  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146530  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146533  4597 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:49:27.146534  4597 caffe.cpp:501] detection_eval = 13.4899
-I0511 11:49:27.146538  4597 caffe.cpp:501] detection_eval = 0.0370037
-I0511 11:49:27.146540  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146543  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146545  4597 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:49:27.146548  4597 caffe.cpp:501] detection_eval = 13.5141
-I0511 11:49:27.146550  4597 caffe.cpp:501] detection_eval = 0.0316733
-I0511 11:49:27.146553  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.146556  4597 caffe.cpp:501] detection_eval = 1
-I0511 11:49:27.146559  4597 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:49:27.146561  4597 caffe.cpp:501] detection_eval = 13.5827
-I0511 11:49:27.146564  4597 caffe.cpp:501] detection_eval = 0.035012
-I0511 11:49:27.146566  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146572  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146575  4597 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:49:27.146577  4597 caffe.cpp:501] detection_eval = 13.6149
-I0511 11:49:27.146580  4597 caffe.cpp:501] detection_eval = 0.0362268
-I0511 11:49:27.146582  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146585  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146587  4597 caffe.cpp:501] detection_eval = 1.29637
-I0511 11:49:27.146589  4597 caffe.cpp:501] detection_eval = 13.5968
-I0511 11:49:27.146594  4597 caffe.cpp:501] detection_eval = 0.032313
-I0511 11:49:27.146595  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146598  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146600  4597 caffe.cpp:501] detection_eval = 1.29637
-I0511 11:49:27.146602  4597 caffe.cpp:501] detection_eval = 13.6532
-I0511 11:49:27.146606  4597 caffe.cpp:501] detection_eval = 0.0374724
-I0511 11:49:27.146608  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146611  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146613  4597 caffe.cpp:501] detection_eval = 1.29839
-I0511 11:49:27.146615  4597 caffe.cpp:501] detection_eval = 13.6835
-I0511 11:49:27.146620  4597 caffe.cpp:501] detection_eval = 0.0350892
-I0511 11:49:27.146622  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146625  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146626  4597 caffe.cpp:501] detection_eval = 1.30242
-I0511 11:49:27.146630  4597 caffe.cpp:501] detection_eval = 13.6552
-I0511 11:49:27.146631  4597 caffe.cpp:501] detection_eval = 0.0345291
-I0511 11:49:27.146634  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146636  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146639  4597 caffe.cpp:501] detection_eval = 1.30645
-I0511 11:49:27.146641  4597 caffe.cpp:501] detection_eval = 13.6512
-I0511 11:49:27.146646  4597 caffe.cpp:501] detection_eval = 0.0392117
-I0511 11:49:27.146647  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146649  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146652  4597 caffe.cpp:501] detection_eval = 1.30847
-I0511 11:49:27.146654  4597 caffe.cpp:501] detection_eval = 13.6694
-I0511 11:49:27.146657  4597 caffe.cpp:501] detection_eval = 0.0382653
-I0511 11:49:27.146661  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146662  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146664  4597 caffe.cpp:501] detection_eval = 1.30847
-I0511 11:49:27.146667  4597 caffe.cpp:501] detection_eval = 13.7198
-I0511 11:49:27.146669  4597 caffe.cpp:501] detection_eval = 0.0359233
-I0511 11:49:27.146672  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146674  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146677  4597 caffe.cpp:501] detection_eval = 1.3125
-I0511 11:49:27.146679  4597 caffe.cpp:501] detection_eval = 13.7077
-I0511 11:49:27.146683  4597 caffe.cpp:501] detection_eval = 0.035042
-I0511 11:49:27.146685  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146687  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146690  4597 caffe.cpp:501] detection_eval = 1.31653
-I0511 11:49:27.146692  4597 caffe.cpp:501] detection_eval = 13.6915
-I0511 11:49:27.146694  4597 caffe.cpp:501] detection_eval = 0.0348875
-I0511 11:49:27.146697  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.146699  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.146703  4597 caffe.cpp:501] detection_eval = 1.31855
-I0511 11:49:27.146704  4597 caffe.cpp:501] detection_eval = 13.7198
-I0511 11:49:27.146708  4597 caffe.cpp:501] detection_eval = 0.0367038
-I0511 11:49:27.146709  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146713  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146714  4597 caffe.cpp:501] detection_eval = 1.32661
-I0511 11:49:27.146716  4597 caffe.cpp:501] detection_eval = 13.6552
-I0511 11:49:27.146719  4597 caffe.cpp:501] detection_eval = 0.0385572
-I0511 11:49:27.146724  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146728  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146730  4597 caffe.cpp:501] detection_eval = 1.32661
-I0511 11:49:27.146733  4597 caffe.cpp:501] detection_eval = 13.7419
-I0511 11:49:27.146736  4597 caffe.cpp:501] detection_eval = 0.0396626
-I0511 11:49:27.146739  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146741  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146744  4597 caffe.cpp:501] detection_eval = 1.33266
-I0511 11:49:27.146746  4597 caffe.cpp:501] detection_eval = 13.7641
-I0511 11:49:27.146749  4597 caffe.cpp:501] detection_eval = 0.0398071
-I0511 11:49:27.146752  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146754  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146757  4597 caffe.cpp:501] detection_eval = 1.33468
-I0511 11:49:27.146759  4597 caffe.cpp:501] detection_eval = 13.7964
-I0511 11:49:27.146764  4597 caffe.cpp:501] detection_eval = 0.0363419
-I0511 11:49:27.146765  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146767  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146770  4597 caffe.cpp:501] detection_eval = 1.33871
-I0511 11:49:27.146773  4597 caffe.cpp:501] detection_eval = 13.8387
-I0511 11:49:27.146775  4597 caffe.cpp:501] detection_eval = 0.0390332
-I0511 11:49:27.146778  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146781  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146785  4597 caffe.cpp:501] detection_eval = 1.34274
-I0511 11:49:27.146786  4597 caffe.cpp:501] detection_eval = 13.8427
-I0511 11:49:27.146790  4597 caffe.cpp:501] detection_eval = 0.0365928
-I0511 11:49:27.146792  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146795  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146797  4597 caffe.cpp:501] detection_eval = 1.34476
-I0511 11:49:27.146800  4597 caffe.cpp:501] detection_eval = 13.9173
-I0511 11:49:27.146802  4597 caffe.cpp:501] detection_eval = 0.035152
-I0511 11:49:27.146806  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146808  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146811  4597 caffe.cpp:501] detection_eval = 1.34677
-I0511 11:49:27.146812  4597 caffe.cpp:501] detection_eval = 14.002
-I0511 11:49:27.146816  4597 caffe.cpp:501] detection_eval = 0.0362133
-I0511 11:49:27.146819  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146822  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146824  4597 caffe.cpp:501] detection_eval = 1.34677
-I0511 11:49:27.146827  4597 caffe.cpp:501] detection_eval = 14.0907
-I0511 11:49:27.146831  4597 caffe.cpp:501] detection_eval = 0.0410121
-I0511 11:49:27.146832  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146836  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146837  4597 caffe.cpp:501] detection_eval = 1.34677
-I0511 11:49:27.146841  4597 caffe.cpp:501] detection_eval = 14.2258
-I0511 11:49:27.146842  4597 caffe.cpp:501] detection_eval = 0.0446848
-I0511 11:49:27.146845  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146847  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146849  4597 caffe.cpp:501] detection_eval = 1.34879
-I0511 11:49:27.146852  4597 caffe.cpp:501] detection_eval = 14.2621
-I0511 11:49:27.146854  4597 caffe.cpp:501] detection_eval = 0.0358699
-I0511 11:49:27.146857  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146860  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146863  4597 caffe.cpp:501] detection_eval = 1.3629
-I0511 11:49:27.146865  4597 caffe.cpp:501] detection_eval = 14.1754
-I0511 11:49:27.146868  4597 caffe.cpp:501] detection_eval = 0.0348599
-I0511 11:49:27.146870  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146873  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146875  4597 caffe.cpp:501] detection_eval = 1.3629
-I0511 11:49:27.146878  4597 caffe.cpp:501] detection_eval = 14.2581
-I0511 11:49:27.146880  4597 caffe.cpp:501] detection_eval = 0.0377557
-I0511 11:49:27.146886  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146889  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146893  4597 caffe.cpp:501] detection_eval = 1.36492
-I0511 11:49:27.146894  4597 caffe.cpp:501] detection_eval = 14.3468
-I0511 11:49:27.146898  4597 caffe.cpp:501] detection_eval = 0.035452
-I0511 11:49:27.146899  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146901  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146903  4597 caffe.cpp:501] detection_eval = 1.36694
-I0511 11:49:27.146906  4597 caffe.cpp:501] detection_eval = 14.4718
-I0511 11:49:27.146908  4597 caffe.cpp:501] detection_eval = 0.0382334
-I0511 11:49:27.146910  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146914  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146915  4597 caffe.cpp:501] detection_eval = 1.37097
-I0511 11:49:27.146917  4597 caffe.cpp:501] detection_eval = 14.5948
-I0511 11:49:27.146920  4597 caffe.cpp:501] detection_eval = 0.0380794
-I0511 11:49:27.146922  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146925  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146927  4597 caffe.cpp:501] detection_eval = 1.37097
-I0511 11:49:27.146929  4597 caffe.cpp:501] detection_eval = 14.9194
-I0511 11:49:27.146932  4597 caffe.cpp:501] detection_eval = 0.0322236
-I0511 11:49:27.146934  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146936  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146939  4597 caffe.cpp:501] detection_eval = 1.37298
-I0511 11:49:27.146941  4597 caffe.cpp:501] detection_eval = 15.2298
-I0511 11:49:27.146944  4597 caffe.cpp:501] detection_eval = 0.0331973
-I0511 11:49:27.146946  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146948  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146950  4597 caffe.cpp:501] detection_eval = 2.04234
-I0511 11:49:27.146953  4597 caffe.cpp:501] detection_eval = 5.3004
-I0511 11:49:27.146956  4597 caffe.cpp:501] detection_eval = 0.133413
-I0511 11:49:27.146960  4597 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:49:27.146962  4597 caffe.cpp:501] detection_eval = 0.885081
-I0511 11:49:27.146965  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.146968  4597 caffe.cpp:501] detection_eval = 5.52218
-I0511 11:49:27.146970  4597 caffe.cpp:501] detection_eval = 0.0676833
-I0511 11:49:27.146973  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.146976  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.146978  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.146981  4597 caffe.cpp:501] detection_eval = 5.72581
-I0511 11:49:27.146983  4597 caffe.cpp:501] detection_eval = 0.0587982
-I0511 11:49:27.146986  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.146988  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.146991  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.146992  4597 caffe.cpp:501] detection_eval = 5.90524
-I0511 11:49:27.146996  4597 caffe.cpp:501] detection_eval = 0.0458608
-I0511 11:49:27.146998  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147001  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.147002  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.147006  4597 caffe.cpp:501] detection_eval = 6.05444
-I0511 11:49:27.147007  4597 caffe.cpp:501] detection_eval = 0.0518086
-I0511 11:49:27.147011  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.147012  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147014  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.147017  4597 caffe.cpp:501] detection_eval = 6.18347
-I0511 11:49:27.147019  4597 caffe.cpp:501] detection_eval = 0.0473676
-I0511 11:49:27.147022  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.147024  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147027  4597 caffe.cpp:501] detection_eval = 2.04839
-I0511 11:49:27.147029  4597 caffe.cpp:501] detection_eval = 6.21976
-I0511 11:49:27.147035  4597 caffe.cpp:501] detection_eval = 0.0447459
-I0511 11:49:27.147037  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.147040  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.147042  4597 caffe.cpp:501] detection_eval = 2.05242
-I0511 11:49:27.147045  4597 caffe.cpp:501] detection_eval = 6.21774
-I0511 11:49:27.147047  4597 caffe.cpp:501] detection_eval = 0.0400823
-I0511 11:49:27.147050  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147053  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147055  4597 caffe.cpp:501] detection_eval = 2.05645
-I0511 11:49:27.147058  4597 caffe.cpp:501] detection_eval = 6.22581
-I0511 11:49:27.147060  4597 caffe.cpp:501] detection_eval = 0.0409995
-I0511 11:49:27.147063  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147065  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.147068  4597 caffe.cpp:501] detection_eval = 2.05645
-I0511 11:49:27.147070  4597 caffe.cpp:501] detection_eval = 6.30444
-I0511 11:49:27.147073  4597 caffe.cpp:501] detection_eval = 0.0415906
-I0511 11:49:27.147075  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147078  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147079  4597 caffe.cpp:501] detection_eval = 2.05645
-I0511 11:49:27.147083  4597 caffe.cpp:501] detection_eval = 6.41935
-I0511 11:49:27.147085  4597 caffe.cpp:501] detection_eval = 0.0442366
-I0511 11:49:27.147087  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147090  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147092  4597 caffe.cpp:501] detection_eval = 2.06048
-I0511 11:49:27.147095  4597 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:49:27.147097  4597 caffe.cpp:501] detection_eval = 0.0427659
-I0511 11:49:27.147099  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.147102  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147104  4597 caffe.cpp:501] detection_eval = 2.06048
-I0511 11:49:27.147107  4597 caffe.cpp:501] detection_eval = 6.58669
-I0511 11:49:27.147109  4597 caffe.cpp:501] detection_eval = 0.0390561
-I0511 11:49:27.147111  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.147114  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147116  4597 caffe.cpp:501] detection_eval = 2.0625
-I0511 11:49:27.147119  4597 caffe.cpp:501] detection_eval = 6.63306
-I0511 11:49:27.147122  4597 caffe.cpp:501] detection_eval = 0.0400544
-I0511 11:49:27.147125  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147130  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147135  4597 caffe.cpp:501] detection_eval = 2.06452
-I0511 11:49:27.147138  4597 caffe.cpp:501] detection_eval = 6.64315
-I0511 11:49:27.147143  4597 caffe.cpp:501] detection_eval = 0.0356438
-I0511 11:49:27.147147  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.147152  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147156  4597 caffe.cpp:501] detection_eval = 2.06653
-I0511 11:49:27.147161  4597 caffe.cpp:501] detection_eval = 6.67742
-I0511 11:49:27.147166  4597 caffe.cpp:501] detection_eval = 0.0377647
-I0511 11:49:27.147171  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147174  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147179  4597 caffe.cpp:501] detection_eval = 2.07056
-I0511 11:49:27.147184  4597 caffe.cpp:501] detection_eval = 6.71573
-I0511 11:49:27.147188  4597 caffe.cpp:501] detection_eval = 0.041873
-I0511 11:49:27.147193  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147197  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147202  4597 caffe.cpp:501] detection_eval = 2.07056
-I0511 11:49:27.147207  4597 caffe.cpp:501] detection_eval = 6.78831
-I0511 11:49:27.147212  4597 caffe.cpp:501] detection_eval = 0.0421586
-I0511 11:49:27.147215  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147220  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147225  4597 caffe.cpp:501] detection_eval = 2.0746
-I0511 11:49:27.147233  4597 caffe.cpp:501] detection_eval = 6.84073
-I0511 11:49:27.147238  4597 caffe.cpp:501] detection_eval = 0.0416998
-I0511 11:49:27.147243  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147246  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.147250  4597 caffe.cpp:501] detection_eval = 2.0746
-I0511 11:49:27.147254  4597 caffe.cpp:501] detection_eval = 6.95565
-I0511 11:49:27.147258  4597 caffe.cpp:501] detection_eval = 0.047217
-I0511 11:49:27.147263  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.147266  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.147271  4597 caffe.cpp:501] detection_eval = 2.07661
-I0511 11:49:27.147275  4597 caffe.cpp:501] detection_eval = 7.06048
-I0511 11:49:27.147279  4597 caffe.cpp:501] detection_eval = 0.0413395
-I0511 11:49:27.147282  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147286  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147290  4597 caffe.cpp:501] detection_eval = 2.07661
-I0511 11:49:27.147294  4597 caffe.cpp:501] detection_eval = 7.13306
-I0511 11:49:27.147297  4597 caffe.cpp:501] detection_eval = 0.0413058
-I0511 11:49:27.147302  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147305  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147310  4597 caffe.cpp:501] detection_eval = 2.07863
-I0511 11:49:27.147313  4597 caffe.cpp:501] detection_eval = 7.16734
-I0511 11:49:27.147317  4597 caffe.cpp:501] detection_eval = 0.0348343
-I0511 11:49:27.147321  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.147325  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.147328  4597 caffe.cpp:501] detection_eval = 2.08871
-I0511 11:49:27.147332  4597 caffe.cpp:501] detection_eval = 7.1371
-I0511 11:49:27.147336  4597 caffe.cpp:501] detection_eval = 0.0393197
-I0511 11:49:27.147339  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147343  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147348  4597 caffe.cpp:501] detection_eval = 2.09073
-I0511 11:49:27.147351  4597 caffe.cpp:501] detection_eval = 7.17944
-I0511 11:49:27.147356  4597 caffe.cpp:501] detection_eval = 0.0418969
-I0511 11:49:27.147359  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147363  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147367  4597 caffe.cpp:501] detection_eval = 2.09073
-I0511 11:49:27.147372  4597 caffe.cpp:501] detection_eval = 7.25806
-I0511 11:49:27.147374  4597 caffe.cpp:501] detection_eval = 0.0447404
-I0511 11:49:27.147378  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147382  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147387  4597 caffe.cpp:501] detection_eval = 2.09677
-I0511 11:49:27.147390  4597 caffe.cpp:501] detection_eval = 7.26008
-I0511 11:49:27.147394  4597 caffe.cpp:501] detection_eval = 0.0433293
-I0511 11:49:27.147397  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147402  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147405  4597 caffe.cpp:501] detection_eval = 2.10081
-I0511 11:49:27.147409  4597 caffe.cpp:501] detection_eval = 7.26815
-I0511 11:49:27.147413  4597 caffe.cpp:501] detection_eval = 0.0421945
-I0511 11:49:27.147418  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147421  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147425  4597 caffe.cpp:501] detection_eval = 2.10282
-I0511 11:49:27.147429  4597 caffe.cpp:501] detection_eval = 7.33065
-I0511 11:49:27.147433  4597 caffe.cpp:501] detection_eval = 0.0455296
-I0511 11:49:27.147438  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147442  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147446  4597 caffe.cpp:501] detection_eval = 2.10282
-I0511 11:49:27.147450  4597 caffe.cpp:501] detection_eval = 7.42137
-I0511 11:49:27.147454  4597 caffe.cpp:501] detection_eval = 0.0425508
-I0511 11:49:27.147457  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147460  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147464  4597 caffe.cpp:501] detection_eval = 2.10282
-I0511 11:49:27.147476  4597 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:49:27.147480  4597 caffe.cpp:501] detection_eval = 0.0372372
-I0511 11:49:27.147485  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147487  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.147490  4597 caffe.cpp:501] detection_eval = 2.10685
-I0511 11:49:27.147495  4597 caffe.cpp:501] detection_eval = 7.52016
-I0511 11:49:27.147498  4597 caffe.cpp:501] detection_eval = 0.0412541
-I0511 11:49:27.147502  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147506  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147511  4597 caffe.cpp:501] detection_eval = 2.10887
-I0511 11:49:27.147514  4597 caffe.cpp:501] detection_eval = 7.57863
-I0511 11:49:27.147519  4597 caffe.cpp:501] detection_eval = 0.0397699
-I0511 11:49:27.147523  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147528  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147533  4597 caffe.cpp:501] detection_eval = 2.10887
-I0511 11:49:27.147537  4597 caffe.cpp:501] detection_eval = 7.625
-I0511 11:49:27.147542  4597 caffe.cpp:501] detection_eval = 0.0385895
-I0511 11:49:27.147547  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.147552  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.147555  4597 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:49:27.147560  4597 caffe.cpp:501] detection_eval = 7.64919
-I0511 11:49:27.147565  4597 caffe.cpp:501] detection_eval = 0.041084
-I0511 11:49:27.147569  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147573  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.147578  4597 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:49:27.147583  4597 caffe.cpp:501] detection_eval = 7.75
-I0511 11:49:27.147588  4597 caffe.cpp:501] detection_eval = 0.0403033
-I0511 11:49:27.147593  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147596  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.147601  4597 caffe.cpp:501] detection_eval = 2.1129
-I0511 11:49:27.147605  4597 caffe.cpp:501] detection_eval = 7.77823
-I0511 11:49:27.147610  4597 caffe.cpp:501] detection_eval = 0.0425358
-I0511 11:49:27.147614  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147619  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.147624  4597 caffe.cpp:501] detection_eval = 2.11694
-I0511 11:49:27.147629  4597 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:49:27.147632  4597 caffe.cpp:501] detection_eval = 0.0427766
-I0511 11:49:27.147637  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147641  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147646  4597 caffe.cpp:501] detection_eval = 2.11895
-I0511 11:49:27.147650  4597 caffe.cpp:501] detection_eval = 7.83065
-I0511 11:49:27.147667  4597 caffe.cpp:501] detection_eval = 0.0400002
-I0511 11:49:27.147680  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147688  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147697  4597 caffe.cpp:501] detection_eval = 2.11895
-I0511 11:49:27.147708  4597 caffe.cpp:501] detection_eval = 7.89919
-I0511 11:49:27.147713  4597 caffe.cpp:501] detection_eval = 0.0405098
-I0511 11:49:27.147718  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147723  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147727  4597 caffe.cpp:501] detection_eval = 2.11895
-I0511 11:49:27.147732  4597 caffe.cpp:501] detection_eval = 7.97177
-I0511 11:49:27.147737  4597 caffe.cpp:501] detection_eval = 0.0406517
-I0511 11:49:27.147742  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147747  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147750  4597 caffe.cpp:501] detection_eval = 2.12298
-I0511 11:49:27.147755  4597 caffe.cpp:501] detection_eval = 8.02016
-I0511 11:49:27.147760  4597 caffe.cpp:501] detection_eval = 0.0412307
-I0511 11:49:27.147764  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147769  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147780  4597 caffe.cpp:501] detection_eval = 2.125
-I0511 11:49:27.147785  4597 caffe.cpp:501] detection_eval = 8.08468
-I0511 11:49:27.147790  4597 caffe.cpp:501] detection_eval = 0.0389765
-I0511 11:49:27.147795  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147799  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147804  4597 caffe.cpp:501] detection_eval = 2.12903
-I0511 11:49:27.147809  4597 caffe.cpp:501] detection_eval = 8.14718
-I0511 11:49:27.147814  4597 caffe.cpp:501] detection_eval = 0.035977
-I0511 11:49:27.147817  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.147822  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.147827  4597 caffe.cpp:501] detection_eval = 2.13105
-I0511 11:49:27.147831  4597 caffe.cpp:501] detection_eval = 8.19355
-I0511 11:49:27.147835  4597 caffe.cpp:501] detection_eval = 0.039489
-I0511 11:49:27.147840  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147845  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147850  4597 caffe.cpp:501] detection_eval = 2.13105
-I0511 11:49:27.147855  4597 caffe.cpp:501] detection_eval = 8.28629
-I0511 11:49:27.147859  4597 caffe.cpp:501] detection_eval = 0.0397669
-I0511 11:49:27.147863  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147868  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147873  4597 caffe.cpp:501] detection_eval = 2.13306
-I0511 11:49:27.147877  4597 caffe.cpp:501] detection_eval = 8.34476
-I0511 11:49:27.147882  4597 caffe.cpp:501] detection_eval = 0.0432779
-I0511 11:49:27.147886  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147891  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147895  4597 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:49:27.147900  4597 caffe.cpp:501] detection_eval = 8.35081
-I0511 11:49:27.147904  4597 caffe.cpp:501] detection_eval = 0.0477884
-I0511 11:49:27.147909  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.147913  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.147918  4597 caffe.cpp:501] detection_eval = 2.14315
-I0511 11:49:27.147923  4597 caffe.cpp:501] detection_eval = 8.41935
-I0511 11:49:27.147927  4597 caffe.cpp:501] detection_eval = 0.0443906
-I0511 11:49:27.147931  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147936  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147941  4597 caffe.cpp:501] detection_eval = 2.14516
-I0511 11:49:27.147945  4597 caffe.cpp:501] detection_eval = 8.44153
-I0511 11:49:27.147950  4597 caffe.cpp:501] detection_eval = 0.0463691
-I0511 11:49:27.147954  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147959  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147964  4597 caffe.cpp:501] detection_eval = 2.14919
-I0511 11:49:27.147967  4597 caffe.cpp:501] detection_eval = 8.46976
-I0511 11:49:27.147972  4597 caffe.cpp:501] detection_eval = 0.0425091
-I0511 11:49:27.147977  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147981  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147986  4597 caffe.cpp:501] detection_eval = 2.14919
-I0511 11:49:27.147990  4597 caffe.cpp:501] detection_eval = 8.53831
-I0511 11:49:27.147995  4597 caffe.cpp:501] detection_eval = 0.0396673
-I0511 11:49:27.148000  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.148005  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.148008  4597 caffe.cpp:501] detection_eval = 2.15121
-I0511 11:49:27.148012  4597 caffe.cpp:501] detection_eval = 8.58266
-I0511 11:49:27.148017  4597 caffe.cpp:501] detection_eval = 0.0346807
-I0511 11:49:27.148022  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.148026  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.148031  4597 caffe.cpp:501] detection_eval = 2.15121
-I0511 11:49:27.148036  4597 caffe.cpp:501] detection_eval = 8.66129
-I0511 11:49:27.148041  4597 caffe.cpp:501] detection_eval = 0.0385228
-I0511 11:49:27.148046  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.148054  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148059  4597 caffe.cpp:501] detection_eval = 2.15323
-I0511 11:49:27.148064  4597 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:49:27.148068  4597 caffe.cpp:501] detection_eval = 0.0394484
-I0511 11:49:27.148073  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148077  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148082  4597 caffe.cpp:501] detection_eval = 2.15323
-I0511 11:49:27.148087  4597 caffe.cpp:501] detection_eval = 8.75403
-I0511 11:49:27.148092  4597 caffe.cpp:501] detection_eval = 0.0413556
-I0511 11:49:27.148097  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148102  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148106  4597 caffe.cpp:501] detection_eval = 2.15524
-I0511 11:49:27.148110  4597 caffe.cpp:501] detection_eval = 8.83468
-I0511 11:49:27.148115  4597 caffe.cpp:501] detection_eval = 0.0427899
-I0511 11:49:27.148119  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148124  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148128  4597 caffe.cpp:501] detection_eval = 2.15726
-I0511 11:49:27.148133  4597 caffe.cpp:501] detection_eval = 8.8871
-I0511 11:49:27.148138  4597 caffe.cpp:501] detection_eval = 0.0401683
-I0511 11:49:27.148142  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148146  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148151  4597 caffe.cpp:501] detection_eval = 2.16129
-I0511 11:49:27.148155  4597 caffe.cpp:501] detection_eval = 8.88105
-I0511 11:49:27.148160  4597 caffe.cpp:501] detection_eval = 0.0469561
-I0511 11:49:27.148164  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.148169  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148174  4597 caffe.cpp:501] detection_eval = 2.16331
-I0511 11:49:27.148178  4597 caffe.cpp:501] detection_eval = 8.91935
-I0511 11:49:27.148182  4597 caffe.cpp:501] detection_eval = 0.0382685
-I0511 11:49:27.148187  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.148191  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148196  4597 caffe.cpp:501] detection_eval = 2.16331
-I0511 11:49:27.148201  4597 caffe.cpp:501] detection_eval = 8.96976
-I0511 11:49:27.148205  4597 caffe.cpp:501] detection_eval = 0.0368055
-I0511 11:49:27.148211  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148214  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148219  4597 caffe.cpp:501] detection_eval = 2.16331
-I0511 11:49:27.148223  4597 caffe.cpp:501] detection_eval = 9.02823
-I0511 11:49:27.148228  4597 caffe.cpp:501] detection_eval = 0.0371279
-I0511 11:49:27.148232  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.148237  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.148241  4597 caffe.cpp:501] detection_eval = 2.16532
-I0511 11:49:27.148247  4597 caffe.cpp:501] detection_eval = 9.08065
-I0511 11:49:27.148250  4597 caffe.cpp:501] detection_eval = 0.0445336
-I0511 11:49:27.148255  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.148259  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148264  4597 caffe.cpp:501] detection_eval = 2.16734
-I0511 11:49:27.148269  4597 caffe.cpp:501] detection_eval = 9.14113
-I0511 11:49:27.148273  4597 caffe.cpp:501] detection_eval = 0.0473416
-I0511 11:49:27.148278  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148283  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148288  4597 caffe.cpp:501] detection_eval = 2.16734
-I0511 11:49:27.148291  4597 caffe.cpp:501] detection_eval = 9.27218
-I0511 11:49:27.148296  4597 caffe.cpp:501] detection_eval = 0.036409
-I0511 11:49:27.148300  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.148305  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.148310  4597 caffe.cpp:501] detection_eval = 2.17137
-I0511 11:49:27.148314  4597 caffe.cpp:501] detection_eval = 9.28427
-I0511 11:49:27.148319  4597 caffe.cpp:501] detection_eval = 0.0450085
-I0511 11:49:27.148324  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.148332  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.148337  4597 caffe.cpp:501] detection_eval = 2.17137
-I0511 11:49:27.148342  4597 caffe.cpp:501] detection_eval = 9.40726
-I0511 11:49:27.148346  4597 caffe.cpp:501] detection_eval = 0.0398951
-I0511 11:49:27.148351  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.148355  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.148360  4597 caffe.cpp:501] detection_eval = 2.17339
-I0511 11:49:27.148365  4597 caffe.cpp:501] detection_eval = 9.46169
-I0511 11:49:27.148370  4597 caffe.cpp:501] detection_eval = 0.0432768
-I0511 11:49:27.148373  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148378  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.148382  4597 caffe.cpp:501] detection_eval = 2.17339
-I0511 11:49:27.148387  4597 caffe.cpp:501] detection_eval = 9.63306
-I0511 11:49:27.148391  4597 caffe.cpp:501] detection_eval = 0.0467469
-I0511 11:49:27.148396  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.148401  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.148406  4597 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:49:27.148411  4597 caffe.cpp:501] detection_eval = 9.65524
-I0511 11:49:27.148414  4597 caffe.cpp:501] detection_eval = 0.0482485
-I0511 11:49:27.148419  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148423  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148428  4597 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:49:27.148432  4597 caffe.cpp:501] detection_eval = 9.79435
-I0511 11:49:27.148437  4597 caffe.cpp:501] detection_eval = 0.047979
-I0511 11:49:27.148442  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148447  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148450  4597 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:49:27.148455  4597 caffe.cpp:501] detection_eval = 9.87298
-I0511 11:49:27.148459  4597 caffe.cpp:501] detection_eval = 0.0429694
-I0511 11:49:27.148463  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.148468  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.148473  4597 caffe.cpp:501] detection_eval = 2.18145
-I0511 11:49:27.148478  4597 caffe.cpp:501] detection_eval = 9.86492
-I0511 11:49:27.148483  4597 caffe.cpp:501] detection_eval = 0.0423322
-I0511 11:49:27.148486  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148491  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148496  4597 caffe.cpp:501] detection_eval = 2.18548
-I0511 11:49:27.148501  4597 caffe.cpp:501] detection_eval = 9.95766
-I0511 11:49:27.148505  4597 caffe.cpp:501] detection_eval = 0.0468316
-I0511 11:49:27.148510  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.148514  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148519  4597 caffe.cpp:501] detection_eval = 2.18952
-I0511 11:49:27.148530  4597 caffe.cpp:501] detection_eval = 9.98589
-I0511 11:49:27.148535  4597 caffe.cpp:501] detection_eval = 0.040069
-I0511 11:49:27.148540  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148543  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148547  4597 caffe.cpp:501] detection_eval = 2.18952
-I0511 11:49:27.148551  4597 caffe.cpp:501] detection_eval = 10.1149
-I0511 11:49:27.148556  4597 caffe.cpp:501] detection_eval = 0.0409916
-I0511 11:49:27.148561  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.148566  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.148571  4597 caffe.cpp:501] detection_eval = 2.19556
-I0511 11:49:27.148576  4597 caffe.cpp:501] detection_eval = 10.0867
-I0511 11:49:27.148579  4597 caffe.cpp:501] detection_eval = 0.0399014
-I0511 11:49:27.148584  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.148589  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.148593  4597 caffe.cpp:501] detection_eval = 2.20161
-I0511 11:49:27.148598  4597 caffe.cpp:501] detection_eval = 10.125
-I0511 11:49:27.148602  4597 caffe.cpp:501] detection_eval = 0.0449894
-I0511 11:49:27.148612  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148617  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148622  4597 caffe.cpp:501] detection_eval = 2.20363
-I0511 11:49:27.148625  4597 caffe.cpp:501] detection_eval = 10.1794
-I0511 11:49:27.148630  4597 caffe.cpp:501] detection_eval = 0.0426234
-I0511 11:49:27.148635  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148639  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148644  4597 caffe.cpp:501] detection_eval = 2.20766
-I0511 11:49:27.148648  4597 caffe.cpp:501] detection_eval = 10.1714
-I0511 11:49:27.148653  4597 caffe.cpp:501] detection_eval = 0.04198
-I0511 11:49:27.148658  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148663  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148667  4597 caffe.cpp:501] detection_eval = 2.20766
-I0511 11:49:27.148671  4597 caffe.cpp:501] detection_eval = 10.2621
-I0511 11:49:27.148676  4597 caffe.cpp:501] detection_eval = 0.0417781
-I0511 11:49:27.148681  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148685  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148690  4597 caffe.cpp:501] detection_eval = 2.21371
-I0511 11:49:27.148694  4597 caffe.cpp:501] detection_eval = 10.2621
-I0511 11:49:27.148699  4597 caffe.cpp:501] detection_eval = 0.0426701
-I0511 11:49:27.148705  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148708  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148713  4597 caffe.cpp:501] detection_eval = 2.21573
-I0511 11:49:27.148717  4597 caffe.cpp:501] detection_eval = 10.3165
-I0511 11:49:27.148722  4597 caffe.cpp:501] detection_eval = 0.04341
-I0511 11:49:27.148726  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148731  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148736  4597 caffe.cpp:501] detection_eval = 2.21573
-I0511 11:49:27.148741  4597 caffe.cpp:501] detection_eval = 10.4173
-I0511 11:49:27.148746  4597 caffe.cpp:501] detection_eval = 0.0415825
-I0511 11:49:27.148749  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148754  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148758  4597 caffe.cpp:501] detection_eval = 2.21976
-I0511 11:49:27.148762  4597 caffe.cpp:501] detection_eval = 10.4496
-I0511 11:49:27.148767  4597 caffe.cpp:501] detection_eval = 0.0436784
-I0511 11:49:27.148772  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148777  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.148780  4597 caffe.cpp:501] detection_eval = 2.22177
-I0511 11:49:27.148784  4597 caffe.cpp:501] detection_eval = 10.4617
-I0511 11:49:27.148788  4597 caffe.cpp:501] detection_eval = 0.0425902
-I0511 11:49:27.148792  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148797  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148802  4597 caffe.cpp:501] detection_eval = 2.22379
-I0511 11:49:27.148805  4597 caffe.cpp:501] detection_eval = 10.5141
-I0511 11:49:27.148810  4597 caffe.cpp:501] detection_eval = 0.0450279
-I0511 11:49:27.148814  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.148818  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.148823  4597 caffe.cpp:501] detection_eval = 2.22984
-I0511 11:49:27.148825  4597 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:49:27.148829  4597 caffe.cpp:501] detection_eval = 0.0487626
-I0511 11:49:27.148834  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.148839  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.148844  4597 caffe.cpp:501] detection_eval = 2.23185
-I0511 11:49:27.148849  4597 caffe.cpp:501] detection_eval = 10.5484
-I0511 11:49:27.148852  4597 caffe.cpp:501] detection_eval = 0.0416015
-I0511 11:49:27.148857  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.148861  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.148866  4597 caffe.cpp:501] detection_eval = 2.23185
-I0511 11:49:27.148870  4597 caffe.cpp:501] detection_eval = 10.6472
-I0511 11:49:27.148875  4597 caffe.cpp:501] detection_eval = 0.0393731
-I0511 11:49:27.148883  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148888  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148892  4597 caffe.cpp:501] detection_eval = 2.23185
-I0511 11:49:27.148897  4597 caffe.cpp:501] detection_eval = 10.6996
-I0511 11:49:27.148902  4597 caffe.cpp:501] detection_eval = 0.0403121
-I0511 11:49:27.148906  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148911  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148916  4597 caffe.cpp:501] detection_eval = 2.2379
-I0511 11:49:27.148921  4597 caffe.cpp:501] detection_eval = 10.6754
-I0511 11:49:27.148924  4597 caffe.cpp:501] detection_eval = 0.0437596
-I0511 11:49:27.148929  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148934  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148939  4597 caffe.cpp:501] detection_eval = 2.2379
-I0511 11:49:27.148944  4597 caffe.cpp:501] detection_eval = 10.7903
-I0511 11:49:27.148949  4597 caffe.cpp:501] detection_eval = 0.0443543
-I0511 11:49:27.148953  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.148958  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.148962  4597 caffe.cpp:501] detection_eval = 2.23992
-I0511 11:49:27.148967  4597 caffe.cpp:501] detection_eval = 10.8226
-I0511 11:49:27.148972  4597 caffe.cpp:501] detection_eval = 0.0393024
-I0511 11:49:27.148977  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148980  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148985  4597 caffe.cpp:501] detection_eval = 2.23992
-I0511 11:49:27.148989  4597 caffe.cpp:501] detection_eval = 10.9073
-I0511 11:49:27.148994  4597 caffe.cpp:501] detection_eval = 0.0388229
-I0511 11:49:27.148999  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149003  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149008  4597 caffe.cpp:501] detection_eval = 2.24194
-I0511 11:49:27.149013  4597 caffe.cpp:501] detection_eval = 10.9536
-I0511 11:49:27.149018  4597 caffe.cpp:501] detection_eval = 0.0373147
-I0511 11:49:27.149021  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.149026  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.149031  4597 caffe.cpp:501] detection_eval = 2.24597
-I0511 11:49:27.149035  4597 caffe.cpp:501] detection_eval = 10.9456
-I0511 11:49:27.149040  4597 caffe.cpp:501] detection_eval = 0.0377576
-I0511 11:49:27.149044  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.149049  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149055  4597 caffe.cpp:501] detection_eval = 2.24798
-I0511 11:49:27.149058  4597 caffe.cpp:501] detection_eval = 10.9899
-I0511 11:49:27.149063  4597 caffe.cpp:501] detection_eval = 0.0406665
-I0511 11:49:27.149067  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149072  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149076  4597 caffe.cpp:501] detection_eval = 2.25
-I0511 11:49:27.149081  4597 caffe.cpp:501] detection_eval = 11.0484
-I0511 11:49:27.149086  4597 caffe.cpp:501] detection_eval = 0.040189
-I0511 11:49:27.149091  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149096  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149101  4597 caffe.cpp:501] detection_eval = 2.25
-I0511 11:49:27.149104  4597 caffe.cpp:501] detection_eval = 11.121
-I0511 11:49:27.149109  4597 caffe.cpp:501] detection_eval = 0.0411637
-I0511 11:49:27.149114  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.149118  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.149123  4597 caffe.cpp:501] detection_eval = 2.25202
-I0511 11:49:27.149127  4597 caffe.cpp:501] detection_eval = 11.1875
-I0511 11:49:27.149132  4597 caffe.cpp:501] detection_eval = 0.0421608
-I0511 11:49:27.149137  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149142  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149147  4597 caffe.cpp:501] detection_eval = 2.25202
-I0511 11:49:27.149152  4597 caffe.cpp:501] detection_eval = 11.2782
-I0511 11:49:27.149160  4597 caffe.cpp:501] detection_eval = 0.0465724
-I0511 11:49:27.149165  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149170  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.149175  4597 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:49:27.149179  4597 caffe.cpp:501] detection_eval = 11.2581
-I0511 11:49:27.149184  4597 caffe.cpp:501] detection_eval = 0.0395285
-I0511 11:49:27.149188  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149194  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149199  4597 caffe.cpp:501] detection_eval = 2.26411
-I0511 11:49:27.149202  4597 caffe.cpp:501] detection_eval = 11.1855
-I0511 11:49:27.149207  4597 caffe.cpp:501] detection_eval = 0.0422078
-I0511 11:49:27.149211  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149216  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149220  4597 caffe.cpp:501] detection_eval = 2.27016
-I0511 11:49:27.149225  4597 caffe.cpp:501] detection_eval = 11.1613
-I0511 11:49:27.149230  4597 caffe.cpp:501] detection_eval = 0.0413146
-I0511 11:49:27.149235  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149240  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149245  4597 caffe.cpp:501] detection_eval = 2.27218
-I0511 11:49:27.149248  4597 caffe.cpp:501] detection_eval = 11.2641
-I0511 11:49:27.149253  4597 caffe.cpp:501] detection_eval = 0.051111
-I0511 11:49:27.149257  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.149262  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.149266  4597 caffe.cpp:501] detection_eval = 2.27419
-I0511 11:49:27.149271  4597 caffe.cpp:501] detection_eval = 11.3226
-I0511 11:49:27.149276  4597 caffe.cpp:501] detection_eval = 0.0490444
-I0511 11:49:27.149281  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149286  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149289  4597 caffe.cpp:501] detection_eval = 2.27823
-I0511 11:49:27.149294  4597 caffe.cpp:501] detection_eval = 11.3468
-I0511 11:49:27.149298  4597 caffe.cpp:501] detection_eval = 0.046179
-I0511 11:49:27.149303  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149308  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149312  4597 caffe.cpp:501] detection_eval = 2.28226
-I0511 11:49:27.149317  4597 caffe.cpp:501] detection_eval = 11.3992
-I0511 11:49:27.149322  4597 caffe.cpp:501] detection_eval = 0.050707
-I0511 11:49:27.149327  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.149330  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.149335  4597 caffe.cpp:501] detection_eval = 2.28629
-I0511 11:49:27.149346  4597 caffe.cpp:501] detection_eval = 11.4234
-I0511 11:49:27.149356  4597 caffe.cpp:501] detection_eval = 0.0476655
-I0511 11:49:27.149365  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149374  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.149381  4597 caffe.cpp:501] detection_eval = 2.28629
-I0511 11:49:27.149389  4597 caffe.cpp:501] detection_eval = 11.4899
-I0511 11:49:27.149395  4597 caffe.cpp:501] detection_eval = 0.0419335
-I0511 11:49:27.149399  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.149405  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.149408  4597 caffe.cpp:501] detection_eval = 2.28629
-I0511 11:49:27.149413  4597 caffe.cpp:501] detection_eval = 11.5625
-I0511 11:49:27.149418  4597 caffe.cpp:501] detection_eval = 0.0424994
-I0511 11:49:27.149422  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.149427  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149431  4597 caffe.cpp:501] detection_eval = 2.28629
-I0511 11:49:27.149436  4597 caffe.cpp:501] detection_eval = 11.6472
-I0511 11:49:27.149441  4597 caffe.cpp:501] detection_eval = 0.0458754
-I0511 11:49:27.149446  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149449  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.149454  4597 caffe.cpp:501] detection_eval = 2.28831
-I0511 11:49:27.149458  4597 caffe.cpp:501] detection_eval = 11.6754
-I0511 11:49:27.149467  4597 caffe.cpp:501] detection_eval = 0.0457525
-I0511 11:49:27.149472  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.149477  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.149482  4597 caffe.cpp:501] detection_eval = 2.29032
-I0511 11:49:27.149487  4597 caffe.cpp:501] detection_eval = 11.7137
-I0511 11:49:27.149492  4597 caffe.cpp:501] detection_eval = 0.0428728
-I0511 11:49:27.149495  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149500  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149504  4597 caffe.cpp:501] detection_eval = 2.29435
-I0511 11:49:27.149509  4597 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:49:27.149513  4597 caffe.cpp:501] detection_eval = 0.0429885
-I0511 11:49:27.149518  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149523  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149528  4597 caffe.cpp:501] detection_eval = 2.29839
-I0511 11:49:27.149531  4597 caffe.cpp:501] detection_eval = 11.6875
-I0511 11:49:27.149536  4597 caffe.cpp:501] detection_eval = 0.0391875
-I0511 11:49:27.149541  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.149545  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149549  4597 caffe.cpp:501] detection_eval = 2.3004
-I0511 11:49:27.149552  4597 caffe.cpp:501] detection_eval = 11.7177
-I0511 11:49:27.149556  4597 caffe.cpp:501] detection_eval = 0.041563
-I0511 11:49:27.149561  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149566  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149570  4597 caffe.cpp:501] detection_eval = 2.3004
-I0511 11:49:27.149575  4597 caffe.cpp:501] detection_eval = 11.7944
-I0511 11:49:27.149580  4597 caffe.cpp:501] detection_eval = 0.0366132
-I0511 11:49:27.149585  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.149590  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.149593  4597 caffe.cpp:501] detection_eval = 2.30242
-I0511 11:49:27.149598  4597 caffe.cpp:501] detection_eval = 11.8609
-I0511 11:49:27.149602  4597 caffe.cpp:501] detection_eval = 0.036291
-I0511 11:49:27.149607  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.149611  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149616  4597 caffe.cpp:501] detection_eval = 2.30444
-I0511 11:49:27.149621  4597 caffe.cpp:501] detection_eval = 11.9395
-I0511 11:49:27.149626  4597 caffe.cpp:501] detection_eval = 0.0379277
-I0511 11:49:27.149629  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.149634  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.149639  4597 caffe.cpp:501] detection_eval = 2.30645
-I0511 11:49:27.149643  4597 caffe.cpp:501] detection_eval = 11.9819
-I0511 11:49:27.149648  4597 caffe.cpp:501] detection_eval = 0.0395199
-I0511 11:49:27.149652  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.149657  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149662  4597 caffe.cpp:501] detection_eval = 2.31048
-I0511 11:49:27.149667  4597 caffe.cpp:501] detection_eval = 12.0202
-I0511 11:49:27.149670  4597 caffe.cpp:501] detection_eval = 0.040769
-I0511 11:49:27.149675  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149679  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149684  4597 caffe.cpp:501] detection_eval = 2.31653
-I0511 11:49:27.149688  4597 caffe.cpp:501] detection_eval = 11.9839
-I0511 11:49:27.149693  4597 caffe.cpp:501] detection_eval = 0.0399254
-I0511 11:49:27.149698  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.149703  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.149708  4597 caffe.cpp:501] detection_eval = 2.32258
-I0511 11:49:27.149711  4597 caffe.cpp:501] detection_eval = 11.9536
-I0511 11:49:27.149716  4597 caffe.cpp:501] detection_eval = 0.0350768
-I0511 11:49:27.149721  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.149725  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.149730  4597 caffe.cpp:501] detection_eval = 2.32661
-I0511 11:49:27.149739  4597 caffe.cpp:501] detection_eval = 11.9778
-I0511 11:49:27.149744  4597 caffe.cpp:501] detection_eval = 0.0423888
-I0511 11:49:27.149747  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149752  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149756  4597 caffe.cpp:501] detection_eval = 2.32661
-I0511 11:49:27.149761  4597 caffe.cpp:501] detection_eval = 12.0242
-I0511 11:49:27.149765  4597 caffe.cpp:501] detection_eval = 0.0381201
-I0511 11:49:27.149770  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149775  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149780  4597 caffe.cpp:501] detection_eval = 2.32863
-I0511 11:49:27.149790  4597 caffe.cpp:501] detection_eval = 12.0665
-I0511 11:49:27.149798  4597 caffe.cpp:501] detection_eval = 0.0392492
-I0511 11:49:27.149806  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149816  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.149823  4597 caffe.cpp:501] detection_eval = 2.32863
-I0511 11:49:27.149832  4597 caffe.cpp:501] detection_eval = 12.1391
-I0511 11:49:27.149837  4597 caffe.cpp:501] detection_eval = 0.0379095
-I0511 11:49:27.149842  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.149847  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149852  4597 caffe.cpp:501] detection_eval = 2.32863
-I0511 11:49:27.149855  4597 caffe.cpp:501] detection_eval = 12.2157
-I0511 11:49:27.149860  4597 caffe.cpp:501] detection_eval = 0.0364523
-I0511 11:49:27.149864  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.149869  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149874  4597 caffe.cpp:501] detection_eval = 2.33669
-I0511 11:49:27.149878  4597 caffe.cpp:501] detection_eval = 12.1875
-I0511 11:49:27.149883  4597 caffe.cpp:501] detection_eval = 0.0422583
-I0511 11:49:27.149888  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149893  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149896  4597 caffe.cpp:501] detection_eval = 2.33669
-I0511 11:49:27.149901  4597 caffe.cpp:501] detection_eval = 12.2722
-I0511 11:49:27.149906  4597 caffe.cpp:501] detection_eval = 0.0403973
-I0511 11:49:27.149910  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149914  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149919  4597 caffe.cpp:501] detection_eval = 2.33871
-I0511 11:49:27.149924  4597 caffe.cpp:501] detection_eval = 12.3206
-I0511 11:49:27.149929  4597 caffe.cpp:501] detection_eval = 0.0492333
-I0511 11:49:27.149933  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149937  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.149942  4597 caffe.cpp:501] detection_eval = 2.34476
-I0511 11:49:27.149946  4597 caffe.cpp:501] detection_eval = 12.2762
-I0511 11:49:27.149951  4597 caffe.cpp:501] detection_eval = 0.0394243
-I0511 11:49:27.149955  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149960  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149965  4597 caffe.cpp:501] detection_eval = 2.34879
-I0511 11:49:27.149969  4597 caffe.cpp:501] detection_eval = 12.256
-I0511 11:49:27.149974  4597 caffe.cpp:501] detection_eval = 0.0380893
-I0511 11:49:27.149978  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149983  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.149987  4597 caffe.cpp:501] detection_eval = 2.35081
-I0511 11:49:27.149992  4597 caffe.cpp:501] detection_eval = 12.2702
-I0511 11:49:27.149997  4597 caffe.cpp:501] detection_eval = 0.0336209
-I0511 11:49:27.150002  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150007  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.150010  4597 caffe.cpp:501] detection_eval = 2.35484
-I0511 11:49:27.150015  4597 caffe.cpp:501] detection_eval = 12.2762
-I0511 11:49:27.150019  4597 caffe.cpp:501] detection_eval = 0.041551
-I0511 11:49:27.150024  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150028  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150038  4597 caffe.cpp:501] detection_eval = 2.35887
-I0511 11:49:27.150043  4597 caffe.cpp:501] detection_eval = 12.2802
-I0511 11:49:27.150048  4597 caffe.cpp:501] detection_eval = 0.0416252
-I0511 11:49:27.150053  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150056  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150061  4597 caffe.cpp:501] detection_eval = 2.36694
-I0511 11:49:27.150065  4597 caffe.cpp:501] detection_eval = 12.25
-I0511 11:49:27.150070  4597 caffe.cpp:501] detection_eval = 0.0402391
-I0511 11:49:27.150074  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.150079  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150084  4597 caffe.cpp:501] detection_eval = 2.36895
-I0511 11:49:27.150089  4597 caffe.cpp:501] detection_eval = 12.2903
-I0511 11:49:27.150094  4597 caffe.cpp:501] detection_eval = 0.0380401
-I0511 11:49:27.150097  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150102  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150106  4597 caffe.cpp:501] detection_eval = 2.37298
-I0511 11:49:27.150111  4597 caffe.cpp:501] detection_eval = 12.2762
-I0511 11:49:27.150115  4597 caffe.cpp:501] detection_eval = 0.0418109
-I0511 11:49:27.150120  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150125  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.150130  4597 caffe.cpp:501] detection_eval = 2.37298
-I0511 11:49:27.150133  4597 caffe.cpp:501] detection_eval = 12.3528
-I0511 11:49:27.150138  4597 caffe.cpp:501] detection_eval = 0.0400792
-I0511 11:49:27.150143  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150147  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150151  4597 caffe.cpp:501] detection_eval = 2.375
-I0511 11:49:27.150156  4597 caffe.cpp:501] detection_eval = 12.3972
-I0511 11:49:27.150161  4597 caffe.cpp:501] detection_eval = 0.0392371
-I0511 11:49:27.150166  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150171  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150174  4597 caffe.cpp:501] detection_eval = 2.38105
-I0511 11:49:27.150179  4597 caffe.cpp:501] detection_eval = 12.3427
-I0511 11:49:27.150184  4597 caffe.cpp:501] detection_eval = 0.0415699
-I0511 11:49:27.150188  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.150193  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.150197  4597 caffe.cpp:501] detection_eval = 2.38911
-I0511 11:49:27.150202  4597 caffe.cpp:501] detection_eval = 12.2782
-I0511 11:49:27.150207  4597 caffe.cpp:501] detection_eval = 0.0471242
-I0511 11:49:27.150216  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150225  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150234  4597 caffe.cpp:501] detection_eval = 2.39113
-I0511 11:49:27.150243  4597 caffe.cpp:501] detection_eval = 12.375
-I0511 11:49:27.150251  4597 caffe.cpp:501] detection_eval = 0.0439591
-I0511 11:49:27.150259  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150265  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.150270  4597 caffe.cpp:501] detection_eval = 2.39113
-I0511 11:49:27.150274  4597 caffe.cpp:501] detection_eval = 12.4234
-I0511 11:49:27.150279  4597 caffe.cpp:501] detection_eval = 0.0383429
-I0511 11:49:27.150283  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150288  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.150293  4597 caffe.cpp:501] detection_eval = 2.39113
-I0511 11:49:27.150297  4597 caffe.cpp:501] detection_eval = 12.4778
-I0511 11:49:27.150302  4597 caffe.cpp:501] detection_eval = 0.0366566
-I0511 11:49:27.150306  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150311  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150316  4597 caffe.cpp:501] detection_eval = 2.39315
-I0511 11:49:27.150321  4597 caffe.cpp:501] detection_eval = 12.5141
-I0511 11:49:27.150326  4597 caffe.cpp:501] detection_eval = 0.0373185
-I0511 11:49:27.150329  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150334  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150342  4597 caffe.cpp:501] detection_eval = 2.39315
-I0511 11:49:27.150347  4597 caffe.cpp:501] detection_eval = 12.5585
-I0511 11:49:27.150352  4597 caffe.cpp:501] detection_eval = 0.0350957
-I0511 11:49:27.150355  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150359  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150363  4597 caffe.cpp:501] detection_eval = 2.39516
-I0511 11:49:27.150368  4597 caffe.cpp:501] detection_eval = 12.5927
-I0511 11:49:27.150373  4597 caffe.cpp:501] detection_eval = 0.0371443
-I0511 11:49:27.150377  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150382  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150387  4597 caffe.cpp:501] detection_eval = 2.39718
-I0511 11:49:27.150391  4597 caffe.cpp:501] detection_eval = 12.6593
-I0511 11:49:27.150395  4597 caffe.cpp:501] detection_eval = 0.0382026
-I0511 11:49:27.150400  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.150404  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150409  4597 caffe.cpp:501] detection_eval = 2.40121
-I0511 11:49:27.150413  4597 caffe.cpp:501] detection_eval = 12.6371
-I0511 11:49:27.150418  4597 caffe.cpp:501] detection_eval = 0.0410381
-I0511 11:49:27.150424  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150427  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.150432  4597 caffe.cpp:501] detection_eval = 2.40121
-I0511 11:49:27.150436  4597 caffe.cpp:501] detection_eval = 12.6835
-I0511 11:49:27.150441  4597 caffe.cpp:501] detection_eval = 0.0402094
-I0511 11:49:27.150445  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150450  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150454  4597 caffe.cpp:501] detection_eval = 2.40323
-I0511 11:49:27.150460  4597 caffe.cpp:501] detection_eval = 12.6956
-I0511 11:49:27.150465  4597 caffe.cpp:501] detection_eval = 0.0408201
-I0511 11:49:27.150468  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150473  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150478  4597 caffe.cpp:501] detection_eval = 2.40927
-I0511 11:49:27.150482  4597 caffe.cpp:501] detection_eval = 12.6875
-I0511 11:49:27.150487  4597 caffe.cpp:501] detection_eval = 0.0416168
-I0511 11:49:27.150491  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.150496  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.150501  4597 caffe.cpp:501] detection_eval = 2.41331
-I0511 11:49:27.150506  4597 caffe.cpp:501] detection_eval = 12.6633
-I0511 11:49:27.150509  4597 caffe.cpp:501] detection_eval = 0.039459
-I0511 11:49:27.150514  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150519  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150523  4597 caffe.cpp:501] detection_eval = 2.41331
-I0511 11:49:27.150528  4597 caffe.cpp:501] detection_eval = 12.7198
-I0511 11:49:27.150532  4597 caffe.cpp:501] detection_eval = 0.0383806
-I0511 11:49:27.150537  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.150542  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.150547  4597 caffe.cpp:501] detection_eval = 2.41532
-I0511 11:49:27.150552  4597 caffe.cpp:501] detection_eval = 12.7702
-I0511 11:49:27.150557  4597 caffe.cpp:501] detection_eval = 0.0405816
-I0511 11:49:27.150560  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150565  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.150569  4597 caffe.cpp:501] detection_eval = 2.41734
-I0511 11:49:27.150574  4597 caffe.cpp:501] detection_eval = 12.7823
-I0511 11:49:27.150578  4597 caffe.cpp:501] detection_eval = 0.0382321
-I0511 11:49:27.150583  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150588  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150593  4597 caffe.cpp:501] detection_eval = 2.41734
-I0511 11:49:27.150598  4597 caffe.cpp:501] detection_eval = 12.8528
-I0511 11:49:27.150601  4597 caffe.cpp:501] detection_eval = 0.0418643
-I0511 11:49:27.150606  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.150614  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.150619  4597 caffe.cpp:501] detection_eval = 2.42339
-I0511 11:49:27.150624  4597 caffe.cpp:501] detection_eval = 12.8044
-I0511 11:49:27.150629  4597 caffe.cpp:501] detection_eval = 0.0426642
-I0511 11:49:27.150632  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150637  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150642  4597 caffe.cpp:501] detection_eval = 2.42944
-I0511 11:49:27.150646  4597 caffe.cpp:501] detection_eval = 12.8105
-I0511 11:49:27.150656  4597 caffe.cpp:501] detection_eval = 0.0378261
-I0511 11:49:27.150665  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150674  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150682  4597 caffe.cpp:501] detection_eval = 2.4375
-I0511 11:49:27.150691  4597 caffe.cpp:501] detection_eval = 12.75
-I0511 11:49:27.150699  4597 caffe.cpp:501] detection_eval = 0.0351373
-I0511 11:49:27.150704  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.150709  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.150714  4597 caffe.cpp:501] detection_eval = 2.44153
-I0511 11:49:27.150719  4597 caffe.cpp:501] detection_eval = 12.7681
-I0511 11:49:27.150723  4597 caffe.cpp:501] detection_eval = 0.0400386
-I0511 11:49:27.150728  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150732  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.150738  4597 caffe.cpp:501] detection_eval = 2.44556
-I0511 11:49:27.150741  4597 caffe.cpp:501] detection_eval = 12.7823
-I0511 11:49:27.150746  4597 caffe.cpp:501] detection_eval = 0.0394807
-I0511 11:49:27.150751  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150755  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150760  4597 caffe.cpp:501] detection_eval = 2.4496
-I0511 11:49:27.150765  4597 caffe.cpp:501] detection_eval = 12.7661
-I0511 11:49:27.150769  4597 caffe.cpp:501] detection_eval = 0.0382113
-I0511 11:49:27.150774  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150779  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150784  4597 caffe.cpp:501] detection_eval = 2.4496
-I0511 11:49:27.150787  4597 caffe.cpp:501] detection_eval = 12.8185
-I0511 11:49:27.150792  4597 caffe.cpp:501] detection_eval = 0.0357022
-I0511 11:49:27.150796  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150801  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150805  4597 caffe.cpp:501] detection_eval = 2.45363
-I0511 11:49:27.150810  4597 caffe.cpp:501] detection_eval = 12.8125
-I0511 11:49:27.150815  4597 caffe.cpp:501] detection_eval = 0.03798
-I0511 11:49:27.150820  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150825  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150830  4597 caffe.cpp:501] detection_eval = 2.45363
-I0511 11:49:27.150833  4597 caffe.cpp:501] detection_eval = 12.8952
-I0511 11:49:27.150838  4597 caffe.cpp:501] detection_eval = 0.042409
-I0511 11:49:27.150842  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150847  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150851  4597 caffe.cpp:501] detection_eval = 2.45565
-I0511 11:49:27.150856  4597 caffe.cpp:501] detection_eval = 12.9234
-I0511 11:49:27.150861  4597 caffe.cpp:501] detection_eval = 0.0380439
-I0511 11:49:27.150866  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150869  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.150874  4597 caffe.cpp:501] detection_eval = 2.45565
-I0511 11:49:27.150878  4597 caffe.cpp:501] detection_eval = 12.9758
-I0511 11:49:27.150883  4597 caffe.cpp:501] detection_eval = 0.0350995
-I0511 11:49:27.150888  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.150892  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150897  4597 caffe.cpp:501] detection_eval = 2.45968
-I0511 11:49:27.150902  4597 caffe.cpp:501] detection_eval = 12.998
-I0511 11:49:27.150907  4597 caffe.cpp:501] detection_eval = 0.039502
-I0511 11:49:27.150915  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.150919  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150924  4597 caffe.cpp:501] detection_eval = 2.45968
-I0511 11:49:27.150928  4597 caffe.cpp:501] detection_eval = 13.0827
-I0511 11:49:27.150933  4597 caffe.cpp:501] detection_eval = 0.0368795
-I0511 11:49:27.150938  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150943  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150948  4597 caffe.cpp:501] detection_eval = 2.46169
-I0511 11:49:27.150951  4597 caffe.cpp:501] detection_eval = 13.1331
-I0511 11:49:27.150956  4597 caffe.cpp:501] detection_eval = 0.0381957
-I0511 11:49:27.150960  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150965  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150970  4597 caffe.cpp:501] detection_eval = 2.46573
-I0511 11:49:27.150974  4597 caffe.cpp:501] detection_eval = 13.1351
-I0511 11:49:27.150979  4597 caffe.cpp:501] detection_eval = 0.0448654
-I0511 11:49:27.150985  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150988  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150993  4597 caffe.cpp:501] detection_eval = 2.46976
-I0511 11:49:27.150997  4597 caffe.cpp:501] detection_eval = 13.1069
-I0511 11:49:27.151002  4597 caffe.cpp:501] detection_eval = 0.0377625
-I0511 11:49:27.151006  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.151011  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151015  4597 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:49:27.151021  4597 caffe.cpp:501] detection_eval = 13.1472
-I0511 11:49:27.151026  4597 caffe.cpp:501] detection_eval = 0.0362461
-I0511 11:49:27.151029  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151033  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151038  4597 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:49:27.151043  4597 caffe.cpp:501] detection_eval = 13.2177
-I0511 11:49:27.151047  4597 caffe.cpp:501] detection_eval = 0.0344065
-I0511 11:49:27.151052  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151057  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151062  4597 caffe.cpp:501] detection_eval = 2.47581
-I0511 11:49:27.151067  4597 caffe.cpp:501] detection_eval = 13.2258
-I0511 11:49:27.151072  4597 caffe.cpp:501] detection_eval = 0.0381641
-I0511 11:49:27.151075  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151087  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151095  4597 caffe.cpp:501] detection_eval = 2.47782
-I0511 11:49:27.151104  4597 caffe.cpp:501] detection_eval = 13.2782
-I0511 11:49:27.151113  4597 caffe.cpp:501] detection_eval = 0.0390413
-I0511 11:49:27.151121  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151129  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151134  4597 caffe.cpp:501] detection_eval = 2.47984
-I0511 11:49:27.151139  4597 caffe.cpp:501] detection_eval = 13.2823
-I0511 11:49:27.151144  4597 caffe.cpp:501] detection_eval = 0.0340876
-I0511 11:49:27.151147  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.151151  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.151156  4597 caffe.cpp:501] detection_eval = 2.49395
-I0511 11:49:27.151160  4597 caffe.cpp:501] detection_eval = 13.1532
-I0511 11:49:27.151165  4597 caffe.cpp:501] detection_eval = 0.0371462
-I0511 11:49:27.151170  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.151175  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151178  4597 caffe.cpp:501] detection_eval = 2.49395
-I0511 11:49:27.151183  4597 caffe.cpp:501] detection_eval = 13.2419
-I0511 11:49:27.151188  4597 caffe.cpp:501] detection_eval = 0.0375995
-I0511 11:49:27.151192  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151197  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151201  4597 caffe.cpp:501] detection_eval = 2.49798
-I0511 11:49:27.151206  4597 caffe.cpp:501] detection_eval = 13.2198
-I0511 11:49:27.151211  4597 caffe.cpp:501] detection_eval = 0.0327908
-I0511 11:49:27.151219  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151224  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.151228  4597 caffe.cpp:501] detection_eval = 2.49798
-I0511 11:49:27.151233  4597 caffe.cpp:501] detection_eval = 13.2984
-I0511 11:49:27.151237  4597 caffe.cpp:501] detection_eval = 0.0408301
-I0511 11:49:27.151242  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.151247  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.151252  4597 caffe.cpp:501] detection_eval = 2.50202
-I0511 11:49:27.151255  4597 caffe.cpp:501] detection_eval = 13.3185
-I0511 11:49:27.151260  4597 caffe.cpp:501] detection_eval = 0.0363852
-I0511 11:49:27.151265  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151269  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151274  4597 caffe.cpp:501] detection_eval = 2.50806
-I0511 11:49:27.151278  4597 caffe.cpp:501] detection_eval = 13.3105
-I0511 11:49:27.151283  4597 caffe.cpp:501] detection_eval = 0.0423162
-I0511 11:49:27.151288  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151293  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.151296  4597 caffe.cpp:501] detection_eval = 2.50806
-I0511 11:49:27.151301  4597 caffe.cpp:501] detection_eval = 13.3891
-I0511 11:49:27.151306  4597 caffe.cpp:501] detection_eval = 0.0378473
-I0511 11:49:27.151310  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151315  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151319  4597 caffe.cpp:501] detection_eval = 2.51008
-I0511 11:49:27.151324  4597 caffe.cpp:501] detection_eval = 13.4214
-I0511 11:49:27.151329  4597 caffe.cpp:501] detection_eval = 0.0358066
-I0511 11:49:27.151334  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.151337  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151342  4597 caffe.cpp:501] detection_eval = 2.51008
-I0511 11:49:27.151346  4597 caffe.cpp:501] detection_eval = 13.494
-I0511 11:49:27.151351  4597 caffe.cpp:501] detection_eval = 0.0365599
-I0511 11:49:27.151356  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151360  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151365  4597 caffe.cpp:501] detection_eval = 2.5121
-I0511 11:49:27.151371  4597 caffe.cpp:501] detection_eval = 13.5746
-I0511 11:49:27.151374  4597 caffe.cpp:501] detection_eval = 0.0346992
-I0511 11:49:27.151379  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151383  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151388  4597 caffe.cpp:501] detection_eval = 2.51411
-I0511 11:49:27.151392  4597 caffe.cpp:501] detection_eval = 13.629
-I0511 11:49:27.151397  4597 caffe.cpp:501] detection_eval = 0.0378362
-I0511 11:49:27.151401  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.151407  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151410  4597 caffe.cpp:501] detection_eval = 2.52621
-I0511 11:49:27.151415  4597 caffe.cpp:501] detection_eval = 13.5806
-I0511 11:49:27.151420  4597 caffe.cpp:501] detection_eval = 0.0434219
-I0511 11:49:27.151424  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.151429  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.151433  4597 caffe.cpp:501] detection_eval = 2.52621
-I0511 11:49:27.151438  4597 caffe.cpp:501] detection_eval = 13.7097
-I0511 11:49:27.151443  4597 caffe.cpp:501] detection_eval = 0.0425423
-I0511 11:49:27.151448  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.151453  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.151456  4597 caffe.cpp:501] detection_eval = 2.52823
-I0511 11:49:27.151461  4597 caffe.cpp:501] detection_eval = 13.7661
-I0511 11:49:27.151465  4597 caffe.cpp:501] detection_eval = 0.0360792
-I0511 11:49:27.151470  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151474  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151479  4597 caffe.cpp:501] detection_eval = 2.53024
-I0511 11:49:27.151484  4597 caffe.cpp:501] detection_eval = 13.9153
-I0511 11:49:27.151499  4597 caffe.cpp:501] detection_eval = 0.0414179
-I0511 11:49:27.151507  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151516  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.151525  4597 caffe.cpp:501] detection_eval = 2.53427
-I0511 11:49:27.151532  4597 caffe.cpp:501] detection_eval = 14.0524
-I0511 11:49:27.151538  4597 caffe.cpp:501] detection_eval = 0.033771
-I0511 11:49:27.151543  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.151547  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.151552  4597 caffe.cpp:501] detection_eval = 2.53629
-I0511 11:49:27.151556  4597 caffe.cpp:501] detection_eval = 14.2319
-I0511 11:49:27.151561  4597 caffe.cpp:501] detection_eval = 0.0354508
-I0511 11:49:27.151566  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151571  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.151576  4597 caffe.cpp:501] detection_eval = 2.53831
-I0511 11:49:27.151581  4597 caffe.cpp:501] detection_eval = 14.6028
-I0511 11:49:27.151584  4597 caffe.cpp:501] detection_eval = 0.0349725
-I0511 11:49:27.151589  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151593  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.151598  4597 caffe.cpp:501] detection_eval = 3.08468
-I0511 11:49:27.151603  4597 caffe.cpp:501] detection_eval = 6.43548
-I0511 11:49:27.151607  4597 caffe.cpp:501] detection_eval = 0.112306
-I0511 11:49:27.151612  4597 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:49:27.151616  4597 caffe.cpp:501] detection_eval = 0.923387
-I0511 11:49:27.151621  4597 caffe.cpp:501] detection_eval = 3.08871
-I0511 11:49:27.151625  4597 caffe.cpp:501] detection_eval = 6.65524
-I0511 11:49:27.151630  4597 caffe.cpp:501] detection_eval = 0.0733243
-I0511 11:49:27.151635  4597 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:49:27.151639  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.151644  4597 caffe.cpp:501] detection_eval = 3.09073
-I0511 11:49:27.151648  4597 caffe.cpp:501] detection_eval = 6.78831
-I0511 11:49:27.151654  4597 caffe.cpp:501] detection_eval = 0.0606407
-I0511 11:49:27.151657  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.151662  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.151666  4597 caffe.cpp:501] detection_eval = 3.09073
-I0511 11:49:27.151671  4597 caffe.cpp:501] detection_eval = 6.91129
-I0511 11:49:27.151675  4597 caffe.cpp:501] detection_eval = 0.0614009
-I0511 11:49:27.151680  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.151685  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.151690  4597 caffe.cpp:501] detection_eval = 3.09073
-I0511 11:49:27.151695  4597 caffe.cpp:501] detection_eval = 7.00202
-I0511 11:49:27.151698  4597 caffe.cpp:501] detection_eval = 0.052092
-I0511 11:49:27.151703  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.151707  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.151712  4597 caffe.cpp:501] detection_eval = 3.09274
-I0511 11:49:27.151717  4597 caffe.cpp:501] detection_eval = 7.06048
-I0511 11:49:27.151721  4597 caffe.cpp:501] detection_eval = 0.0492056
-I0511 11:49:27.151726  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151731  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151736  4597 caffe.cpp:501] detection_eval = 3.09476
-I0511 11:49:27.151739  4597 caffe.cpp:501] detection_eval = 7.12097
-I0511 11:49:27.151744  4597 caffe.cpp:501] detection_eval = 0.0503446
-I0511 11:49:27.151748  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.151753  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.151758  4597 caffe.cpp:501] detection_eval = 3.09879
-I0511 11:49:27.151762  4597 caffe.cpp:501] detection_eval = 7.16935
-I0511 11:49:27.151767  4597 caffe.cpp:501] detection_eval = 0.0471233
-I0511 11:49:27.151772  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151777  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151780  4597 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:49:27.151789  4597 caffe.cpp:501] detection_eval = 7.21371
-I0511 11:49:27.151794  4597 caffe.cpp:501] detection_eval = 0.0537842
-I0511 11:49:27.151798  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.151803  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.151808  4597 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:49:27.151813  4597 caffe.cpp:501] detection_eval = 7.29234
-I0511 11:49:27.151816  4597 caffe.cpp:501] detection_eval = 0.051197
-I0511 11:49:27.151821  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.151825  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.151830  4597 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:49:27.151834  4597 caffe.cpp:501] detection_eval = 7.35484
-I0511 11:49:27.151839  4597 caffe.cpp:501] detection_eval = 0.0515726
-I0511 11:49:27.151844  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.151849  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.151852  4597 caffe.cpp:501] detection_eval = 3.10887
-I0511 11:49:27.151857  4597 caffe.cpp:501] detection_eval = 7.30444
-I0511 11:49:27.151861  4597 caffe.cpp:501] detection_eval = 0.0465375
-I0511 11:49:27.151866  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.151870  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151875  4597 caffe.cpp:501] detection_eval = 3.10887
-I0511 11:49:27.151878  4597 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:49:27.151882  4597 caffe.cpp:501] detection_eval = 0.0428972
-I0511 11:49:27.151886  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151890  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151895  4597 caffe.cpp:501] detection_eval = 3.11089
-I0511 11:49:27.151899  4597 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:49:27.151904  4597 caffe.cpp:501] detection_eval = 0.043998
-I0511 11:49:27.151909  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.151914  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.151918  4597 caffe.cpp:501] detection_eval = 3.11089
-I0511 11:49:27.151923  4597 caffe.cpp:501] detection_eval = 7.50605
-I0511 11:49:27.151927  4597 caffe.cpp:501] detection_eval = 0.0434543
-I0511 11:49:27.151932  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151937  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151942  4597 caffe.cpp:501] detection_eval = 3.1129
-I0511 11:49:27.151947  4597 caffe.cpp:501] detection_eval = 7.52016
-I0511 11:49:27.151950  4597 caffe.cpp:501] detection_eval = 0.0409318
-I0511 11:49:27.151954  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.151959  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151964  4597 caffe.cpp:501] detection_eval = 3.11492
-I0511 11:49:27.151968  4597 caffe.cpp:501] detection_eval = 7.53226
-I0511 11:49:27.151973  4597 caffe.cpp:501] detection_eval = 0.0373753
-I0511 11:49:27.151978  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151983  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151986  4597 caffe.cpp:501] detection_eval = 3.11492
-I0511 11:49:27.151990  4597 caffe.cpp:501] detection_eval = 7.625
-I0511 11:49:27.151995  4597 caffe.cpp:501] detection_eval = 0.0456734
-I0511 11:49:27.152000  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152004  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152009  4597 caffe.cpp:501] detection_eval = 3.11895
-I0511 11:49:27.152014  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.152019  4597 caffe.cpp:501] detection_eval = 0.0405715
-I0511 11:49:27.152022  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152027  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152031  4597 caffe.cpp:501] detection_eval = 3.11895
-I0511 11:49:27.152036  4597 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:49:27.152040  4597 caffe.cpp:501] detection_eval = 0.0450406
-I0511 11:49:27.152045  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152050  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.152055  4597 caffe.cpp:501] detection_eval = 3.12097
-I0511 11:49:27.152062  4597 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:49:27.152067  4597 caffe.cpp:501] detection_eval = 0.0423403
-I0511 11:49:27.152072  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152076  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152081  4597 caffe.cpp:501] detection_eval = 3.12097
-I0511 11:49:27.152086  4597 caffe.cpp:501] detection_eval = 7.85282
-I0511 11:49:27.152091  4597 caffe.cpp:501] detection_eval = 0.0402714
-I0511 11:49:27.152094  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152099  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152103  4597 caffe.cpp:501] detection_eval = 3.125
-I0511 11:49:27.152108  4597 caffe.cpp:501] detection_eval = 7.87097
-I0511 11:49:27.152112  4597 caffe.cpp:501] detection_eval = 0.040527
-I0511 11:49:27.152117  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.152122  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152127  4597 caffe.cpp:501] detection_eval = 3.13508
-I0511 11:49:27.152132  4597 caffe.cpp:501] detection_eval = 7.84879
-I0511 11:49:27.152135  4597 caffe.cpp:501] detection_eval = 0.0440069
-I0511 11:49:27.152140  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152144  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152149  4597 caffe.cpp:501] detection_eval = 3.1371
-I0511 11:49:27.152153  4597 caffe.cpp:501] detection_eval = 7.875
-I0511 11:49:27.152158  4597 caffe.cpp:501] detection_eval = 0.0388546
-I0511 11:49:27.152163  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152168  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152171  4597 caffe.cpp:501] detection_eval = 3.1371
-I0511 11:49:27.152176  4597 caffe.cpp:501] detection_eval = 8
-I0511 11:49:27.152180  4597 caffe.cpp:501] detection_eval = 0.0440461
-I0511 11:49:27.152185  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152189  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152194  4597 caffe.cpp:501] detection_eval = 3.14516
-I0511 11:49:27.152199  4597 caffe.cpp:501] detection_eval = 7.93548
-I0511 11:49:27.152204  4597 caffe.cpp:501] detection_eval = 0.0448261
-I0511 11:49:27.152209  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.152212  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.152217  4597 caffe.cpp:501] detection_eval = 3.14718
-I0511 11:49:27.152220  4597 caffe.cpp:501] detection_eval = 8.02218
-I0511 11:49:27.152225  4597 caffe.cpp:501] detection_eval = 0.0461768
-I0511 11:49:27.152228  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152233  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.152237  4597 caffe.cpp:501] detection_eval = 3.14919
-I0511 11:49:27.152242  4597 caffe.cpp:501] detection_eval = 8.08065
-I0511 11:49:27.152246  4597 caffe.cpp:501] detection_eval = 0.0410155
-I0511 11:49:27.152251  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152256  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152261  4597 caffe.cpp:501] detection_eval = 3.14919
-I0511 11:49:27.152264  4597 caffe.cpp:501] detection_eval = 8.13306
-I0511 11:49:27.152269  4597 caffe.cpp:501] detection_eval = 0.041873
-I0511 11:49:27.152273  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152278  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152283  4597 caffe.cpp:501] detection_eval = 3.15323
-I0511 11:49:27.152287  4597 caffe.cpp:501] detection_eval = 8.14718
-I0511 11:49:27.152292  4597 caffe.cpp:501] detection_eval = 0.0416011
-I0511 11:49:27.152297  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152302  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152307  4597 caffe.cpp:501] detection_eval = 3.15323
-I0511 11:49:27.152310  4597 caffe.cpp:501] detection_eval = 8.23589
-I0511 11:49:27.152315  4597 caffe.cpp:501] detection_eval = 0.0392452
-I0511 11:49:27.152319  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152324  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.152334  4597 caffe.cpp:501] detection_eval = 3.15524
-I0511 11:49:27.152338  4597 caffe.cpp:501] detection_eval = 8.28427
-I0511 11:49:27.152343  4597 caffe.cpp:501] detection_eval = 0.0397426
-I0511 11:49:27.152348  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152351  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152355  4597 caffe.cpp:501] detection_eval = 3.15927
-I0511 11:49:27.152359  4597 caffe.cpp:501] detection_eval = 8.3125
-I0511 11:49:27.152362  4597 caffe.cpp:501] detection_eval = 0.0466889
-I0511 11:49:27.152366  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152370  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.152374  4597 caffe.cpp:501] detection_eval = 3.16129
-I0511 11:49:27.152379  4597 caffe.cpp:501] detection_eval = 8.3125
-I0511 11:49:27.152381  4597 caffe.cpp:501] detection_eval = 0.0369168
-I0511 11:49:27.152385  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.152390  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.152393  4597 caffe.cpp:501] detection_eval = 3.16129
-I0511 11:49:27.152396  4597 caffe.cpp:501] detection_eval = 8.35685
-I0511 11:49:27.152400  4597 caffe.cpp:501] detection_eval = 0.0391665
-I0511 11:49:27.152405  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152408  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152411  4597 caffe.cpp:501] detection_eval = 3.16129
-I0511 11:49:27.152415  4597 caffe.cpp:501] detection_eval = 8.42137
-I0511 11:49:27.152420  4597 caffe.cpp:501] detection_eval = 0.0390195
-I0511 11:49:27.152422  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.152426  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152431  4597 caffe.cpp:501] detection_eval = 3.16532
-I0511 11:49:27.152433  4597 caffe.cpp:501] detection_eval = 8.48185
-I0511 11:49:27.152437  4597 caffe.cpp:501] detection_eval = 0.0436286
-I0511 11:49:27.152441  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152444  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152448  4597 caffe.cpp:501] detection_eval = 3.16734
-I0511 11:49:27.152452  4597 caffe.cpp:501] detection_eval = 8.51008
-I0511 11:49:27.152456  4597 caffe.cpp:501] detection_eval = 0.0411691
-I0511 11:49:27.152459  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152463  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152467  4597 caffe.cpp:501] detection_eval = 3.16935
-I0511 11:49:27.152470  4597 caffe.cpp:501] detection_eval = 8.52621
-I0511 11:49:27.152474  4597 caffe.cpp:501] detection_eval = 0.0441648
-I0511 11:49:27.152477  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.152482  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.152485  4597 caffe.cpp:501] detection_eval = 3.16935
-I0511 11:49:27.152489  4597 caffe.cpp:501] detection_eval = 8.60685
-I0511 11:49:27.152493  4597 caffe.cpp:501] detection_eval = 0.0394599
-I0511 11:49:27.152496  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152499  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152503  4597 caffe.cpp:501] detection_eval = 3.17742
-I0511 11:49:27.152508  4597 caffe.cpp:501] detection_eval = 8.5625
-I0511 11:49:27.152510  4597 caffe.cpp:501] detection_eval = 0.0389344
-I0511 11:49:27.152514  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152518  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152521  4597 caffe.cpp:501] detection_eval = 3.17944
-I0511 11:49:27.152530  4597 caffe.cpp:501] detection_eval = 8.62298
-I0511 11:49:27.152534  4597 caffe.cpp:501] detection_eval = 0.0426356
-I0511 11:49:27.152537  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152541  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152545  4597 caffe.cpp:501] detection_eval = 3.18548
-I0511 11:49:27.152549  4597 caffe.cpp:501] detection_eval = 8.57056
-I0511 11:49:27.152552  4597 caffe.cpp:501] detection_eval = 0.0415749
-I0511 11:49:27.152556  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152560  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152570  4597 caffe.cpp:501] detection_eval = 3.18952
-I0511 11:49:27.152573  4597 caffe.cpp:501] detection_eval = 8.55645
-I0511 11:49:27.152577  4597 caffe.cpp:501] detection_eval = 0.0385256
-I0511 11:49:27.152585  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152590  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152593  4597 caffe.cpp:501] detection_eval = 3.18952
-I0511 11:49:27.152597  4597 caffe.cpp:501] detection_eval = 8.625
-I0511 11:49:27.152601  4597 caffe.cpp:501] detection_eval = 0.0368843
-I0511 11:49:27.152604  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.152608  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152612  4597 caffe.cpp:501] detection_eval = 3.19556
-I0511 11:49:27.152616  4597 caffe.cpp:501] detection_eval = 8.625
-I0511 11:49:27.152619  4597 caffe.cpp:501] detection_eval = 0.0435754
-I0511 11:49:27.152623  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152627  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152631  4597 caffe.cpp:501] detection_eval = 3.20161
-I0511 11:49:27.152634  4597 caffe.cpp:501] detection_eval = 8.61089
-I0511 11:49:27.152637  4597 caffe.cpp:501] detection_eval = 0.043302
-I0511 11:49:27.152639  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152642  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152645  4597 caffe.cpp:501] detection_eval = 3.20565
-I0511 11:49:27.152649  4597 caffe.cpp:501] detection_eval = 8.6371
-I0511 11:49:27.152652  4597 caffe.cpp:501] detection_eval = 0.0506126
-I0511 11:49:27.152657  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.152659  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152663  4597 caffe.cpp:501] detection_eval = 3.20766
-I0511 11:49:27.152667  4597 caffe.cpp:501] detection_eval = 8.68347
-I0511 11:49:27.152671  4597 caffe.cpp:501] detection_eval = 0.0452079
-I0511 11:49:27.152674  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152678  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152683  4597 caffe.cpp:501] detection_eval = 3.20968
-I0511 11:49:27.152686  4597 caffe.cpp:501] detection_eval = 8.76613
-I0511 11:49:27.152689  4597 caffe.cpp:501] detection_eval = 0.0383057
-I0511 11:49:27.152693  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152698  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.152700  4597 caffe.cpp:501] detection_eval = 3.21169
-I0511 11:49:27.152704  4597 caffe.cpp:501] detection_eval = 8.83266
-I0511 11:49:27.152709  4597 caffe.cpp:501] detection_eval = 0.0444229
-I0511 11:49:27.152712  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152715  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152719  4597 caffe.cpp:501] detection_eval = 3.21774
-I0511 11:49:27.152724  4597 caffe.cpp:501] detection_eval = 8.86492
-I0511 11:49:27.152727  4597 caffe.cpp:501] detection_eval = 0.0452755
-I0511 11:49:27.152730  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152734  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152739  4597 caffe.cpp:501] detection_eval = 3.21774
-I0511 11:49:27.152742  4597 caffe.cpp:501] detection_eval = 8.95968
-I0511 11:49:27.152746  4597 caffe.cpp:501] detection_eval = 0.0407374
-I0511 11:49:27.152750  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152753  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152757  4597 caffe.cpp:501] detection_eval = 3.22177
-I0511 11:49:27.152761  4597 caffe.cpp:501] detection_eval = 9.01411
-I0511 11:49:27.152765  4597 caffe.cpp:501] detection_eval = 0.0426849
-I0511 11:49:27.152768  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152772  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152776  4597 caffe.cpp:501] detection_eval = 3.22177
-I0511 11:49:27.152781  4597 caffe.cpp:501] detection_eval = 9.05847
-I0511 11:49:27.152783  4597 caffe.cpp:501] detection_eval = 0.0415161
-I0511 11:49:27.152787  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152796  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152801  4597 caffe.cpp:501] detection_eval = 3.22379
-I0511 11:49:27.152803  4597 caffe.cpp:501] detection_eval = 9.1371
-I0511 11:49:27.152807  4597 caffe.cpp:501] detection_eval = 0.0415253
-I0511 11:49:27.152812  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152815  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152818  4597 caffe.cpp:501] detection_eval = 3.22581
-I0511 11:49:27.152822  4597 caffe.cpp:501] detection_eval = 9.16532
-I0511 11:49:27.152827  4597 caffe.cpp:501] detection_eval = 0.0399029
-I0511 11:49:27.152829  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152833  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152837  4597 caffe.cpp:501] detection_eval = 3.22984
-I0511 11:49:27.152840  4597 caffe.cpp:501] detection_eval = 9.20766
-I0511 11:49:27.152844  4597 caffe.cpp:501] detection_eval = 0.044318
-I0511 11:49:27.152848  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152853  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152856  4597 caffe.cpp:501] detection_eval = 3.23185
-I0511 11:49:27.152860  4597 caffe.cpp:501] detection_eval = 9.27621
-I0511 11:49:27.152863  4597 caffe.cpp:501] detection_eval = 0.0447398
-I0511 11:49:27.152866  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152869  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152873  4597 caffe.cpp:501] detection_eval = 3.23185
-I0511 11:49:27.152875  4597 caffe.cpp:501] detection_eval = 9.37298
-I0511 11:49:27.152878  4597 caffe.cpp:501] detection_eval = 0.036686
-I0511 11:49:27.152881  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152884  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152887  4597 caffe.cpp:501] detection_eval = 3.23185
-I0511 11:49:27.152891  4597 caffe.cpp:501] detection_eval = 9.43145
-I0511 11:49:27.152894  4597 caffe.cpp:501] detection_eval = 0.0405621
-I0511 11:49:27.152897  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152900  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152904  4597 caffe.cpp:501] detection_eval = 3.23387
-I0511 11:49:27.152906  4597 caffe.cpp:501] detection_eval = 9.52016
-I0511 11:49:27.152909  4597 caffe.cpp:501] detection_eval = 0.0485003
-I0511 11:49:27.152912  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152916  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152920  4597 caffe.cpp:501] detection_eval = 3.2379
-I0511 11:49:27.152922  4597 caffe.cpp:501] detection_eval = 9.55242
-I0511 11:49:27.152925  4597 caffe.cpp:501] detection_eval = 0.046264
-I0511 11:49:27.152928  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.152931  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.152935  4597 caffe.cpp:501] detection_eval = 3.23992
-I0511 11:49:27.152938  4597 caffe.cpp:501] detection_eval = 9.61694
-I0511 11:49:27.152941  4597 caffe.cpp:501] detection_eval = 0.045028
-I0511 11:49:27.152945  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152947  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152951  4597 caffe.cpp:501] detection_eval = 3.24395
-I0511 11:49:27.152954  4597 caffe.cpp:501] detection_eval = 9.64113
-I0511 11:49:27.152957  4597 caffe.cpp:501] detection_eval = 0.0462392
-I0511 11:49:27.152961  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152963  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152966  4597 caffe.cpp:501] detection_eval = 3.24597
-I0511 11:49:27.152971  4597 caffe.cpp:501] detection_eval = 9.6875
-I0511 11:49:27.152973  4597 caffe.cpp:501] detection_eval = 0.0422627
-I0511 11:49:27.152976  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152979  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152982  4597 caffe.cpp:501] detection_eval = 3.25
-I0511 11:49:27.152987  4597 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:49:27.152989  4597 caffe.cpp:501] detection_eval = 0.0485173
-I0511 11:49:27.152992  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153002  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.153005  4597 caffe.cpp:501] detection_eval = 3.25
-I0511 11:49:27.153008  4597 caffe.cpp:501] detection_eval = 9.77621
-I0511 11:49:27.153012  4597 caffe.cpp:501] detection_eval = 0.0414143
-I0511 11:49:27.153015  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153018  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153021  4597 caffe.cpp:501] detection_eval = 3.25403
-I0511 11:49:27.153024  4597 caffe.cpp:501] detection_eval = 9.79032
-I0511 11:49:27.153028  4597 caffe.cpp:501] detection_eval = 0.0382315
-I0511 11:49:27.153031  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.153034  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153038  4597 caffe.cpp:501] detection_eval = 3.25403
-I0511 11:49:27.153040  4597 caffe.cpp:501] detection_eval = 9.91532
-I0511 11:49:27.153043  4597 caffe.cpp:501] detection_eval = 0.0424618
-I0511 11:49:27.153046  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153050  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153053  4597 caffe.cpp:501] detection_eval = 3.25403
-I0511 11:49:27.153056  4597 caffe.cpp:501] detection_eval = 10.002
-I0511 11:49:27.153060  4597 caffe.cpp:501] detection_eval = 0.0471143
-I0511 11:49:27.153064  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153066  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153069  4597 caffe.cpp:501] detection_eval = 3.25605
-I0511 11:49:27.153072  4597 caffe.cpp:501] detection_eval = 10.0544
-I0511 11:49:27.153076  4597 caffe.cpp:501] detection_eval = 0.0453307
-I0511 11:49:27.153079  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153082  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153085  4597 caffe.cpp:501] detection_eval = 3.26008
-I0511 11:49:27.153089  4597 caffe.cpp:501] detection_eval = 10.129
-I0511 11:49:27.153091  4597 caffe.cpp:501] detection_eval = 0.0452135
-I0511 11:49:27.153095  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153098  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153102  4597 caffe.cpp:501] detection_eval = 3.26613
-I0511 11:49:27.153106  4597 caffe.cpp:501] detection_eval = 10.1512
-I0511 11:49:27.153111  4597 caffe.cpp:501] detection_eval = 0.0456583
-I0511 11:49:27.153115  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153120  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153123  4597 caffe.cpp:501] detection_eval = 3.26613
-I0511 11:49:27.153128  4597 caffe.cpp:501] detection_eval = 10.2782
-I0511 11:49:27.153132  4597 caffe.cpp:501] detection_eval = 0.0444525
-I0511 11:49:27.153137  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153141  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153144  4597 caffe.cpp:501] detection_eval = 3.27218
-I0511 11:49:27.153148  4597 caffe.cpp:501] detection_eval = 10.248
-I0511 11:49:27.153151  4597 caffe.cpp:501] detection_eval = 0.0425943
-I0511 11:49:27.153156  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.153159  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.153162  4597 caffe.cpp:501] detection_eval = 3.28024
-I0511 11:49:27.153165  4597 caffe.cpp:501] detection_eval = 10.1694
-I0511 11:49:27.153169  4597 caffe.cpp:501] detection_eval = 0.0454558
-I0511 11:49:27.153174  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153177  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153182  4597 caffe.cpp:501] detection_eval = 3.28226
-I0511 11:49:27.153185  4597 caffe.cpp:501] detection_eval = 10.1976
-I0511 11:49:27.153188  4597 caffe.cpp:501] detection_eval = 0.0412913
-I0511 11:49:27.153192  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153195  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153199  4597 caffe.cpp:501] detection_eval = 3.28629
-I0511 11:49:27.153203  4597 caffe.cpp:501] detection_eval = 10.1754
-I0511 11:49:27.153206  4597 caffe.cpp:501] detection_eval = 0.0441255
-I0511 11:49:27.153213  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.153218  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.153223  4597 caffe.cpp:501] detection_eval = 3.28831
-I0511 11:49:27.153228  4597 caffe.cpp:501] detection_eval = 10.1976
-I0511 11:49:27.153231  4597 caffe.cpp:501] detection_eval = 0.0426045
-I0511 11:49:27.153235  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153240  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153244  4597 caffe.cpp:501] detection_eval = 3.29234
-I0511 11:49:27.153247  4597 caffe.cpp:501] detection_eval = 10.2198
-I0511 11:49:27.153250  4597 caffe.cpp:501] detection_eval = 0.0416863
-I0511 11:49:27.153254  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153257  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153261  4597 caffe.cpp:501] detection_eval = 3.29435
-I0511 11:49:27.153265  4597 caffe.cpp:501] detection_eval = 10.2883
-I0511 11:49:27.153270  4597 caffe.cpp:501] detection_eval = 0.049003
-I0511 11:49:27.153272  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153275  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153280  4597 caffe.cpp:501] detection_eval = 3.29839
-I0511 11:49:27.153282  4597 caffe.cpp:501] detection_eval = 10.3226
-I0511 11:49:27.153285  4597 caffe.cpp:501] detection_eval = 0.0428636
-I0511 11:49:27.153290  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153292  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153296  4597 caffe.cpp:501] detection_eval = 3.30444
-I0511 11:49:27.153300  4597 caffe.cpp:501] detection_eval = 10.3065
-I0511 11:49:27.153302  4597 caffe.cpp:501] detection_eval = 0.0454338
-I0511 11:49:27.153306  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153309  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153312  4597 caffe.cpp:501] detection_eval = 3.30645
-I0511 11:49:27.153316  4597 caffe.cpp:501] detection_eval = 10.3407
-I0511 11:49:27.153319  4597 caffe.cpp:501] detection_eval = 0.040954
-I0511 11:49:27.153323  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153326  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153329  4597 caffe.cpp:501] detection_eval = 3.30847
-I0511 11:49:27.153333  4597 caffe.cpp:501] detection_eval = 10.4093
-I0511 11:49:27.153337  4597 caffe.cpp:501] detection_eval = 0.0444435
-I0511 11:49:27.153340  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.153343  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153347  4597 caffe.cpp:501] detection_eval = 3.31653
-I0511 11:49:27.153349  4597 caffe.cpp:501] detection_eval = 10.3851
-I0511 11:49:27.153353  4597 caffe.cpp:501] detection_eval = 0.0424642
-I0511 11:49:27.153357  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153360  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153363  4597 caffe.cpp:501] detection_eval = 3.31855
-I0511 11:49:27.153367  4597 caffe.cpp:501] detection_eval = 10.4496
-I0511 11:49:27.153370  4597 caffe.cpp:501] detection_eval = 0.0432248
-I0511 11:49:27.153373  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.153378  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.153383  4597 caffe.cpp:501] detection_eval = 3.31855
-I0511 11:49:27.153385  4597 caffe.cpp:501] detection_eval = 10.5343
-I0511 11:49:27.153389  4597 caffe.cpp:501] detection_eval = 0.046504
-I0511 11:49:27.153393  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153395  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153398  4597 caffe.cpp:501] detection_eval = 3.32056
-I0511 11:49:27.153403  4597 caffe.cpp:501] detection_eval = 10.5383
-I0511 11:49:27.153405  4597 caffe.cpp:501] detection_eval = 0.0392196
-I0511 11:49:27.153409  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153412  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153415  4597 caffe.cpp:501] detection_eval = 3.32661
-I0511 11:49:27.153419  4597 caffe.cpp:501] detection_eval = 10.4778
-I0511 11:49:27.153422  4597 caffe.cpp:501] detection_eval = 0.048008
-I0511 11:49:27.153429  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153434  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.153436  4597 caffe.cpp:501] detection_eval = 3.32863
-I0511 11:49:27.153439  4597 caffe.cpp:501] detection_eval = 10.5121
-I0511 11:49:27.153443  4597 caffe.cpp:501] detection_eval = 0.0472867
-I0511 11:49:27.153446  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153450  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153453  4597 caffe.cpp:501] detection_eval = 3.33266
-I0511 11:49:27.153456  4597 caffe.cpp:501] detection_eval = 10.5
-I0511 11:49:27.153460  4597 caffe.cpp:501] detection_eval = 0.0381142
-I0511 11:49:27.153463  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153466  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153470  4597 caffe.cpp:501] detection_eval = 3.33266
-I0511 11:49:27.153473  4597 caffe.cpp:501] detection_eval = 10.5645
-I0511 11:49:27.153476  4597 caffe.cpp:501] detection_eval = 0.042484
-I0511 11:49:27.153479  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153482  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153486  4597 caffe.cpp:501] detection_eval = 3.33468
-I0511 11:49:27.153489  4597 caffe.cpp:501] detection_eval = 10.5827
-I0511 11:49:27.153492  4597 caffe.cpp:501] detection_eval = 0.0410557
-I0511 11:49:27.153496  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153499  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.153502  4597 caffe.cpp:501] detection_eval = 3.33871
-I0511 11:49:27.153506  4597 caffe.cpp:501] detection_eval = 10.5806
-I0511 11:49:27.153508  4597 caffe.cpp:501] detection_eval = 0.0408412
-I0511 11:49:27.153512  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153515  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153519  4597 caffe.cpp:501] detection_eval = 3.34073
-I0511 11:49:27.153522  4597 caffe.cpp:501] detection_eval = 10.623
-I0511 11:49:27.153525  4597 caffe.cpp:501] detection_eval = 0.0379402
-I0511 11:49:27.153529  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.153532  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.153535  4597 caffe.cpp:501] detection_eval = 3.34274
-I0511 11:49:27.153539  4597 caffe.cpp:501] detection_eval = 10.6673
-I0511 11:49:27.153542  4597 caffe.cpp:501] detection_eval = 0.0444984
-I0511 11:49:27.153547  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.153549  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153553  4597 caffe.cpp:501] detection_eval = 3.34274
-I0511 11:49:27.153555  4597 caffe.cpp:501] detection_eval = 10.7137
-I0511 11:49:27.153558  4597 caffe.cpp:501] detection_eval = 0.0387068
-I0511 11:49:27.153563  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153565  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153568  4597 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:49:27.153573  4597 caffe.cpp:501] detection_eval = 10.7883
-I0511 11:49:27.153578  4597 caffe.cpp:501] detection_eval = 0.0405686
-I0511 11:49:27.153583  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.153587  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153591  4597 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:49:27.153595  4597 caffe.cpp:501] detection_eval = 10.8589
-I0511 11:49:27.153599  4597 caffe.cpp:501] detection_eval = 0.0389239
-I0511 11:49:27.153604  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153606  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153609  4597 caffe.cpp:501] detection_eval = 3.34879
-I0511 11:49:27.153614  4597 caffe.cpp:501] detection_eval = 10.8972
-I0511 11:49:27.153616  4597 caffe.cpp:501] detection_eval = 0.0452635
-I0511 11:49:27.153620  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.153625  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153628  4597 caffe.cpp:501] detection_eval = 3.35484
-I0511 11:49:27.153632  4597 caffe.cpp:501] detection_eval = 10.871
-I0511 11:49:27.153641  4597 caffe.cpp:501] detection_eval = 0.0455467
-I0511 11:49:27.153647  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153651  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153656  4597 caffe.cpp:501] detection_eval = 3.35887
-I0511 11:49:27.153659  4597 caffe.cpp:501] detection_eval = 10.9214
-I0511 11:49:27.153663  4597 caffe.cpp:501] detection_eval = 0.0479988
-I0511 11:49:27.153667  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153671  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.153674  4597 caffe.cpp:501] detection_eval = 3.36089
-I0511 11:49:27.153679  4597 caffe.cpp:501] detection_eval = 10.9395
-I0511 11:49:27.153683  4597 caffe.cpp:501] detection_eval = 0.0459227
-I0511 11:49:27.153687  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.153690  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.153694  4597 caffe.cpp:501] detection_eval = 3.3629
-I0511 11:49:27.153698  4597 caffe.cpp:501] detection_eval = 10.998
-I0511 11:49:27.153702  4597 caffe.cpp:501] detection_eval = 0.0506618
-I0511 11:49:27.153707  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.153710  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.153713  4597 caffe.cpp:501] detection_eval = 3.36492
-I0511 11:49:27.153717  4597 caffe.cpp:501] detection_eval = 11.0202
-I0511 11:49:27.153722  4597 caffe.cpp:501] detection_eval = 0.043561
-I0511 11:49:27.153725  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153729  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153733  4597 caffe.cpp:501] detection_eval = 3.37097
-I0511 11:49:27.153738  4597 caffe.cpp:501] detection_eval = 11
-I0511 11:49:27.153741  4597 caffe.cpp:501] detection_eval = 0.0421032
-I0511 11:49:27.153745  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.153748  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.153753  4597 caffe.cpp:501] detection_eval = 3.37298
-I0511 11:49:27.153756  4597 caffe.cpp:501] detection_eval = 11.0222
-I0511 11:49:27.153760  4597 caffe.cpp:501] detection_eval = 0.0413465
-I0511 11:49:27.153764  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153769  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153771  4597 caffe.cpp:501] detection_eval = 3.37298
-I0511 11:49:27.153775  4597 caffe.cpp:501] detection_eval = 11.1069
-I0511 11:49:27.153779  4597 caffe.cpp:501] detection_eval = 0.0478731
-I0511 11:49:27.153784  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153787  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153790  4597 caffe.cpp:501] detection_eval = 3.37298
-I0511 11:49:27.153795  4597 caffe.cpp:501] detection_eval = 11.1331
-I0511 11:49:27.153798  4597 caffe.cpp:501] detection_eval = 0.0393092
-I0511 11:49:27.153802  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153805  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.153810  4597 caffe.cpp:501] detection_eval = 3.37298
-I0511 11:49:27.153813  4597 caffe.cpp:501] detection_eval = 11.1956
-I0511 11:49:27.153817  4597 caffe.cpp:501] detection_eval = 0.0357141
-I0511 11:49:27.153821  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153825  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153828  4597 caffe.cpp:501] detection_eval = 3.375
-I0511 11:49:27.153832  4597 caffe.cpp:501] detection_eval = 11.256
-I0511 11:49:27.153836  4597 caffe.cpp:501] detection_eval = 0.0397309
-I0511 11:49:27.153841  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.153843  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153847  4597 caffe.cpp:501] detection_eval = 3.37702
-I0511 11:49:27.153851  4597 caffe.cpp:501] detection_eval = 11.2863
-I0511 11:49:27.153856  4597 caffe.cpp:501] detection_eval = 0.0429492
-I0511 11:49:27.153858  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153862  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153867  4597 caffe.cpp:501] detection_eval = 3.37702
-I0511 11:49:27.153873  4597 caffe.cpp:501] detection_eval = 11.3871
-I0511 11:49:27.153877  4597 caffe.cpp:501] detection_eval = 0.0470726
-I0511 11:49:27.153882  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153885  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153888  4597 caffe.cpp:501] detection_eval = 3.37903
-I0511 11:49:27.153892  4597 caffe.cpp:501] detection_eval = 11.4577
-I0511 11:49:27.153897  4597 caffe.cpp:501] detection_eval = 0.0455222
-I0511 11:49:27.153899  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153903  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153908  4597 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:49:27.153910  4597 caffe.cpp:501] detection_eval = 11.496
-I0511 11:49:27.153914  4597 caffe.cpp:501] detection_eval = 0.0377702
-I0511 11:49:27.153918  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153923  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153926  4597 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:49:27.153929  4597 caffe.cpp:501] detection_eval = 11.6129
-I0511 11:49:27.153934  4597 caffe.cpp:501] detection_eval = 0.0432228
-I0511 11:49:27.153937  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153941  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153944  4597 caffe.cpp:501] detection_eval = 3.38508
-I0511 11:49:27.153949  4597 caffe.cpp:501] detection_eval = 11.6472
-I0511 11:49:27.153952  4597 caffe.cpp:501] detection_eval = 0.0457813
-I0511 11:49:27.153956  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.153960  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153964  4597 caffe.cpp:501] detection_eval = 3.3871
-I0511 11:49:27.153967  4597 caffe.cpp:501] detection_eval = 11.6754
-I0511 11:49:27.153971  4597 caffe.cpp:501] detection_eval = 0.0452665
-I0511 11:49:27.153975  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153978  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153982  4597 caffe.cpp:501] detection_eval = 3.38911
-I0511 11:49:27.153986  4597 caffe.cpp:501] detection_eval = 11.7379
-I0511 11:49:27.153990  4597 caffe.cpp:501] detection_eval = 0.0458116
-I0511 11:49:27.153993  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153997  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.154001  4597 caffe.cpp:501] detection_eval = 3.39315
-I0511 11:49:27.154004  4597 caffe.cpp:501] detection_eval = 11.7742
-I0511 11:49:27.154008  4597 caffe.cpp:501] detection_eval = 0.042421
-I0511 11:49:27.154012  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154016  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.154019  4597 caffe.cpp:501] detection_eval = 3.39919
-I0511 11:49:27.154023  4597 caffe.cpp:501] detection_eval = 11.8468
-I0511 11:49:27.154027  4597 caffe.cpp:501] detection_eval = 0.0538771
-I0511 11:49:27.154031  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.154034  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.154038  4597 caffe.cpp:501] detection_eval = 3.40323
-I0511 11:49:27.154042  4597 caffe.cpp:501] detection_eval = 11.8548
-I0511 11:49:27.154047  4597 caffe.cpp:501] detection_eval = 0.0412682
-I0511 11:49:27.154050  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154053  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154057  4597 caffe.cpp:501] detection_eval = 3.40726
-I0511 11:49:27.154062  4597 caffe.cpp:501] detection_eval = 11.8468
-I0511 11:49:27.154065  4597 caffe.cpp:501] detection_eval = 0.0429546
-I0511 11:49:27.154069  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154073  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154076  4597 caffe.cpp:501] detection_eval = 3.40726
-I0511 11:49:27.154080  4597 caffe.cpp:501] detection_eval = 11.8891
-I0511 11:49:27.154084  4597 caffe.cpp:501] detection_eval = 0.0432336
-I0511 11:49:27.154088  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154093  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154095  4597 caffe.cpp:501] detection_eval = 3.40927
-I0511 11:49:27.154103  4597 caffe.cpp:501] detection_eval = 11.9395
-I0511 11:49:27.154109  4597 caffe.cpp:501] detection_eval = 0.03952
-I0511 11:49:27.154111  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154115  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154119  4597 caffe.cpp:501] detection_eval = 3.40927
-I0511 11:49:27.154124  4597 caffe.cpp:501] detection_eval = 11.9819
-I0511 11:49:27.154127  4597 caffe.cpp:501] detection_eval = 0.0377363
-I0511 11:49:27.154131  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154135  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154139  4597 caffe.cpp:501] detection_eval = 3.40927
-I0511 11:49:27.154142  4597 caffe.cpp:501] detection_eval = 12.0444
-I0511 11:49:27.154146  4597 caffe.cpp:501] detection_eval = 0.040587
-I0511 11:49:27.154150  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154155  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154157  4597 caffe.cpp:501] detection_eval = 3.41734
-I0511 11:49:27.154161  4597 caffe.cpp:501] detection_eval = 11.9899
-I0511 11:49:27.154165  4597 caffe.cpp:501] detection_eval = 0.0405691
-I0511 11:49:27.154170  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154173  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154176  4597 caffe.cpp:501] detection_eval = 3.41935
-I0511 11:49:27.154181  4597 caffe.cpp:501] detection_eval = 12.0101
-I0511 11:49:27.154184  4597 caffe.cpp:501] detection_eval = 0.0373197
-I0511 11:49:27.154188  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154192  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154196  4597 caffe.cpp:501] detection_eval = 3.42137
-I0511 11:49:27.154199  4597 caffe.cpp:501] detection_eval = 12.0383
-I0511 11:49:27.154203  4597 caffe.cpp:501] detection_eval = 0.0420197
-I0511 11:49:27.154207  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154211  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154214  4597 caffe.cpp:501] detection_eval = 3.42742
-I0511 11:49:27.154218  4597 caffe.cpp:501] detection_eval = 11.9919
-I0511 11:49:27.154222  4597 caffe.cpp:501] detection_eval = 0.0407463
-I0511 11:49:27.154227  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154229  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154233  4597 caffe.cpp:501] detection_eval = 3.43145
-I0511 11:49:27.154237  4597 caffe.cpp:501] detection_eval = 12.0121
-I0511 11:49:27.154242  4597 caffe.cpp:501] detection_eval = 0.0429001
-I0511 11:49:27.154245  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.154248  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.154253  4597 caffe.cpp:501] detection_eval = 3.43347
-I0511 11:49:27.154256  4597 caffe.cpp:501] detection_eval = 12.0242
-I0511 11:49:27.154260  4597 caffe.cpp:501] detection_eval = 0.0425635
-I0511 11:49:27.154265  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154268  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154273  4597 caffe.cpp:501] detection_eval = 3.43548
-I0511 11:49:27.154276  4597 caffe.cpp:501] detection_eval = 12.0645
-I0511 11:49:27.154280  4597 caffe.cpp:501] detection_eval = 0.0406314
-I0511 11:49:27.154284  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154287  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154291  4597 caffe.cpp:501] detection_eval = 3.43952
-I0511 11:49:27.154295  4597 caffe.cpp:501] detection_eval = 12.0706
-I0511 11:49:27.154299  4597 caffe.cpp:501] detection_eval = 0.0404113
-I0511 11:49:27.154304  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154307  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154311  4597 caffe.cpp:501] detection_eval = 3.4496
-I0511 11:49:27.154315  4597 caffe.cpp:501] detection_eval = 11.998
-I0511 11:49:27.154320  4597 caffe.cpp:501] detection_eval = 0.0431162
-I0511 11:49:27.154323  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154327  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.154336  4597 caffe.cpp:501] detection_eval = 3.45161
-I0511 11:49:27.154340  4597 caffe.cpp:501] detection_eval = 12.0383
-I0511 11:49:27.154345  4597 caffe.cpp:501] detection_eval = 0.0391035
-I0511 11:49:27.154348  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154352  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154356  4597 caffe.cpp:501] detection_eval = 3.45766
-I0511 11:49:27.154359  4597 caffe.cpp:501] detection_eval = 12.0444
-I0511 11:49:27.154363  4597 caffe.cpp:501] detection_eval = 0.0427302
-I0511 11:49:27.154367  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.154371  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.154376  4597 caffe.cpp:501] detection_eval = 3.45968
-I0511 11:49:27.154378  4597 caffe.cpp:501] detection_eval = 12.0907
-I0511 11:49:27.154382  4597 caffe.cpp:501] detection_eval = 0.0453491
-I0511 11:49:27.154386  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154390  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154394  4597 caffe.cpp:501] detection_eval = 3.46169
-I0511 11:49:27.154397  4597 caffe.cpp:501] detection_eval = 12.123
-I0511 11:49:27.154402  4597 caffe.cpp:501] detection_eval = 0.0436261
-I0511 11:49:27.154405  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154409  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154413  4597 caffe.cpp:501] detection_eval = 3.46976
-I0511 11:49:27.154417  4597 caffe.cpp:501] detection_eval = 12.0403
-I0511 11:49:27.154420  4597 caffe.cpp:501] detection_eval = 0.041762
-I0511 11:49:27.154424  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154428  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.154431  4597 caffe.cpp:501] detection_eval = 3.47782
-I0511 11:49:27.154435  4597 caffe.cpp:501] detection_eval = 11.9496
-I0511 11:49:27.154439  4597 caffe.cpp:501] detection_eval = 0.0373443
-I0511 11:49:27.154443  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154446  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154450  4597 caffe.cpp:501] detection_eval = 3.47984
-I0511 11:49:27.154454  4597 caffe.cpp:501] detection_eval = 11.994
-I0511 11:49:27.154458  4597 caffe.cpp:501] detection_eval = 0.0407181
-I0511 11:49:27.154462  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154466  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154469  4597 caffe.cpp:501] detection_eval = 3.47984
-I0511 11:49:27.154474  4597 caffe.cpp:501] detection_eval = 12.0524
-I0511 11:49:27.154477  4597 caffe.cpp:501] detection_eval = 0.0409062
-I0511 11:49:27.154481  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154485  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.154489  4597 caffe.cpp:501] detection_eval = 3.48185
-I0511 11:49:27.154492  4597 caffe.cpp:501] detection_eval = 12.0726
-I0511 11:49:27.154497  4597 caffe.cpp:501] detection_eval = 0.0378516
-I0511 11:49:27.154500  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154505  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154508  4597 caffe.cpp:501] detection_eval = 3.48185
-I0511 11:49:27.154512  4597 caffe.cpp:501] detection_eval = 12.1815
-I0511 11:49:27.154516  4597 caffe.cpp:501] detection_eval = 0.0447198
-I0511 11:49:27.154520  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154525  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154527  4597 caffe.cpp:501] detection_eval = 3.48185
-I0511 11:49:27.154531  4597 caffe.cpp:501] detection_eval = 12.2056
-I0511 11:49:27.154536  4597 caffe.cpp:501] detection_eval = 0.0356161
-I0511 11:49:27.154539  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154543  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154546  4597 caffe.cpp:501] detection_eval = 3.48387
-I0511 11:49:27.154551  4597 caffe.cpp:501] detection_eval = 12.2621
-I0511 11:49:27.154554  4597 caffe.cpp:501] detection_eval = 0.0392694
-I0511 11:49:27.154558  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154561  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154569  4597 caffe.cpp:501] detection_eval = 3.48589
-I0511 11:49:27.154573  4597 caffe.cpp:501] detection_eval = 12.3206
-I0511 11:49:27.154577  4597 caffe.cpp:501] detection_eval = 0.0422359
-I0511 11:49:27.154580  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154584  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154588  4597 caffe.cpp:501] detection_eval = 3.49194
-I0511 11:49:27.154592  4597 caffe.cpp:501] detection_eval = 12.3024
-I0511 11:49:27.154597  4597 caffe.cpp:501] detection_eval = 0.0398411
-I0511 11:49:27.154599  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154603  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154608  4597 caffe.cpp:501] detection_eval = 3.49395
-I0511 11:49:27.154610  4597 caffe.cpp:501] detection_eval = 12.3508
-I0511 11:49:27.154614  4597 caffe.cpp:501] detection_eval = 0.0360825
-I0511 11:49:27.154618  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.154623  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154626  4597 caffe.cpp:501] detection_eval = 3.49395
-I0511 11:49:27.154629  4597 caffe.cpp:501] detection_eval = 12.4153
-I0511 11:49:27.154633  4597 caffe.cpp:501] detection_eval = 0.0379566
-I0511 11:49:27.154637  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154641  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154645  4597 caffe.cpp:501] detection_eval = 3.5
-I0511 11:49:27.154649  4597 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:49:27.154654  4597 caffe.cpp:501] detection_eval = 0.0408221
-I0511 11:49:27.154657  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154660  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154664  4597 caffe.cpp:501] detection_eval = 3.50806
-I0511 11:49:27.154669  4597 caffe.cpp:501] detection_eval = 12.3569
-I0511 11:49:27.154672  4597 caffe.cpp:501] detection_eval = 0.0385258
-I0511 11:49:27.154675  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154680  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154683  4597 caffe.cpp:501] detection_eval = 3.51008
-I0511 11:49:27.154687  4597 caffe.cpp:501] detection_eval = 12.371
-I0511 11:49:27.154691  4597 caffe.cpp:501] detection_eval = 0.0400125
-I0511 11:49:27.154695  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154698  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154702  4597 caffe.cpp:501] detection_eval = 3.5121
-I0511 11:49:27.154706  4597 caffe.cpp:501] detection_eval = 12.4173
-I0511 11:49:27.154711  4597 caffe.cpp:501] detection_eval = 0.0370765
-I0511 11:49:27.154713  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154718  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154722  4597 caffe.cpp:501] detection_eval = 3.5121
-I0511 11:49:27.154726  4597 caffe.cpp:501] detection_eval = 12.4839
-I0511 11:49:27.154729  4597 caffe.cpp:501] detection_eval = 0.0374453
-I0511 11:49:27.154733  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154737  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.154742  4597 caffe.cpp:501] detection_eval = 3.5121
-I0511 11:49:27.154744  4597 caffe.cpp:501] detection_eval = 12.5645
-I0511 11:49:27.154748  4597 caffe.cpp:501] detection_eval = 0.0435159
-I0511 11:49:27.154752  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154757  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.154760  4597 caffe.cpp:501] detection_eval = 3.51613
-I0511 11:49:27.154764  4597 caffe.cpp:501] detection_eval = 12.6149
-I0511 11:49:27.154768  4597 caffe.cpp:501] detection_eval = 0.0416669
-I0511 11:49:27.154772  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154775  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.154779  4597 caffe.cpp:501] detection_eval = 3.52218
-I0511 11:49:27.154783  4597 caffe.cpp:501] detection_eval = 12.6089
-I0511 11:49:27.154786  4597 caffe.cpp:501] detection_eval = 0.0419004
-I0511 11:49:27.154790  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154798  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154803  4597 caffe.cpp:501] detection_eval = 3.52621
-I0511 11:49:27.154806  4597 caffe.cpp:501] detection_eval = 12.5988
-I0511 11:49:27.154810  4597 caffe.cpp:501] detection_eval = 0.0393724
-I0511 11:49:27.154814  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154817  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154821  4597 caffe.cpp:501] detection_eval = 3.53024
-I0511 11:49:27.154824  4597 caffe.cpp:501] detection_eval = 12.5665
-I0511 11:49:27.154829  4597 caffe.cpp:501] detection_eval = 0.0363939
-I0511 11:49:27.154832  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154836  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154840  4597 caffe.cpp:501] detection_eval = 3.53427
-I0511 11:49:27.154844  4597 caffe.cpp:501] detection_eval = 12.5665
-I0511 11:49:27.154847  4597 caffe.cpp:501] detection_eval = 0.0383389
-I0511 11:49:27.154851  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154855  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154860  4597 caffe.cpp:501] detection_eval = 3.53831
-I0511 11:49:27.154862  4597 caffe.cpp:501] detection_eval = 12.5706
-I0511 11:49:27.154866  4597 caffe.cpp:501] detection_eval = 0.0337247
-I0511 11:49:27.154870  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.154875  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.154878  4597 caffe.cpp:501] detection_eval = 3.53831
-I0511 11:49:27.154881  4597 caffe.cpp:501] detection_eval = 12.6411
-I0511 11:49:27.154886  4597 caffe.cpp:501] detection_eval = 0.0380939
-I0511 11:49:27.154889  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154893  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154897  4597 caffe.cpp:501] detection_eval = 3.54234
-I0511 11:49:27.154901  4597 caffe.cpp:501] detection_eval = 12.6331
-I0511 11:49:27.154904  4597 caffe.cpp:501] detection_eval = 0.037627
-I0511 11:49:27.154908  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154912  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154917  4597 caffe.cpp:501] detection_eval = 3.54234
-I0511 11:49:27.154919  4597 caffe.cpp:501] detection_eval = 12.6855
-I0511 11:49:27.154923  4597 caffe.cpp:501] detection_eval = 0.0369024
-I0511 11:49:27.154927  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154932  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.154934  4597 caffe.cpp:501] detection_eval = 3.54435
-I0511 11:49:27.154938  4597 caffe.cpp:501] detection_eval = 12.6996
-I0511 11:49:27.154942  4597 caffe.cpp:501] detection_eval = 0.0372405
-I0511 11:49:27.154947  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154950  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154953  4597 caffe.cpp:501] detection_eval = 3.54637
-I0511 11:49:27.154958  4597 caffe.cpp:501] detection_eval = 12.7319
-I0511 11:49:27.154961  4597 caffe.cpp:501] detection_eval = 0.0383912
-I0511 11:49:27.154964  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154968  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154973  4597 caffe.cpp:501] detection_eval = 3.5504
-I0511 11:49:27.154976  4597 caffe.cpp:501] detection_eval = 12.7298
-I0511 11:49:27.154980  4597 caffe.cpp:501] detection_eval = 0.0358585
-I0511 11:49:27.154984  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.154987  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.154991  4597 caffe.cpp:501] detection_eval = 3.55444
-I0511 11:49:27.154995  4597 caffe.cpp:501] detection_eval = 12.7419
-I0511 11:49:27.154999  4597 caffe.cpp:501] detection_eval = 0.034492
-I0511 11:49:27.155004  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155006  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155010  4597 caffe.cpp:501] detection_eval = 3.55645
-I0511 11:49:27.155014  4597 caffe.cpp:501] detection_eval = 12.7722
-I0511 11:49:27.155019  4597 caffe.cpp:501] detection_eval = 0.036101
-I0511 11:49:27.155026  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155030  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155035  4597 caffe.cpp:501] detection_eval = 3.56048
-I0511 11:49:27.155037  4597 caffe.cpp:501] detection_eval = 12.7823
-I0511 11:49:27.155041  4597 caffe.cpp:501] detection_eval = 0.0382512
-I0511 11:49:27.155045  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.155050  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155053  4597 caffe.cpp:501] detection_eval = 3.56653
-I0511 11:49:27.155056  4597 caffe.cpp:501] detection_eval = 12.7702
-I0511 11:49:27.155061  4597 caffe.cpp:501] detection_eval = 0.0426121
-I0511 11:49:27.155064  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155068  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.155071  4597 caffe.cpp:501] detection_eval = 3.56855
-I0511 11:49:27.155076  4597 caffe.cpp:501] detection_eval = 12.7762
-I0511 11:49:27.155079  4597 caffe.cpp:501] detection_eval = 0.0349352
-I0511 11:49:27.155083  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.155086  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155091  4597 caffe.cpp:501] detection_eval = 3.56855
-I0511 11:49:27.155094  4597 caffe.cpp:501] detection_eval = 12.8468
-I0511 11:49:27.155098  4597 caffe.cpp:501] detection_eval = 0.0353602
-I0511 11:49:27.155102  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.155105  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155109  4597 caffe.cpp:501] detection_eval = 3.57056
-I0511 11:49:27.155113  4597 caffe.cpp:501] detection_eval = 12.8649
-I0511 11:49:27.155117  4597 caffe.cpp:501] detection_eval = 0.0339189
-I0511 11:49:27.155120  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155124  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155128  4597 caffe.cpp:501] detection_eval = 3.5746
-I0511 11:49:27.155131  4597 caffe.cpp:501] detection_eval = 12.877
-I0511 11:49:27.155135  4597 caffe.cpp:501] detection_eval = 0.0349053
-I0511 11:49:27.155139  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155143  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155148  4597 caffe.cpp:501] detection_eval = 3.5746
-I0511 11:49:27.155150  4597 caffe.cpp:501] detection_eval = 12.9294
-I0511 11:49:27.155154  4597 caffe.cpp:501] detection_eval = 0.0316819
-I0511 11:49:27.155158  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155163  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155166  4597 caffe.cpp:501] detection_eval = 3.58669
-I0511 11:49:27.155170  4597 caffe.cpp:501] detection_eval = 12.8327
-I0511 11:49:27.155174  4597 caffe.cpp:501] detection_eval = 0.0345945
-I0511 11:49:27.155177  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155181  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155185  4597 caffe.cpp:501] detection_eval = 3.58669
-I0511 11:49:27.155189  4597 caffe.cpp:501] detection_eval = 12.9254
-I0511 11:49:27.155192  4597 caffe.cpp:501] detection_eval = 0.0364048
-I0511 11:49:27.155196  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155200  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155203  4597 caffe.cpp:501] detection_eval = 3.59476
-I0511 11:49:27.155207  4597 caffe.cpp:501] detection_eval = 12.871
-I0511 11:49:27.155211  4597 caffe.cpp:501] detection_eval = 0.0391323
-I0511 11:49:27.155215  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155218  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155222  4597 caffe.cpp:501] detection_eval = 3.59677
-I0511 11:49:27.155226  4597 caffe.cpp:501] detection_eval = 12.9194
-I0511 11:49:27.155230  4597 caffe.cpp:501] detection_eval = 0.0375311
-I0511 11:49:27.155233  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155237  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155241  4597 caffe.cpp:501] detection_eval = 3.60081
-I0511 11:49:27.155246  4597 caffe.cpp:501] detection_eval = 12.9294
-I0511 11:49:27.155249  4597 caffe.cpp:501] detection_eval = 0.0343586
-I0511 11:49:27.155256  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.155261  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155264  4597 caffe.cpp:501] detection_eval = 3.60685
-I0511 11:49:27.155268  4597 caffe.cpp:501] detection_eval = 12.9556
-I0511 11:49:27.155272  4597 caffe.cpp:501] detection_eval = 0.0430812
-I0511 11:49:27.155275  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155279  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155283  4597 caffe.cpp:501] detection_eval = 3.60685
-I0511 11:49:27.155287  4597 caffe.cpp:501] detection_eval = 13.0423
-I0511 11:49:27.155292  4597 caffe.cpp:501] detection_eval = 0.0405538
-I0511 11:49:27.155295  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155298  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155303  4597 caffe.cpp:501] detection_eval = 3.60887
-I0511 11:49:27.155306  4597 caffe.cpp:501] detection_eval = 13.0887
-I0511 11:49:27.155310  4597 caffe.cpp:501] detection_eval = 0.0370188
-I0511 11:49:27.155314  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155318  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155321  4597 caffe.cpp:501] detection_eval = 3.60887
-I0511 11:49:27.155325  4597 caffe.cpp:501] detection_eval = 13.1815
-I0511 11:49:27.155329  4597 caffe.cpp:501] detection_eval = 0.0410786
-I0511 11:49:27.155333  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155336  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155340  4597 caffe.cpp:501] detection_eval = 3.61089
-I0511 11:49:27.155344  4597 caffe.cpp:501] detection_eval = 13.2621
-I0511 11:49:27.155347  4597 caffe.cpp:501] detection_eval = 0.0463212
-I0511 11:49:27.155351  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155355  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155359  4597 caffe.cpp:501] detection_eval = 3.6129
-I0511 11:49:27.155364  4597 caffe.cpp:501] detection_eval = 13.3407
-I0511 11:49:27.155367  4597 caffe.cpp:501] detection_eval = 0.044323
-I0511 11:49:27.155371  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155375  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155378  4597 caffe.cpp:501] detection_eval = 3.625
-I0511 11:49:27.155382  4597 caffe.cpp:501] detection_eval = 13.2762
-I0511 11:49:27.155386  4597 caffe.cpp:501] detection_eval = 0.0458902
-I0511 11:49:27.155390  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155395  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.155398  4597 caffe.cpp:501] detection_eval = 3.625
-I0511 11:49:27.155402  4597 caffe.cpp:501] detection_eval = 13.4234
-I0511 11:49:27.155406  4597 caffe.cpp:501] detection_eval = 0.0362259
-I0511 11:49:27.155409  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155413  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155417  4597 caffe.cpp:501] detection_eval = 3.62702
-I0511 11:49:27.155421  4597 caffe.cpp:501] detection_eval = 13.5222
-I0511 11:49:27.155426  4597 caffe.cpp:501] detection_eval = 0.0388758
-I0511 11:49:27.155428  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155432  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155436  4597 caffe.cpp:501] detection_eval = 3.62903
-I0511 11:49:27.155441  4597 caffe.cpp:501] detection_eval = 13.6331
-I0511 11:49:27.155444  4597 caffe.cpp:501] detection_eval = 0.0345768
-I0511 11:49:27.155447  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155452  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155454  4597 caffe.cpp:501] detection_eval = 3.63508
-I0511 11:49:27.155458  4597 caffe.cpp:501] detection_eval = 13.7056
-I0511 11:49:27.155462  4597 caffe.cpp:501] detection_eval = 0.0406952
-I0511 11:49:27.155467  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155470  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155474  4597 caffe.cpp:501] detection_eval = 3.6371
-I0511 11:49:27.155478  4597 caffe.cpp:501] detection_eval = 13.8649
-I0511 11:49:27.155485  4597 caffe.cpp:501] detection_eval = 0.0384295
-I0511 11:49:27.155489  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155493  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155498  4597 caffe.cpp:501] detection_eval = 3.64315
-I0511 11:49:27.155501  4597 caffe.cpp:501] detection_eval = 14.0081
-I0511 11:49:27.155505  4597 caffe.cpp:501] detection_eval = 0.0350933
-I0511 11:49:27.155509  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155513  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155516  4597 caffe.cpp:501] detection_eval = 4.11694
-I0511 11:49:27.155520  4597 caffe.cpp:501] detection_eval = 7.05847
-I0511 11:49:27.155524  4597 caffe.cpp:501] detection_eval = 0.0858396
-I0511 11:49:27.155527  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.155531  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.155535  4597 caffe.cpp:501] detection_eval = 4.11895
-I0511 11:49:27.155539  4597 caffe.cpp:501] detection_eval = 7.24395
-I0511 11:49:27.155544  4597 caffe.cpp:501] detection_eval = 0.0593276
-I0511 11:49:27.155547  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.155550  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.155555  4597 caffe.cpp:501] detection_eval = 4.12097
-I0511 11:49:27.155558  4597 caffe.cpp:501] detection_eval = 7.36895
-I0511 11:49:27.155562  4597 caffe.cpp:501] detection_eval = 0.0512497
-I0511 11:49:27.155565  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.155570  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.155573  4597 caffe.cpp:501] detection_eval = 4.12298
-I0511 11:49:27.155577  4597 caffe.cpp:501] detection_eval = 7.46976
-I0511 11:49:27.155581  4597 caffe.cpp:501] detection_eval = 0.0515406
-I0511 11:49:27.155584  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155588  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.155592  4597 caffe.cpp:501] detection_eval = 4.125
-I0511 11:49:27.155596  4597 caffe.cpp:501] detection_eval = 7.57661
-I0511 11:49:27.155599  4597 caffe.cpp:501] detection_eval = 0.0499778
-I0511 11:49:27.155603  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155607  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.155611  4597 caffe.cpp:501] detection_eval = 4.12702
-I0511 11:49:27.155614  4597 caffe.cpp:501] detection_eval = 7.63911
-I0511 11:49:27.155618  4597 caffe.cpp:501] detection_eval = 0.0468457
-I0511 11:49:27.155622  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.155625  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155629  4597 caffe.cpp:501] detection_eval = 4.12903
-I0511 11:49:27.155633  4597 caffe.cpp:501] detection_eval = 7.69758
-I0511 11:49:27.155637  4597 caffe.cpp:501] detection_eval = 0.0444881
-I0511 11:49:27.155640  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155644  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155648  4597 caffe.cpp:501] detection_eval = 4.13508
-I0511 11:49:27.155652  4597 caffe.cpp:501] detection_eval = 7.67137
-I0511 11:49:27.155655  4597 caffe.cpp:501] detection_eval = 0.0415724
-I0511 11:49:27.155659  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155663  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155668  4597 caffe.cpp:501] detection_eval = 4.13911
-I0511 11:49:27.155671  4597 caffe.cpp:501] detection_eval = 7.67944
-I0511 11:49:27.155675  4597 caffe.cpp:501] detection_eval = 0.0446926
-I0511 11:49:27.155678  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.155683  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.155686  4597 caffe.cpp:501] detection_eval = 4.14113
-I0511 11:49:27.155690  4597 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:49:27.155694  4597 caffe.cpp:501] detection_eval = 0.0431846
-I0511 11:49:27.155697  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155701  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155705  4597 caffe.cpp:501] detection_eval = 4.14113
-I0511 11:49:27.155714  4597 caffe.cpp:501] detection_eval = 7.82863
-I0511 11:49:27.155717  4597 caffe.cpp:501] detection_eval = 0.041058
-I0511 11:49:27.155721  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155725  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155728  4597 caffe.cpp:501] detection_eval = 4.14718
-I0511 11:49:27.155732  4597 caffe.cpp:501] detection_eval = 7.83871
-I0511 11:49:27.155736  4597 caffe.cpp:501] detection_eval = 0.0447293
-I0511 11:49:27.155740  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155743  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155747  4597 caffe.cpp:501] detection_eval = 4.14718
-I0511 11:49:27.155751  4597 caffe.cpp:501] detection_eval = 7.92137
-I0511 11:49:27.155755  4597 caffe.cpp:501] detection_eval = 0.0416813
-I0511 11:49:27.155758  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155762  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.155766  4597 caffe.cpp:501] detection_eval = 4.15323
-I0511 11:49:27.155771  4597 caffe.cpp:501] detection_eval = 7.92339
-I0511 11:49:27.155773  4597 caffe.cpp:501] detection_eval = 0.0464219
-I0511 11:49:27.155777  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155781  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155786  4597 caffe.cpp:501] detection_eval = 4.15524
-I0511 11:49:27.155788  4597 caffe.cpp:501] detection_eval = 7.9496
-I0511 11:49:27.155792  4597 caffe.cpp:501] detection_eval = 0.0425792
-I0511 11:49:27.155797  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155800  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.155804  4597 caffe.cpp:501] detection_eval = 4.15726
-I0511 11:49:27.155807  4597 caffe.cpp:501] detection_eval = 7.98992
-I0511 11:49:27.155812  4597 caffe.cpp:501] detection_eval = 0.0450335
-I0511 11:49:27.155815  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155819  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155823  4597 caffe.cpp:501] detection_eval = 4.15927
-I0511 11:49:27.155827  4597 caffe.cpp:501] detection_eval = 8.0504
-I0511 11:49:27.155831  4597 caffe.cpp:501] detection_eval = 0.0480609
-I0511 11:49:27.155835  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155839  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155843  4597 caffe.cpp:501] detection_eval = 4.15927
-I0511 11:49:27.155846  4597 caffe.cpp:501] detection_eval = 8.11089
-I0511 11:49:27.155850  4597 caffe.cpp:501] detection_eval = 0.0410535
-I0511 11:49:27.155854  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155858  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155861  4597 caffe.cpp:501] detection_eval = 4.16129
-I0511 11:49:27.155865  4597 caffe.cpp:501] detection_eval = 8.14516
-I0511 11:49:27.155869  4597 caffe.cpp:501] detection_eval = 0.0408988
-I0511 11:49:27.155872  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.155876  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.155880  4597 caffe.cpp:501] detection_eval = 4.16129
-I0511 11:49:27.155884  4597 caffe.cpp:501] detection_eval = 8.19153
-I0511 11:49:27.155887  4597 caffe.cpp:501] detection_eval = 0.0385151
-I0511 11:49:27.155891  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.155895  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155899  4597 caffe.cpp:501] detection_eval = 4.16331
-I0511 11:49:27.155902  4597 caffe.cpp:501] detection_eval = 8.21774
-I0511 11:49:27.155906  4597 caffe.cpp:501] detection_eval = 0.0343173
-I0511 11:49:27.155910  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155913  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155917  4597 caffe.cpp:501] detection_eval = 4.16331
-I0511 11:49:27.155921  4597 caffe.cpp:501] detection_eval = 8.30242
-I0511 11:49:27.155925  4597 caffe.cpp:501] detection_eval = 0.0414283
-I0511 11:49:27.155930  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155933  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155937  4597 caffe.cpp:501] detection_eval = 4.16935
-I0511 11:49:27.155944  4597 caffe.cpp:501] detection_eval = 8.32661
-I0511 11:49:27.155948  4597 caffe.cpp:501] detection_eval = 0.0370563
-I0511 11:49:27.155952  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155956  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155961  4597 caffe.cpp:501] detection_eval = 4.17944
-I0511 11:49:27.155963  4597 caffe.cpp:501] detection_eval = 8.22177
-I0511 11:49:27.155967  4597 caffe.cpp:501] detection_eval = 0.039177
-I0511 11:49:27.155972  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155975  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.155979  4597 caffe.cpp:501] detection_eval = 4.18145
-I0511 11:49:27.155982  4597 caffe.cpp:501] detection_eval = 8.27823
-I0511 11:49:27.155987  4597 caffe.cpp:501] detection_eval = 0.0412711
-I0511 11:49:27.155992  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155995  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155999  4597 caffe.cpp:501] detection_eval = 4.18145
-I0511 11:49:27.156003  4597 caffe.cpp:501] detection_eval = 8.38105
-I0511 11:49:27.156008  4597 caffe.cpp:501] detection_eval = 0.0424748
-I0511 11:49:27.156010  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156014  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156018  4597 caffe.cpp:501] detection_eval = 4.18952
-I0511 11:49:27.156023  4597 caffe.cpp:501] detection_eval = 8.30444
-I0511 11:49:27.156026  4597 caffe.cpp:501] detection_eval = 0.0459202
-I0511 11:49:27.156030  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156034  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156038  4597 caffe.cpp:501] detection_eval = 4.19153
-I0511 11:49:27.156041  4597 caffe.cpp:501] detection_eval = 8.34073
-I0511 11:49:27.156045  4597 caffe.cpp:501] detection_eval = 0.0432066
-I0511 11:49:27.156049  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.156052  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.156056  4597 caffe.cpp:501] detection_eval = 4.19556
-I0511 11:49:27.156060  4597 caffe.cpp:501] detection_eval = 8.39315
-I0511 11:49:27.156064  4597 caffe.cpp:501] detection_eval = 0.0417494
-I0511 11:49:27.156067  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156071  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156075  4597 caffe.cpp:501] detection_eval = 4.19556
-I0511 11:49:27.156078  4597 caffe.cpp:501] detection_eval = 8.43952
-I0511 11:49:27.156082  4597 caffe.cpp:501] detection_eval = 0.0404347
-I0511 11:49:27.156086  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156090  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156093  4597 caffe.cpp:501] detection_eval = 4.19758
-I0511 11:49:27.156097  4597 caffe.cpp:501] detection_eval = 8.49798
-I0511 11:49:27.156101  4597 caffe.cpp:501] detection_eval = 0.0408992
-I0511 11:49:27.156105  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.156110  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156113  4597 caffe.cpp:501] detection_eval = 4.19758
-I0511 11:49:27.156116  4597 caffe.cpp:501] detection_eval = 8.54839
-I0511 11:49:27.156121  4597 caffe.cpp:501] detection_eval = 0.0413191
-I0511 11:49:27.156124  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156127  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156131  4597 caffe.cpp:501] detection_eval = 4.1996
-I0511 11:49:27.156136  4597 caffe.cpp:501] detection_eval = 8.60685
-I0511 11:49:27.156139  4597 caffe.cpp:501] detection_eval = 0.0435699
-I0511 11:49:27.156143  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156147  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156150  4597 caffe.cpp:501] detection_eval = 4.1996
-I0511 11:49:27.156154  4597 caffe.cpp:501] detection_eval = 8.66532
-I0511 11:49:27.156158  4597 caffe.cpp:501] detection_eval = 0.0383632
-I0511 11:49:27.156162  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156167  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156173  4597 caffe.cpp:501] detection_eval = 4.20363
-I0511 11:49:27.156178  4597 caffe.cpp:501] detection_eval = 8.6754
-I0511 11:49:27.156183  4597 caffe.cpp:501] detection_eval = 0.0404755
-I0511 11:49:27.156185  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156189  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156193  4597 caffe.cpp:501] detection_eval = 4.20565
-I0511 11:49:27.156198  4597 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:49:27.156200  4597 caffe.cpp:501] detection_eval = 0.0379169
-I0511 11:49:27.156204  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156208  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156213  4597 caffe.cpp:501] detection_eval = 4.20766
-I0511 11:49:27.156216  4597 caffe.cpp:501] detection_eval = 8.7379
-I0511 11:49:27.156219  4597 caffe.cpp:501] detection_eval = 0.0388246
-I0511 11:49:27.156224  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156227  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156231  4597 caffe.cpp:501] detection_eval = 4.21169
-I0511 11:49:27.156234  4597 caffe.cpp:501] detection_eval = 8.77419
-I0511 11:49:27.156239  4597 caffe.cpp:501] detection_eval = 0.0443882
-I0511 11:49:27.156242  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156246  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156250  4597 caffe.cpp:501] detection_eval = 4.21371
-I0511 11:49:27.156255  4597 caffe.cpp:501] detection_eval = 8.84677
-I0511 11:49:27.156257  4597 caffe.cpp:501] detection_eval = 0.0414387
-I0511 11:49:27.156261  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156265  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156270  4597 caffe.cpp:501] detection_eval = 4.21573
-I0511 11:49:27.156272  4597 caffe.cpp:501] detection_eval = 8.87702
-I0511 11:49:27.156276  4597 caffe.cpp:501] detection_eval = 0.0371307
-I0511 11:49:27.156280  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156285  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.156287  4597 caffe.cpp:501] detection_eval = 4.21573
-I0511 11:49:27.156291  4597 caffe.cpp:501] detection_eval = 8.97984
-I0511 11:49:27.156296  4597 caffe.cpp:501] detection_eval = 0.0383036
-I0511 11:49:27.156298  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156302  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156306  4597 caffe.cpp:501] detection_eval = 4.22177
-I0511 11:49:27.156311  4597 caffe.cpp:501] detection_eval = 8.94758
-I0511 11:49:27.156313  4597 caffe.cpp:501] detection_eval = 0.0437555
-I0511 11:49:27.156317  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156322  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156325  4597 caffe.cpp:501] detection_eval = 4.22379
-I0511 11:49:27.156328  4597 caffe.cpp:501] detection_eval = 9.00605
-I0511 11:49:27.156332  4597 caffe.cpp:501] detection_eval = 0.0451073
-I0511 11:49:27.156337  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156339  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156343  4597 caffe.cpp:501] detection_eval = 4.22984
-I0511 11:49:27.156347  4597 caffe.cpp:501] detection_eval = 9.02218
-I0511 11:49:27.156352  4597 caffe.cpp:501] detection_eval = 0.0392549
-I0511 11:49:27.156354  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156358  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.156363  4597 caffe.cpp:501] detection_eval = 4.23387
-I0511 11:49:27.156366  4597 caffe.cpp:501] detection_eval = 9.04234
-I0511 11:49:27.156370  4597 caffe.cpp:501] detection_eval = 0.0434554
-I0511 11:49:27.156374  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156378  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.156381  4597 caffe.cpp:501] detection_eval = 4.23387
-I0511 11:49:27.156385  4597 caffe.cpp:501] detection_eval = 9.12298
-I0511 11:49:27.156389  4597 caffe.cpp:501] detection_eval = 0.0380915
-I0511 11:49:27.156394  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156397  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156404  4597 caffe.cpp:501] detection_eval = 4.24194
-I0511 11:49:27.156409  4597 caffe.cpp:501] detection_eval = 9.08065
-I0511 11:49:27.156412  4597 caffe.cpp:501] detection_eval = 0.0377101
-I0511 11:49:27.156416  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156420  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.156424  4597 caffe.cpp:501] detection_eval = 4.24597
-I0511 11:49:27.156427  4597 caffe.cpp:501] detection_eval = 9.08065
-I0511 11:49:27.156431  4597 caffe.cpp:501] detection_eval = 0.040412
-I0511 11:49:27.156435  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156438  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.156442  4597 caffe.cpp:501] detection_eval = 4.25403
-I0511 11:49:27.156446  4597 caffe.cpp:501] detection_eval = 9.04032
-I0511 11:49:27.156450  4597 caffe.cpp:501] detection_eval = 0.0430151
-I0511 11:49:27.156453  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156457  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156461  4597 caffe.cpp:501] detection_eval = 4.25403
-I0511 11:49:27.156464  4597 caffe.cpp:501] detection_eval = 9.12097
-I0511 11:49:27.156468  4597 caffe.cpp:501] detection_eval = 0.0423637
-I0511 11:49:27.156472  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156476  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156481  4597 caffe.cpp:501] detection_eval = 4.25605
-I0511 11:49:27.156483  4597 caffe.cpp:501] detection_eval = 9.22581
-I0511 11:49:27.156487  4597 caffe.cpp:501] detection_eval = 0.0471794
-I0511 11:49:27.156491  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156496  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156498  4597 caffe.cpp:501] detection_eval = 4.25605
-I0511 11:49:27.156502  4597 caffe.cpp:501] detection_eval = 9.33871
-I0511 11:49:27.156507  4597 caffe.cpp:501] detection_eval = 0.0446415
-I0511 11:49:27.156510  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156513  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156517  4597 caffe.cpp:501] detection_eval = 4.2621
-I0511 11:49:27.156519  4597 caffe.cpp:501] detection_eval = 9.32863
-I0511 11:49:27.156522  4597 caffe.cpp:501] detection_eval = 0.0452137
-I0511 11:49:27.156533  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.156536  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.156540  4597 caffe.cpp:501] detection_eval = 4.2621
-I0511 11:49:27.156544  4597 caffe.cpp:501] detection_eval = 9.375
-I0511 11:49:27.156548  4597 caffe.cpp:501] detection_eval = 0.0429895
-I0511 11:49:27.156553  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156556  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156559  4597 caffe.cpp:501] detection_eval = 4.26613
-I0511 11:49:27.156563  4597 caffe.cpp:501] detection_eval = 9.40726
-I0511 11:49:27.156565  4597 caffe.cpp:501] detection_eval = 0.0457677
-I0511 11:49:27.156569  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156574  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156576  4597 caffe.cpp:501] detection_eval = 4.26613
-I0511 11:49:27.156580  4597 caffe.cpp:501] detection_eval = 9.48185
-I0511 11:49:27.156584  4597 caffe.cpp:501] detection_eval = 0.0435685
-I0511 11:49:27.156589  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156591  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156595  4597 caffe.cpp:501] detection_eval = 4.27016
-I0511 11:49:27.156599  4597 caffe.cpp:501] detection_eval = 9.48185
-I0511 11:49:27.156602  4597 caffe.cpp:501] detection_eval = 0.038904
-I0511 11:49:27.156606  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.156610  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.156615  4597 caffe.cpp:501] detection_eval = 4.27218
-I0511 11:49:27.156618  4597 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:49:27.156622  4597 caffe.cpp:501] detection_eval = 0.0382874
-I0511 11:49:27.156625  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156633  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.156638  4597 caffe.cpp:501] detection_eval = 4.27621
-I0511 11:49:27.156641  4597 caffe.cpp:501] detection_eval = 9.51411
-I0511 11:49:27.156646  4597 caffe.cpp:501] detection_eval = 0.0401356
-I0511 11:49:27.156649  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156653  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156656  4597 caffe.cpp:501] detection_eval = 4.27823
-I0511 11:49:27.156661  4597 caffe.cpp:501] detection_eval = 9.58669
-I0511 11:49:27.156664  4597 caffe.cpp:501] detection_eval = 0.0485891
-I0511 11:49:27.156668  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.156672  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.156677  4597 caffe.cpp:501] detection_eval = 4.28024
-I0511 11:49:27.156680  4597 caffe.cpp:501] detection_eval = 9.67339
-I0511 11:49:27.156683  4597 caffe.cpp:501] detection_eval = 0.0479873
-I0511 11:49:27.156687  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156692  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156695  4597 caffe.cpp:501] detection_eval = 4.28024
-I0511 11:49:27.156699  4597 caffe.cpp:501] detection_eval = 9.78226
-I0511 11:49:27.156702  4597 caffe.cpp:501] detection_eval = 0.0446545
-I0511 11:49:27.156707  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.156710  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156714  4597 caffe.cpp:501] detection_eval = 4.28226
-I0511 11:49:27.156718  4597 caffe.cpp:501] detection_eval = 9.8246
-I0511 11:49:27.156721  4597 caffe.cpp:501] detection_eval = 0.0395816
-I0511 11:49:27.156725  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156729  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156733  4597 caffe.cpp:501] detection_eval = 4.28629
-I0511 11:49:27.156736  4597 caffe.cpp:501] detection_eval = 9.85081
-I0511 11:49:27.156740  4597 caffe.cpp:501] detection_eval = 0.0462541
-I0511 11:49:27.156744  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156749  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156751  4597 caffe.cpp:501] detection_eval = 4.29234
-I0511 11:49:27.156755  4597 caffe.cpp:501] detection_eval = 9.88911
-I0511 11:49:27.156759  4597 caffe.cpp:501] detection_eval = 0.0437931
-I0511 11:49:27.156762  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156766  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156770  4597 caffe.cpp:501] detection_eval = 4.29839
-I0511 11:49:27.156774  4597 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:49:27.156777  4597 caffe.cpp:501] detection_eval = 0.0497577
-I0511 11:49:27.156781  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156785  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156788  4597 caffe.cpp:501] detection_eval = 4.3004
-I0511 11:49:27.156792  4597 caffe.cpp:501] detection_eval = 9.97782
-I0511 11:49:27.156796  4597 caffe.cpp:501] detection_eval = 0.0463998
-I0511 11:49:27.156800  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156805  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156807  4597 caffe.cpp:501] detection_eval = 4.30242
-I0511 11:49:27.156811  4597 caffe.cpp:501] detection_eval = 10.0242
-I0511 11:49:27.156816  4597 caffe.cpp:501] detection_eval = 0.050358
-I0511 11:49:27.156819  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156823  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156828  4597 caffe.cpp:501] detection_eval = 4.30242
-I0511 11:49:27.156832  4597 caffe.cpp:501] detection_eval = 10.1089
-I0511 11:49:27.156836  4597 caffe.cpp:501] detection_eval = 0.042978
-I0511 11:49:27.156841  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156846  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.156852  4597 caffe.cpp:501] detection_eval = 4.30645
-I0511 11:49:27.156855  4597 caffe.cpp:501] detection_eval = 10.1069
-I0511 11:49:27.156859  4597 caffe.cpp:501] detection_eval = 0.0405982
-I0511 11:49:27.156867  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156872  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156875  4597 caffe.cpp:501] detection_eval = 4.30847
-I0511 11:49:27.156879  4597 caffe.cpp:501] detection_eval = 10.127
-I0511 11:49:27.156883  4597 caffe.cpp:501] detection_eval = 0.0473988
-I0511 11:49:27.156888  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156890  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156894  4597 caffe.cpp:501] detection_eval = 4.30847
-I0511 11:49:27.156898  4597 caffe.cpp:501] detection_eval = 10.1895
-I0511 11:49:27.156903  4597 caffe.cpp:501] detection_eval = 0.039365
-I0511 11:49:27.156906  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156909  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156913  4597 caffe.cpp:501] detection_eval = 4.3125
-I0511 11:49:27.156918  4597 caffe.cpp:501] detection_eval = 10.2016
-I0511 11:49:27.156921  4597 caffe.cpp:501] detection_eval = 0.0378485
-I0511 11:49:27.156924  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156929  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156932  4597 caffe.cpp:501] detection_eval = 4.31653
-I0511 11:49:27.156936  4597 caffe.cpp:501] detection_eval = 10.25
-I0511 11:49:27.156940  4597 caffe.cpp:501] detection_eval = 0.0420936
-I0511 11:49:27.156944  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156947  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156951  4597 caffe.cpp:501] detection_eval = 4.3246
-I0511 11:49:27.156955  4597 caffe.cpp:501] detection_eval = 10.246
-I0511 11:49:27.156960  4597 caffe.cpp:501] detection_eval = 0.0418166
-I0511 11:49:27.156962  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156966  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156970  4597 caffe.cpp:501] detection_eval = 4.3246
-I0511 11:49:27.156975  4597 caffe.cpp:501] detection_eval = 10.3589
-I0511 11:49:27.156978  4597 caffe.cpp:501] detection_eval = 0.0415671
-I0511 11:49:27.156981  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156985  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156989  4597 caffe.cpp:501] detection_eval = 4.33065
-I0511 11:49:27.156993  4597 caffe.cpp:501] detection_eval = 10.4052
-I0511 11:49:27.156997  4597 caffe.cpp:501] detection_eval = 0.046085
-I0511 11:49:27.157001  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.157004  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.157008  4597 caffe.cpp:501] detection_eval = 4.33871
-I0511 11:49:27.157012  4597 caffe.cpp:501] detection_eval = 10.3569
-I0511 11:49:27.157016  4597 caffe.cpp:501] detection_eval = 0.0408102
-I0511 11:49:27.157021  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157023  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157027  4597 caffe.cpp:501] detection_eval = 4.34073
-I0511 11:49:27.157032  4597 caffe.cpp:501] detection_eval = 10.4133
-I0511 11:49:27.157035  4597 caffe.cpp:501] detection_eval = 0.0407476
-I0511 11:49:27.157038  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.157042  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.157047  4597 caffe.cpp:501] detection_eval = 4.34677
-I0511 11:49:27.157050  4597 caffe.cpp:501] detection_eval = 10.4073
-I0511 11:49:27.157054  4597 caffe.cpp:501] detection_eval = 0.0433495
-I0511 11:49:27.157058  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157061  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157065  4597 caffe.cpp:501] detection_eval = 4.35081
-I0511 11:49:27.157069  4597 caffe.cpp:501] detection_eval = 10.4476
-I0511 11:49:27.157073  4597 caffe.cpp:501] detection_eval = 0.0476197
-I0511 11:49:27.157076  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.157080  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.157084  4597 caffe.cpp:501] detection_eval = 4.35484
-I0511 11:49:27.157088  4597 caffe.cpp:501] detection_eval = 10.4637
-I0511 11:49:27.157091  4597 caffe.cpp:501] detection_eval = 0.037921
-I0511 11:49:27.157099  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.157104  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157106  4597 caffe.cpp:501] detection_eval = 4.35887
-I0511 11:49:27.157110  4597 caffe.cpp:501] detection_eval = 10.4435
-I0511 11:49:27.157114  4597 caffe.cpp:501] detection_eval = 0.0372124
-I0511 11:49:27.157119  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157122  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.157125  4597 caffe.cpp:501] detection_eval = 4.3629
-I0511 11:49:27.157130  4597 caffe.cpp:501] detection_eval = 10.4677
-I0511 11:49:27.157133  4597 caffe.cpp:501] detection_eval = 0.0391093
-I0511 11:49:27.157137  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157141  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.157145  4597 caffe.cpp:501] detection_eval = 4.36694
-I0511 11:49:27.157148  4597 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:49:27.157152  4597 caffe.cpp:501] detection_eval = 0.0444606
-I0511 11:49:27.157156  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157160  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157164  4597 caffe.cpp:501] detection_eval = 4.36694
-I0511 11:49:27.157167  4597 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:49:27.157171  4597 caffe.cpp:501] detection_eval = 0.0435741
-I0511 11:49:27.157176  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157179  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157183  4597 caffe.cpp:501] detection_eval = 4.37097
-I0511 11:49:27.157186  4597 caffe.cpp:501] detection_eval = 10.5565
-I0511 11:49:27.157191  4597 caffe.cpp:501] detection_eval = 0.0388593
-I0511 11:49:27.157194  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.157198  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157202  4597 caffe.cpp:501] detection_eval = 4.38105
-I0511 11:49:27.157207  4597 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:49:27.157210  4597 caffe.cpp:501] detection_eval = 0.0413194
-I0511 11:49:27.157213  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157217  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157222  4597 caffe.cpp:501] detection_eval = 4.38306
-I0511 11:49:27.157225  4597 caffe.cpp:501] detection_eval = 10.506
-I0511 11:49:27.157229  4597 caffe.cpp:501] detection_eval = 0.0445081
-I0511 11:49:27.157233  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157236  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157240  4597 caffe.cpp:501] detection_eval = 4.38508
-I0511 11:49:27.157244  4597 caffe.cpp:501] detection_eval = 10.5302
-I0511 11:49:27.157248  4597 caffe.cpp:501] detection_eval = 0.0367612
-I0511 11:49:27.157251  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157254  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157258  4597 caffe.cpp:501] detection_eval = 4.3871
-I0511 11:49:27.157260  4597 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:49:27.157264  4597 caffe.cpp:501] detection_eval = 0.0351988
-I0511 11:49:27.157268  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.157271  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.157275  4597 caffe.cpp:501] detection_eval = 4.39516
-I0511 11:49:27.157279  4597 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:49:27.157284  4597 caffe.cpp:501] detection_eval = 0.0404685
-I0511 11:49:27.157287  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157290  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157294  4597 caffe.cpp:501] detection_eval = 4.39718
-I0511 11:49:27.157299  4597 caffe.cpp:501] detection_eval = 10.623
-I0511 11:49:27.157302  4597 caffe.cpp:501] detection_eval = 0.0424681
-I0511 11:49:27.157306  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157310  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157315  4597 caffe.cpp:501] detection_eval = 4.40121
-I0511 11:49:27.157318  4597 caffe.cpp:501] detection_eval = 10.6815
-I0511 11:49:27.157326  4597 caffe.cpp:501] detection_eval = 0.0430303
-I0511 11:49:27.157330  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157335  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157338  4597 caffe.cpp:501] detection_eval = 4.40323
-I0511 11:49:27.157341  4597 caffe.cpp:501] detection_eval = 10.7298
-I0511 11:49:27.157346  4597 caffe.cpp:501] detection_eval = 0.0459157
-I0511 11:49:27.157349  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157353  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157357  4597 caffe.cpp:501] detection_eval = 4.40323
-I0511 11:49:27.157361  4597 caffe.cpp:501] detection_eval = 10.8004
-I0511 11:49:27.157366  4597 caffe.cpp:501] detection_eval = 0.0444377
-I0511 11:49:27.157368  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157372  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157377  4597 caffe.cpp:501] detection_eval = 4.40927
-I0511 11:49:27.157380  4597 caffe.cpp:501] detection_eval = 10.748
-I0511 11:49:27.157384  4597 caffe.cpp:501] detection_eval = 0.0443802
-I0511 11:49:27.157388  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157392  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157395  4597 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:49:27.157399  4597 caffe.cpp:501] detection_eval = 10.7782
-I0511 11:49:27.157403  4597 caffe.cpp:501] detection_eval = 0.0450336
-I0511 11:49:27.157407  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.157410  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157414  4597 caffe.cpp:501] detection_eval = 4.41331
-I0511 11:49:27.157418  4597 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:49:27.157423  4597 caffe.cpp:501] detection_eval = 0.0419207
-I0511 11:49:27.157426  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.157429  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.157433  4597 caffe.cpp:501] detection_eval = 4.41532
-I0511 11:49:27.157438  4597 caffe.cpp:501] detection_eval = 10.8589
-I0511 11:49:27.157441  4597 caffe.cpp:501] detection_eval = 0.0427965
-I0511 11:49:27.157444  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157449  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157452  4597 caffe.cpp:501] detection_eval = 4.41935
-I0511 11:49:27.157456  4597 caffe.cpp:501] detection_eval = 10.8589
-I0511 11:49:27.157460  4597 caffe.cpp:501] detection_eval = 0.03864
-I0511 11:49:27.157464  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157467  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.157471  4597 caffe.cpp:501] detection_eval = 4.42137
-I0511 11:49:27.157475  4597 caffe.cpp:501] detection_eval = 10.8831
-I0511 11:49:27.157479  4597 caffe.cpp:501] detection_eval = 0.0366291
-I0511 11:49:27.157482  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157486  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157490  4597 caffe.cpp:501] detection_eval = 4.4254
-I0511 11:49:27.157495  4597 caffe.cpp:501] detection_eval = 10.871
-I0511 11:49:27.157497  4597 caffe.cpp:501] detection_eval = 0.0374958
-I0511 11:49:27.157501  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157505  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157510  4597 caffe.cpp:501] detection_eval = 4.43347
-I0511 11:49:27.157512  4597 caffe.cpp:501] detection_eval = 10.8448
-I0511 11:49:27.157516  4597 caffe.cpp:501] detection_eval = 0.0414161
-I0511 11:49:27.157521  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157524  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157528  4597 caffe.cpp:501] detection_eval = 4.4375
-I0511 11:49:27.157532  4597 caffe.cpp:501] detection_eval = 10.879
-I0511 11:49:27.157536  4597 caffe.cpp:501] detection_eval = 0.041688
-I0511 11:49:27.157539  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157543  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.157547  4597 caffe.cpp:501] detection_eval = 4.43952
-I0511 11:49:27.157550  4597 caffe.cpp:501] detection_eval = 10.8911
-I0511 11:49:27.157558  4597 caffe.cpp:501] detection_eval = 0.0408087
-I0511 11:49:27.157562  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157565  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157569  4597 caffe.cpp:501] detection_eval = 4.44153
-I0511 11:49:27.157573  4597 caffe.cpp:501] detection_eval = 10.9335
-I0511 11:49:27.157577  4597 caffe.cpp:501] detection_eval = 0.0434129
-I0511 11:49:27.157582  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157584  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157588  4597 caffe.cpp:501] detection_eval = 4.44355
-I0511 11:49:27.157593  4597 caffe.cpp:501] detection_eval = 10.9637
-I0511 11:49:27.157596  4597 caffe.cpp:501] detection_eval = 0.0448603
-I0511 11:49:27.157600  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157603  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157608  4597 caffe.cpp:501] detection_eval = 4.4496
-I0511 11:49:27.157611  4597 caffe.cpp:501] detection_eval = 10.9819
-I0511 11:49:27.157615  4597 caffe.cpp:501] detection_eval = 0.0455613
-I0511 11:49:27.157619  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157622  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157626  4597 caffe.cpp:501] detection_eval = 4.45161
-I0511 11:49:27.157631  4597 caffe.cpp:501] detection_eval = 11.0585
-I0511 11:49:27.157635  4597 caffe.cpp:501] detection_eval = 0.0437468
-I0511 11:49:27.157639  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157642  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157647  4597 caffe.cpp:501] detection_eval = 4.45565
-I0511 11:49:27.157650  4597 caffe.cpp:501] detection_eval = 11.0867
-I0511 11:49:27.157655  4597 caffe.cpp:501] detection_eval = 0.041675
-I0511 11:49:27.157658  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157662  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157666  4597 caffe.cpp:501] detection_eval = 4.45565
-I0511 11:49:27.157670  4597 caffe.cpp:501] detection_eval = 11.1613
-I0511 11:49:27.157675  4597 caffe.cpp:501] detection_eval = 0.046394
-I0511 11:49:27.157678  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157682  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.157685  4597 caffe.cpp:501] detection_eval = 4.45766
-I0511 11:49:27.157690  4597 caffe.cpp:501] detection_eval = 11.1956
-I0511 11:49:27.157693  4597 caffe.cpp:501] detection_eval = 0.0452438
-I0511 11:49:27.157697  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157701  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157704  4597 caffe.cpp:501] detection_eval = 4.45968
-I0511 11:49:27.157708  4597 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:49:27.157712  4597 caffe.cpp:501] detection_eval = 0.0494338
-I0511 11:49:27.157716  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.157721  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.157723  4597 caffe.cpp:501] detection_eval = 4.46371
-I0511 11:49:27.157727  4597 caffe.cpp:501] detection_eval = 11.2944
-I0511 11:49:27.157732  4597 caffe.cpp:501] detection_eval = 0.0407226
-I0511 11:49:27.157735  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157738  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157742  4597 caffe.cpp:501] detection_eval = 4.46573
-I0511 11:49:27.157747  4597 caffe.cpp:501] detection_eval = 11.3266
-I0511 11:49:27.157750  4597 caffe.cpp:501] detection_eval = 0.0456388
-I0511 11:49:27.157754  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.157757  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.157761  4597 caffe.cpp:501] detection_eval = 4.46774
-I0511 11:49:27.157765  4597 caffe.cpp:501] detection_eval = 11.4032
-I0511 11:49:27.157769  4597 caffe.cpp:501] detection_eval = 0.048704
-I0511 11:49:27.157773  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157776  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157780  4597 caffe.cpp:501] detection_eval = 4.46774
-I0511 11:49:27.157788  4597 caffe.cpp:501] detection_eval = 11.4556
-I0511 11:49:27.157793  4597 caffe.cpp:501] detection_eval = 0.0452335
-I0511 11:49:27.157796  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157799  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157804  4597 caffe.cpp:501] detection_eval = 4.46774
-I0511 11:49:27.157807  4597 caffe.cpp:501] detection_eval = 11.5101
-I0511 11:49:27.157811  4597 caffe.cpp:501] detection_eval = 0.0416035
-I0511 11:49:27.157814  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157819  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.157822  4597 caffe.cpp:501] detection_eval = 4.46976
-I0511 11:49:27.157826  4597 caffe.cpp:501] detection_eval = 11.5161
-I0511 11:49:27.157829  4597 caffe.cpp:501] detection_eval = 0.0392881
-I0511 11:49:27.157833  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157837  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157841  4597 caffe.cpp:501] detection_eval = 4.47177
-I0511 11:49:27.157845  4597 caffe.cpp:501] detection_eval = 11.5403
-I0511 11:49:27.157848  4597 caffe.cpp:501] detection_eval = 0.0396965
-I0511 11:49:27.157852  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.157856  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.157860  4597 caffe.cpp:501] detection_eval = 4.47177
-I0511 11:49:27.157863  4597 caffe.cpp:501] detection_eval = 11.5968
-I0511 11:49:27.157867  4597 caffe.cpp:501] detection_eval = 0.0395053
-I0511 11:49:27.157871  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157876  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157879  4597 caffe.cpp:501] detection_eval = 4.47782
-I0511 11:49:27.157882  4597 caffe.cpp:501] detection_eval = 11.5766
-I0511 11:49:27.157886  4597 caffe.cpp:501] detection_eval = 0.0413298
-I0511 11:49:27.157891  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157894  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157898  4597 caffe.cpp:501] detection_eval = 4.48185
-I0511 11:49:27.157902  4597 caffe.cpp:501] detection_eval = 11.6008
-I0511 11:49:27.157905  4597 caffe.cpp:501] detection_eval = 0.0437222
-I0511 11:49:27.157909  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157913  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157917  4597 caffe.cpp:501] detection_eval = 4.48589
-I0511 11:49:27.157920  4597 caffe.cpp:501] detection_eval = 11.6835
-I0511 11:49:27.157924  4597 caffe.cpp:501] detection_eval = 0.0432977
-I0511 11:49:27.157928  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157932  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.157935  4597 caffe.cpp:501] detection_eval = 4.48992
-I0511 11:49:27.157939  4597 caffe.cpp:501] detection_eval = 11.6754
-I0511 11:49:27.157943  4597 caffe.cpp:501] detection_eval = 0.0463204
-I0511 11:49:27.157948  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157951  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157954  4597 caffe.cpp:501] detection_eval = 4.49597
-I0511 11:49:27.157958  4597 caffe.cpp:501] detection_eval = 11.7016
-I0511 11:49:27.157963  4597 caffe.cpp:501] detection_eval = 0.0482656
-I0511 11:49:27.157966  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.157969  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.157974  4597 caffe.cpp:501] detection_eval = 4.5
-I0511 11:49:27.157977  4597 caffe.cpp:501] detection_eval = 11.7238
-I0511 11:49:27.157981  4597 caffe.cpp:501] detection_eval = 0.041621
-I0511 11:49:27.157985  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.157989  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157992  4597 caffe.cpp:501] detection_eval = 4.5
-I0511 11:49:27.157996  4597 caffe.cpp:501] detection_eval = 11.7702
-I0511 11:49:27.158000  4597 caffe.cpp:501] detection_eval = 0.0432754
-I0511 11:49:27.158004  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158007  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158015  4597 caffe.cpp:501] detection_eval = 4.50202
-I0511 11:49:27.158018  4597 caffe.cpp:501] detection_eval = 11.7964
-I0511 11:49:27.158022  4597 caffe.cpp:501] detection_eval = 0.0377137
-I0511 11:49:27.158026  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158030  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.158035  4597 caffe.cpp:501] detection_eval = 4.5121
-I0511 11:49:27.158038  4597 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:49:27.158042  4597 caffe.cpp:501] detection_eval = 0.0383119
-I0511 11:49:27.158046  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158049  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158053  4597 caffe.cpp:501] detection_eval = 4.51411
-I0511 11:49:27.158057  4597 caffe.cpp:501] detection_eval = 11.756
-I0511 11:49:27.158061  4597 caffe.cpp:501] detection_eval = 0.0418753
-I0511 11:49:27.158064  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158068  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158072  4597 caffe.cpp:501] detection_eval = 4.51613
-I0511 11:49:27.158077  4597 caffe.cpp:501] detection_eval = 11.7661
-I0511 11:49:27.158080  4597 caffe.cpp:501] detection_eval = 0.0371328
-I0511 11:49:27.158083  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158087  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158092  4597 caffe.cpp:501] detection_eval = 4.52419
-I0511 11:49:27.158094  4597 caffe.cpp:501] detection_eval = 11.7661
-I0511 11:49:27.158098  4597 caffe.cpp:501] detection_eval = 0.0369458
-I0511 11:49:27.158102  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158107  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158110  4597 caffe.cpp:501] detection_eval = 4.53024
-I0511 11:49:27.158113  4597 caffe.cpp:501] detection_eval = 11.7258
-I0511 11:49:27.158118  4597 caffe.cpp:501] detection_eval = 0.0408371
-I0511 11:49:27.158121  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158125  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158129  4597 caffe.cpp:501] detection_eval = 4.53427
-I0511 11:49:27.158133  4597 caffe.cpp:501] detection_eval = 11.7177
-I0511 11:49:27.158136  4597 caffe.cpp:501] detection_eval = 0.0414977
-I0511 11:49:27.158140  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158144  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158149  4597 caffe.cpp:501] detection_eval = 4.53831
-I0511 11:49:27.158151  4597 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:49:27.158155  4597 caffe.cpp:501] detection_eval = 0.0402817
-I0511 11:49:27.158159  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158164  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158167  4597 caffe.cpp:501] detection_eval = 4.54234
-I0511 11:49:27.158170  4597 caffe.cpp:501] detection_eval = 11.75
-I0511 11:49:27.158174  4597 caffe.cpp:501] detection_eval = 0.0401225
-I0511 11:49:27.158179  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158182  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158186  4597 caffe.cpp:501] detection_eval = 4.55242
-I0511 11:49:27.158190  4597 caffe.cpp:501] detection_eval = 11.6714
-I0511 11:49:27.158193  4597 caffe.cpp:501] detection_eval = 0.0438539
-I0511 11:49:27.158197  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.158201  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.158205  4597 caffe.cpp:501] detection_eval = 4.55242
-I0511 11:49:27.158208  4597 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:49:27.158212  4597 caffe.cpp:501] detection_eval = 0.0411232
-I0511 11:49:27.158216  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158221  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.158224  4597 caffe.cpp:501] detection_eval = 4.55847
-I0511 11:49:27.158228  4597 caffe.cpp:501] detection_eval = 11.6915
-I0511 11:49:27.158232  4597 caffe.cpp:501] detection_eval = 0.0390835
-I0511 11:49:27.158236  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158239  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158248  4597 caffe.cpp:501] detection_eval = 4.56048
-I0511 11:49:27.158252  4597 caffe.cpp:501] detection_eval = 11.7298
-I0511 11:49:27.158257  4597 caffe.cpp:501] detection_eval = 0.0414107
-I0511 11:49:27.158260  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158263  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.158267  4597 caffe.cpp:501] detection_eval = 4.5625
-I0511 11:49:27.158272  4597 caffe.cpp:501] detection_eval = 11.8266
-I0511 11:49:27.158275  4597 caffe.cpp:501] detection_eval = 0.0436668
-I0511 11:49:27.158278  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.158282  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.158287  4597 caffe.cpp:501] detection_eval = 4.57056
-I0511 11:49:27.158290  4597 caffe.cpp:501] detection_eval = 11.7681
-I0511 11:49:27.158293  4597 caffe.cpp:501] detection_eval = 0.0438924
-I0511 11:49:27.158298  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158301  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158305  4597 caffe.cpp:501] detection_eval = 4.57661
-I0511 11:49:27.158308  4597 caffe.cpp:501] detection_eval = 11.7661
-I0511 11:49:27.158313  4597 caffe.cpp:501] detection_eval = 0.0436783
-I0511 11:49:27.158316  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158320  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158324  4597 caffe.cpp:501] detection_eval = 4.57863
-I0511 11:49:27.158329  4597 caffe.cpp:501] detection_eval = 11.8286
-I0511 11:49:27.158331  4597 caffe.cpp:501] detection_eval = 0.0407017
-I0511 11:49:27.158335  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158339  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158344  4597 caffe.cpp:501] detection_eval = 4.57863
-I0511 11:49:27.158347  4597 caffe.cpp:501] detection_eval = 11.9113
-I0511 11:49:27.158351  4597 caffe.cpp:501] detection_eval = 0.0422112
-I0511 11:49:27.158355  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.158358  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.158362  4597 caffe.cpp:501] detection_eval = 4.58065
-I0511 11:49:27.158366  4597 caffe.cpp:501] detection_eval = 11.9435
-I0511 11:49:27.158370  4597 caffe.cpp:501] detection_eval = 0.0365646
-I0511 11:49:27.158375  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.158377  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.158381  4597 caffe.cpp:501] detection_eval = 4.58266
-I0511 11:49:27.158385  4597 caffe.cpp:501] detection_eval = 11.9657
-I0511 11:49:27.158390  4597 caffe.cpp:501] detection_eval = 0.0385419
-I0511 11:49:27.158392  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158396  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158401  4597 caffe.cpp:501] detection_eval = 4.58266
-I0511 11:49:27.158404  4597 caffe.cpp:501] detection_eval = 12.0262
-I0511 11:49:27.158408  4597 caffe.cpp:501] detection_eval = 0.0380468
-I0511 11:49:27.158411  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158416  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158419  4597 caffe.cpp:501] detection_eval = 4.58468
-I0511 11:49:27.158423  4597 caffe.cpp:501] detection_eval = 12.0383
-I0511 11:49:27.158427  4597 caffe.cpp:501] detection_eval = 0.0354415
-I0511 11:49:27.158430  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.158434  4597 caffe.cpp:501] detection_eval = 1
-I0511 11:49:27.158438  4597 caffe.cpp:501] detection_eval = 4.58871
-I0511 11:49:27.158442  4597 caffe.cpp:501] detection_eval = 12.0565
-I0511 11:49:27.158447  4597 caffe.cpp:501] detection_eval = 0.038643
-I0511 11:49:27.158450  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158454  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158458  4597 caffe.cpp:501] detection_eval = 4.59274
-I0511 11:49:27.158463  4597 caffe.cpp:501] detection_eval = 12.0484
-I0511 11:49:27.158466  4597 caffe.cpp:501] detection_eval = 0.0424511
-I0511 11:49:27.158469  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158478  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158483  4597 caffe.cpp:501] detection_eval = 4.59476
-I0511 11:49:27.158486  4597 caffe.cpp:501] detection_eval = 12.119
-I0511 11:49:27.158490  4597 caffe.cpp:501] detection_eval = 0.0386666
-I0511 11:49:27.158493  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158498  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158501  4597 caffe.cpp:501] detection_eval = 4.59476
-I0511 11:49:27.158505  4597 caffe.cpp:501] detection_eval = 12.1673
-I0511 11:49:27.158509  4597 caffe.cpp:501] detection_eval = 0.0433378
-I0511 11:49:27.158514  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158516  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158520  4597 caffe.cpp:501] detection_eval = 4.60081
-I0511 11:49:27.158524  4597 caffe.cpp:501] detection_eval = 12.1512
-I0511 11:49:27.158529  4597 caffe.cpp:501] detection_eval = 0.0410943
-I0511 11:49:27.158531  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158535  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158540  4597 caffe.cpp:501] detection_eval = 4.60685
-I0511 11:49:27.158543  4597 caffe.cpp:501] detection_eval = 12.127
-I0511 11:49:27.158547  4597 caffe.cpp:501] detection_eval = 0.0467994
-I0511 11:49:27.158550  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.158555  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.158558  4597 caffe.cpp:501] detection_eval = 4.61089
-I0511 11:49:27.158562  4597 caffe.cpp:501] detection_eval = 12.0948
-I0511 11:49:27.158566  4597 caffe.cpp:501] detection_eval = 0.043666
-I0511 11:49:27.158569  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158573  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158577  4597 caffe.cpp:501] detection_eval = 4.6129
-I0511 11:49:27.158581  4597 caffe.cpp:501] detection_eval = 12.1109
-I0511 11:49:27.158586  4597 caffe.cpp:501] detection_eval = 0.0420169
-I0511 11:49:27.158589  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158592  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.158596  4597 caffe.cpp:501] detection_eval = 4.6129
-I0511 11:49:27.158601  4597 caffe.cpp:501] detection_eval = 12.1613
-I0511 11:49:27.158604  4597 caffe.cpp:501] detection_eval = 0.036278
-I0511 11:49:27.158608  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158612  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158615  4597 caffe.cpp:501] detection_eval = 4.6129
-I0511 11:49:27.158619  4597 caffe.cpp:501] detection_eval = 12.2137
-I0511 11:49:27.158623  4597 caffe.cpp:501] detection_eval = 0.034748
-I0511 11:49:27.158627  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158632  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.158634  4597 caffe.cpp:501] detection_eval = 4.61492
-I0511 11:49:27.158638  4597 caffe.cpp:501] detection_eval = 12.256
-I0511 11:49:27.158643  4597 caffe.cpp:501] detection_eval = 0.0388143
-I0511 11:49:27.158646  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158649  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.158653  4597 caffe.cpp:501] detection_eval = 4.62097
-I0511 11:49:27.158658  4597 caffe.cpp:501] detection_eval = 12.2016
-I0511 11:49:27.158661  4597 caffe.cpp:501] detection_eval = 0.0353157
-I0511 11:49:27.158665  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.158668  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.158673  4597 caffe.cpp:501] detection_eval = 4.62298
-I0511 11:49:27.158676  4597 caffe.cpp:501] detection_eval = 12.2137
-I0511 11:49:27.158680  4597 caffe.cpp:501] detection_eval = 0.0340815
-I0511 11:49:27.158684  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158687  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158691  4597 caffe.cpp:501] detection_eval = 4.625
-I0511 11:49:27.158695  4597 caffe.cpp:501] detection_eval = 12.2621
-I0511 11:49:27.158699  4597 caffe.cpp:501] detection_eval = 0.0360302
-I0511 11:49:27.158704  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158710  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158715  4597 caffe.cpp:501] detection_eval = 4.62903
-I0511 11:49:27.158718  4597 caffe.cpp:501] detection_eval = 12.2419
-I0511 11:49:27.158721  4597 caffe.cpp:501] detection_eval = 0.0383883
-I0511 11:49:27.158725  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158730  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158733  4597 caffe.cpp:501] detection_eval = 4.63508
-I0511 11:49:27.158736  4597 caffe.cpp:501] detection_eval = 12.1794
-I0511 11:49:27.158740  4597 caffe.cpp:501] detection_eval = 0.0369931
-I0511 11:49:27.158744  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158748  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158752  4597 caffe.cpp:501] detection_eval = 4.63508
-I0511 11:49:27.158756  4597 caffe.cpp:501] detection_eval = 12.2137
-I0511 11:49:27.158759  4597 caffe.cpp:501] detection_eval = 0.0361574
-I0511 11:49:27.158763  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158767  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158771  4597 caffe.cpp:501] detection_eval = 4.64113
-I0511 11:49:27.158774  4597 caffe.cpp:501] detection_eval = 12.1915
-I0511 11:49:27.158778  4597 caffe.cpp:501] detection_eval = 0.0395487
-I0511 11:49:27.158782  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158787  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158790  4597 caffe.cpp:501] detection_eval = 4.64315
-I0511 11:49:27.158793  4597 caffe.cpp:501] detection_eval = 12.2379
-I0511 11:49:27.158797  4597 caffe.cpp:501] detection_eval = 0.0375797
-I0511 11:49:27.158802  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158805  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158809  4597 caffe.cpp:501] detection_eval = 4.64919
-I0511 11:49:27.158812  4597 caffe.cpp:501] detection_eval = 12.2056
-I0511 11:49:27.158816  4597 caffe.cpp:501] detection_eval = 0.0351078
-I0511 11:49:27.158820  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.158824  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.158828  4597 caffe.cpp:501] detection_eval = 4.64919
-I0511 11:49:27.158831  4597 caffe.cpp:501] detection_eval = 12.244
-I0511 11:49:27.158835  4597 caffe.cpp:501] detection_eval = 0.0342402
-I0511 11:49:27.158839  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158843  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158848  4597 caffe.cpp:501] detection_eval = 4.65323
-I0511 11:49:27.158851  4597 caffe.cpp:501] detection_eval = 12.2379
-I0511 11:49:27.158855  4597 caffe.cpp:501] detection_eval = 0.033903
-I0511 11:49:27.158859  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158862  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158866  4597 caffe.cpp:501] detection_eval = 4.65726
-I0511 11:49:27.158870  4597 caffe.cpp:501] detection_eval = 12.2177
-I0511 11:49:27.158874  4597 caffe.cpp:501] detection_eval = 0.0364475
-I0511 11:49:27.158879  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158881  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158885  4597 caffe.cpp:501] detection_eval = 4.65927
-I0511 11:49:27.158890  4597 caffe.cpp:501] detection_eval = 12.252
-I0511 11:49:27.158893  4597 caffe.cpp:501] detection_eval = 0.0357001
-I0511 11:49:27.158896  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158900  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158905  4597 caffe.cpp:501] detection_eval = 4.66532
-I0511 11:49:27.158908  4597 caffe.cpp:501] detection_eval = 12.2601
-I0511 11:49:27.158912  4597 caffe.cpp:501] detection_eval = 0.0393888
-I0511 11:49:27.158916  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158921  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.158923  4597 caffe.cpp:501] detection_eval = 4.67137
-I0511 11:49:27.158927  4597 caffe.cpp:501] detection_eval = 12.2399
-I0511 11:49:27.158931  4597 caffe.cpp:501] detection_eval = 0.038015
-I0511 11:49:27.158938  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158943  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158946  4597 caffe.cpp:501] detection_eval = 4.67339
-I0511 11:49:27.158951  4597 caffe.cpp:501] detection_eval = 12.2883
-I0511 11:49:27.158954  4597 caffe.cpp:501] detection_eval = 0.0386486
-I0511 11:49:27.158958  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158962  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158965  4597 caffe.cpp:501] detection_eval = 4.67339
-I0511 11:49:27.158969  4597 caffe.cpp:501] detection_eval = 12.4335
-I0511 11:49:27.158973  4597 caffe.cpp:501] detection_eval = 0.0465097
-I0511 11:49:27.158977  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.158982  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.158984  4597 caffe.cpp:501] detection_eval = 4.67742
-I0511 11:49:27.158988  4597 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:49:27.158993  4597 caffe.cpp:501] detection_eval = 0.0369663
-I0511 11:49:27.158996  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.159000  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159004  4597 caffe.cpp:501] detection_eval = 4.68145
-I0511 11:49:27.159008  4597 caffe.cpp:501] detection_eval = 12.4032
-I0511 11:49:27.159011  4597 caffe.cpp:501] detection_eval = 0.042946
-I0511 11:49:27.159015  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159019  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.159024  4597 caffe.cpp:501] detection_eval = 4.68347
-I0511 11:49:27.159026  4597 caffe.cpp:501] detection_eval = 12.4113
-I0511 11:49:27.159030  4597 caffe.cpp:501] detection_eval = 0.0351064
-I0511 11:49:27.159034  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.159039  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.159042  4597 caffe.cpp:501] detection_eval = 4.69556
-I0511 11:49:27.159045  4597 caffe.cpp:501] detection_eval = 12.3105
-I0511 11:49:27.159049  4597 caffe.cpp:501] detection_eval = 0.0371418
-I0511 11:49:27.159054  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.159057  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159060  4597 caffe.cpp:501] detection_eval = 4.69556
-I0511 11:49:27.159065  4597 caffe.cpp:501] detection_eval = 12.3972
-I0511 11:49:27.159068  4597 caffe.cpp:501] detection_eval = 0.0421836
-I0511 11:49:27.159072  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159076  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159080  4597 caffe.cpp:501] detection_eval = 4.70161
-I0511 11:49:27.159083  4597 caffe.cpp:501] detection_eval = 12.3952
-I0511 11:49:27.159087  4597 caffe.cpp:501] detection_eval = 0.0421523
-I0511 11:49:27.159091  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159096  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.159098  4597 caffe.cpp:501] detection_eval = 4.70766
-I0511 11:49:27.159102  4597 caffe.cpp:501] detection_eval = 12.4012
-I0511 11:49:27.159106  4597 caffe.cpp:501] detection_eval = 0.0440006
-I0511 11:49:27.159111  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159114  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159117  4597 caffe.cpp:501] detection_eval = 4.70968
-I0511 11:49:27.159121  4597 caffe.cpp:501] detection_eval = 12.4375
-I0511 11:49:27.159126  4597 caffe.cpp:501] detection_eval = 0.0413539
-I0511 11:49:27.159129  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159133  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159137  4597 caffe.cpp:501] detection_eval = 4.71573
-I0511 11:49:27.159140  4597 caffe.cpp:501] detection_eval = 12.4214
-I0511 11:49:27.159144  4597 caffe.cpp:501] detection_eval = 0.0441704
-I0511 11:49:27.159148  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159152  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.159157  4597 caffe.cpp:501] detection_eval = 4.71573
-I0511 11:49:27.159159  4597 caffe.cpp:501] detection_eval = 12.5181
-I0511 11:49:27.159166  4597 caffe.cpp:501] detection_eval = 0.0440508
-I0511 11:49:27.159170  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.159174  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159178  4597 caffe.cpp:501] detection_eval = 4.71573
-I0511 11:49:27.159183  4597 caffe.cpp:501] detection_eval = 12.5887
-I0511 11:49:27.159186  4597 caffe.cpp:501] detection_eval = 0.0436599
-I0511 11:49:27.159189  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.159193  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159198  4597 caffe.cpp:501] detection_eval = 4.71573
-I0511 11:49:27.159201  4597 caffe.cpp:501] detection_eval = 12.6956
-I0511 11:49:27.159205  4597 caffe.cpp:501] detection_eval = 0.0428629
-I0511 11:49:27.159209  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159212  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159216  4597 caffe.cpp:501] detection_eval = 4.71976
-I0511 11:49:27.159219  4597 caffe.cpp:501] detection_eval = 12.7581
-I0511 11:49:27.159224  4597 caffe.cpp:501] detection_eval = 0.0448693
-I0511 11:49:27.159227  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.159231  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.159235  4597 caffe.cpp:501] detection_eval = 4.72177
-I0511 11:49:27.159238  4597 caffe.cpp:501] detection_eval = 12.8407
-I0511 11:49:27.159242  4597 caffe.cpp:501] detection_eval = 0.0433908
-I0511 11:49:27.159246  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.159250  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.159255  4597 caffe.cpp:501] detection_eval = 4.73589
-I0511 11:49:27.159257  4597 caffe.cpp:501] detection_eval = 12.7036
-I0511 11:49:27.159262  4597 caffe.cpp:501] detection_eval = 0.0435141
-I0511 11:49:27.159266  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159271  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.159273  4597 caffe.cpp:501] detection_eval = 4.7379
-I0511 11:49:27.159277  4597 caffe.cpp:501] detection_eval = 12.7964
-I0511 11:49:27.159281  4597 caffe.cpp:501] detection_eval = 0.0428964
-I0511 11:49:27.159286  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159288  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159292  4597 caffe.cpp:501] detection_eval = 4.73992
-I0511 11:49:27.159296  4597 caffe.cpp:501] detection_eval = 12.8569
-I0511 11:49:27.159301  4597 caffe.cpp:501] detection_eval = 0.0450329
-I0511 11:49:27.159303  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159307  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159312  4597 caffe.cpp:501] detection_eval = 4.74194
-I0511 11:49:27.159315  4597 caffe.cpp:501] detection_eval = 12.9657
-I0511 11:49:27.159319  4597 caffe.cpp:501] detection_eval = 0.0397115
-I0511 11:49:27.159322  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159327  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159330  4597 caffe.cpp:501] detection_eval = 4.75
-I0511 11:49:27.159333  4597 caffe.cpp:501] detection_eval = 12.996
-I0511 11:49:27.159337  4597 caffe.cpp:501] detection_eval = 0.0457237
-I0511 11:49:27.159341  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.159345  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.159349  4597 caffe.cpp:501] detection_eval = 4.75202
-I0511 11:49:27.159353  4597 caffe.cpp:501] detection_eval = 13.1593
-I0511 11:49:27.159356  4597 caffe.cpp:501] detection_eval = 0.0419493
-I0511 11:49:27.159360  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159364  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.159368  4597 caffe.cpp:501] detection_eval = 4.75605
-I0511 11:49:27.159371  4597 caffe.cpp:501] detection_eval = 13.3488
-I0511 11:49:27.159375  4597 caffe.cpp:501] detection_eval = 0.0408169
-I0511 11:49:27.159379  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.159384  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159386  4597 caffe.cpp:501] detection_eval = 5.14718
-I0511 11:49:27.159390  4597 caffe.cpp:501] detection_eval = 7.51411
-I0511 11:49:27.159397  4597 caffe.cpp:501] detection_eval = 0.0829268
-I0511 11:49:27.159401  4597 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:49:27.159405  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.159409  4597 caffe.cpp:501] detection_eval = 5.14919
-I0511 11:49:27.159413  4597 caffe.cpp:501] detection_eval = 7.66532
-I0511 11:49:27.159417  4597 caffe.cpp:501] detection_eval = 0.0581721
-I0511 11:49:27.159420  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.159425  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.159428  4597 caffe.cpp:501] detection_eval = 5.15323
-I0511 11:49:27.159432  4597 caffe.cpp:501] detection_eval = 7.77218
-I0511 11:49:27.159435  4597 caffe.cpp:501] detection_eval = 0.0568789
-I0511 11:49:27.159440  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.159443  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.159446  4597 caffe.cpp:501] detection_eval = 5.15726
-I0511 11:49:27.159451  4597 caffe.cpp:501] detection_eval = 7.85484
-I0511 11:49:27.159454  4597 caffe.cpp:501] detection_eval = 0.0504249
-I0511 11:49:27.159457  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159461  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159466  4597 caffe.cpp:501] detection_eval = 5.15927
-I0511 11:49:27.159469  4597 caffe.cpp:501] detection_eval = 7.95766
-I0511 11:49:27.159472  4597 caffe.cpp:501] detection_eval = 0.0588796
-I0511 11:49:27.159476  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.159481  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.159484  4597 caffe.cpp:501] detection_eval = 5.16129
-I0511 11:49:27.159487  4597 caffe.cpp:501] detection_eval = 7.99597
-I0511 11:49:27.159492  4597 caffe.cpp:501] detection_eval = 0.046715
-I0511 11:49:27.159494  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.159498  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.159502  4597 caffe.cpp:501] detection_eval = 5.16331
-I0511 11:49:27.159507  4597 caffe.cpp:501] detection_eval = 8.06653
-I0511 11:49:27.159509  4597 caffe.cpp:501] detection_eval = 0.0474749
-I0511 11:49:27.159513  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.159518  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.159521  4597 caffe.cpp:501] detection_eval = 5.16935
-I0511 11:49:27.159524  4597 caffe.cpp:501] detection_eval = 8.06452
-I0511 11:49:27.159528  4597 caffe.cpp:501] detection_eval = 0.0424333
-I0511 11:49:27.159533  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159535  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159539  4597 caffe.cpp:501] detection_eval = 5.1754
-I0511 11:49:27.159543  4597 caffe.cpp:501] detection_eval = 8.04435
-I0511 11:49:27.159546  4597 caffe.cpp:501] detection_eval = 0.0414681
-I0511 11:49:27.159550  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.159554  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159559  4597 caffe.cpp:501] detection_eval = 5.17944
-I0511 11:49:27.159562  4597 caffe.cpp:501] detection_eval = 8.0504
-I0511 11:49:27.159566  4597 caffe.cpp:501] detection_eval = 0.0396226
-I0511 11:49:27.159569  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.159574  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159577  4597 caffe.cpp:501] detection_eval = 5.17944
-I0511 11:49:27.159581  4597 caffe.cpp:501] detection_eval = 8.16734
-I0511 11:49:27.159585  4597 caffe.cpp:501] detection_eval = 0.0495915
-I0511 11:49:27.159590  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.159593  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.159596  4597 caffe.cpp:501] detection_eval = 5.18548
-I0511 11:49:27.159600  4597 caffe.cpp:501] detection_eval = 8.11492
-I0511 11:49:27.159605  4597 caffe.cpp:501] detection_eval = 0.0419437
-I0511 11:49:27.159608  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159611  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.159615  4597 caffe.cpp:501] detection_eval = 5.18548
-I0511 11:49:27.159622  4597 caffe.cpp:501] detection_eval = 8.22782
-I0511 11:49:27.159626  4597 caffe.cpp:501] detection_eval = 0.0442945
-I0511 11:49:27.159631  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159634  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159638  4597 caffe.cpp:501] detection_eval = 5.18952
-I0511 11:49:27.159641  4597 caffe.cpp:501] detection_eval = 8.27419
-I0511 11:49:27.159646  4597 caffe.cpp:501] detection_eval = 0.0484873
-I0511 11:49:27.159649  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159653  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159657  4597 caffe.cpp:501] detection_eval = 5.19153
-I0511 11:49:27.159660  4597 caffe.cpp:501] detection_eval = 8.29234
-I0511 11:49:27.159664  4597 caffe.cpp:501] detection_eval = 0.0438324
-I0511 11:49:27.159668  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.159672  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159677  4597 caffe.cpp:501] detection_eval = 5.19355
-I0511 11:49:27.159680  4597 caffe.cpp:501] detection_eval = 8.34073
-I0511 11:49:27.159684  4597 caffe.cpp:501] detection_eval = 0.0407354
-I0511 11:49:27.159688  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.159692  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.159695  4597 caffe.cpp:501] detection_eval = 5.19758
-I0511 11:49:27.159699  4597 caffe.cpp:501] detection_eval = 8.375
-I0511 11:49:27.159703  4597 caffe.cpp:501] detection_eval = 0.0435065
-I0511 11:49:27.159708  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159710  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159714  4597 caffe.cpp:501] detection_eval = 5.19758
-I0511 11:49:27.159718  4597 caffe.cpp:501] detection_eval = 8.46774
-I0511 11:49:27.159723  4597 caffe.cpp:501] detection_eval = 0.0432391
-I0511 11:49:27.159725  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159729  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.159734  4597 caffe.cpp:501] detection_eval = 5.20161
-I0511 11:49:27.159737  4597 caffe.cpp:501] detection_eval = 8.45968
-I0511 11:49:27.159741  4597 caffe.cpp:501] detection_eval = 0.042085
-I0511 11:49:27.159744  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159749  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159752  4597 caffe.cpp:501] detection_eval = 5.20161
-I0511 11:49:27.159756  4597 caffe.cpp:501] detection_eval = 8.50202
-I0511 11:49:27.159760  4597 caffe.cpp:501] detection_eval = 0.039412
-I0511 11:49:27.159763  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159767  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159771  4597 caffe.cpp:501] detection_eval = 5.20363
-I0511 11:49:27.159775  4597 caffe.cpp:501] detection_eval = 8.53226
-I0511 11:49:27.159778  4597 caffe.cpp:501] detection_eval = 0.0400512
-I0511 11:49:27.159782  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159786  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159790  4597 caffe.cpp:501] detection_eval = 5.20363
-I0511 11:49:27.159795  4597 caffe.cpp:501] detection_eval = 8.66532
-I0511 11:49:27.159798  4597 caffe.cpp:501] detection_eval = 0.0454019
-I0511 11:49:27.159801  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159806  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159809  4597 caffe.cpp:501] detection_eval = 5.20968
-I0511 11:49:27.159813  4597 caffe.cpp:501] detection_eval = 8.67137
-I0511 11:49:27.159817  4597 caffe.cpp:501] detection_eval = 0.0426998
-I0511 11:49:27.159821  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159826  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.159828  4597 caffe.cpp:501] detection_eval = 5.22177
-I0511 11:49:27.159832  4597 caffe.cpp:501] detection_eval = 8.5746
-I0511 11:49:27.159837  4597 caffe.cpp:501] detection_eval = 0.0408018
-I0511 11:49:27.159840  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.159844  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159847  4597 caffe.cpp:501] detection_eval = 5.22379
-I0511 11:49:27.159855  4597 caffe.cpp:501] detection_eval = 8.6754
-I0511 11:49:27.159859  4597 caffe.cpp:501] detection_eval = 0.0395071
-I0511 11:49:27.159863  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159868  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159871  4597 caffe.cpp:501] detection_eval = 5.22379
-I0511 11:49:27.159875  4597 caffe.cpp:501] detection_eval = 8.78831
-I0511 11:49:27.159879  4597 caffe.cpp:501] detection_eval = 0.0442783
-I0511 11:49:27.159883  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.159886  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.159890  4597 caffe.cpp:501] detection_eval = 5.23185
-I0511 11:49:27.159894  4597 caffe.cpp:501] detection_eval = 8.75605
-I0511 11:49:27.159898  4597 caffe.cpp:501] detection_eval = 0.0487317
-I0511 11:49:27.159901  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.159905  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.159909  4597 caffe.cpp:501] detection_eval = 5.23589
-I0511 11:49:27.159912  4597 caffe.cpp:501] detection_eval = 8.76613
-I0511 11:49:27.159916  4597 caffe.cpp:501] detection_eval = 0.0466184
-I0511 11:49:27.159920  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159924  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.159927  4597 caffe.cpp:501] detection_eval = 5.2379
-I0511 11:49:27.159931  4597 caffe.cpp:501] detection_eval = 8.8246
-I0511 11:49:27.159935  4597 caffe.cpp:501] detection_eval = 0.0464592
-I0511 11:49:27.159940  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159943  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159946  4597 caffe.cpp:501] detection_eval = 5.2379
-I0511 11:49:27.159950  4597 caffe.cpp:501] detection_eval = 8.875
-I0511 11:49:27.159955  4597 caffe.cpp:501] detection_eval = 0.0462804
-I0511 11:49:27.159958  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.159961  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159965  4597 caffe.cpp:501] detection_eval = 5.23992
-I0511 11:49:27.159970  4597 caffe.cpp:501] detection_eval = 8.89516
-I0511 11:49:27.159973  4597 caffe.cpp:501] detection_eval = 0.0449413
-I0511 11:49:27.159976  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.159981  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.159984  4597 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:49:27.159988  4597 caffe.cpp:501] detection_eval = 8.91331
-I0511 11:49:27.159992  4597 caffe.cpp:501] detection_eval = 0.0456006
-I0511 11:49:27.159996  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159999  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160004  4597 caffe.cpp:501] detection_eval = 5.24798
-I0511 11:49:27.160008  4597 caffe.cpp:501] detection_eval = 8.90927
-I0511 11:49:27.160012  4597 caffe.cpp:501] detection_eval = 0.0439038
-I0511 11:49:27.160015  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160019  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160023  4597 caffe.cpp:501] detection_eval = 5.25
-I0511 11:49:27.160027  4597 caffe.cpp:501] detection_eval = 8.9254
-I0511 11:49:27.160032  4597 caffe.cpp:501] detection_eval = 0.0369752
-I0511 11:49:27.160035  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160039  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160043  4597 caffe.cpp:501] detection_eval = 5.25202
-I0511 11:49:27.160048  4597 caffe.cpp:501] detection_eval = 8.95968
-I0511 11:49:27.160051  4597 caffe.cpp:501] detection_eval = 0.0460111
-I0511 11:49:27.160055  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160059  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160063  4597 caffe.cpp:501] detection_eval = 5.25403
-I0511 11:49:27.160068  4597 caffe.cpp:501] detection_eval = 9.00806
-I0511 11:49:27.160070  4597 caffe.cpp:501] detection_eval = 0.048944
-I0511 11:49:27.160074  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160079  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160087  4597 caffe.cpp:501] detection_eval = 5.25605
-I0511 11:49:27.160092  4597 caffe.cpp:501] detection_eval = 9.06452
-I0511 11:49:27.160096  4597 caffe.cpp:501] detection_eval = 0.0459543
-I0511 11:49:27.160099  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160104  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160107  4597 caffe.cpp:501] detection_eval = 5.25806
-I0511 11:49:27.160111  4597 caffe.cpp:501] detection_eval = 9.07863
-I0511 11:49:27.160115  4597 caffe.cpp:501] detection_eval = 0.041865
-I0511 11:49:27.160118  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160122  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160127  4597 caffe.cpp:501] detection_eval = 5.26008
-I0511 11:49:27.160131  4597 caffe.cpp:501] detection_eval = 9.09476
-I0511 11:49:27.160135  4597 caffe.cpp:501] detection_eval = 0.037409
-I0511 11:49:27.160140  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160143  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160146  4597 caffe.cpp:501] detection_eval = 5.26411
-I0511 11:49:27.160151  4597 caffe.cpp:501] detection_eval = 9.12298
-I0511 11:49:27.160154  4597 caffe.cpp:501] detection_eval = 0.03876
-I0511 11:49:27.160158  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160161  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160166  4597 caffe.cpp:501] detection_eval = 5.26411
-I0511 11:49:27.160169  4597 caffe.cpp:501] detection_eval = 9.21573
-I0511 11:49:27.160173  4597 caffe.cpp:501] detection_eval = 0.0465169
-I0511 11:49:27.160177  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160181  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160184  4597 caffe.cpp:501] detection_eval = 5.27016
-I0511 11:49:27.160188  4597 caffe.cpp:501] detection_eval = 9.21976
-I0511 11:49:27.160192  4597 caffe.cpp:501] detection_eval = 0.0382264
-I0511 11:49:27.160195  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160199  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160203  4597 caffe.cpp:501] detection_eval = 5.27218
-I0511 11:49:27.160207  4597 caffe.cpp:501] detection_eval = 9.27823
-I0511 11:49:27.160210  4597 caffe.cpp:501] detection_eval = 0.0434479
-I0511 11:49:27.160214  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160218  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160223  4597 caffe.cpp:501] detection_eval = 5.27621
-I0511 11:49:27.160225  4597 caffe.cpp:501] detection_eval = 9.30444
-I0511 11:49:27.160229  4597 caffe.cpp:501] detection_eval = 0.0445045
-I0511 11:49:27.160233  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160238  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160240  4597 caffe.cpp:501] detection_eval = 5.28024
-I0511 11:49:27.160244  4597 caffe.cpp:501] detection_eval = 9.31452
-I0511 11:49:27.160248  4597 caffe.cpp:501] detection_eval = 0.0463289
-I0511 11:49:27.160253  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160255  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160259  4597 caffe.cpp:501] detection_eval = 5.28024
-I0511 11:49:27.160264  4597 caffe.cpp:501] detection_eval = 9.39113
-I0511 11:49:27.160267  4597 caffe.cpp:501] detection_eval = 0.0468363
-I0511 11:49:27.160270  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.160274  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.160279  4597 caffe.cpp:501] detection_eval = 5.29032
-I0511 11:49:27.160282  4597 caffe.cpp:501] detection_eval = 9.29435
-I0511 11:49:27.160285  4597 caffe.cpp:501] detection_eval = 0.0425606
-I0511 11:49:27.160290  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160293  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160297  4597 caffe.cpp:501] detection_eval = 5.29435
-I0511 11:49:27.160301  4597 caffe.cpp:501] detection_eval = 9.34879
-I0511 11:49:27.160305  4597 caffe.cpp:501] detection_eval = 0.0420409
-I0511 11:49:27.160308  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160312  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.160320  4597 caffe.cpp:501] detection_eval = 5.30242
-I0511 11:49:27.160323  4597 caffe.cpp:501] detection_eval = 9.31653
-I0511 11:49:27.160327  4597 caffe.cpp:501] detection_eval = 0.0431198
-I0511 11:49:27.160331  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160336  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160338  4597 caffe.cpp:501] detection_eval = 5.30242
-I0511 11:49:27.160342  4597 caffe.cpp:501] detection_eval = 9.44355
-I0511 11:49:27.160346  4597 caffe.cpp:501] detection_eval = 0.0477149
-I0511 11:49:27.160349  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160353  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160357  4597 caffe.cpp:501] detection_eval = 5.30645
-I0511 11:49:27.160362  4597 caffe.cpp:501] detection_eval = 9.46169
-I0511 11:49:27.160365  4597 caffe.cpp:501] detection_eval = 0.0458819
-I0511 11:49:27.160369  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.160372  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.160377  4597 caffe.cpp:501] detection_eval = 5.30847
-I0511 11:49:27.160380  4597 caffe.cpp:501] detection_eval = 9.48992
-I0511 11:49:27.160384  4597 caffe.cpp:501] detection_eval = 0.0415921
-I0511 11:49:27.160387  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160392  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160395  4597 caffe.cpp:501] detection_eval = 5.31452
-I0511 11:49:27.160399  4597 caffe.cpp:501] detection_eval = 9.45565
-I0511 11:49:27.160403  4597 caffe.cpp:501] detection_eval = 0.0413678
-I0511 11:49:27.160406  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160410  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160414  4597 caffe.cpp:501] detection_eval = 5.31452
-I0511 11:49:27.160418  4597 caffe.cpp:501] detection_eval = 9.55847
-I0511 11:49:27.160421  4597 caffe.cpp:501] detection_eval = 0.0407364
-I0511 11:49:27.160425  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.160429  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.160434  4597 caffe.cpp:501] detection_eval = 5.31653
-I0511 11:49:27.160437  4597 caffe.cpp:501] detection_eval = 9.64919
-I0511 11:49:27.160440  4597 caffe.cpp:501] detection_eval = 0.0472103
-I0511 11:49:27.160444  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160449  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160452  4597 caffe.cpp:501] detection_eval = 5.31653
-I0511 11:49:27.160456  4597 caffe.cpp:501] detection_eval = 9.7379
-I0511 11:49:27.160459  4597 caffe.cpp:501] detection_eval = 0.0452346
-I0511 11:49:27.160464  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160467  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160471  4597 caffe.cpp:501] detection_eval = 5.32258
-I0511 11:49:27.160475  4597 caffe.cpp:501] detection_eval = 9.76008
-I0511 11:49:27.160478  4597 caffe.cpp:501] detection_eval = 0.0499323
-I0511 11:49:27.160482  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.160486  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.160490  4597 caffe.cpp:501] detection_eval = 5.3246
-I0511 11:49:27.160495  4597 caffe.cpp:501] detection_eval = 9.8004
-I0511 11:49:27.160498  4597 caffe.cpp:501] detection_eval = 0.0443093
-I0511 11:49:27.160503  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160506  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160511  4597 caffe.cpp:501] detection_eval = 5.32863
-I0511 11:49:27.160514  4597 caffe.cpp:501] detection_eval = 9.78831
-I0511 11:49:27.160518  4597 caffe.cpp:501] detection_eval = 0.0421533
-I0511 11:49:27.160522  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.160531  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.160535  4597 caffe.cpp:501] detection_eval = 5.33065
-I0511 11:49:27.160539  4597 caffe.cpp:501] detection_eval = 9.83266
-I0511 11:49:27.160543  4597 caffe.cpp:501] detection_eval = 0.0411291
-I0511 11:49:27.160547  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160557  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.160562  4597 caffe.cpp:501] detection_eval = 5.33266
-I0511 11:49:27.160564  4597 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:49:27.160568  4597 caffe.cpp:501] detection_eval = 0.0432754
-I0511 11:49:27.160573  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160576  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160580  4597 caffe.cpp:501] detection_eval = 5.33266
-I0511 11:49:27.160584  4597 caffe.cpp:501] detection_eval = 10
-I0511 11:49:27.160588  4597 caffe.cpp:501] detection_eval = 0.0427896
-I0511 11:49:27.160593  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160596  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160599  4597 caffe.cpp:501] detection_eval = 5.33871
-I0511 11:49:27.160604  4597 caffe.cpp:501] detection_eval = 9.97782
-I0511 11:49:27.160607  4597 caffe.cpp:501] detection_eval = 0.0417101
-I0511 11:49:27.160611  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160615  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160619  4597 caffe.cpp:501] detection_eval = 5.34274
-I0511 11:49:27.160622  4597 caffe.cpp:501] detection_eval = 9.97379
-I0511 11:49:27.160626  4597 caffe.cpp:501] detection_eval = 0.0400292
-I0511 11:49:27.160630  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160634  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160637  4597 caffe.cpp:501] detection_eval = 5.34879
-I0511 11:49:27.160641  4597 caffe.cpp:501] detection_eval = 9.97177
-I0511 11:49:27.160645  4597 caffe.cpp:501] detection_eval = 0.0437753
-I0511 11:49:27.160650  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160653  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160656  4597 caffe.cpp:501] detection_eval = 5.35484
-I0511 11:49:27.160660  4597 caffe.cpp:501] detection_eval = 10.004
-I0511 11:49:27.160662  4597 caffe.cpp:501] detection_eval = 0.0419356
-I0511 11:49:27.160665  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160668  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160672  4597 caffe.cpp:501] detection_eval = 5.35887
-I0511 11:49:27.160676  4597 caffe.cpp:501] detection_eval = 10.0423
-I0511 11:49:27.160678  4597 caffe.cpp:501] detection_eval = 0.0477488
-I0511 11:49:27.160682  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160686  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160688  4597 caffe.cpp:501] detection_eval = 5.36089
-I0511 11:49:27.160691  4597 caffe.cpp:501] detection_eval = 10.0524
-I0511 11:49:27.160696  4597 caffe.cpp:501] detection_eval = 0.0442932
-I0511 11:49:27.160698  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160701  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160704  4597 caffe.cpp:501] detection_eval = 5.3629
-I0511 11:49:27.160708  4597 caffe.cpp:501] detection_eval = 10.0927
-I0511 11:49:27.160712  4597 caffe.cpp:501] detection_eval = 0.0445454
-I0511 11:49:27.160714  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160717  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160720  4597 caffe.cpp:501] detection_eval = 5.36492
-I0511 11:49:27.160724  4597 caffe.cpp:501] detection_eval = 10.1532
-I0511 11:49:27.160727  4597 caffe.cpp:501] detection_eval = 0.0486137
-I0511 11:49:27.160732  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160734  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160737  4597 caffe.cpp:501] detection_eval = 5.36694
-I0511 11:49:27.160740  4597 caffe.cpp:501] detection_eval = 10.1895
-I0511 11:49:27.160744  4597 caffe.cpp:501] detection_eval = 0.0405678
-I0511 11:49:27.160748  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160750  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160754  4597 caffe.cpp:501] detection_eval = 5.37097
-I0511 11:49:27.160758  4597 caffe.cpp:501] detection_eval = 10.2077
-I0511 11:49:27.160761  4597 caffe.cpp:501] detection_eval = 0.0446628
-I0511 11:49:27.160768  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160771  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160774  4597 caffe.cpp:501] detection_eval = 5.375
-I0511 11:49:27.160778  4597 caffe.cpp:501] detection_eval = 10.2198
-I0511 11:49:27.160781  4597 caffe.cpp:501] detection_eval = 0.0413298
-I0511 11:49:27.160784  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160787  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160791  4597 caffe.cpp:501] detection_eval = 5.38105
-I0511 11:49:27.160794  4597 caffe.cpp:501] detection_eval = 10.2419
-I0511 11:49:27.160797  4597 caffe.cpp:501] detection_eval = 0.0400922
-I0511 11:49:27.160800  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160804  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160807  4597 caffe.cpp:501] detection_eval = 5.38911
-I0511 11:49:27.160810  4597 caffe.cpp:501] detection_eval = 10.1875
-I0511 11:49:27.160815  4597 caffe.cpp:501] detection_eval = 0.0443394
-I0511 11:49:27.160817  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160820  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160823  4597 caffe.cpp:501] detection_eval = 5.38911
-I0511 11:49:27.160826  4597 caffe.cpp:501] detection_eval = 10.252
-I0511 11:49:27.160830  4597 caffe.cpp:501] detection_eval = 0.0393483
-I0511 11:49:27.160833  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160836  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160840  4597 caffe.cpp:501] detection_eval = 5.39516
-I0511 11:49:27.160843  4597 caffe.cpp:501] detection_eval = 10.2419
-I0511 11:49:27.160846  4597 caffe.cpp:501] detection_eval = 0.0430957
-I0511 11:49:27.160850  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160853  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160856  4597 caffe.cpp:501] detection_eval = 5.40524
-I0511 11:49:27.160861  4597 caffe.cpp:501] detection_eval = 10.1815
-I0511 11:49:27.160863  4597 caffe.cpp:501] detection_eval = 0.0463508
-I0511 11:49:27.160866  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.160871  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160873  4597 caffe.cpp:501] detection_eval = 5.40726
-I0511 11:49:27.160876  4597 caffe.cpp:501] detection_eval = 10.2359
-I0511 11:49:27.160879  4597 caffe.cpp:501] detection_eval = 0.0478428
-I0511 11:49:27.160883  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160887  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160889  4597 caffe.cpp:501] detection_eval = 5.41331
-I0511 11:49:27.160892  4597 caffe.cpp:501] detection_eval = 10.2117
-I0511 11:49:27.160897  4597 caffe.cpp:501] detection_eval = 0.0406707
-I0511 11:49:27.160899  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160902  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160907  4597 caffe.cpp:501] detection_eval = 5.41734
-I0511 11:49:27.160909  4597 caffe.cpp:501] detection_eval = 10.252
-I0511 11:49:27.160912  4597 caffe.cpp:501] detection_eval = 0.0420435
-I0511 11:49:27.160917  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160921  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.160926  4597 caffe.cpp:501] detection_eval = 5.42137
-I0511 11:49:27.161113  4597 caffe.cpp:501] detection_eval = 10.2782
-I0511 11:49:27.161119  4597 caffe.cpp:501] detection_eval = 0.0423986
-I0511 11:49:27.161123  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161128  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.161131  4597 caffe.cpp:501] detection_eval = 5.4254
-I0511 11:49:27.161134  4597 caffe.cpp:501] detection_eval = 10.3125
-I0511 11:49:27.161139  4597 caffe.cpp:501] detection_eval = 0.0459558
-I0511 11:49:27.161142  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161146  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161150  4597 caffe.cpp:501] detection_eval = 5.42742
-I0511 11:49:27.161154  4597 caffe.cpp:501] detection_eval = 10.3972
-I0511 11:49:27.161159  4597 caffe.cpp:501] detection_eval = 0.0469398
-I0511 11:49:27.161167  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.161171  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.161175  4597 caffe.cpp:501] detection_eval = 5.42944
-I0511 11:49:27.161180  4597 caffe.cpp:501] detection_eval = 10.4476
-I0511 11:49:27.161183  4597 caffe.cpp:501] detection_eval = 0.0426102
-I0511 11:49:27.161187  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161191  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161195  4597 caffe.cpp:501] detection_eval = 5.42944
-I0511 11:49:27.161198  4597 caffe.cpp:501] detection_eval = 10.5444
-I0511 11:49:27.161202  4597 caffe.cpp:501] detection_eval = 0.0389233
-I0511 11:49:27.161206  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161209  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161213  4597 caffe.cpp:501] detection_eval = 5.43548
-I0511 11:49:27.161217  4597 caffe.cpp:501] detection_eval = 10.5444
-I0511 11:49:27.161221  4597 caffe.cpp:501] detection_eval = 0.0445941
-I0511 11:49:27.161224  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161228  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161232  4597 caffe.cpp:501] detection_eval = 5.44556
-I0511 11:49:27.161236  4597 caffe.cpp:501] detection_eval = 10.4415
-I0511 11:49:27.161239  4597 caffe.cpp:501] detection_eval = 0.0488672
-I0511 11:49:27.161243  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161247  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161252  4597 caffe.cpp:501] detection_eval = 5.45161
-I0511 11:49:27.161254  4597 caffe.cpp:501] detection_eval = 10.4415
-I0511 11:49:27.161259  4597 caffe.cpp:501] detection_eval = 0.0396903
-I0511 11:49:27.161262  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.161267  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.161270  4597 caffe.cpp:501] detection_eval = 5.45565
-I0511 11:49:27.161274  4597 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:49:27.161278  4597 caffe.cpp:501] detection_eval = 0.0415952
-I0511 11:49:27.161283  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.161286  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.161289  4597 caffe.cpp:501] detection_eval = 5.45766
-I0511 11:49:27.161293  4597 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:49:27.161298  4597 caffe.cpp:501] detection_eval = 0.0425015
-I0511 11:49:27.161301  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.161305  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.161309  4597 caffe.cpp:501] detection_eval = 5.46573
-I0511 11:49:27.161312  4597 caffe.cpp:501] detection_eval = 10.502
-I0511 11:49:27.161316  4597 caffe.cpp:501] detection_eval = 0.0476768
-I0511 11:49:27.161320  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161324  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161327  4597 caffe.cpp:501] detection_eval = 5.46774
-I0511 11:49:27.161331  4597 caffe.cpp:501] detection_eval = 10.5282
-I0511 11:49:27.161335  4597 caffe.cpp:501] detection_eval = 0.0461731
-I0511 11:49:27.161339  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161342  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161346  4597 caffe.cpp:501] detection_eval = 5.47177
-I0511 11:49:27.161350  4597 caffe.cpp:501] detection_eval = 10.5202
-I0511 11:49:27.161355  4597 caffe.cpp:501] detection_eval = 0.0412965
-I0511 11:49:27.161358  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.161362  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.161366  4597 caffe.cpp:501] detection_eval = 5.47379
-I0511 11:49:27.161370  4597 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:49:27.161373  4597 caffe.cpp:501] detection_eval = 0.0440154
-I0511 11:49:27.161377  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161381  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161384  4597 caffe.cpp:501] detection_eval = 5.47379
-I0511 11:49:27.161388  4597 caffe.cpp:501] detection_eval = 10.6008
-I0511 11:49:27.161396  4597 caffe.cpp:501] detection_eval = 0.0448397
-I0511 11:49:27.161401  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161404  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.161407  4597 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:49:27.161412  4597 caffe.cpp:501] detection_eval = 10.5665
-I0511 11:49:27.161417  4597 caffe.cpp:501] detection_eval = 0.0431499
-I0511 11:49:27.161420  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.161423  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161427  4597 caffe.cpp:501] detection_eval = 5.48387
-I0511 11:49:27.161432  4597 caffe.cpp:501] detection_eval = 10.5867
-I0511 11:49:27.161435  4597 caffe.cpp:501] detection_eval = 0.0461701
-I0511 11:49:27.161438  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161442  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161447  4597 caffe.cpp:501] detection_eval = 5.48589
-I0511 11:49:27.161450  4597 caffe.cpp:501] detection_eval = 10.6089
-I0511 11:49:27.161454  4597 caffe.cpp:501] detection_eval = 0.0417937
-I0511 11:49:27.161458  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161461  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161465  4597 caffe.cpp:501] detection_eval = 5.4879
-I0511 11:49:27.161468  4597 caffe.cpp:501] detection_eval = 10.6794
-I0511 11:49:27.161473  4597 caffe.cpp:501] detection_eval = 0.0506458
-I0511 11:49:27.161476  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161480  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161484  4597 caffe.cpp:501] detection_eval = 5.48992
-I0511 11:49:27.161487  4597 caffe.cpp:501] detection_eval = 10.7157
-I0511 11:49:27.161491  4597 caffe.cpp:501] detection_eval = 0.0439529
-I0511 11:49:27.161495  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.161499  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.161504  4597 caffe.cpp:501] detection_eval = 5.49194
-I0511 11:49:27.161506  4597 caffe.cpp:501] detection_eval = 10.7218
-I0511 11:49:27.161510  4597 caffe.cpp:501] detection_eval = 0.0437257
-I0511 11:49:27.161514  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161518  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161521  4597 caffe.cpp:501] detection_eval = 5.49597
-I0511 11:49:27.161525  4597 caffe.cpp:501] detection_eval = 10.7298
-I0511 11:49:27.161530  4597 caffe.cpp:501] detection_eval = 0.0456176
-I0511 11:49:27.161533  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161537  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161540  4597 caffe.cpp:501] detection_eval = 5.50403
-I0511 11:49:27.161545  4597 caffe.cpp:501] detection_eval = 10.6895
-I0511 11:49:27.161548  4597 caffe.cpp:501] detection_eval = 0.0444774
-I0511 11:49:27.161552  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161556  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161561  4597 caffe.cpp:501] detection_eval = 5.50806
-I0511 11:49:27.161563  4597 caffe.cpp:501] detection_eval = 10.7077
-I0511 11:49:27.161567  4597 caffe.cpp:501] detection_eval = 0.0459073
-I0511 11:49:27.161571  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161743  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161749  4597 caffe.cpp:501] detection_eval = 5.51008
-I0511 11:49:27.161753  4597 caffe.cpp:501] detection_eval = 10.7319
-I0511 11:49:27.161757  4597 caffe.cpp:501] detection_eval = 0.042579
-I0511 11:49:27.161761  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161765  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.161768  4597 caffe.cpp:501] detection_eval = 5.5121
-I0511 11:49:27.161772  4597 caffe.cpp:501] detection_eval = 10.7883
-I0511 11:49:27.161777  4597 caffe.cpp:501] detection_eval = 0.0499974
-I0511 11:49:27.161780  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161784  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161788  4597 caffe.cpp:501] detection_eval = 5.5121
-I0511 11:49:27.161797  4597 caffe.cpp:501] detection_eval = 10.8851
-I0511 11:49:27.161801  4597 caffe.cpp:501] detection_eval = 0.042366
-I0511 11:49:27.161804  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161808  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.161813  4597 caffe.cpp:501] detection_eval = 5.51815
-I0511 11:49:27.161815  4597 caffe.cpp:501] detection_eval = 10.8831
-I0511 11:49:27.161819  4597 caffe.cpp:501] detection_eval = 0.0477807
-I0511 11:49:27.161823  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.161828  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161831  4597 caffe.cpp:501] detection_eval = 5.52016
-I0511 11:49:27.161834  4597 caffe.cpp:501] detection_eval = 10.9819
-I0511 11:49:27.161839  4597 caffe.cpp:501] detection_eval = 0.0444135
-I0511 11:49:27.161842  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161846  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.161850  4597 caffe.cpp:501] detection_eval = 5.52621
-I0511 11:49:27.161854  4597 caffe.cpp:501] detection_eval = 10.9355
-I0511 11:49:27.161859  4597 caffe.cpp:501] detection_eval = 0.043241
-I0511 11:49:27.161861  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161865  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161870  4597 caffe.cpp:501] detection_eval = 5.52621
-I0511 11:49:27.161873  4597 caffe.cpp:501] detection_eval = 11.004
-I0511 11:49:27.161876  4597 caffe.cpp:501] detection_eval = 0.0428463
-I0511 11:49:27.161880  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161885  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161888  4597 caffe.cpp:501] detection_eval = 5.52621
-I0511 11:49:27.161891  4597 caffe.cpp:501] detection_eval = 11.0927
-I0511 11:49:27.161895  4597 caffe.cpp:501] detection_eval = 0.0443812
-I0511 11:49:27.161900  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161903  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161907  4597 caffe.cpp:501] detection_eval = 5.53024
-I0511 11:49:27.161911  4597 caffe.cpp:501] detection_eval = 11.119
-I0511 11:49:27.161914  4597 caffe.cpp:501] detection_eval = 0.0419728
-I0511 11:49:27.161918  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161922  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161926  4597 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:49:27.161929  4597 caffe.cpp:501] detection_eval = 11.1331
-I0511 11:49:27.161933  4597 caffe.cpp:501] detection_eval = 0.0406407
-I0511 11:49:27.161937  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161940  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161944  4597 caffe.cpp:501] detection_eval = 5.53831
-I0511 11:49:27.161948  4597 caffe.cpp:501] detection_eval = 11.1512
-I0511 11:49:27.161952  4597 caffe.cpp:501] detection_eval = 0.0448388
-I0511 11:49:27.161955  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161959  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161963  4597 caffe.cpp:501] detection_eval = 5.54234
-I0511 11:49:27.161967  4597 caffe.cpp:501] detection_eval = 11.1633
-I0511 11:49:27.161970  4597 caffe.cpp:501] detection_eval = 0.0418458
-I0511 11:49:27.161974  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161978  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161983  4597 caffe.cpp:501] detection_eval = 5.54234
-I0511 11:49:27.161986  4597 caffe.cpp:501] detection_eval = 11.2923
-I0511 11:49:27.161989  4597 caffe.cpp:501] detection_eval = 0.0507683
-I0511 11:49:27.161993  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161998  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.162001  4597 caffe.cpp:501] detection_eval = 5.54234
-I0511 11:49:27.162004  4597 caffe.cpp:501] detection_eval = 11.3306
-I0511 11:49:27.162009  4597 caffe.cpp:501] detection_eval = 0.044087
-I0511 11:49:27.162012  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.162016  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.162020  4597 caffe.cpp:501] detection_eval = 5.54839
-I0511 11:49:27.162027  4597 caffe.cpp:501] detection_eval = 11.2964
-I0511 11:49:27.162031  4597 caffe.cpp:501] detection_eval = 0.0475861
-I0511 11:49:27.162035  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162039  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162042  4597 caffe.cpp:501] detection_eval = 5.5504
-I0511 11:49:27.162046  4597 caffe.cpp:501] detection_eval = 11.3508
-I0511 11:49:27.162050  4597 caffe.cpp:501] detection_eval = 0.0519199
-I0511 11:49:27.162055  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.162058  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162061  4597 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:49:27.162065  4597 caffe.cpp:501] detection_eval = 11.381
-I0511 11:49:27.162070  4597 caffe.cpp:501] detection_eval = 0.0452902
-I0511 11:49:27.162073  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.162077  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.162081  4597 caffe.cpp:501] detection_eval = 5.55847
-I0511 11:49:27.162084  4597 caffe.cpp:501] detection_eval = 11.3891
-I0511 11:49:27.162088  4597 caffe.cpp:501] detection_eval = 0.0478307
-I0511 11:49:27.162092  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.162096  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162099  4597 caffe.cpp:501] detection_eval = 5.5625
-I0511 11:49:27.162103  4597 caffe.cpp:501] detection_eval = 11.369
-I0511 11:49:27.162107  4597 caffe.cpp:501] detection_eval = 0.0431125
-I0511 11:49:27.162111  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.162114  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.162118  4597 caffe.cpp:501] detection_eval = 5.56653
-I0511 11:49:27.162122  4597 caffe.cpp:501] detection_eval = 11.4012
-I0511 11:49:27.162127  4597 caffe.cpp:501] detection_eval = 0.0432105
-I0511 11:49:27.162129  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.162133  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.162137  4597 caffe.cpp:501] detection_eval = 5.57056
-I0511 11:49:27.162140  4597 caffe.cpp:501] detection_eval = 11.4536
-I0511 11:49:27.162144  4597 caffe.cpp:501] detection_eval = 0.0533981
-I0511 11:49:27.162148  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.162153  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.162155  4597 caffe.cpp:501] detection_eval = 5.5746
-I0511 11:49:27.162159  4597 caffe.cpp:501] detection_eval = 11.4859
-I0511 11:49:27.162163  4597 caffe.cpp:501] detection_eval = 0.0472518
-I0511 11:49:27.162168  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.162170  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.162174  4597 caffe.cpp:501] detection_eval = 5.58065
-I0511 11:49:27.162178  4597 caffe.cpp:501] detection_eval = 11.5181
-I0511 11:49:27.162183  4597 caffe.cpp:501] detection_eval = 0.0493227
-I0511 11:49:27.162185  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.162189  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162192  4597 caffe.cpp:501] detection_eval = 5.58065
-I0511 11:49:27.162196  4597 caffe.cpp:501] detection_eval = 11.6048
-I0511 11:49:27.162374  4597 caffe.cpp:501] detection_eval = 0.0414111
-I0511 11:49:27.162380  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162384  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.162387  4597 caffe.cpp:501] detection_eval = 5.58266
-I0511 11:49:27.162391  4597 caffe.cpp:501] detection_eval = 11.6371
-I0511 11:49:27.162395  4597 caffe.cpp:501] detection_eval = 0.0464631
-I0511 11:49:27.162400  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162402  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162406  4597 caffe.cpp:501] detection_eval = 5.59073
-I0511 11:49:27.162410  4597 caffe.cpp:501] detection_eval = 11.5504
-I0511 11:49:27.162415  4597 caffe.cpp:501] detection_eval = 0.0493058
-I0511 11:49:27.162418  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162422  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162431  4597 caffe.cpp:501] detection_eval = 5.59274
-I0511 11:49:27.162434  4597 caffe.cpp:501] detection_eval = 11.625
-I0511 11:49:27.162438  4597 caffe.cpp:501] detection_eval = 0.0454611
-I0511 11:49:27.162442  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162446  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162451  4597 caffe.cpp:501] detection_eval = 5.59476
-I0511 11:49:27.162454  4597 caffe.cpp:501] detection_eval = 11.6835
-I0511 11:49:27.162458  4597 caffe.cpp:501] detection_eval = 0.0434493
-I0511 11:49:27.162461  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162466  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162469  4597 caffe.cpp:501] detection_eval = 5.60282
-I0511 11:49:27.162472  4597 caffe.cpp:501] detection_eval = 11.621
-I0511 11:49:27.162477  4597 caffe.cpp:501] detection_eval = 0.0392699
-I0511 11:49:27.162480  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.162484  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.162488  4597 caffe.cpp:501] detection_eval = 5.61089
-I0511 11:49:27.162492  4597 caffe.cpp:501] detection_eval = 11.5847
-I0511 11:49:27.162497  4597 caffe.cpp:501] detection_eval = 0.0437702
-I0511 11:49:27.162499  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.162503  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162508  4597 caffe.cpp:501] detection_eval = 5.61694
-I0511 11:49:27.162511  4597 caffe.cpp:501] detection_eval = 11.5282
-I0511 11:49:27.162515  4597 caffe.cpp:501] detection_eval = 0.0404295
-I0511 11:49:27.162518  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162523  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162526  4597 caffe.cpp:501] detection_eval = 5.62097
-I0511 11:49:27.162530  4597 caffe.cpp:501] detection_eval = 11.5585
-I0511 11:49:27.162534  4597 caffe.cpp:501] detection_eval = 0.0477996
-I0511 11:49:27.162537  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.162541  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162545  4597 caffe.cpp:501] detection_eval = 5.625
-I0511 11:49:27.162549  4597 caffe.cpp:501] detection_eval = 11.5726
-I0511 11:49:27.162552  4597 caffe.cpp:501] detection_eval = 0.0435699
-I0511 11:49:27.162556  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.162560  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.162564  4597 caffe.cpp:501] detection_eval = 5.6371
-I0511 11:49:27.162569  4597 caffe.cpp:501] detection_eval = 11.4617
-I0511 11:49:27.162572  4597 caffe.cpp:501] detection_eval = 0.0415749
-I0511 11:49:27.162575  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162580  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162583  4597 caffe.cpp:501] detection_eval = 5.6371
-I0511 11:49:27.162587  4597 caffe.cpp:501] detection_eval = 11.506
-I0511 11:49:27.162591  4597 caffe.cpp:501] detection_eval = 0.0371579
-I0511 11:49:27.162595  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.162598  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.162602  4597 caffe.cpp:501] detection_eval = 5.64315
-I0511 11:49:27.162606  4597 caffe.cpp:501] detection_eval = 11.5
-I0511 11:49:27.162611  4597 caffe.cpp:501] detection_eval = 0.0378634
-I0511 11:49:27.162614  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.162618  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.162621  4597 caffe.cpp:501] detection_eval = 5.64516
-I0511 11:49:27.162626  4597 caffe.cpp:501] detection_eval = 11.5887
-I0511 11:49:27.162629  4597 caffe.cpp:501] detection_eval = 0.0424586
-I0511 11:49:27.162633  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.162637  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.162641  4597 caffe.cpp:501] detection_eval = 5.64718
-I0511 11:49:27.162644  4597 caffe.cpp:501] detection_eval = 11.6593
-I0511 11:49:27.162648  4597 caffe.cpp:501] detection_eval = 0.0441311
-I0511 11:49:27.162652  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.162655  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.162663  4597 caffe.cpp:501] detection_eval = 5.65524
-I0511 11:49:27.162667  4597 caffe.cpp:501] detection_eval = 11.627
-I0511 11:49:27.162672  4597 caffe.cpp:501] detection_eval = 0.0482354
-I0511 11:49:27.162674  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.162678  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.162683  4597 caffe.cpp:501] detection_eval = 5.66129
-I0511 11:49:27.162686  4597 caffe.cpp:501] detection_eval = 11.5867
-I0511 11:49:27.162690  4597 caffe.cpp:501] detection_eval = 0.0463853
-I0511 11:49:27.162694  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.162698  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162701  4597 caffe.cpp:501] detection_eval = 5.66331
-I0511 11:49:27.162705  4597 caffe.cpp:501] detection_eval = 11.5867
-I0511 11:49:27.162709  4597 caffe.cpp:501] detection_eval = 0.0423538
-I0511 11:49:27.162714  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162716  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.162720  4597 caffe.cpp:501] detection_eval = 5.66331
-I0511 11:49:27.162724  4597 caffe.cpp:501] detection_eval = 11.6794
-I0511 11:49:27.162729  4597 caffe.cpp:501] detection_eval = 0.0366064
-I0511 11:49:27.162732  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.162735  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.162739  4597 caffe.cpp:501] detection_eval = 5.66532
-I0511 11:49:27.162744  4597 caffe.cpp:501] detection_eval = 11.7137
-I0511 11:49:27.162747  4597 caffe.cpp:501] detection_eval = 0.0415668
-I0511 11:49:27.162750  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162755  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162758  4597 caffe.cpp:501] detection_eval = 5.66935
-I0511 11:49:27.162762  4597 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:49:27.162766  4597 caffe.cpp:501] detection_eval = 0.0378184
-I0511 11:49:27.162770  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.162773  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162777  4597 caffe.cpp:501] detection_eval = 5.67339
-I0511 11:49:27.162781  4597 caffe.cpp:501] detection_eval = 11.7238
-I0511 11:49:27.162784  4597 caffe.cpp:501] detection_eval = 0.0453912
-I0511 11:49:27.162788  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162792  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162796  4597 caffe.cpp:501] detection_eval = 5.67742
-I0511 11:49:27.162799  4597 caffe.cpp:501] detection_eval = 11.6976
-I0511 11:49:27.162803  4597 caffe.cpp:501] detection_eval = 0.0440392
-I0511 11:49:27.162807  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.162811  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162814  4597 caffe.cpp:501] detection_eval = 5.68145
-I0511 11:49:27.162818  4597 caffe.cpp:501] detection_eval = 11.7177
-I0511 11:49:27.162822  4597 caffe.cpp:501] detection_eval = 0.0465293
-I0511 11:49:27.162827  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162830  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163008  4597 caffe.cpp:501] detection_eval = 5.6875
-I0511 11:49:27.163014  4597 caffe.cpp:501] detection_eval = 11.6855
-I0511 11:49:27.163018  4597 caffe.cpp:501] detection_eval = 0.0466328
-I0511 11:49:27.163022  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.163025  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163029  4597 caffe.cpp:501] detection_eval = 5.68952
-I0511 11:49:27.163033  4597 caffe.cpp:501] detection_eval = 11.7056
-I0511 11:49:27.163038  4597 caffe.cpp:501] detection_eval = 0.0445552
-I0511 11:49:27.163041  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.163044  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.163048  4597 caffe.cpp:501] detection_eval = 5.68952
-I0511 11:49:27.163053  4597 caffe.cpp:501] detection_eval = 11.7722
-I0511 11:49:27.163056  4597 caffe.cpp:501] detection_eval = 0.0455712
-I0511 11:49:27.163059  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.163069  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.163072  4597 caffe.cpp:501] detection_eval = 5.6996
-I0511 11:49:27.163076  4597 caffe.cpp:501] detection_eval = 11.6794
-I0511 11:49:27.163080  4597 caffe.cpp:501] detection_eval = 0.0432129
-I0511 11:49:27.163084  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.163089  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.163091  4597 caffe.cpp:501] detection_eval = 5.70363
-I0511 11:49:27.163095  4597 caffe.cpp:501] detection_eval = 11.6472
-I0511 11:49:27.163100  4597 caffe.cpp:501] detection_eval = 0.044814
-I0511 11:49:27.163103  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163107  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163110  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163115  4597 caffe.cpp:501] detection_eval = 11.6452
-I0511 11:49:27.163118  4597 caffe.cpp:501] detection_eval = 0.0442991
-I0511 11:49:27.163122  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.163125  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163130  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163132  4597 caffe.cpp:501] detection_eval = 11.6915
-I0511 11:49:27.163136  4597 caffe.cpp:501] detection_eval = 0.0426855
-I0511 11:49:27.163141  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.163144  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163148  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163151  4597 caffe.cpp:501] detection_eval = 11.75
-I0511 11:49:27.163156  4597 caffe.cpp:501] detection_eval = 0.0402009
-I0511 11:49:27.163159  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163162  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163166  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163170  4597 caffe.cpp:501] detection_eval = 11.8266
-I0511 11:49:27.163174  4597 caffe.cpp:501] detection_eval = 0.0375853
-I0511 11:49:27.163178  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.163182  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163185  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163189  4597 caffe.cpp:501] detection_eval = 11.875
-I0511 11:49:27.163193  4597 caffe.cpp:501] detection_eval = 0.0399351
-I0511 11:49:27.163197  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.163200  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163204  4597 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:49:27.163208  4597 caffe.cpp:501] detection_eval = 11.8427
-I0511 11:49:27.163211  4597 caffe.cpp:501] detection_eval = 0.0388135
-I0511 11:49:27.163215  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163219  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163223  4597 caffe.cpp:501] detection_eval = 5.71774
-I0511 11:49:27.163226  4597 caffe.cpp:501] detection_eval = 11.8851
-I0511 11:49:27.163230  4597 caffe.cpp:501] detection_eval = 0.0457987
-I0511 11:49:27.163234  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.163240  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.163244  4597 caffe.cpp:501] detection_eval = 5.72177
-I0511 11:49:27.163249  4597 caffe.cpp:501] detection_eval = 11.9052
-I0511 11:49:27.163251  4597 caffe.cpp:501] detection_eval = 0.0446153
-I0511 11:49:27.163255  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.163259  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.163264  4597 caffe.cpp:501] detection_eval = 5.72782
-I0511 11:49:27.163266  4597 caffe.cpp:501] detection_eval = 11.8629
-I0511 11:49:27.163270  4597 caffe.cpp:501] detection_eval = 0.0366044
-I0511 11:49:27.163275  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.163278  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.163281  4597 caffe.cpp:501] detection_eval = 5.73185
-I0511 11:49:27.163285  4597 caffe.cpp:501] detection_eval = 11.8589
-I0511 11:49:27.163290  4597 caffe.cpp:501] detection_eval = 0.0373293
-I0511 11:49:27.163293  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163301  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163305  4597 caffe.cpp:501] detection_eval = 5.73185
-I0511 11:49:27.163309  4597 caffe.cpp:501] detection_eval = 11.9335
-I0511 11:49:27.163313  4597 caffe.cpp:501] detection_eval = 0.0344321
-I0511 11:49:27.163317  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.163321  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.163324  4597 caffe.cpp:501] detection_eval = 5.7379
-I0511 11:49:27.163327  4597 caffe.cpp:501] detection_eval = 11.9556
-I0511 11:49:27.163331  4597 caffe.cpp:501] detection_eval = 0.0369631
-I0511 11:49:27.163336  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163339  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163343  4597 caffe.cpp:501] detection_eval = 5.74194
-I0511 11:49:27.163347  4597 caffe.cpp:501] detection_eval = 11.9819
-I0511 11:49:27.163352  4597 caffe.cpp:501] detection_eval = 0.0419468
-I0511 11:49:27.163355  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163359  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163363  4597 caffe.cpp:501] detection_eval = 5.74798
-I0511 11:49:27.163367  4597 caffe.cpp:501] detection_eval = 12.0202
-I0511 11:49:27.163370  4597 caffe.cpp:501] detection_eval = 0.0448674
-I0511 11:49:27.163374  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.163378  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163383  4597 caffe.cpp:501] detection_eval = 5.75
-I0511 11:49:27.163385  4597 caffe.cpp:501] detection_eval = 12.0665
-I0511 11:49:27.163389  4597 caffe.cpp:501] detection_eval = 0.0403543
-I0511 11:49:27.163393  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163398  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163400  4597 caffe.cpp:501] detection_eval = 5.75403
-I0511 11:49:27.163404  4597 caffe.cpp:501] detection_eval = 12.0544
-I0511 11:49:27.163408  4597 caffe.cpp:501] detection_eval = 0.0392934
-I0511 11:49:27.163413  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.163416  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163419  4597 caffe.cpp:501] detection_eval = 5.75806
-I0511 11:49:27.163424  4597 caffe.cpp:501] detection_eval = 12.0323
-I0511 11:49:27.163427  4597 caffe.cpp:501] detection_eval = 0.0426397
-I0511 11:49:27.163431  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163435  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163439  4597 caffe.cpp:501] detection_eval = 5.76008
-I0511 11:49:27.163442  4597 caffe.cpp:501] detection_eval = 12.1089
-I0511 11:49:27.163446  4597 caffe.cpp:501] detection_eval = 0.0402482
-I0511 11:49:27.163450  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163455  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163458  4597 caffe.cpp:501] detection_eval = 5.76411
-I0511 11:49:27.163461  4597 caffe.cpp:501] detection_eval = 12.0867
-I0511 11:49:27.163465  4597 caffe.cpp:501] detection_eval = 0.0386994
-I0511 11:49:27.163663  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163669  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163673  4597 caffe.cpp:501] detection_eval = 5.77218
-I0511 11:49:27.163677  4597 caffe.cpp:501] detection_eval = 12.0544
-I0511 11:49:27.163681  4597 caffe.cpp:501] detection_eval = 0.0352902
-I0511 11:49:27.163684  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.163688  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163692  4597 caffe.cpp:501] detection_eval = 5.77621
-I0511 11:49:27.163695  4597 caffe.cpp:501] detection_eval = 12.0403
-I0511 11:49:27.163699  4597 caffe.cpp:501] detection_eval = 0.036581
-I0511 11:49:27.163703  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163707  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163710  4597 caffe.cpp:501] detection_eval = 5.77621
-I0511 11:49:27.163714  4597 caffe.cpp:501] detection_eval = 12.1028
-I0511 11:49:27.163718  4597 caffe.cpp:501] detection_eval = 0.0353292
-I0511 11:49:27.163727  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.163731  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163734  4597 caffe.cpp:501] detection_eval = 5.78024
-I0511 11:49:27.163738  4597 caffe.cpp:501] detection_eval = 12.0948
-I0511 11:49:27.163743  4597 caffe.cpp:501] detection_eval = 0.0369279
-I0511 11:49:27.163746  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163750  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.163753  4597 caffe.cpp:501] detection_eval = 5.78629
-I0511 11:49:27.163758  4597 caffe.cpp:501] detection_eval = 12.0403
-I0511 11:49:27.163761  4597 caffe.cpp:501] detection_eval = 0.036216
-I0511 11:49:27.163765  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.163769  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.163772  4597 caffe.cpp:501] detection_eval = 5.78831
-I0511 11:49:27.163776  4597 caffe.cpp:501] detection_eval = 12.1149
-I0511 11:49:27.163780  4597 caffe.cpp:501] detection_eval = 0.0408232
-I0511 11:49:27.163784  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163787  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163791  4597 caffe.cpp:501] detection_eval = 5.8004
-I0511 11:49:27.163794  4597 caffe.cpp:501] detection_eval = 12.002
-I0511 11:49:27.163799  4597 caffe.cpp:501] detection_eval = 0.0424982
-I0511 11:49:27.163802  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163806  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163810  4597 caffe.cpp:501] detection_eval = 5.8004
-I0511 11:49:27.163813  4597 caffe.cpp:501] detection_eval = 12.0887
-I0511 11:49:27.163817  4597 caffe.cpp:501] detection_eval = 0.0353425
-I0511 11:49:27.163821  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163825  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163828  4597 caffe.cpp:501] detection_eval = 5.80645
-I0511 11:49:27.163832  4597 caffe.cpp:501] detection_eval = 12.1129
-I0511 11:49:27.163836  4597 caffe.cpp:501] detection_eval = 0.0404876
-I0511 11:49:27.163841  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163843  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163847  4597 caffe.cpp:501] detection_eval = 5.8125
-I0511 11:49:27.163851  4597 caffe.cpp:501] detection_eval = 12.0927
-I0511 11:49:27.163854  4597 caffe.cpp:501] detection_eval = 0.0459566
-I0511 11:49:27.163858  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.163862  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.163866  4597 caffe.cpp:501] detection_eval = 5.81452
-I0511 11:49:27.163869  4597 caffe.cpp:501] detection_eval = 12.121
-I0511 11:49:27.163873  4597 caffe.cpp:501] detection_eval = 0.039085
-I0511 11:49:27.163877  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163882  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163885  4597 caffe.cpp:501] detection_eval = 5.81855
-I0511 11:49:27.163889  4597 caffe.cpp:501] detection_eval = 12.1048
-I0511 11:49:27.163893  4597 caffe.cpp:501] detection_eval = 0.0381383
-I0511 11:49:27.163897  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163902  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163904  4597 caffe.cpp:501] detection_eval = 5.81855
-I0511 11:49:27.163908  4597 caffe.cpp:501] detection_eval = 12.1774
-I0511 11:49:27.163913  4597 caffe.cpp:501] detection_eval = 0.0394167
-I0511 11:49:27.163916  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163920  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163923  4597 caffe.cpp:501] detection_eval = 5.81855
-I0511 11:49:27.163928  4597 caffe.cpp:501] detection_eval = 12.2802
-I0511 11:49:27.163931  4597 caffe.cpp:501] detection_eval = 0.03695
-I0511 11:49:27.163935  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.163939  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.163944  4597 caffe.cpp:501] detection_eval = 5.82056
-I0511 11:49:27.163946  4597 caffe.cpp:501] detection_eval = 12.3226
-I0511 11:49:27.163954  4597 caffe.cpp:501] detection_eval = 0.0371963
-I0511 11:49:27.163959  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163962  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163966  4597 caffe.cpp:501] detection_eval = 5.8246
-I0511 11:49:27.163969  4597 caffe.cpp:501] detection_eval = 12.3024
-I0511 11:49:27.163975  4597 caffe.cpp:501] detection_eval = 0.0401487
-I0511 11:49:27.163978  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.163981  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163985  4597 caffe.cpp:501] detection_eval = 5.82661
-I0511 11:49:27.163990  4597 caffe.cpp:501] detection_eval = 12.3629
-I0511 11:49:27.163993  4597 caffe.cpp:501] detection_eval = 0.0408615
-I0511 11:49:27.163997  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.164001  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.164005  4597 caffe.cpp:501] detection_eval = 5.83669
-I0511 11:49:27.164008  4597 caffe.cpp:501] detection_eval = 12.2681
-I0511 11:49:27.164012  4597 caffe.cpp:501] detection_eval = 0.0363798
-I0511 11:49:27.164016  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.164019  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.164023  4597 caffe.cpp:501] detection_eval = 5.83871
-I0511 11:49:27.164027  4597 caffe.cpp:501] detection_eval = 12.3427
-I0511 11:49:27.164031  4597 caffe.cpp:501] detection_eval = 0.0426772
-I0511 11:49:27.164034  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.164038  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.164042  4597 caffe.cpp:501] detection_eval = 5.84073
-I0511 11:49:27.164047  4597 caffe.cpp:501] detection_eval = 12.4093
-I0511 11:49:27.164049  4597 caffe.cpp:501] detection_eval = 0.0398318
-I0511 11:49:27.164053  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164057  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.164062  4597 caffe.cpp:501] detection_eval = 5.84073
-I0511 11:49:27.164065  4597 caffe.cpp:501] detection_eval = 12.5464
-I0511 11:49:27.164069  4597 caffe.cpp:501] detection_eval = 0.0405751
-I0511 11:49:27.164072  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.164077  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.164080  4597 caffe.cpp:501] detection_eval = 5.85081
-I0511 11:49:27.164083  4597 caffe.cpp:501] detection_eval = 12.6028
-I0511 11:49:27.164088  4597 caffe.cpp:501] detection_eval = 0.0437554
-I0511 11:49:27.164091  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164095  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.164099  4597 caffe.cpp:501] detection_eval = 5.85282
-I0511 11:49:27.164103  4597 caffe.cpp:501] detection_eval = 12.7702
-I0511 11:49:27.164108  4597 caffe.cpp:501] detection_eval = 0.0417783
-I0511 11:49:27.164111  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.164115  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.164120  4597 caffe.cpp:501] detection_eval = 5.85685
-I0511 11:49:27.164304  4597 caffe.cpp:501] detection_eval = 12.9194
-I0511 11:49:27.164311  4597 caffe.cpp:501] detection_eval = 0.0425652
-I0511 11:49:27.164314  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.164319  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164322  4597 caffe.cpp:501] detection_eval = 6.1875
-I0511 11:49:27.164326  4597 caffe.cpp:501] detection_eval = 7.95565
-I0511 11:49:27.164330  4597 caffe.cpp:501] detection_eval = 0.0710047
-I0511 11:49:27.164333  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.164337  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.164341  4597 caffe.cpp:501] detection_eval = 6.18952
-I0511 11:49:27.164345  4597 caffe.cpp:501] detection_eval = 8.11694
-I0511 11:49:27.164348  4597 caffe.cpp:501] detection_eval = 0.0543399
-I0511 11:49:27.164352  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.164356  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164361  4597 caffe.cpp:501] detection_eval = 6.19355
-I0511 11:49:27.164363  4597 caffe.cpp:501] detection_eval = 8.16935
-I0511 11:49:27.164372  4597 caffe.cpp:501] detection_eval = 0.0498162
-I0511 11:49:27.164376  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.164381  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.164384  4597 caffe.cpp:501] detection_eval = 6.19758
-I0511 11:49:27.164387  4597 caffe.cpp:501] detection_eval = 8.20968
-I0511 11:49:27.164391  4597 caffe.cpp:501] detection_eval = 0.0504134
-I0511 11:49:27.164396  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.164399  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164403  4597 caffe.cpp:501] detection_eval = 6.20161
-I0511 11:49:27.164407  4597 caffe.cpp:501] detection_eval = 8.23992
-I0511 11:49:27.164410  4597 caffe.cpp:501] detection_eval = 0.0517857
-I0511 11:49:27.164414  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.164418  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.164422  4597 caffe.cpp:501] detection_eval = 6.20363
-I0511 11:49:27.164425  4597 caffe.cpp:501] detection_eval = 8.28024
-I0511 11:49:27.164429  4597 caffe.cpp:501] detection_eval = 0.0472596
-I0511 11:49:27.164433  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.164436  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.164440  4597 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:49:27.164444  4597 caffe.cpp:501] detection_eval = 8.33065
-I0511 11:49:27.164448  4597 caffe.cpp:501] detection_eval = 0.0494016
-I0511 11:49:27.164451  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.164455  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.164459  4597 caffe.cpp:501] detection_eval = 6.21573
-I0511 11:49:27.164463  4597 caffe.cpp:501] detection_eval = 8.26613
-I0511 11:49:27.164466  4597 caffe.cpp:501] detection_eval = 0.0445944
-I0511 11:49:27.164470  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.164474  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164477  4597 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:49:27.164481  4597 caffe.cpp:501] detection_eval = 8.22782
-I0511 11:49:27.164485  4597 caffe.cpp:501] detection_eval = 0.0461823
-I0511 11:49:27.164489  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.164494  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.164496  4597 caffe.cpp:501] detection_eval = 6.23185
-I0511 11:49:27.164500  4597 caffe.cpp:501] detection_eval = 8.18952
-I0511 11:49:27.164505  4597 caffe.cpp:501] detection_eval = 0.041241
-I0511 11:49:27.164507  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164511  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.164515  4597 caffe.cpp:501] detection_eval = 6.23185
-I0511 11:49:27.164520  4597 caffe.cpp:501] detection_eval = 8.26815
-I0511 11:49:27.164522  4597 caffe.cpp:501] detection_eval = 0.0411695
-I0511 11:49:27.164553  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.164557  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.164562  4597 caffe.cpp:501] detection_eval = 6.2379
-I0511 11:49:27.164566  4597 caffe.cpp:501] detection_eval = 8.29032
-I0511 11:49:27.164569  4597 caffe.cpp:501] detection_eval = 0.0415703
-I0511 11:49:27.164573  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164577  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.164582  4597 caffe.cpp:501] detection_eval = 6.2379
-I0511 11:49:27.164584  4597 caffe.cpp:501] detection_eval = 8.36089
-I0511 11:49:27.164588  4597 caffe.cpp:501] detection_eval = 0.0380232
-I0511 11:49:27.164592  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.164597  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.164599  4597 caffe.cpp:501] detection_eval = 6.24194
-I0511 11:49:27.164602  4597 caffe.cpp:501] detection_eval = 8.35081
-I0511 11:49:27.164607  4597 caffe.cpp:501] detection_eval = 0.0380361
-I0511 11:49:27.164610  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.164614  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.164618  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.164628  4597 caffe.cpp:501] detection_eval = 8.42137
-I0511 11:49:27.164633  4597 caffe.cpp:501] detection_eval = 0.0435461
-I0511 11:49:27.164636  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164640  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.164644  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.164649  4597 caffe.cpp:501] detection_eval = 8.45363
-I0511 11:49:27.164651  4597 caffe.cpp:501] detection_eval = 0.038644
-I0511 11:49:27.164655  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.164659  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.164662  4597 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:49:27.164666  4597 caffe.cpp:501] detection_eval = 8.52621
-I0511 11:49:27.164670  4597 caffe.cpp:501] detection_eval = 0.0411444
-I0511 11:49:27.164674  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.164678  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.164682  4597 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:49:27.164686  4597 caffe.cpp:501] detection_eval = 8.59073
-I0511 11:49:27.164690  4597 caffe.cpp:501] detection_eval = 0.0423966
-I0511 11:49:27.164693  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.164697  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164701  4597 caffe.cpp:501] detection_eval = 6.25
-I0511 11:49:27.164705  4597 caffe.cpp:501] detection_eval = 8.625
-I0511 11:49:27.164708  4597 caffe.cpp:501] detection_eval = 0.0414748
-I0511 11:49:27.164712  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.164716  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.164719  4597 caffe.cpp:501] detection_eval = 6.25
-I0511 11:49:27.164723  4597 caffe.cpp:501] detection_eval = 8.70565
-I0511 11:49:27.164727  4597 caffe.cpp:501] detection_eval = 0.047824
-I0511 11:49:27.164731  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.164734  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.164738  4597 caffe.cpp:501] detection_eval = 6.25403
-I0511 11:49:27.164742  4597 caffe.cpp:501] detection_eval = 8.7379
-I0511 11:49:27.164746  4597 caffe.cpp:501] detection_eval = 0.0440503
-I0511 11:49:27.164749  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.164753  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.164757  4597 caffe.cpp:501] detection_eval = 6.25403
-I0511 11:49:27.164760  4597 caffe.cpp:501] detection_eval = 8.84073
-I0511 11:49:27.164764  4597 caffe.cpp:501] detection_eval = 0.043202
-I0511 11:49:27.164768  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.164772  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.164777  4597 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:49:27.164780  4597 caffe.cpp:501] detection_eval = 8.78226
-I0511 11:49:27.164784  4597 caffe.cpp:501] detection_eval = 0.0408459
-I0511 11:49:27.164788  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.164976  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.164983  4597 caffe.cpp:501] detection_eval = 6.27218
-I0511 11:49:27.164988  4597 caffe.cpp:501] detection_eval = 8.66129
-I0511 11:49:27.164991  4597 caffe.cpp:501] detection_eval = 0.0375982
-I0511 11:49:27.164995  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.164999  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165002  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.165006  4597 caffe.cpp:501] detection_eval = 8.71371
-I0511 11:49:27.165010  4597 caffe.cpp:501] detection_eval = 0.0380173
-I0511 11:49:27.165014  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.165017  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165021  4597 caffe.cpp:501] detection_eval = 6.27621
-I0511 11:49:27.165025  4597 caffe.cpp:501] detection_eval = 8.75403
-I0511 11:49:27.165029  4597 caffe.cpp:501] detection_eval = 0.0410263
-I0511 11:49:27.165032  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165036  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165040  4597 caffe.cpp:501] detection_eval = 6.28629
-I0511 11:49:27.165048  4597 caffe.cpp:501] detection_eval = 8.66935
-I0511 11:49:27.165052  4597 caffe.cpp:501] detection_eval = 0.0394351
-I0511 11:49:27.165056  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165060  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.165065  4597 caffe.cpp:501] detection_eval = 6.29032
-I0511 11:49:27.165067  4597 caffe.cpp:501] detection_eval = 8.71169
-I0511 11:49:27.165071  4597 caffe.cpp:501] detection_eval = 0.0424281
-I0511 11:49:27.165076  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.165079  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165082  4597 caffe.cpp:501] detection_eval = 6.29234
-I0511 11:49:27.165086  4597 caffe.cpp:501] detection_eval = 8.75605
-I0511 11:49:27.165091  4597 caffe.cpp:501] detection_eval = 0.0393914
-I0511 11:49:27.165094  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165097  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165102  4597 caffe.cpp:501] detection_eval = 6.29234
-I0511 11:49:27.165105  4597 caffe.cpp:501] detection_eval = 8.82863
-I0511 11:49:27.165109  4597 caffe.cpp:501] detection_eval = 0.0390766
-I0511 11:49:27.165113  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165117  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165120  4597 caffe.cpp:501] detection_eval = 6.29435
-I0511 11:49:27.165124  4597 caffe.cpp:501] detection_eval = 8.89315
-I0511 11:49:27.165128  4597 caffe.cpp:501] detection_eval = 0.0416115
-I0511 11:49:27.165132  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165136  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165139  4597 caffe.cpp:501] detection_eval = 6.29839
-I0511 11:49:27.165143  4597 caffe.cpp:501] detection_eval = 8.875
-I0511 11:49:27.165148  4597 caffe.cpp:501] detection_eval = 0.0403249
-I0511 11:49:27.165151  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.165154  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165158  4597 caffe.cpp:501] detection_eval = 6.3004
-I0511 11:49:27.165161  4597 caffe.cpp:501] detection_eval = 8.90524
-I0511 11:49:27.165165  4597 caffe.cpp:501] detection_eval = 0.0396633
-I0511 11:49:27.165169  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165174  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.165177  4597 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:49:27.165180  4597 caffe.cpp:501] detection_eval = 8.9879
-I0511 11:49:27.165184  4597 caffe.cpp:501] detection_eval = 0.03926
-I0511 11:49:27.165189  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165192  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165195  4597 caffe.cpp:501] detection_eval = 6.30645
-I0511 11:49:27.165199  4597 caffe.cpp:501] detection_eval = 9.03629
-I0511 11:49:27.165204  4597 caffe.cpp:501] detection_eval = 0.0462224
-I0511 11:49:27.165207  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165211  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.165215  4597 caffe.cpp:501] detection_eval = 6.31048
-I0511 11:49:27.165218  4597 caffe.cpp:501] detection_eval = 9.04839
-I0511 11:49:27.165222  4597 caffe.cpp:501] detection_eval = 0.0469885
-I0511 11:49:27.165226  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.165230  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.165233  4597 caffe.cpp:501] detection_eval = 6.3125
-I0511 11:49:27.165237  4597 caffe.cpp:501] detection_eval = 9.05847
-I0511 11:49:27.165241  4597 caffe.cpp:501] detection_eval = 0.0391533
-I0511 11:49:27.165244  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165248  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165252  4597 caffe.cpp:501] detection_eval = 6.3125
-I0511 11:49:27.165256  4597 caffe.cpp:501] detection_eval = 9.13911
-I0511 11:49:27.165259  4597 caffe.cpp:501] detection_eval = 0.0391493
-I0511 11:49:27.165263  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165267  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165274  4597 caffe.cpp:501] detection_eval = 6.31452
-I0511 11:49:27.165278  4597 caffe.cpp:501] detection_eval = 9.18347
-I0511 11:49:27.165282  4597 caffe.cpp:501] detection_eval = 0.0419038
-I0511 11:49:27.165287  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165290  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165294  4597 caffe.cpp:501] detection_eval = 6.31855
-I0511 11:49:27.165298  4597 caffe.cpp:501] detection_eval = 9.24194
-I0511 11:49:27.165302  4597 caffe.cpp:501] detection_eval = 0.047811
-I0511 11:49:27.165305  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.165309  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.165313  4597 caffe.cpp:501] detection_eval = 6.31855
-I0511 11:49:27.165316  4597 caffe.cpp:501] detection_eval = 9.3004
-I0511 11:49:27.165321  4597 caffe.cpp:501] detection_eval = 0.0427403
-I0511 11:49:27.165325  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165328  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165333  4597 caffe.cpp:501] detection_eval = 6.32863
-I0511 11:49:27.165336  4597 caffe.cpp:501] detection_eval = 9.26613
-I0511 11:49:27.165339  4597 caffe.cpp:501] detection_eval = 0.0379645
-I0511 11:49:27.165343  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.165347  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165351  4597 caffe.cpp:501] detection_eval = 6.33065
-I0511 11:49:27.165354  4597 caffe.cpp:501] detection_eval = 9.29839
-I0511 11:49:27.165359  4597 caffe.cpp:501] detection_eval = 0.038076
-I0511 11:49:27.165362  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.165366  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165369  4597 caffe.cpp:501] detection_eval = 6.33871
-I0511 11:49:27.165374  4597 caffe.cpp:501] detection_eval = 9.26008
-I0511 11:49:27.165377  4597 caffe.cpp:501] detection_eval = 0.0373264
-I0511 11:49:27.165381  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165385  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.165388  4597 caffe.cpp:501] detection_eval = 6.34274
-I0511 11:49:27.165391  4597 caffe.cpp:501] detection_eval = 9.27419
-I0511 11:49:27.165395  4597 caffe.cpp:501] detection_eval = 0.0348104
-I0511 11:49:27.165400  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.165403  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.165406  4597 caffe.cpp:501] detection_eval = 6.34274
-I0511 11:49:27.165410  4597 caffe.cpp:501] detection_eval = 9.34073
-I0511 11:49:27.165415  4597 caffe.cpp:501] detection_eval = 0.0386115
-I0511 11:49:27.165418  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165422  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165426  4597 caffe.cpp:501] detection_eval = 6.35282
-I0511 11:49:27.165429  4597 caffe.cpp:501] detection_eval = 9.29032
-I0511 11:49:27.165616  4597 caffe.cpp:501] detection_eval = 0.0444557
-I0511 11:49:27.165621  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.165626  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.165629  4597 caffe.cpp:501] detection_eval = 6.35685
-I0511 11:49:27.165633  4597 caffe.cpp:501] detection_eval = 9.30645
-I0511 11:49:27.165637  4597 caffe.cpp:501] detection_eval = 0.037653
-I0511 11:49:27.165642  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165644  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165648  4597 caffe.cpp:501] detection_eval = 6.36492
-I0511 11:49:27.165652  4597 caffe.cpp:501] detection_eval = 9.26815
-I0511 11:49:27.165655  4597 caffe.cpp:501] detection_eval = 0.0390366
-I0511 11:49:27.165659  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165663  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165668  4597 caffe.cpp:501] detection_eval = 6.36492
-I0511 11:49:27.165670  4597 caffe.cpp:501] detection_eval = 9.35484
-I0511 11:49:27.165674  4597 caffe.cpp:501] detection_eval = 0.0425326
-I0511 11:49:27.165678  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165681  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165689  4597 caffe.cpp:501] detection_eval = 6.36895
-I0511 11:49:27.165694  4597 caffe.cpp:501] detection_eval = 9.37298
-I0511 11:49:27.165697  4597 caffe.cpp:501] detection_eval = 0.0398418
-I0511 11:49:27.165701  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165705  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165709  4597 caffe.cpp:501] detection_eval = 6.37097
-I0511 11:49:27.165712  4597 caffe.cpp:501] detection_eval = 9.42137
-I0511 11:49:27.165716  4597 caffe.cpp:501] detection_eval = 0.043694
-I0511 11:49:27.165720  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165724  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165727  4597 caffe.cpp:501] detection_eval = 6.375
-I0511 11:49:27.165731  4597 caffe.cpp:501] detection_eval = 9.42742
-I0511 11:49:27.165735  4597 caffe.cpp:501] detection_eval = 0.0458208
-I0511 11:49:27.165738  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165742  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165746  4597 caffe.cpp:501] detection_eval = 6.37702
-I0511 11:49:27.165750  4597 caffe.cpp:501] detection_eval = 9.50403
-I0511 11:49:27.165753  4597 caffe.cpp:501] detection_eval = 0.0450507
-I0511 11:49:27.165757  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165761  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.165765  4597 caffe.cpp:501] detection_eval = 6.37702
-I0511 11:49:27.165768  4597 caffe.cpp:501] detection_eval = 9.57863
-I0511 11:49:27.165772  4597 caffe.cpp:501] detection_eval = 0.0409484
-I0511 11:49:27.165776  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165779  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.165783  4597 caffe.cpp:501] detection_eval = 6.37702
-I0511 11:49:27.165786  4597 caffe.cpp:501] detection_eval = 9.6875
-I0511 11:49:27.165791  4597 caffe.cpp:501] detection_eval = 0.0449141
-I0511 11:49:27.165794  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165797  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.165802  4597 caffe.cpp:501] detection_eval = 6.38508
-I0511 11:49:27.165805  4597 caffe.cpp:501] detection_eval = 9.69355
-I0511 11:49:27.165809  4597 caffe.cpp:501] detection_eval = 0.0414317
-I0511 11:49:27.165812  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165817  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.165820  4597 caffe.cpp:501] detection_eval = 6.3871
-I0511 11:49:27.165823  4597 caffe.cpp:501] detection_eval = 9.80645
-I0511 11:49:27.165827  4597 caffe.cpp:501] detection_eval = 0.0417695
-I0511 11:49:27.165832  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165834  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165838  4597 caffe.cpp:501] detection_eval = 6.39113
-I0511 11:49:27.165843  4597 caffe.cpp:501] detection_eval = 9.8004
-I0511 11:49:27.165846  4597 caffe.cpp:501] detection_eval = 0.0433207
-I0511 11:49:27.165850  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165853  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.165858  4597 caffe.cpp:501] detection_eval = 6.39516
-I0511 11:49:27.165861  4597 caffe.cpp:501] detection_eval = 9.85282
-I0511 11:49:27.165864  4597 caffe.cpp:501] detection_eval = 0.0437603
-I0511 11:49:27.165868  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165872  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165876  4597 caffe.cpp:501] detection_eval = 6.39718
-I0511 11:49:27.165879  4597 caffe.cpp:501] detection_eval = 9.92944
-I0511 11:49:27.165884  4597 caffe.cpp:501] detection_eval = 0.0469438
-I0511 11:49:27.165887  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165890  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.165894  4597 caffe.cpp:501] detection_eval = 6.39718
-I0511 11:49:27.165899  4597 caffe.cpp:501] detection_eval = 9.99798
-I0511 11:49:27.165902  4597 caffe.cpp:501] detection_eval = 0.0422279
-I0511 11:49:27.165905  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.165913  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.165917  4597 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:49:27.165920  4597 caffe.cpp:501] detection_eval = 9.99194
-I0511 11:49:27.165925  4597 caffe.cpp:501] detection_eval = 0.0505361
-I0511 11:49:27.165928  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.165931  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.165936  4597 caffe.cpp:501] detection_eval = 6.40726
-I0511 11:49:27.165940  4597 caffe.cpp:501] detection_eval = 10.0141
-I0511 11:49:27.165944  4597 caffe.cpp:501] detection_eval = 0.0402911
-I0511 11:49:27.165948  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.165951  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.165956  4597 caffe.cpp:501] detection_eval = 6.41331
-I0511 11:49:27.165959  4597 caffe.cpp:501] detection_eval = 10.0383
-I0511 11:49:27.165963  4597 caffe.cpp:501] detection_eval = 0.0467144
-I0511 11:49:27.165967  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165971  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165974  4597 caffe.cpp:501] detection_eval = 6.41935
-I0511 11:49:27.165978  4597 caffe.cpp:501] detection_eval = 10.0222
-I0511 11:49:27.165982  4597 caffe.cpp:501] detection_eval = 0.0429677
-I0511 11:49:27.165987  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.165989  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.165993  4597 caffe.cpp:501] detection_eval = 6.42742
-I0511 11:49:27.165997  4597 caffe.cpp:501] detection_eval = 9.97984
-I0511 11:49:27.166000  4597 caffe.cpp:501] detection_eval = 0.036843
-I0511 11:49:27.166004  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.166008  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.166012  4597 caffe.cpp:501] detection_eval = 6.42742
-I0511 11:49:27.166015  4597 caffe.cpp:501] detection_eval = 10.0786
-I0511 11:49:27.166019  4597 caffe.cpp:501] detection_eval = 0.0435872
-I0511 11:49:27.166023  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166028  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166030  4597 caffe.cpp:501] detection_eval = 6.43145
-I0511 11:49:27.166034  4597 caffe.cpp:501] detection_eval = 10.1028
-I0511 11:49:27.166038  4597 caffe.cpp:501] detection_eval = 0.0429136
-I0511 11:49:27.166043  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166045  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.166049  4597 caffe.cpp:501] detection_eval = 6.43145
-I0511 11:49:27.166054  4597 caffe.cpp:501] detection_eval = 10.1996
-I0511 11:49:27.166057  4597 caffe.cpp:501] detection_eval = 0.0437629
-I0511 11:49:27.166060  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166064  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166257  4597 caffe.cpp:501] detection_eval = 6.43347
-I0511 11:49:27.166263  4597 caffe.cpp:501] detection_eval = 10.244
-I0511 11:49:27.166267  4597 caffe.cpp:501] detection_eval = 0.03941
-I0511 11:49:27.166271  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166275  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.166278  4597 caffe.cpp:501] detection_eval = 6.4375
-I0511 11:49:27.166282  4597 caffe.cpp:501] detection_eval = 10.2762
-I0511 11:49:27.166286  4597 caffe.cpp:501] detection_eval = 0.0405624
-I0511 11:49:27.166290  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166293  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.166297  4597 caffe.cpp:501] detection_eval = 6.44355
-I0511 11:49:27.166301  4597 caffe.cpp:501] detection_eval = 10.2661
-I0511 11:49:27.166306  4597 caffe.cpp:501] detection_eval = 0.0467523
-I0511 11:49:27.166309  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166312  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.166316  4597 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:49:27.166321  4597 caffe.cpp:501] detection_eval = 10.2278
-I0511 11:49:27.166324  4597 caffe.cpp:501] detection_eval = 0.0424976
-I0511 11:49:27.166333  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166337  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166340  4597 caffe.cpp:501] detection_eval = 6.45565
-I0511 11:49:27.166344  4597 caffe.cpp:501] detection_eval = 10.2177
-I0511 11:49:27.166347  4597 caffe.cpp:501] detection_eval = 0.0425759
-I0511 11:49:27.166350  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166354  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.166357  4597 caffe.cpp:501] detection_eval = 6.45565
-I0511 11:49:27.166360  4597 caffe.cpp:501] detection_eval = 10.3206
-I0511 11:49:27.166363  4597 caffe.cpp:501] detection_eval = 0.0432726
-I0511 11:49:27.166366  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166370  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.166373  4597 caffe.cpp:501] detection_eval = 6.46169
-I0511 11:49:27.166376  4597 caffe.cpp:501] detection_eval = 10.3044
-I0511 11:49:27.166379  4597 caffe.cpp:501] detection_eval = 0.0396476
-I0511 11:49:27.166383  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166386  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.166389  4597 caffe.cpp:501] detection_eval = 6.47177
-I0511 11:49:27.166393  4597 caffe.cpp:501] detection_eval = 10.2177
-I0511 11:49:27.166395  4597 caffe.cpp:501] detection_eval = 0.0445121
-I0511 11:49:27.166399  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166402  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166405  4597 caffe.cpp:501] detection_eval = 6.47581
-I0511 11:49:27.166409  4597 caffe.cpp:501] detection_eval = 10.254
-I0511 11:49:27.166412  4597 caffe.cpp:501] detection_eval = 0.0411957
-I0511 11:49:27.166415  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166419  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.166421  4597 caffe.cpp:501] detection_eval = 6.48185
-I0511 11:49:27.166424  4597 caffe.cpp:501] detection_eval = 10.3044
-I0511 11:49:27.166429  4597 caffe.cpp:501] detection_eval = 0.0476864
-I0511 11:49:27.166431  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166435  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.166438  4597 caffe.cpp:501] detection_eval = 6.48387
-I0511 11:49:27.166441  4597 caffe.cpp:501] detection_eval = 10.3367
-I0511 11:49:27.166445  4597 caffe.cpp:501] detection_eval = 0.0436602
-I0511 11:49:27.166447  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166451  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166455  4597 caffe.cpp:501] detection_eval = 6.4879
-I0511 11:49:27.166457  4597 caffe.cpp:501] detection_eval = 10.3891
-I0511 11:49:27.166460  4597 caffe.cpp:501] detection_eval = 0.0480804
-I0511 11:49:27.166465  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166467  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.166471  4597 caffe.cpp:501] detection_eval = 6.49194
-I0511 11:49:27.166474  4597 caffe.cpp:501] detection_eval = 10.4093
-I0511 11:49:27.166477  4597 caffe.cpp:501] detection_eval = 0.0521192
-I0511 11:49:27.166481  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166484  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.166487  4597 caffe.cpp:501] detection_eval = 6.49597
-I0511 11:49:27.166491  4597 caffe.cpp:501] detection_eval = 10.4214
-I0511 11:49:27.166493  4597 caffe.cpp:501] detection_eval = 0.0463212
-I0511 11:49:27.166497  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166501  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.166503  4597 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:49:27.166507  4597 caffe.cpp:501] detection_eval = 10.4577
-I0511 11:49:27.166510  4597 caffe.cpp:501] detection_eval = 0.0438618
-I0511 11:49:27.166513  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166517  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.166519  4597 caffe.cpp:501] detection_eval = 6.5
-I0511 11:49:27.166523  4597 caffe.cpp:501] detection_eval = 10.5565
-I0511 11:49:27.166527  4597 caffe.cpp:501] detection_eval = 0.0417948
-I0511 11:49:27.166533  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166537  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.166540  4597 caffe.cpp:501] detection_eval = 6.50403
-I0511 11:49:27.166543  4597 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:49:27.166546  4597 caffe.cpp:501] detection_eval = 0.0370019
-I0511 11:49:27.166550  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.166553  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.166556  4597 caffe.cpp:501] detection_eval = 6.5121
-I0511 11:49:27.166559  4597 caffe.cpp:501] detection_eval = 10.5464
-I0511 11:49:27.166563  4597 caffe.cpp:501] detection_eval = 0.0423572
-I0511 11:49:27.166566  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166569  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.166573  4597 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:49:27.166575  4597 caffe.cpp:501] detection_eval = 10.5101
-I0511 11:49:27.166579  4597 caffe.cpp:501] detection_eval = 0.0417664
-I0511 11:49:27.166582  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166585  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.166589  4597 caffe.cpp:501] detection_eval = 6.52218
-I0511 11:49:27.166592  4597 caffe.cpp:501] detection_eval = 10.5181
-I0511 11:49:27.166595  4597 caffe.cpp:501] detection_eval = 0.0393381
-I0511 11:49:27.166600  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.166604  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.166609  4597 caffe.cpp:501] detection_eval = 6.52823
-I0511 11:49:27.166611  4597 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:49:27.166615  4597 caffe.cpp:501] detection_eval = 0.0440267
-I0511 11:49:27.166618  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166622  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166625  4597 caffe.cpp:501] detection_eval = 6.53629
-I0511 11:49:27.166630  4597 caffe.cpp:501] detection_eval = 10.4859
-I0511 11:49:27.166633  4597 caffe.cpp:501] detection_eval = 0.0369024
-I0511 11:49:27.166637  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.166640  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.166645  4597 caffe.cpp:501] detection_eval = 6.53831
-I0511 11:49:27.166648  4597 caffe.cpp:501] detection_eval = 10.5444
-I0511 11:49:27.166652  4597 caffe.cpp:501] detection_eval = 0.0401352
-I0511 11:49:27.166656  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166661  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.166663  4597 caffe.cpp:501] detection_eval = 6.54234
-I0511 11:49:27.166667  4597 caffe.cpp:501] detection_eval = 10.5827
-I0511 11:49:27.166671  4597 caffe.cpp:501] detection_eval = 0.0389087
-I0511 11:49:27.167176  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167182  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.167186  4597 caffe.cpp:501] detection_eval = 6.54435
-I0511 11:49:27.167189  4597 caffe.cpp:501] detection_eval = 10.6573
-I0511 11:49:27.167193  4597 caffe.cpp:501] detection_eval = 0.0442123
-I0511 11:49:27.167197  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167201  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167206  4597 caffe.cpp:501] detection_eval = 6.54637
-I0511 11:49:27.167208  4597 caffe.cpp:501] detection_eval = 10.6875
-I0511 11:49:27.167212  4597 caffe.cpp:501] detection_eval = 0.0392356
-I0511 11:49:27.167217  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167220  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167224  4597 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:49:27.167227  4597 caffe.cpp:501] detection_eval = 10.6673
-I0511 11:49:27.167232  4597 caffe.cpp:501] detection_eval = 0.0412143
-I0511 11:49:27.167235  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167239  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167243  4597 caffe.cpp:501] detection_eval = 6.55645
-I0511 11:49:27.167246  4597 caffe.cpp:501] detection_eval = 10.6532
-I0511 11:49:27.167254  4597 caffe.cpp:501] detection_eval = 0.0370152
-I0511 11:49:27.167258  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167263  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167266  4597 caffe.cpp:501] detection_eval = 6.55847
-I0511 11:49:27.167269  4597 caffe.cpp:501] detection_eval = 10.7399
-I0511 11:49:27.167273  4597 caffe.cpp:501] detection_eval = 0.0377675
-I0511 11:49:27.167277  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167281  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167284  4597 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:49:27.167289  4597 caffe.cpp:501] detection_eval = 10.752
-I0511 11:49:27.167292  4597 caffe.cpp:501] detection_eval = 0.0435966
-I0511 11:49:27.167296  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167299  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167304  4597 caffe.cpp:501] detection_eval = 6.56653
-I0511 11:49:27.167307  4597 caffe.cpp:501] detection_eval = 10.8206
-I0511 11:49:27.167311  4597 caffe.cpp:501] detection_eval = 0.0392458
-I0511 11:49:27.167315  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167318  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167322  4597 caffe.cpp:501] detection_eval = 6.56855
-I0511 11:49:27.167325  4597 caffe.cpp:501] detection_eval = 10.8468
-I0511 11:49:27.167330  4597 caffe.cpp:501] detection_eval = 0.0400146
-I0511 11:49:27.167333  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167337  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.167341  4597 caffe.cpp:501] detection_eval = 6.5746
-I0511 11:49:27.167345  4597 caffe.cpp:501] detection_eval = 10.8488
-I0511 11:49:27.167348  4597 caffe.cpp:501] detection_eval = 0.0424466
-I0511 11:49:27.167352  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.167356  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.167361  4597 caffe.cpp:501] detection_eval = 6.58669
-I0511 11:49:27.167363  4597 caffe.cpp:501] detection_eval = 10.7399
-I0511 11:49:27.167367  4597 caffe.cpp:501] detection_eval = 0.0352173
-I0511 11:49:27.167371  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.167376  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.167378  4597 caffe.cpp:501] detection_eval = 6.59274
-I0511 11:49:27.167382  4597 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:49:27.167387  4597 caffe.cpp:501] detection_eval = 0.0463454
-I0511 11:49:27.167390  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.167393  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.167397  4597 caffe.cpp:501] detection_eval = 6.59476
-I0511 11:49:27.167402  4597 caffe.cpp:501] detection_eval = 10.8569
-I0511 11:49:27.167405  4597 caffe.cpp:501] detection_eval = 0.0412809
-I0511 11:49:27.167409  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167413  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167418  4597 caffe.cpp:501] detection_eval = 6.59677
-I0511 11:49:27.167420  4597 caffe.cpp:501] detection_eval = 10.8891
-I0511 11:49:27.167424  4597 caffe.cpp:501] detection_eval = 0.0431516
-I0511 11:49:27.167428  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167433  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.167435  4597 caffe.cpp:501] detection_eval = 6.59879
-I0511 11:49:27.167439  4597 caffe.cpp:501] detection_eval = 10.9395
-I0511 11:49:27.167443  4597 caffe.cpp:501] detection_eval = 0.0393903
-I0511 11:49:27.167448  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167450  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167454  4597 caffe.cpp:501] detection_eval = 6.60282
-I0511 11:49:27.167459  4597 caffe.cpp:501] detection_eval = 10.9698
-I0511 11:49:27.167462  4597 caffe.cpp:501] detection_eval = 0.0453448
-I0511 11:49:27.167465  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.167469  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.167474  4597 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:49:27.167476  4597 caffe.cpp:501] detection_eval = 11.0222
-I0511 11:49:27.167484  4597 caffe.cpp:501] detection_eval = 0.0449609
-I0511 11:49:27.167488  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.167492  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.167495  4597 caffe.cpp:501] detection_eval = 6.61089
-I0511 11:49:27.167500  4597 caffe.cpp:501] detection_eval = 10.994
-I0511 11:49:27.167503  4597 caffe.cpp:501] detection_eval = 0.0387491
-I0511 11:49:27.167507  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.167511  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167515  4597 caffe.cpp:501] detection_eval = 6.61089
-I0511 11:49:27.167520  4597 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:49:27.167523  4597 caffe.cpp:501] detection_eval = 0.0465081
-I0511 11:49:27.167527  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.167531  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.167534  4597 caffe.cpp:501] detection_eval = 6.6129
-I0511 11:49:27.167538  4597 caffe.cpp:501] detection_eval = 11.1573
-I0511 11:49:27.167542  4597 caffe.cpp:501] detection_eval = 0.0376537
-I0511 11:49:27.167546  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167549  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167553  4597 caffe.cpp:501] detection_eval = 6.61492
-I0511 11:49:27.167557  4597 caffe.cpp:501] detection_eval = 11.1794
-I0511 11:49:27.167562  4597 caffe.cpp:501] detection_eval = 0.0362195
-I0511 11:49:27.167564  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.167568  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.167572  4597 caffe.cpp:501] detection_eval = 6.61895
-I0511 11:49:27.167575  4597 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:49:27.167579  4597 caffe.cpp:501] detection_eval = 0.037401
-I0511 11:49:27.167583  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167587  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167590  4597 caffe.cpp:501] detection_eval = 6.62298
-I0511 11:49:27.167594  4597 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:49:27.167598  4597 caffe.cpp:501] detection_eval = 0.0384131
-I0511 11:49:27.167603  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167606  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.167609  4597 caffe.cpp:501] detection_eval = 6.62903
-I0511 11:49:27.167613  4597 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:49:27.167618  4597 caffe.cpp:501] detection_eval = 0.0406666
-I0511 11:49:27.167621  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167624  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167629  4597 caffe.cpp:501] detection_eval = 6.63105
-I0511 11:49:27.167801  4597 caffe.cpp:501] detection_eval = 11.244
-I0511 11:49:27.167806  4597 caffe.cpp:501] detection_eval = 0.0376225
-I0511 11:49:27.167810  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167814  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167819  4597 caffe.cpp:501] detection_eval = 6.63105
-I0511 11:49:27.167822  4597 caffe.cpp:501] detection_eval = 11.3327
-I0511 11:49:27.167826  4597 caffe.cpp:501] detection_eval = 0.0416811
-I0511 11:49:27.167830  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167834  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167837  4597 caffe.cpp:501] detection_eval = 6.63911
-I0511 11:49:27.167841  4597 caffe.cpp:501] detection_eval = 11.3065
-I0511 11:49:27.167845  4597 caffe.cpp:501] detection_eval = 0.0433205
-I0511 11:49:27.167848  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.167852  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.167856  4597 caffe.cpp:501] detection_eval = 6.64516
-I0511 11:49:27.167860  4597 caffe.cpp:501] detection_eval = 11.2681
-I0511 11:49:27.167865  4597 caffe.cpp:501] detection_eval = 0.0380282
-I0511 11:49:27.167867  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167871  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167876  4597 caffe.cpp:501] detection_eval = 6.64718
-I0511 11:49:27.167883  4597 caffe.cpp:501] detection_eval = 11.256
-I0511 11:49:27.167887  4597 caffe.cpp:501] detection_eval = 0.0357891
-I0511 11:49:27.167891  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.167896  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167898  4597 caffe.cpp:501] detection_eval = 6.65524
-I0511 11:49:27.167902  4597 caffe.cpp:501] detection_eval = 11.2117
-I0511 11:49:27.167906  4597 caffe.cpp:501] detection_eval = 0.0388631
-I0511 11:49:27.167910  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167914  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167917  4597 caffe.cpp:501] detection_eval = 6.65927
-I0511 11:49:27.167922  4597 caffe.cpp:501] detection_eval = 11.2056
-I0511 11:49:27.167925  4597 caffe.cpp:501] detection_eval = 0.0361406
-I0511 11:49:27.167929  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167932  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167937  4597 caffe.cpp:501] detection_eval = 6.66331
-I0511 11:49:27.167940  4597 caffe.cpp:501] detection_eval = 11.2379
-I0511 11:49:27.167944  4597 caffe.cpp:501] detection_eval = 0.03999
-I0511 11:49:27.167948  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167951  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167955  4597 caffe.cpp:501] detection_eval = 6.66734
-I0511 11:49:27.167959  4597 caffe.cpp:501] detection_eval = 11.3024
-I0511 11:49:27.167963  4597 caffe.cpp:501] detection_eval = 0.0418456
-I0511 11:49:27.167968  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.167970  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167974  4597 caffe.cpp:501] detection_eval = 6.67339
-I0511 11:49:27.167979  4597 caffe.cpp:501] detection_eval = 11.2883
-I0511 11:49:27.167982  4597 caffe.cpp:501] detection_eval = 0.0403524
-I0511 11:49:27.167986  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167989  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167994  4597 caffe.cpp:501] detection_eval = 6.67944
-I0511 11:49:27.167997  4597 caffe.cpp:501] detection_eval = 11.252
-I0511 11:49:27.168001  4597 caffe.cpp:501] detection_eval = 0.0454081
-I0511 11:49:27.168004  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.168009  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.168012  4597 caffe.cpp:501] detection_eval = 6.68145
-I0511 11:49:27.168015  4597 caffe.cpp:501] detection_eval = 11.3024
-I0511 11:49:27.168020  4597 caffe.cpp:501] detection_eval = 0.0455169
-I0511 11:49:27.168023  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.168027  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.168031  4597 caffe.cpp:501] detection_eval = 6.68347
-I0511 11:49:27.168035  4597 caffe.cpp:501] detection_eval = 11.3569
-I0511 11:49:27.168040  4597 caffe.cpp:501] detection_eval = 0.0395973
-I0511 11:49:27.168042  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168046  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168051  4597 caffe.cpp:501] detection_eval = 6.69153
-I0511 11:49:27.168053  4597 caffe.cpp:501] detection_eval = 11.2944
-I0511 11:49:27.168057  4597 caffe.cpp:501] detection_eval = 0.037244
-I0511 11:49:27.168061  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.168066  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.168069  4597 caffe.cpp:501] detection_eval = 6.69355
-I0511 11:49:27.168072  4597 caffe.cpp:501] detection_eval = 11.3548
-I0511 11:49:27.168076  4597 caffe.cpp:501] detection_eval = 0.0397247
-I0511 11:49:27.168081  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168084  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.168088  4597 caffe.cpp:501] detection_eval = 6.69758
-I0511 11:49:27.168092  4597 caffe.cpp:501] detection_eval = 11.3911
-I0511 11:49:27.168095  4597 caffe.cpp:501] detection_eval = 0.0389596
-I0511 11:49:27.168099  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168102  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.168109  4597 caffe.cpp:501] detection_eval = 6.70161
-I0511 11:49:27.168113  4597 caffe.cpp:501] detection_eval = 11.4173
-I0511 11:49:27.168118  4597 caffe.cpp:501] detection_eval = 0.0396886
-I0511 11:49:27.168121  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168125  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168129  4597 caffe.cpp:501] detection_eval = 6.70968
-I0511 11:49:27.168133  4597 caffe.cpp:501] detection_eval = 11.4012
-I0511 11:49:27.168136  4597 caffe.cpp:501] detection_eval = 0.0414539
-I0511 11:49:27.168140  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168144  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168148  4597 caffe.cpp:501] detection_eval = 6.71371
-I0511 11:49:27.168151  4597 caffe.cpp:501] detection_eval = 11.3931
-I0511 11:49:27.168156  4597 caffe.cpp:501] detection_eval = 0.0399272
-I0511 11:49:27.168159  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168164  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168167  4597 caffe.cpp:501] detection_eval = 6.71573
-I0511 11:49:27.168171  4597 caffe.cpp:501] detection_eval = 11.4173
-I0511 11:49:27.168174  4597 caffe.cpp:501] detection_eval = 0.0440318
-I0511 11:49:27.168179  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.168182  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.168186  4597 caffe.cpp:501] detection_eval = 6.71774
-I0511 11:49:27.168190  4597 caffe.cpp:501] detection_eval = 11.4335
-I0511 11:49:27.168193  4597 caffe.cpp:501] detection_eval = 0.0372345
-I0511 11:49:27.168197  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.168200  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168205  4597 caffe.cpp:501] detection_eval = 6.72782
-I0511 11:49:27.168208  4597 caffe.cpp:501] detection_eval = 11.3468
-I0511 11:49:27.168212  4597 caffe.cpp:501] detection_eval = 0.040946
-I0511 11:49:27.168216  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.168220  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168223  4597 caffe.cpp:501] detection_eval = 6.72782
-I0511 11:49:27.168227  4597 caffe.cpp:501] detection_eval = 11.4194
-I0511 11:49:27.168231  4597 caffe.cpp:501] detection_eval = 0.0395217
-I0511 11:49:27.168234  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168238  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168242  4597 caffe.cpp:501] detection_eval = 6.73185
-I0511 11:49:27.168246  4597 caffe.cpp:501] detection_eval = 11.4859
-I0511 11:49:27.168249  4597 caffe.cpp:501] detection_eval = 0.0395931
-I0511 11:49:27.168253  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.168439  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.168444  4597 caffe.cpp:501] detection_eval = 6.73387
-I0511 11:49:27.168448  4597 caffe.cpp:501] detection_eval = 11.5302
-I0511 11:49:27.168452  4597 caffe.cpp:501] detection_eval = 0.0451198
-I0511 11:49:27.168457  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.168460  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.168464  4597 caffe.cpp:501] detection_eval = 6.73589
-I0511 11:49:27.168467  4597 caffe.cpp:501] detection_eval = 11.5605
-I0511 11:49:27.168471  4597 caffe.cpp:501] detection_eval = 0.0444733
-I0511 11:49:27.168475  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.168479  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.168483  4597 caffe.cpp:501] detection_eval = 6.74395
-I0511 11:49:27.168486  4597 caffe.cpp:501] detection_eval = 11.5625
-I0511 11:49:27.168490  4597 caffe.cpp:501] detection_eval = 0.0427075
-I0511 11:49:27.168494  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168498  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168501  4597 caffe.cpp:501] detection_eval = 6.75202
-I0511 11:49:27.168505  4597 caffe.cpp:501] detection_eval = 11.5625
-I0511 11:49:27.168509  4597 caffe.cpp:501] detection_eval = 0.0470093
-I0511 11:49:27.168514  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168516  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168541  4597 caffe.cpp:501] detection_eval = 6.75403
-I0511 11:49:27.168545  4597 caffe.cpp:501] detection_eval = 11.6089
-I0511 11:49:27.168550  4597 caffe.cpp:501] detection_eval = 0.0426307
-I0511 11:49:27.168553  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168557  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.168561  4597 caffe.cpp:501] detection_eval = 6.75806
-I0511 11:49:27.168565  4597 caffe.cpp:501] detection_eval = 11.5847
-I0511 11:49:27.168570  4597 caffe.cpp:501] detection_eval = 0.0393675
-I0511 11:49:27.168572  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168576  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168581  4597 caffe.cpp:501] detection_eval = 6.76411
-I0511 11:49:27.168584  4597 caffe.cpp:501] detection_eval = 11.5746
-I0511 11:49:27.168588  4597 caffe.cpp:501] detection_eval = 0.0448684
-I0511 11:49:27.168591  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.168596  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.168599  4597 caffe.cpp:501] detection_eval = 6.77016
-I0511 11:49:27.168602  4597 caffe.cpp:501] detection_eval = 11.5403
-I0511 11:49:27.168606  4597 caffe.cpp:501] detection_eval = 0.0388882
-I0511 11:49:27.168611  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168614  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.168617  4597 caffe.cpp:501] detection_eval = 6.77016
-I0511 11:49:27.168622  4597 caffe.cpp:501] detection_eval = 11.625
-I0511 11:49:27.168625  4597 caffe.cpp:501] detection_eval = 0.0390283
-I0511 11:49:27.168629  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168633  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168637  4597 caffe.cpp:501] detection_eval = 6.77218
-I0511 11:49:27.168640  4597 caffe.cpp:501] detection_eval = 11.6431
-I0511 11:49:27.168644  4597 caffe.cpp:501] detection_eval = 0.0379601
-I0511 11:49:27.168648  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.168651  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.168655  4597 caffe.cpp:501] detection_eval = 6.77621
-I0511 11:49:27.168659  4597 caffe.cpp:501] detection_eval = 11.6633
-I0511 11:49:27.168663  4597 caffe.cpp:501] detection_eval = 0.0393689
-I0511 11:49:27.168666  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168670  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168674  4597 caffe.cpp:501] detection_eval = 6.78427
-I0511 11:49:27.168678  4597 caffe.cpp:501] detection_eval = 11.629
-I0511 11:49:27.168682  4597 caffe.cpp:501] detection_eval = 0.0439522
-I0511 11:49:27.168686  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168690  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168694  4597 caffe.cpp:501] detection_eval = 6.78831
-I0511 11:49:27.168697  4597 caffe.cpp:501] detection_eval = 11.6391
-I0511 11:49:27.168701  4597 caffe.cpp:501] detection_eval = 0.0405236
-I0511 11:49:27.168705  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168709  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168712  4597 caffe.cpp:501] detection_eval = 6.78831
-I0511 11:49:27.168716  4597 caffe.cpp:501] detection_eval = 11.6996
-I0511 11:49:27.168720  4597 caffe.cpp:501] detection_eval = 0.0362257
-I0511 11:49:27.168723  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.168727  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168731  4597 caffe.cpp:501] detection_eval = 6.79637
-I0511 11:49:27.168735  4597 caffe.cpp:501] detection_eval = 11.629
-I0511 11:49:27.168740  4597 caffe.cpp:501] detection_eval = 0.0355739
-I0511 11:49:27.168742  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.168746  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.168751  4597 caffe.cpp:501] detection_eval = 6.8004
-I0511 11:49:27.168753  4597 caffe.cpp:501] detection_eval = 11.6452
-I0511 11:49:27.168757  4597 caffe.cpp:501] detection_eval = 0.0378909
-I0511 11:49:27.168761  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.168769  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.168773  4597 caffe.cpp:501] detection_eval = 6.80444
-I0511 11:49:27.168777  4597 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:49:27.168781  4597 caffe.cpp:501] detection_eval = 0.0469753
-I0511 11:49:27.168784  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.168788  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168792  4597 caffe.cpp:501] detection_eval = 6.80847
-I0511 11:49:27.168795  4597 caffe.cpp:501] detection_eval = 11.6875
-I0511 11:49:27.168800  4597 caffe.cpp:501] detection_eval = 0.0398264
-I0511 11:49:27.168804  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.168807  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.168812  4597 caffe.cpp:501] detection_eval = 6.80847
-I0511 11:49:27.168815  4597 caffe.cpp:501] detection_eval = 11.7944
-I0511 11:49:27.168819  4597 caffe.cpp:501] detection_eval = 0.0426049
-I0511 11:49:27.168823  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.168826  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168830  4597 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:49:27.168834  4597 caffe.cpp:501] detection_eval = 11.8226
-I0511 11:49:27.168838  4597 caffe.cpp:501] detection_eval = 0.0409968
-I0511 11:49:27.168841  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168845  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168848  4597 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:49:27.168853  4597 caffe.cpp:501] detection_eval = 11.875
-I0511 11:49:27.168856  4597 caffe.cpp:501] detection_eval = 0.0380478
-I0511 11:49:27.168860  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168864  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168867  4597 caffe.cpp:501] detection_eval = 6.82258
-I0511 11:49:27.168871  4597 caffe.cpp:501] detection_eval = 11.7802
-I0511 11:49:27.168875  4597 caffe.cpp:501] detection_eval = 0.043771
-I0511 11:49:27.168879  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168884  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168886  4597 caffe.cpp:501] detection_eval = 6.82863
-I0511 11:49:27.168890  4597 caffe.cpp:501] detection_eval = 11.7863
-I0511 11:49:27.168895  4597 caffe.cpp:501] detection_eval = 0.0417161
-I0511 11:49:27.168898  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.168901  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.168905  4597 caffe.cpp:501] detection_eval = 6.83266
-I0511 11:49:27.168910  4597 caffe.cpp:501] detection_eval = 11.7802
-I0511 11:49:27.169088  4597 caffe.cpp:501] detection_eval = 0.0366694
-I0511 11:49:27.169095  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169098  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.169101  4597 caffe.cpp:501] detection_eval = 6.83871
-I0511 11:49:27.169106  4597 caffe.cpp:501] detection_eval = 11.8024
-I0511 11:49:27.169109  4597 caffe.cpp:501] detection_eval = 0.0368604
-I0511 11:49:27.169113  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169117  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169121  4597 caffe.cpp:501] detection_eval = 6.84274
-I0511 11:49:27.169124  4597 caffe.cpp:501] detection_eval = 11.8185
-I0511 11:49:27.169128  4597 caffe.cpp:501] detection_eval = 0.037931
-I0511 11:49:27.169132  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169137  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.169139  4597 caffe.cpp:501] detection_eval = 6.84274
-I0511 11:49:27.169143  4597 caffe.cpp:501] detection_eval = 11.8609
-I0511 11:49:27.169147  4597 caffe.cpp:501] detection_eval = 0.0346255
-I0511 11:49:27.169152  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.169155  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.169158  4597 caffe.cpp:501] detection_eval = 6.85081
-I0511 11:49:27.169162  4597 caffe.cpp:501] detection_eval = 11.8065
-I0511 11:49:27.169167  4597 caffe.cpp:501] detection_eval = 0.0420333
-I0511 11:49:27.169174  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.169178  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169183  4597 caffe.cpp:501] detection_eval = 6.85887
-I0511 11:49:27.169185  4597 caffe.cpp:501] detection_eval = 11.7843
-I0511 11:49:27.169189  4597 caffe.cpp:501] detection_eval = 0.0397865
-I0511 11:49:27.169193  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169198  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.169200  4597 caffe.cpp:501] detection_eval = 6.86492
-I0511 11:49:27.169204  4597 caffe.cpp:501] detection_eval = 11.7802
-I0511 11:49:27.169209  4597 caffe.cpp:501] detection_eval = 0.0382312
-I0511 11:49:27.169212  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.169216  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.169219  4597 caffe.cpp:501] detection_eval = 6.87097
-I0511 11:49:27.169224  4597 caffe.cpp:501] detection_eval = 11.7923
-I0511 11:49:27.169227  4597 caffe.cpp:501] detection_eval = 0.0417241
-I0511 11:49:27.169230  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169234  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.169239  4597 caffe.cpp:501] detection_eval = 6.875
-I0511 11:49:27.169242  4597 caffe.cpp:501] detection_eval = 11.8669
-I0511 11:49:27.169245  4597 caffe.cpp:501] detection_eval = 0.0417634
-I0511 11:49:27.169250  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169253  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.169257  4597 caffe.cpp:501] detection_eval = 6.87702
-I0511 11:49:27.169260  4597 caffe.cpp:501] detection_eval = 11.9294
-I0511 11:49:27.169265  4597 caffe.cpp:501] detection_eval = 0.040084
-I0511 11:49:27.169268  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.169272  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169275  4597 caffe.cpp:501] detection_eval = 6.87903
-I0511 11:49:27.169279  4597 caffe.cpp:501] detection_eval = 11.9597
-I0511 11:49:27.169283  4597 caffe.cpp:501] detection_eval = 0.0393739
-I0511 11:49:27.169287  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169291  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169294  4597 caffe.cpp:501] detection_eval = 6.88105
-I0511 11:49:27.169298  4597 caffe.cpp:501] detection_eval = 12.0101
-I0511 11:49:27.169302  4597 caffe.cpp:501] detection_eval = 0.0377377
-I0511 11:49:27.169306  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169309  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.169313  4597 caffe.cpp:501] detection_eval = 6.89113
-I0511 11:49:27.169317  4597 caffe.cpp:501] detection_eval = 11.9657
-I0511 11:49:27.169322  4597 caffe.cpp:501] detection_eval = 0.039285
-I0511 11:49:27.169325  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.169329  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.169332  4597 caffe.cpp:501] detection_eval = 6.89315
-I0511 11:49:27.169337  4597 caffe.cpp:501] detection_eval = 12.0242
-I0511 11:49:27.169340  4597 caffe.cpp:501] detection_eval = 0.0362258
-I0511 11:49:27.169344  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.169348  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169351  4597 caffe.cpp:501] detection_eval = 6.89718
-I0511 11:49:27.169355  4597 caffe.cpp:501] detection_eval = 12.0464
-I0511 11:49:27.169359  4597 caffe.cpp:501] detection_eval = 0.040422
-I0511 11:49:27.169363  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.169366  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169370  4597 caffe.cpp:501] detection_eval = 6.89919
-I0511 11:49:27.169374  4597 caffe.cpp:501] detection_eval = 12.0806
-I0511 11:49:27.169378  4597 caffe.cpp:501] detection_eval = 0.0369308
-I0511 11:49:27.169381  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.169385  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.169389  4597 caffe.cpp:501] detection_eval = 6.90726
-I0511 11:49:27.169392  4597 caffe.cpp:501] detection_eval = 12.0121
-I0511 11:49:27.169396  4597 caffe.cpp:501] detection_eval = 0.0395874
-I0511 11:49:27.169404  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.169407  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169411  4597 caffe.cpp:501] detection_eval = 6.91129
-I0511 11:49:27.169415  4597 caffe.cpp:501] detection_eval = 12.0121
-I0511 11:49:27.169420  4597 caffe.cpp:501] detection_eval = 0.041466
-I0511 11:49:27.169422  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169426  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169430  4597 caffe.cpp:501] detection_eval = 6.91734
-I0511 11:49:27.169435  4597 caffe.cpp:501] detection_eval = 11.9778
-I0511 11:49:27.169438  4597 caffe.cpp:501] detection_eval = 0.0398929
-I0511 11:49:27.169441  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169445  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169450  4597 caffe.cpp:501] detection_eval = 6.91935
-I0511 11:49:27.169453  4597 caffe.cpp:501] detection_eval = 12.002
-I0511 11:49:27.169457  4597 caffe.cpp:501] detection_eval = 0.0376612
-I0511 11:49:27.169461  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169464  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.169468  4597 caffe.cpp:501] detection_eval = 6.92944
-I0511 11:49:27.169472  4597 caffe.cpp:501] detection_eval = 11.9456
-I0511 11:49:27.169476  4597 caffe.cpp:501] detection_eval = 0.0462506
-I0511 11:49:27.169479  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.169483  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.169487  4597 caffe.cpp:501] detection_eval = 6.93548
-I0511 11:49:27.169492  4597 caffe.cpp:501] detection_eval = 11.9738
-I0511 11:49:27.169495  4597 caffe.cpp:501] detection_eval = 0.0432693
-I0511 11:49:27.169498  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169502  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.169507  4597 caffe.cpp:501] detection_eval = 6.9375
-I0511 11:49:27.169509  4597 caffe.cpp:501] detection_eval = 12.0141
-I0511 11:49:27.169513  4597 caffe.cpp:501] detection_eval = 0.0364303
-I0511 11:49:27.169517  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.169522  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.169525  4597 caffe.cpp:501] detection_eval = 6.94355
-I0511 11:49:27.169528  4597 caffe.cpp:501] detection_eval = 12.0141
-I0511 11:49:27.169533  4597 caffe.cpp:501] detection_eval = 0.0472611
-I0511 11:49:27.169536  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.169540  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.172562  4597 caffe.cpp:501] detection_eval = 6.94355
-I0511 11:49:27.172579  4597 caffe.cpp:501] detection_eval = 12.0625
-I0511 11:49:27.172582  4597 caffe.cpp:501] detection_eval = 0.0390168
-I0511 11:49:27.172585  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172587  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.172590  4597 caffe.cpp:501] detection_eval = 6.94556
-I0511 11:49:27.172591  4597 caffe.cpp:501] detection_eval = 12.1149
-I0511 11:49:27.172595  4597 caffe.cpp:501] detection_eval = 0.0399723
-I0511 11:49:27.172596  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172598  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.172600  4597 caffe.cpp:501] detection_eval = 6.94758
-I0511 11:49:27.172602  4597 caffe.cpp:501] detection_eval = 12.1532
-I0511 11:49:27.172605  4597 caffe.cpp:501] detection_eval = 0.045016
-I0511 11:49:27.172607  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.172610  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.172611  4597 caffe.cpp:501] detection_eval = 6.95161
-I0511 11:49:27.172613  4597 caffe.cpp:501] detection_eval = 12.1573
-I0511 11:49:27.172616  4597 caffe.cpp:501] detection_eval = 0.0391619
-I0511 11:49:27.172621  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172623  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.172627  4597 caffe.cpp:501] detection_eval = 6.95363
-I0511 11:49:27.172631  4597 caffe.cpp:501] detection_eval = 12.2238
-I0511 11:49:27.172644  4597 caffe.cpp:501] detection_eval = 0.0420103
-I0511 11:49:27.172649  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.172652  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.172654  4597 caffe.cpp:501] detection_eval = 6.96169
-I0511 11:49:27.172657  4597 caffe.cpp:501] detection_eval = 12.2097
-I0511 11:49:27.172659  4597 caffe.cpp:501] detection_eval = 0.0436526
-I0511 11:49:27.172662  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172663  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.172665  4597 caffe.cpp:501] detection_eval = 6.96573
-I0511 11:49:27.172667  4597 caffe.cpp:501] detection_eval = 12.256
-I0511 11:49:27.172670  4597 caffe.cpp:501] detection_eval = 0.0421588
-I0511 11:49:27.172672  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172674  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.172677  4597 caffe.cpp:501] detection_eval = 6.95363
-I0511 11:49:27.172678  4597 caffe.cpp:501] detection_eval = 12.254
-I0511 11:49:27.172682  4597 caffe.cpp:501] detection_eval = 0.0394665
-I0511 11:49:27.172683  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172685  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.172688  4597 caffe.cpp:501] detection_eval = 6.93548
-I0511 11:49:27.172689  4597 caffe.cpp:501] detection_eval = 12.3609
-I0511 11:49:27.172691  4597 caffe.cpp:501] detection_eval = 0.0459468
-I0511 11:49:27.172693  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.172695  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.172698  4597 caffe.cpp:501] detection_eval = 6.94355
-I0511 11:49:27.172700  4597 caffe.cpp:501] detection_eval = 12.3407
-I0511 11:49:27.172703  4597 caffe.cpp:501] detection_eval = 0.0409542
-I0511 11:49:27.172704  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172706  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.172708  4597 caffe.cpp:501] detection_eval = 6.94758
-I0511 11:49:27.172710  4597 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:49:27.172713  4597 caffe.cpp:501] detection_eval = 0.0426733
-I0511 11:49:27.172715  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172718  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.172719  4597 caffe.cpp:501] detection_eval = 6.95565
-I0511 11:49:27.172722  4597 caffe.cpp:501] detection_eval = 12.4012
-I0511 11:49:27.172726  4597 caffe.cpp:501] detection_eval = 0.0403951
-I0511 11:49:27.172730  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172742  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.172747  4597 caffe.cpp:501] detection_eval = 7.23185
-I0511 11:49:27.172751  4597 caffe.cpp:501] detection_eval = 8.34879
-I0511 11:49:27.172755  4597 caffe.cpp:501] detection_eval = 0.0834918
-I0511 11:49:27.172758  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.172762  4597 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:49:27.172765  4597 caffe.cpp:501] detection_eval = 7.23589
-I0511 11:49:27.172770  4597 caffe.cpp:501] detection_eval = 8.40323
-I0511 11:49:27.172772  4597 caffe.cpp:501] detection_eval = 0.0517371
-I0511 11:49:27.172777  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.172781  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.172785  4597 caffe.cpp:501] detection_eval = 7.2379
-I0511 11:49:27.172788  4597 caffe.cpp:501] detection_eval = 8.53024
-I0511 11:49:27.172791  4597 caffe.cpp:501] detection_eval = 0.0466181
-I0511 11:49:27.172796  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.172798  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.172801  4597 caffe.cpp:501] detection_eval = 7.24194
-I0511 11:49:27.172806  4597 caffe.cpp:501] detection_eval = 8.5625
-I0511 11:49:27.172809  4597 caffe.cpp:501] detection_eval = 0.043981
-I0511 11:49:27.172812  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.172816  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.172821  4597 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:49:27.172823  4597 caffe.cpp:501] detection_eval = 8.57661
-I0511 11:49:27.172832  4597 caffe.cpp:501] detection_eval = 0.0444849
-I0511 11:49:27.172837  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172847  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.172850  4597 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:49:27.172853  4597 caffe.cpp:501] detection_eval = 8.65121
-I0511 11:49:27.172857  4597 caffe.cpp:501] detection_eval = 0.0417519
-I0511 11:49:27.172861  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172864  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.172868  4597 caffe.cpp:501] detection_eval = 7.24798
-I0511 11:49:27.172873  4597 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:49:27.172875  4597 caffe.cpp:501] detection_eval = 0.042867
-I0511 11:49:27.172879  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172883  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.172885  4597 caffe.cpp:501] detection_eval = 7.25806
-I0511 11:49:27.172889  4597 caffe.cpp:501] detection_eval = 8.60282
-I0511 11:49:27.172893  4597 caffe.cpp:501] detection_eval = 0.0427657
-I0511 11:49:27.172896  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.172900  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.172904  4597 caffe.cpp:501] detection_eval = 7.26815
-I0511 11:49:27.172907  4597 caffe.cpp:501] detection_eval = 8.55847
-I0511 11:49:27.172911  4597 caffe.cpp:501] detection_eval = 0.0481058
-I0511 11:49:27.172914  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.172919  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.172922  4597 caffe.cpp:501] detection_eval = 7.27419
-I0511 11:49:27.172925  4597 caffe.cpp:501] detection_eval = 8.53024
-I0511 11:49:27.172930  4597 caffe.cpp:501] detection_eval = 0.0418924
-I0511 11:49:27.172933  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.172936  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.172940  4597 caffe.cpp:501] detection_eval = 7.27419
-I0511 11:49:27.172945  4597 caffe.cpp:501] detection_eval = 8.63306
-I0511 11:49:27.172947  4597 caffe.cpp:501] detection_eval = 0.0396848
-I0511 11:49:27.172951  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172955  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.172958  4597 caffe.cpp:501] detection_eval = 7.27621
-I0511 11:49:27.172962  4597 caffe.cpp:501] detection_eval = 8.69758
-I0511 11:49:27.172966  4597 caffe.cpp:501] detection_eval = 0.0444746
-I0511 11:49:27.172969  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.172972  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.172976  4597 caffe.cpp:501] detection_eval = 7.27823
-I0511 11:49:27.172979  4597 caffe.cpp:501] detection_eval = 8.75
-I0511 11:49:27.172983  4597 caffe.cpp:501] detection_eval = 0.0412421
-I0511 11:49:27.172986  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172991  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.172994  4597 caffe.cpp:501] detection_eval = 7.28226
-I0511 11:49:27.172997  4597 caffe.cpp:501] detection_eval = 8.79234
-I0511 11:49:27.173002  4597 caffe.cpp:501] detection_eval = 0.0431306
-I0511 11:49:27.173005  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173009  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173012  4597 caffe.cpp:501] detection_eval = 7.28427
-I0511 11:49:27.173017  4597 caffe.cpp:501] detection_eval = 8.84677
-I0511 11:49:27.173019  4597 caffe.cpp:501] detection_eval = 0.0469652
-I0511 11:49:27.173023  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173027  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173030  4597 caffe.cpp:501] detection_eval = 7.28629
-I0511 11:49:27.173034  4597 caffe.cpp:501] detection_eval = 8.85685
-I0511 11:49:27.173038  4597 caffe.cpp:501] detection_eval = 0.0385625
-I0511 11:49:27.173041  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173045  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.173048  4597 caffe.cpp:501] detection_eval = 7.28831
-I0511 11:49:27.173056  4597 caffe.cpp:501] detection_eval = 8.90121
-I0511 11:49:27.173060  4597 caffe.cpp:501] detection_eval = 0.0392946
-I0511 11:49:27.173063  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173068  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173071  4597 caffe.cpp:501] detection_eval = 7.28831
-I0511 11:49:27.173075  4597 caffe.cpp:501] detection_eval = 8.97782
-I0511 11:49:27.173079  4597 caffe.cpp:501] detection_eval = 0.0418654
-I0511 11:49:27.173082  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173086  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.173089  4597 caffe.cpp:501] detection_eval = 7.29234
-I0511 11:49:27.173094  4597 caffe.cpp:501] detection_eval = 8.95565
-I0511 11:49:27.173097  4597 caffe.cpp:501] detection_eval = 0.0354717
-I0511 11:49:27.173100  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173105  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.173108  4597 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:49:27.173111  4597 caffe.cpp:501] detection_eval = 8.99395
-I0511 11:49:27.173115  4597 caffe.cpp:501] detection_eval = 0.0422992
-I0511 11:49:27.173120  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173122  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173126  4597 caffe.cpp:501] detection_eval = 7.29839
-I0511 11:49:27.173130  4597 caffe.cpp:501] detection_eval = 9
-I0511 11:49:27.173133  4597 caffe.cpp:501] detection_eval = 0.0390463
-I0511 11:49:27.173137  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.173141  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.173144  4597 caffe.cpp:501] detection_eval = 7.29839
-I0511 11:49:27.173147  4597 caffe.cpp:501] detection_eval = 9.08871
-I0511 11:49:27.173151  4597 caffe.cpp:501] detection_eval = 0.0395434
-I0511 11:49:27.173154  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173158  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.173162  4597 caffe.cpp:501] detection_eval = 7.30444
-I0511 11:49:27.173166  4597 caffe.cpp:501] detection_eval = 9.0746
-I0511 11:49:27.173169  4597 caffe.cpp:501] detection_eval = 0.0334855
-I0511 11:49:27.173173  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.173177  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.173180  4597 caffe.cpp:501] detection_eval = 7.31653
-I0511 11:49:27.173184  4597 caffe.cpp:501] detection_eval = 9.0121
-I0511 11:49:27.173188  4597 caffe.cpp:501] detection_eval = 0.0417966
-I0511 11:49:27.173192  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173195  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173199  4597 caffe.cpp:501] detection_eval = 7.31855
-I0511 11:49:27.173203  4597 caffe.cpp:501] detection_eval = 9.1129
-I0511 11:49:27.173207  4597 caffe.cpp:501] detection_eval = 0.0484479
-I0511 11:49:27.173210  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.173214  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173218  4597 caffe.cpp:501] detection_eval = 7.32056
-I0511 11:49:27.173221  4597 caffe.cpp:501] detection_eval = 9.18548
-I0511 11:49:27.173225  4597 caffe.cpp:501] detection_eval = 0.0456804
-I0511 11:49:27.173228  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173231  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173235  4597 caffe.cpp:501] detection_eval = 7.30847
-I0511 11:49:27.173238  4597 caffe.cpp:501] detection_eval = 9.11492
-I0511 11:49:27.173243  4597 caffe.cpp:501] detection_eval = 0.0449065
-I0511 11:49:27.173245  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173249  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173254  4597 caffe.cpp:501] detection_eval = 7.31048
-I0511 11:49:27.173256  4597 caffe.cpp:501] detection_eval = 9.19758
-I0511 11:49:27.173260  4597 caffe.cpp:501] detection_eval = 0.047664
-I0511 11:49:27.173264  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173267  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173276  4597 caffe.cpp:501] detection_eval = 7.31452
-I0511 11:49:27.173280  4597 caffe.cpp:501] detection_eval = 9.19153
-I0511 11:49:27.173283  4597 caffe.cpp:501] detection_eval = 0.0467778
-I0511 11:49:27.173287  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173291  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173295  4597 caffe.cpp:501] detection_eval = 7.31452
-I0511 11:49:27.173298  4597 caffe.cpp:501] detection_eval = 9.26613
-I0511 11:49:27.173302  4597 caffe.cpp:501] detection_eval = 0.0438267
-I0511 11:49:27.173305  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.173310  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173313  4597 caffe.cpp:501] detection_eval = 7.31653
-I0511 11:49:27.173316  4597 caffe.cpp:501] detection_eval = 9.31653
-I0511 11:49:27.173319  4597 caffe.cpp:501] detection_eval = 0.0454528
-I0511 11:49:27.173323  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173326  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173331  4597 caffe.cpp:501] detection_eval = 7.30242
-I0511 11:49:27.173334  4597 caffe.cpp:501] detection_eval = 9.25202
-I0511 11:49:27.173337  4597 caffe.cpp:501] detection_eval = 0.0390277
-I0511 11:49:27.173341  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173346  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173349  4597 caffe.cpp:501] detection_eval = 7.30645
-I0511 11:49:27.173352  4597 caffe.cpp:501] detection_eval = 9.24395
-I0511 11:49:27.173357  4597 caffe.cpp:501] detection_eval = 0.0396357
-I0511 11:49:27.173359  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173363  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173367  4597 caffe.cpp:501] detection_eval = 7.30847
-I0511 11:49:27.173372  4597 caffe.cpp:501] detection_eval = 9.30645
-I0511 11:49:27.173374  4597 caffe.cpp:501] detection_eval = 0.0380932
-I0511 11:49:27.173378  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173382  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173385  4597 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:49:27.173389  4597 caffe.cpp:501] detection_eval = 9.37298
-I0511 11:49:27.173393  4597 caffe.cpp:501] detection_eval = 0.0451464
-I0511 11:49:27.173396  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.173400  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.173403  4597 caffe.cpp:501] detection_eval = 7.31653
-I0511 11:49:27.173406  4597 caffe.cpp:501] detection_eval = 9.39718
-I0511 11:49:27.173410  4597 caffe.cpp:501] detection_eval = 0.0388492
-I0511 11:49:27.173413  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173416  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173419  4597 caffe.cpp:501] detection_eval = 7.32056
-I0511 11:49:27.173422  4597 caffe.cpp:501] detection_eval = 9.35887
-I0511 11:49:27.173425  4597 caffe.cpp:501] detection_eval = 0.0406518
-I0511 11:49:27.173429  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173431  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.173435  4597 caffe.cpp:501] detection_eval = 7.32056
-I0511 11:49:27.173439  4597 caffe.cpp:501] detection_eval = 9.43548
-I0511 11:49:27.173441  4597 caffe.cpp:501] detection_eval = 0.0383426
-I0511 11:49:27.173444  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.173447  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173451  4597 caffe.cpp:501] detection_eval = 7.3246
-I0511 11:49:27.173454  4597 caffe.cpp:501] detection_eval = 9.44355
-I0511 11:49:27.173457  4597 caffe.cpp:501] detection_eval = 0.0367932
-I0511 11:49:27.173460  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.173463  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173466  4597 caffe.cpp:501] detection_eval = 7.33266
-I0511 11:49:27.173470  4597 caffe.cpp:501] detection_eval = 9.38105
-I0511 11:49:27.173475  4597 caffe.cpp:501] detection_eval = 0.0361728
-I0511 11:49:27.173480  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.173485  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173493  4597 caffe.cpp:501] detection_eval = 7.33266
-I0511 11:49:27.173496  4597 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:49:27.173499  4597 caffe.cpp:501] detection_eval = 0.0407517
-I0511 11:49:27.173503  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173506  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173511  4597 caffe.cpp:501] detection_eval = 7.34073
-I0511 11:49:27.173513  4597 caffe.cpp:501] detection_eval = 9.43548
-I0511 11:49:27.173517  4597 caffe.cpp:501] detection_eval = 0.0421996
-I0511 11:49:27.173521  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.173524  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.173527  4597 caffe.cpp:501] detection_eval = 7.34274
-I0511 11:49:27.173532  4597 caffe.cpp:501] detection_eval = 9.50403
-I0511 11:49:27.173534  4597 caffe.cpp:501] detection_eval = 0.0435659
-I0511 11:49:27.173538  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173542  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173545  4597 caffe.cpp:501] detection_eval = 7.34677
-I0511 11:49:27.173548  4597 caffe.cpp:501] detection_eval = 9.53831
-I0511 11:49:27.173552  4597 caffe.cpp:501] detection_eval = 0.0458897
-I0511 11:49:27.173555  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173559  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173563  4597 caffe.cpp:501] detection_eval = 7.35282
-I0511 11:49:27.173565  4597 caffe.cpp:501] detection_eval = 9.53226
-I0511 11:49:27.173569  4597 caffe.cpp:501] detection_eval = 0.0465716
-I0511 11:49:27.173573  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.173576  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.173580  4597 caffe.cpp:501] detection_eval = 7.35282
-I0511 11:49:27.173583  4597 caffe.cpp:501] detection_eval = 9.64315
-I0511 11:49:27.173588  4597 caffe.cpp:501] detection_eval = 0.0427801
-I0511 11:49:27.173591  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173594  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173599  4597 caffe.cpp:501] detection_eval = 7.36089
-I0511 11:49:27.173602  4597 caffe.cpp:501] detection_eval = 9.59274
-I0511 11:49:27.173605  4597 caffe.cpp:501] detection_eval = 0.0423031
-I0511 11:49:27.173609  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173614  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173617  4597 caffe.cpp:501] detection_eval = 7.36089
-I0511 11:49:27.173621  4597 caffe.cpp:501] detection_eval = 9.65121
-I0511 11:49:27.173625  4597 caffe.cpp:501] detection_eval = 0.0383204
-I0511 11:49:27.173629  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173632  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173636  4597 caffe.cpp:501] detection_eval = 7.36694
-I0511 11:49:27.173640  4597 caffe.cpp:501] detection_eval = 9.62097
-I0511 11:49:27.173643  4597 caffe.cpp:501] detection_eval = 0.0369999
-I0511 11:49:27.173647  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173651  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173655  4597 caffe.cpp:501] detection_eval = 7.36895
-I0511 11:49:27.173658  4597 caffe.cpp:501] detection_eval = 9.67137
-I0511 11:49:27.173662  4597 caffe.cpp:501] detection_eval = 0.0430567
-I0511 11:49:27.173666  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173671  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173673  4597 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:49:27.173677  4597 caffe.cpp:501] detection_eval = 9.64113
-I0511 11:49:27.173681  4597 caffe.cpp:501] detection_eval = 0.0372989
-I0511 11:49:27.173684  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.173688  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.173692  4597 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:49:27.173696  4597 caffe.cpp:501] detection_eval = 9.69355
-I0511 11:49:27.173699  4597 caffe.cpp:501] detection_eval = 0.0357105
-I0511 11:49:27.173703  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173712  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173715  4597 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:49:27.173719  4597 caffe.cpp:501] detection_eval = 9.67944
-I0511 11:49:27.173723  4597 caffe.cpp:501] detection_eval = 0.0399388
-I0511 11:49:27.173727  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173732  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173734  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.173738  4597 caffe.cpp:501] detection_eval = 9.70363
-I0511 11:49:27.173743  4597 caffe.cpp:501] detection_eval = 0.0429139
-I0511 11:49:27.173746  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173749  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173753  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.173758  4597 caffe.cpp:501] detection_eval = 9.78226
-I0511 11:49:27.173760  4597 caffe.cpp:501] detection_eval = 0.0461725
-I0511 11:49:27.173764  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.173768  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173771  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.173774  4597 caffe.cpp:501] detection_eval = 9.86694
-I0511 11:49:27.173779  4597 caffe.cpp:501] detection_eval = 0.0451524
-I0511 11:49:27.173781  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173784  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173787  4597 caffe.cpp:501] detection_eval = 7.36694
-I0511 11:49:27.173791  4597 caffe.cpp:501] detection_eval = 9.90323
-I0511 11:49:27.173794  4597 caffe.cpp:501] detection_eval = 0.0449568
-I0511 11:49:27.173797  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173801  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173804  4597 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:49:27.173807  4597 caffe.cpp:501] detection_eval = 9.92137
-I0511 11:49:27.173811  4597 caffe.cpp:501] detection_eval = 0.0478809
-I0511 11:49:27.173815  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173818  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.173822  4597 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:49:27.173826  4597 caffe.cpp:501] detection_eval = 9.86694
-I0511 11:49:27.173830  4597 caffe.cpp:501] detection_eval = 0.0393446
-I0511 11:49:27.173833  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173838  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173842  4597 caffe.cpp:501] detection_eval = 7.38306
-I0511 11:49:27.173846  4597 caffe.cpp:501] detection_eval = 9.94153
-I0511 11:49:27.173849  4597 caffe.cpp:501] detection_eval = 0.0461554
-I0511 11:49:27.173853  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173856  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173861  4597 caffe.cpp:501] detection_eval = 7.36492
-I0511 11:49:27.173864  4597 caffe.cpp:501] detection_eval = 10.0141
-I0511 11:49:27.173868  4597 caffe.cpp:501] detection_eval = 0.0447228
-I0511 11:49:27.173871  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173876  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173879  4597 caffe.cpp:501] detection_eval = 7.36895
-I0511 11:49:27.173882  4597 caffe.cpp:501] detection_eval = 10.0665
-I0511 11:49:27.173887  4597 caffe.cpp:501] detection_eval = 0.0444906
-I0511 11:49:27.173889  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173892  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.173897  4597 caffe.cpp:501] detection_eval = 7.375
-I0511 11:49:27.173900  4597 caffe.cpp:501] detection_eval = 10.0706
-I0511 11:49:27.173904  4597 caffe.cpp:501] detection_eval = 0.0490498
-I0511 11:49:27.173908  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.173912  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.173915  4597 caffe.cpp:501] detection_eval = 7.37702
-I0511 11:49:27.173919  4597 caffe.cpp:501] detection_eval = 10.1694
-I0511 11:49:27.173923  4597 caffe.cpp:501] detection_eval = 0.0458965
-I0511 11:49:27.173926  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173934  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173938  4597 caffe.cpp:501] detection_eval = 7.3629
-I0511 11:49:27.173943  4597 caffe.cpp:501] detection_eval = 10.1371
-I0511 11:49:27.173946  4597 caffe.cpp:501] detection_eval = 0.0475492
-I0511 11:49:27.173950  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173954  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.173957  4597 caffe.cpp:501] detection_eval = 7.37097
-I0511 11:49:27.173961  4597 caffe.cpp:501] detection_eval = 10.1089
-I0511 11:49:27.173965  4597 caffe.cpp:501] detection_eval = 0.0499534
-I0511 11:49:27.173969  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173972  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173975  4597 caffe.cpp:501] detection_eval = 7.35685
-I0511 11:49:27.173979  4597 caffe.cpp:501] detection_eval = 10.1008
-I0511 11:49:27.173982  4597 caffe.cpp:501] detection_eval = 0.0470224
-I0511 11:49:27.173985  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173990  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173993  4597 caffe.cpp:501] detection_eval = 7.35887
-I0511 11:49:27.173996  4597 caffe.cpp:501] detection_eval = 10.1391
-I0511 11:49:27.174000  4597 caffe.cpp:501] detection_eval = 0.0408047
-I0511 11:49:27.174005  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174008  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174012  4597 caffe.cpp:501] detection_eval = 7.36089
-I0511 11:49:27.174015  4597 caffe.cpp:501] detection_eval = 10.2339
-I0511 11:49:27.174019  4597 caffe.cpp:501] detection_eval = 0.0501116
-I0511 11:49:27.174023  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.174026  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174031  4597 caffe.cpp:501] detection_eval = 7.34476
-I0511 11:49:27.174034  4597 caffe.cpp:501] detection_eval = 10.2238
-I0511 11:49:27.174038  4597 caffe.cpp:501] detection_eval = 0.0431928
-I0511 11:49:27.174041  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174046  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174049  4597 caffe.cpp:501] detection_eval = 7.34677
-I0511 11:49:27.174052  4597 caffe.cpp:501] detection_eval = 10.3065
-I0511 11:49:27.174057  4597 caffe.cpp:501] detection_eval = 0.0532231
-I0511 11:49:27.174060  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.174063  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.174067  4597 caffe.cpp:501] detection_eval = 7.35081
-I0511 11:49:27.174070  4597 caffe.cpp:501] detection_eval = 10.2903
-I0511 11:49:27.174074  4597 caffe.cpp:501] detection_eval = 0.0425843
-I0511 11:49:27.174077  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174082  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174085  4597 caffe.cpp:501] detection_eval = 7.33669
-I0511 11:49:27.174088  4597 caffe.cpp:501] detection_eval = 10.2621
-I0511 11:49:27.174093  4597 caffe.cpp:501] detection_eval = 0.0404038
-I0511 11:49:27.174096  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174100  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174103  4597 caffe.cpp:501] detection_eval = 7.34476
-I0511 11:49:27.174108  4597 caffe.cpp:501] detection_eval = 10.2137
-I0511 11:49:27.174111  4597 caffe.cpp:501] detection_eval = 0.0397234
-I0511 11:49:27.174115  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174118  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174123  4597 caffe.cpp:501] detection_eval = 7.35081
-I0511 11:49:27.174125  4597 caffe.cpp:501] detection_eval = 10.2077
-I0511 11:49:27.174129  4597 caffe.cpp:501] detection_eval = 0.0453921
-I0511 11:49:27.174134  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174136  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174140  4597 caffe.cpp:501] detection_eval = 7.35081
-I0511 11:49:27.174144  4597 caffe.cpp:501] detection_eval = 10.252
-I0511 11:49:27.174147  4597 caffe.cpp:501] detection_eval = 0.0410711
-I0511 11:49:27.174154  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174159  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174162  4597 caffe.cpp:501] detection_eval = 7.35685
-I0511 11:49:27.174166  4597 caffe.cpp:501] detection_eval = 10.2036
-I0511 11:49:27.174170  4597 caffe.cpp:501] detection_eval = 0.0424807
-I0511 11:49:27.174173  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174177  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174181  4597 caffe.cpp:501] detection_eval = 7.36694
-I0511 11:49:27.174185  4597 caffe.cpp:501] detection_eval = 10.1593
-I0511 11:49:27.174188  4597 caffe.cpp:501] detection_eval = 0.0441527
-I0511 11:49:27.174192  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174196  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174199  4597 caffe.cpp:501] detection_eval = 7.36895
-I0511 11:49:27.174203  4597 caffe.cpp:501] detection_eval = 10.2419
-I0511 11:49:27.174207  4597 caffe.cpp:501] detection_eval = 0.043085
-I0511 11:49:27.174211  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174214  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174217  4597 caffe.cpp:501] detection_eval = 7.37702
-I0511 11:49:27.174221  4597 caffe.cpp:501] detection_eval = 10.2177
-I0511 11:49:27.174226  4597 caffe.cpp:501] detection_eval = 0.0489284
-I0511 11:49:27.174229  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.174232  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.174237  4597 caffe.cpp:501] detection_eval = 7.37702
-I0511 11:49:27.174239  4597 caffe.cpp:501] detection_eval = 10.2843
-I0511 11:49:27.174242  4597 caffe.cpp:501] detection_eval = 0.0482222
-I0511 11:49:27.174247  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.174249  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.174253  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.174257  4597 caffe.cpp:501] detection_eval = 10.2722
-I0511 11:49:27.174260  4597 caffe.cpp:501] detection_eval = 0.0402078
-I0511 11:49:27.174264  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174268  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174271  4597 caffe.cpp:501] detection_eval = 7.38306
-I0511 11:49:27.174275  4597 caffe.cpp:501] detection_eval = 10.3024
-I0511 11:49:27.174279  4597 caffe.cpp:501] detection_eval = 0.0363361
-I0511 11:49:27.174283  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174286  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174290  4597 caffe.cpp:501] detection_eval = 7.3871
-I0511 11:49:27.174294  4597 caffe.cpp:501] detection_eval = 10.2944
-I0511 11:49:27.174298  4597 caffe.cpp:501] detection_eval = 0.0363834
-I0511 11:49:27.174301  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.174305  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.174309  4597 caffe.cpp:501] detection_eval = 7.38911
-I0511 11:49:27.174312  4597 caffe.cpp:501] detection_eval = 10.3246
-I0511 11:49:27.174316  4597 caffe.cpp:501] detection_eval = 0.0420944
-I0511 11:49:27.174320  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174324  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174326  4597 caffe.cpp:501] detection_eval = 7.39113
-I0511 11:49:27.174330  4597 caffe.cpp:501] detection_eval = 10.3972
-I0511 11:49:27.174334  4597 caffe.cpp:501] detection_eval = 0.0490882
-I0511 11:49:27.174337  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.174340  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.174345  4597 caffe.cpp:501] detection_eval = 7.39516
-I0511 11:49:27.174348  4597 caffe.cpp:501] detection_eval = 10.4435
-I0511 11:49:27.174352  4597 caffe.cpp:501] detection_eval = 0.0413695
-I0511 11:49:27.174355  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174360  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174362  4597 caffe.cpp:501] detection_eval = 7.40524
-I0511 11:49:27.174366  4597 caffe.cpp:501] detection_eval = 10.3427
-I0511 11:49:27.174374  4597 caffe.cpp:501] detection_eval = 0.0429845
-I0511 11:49:27.174377  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174381  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174386  4597 caffe.cpp:501] detection_eval = 7.41129
-I0511 11:49:27.174388  4597 caffe.cpp:501] detection_eval = 10.3286
-I0511 11:49:27.174392  4597 caffe.cpp:501] detection_eval = 0.0392333
-I0511 11:49:27.174396  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174401  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174403  4597 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:49:27.174407  4597 caffe.cpp:501] detection_eval = 10.3649
-I0511 11:49:27.174410  4597 caffe.cpp:501] detection_eval = 0.0483903
-I0511 11:49:27.174414  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.174417  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174420  4597 caffe.cpp:501] detection_eval = 7.42339
-I0511 11:49:27.174424  4597 caffe.cpp:501] detection_eval = 10.3548
-I0511 11:49:27.174428  4597 caffe.cpp:501] detection_eval = 0.0470593
-I0511 11:49:27.174432  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.174435  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174439  4597 caffe.cpp:501] detection_eval = 7.43347
-I0511 11:49:27.174443  4597 caffe.cpp:501] detection_eval = 10.254
-I0511 11:49:27.174446  4597 caffe.cpp:501] detection_eval = 0.0456793
-I0511 11:49:27.174450  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174454  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174458  4597 caffe.cpp:501] detection_eval = 7.43548
-I0511 11:49:27.174461  4597 caffe.cpp:501] detection_eval = 10.2823
-I0511 11:49:27.174465  4597 caffe.cpp:501] detection_eval = 0.0433553
-I0511 11:49:27.174468  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174473  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174475  4597 caffe.cpp:501] detection_eval = 7.43952
-I0511 11:49:27.174479  4597 caffe.cpp:501] detection_eval = 10.2883
-I0511 11:49:27.174484  4597 caffe.cpp:501] detection_eval = 0.0454525
-I0511 11:49:27.174487  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174490  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174494  4597 caffe.cpp:501] detection_eval = 7.43952
-I0511 11:49:27.174497  4597 caffe.cpp:501] detection_eval = 10.3488
-I0511 11:49:27.174501  4597 caffe.cpp:501] detection_eval = 0.0430456
-I0511 11:49:27.174504  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174507  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174511  4597 caffe.cpp:501] detection_eval = 7.44355
-I0511 11:49:27.174515  4597 caffe.cpp:501] detection_eval = 10.3649
-I0511 11:49:27.174518  4597 caffe.cpp:501] detection_eval = 0.040618
-I0511 11:49:27.174522  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174526  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174530  4597 caffe.cpp:501] detection_eval = 7.4496
-I0511 11:49:27.174533  4597 caffe.cpp:501] detection_eval = 10.3609
-I0511 11:49:27.174537  4597 caffe.cpp:501] detection_eval = 0.0411297
-I0511 11:49:27.174540  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174545  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174548  4597 caffe.cpp:501] detection_eval = 7.45161
-I0511 11:49:27.174551  4597 caffe.cpp:501] detection_eval = 10.4093
-I0511 11:49:27.174556  4597 caffe.cpp:501] detection_eval = 0.0402608
-I0511 11:49:27.174559  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174562  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174566  4597 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:49:27.174571  4597 caffe.cpp:501] detection_eval = 10.496
-I0511 11:49:27.174573  4597 caffe.cpp:501] detection_eval = 0.0405892
-I0511 11:49:27.174577  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174582  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174584  4597 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:49:27.174587  4597 caffe.cpp:501] detection_eval = 10.4415
-I0511 11:49:27.174595  4597 caffe.cpp:501] detection_eval = 0.0413932
-I0511 11:49:27.174599  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174603  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174607  4597 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:49:27.174610  4597 caffe.cpp:501] detection_eval = 10.5181
-I0511 11:49:27.174614  4597 caffe.cpp:501] detection_eval = 0.0432672
-I0511 11:49:27.174618  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174621  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174625  4597 caffe.cpp:501] detection_eval = 7.44355
-I0511 11:49:27.174629  4597 caffe.cpp:501] detection_eval = 10.5766
-I0511 11:49:27.174633  4597 caffe.cpp:501] detection_eval = 0.0451075
-I0511 11:49:27.174636  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.174640  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.174643  4597 caffe.cpp:501] detection_eval = 7.44556
-I0511 11:49:27.174648  4597 caffe.cpp:501] detection_eval = 10.6149
-I0511 11:49:27.174651  4597 caffe.cpp:501] detection_eval = 0.0448866
-I0511 11:49:27.174654  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174659  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174661  4597 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:49:27.174665  4597 caffe.cpp:501] detection_eval = 10.5645
-I0511 11:49:27.174669  4597 caffe.cpp:501] detection_eval = 0.0463545
-I0511 11:49:27.174672  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174675  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.174679  4597 caffe.cpp:501] detection_eval = 7.45565
-I0511 11:49:27.174682  4597 caffe.cpp:501] detection_eval = 10.5887
-I0511 11:49:27.174686  4597 caffe.cpp:501] detection_eval = 0.0414429
-I0511 11:49:27.174690  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174695  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174697  4597 caffe.cpp:501] detection_eval = 7.45565
-I0511 11:49:27.174701  4597 caffe.cpp:501] detection_eval = 10.6633
-I0511 11:49:27.174705  4597 caffe.cpp:501] detection_eval = 0.0390254
-I0511 11:49:27.174708  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174712  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174716  4597 caffe.cpp:501] detection_eval = 7.45766
-I0511 11:49:27.174720  4597 caffe.cpp:501] detection_eval = 10.7258
-I0511 11:49:27.174723  4597 caffe.cpp:501] detection_eval = 0.0485399
-I0511 11:49:27.174727  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174731  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174734  4597 caffe.cpp:501] detection_eval = 7.45968
-I0511 11:49:27.174738  4597 caffe.cpp:501] detection_eval = 10.7601
-I0511 11:49:27.174741  4597 caffe.cpp:501] detection_eval = 0.0457567
-I0511 11:49:27.174746  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.174749  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.174752  4597 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:49:27.174756  4597 caffe.cpp:501] detection_eval = 10.7782
-I0511 11:49:27.174758  4597 caffe.cpp:501] detection_eval = 0.0452479
-I0511 11:49:27.174762  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174767  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.174769  4597 caffe.cpp:501] detection_eval = 7.46371
-I0511 11:49:27.174773  4597 caffe.cpp:501] detection_eval = 10.7903
-I0511 11:49:27.174777  4597 caffe.cpp:501] detection_eval = 0.0370989
-I0511 11:49:27.174782  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174784  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174788  4597 caffe.cpp:501] detection_eval = 7.46976
-I0511 11:49:27.174793  4597 caffe.cpp:501] detection_eval = 10.7762
-I0511 11:49:27.174796  4597 caffe.cpp:501] detection_eval = 0.0458781
-I0511 11:49:27.174799  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.174803  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.174806  4597 caffe.cpp:501] detection_eval = 7.46976
-I0511 11:49:27.174813  4597 caffe.cpp:501] detection_eval = 10.8226
-I0511 11:49:27.174818  4597 caffe.cpp:501] detection_eval = 0.0386743
-I0511 11:49:27.174821  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174825  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174829  4597 caffe.cpp:501] detection_eval = 7.47379
-I0511 11:49:27.174832  4597 caffe.cpp:501] detection_eval = 10.7923
-I0511 11:49:27.174836  4597 caffe.cpp:501] detection_eval = 0.0367524
-I0511 11:49:27.174839  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.174842  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174846  4597 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:49:27.174849  4597 caffe.cpp:501] detection_eval = 10.7903
-I0511 11:49:27.174854  4597 caffe.cpp:501] detection_eval = 0.0369325
-I0511 11:49:27.174857  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174860  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174865  4597 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:49:27.174868  4597 caffe.cpp:501] detection_eval = 10.8286
-I0511 11:49:27.174871  4597 caffe.cpp:501] detection_eval = 0.039236
-I0511 11:49:27.174875  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174880  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174882  4597 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:49:27.174886  4597 caffe.cpp:501] detection_eval = 10.75
-I0511 11:49:27.174890  4597 caffe.cpp:501] detection_eval = 0.0486638
-I0511 11:49:27.174893  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174897  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.174901  4597 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:49:27.174904  4597 caffe.cpp:501] detection_eval = 10.7157
-I0511 11:49:27.174908  4597 caffe.cpp:501] detection_eval = 0.0394219
-I0511 11:49:27.174912  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174916  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174919  4597 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:49:27.174922  4597 caffe.cpp:501] detection_eval = 10.8004
-I0511 11:49:27.174926  4597 caffe.cpp:501] detection_eval = 0.0437894
-I0511 11:49:27.174929  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174933  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174937  4597 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:49:27.174940  4597 caffe.cpp:501] detection_eval = 10.8105
-I0511 11:49:27.174944  4597 caffe.cpp:501] detection_eval = 0.0412713
-I0511 11:49:27.174948  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174952  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.174955  4597 caffe.cpp:501] detection_eval = 7.4879
-I0511 11:49:27.174959  4597 caffe.cpp:501] detection_eval = 10.8226
-I0511 11:49:27.174963  4597 caffe.cpp:501] detection_eval = 0.0410146
-I0511 11:49:27.174966  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174970  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174974  4597 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:49:27.174978  4597 caffe.cpp:501] detection_eval = 10.746
-I0511 11:49:27.174981  4597 caffe.cpp:501] detection_eval = 0.0432423
-I0511 11:49:27.174985  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174988  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174993  4597 caffe.cpp:501] detection_eval = 7.5
-I0511 11:49:27.174996  4597 caffe.cpp:501] detection_eval = 10.8185
-I0511 11:49:27.175000  4597 caffe.cpp:501] detection_eval = 0.0420377
-I0511 11:49:27.175004  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175007  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.175010  4597 caffe.cpp:501] detection_eval = 7.50605
-I0511 11:49:27.175014  4597 caffe.cpp:501] detection_eval = 10.7923
-I0511 11:49:27.175017  4597 caffe.cpp:501] detection_eval = 0.0398127
-I0511 11:49:27.175021  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.175024  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.175029  4597 caffe.cpp:501] detection_eval = 7.51008
-I0511 11:49:27.175035  4597 caffe.cpp:501] detection_eval = 10.8327
-I0511 11:49:27.175040  4597 caffe.cpp:501] detection_eval = 0.0384945
-I0511 11:49:27.175043  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.175047  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.175050  4597 caffe.cpp:501] detection_eval = 7.52016
-I0511 11:49:27.175055  4597 caffe.cpp:501] detection_eval = 10.7621
-I0511 11:49:27.175058  4597 caffe.cpp:501] detection_eval = 0.0405141
-I0511 11:49:27.175062  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175065  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175070  4597 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:49:27.175072  4597 caffe.cpp:501] detection_eval = 10.7883
-I0511 11:49:27.175076  4597 caffe.cpp:501] detection_eval = 0.0368635
-I0511 11:49:27.175081  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.175084  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.175087  4597 caffe.cpp:501] detection_eval = 7.53024
-I0511 11:49:27.175091  4597 caffe.cpp:501] detection_eval = 10.7681
-I0511 11:49:27.175096  4597 caffe.cpp:501] detection_eval = 0.0424594
-I0511 11:49:27.175098  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175101  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175106  4597 caffe.cpp:501] detection_eval = 7.53629
-I0511 11:49:27.175108  4597 caffe.cpp:501] detection_eval = 10.7399
-I0511 11:49:27.175112  4597 caffe.cpp:501] detection_eval = 0.0415589
-I0511 11:49:27.175117  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.175119  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.175123  4597 caffe.cpp:501] detection_eval = 7.52016
-I0511 11:49:27.175127  4597 caffe.cpp:501] detection_eval = 10.8145
-I0511 11:49:27.175130  4597 caffe.cpp:501] detection_eval = 0.0470319
-I0511 11:49:27.175134  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.175138  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.175143  4597 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:49:27.175145  4597 caffe.cpp:501] detection_eval = 10.8387
-I0511 11:49:27.175149  4597 caffe.cpp:501] detection_eval = 0.0430624
-I0511 11:49:27.175565  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.175572  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.175575  4597 caffe.cpp:501] detection_eval = 7.52823
-I0511 11:49:27.175580  4597 caffe.cpp:501] detection_eval = 10.8609
-I0511 11:49:27.175583  4597 caffe.cpp:501] detection_eval = 0.0490111
-I0511 11:49:27.175586  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175590  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175595  4597 caffe.cpp:501] detection_eval = 7.53024
-I0511 11:49:27.175598  4597 caffe.cpp:501] detection_eval = 10.9234
-I0511 11:49:27.175602  4597 caffe.cpp:501] detection_eval = 0.0421941
-I0511 11:49:27.175606  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175609  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175613  4597 caffe.cpp:501] detection_eval = 7.53427
-I0511 11:49:27.175616  4597 caffe.cpp:501] detection_eval = 10.9456
-I0511 11:49:27.175621  4597 caffe.cpp:501] detection_eval = 0.0405491
-I0511 11:49:27.175624  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175628  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.175631  4597 caffe.cpp:501] detection_eval = 7.53831
-I0511 11:49:27.175635  4597 caffe.cpp:501] detection_eval = 11
-I0511 11:49:27.175639  4597 caffe.cpp:501] detection_eval = 0.047071
-I0511 11:49:27.175642  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175645  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175648  4597 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:49:27.175653  4597 caffe.cpp:501] detection_eval = 10.9214
-I0511 11:49:27.175657  4597 caffe.cpp:501] detection_eval = 0.0439473
-I0511 11:49:27.175662  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.175668  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.175680  4597 caffe.cpp:501] detection_eval = 7.5504
-I0511 11:49:27.175686  4597 caffe.cpp:501] detection_eval = 10.9254
-I0511 11:49:27.175690  4597 caffe.cpp:501] detection_eval = 0.0403158
-I0511 11:49:27.175693  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175698  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.175701  4597 caffe.cpp:501] detection_eval = 7.55242
-I0511 11:49:27.175704  4597 caffe.cpp:501] detection_eval = 10.9556
-I0511 11:49:27.175707  4597 caffe.cpp:501] detection_eval = 0.0456277
-I0511 11:49:27.175711  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.175714  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175719  4597 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:49:27.175721  4597 caffe.cpp:501] detection_eval = 10.9476
-I0511 11:49:27.175725  4597 caffe.cpp:501] detection_eval = 0.0426379
-I0511 11:49:27.175729  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175734  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.175736  4597 caffe.cpp:501] detection_eval = 7.56452
-I0511 11:49:27.175740  4597 caffe.cpp:501] detection_eval = 10.9173
-I0511 11:49:27.175745  4597 caffe.cpp:501] detection_eval = 0.0448893
-I0511 11:49:27.175747  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.175751  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.175755  4597 caffe.cpp:501] detection_eval = 7.56653
-I0511 11:49:27.175758  4597 caffe.cpp:501] detection_eval = 10.9758
-I0511 11:49:27.175762  4597 caffe.cpp:501] detection_eval = 0.0458773
-I0511 11:49:27.175766  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.175770  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.175773  4597 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:49:27.175776  4597 caffe.cpp:501] detection_eval = 11.0121
-I0511 11:49:27.175781  4597 caffe.cpp:501] detection_eval = 0.0412877
-I0511 11:49:27.175784  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175788  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.175791  4597 caffe.cpp:501] detection_eval = 7.57258
-I0511 11:49:27.175794  4597 caffe.cpp:501] detection_eval = 11.002
-I0511 11:49:27.175798  4597 caffe.cpp:501] detection_eval = 0.0379916
-I0511 11:49:27.175802  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175806  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175810  4597 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:49:27.175813  4597 caffe.cpp:501] detection_eval = 11.0847
-I0511 11:49:27.175817  4597 caffe.cpp:501] detection_eval = 0.0451914
-I0511 11:49:27.175822  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175824  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175828  4597 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:49:27.175832  4597 caffe.cpp:501] detection_eval = 11.0323
-I0511 11:49:27.175835  4597 caffe.cpp:501] detection_eval = 0.0439928
-I0511 11:49:27.175839  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175843  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.175846  4597 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:49:27.175850  4597 caffe.cpp:501] detection_eval = 10.9899
-I0511 11:49:27.175854  4597 caffe.cpp:501] detection_eval = 0.0409328
-I0511 11:49:27.175858  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.175861  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175865  4597 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:49:27.175868  4597 caffe.cpp:501] detection_eval = 10.9839
-I0511 11:49:27.175873  4597 caffe.cpp:501] detection_eval = 0.0389855
-I0511 11:49:27.175875  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.175879  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175882  4597 caffe.cpp:501] detection_eval = 7.57863
-I0511 11:49:27.175886  4597 caffe.cpp:501] detection_eval = 10.9859
-I0511 11:49:27.175890  4597 caffe.cpp:501] detection_eval = 0.0393829
-I0511 11:49:27.175894  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175901  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175905  4597 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:49:27.175909  4597 caffe.cpp:501] detection_eval = 11.0081
-I0511 11:49:27.175914  4597 caffe.cpp:501] detection_eval = 0.0406608
-I0511 11:49:27.175916  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175920  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175925  4597 caffe.cpp:501] detection_eval = 7.59073
-I0511 11:49:27.175928  4597 caffe.cpp:501] detection_eval = 10.9456
-I0511 11:49:27.175932  4597 caffe.cpp:501] detection_eval = 0.0404323
-I0511 11:49:27.175935  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.175940  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175943  4597 caffe.cpp:501] detection_eval = 7.59073
-I0511 11:49:27.175946  4597 caffe.cpp:501] detection_eval = 11.0282
-I0511 11:49:27.175951  4597 caffe.cpp:501] detection_eval = 0.043047
-I0511 11:49:27.175954  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175957  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175961  4597 caffe.cpp:501] detection_eval = 7.59476
-I0511 11:49:27.175964  4597 caffe.cpp:501] detection_eval = 11.0524
-I0511 11:49:27.175967  4597 caffe.cpp:501] detection_eval = 0.0417951
-I0511 11:49:27.175971  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175976  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175978  4597 caffe.cpp:501] detection_eval = 7.59677
-I0511 11:49:27.175982  4597 caffe.cpp:501] detection_eval = 11.0927
-I0511 11:49:27.175987  4597 caffe.cpp:501] detection_eval = 0.0371979
-I0511 11:49:27.175989  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175993  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175997  4597 caffe.cpp:501] detection_eval = 7.60282
-I0511 11:49:27.176000  4597 caffe.cpp:501] detection_eval = 11.0685
-I0511 11:49:27.176004  4597 caffe.cpp:501] detection_eval = 0.0440634
-I0511 11:49:27.176008  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.176012  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176015  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176309  4597 caffe.cpp:501] detection_eval = 11.0423
-I0511 11:49:27.176316  4597 caffe.cpp:501] detection_eval = 0.0465861
-I0511 11:49:27.176319  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.176323  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.176326  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176331  4597 caffe.cpp:501] detection_eval = 11.1351
-I0511 11:49:27.176334  4597 caffe.cpp:501] detection_eval = 0.0409808
-I0511 11:49:27.176338  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176342  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.176345  4597 caffe.cpp:501] detection_eval = 7.59677
-I0511 11:49:27.176349  4597 caffe.cpp:501] detection_eval = 11.0786
-I0511 11:49:27.176352  4597 caffe.cpp:501] detection_eval = 0.0377656
-I0511 11:49:27.176357  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176360  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176363  4597 caffe.cpp:501] detection_eval = 7.60081
-I0511 11:49:27.176367  4597 caffe.cpp:501] detection_eval = 11.0585
-I0511 11:49:27.176370  4597 caffe.cpp:501] detection_eval = 0.0357857
-I0511 11:49:27.176374  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.176378  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.176381  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.176385  4597 caffe.cpp:501] detection_eval = 11.0504
-I0511 11:49:27.176388  4597 caffe.cpp:501] detection_eval = 0.036233
-I0511 11:49:27.176393  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.176396  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.176400  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176403  4597 caffe.cpp:501] detection_eval = 11.0484
-I0511 11:49:27.176407  4597 caffe.cpp:501] detection_eval = 0.0392681
-I0511 11:49:27.176411  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.176419  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176424  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176427  4597 caffe.cpp:501] detection_eval = 11.123
-I0511 11:49:27.176431  4597 caffe.cpp:501] detection_eval = 0.0397001
-I0511 11:49:27.176434  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.176439  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.176441  4597 caffe.cpp:501] detection_eval = 7.61492
-I0511 11:49:27.176445  4597 caffe.cpp:501] detection_eval = 11.121
-I0511 11:49:27.176448  4597 caffe.cpp:501] detection_eval = 0.0381308
-I0511 11:49:27.176452  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.176456  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.176460  4597 caffe.cpp:501] detection_eval = 7.61492
-I0511 11:49:27.176463  4597 caffe.cpp:501] detection_eval = 11.1996
-I0511 11:49:27.176467  4597 caffe.cpp:501] detection_eval = 0.0407439
-I0511 11:49:27.176470  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176475  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.176478  4597 caffe.cpp:501] detection_eval = 7.62097
-I0511 11:49:27.176481  4597 caffe.cpp:501] detection_eval = 11.2056
-I0511 11:49:27.176486  4597 caffe.cpp:501] detection_eval = 0.0421225
-I0511 11:49:27.176489  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.176492  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.176496  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176501  4597 caffe.cpp:501] detection_eval = 11.1492
-I0511 11:49:27.176503  4597 caffe.cpp:501] detection_eval = 0.0440622
-I0511 11:49:27.176507  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176512  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176514  4597 caffe.cpp:501] detection_eval = 7.59476
-I0511 11:49:27.176518  4597 caffe.cpp:501] detection_eval = 11.125
-I0511 11:49:27.176522  4597 caffe.cpp:501] detection_eval = 0.0411818
-I0511 11:49:27.176542  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.176545  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.176549  4597 caffe.cpp:501] detection_eval = 7.60081
-I0511 11:49:27.176553  4597 caffe.cpp:501] detection_eval = 11.0847
-I0511 11:49:27.176558  4597 caffe.cpp:501] detection_eval = 0.0365465
-I0511 11:49:27.176561  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.176564  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176568  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.176573  4597 caffe.cpp:501] detection_eval = 11.0746
-I0511 11:49:27.176575  4597 caffe.cpp:501] detection_eval = 0.0397285
-I0511 11:49:27.176579  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.176584  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176587  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.176590  4597 caffe.cpp:501] detection_eval = 11.1391
-I0511 11:49:27.176594  4597 caffe.cpp:501] detection_eval = 0.037983
-I0511 11:49:27.176599  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.176602  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.176605  4597 caffe.cpp:501] detection_eval = 7.61089
-I0511 11:49:27.176609  4597 caffe.cpp:501] detection_eval = 11.1028
-I0511 11:49:27.176614  4597 caffe.cpp:501] detection_eval = 0.0400337
-I0511 11:49:27.176617  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.176620  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176625  4597 caffe.cpp:501] detection_eval = 7.61895
-I0511 11:49:27.176627  4597 caffe.cpp:501] detection_eval = 11.0625
-I0511 11:49:27.176630  4597 caffe.cpp:501] detection_eval = 0.0397385
-I0511 11:49:27.176635  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.176638  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.176641  4597 caffe.cpp:501] detection_eval = 7.62097
-I0511 11:49:27.176645  4597 caffe.cpp:501] detection_eval = 11.1109
-I0511 11:49:27.176650  4597 caffe.cpp:501] detection_eval = 0.0427227
-I0511 11:49:27.176657  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.176661  4597 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:49:27.176666  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.176669  4597 caffe.cpp:501] detection_eval = 11.1069
-I0511 11:49:27.176673  4597 caffe.cpp:501] detection_eval = 0.0386111
-I0511 11:49:27.176676  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176681  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.176684  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176687  4597 caffe.cpp:501] detection_eval = 11.0907
-I0511 11:49:27.176692  4597 caffe.cpp:501] detection_eval = 0.036727
-I0511 11:49:27.176695  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176699  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.176702  4597 caffe.cpp:501] detection_eval = 7.59476
-I0511 11:49:27.176707  4597 caffe.cpp:501] detection_eval = 11.0665
-I0511 11:49:27.176709  4597 caffe.cpp:501] detection_eval = 0.036776
-I0511 11:49:27.176713  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.176717  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.176720  4597 caffe.cpp:501] detection_eval = 7.59677
-I0511 11:49:27.176723  4597 caffe.cpp:501] detection_eval = 11.0927
-I0511 11:49:27.176728  4597 caffe.cpp:501] detection_eval = 0.0361817
-I0511 11:49:27.176731  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.176735  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.176738  4597 caffe.cpp:501] detection_eval = 7.59879
-I0511 11:49:27.176743  4597 caffe.cpp:501] detection_eval = 11.129
-I0511 11:49:27.176746  4597 caffe.cpp:501] detection_eval = 0.0378719
-I0511 11:49:27.176749  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.176753  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.176757  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176760  4597 caffe.cpp:501] detection_eval = 11.0565
-I0511 11:49:27.176764  4597 caffe.cpp:501] detection_eval = 0.0374305
-I0511 11:49:27.176769  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.177091  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.177096  4597 caffe.cpp:501] detection_eval = 7.61089
-I0511 11:49:27.177100  4597 caffe.cpp:501] detection_eval = 11.123
-I0511 11:49:27.177104  4597 caffe.cpp:501] detection_eval = 0.0417044
-I0511 11:49:27.177109  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177111  4597 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:49:27.177115  4597 caffe.cpp:501] detection_eval = 7.61492
-I0511 11:49:27.177119  4597 caffe.cpp:501] detection_eval = 11.1048
-I0511 11:49:27.177122  4597 caffe.cpp:501] detection_eval = 0.0383507
-I0511 11:49:27.177125  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177140  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.177145  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.177148  4597 caffe.cpp:501] detection_eval = 11.1573
-I0511 11:49:27.177152  4597 caffe.cpp:501] detection_eval = 0.0405986
-I0511 11:49:27.177156  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177160  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.177163  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.177167  4597 caffe.cpp:501] detection_eval = 11.127
-I0511 11:49:27.177171  4597 caffe.cpp:501] detection_eval = 0.042147
-I0511 11:49:27.177175  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177178  4597 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:49:27.177182  4597 caffe.cpp:501] detection_eval = 7.58871
-I0511 11:49:27.177186  4597 caffe.cpp:501] detection_eval = 11.1512
-I0511 11:49:27.177189  4597 caffe.cpp:501] detection_eval = 0.0426079
-I0511 11:49:27.177193  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.177196  4597 caffe.cpp:501] detection_eval = 0.939516
-I0511 11:49:27.177201  4597 caffe.cpp:501] detection_eval = 7.59476
-I0511 11:49:27.177203  4597 caffe.cpp:501] detection_eval = 11.1331
-I0511 11:49:27.177206  4597 caffe.cpp:501] detection_eval = 0.0364144
-I0511 11:49:27.177215  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177219  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.177222  4597 caffe.cpp:501] detection_eval = 7.57863
-I0511 11:49:27.177227  4597 caffe.cpp:501] detection_eval = 11.1694
-I0511 11:49:27.177230  4597 caffe.cpp:501] detection_eval = 0.038096
-I0511 11:49:27.177234  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177237  4597 caffe.cpp:501] detection_eval = 0.941532
-I0511 11:49:27.177242  4597 caffe.cpp:501] detection_eval = 7.5625
-I0511 11:49:27.177245  4597 caffe.cpp:501] detection_eval = 11.1815
-I0511 11:49:27.177249  4597 caffe.cpp:501] detection_eval = 0.0357599
-I0511 11:49:27.177253  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.177256  4597 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:49:27.177260  4597 caffe.cpp:501] detection_eval = 7.56653
-I0511 11:49:27.177264  4597 caffe.cpp:501] detection_eval = 11.1996
-I0511 11:49:27.177268  4597 caffe.cpp:501] detection_eval = 0.0355026
-I0511 11:49:27.177271  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.177275  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.177279  4597 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:49:27.177283  4597 caffe.cpp:501] detection_eval = 11.2238
-I0511 11:49:27.177286  4597 caffe.cpp:501] detection_eval = 0.0386533
-I0511 11:49:27.177289  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.177294  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.177297  4597 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:49:27.177301  4597 caffe.cpp:501] detection_eval = 11.2601
-I0511 11:49:27.177304  4597 caffe.cpp:501] detection_eval = 0.0463732
-I0511 11:49:27.177309  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177312  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.177316  4597 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:49:27.177320  4597 caffe.cpp:501] detection_eval = 11.3528
-I0511 11:49:27.177323  4597 caffe.cpp:501] detection_eval = 0.0391411
-I0511 11:49:27.177327  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.177331  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.177335  4597 caffe.cpp:501] detection_eval = 7.55847
-I0511 11:49:27.177338  4597 caffe.cpp:501] detection_eval = 11.3427
-I0511 11:49:27.177342  4597 caffe.cpp:501] detection_eval = 0.035949
-I0511 11:49:27.177346  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.177350  4597 caffe.cpp:501] detection_eval = 0.939516
-I0511 11:49:27.177353  4597 caffe.cpp:501] detection_eval = 7.56048
-I0511 11:49:27.177357  4597 caffe.cpp:501] detection_eval = 11.3891
-I0511 11:49:27.177361  4597 caffe.cpp:501] detection_eval = 0.0401412
-I0511 11:49:27.177364  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.177368  4597 caffe.cpp:501] detection_eval = 0.939516
-I0511 11:49:27.177371  4597 caffe.cpp:501] detection_eval = 7.56452
-I0511 11:49:27.177374  4597 caffe.cpp:501] detection_eval = 11.4093
-I0511 11:49:27.177378  4597 caffe.cpp:501] detection_eval = 0.0390099
-I0511 11:49:27.177381  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.177386  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.177389  4597 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:49:27.177392  4597 caffe.cpp:501] detection_eval = 11.4435
-I0511 11:49:27.177397  4597 caffe.cpp:501] detection_eval = 0.040263
-I0511 11:49:27.177400  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.177404  4597 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:49:27.177407  4597 caffe.cpp:501] detection_eval = 7.53427
-I0511 11:49:27.177412  4597 caffe.cpp:501] detection_eval = 11.4032
-I0511 11:49:27.177415  4597 caffe.cpp:501] detection_eval = 0.0402077
-I0511 11:49:27.177418  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177423  4597 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:49:27.177426  4597 caffe.cpp:501] detection_eval = 7.51815
-I0511 11:49:27.177429  4597 caffe.cpp:501] detection_eval = 11.4355
-I0511 11:49:27.177438  4597 caffe.cpp:501] detection_eval = 0.0371625
-I0511 11:49:27.177441  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.177445  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.177449  4597 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:49:27.177453  4597 caffe.cpp:501] detection_eval = 11.4718
-I0511 11:49:27.177456  4597 caffe.cpp:501] detection_eval = 0.0411716
-I0511 11:49:27.177459  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177462  4597 caffe.cpp:501] detection_eval = 0.927419
-I0511 11:49:27.177466  4597 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:49:27.177469  4597 caffe.cpp:501] detection_eval = 11.5565
-I0511 11:49:27.177474  4597 caffe.cpp:501] detection_eval = 0.0383002
-I0511 11:49:27.177477  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.177481  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.177485  4597 caffe.cpp:501] detection_eval = 7.53024
-I0511 11:49:27.177489  4597 caffe.cpp:501] detection_eval = 11.5988
-I0511 11:49:27.177492  4597 caffe.cpp:501] detection_eval = 0.0439466
-I0511 11:49:27.177496  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177500  4597 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:49:27.177510  4597 caffe.cpp:501] detection_eval = 7.53427
-I0511 11:49:27.177513  4597 caffe.cpp:501] detection_eval = 11.6996
-I0511 11:49:27.177517  4597 caffe.cpp:501] detection_eval = 0.0420059
-I0511 11:49:27.177521  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.177525  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.177528  4597 caffe.cpp:501] detection_eval = 7.54234
-I0511 11:49:27.177532  4597 caffe.cpp:501] detection_eval = 11.7843
-I0511 11:49:27.177536  4597 caffe.cpp:501] detection_eval = 0.0382367
-I0511 11:49:27.177539  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177542  4597 caffe.cpp:501] detection_eval = 0.935484
-I0511 11:49:27.177546  4597 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:49:27.177549  4597 caffe.cpp:501] detection_eval = 8.28024
-I0511 11:49:27.178318  4597 caffe.cpp:501] detection_eval = 0.058111
-I0511 11:49:27.178328  4597 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:49:27.178333  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178335  4597 caffe.cpp:501] detection_eval = 7.78226
-I0511 11:49:27.178339  4597 caffe.cpp:501] detection_eval = 8.29839
-I0511 11:49:27.178344  4597 caffe.cpp:501] detection_eval = 0.0464954
-I0511 11:49:27.178346  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178350  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178354  4597 caffe.cpp:501] detection_eval = 7.78427
-I0511 11:49:27.178357  4597 caffe.cpp:501] detection_eval = 8.37903
-I0511 11:49:27.178360  4597 caffe.cpp:501] detection_eval = 0.0468021
-I0511 11:49:27.178364  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178369  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178372  4597 caffe.cpp:501] detection_eval = 7.77016
-I0511 11:49:27.178375  4597 caffe.cpp:501] detection_eval = 8.39919
-I0511 11:49:27.178380  4597 caffe.cpp:501] detection_eval = 0.0519864
-I0511 11:49:27.178382  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.178386  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178390  4597 caffe.cpp:501] detection_eval = 7.77419
-I0511 11:49:27.178393  4597 caffe.cpp:501] detection_eval = 8.43347
-I0511 11:49:27.178396  4597 caffe.cpp:501] detection_eval = 0.0548872
-I0511 11:49:27.178400  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.178403  4597 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:49:27.178406  4597 caffe.cpp:501] detection_eval = 7.77419
-I0511 11:49:27.178411  4597 caffe.cpp:501] detection_eval = 8.51411
-I0511 11:49:27.178413  4597 caffe.cpp:501] detection_eval = 0.0448702
-I0511 11:49:27.178417  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.178421  4597 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:49:27.178424  4597 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:49:27.178427  4597 caffe.cpp:501] detection_eval = 8.54234
-I0511 11:49:27.178436  4597 caffe.cpp:501] detection_eval = 0.0396127
-I0511 11:49:27.178442  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178444  4597 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:49:27.178447  4597 caffe.cpp:501] detection_eval = 7.76411
-I0511 11:49:27.178449  4597 caffe.cpp:501] detection_eval = 8.52016
-I0511 11:49:27.178452  4597 caffe.cpp:501] detection_eval = 0.0431888
-I0511 11:49:27.178453  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.178457  4597 caffe.cpp:501] detection_eval = 0.923387
-I0511 11:49:27.178458  4597 caffe.cpp:501] detection_eval = 7.75605
-I0511 11:49:27.178460  4597 caffe.cpp:501] detection_eval = 8.41129
-I0511 11:49:27.178462  4597 caffe.cpp:501] detection_eval = 0.0442477
-I0511 11:49:27.178464  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.178467  4597 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:49:27.178468  4597 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:49:27.178470  4597 caffe.cpp:501] detection_eval = 8.37702
-I0511 11:49:27.178473  4597 caffe.cpp:501] detection_eval = 0.0369189
-I0511 11:49:27.178475  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178478  4597 caffe.cpp:501] detection_eval = 0.927419
-I0511 11:49:27.178479  4597 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:49:27.178481  4597 caffe.cpp:501] detection_eval = 8.44758
-I0511 11:49:27.178483  4597 caffe.cpp:501] detection_eval = 0.0387095
-I0511 11:49:27.178485  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178488  4597 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:49:27.178489  4597 caffe.cpp:501] detection_eval = 7.74395
-I0511 11:49:27.178491  4597 caffe.cpp:501] detection_eval = 8.44758
-I0511 11:49:27.178494  4597 caffe.cpp:501] detection_eval = 0.0371474
-I0511 11:49:27.178496  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178498  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178500  4597 caffe.cpp:501] detection_eval = 7.74395
-I0511 11:49:27.178503  4597 caffe.cpp:501] detection_eval = 8.54637
-I0511 11:49:27.178504  4597 caffe.cpp:501] detection_eval = 0.0432443
-I0511 11:49:27.178508  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178509  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178511  4597 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:49:27.178514  4597 caffe.cpp:501] detection_eval = 8.57056
-I0511 11:49:27.178515  4597 caffe.cpp:501] detection_eval = 0.0418594
-I0511 11:49:27.178517  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178519  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178521  4597 caffe.cpp:501] detection_eval = 7.72782
-I0511 11:49:27.178524  4597 caffe.cpp:501] detection_eval = 8.60282
-I0511 11:49:27.178526  4597 caffe.cpp:501] detection_eval = 0.042764
-I0511 11:49:27.178529  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178530  4597 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:49:27.178532  4597 caffe.cpp:501] detection_eval = 7.72984
-I0511 11:49:27.178534  4597 caffe.cpp:501] detection_eval = 8.62298
-I0511 11:49:27.178536  4597 caffe.cpp:501] detection_eval = 0.0355886
-I0511 11:49:27.178539  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.178540  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178544  4597 caffe.cpp:501] detection_eval = 7.71169
-I0511 11:49:27.178545  4597 caffe.cpp:501] detection_eval = 8.65121
-I0511 11:49:27.178547  4597 caffe.cpp:501] detection_eval = 0.0369829
-I0511 11:49:27.178550  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.178551  4597 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:49:27.178553  4597 caffe.cpp:501] detection_eval = 7.71169
-I0511 11:49:27.178555  4597 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:49:27.178557  4597 caffe.cpp:501] detection_eval = 0.0373797
-I0511 11:49:27.178560  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.178562  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178565  4597 caffe.cpp:501] detection_eval = 7.71573
-I0511 11:49:27.178570  4597 caffe.cpp:501] detection_eval = 8.71169
-I0511 11:49:27.178571  4597 caffe.cpp:501] detection_eval = 0.0356923
-I0511 11:49:27.178573  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.178576  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178578  4597 caffe.cpp:501] detection_eval = 7.71976
-I0511 11:49:27.178581  4597 caffe.cpp:501] detection_eval = 8.71169
-I0511 11:49:27.178586  4597 caffe.cpp:501] detection_eval = 0.0388887
-I0511 11:49:27.178588  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.178592  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178596  4597 caffe.cpp:501] detection_eval = 7.6875
-I0511 11:49:27.178599  4597 caffe.cpp:501] detection_eval = 8.6371
-I0511 11:49:27.178603  4597 caffe.cpp:501] detection_eval = 0.0367226
-I0511 11:49:27.178607  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178611  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178614  4597 caffe.cpp:501] detection_eval = 7.6875
-I0511 11:49:27.178617  4597 caffe.cpp:501] detection_eval = 8.7379
-I0511 11:49:27.178620  4597 caffe.cpp:501] detection_eval = 0.0418173
-I0511 11:49:27.178624  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178627  4597 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:49:27.178632  4597 caffe.cpp:501] detection_eval = 7.69355
-I0511 11:49:27.178637  4597 caffe.cpp:501] detection_eval = 8.72984
-I0511 11:49:27.178639  4597 caffe.cpp:501] detection_eval = 0.0378575
-I0511 11:49:27.178642  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178643  4597 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:49:27.178647  4597 caffe.cpp:501] detection_eval = 7.70565
-I0511 11:49:27.178648  4597 caffe.cpp:501] detection_eval = 8.62097
-I0511 11:49:27.178650  4597 caffe.cpp:501] detection_eval = 0.0408286
-I0511 11:49:27.178653  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.178654  4597 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:49:27.178656  4597 caffe.cpp:501] detection_eval = 7.70766
-I0511 11:49:27.178658  4597 caffe.cpp:501] detection_eval = 8.65726
-I0511 11:49:27.178660  4597 caffe.cpp:501] detection_eval = 0.0408957
-I0511 11:49:27.178663  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.178665  4597 caffe.cpp:501] detection_eval = 0.903226
-I0511 11:49:27.178668  4597 caffe.cpp:501] detection_eval = 7.70968
-I0511 11:49:27.178669  4597 caffe.cpp:501] detection_eval = 8.74194
-I0511 11:49:27.178671  4597 caffe.cpp:501] detection_eval = 0.0408394
-I0511 11:49:27.178673  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178675  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178678  4597 caffe.cpp:501] detection_eval = 7.69556
-I0511 11:49:27.178679  4597 caffe.cpp:501] detection_eval = 8.71976
-I0511 11:49:27.178681  4597 caffe.cpp:501] detection_eval = 0.0373829
-I0511 11:49:27.178683  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178685  4597 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:49:27.178688  4597 caffe.cpp:501] detection_eval = 7.69758
-I0511 11:49:27.178690  4597 caffe.cpp:501] detection_eval = 8.7621
-I0511 11:49:27.178692  4597 caffe.cpp:501] detection_eval = 0.0379139
-I0511 11:49:27.178694  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178696  4597 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:49:27.178699  4597 caffe.cpp:501] detection_eval = 7.70161
-I0511 11:49:27.178700  4597 caffe.cpp:501] detection_eval = 8.77419
-I0511 11:49:27.178702  4597 caffe.cpp:501] detection_eval = 0.0377139
-I0511 11:49:27.178704  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178706  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178709  4597 caffe.cpp:501] detection_eval = 7.70161
-I0511 11:49:27.178710  4597 caffe.cpp:501] detection_eval = 8.81452
-I0511 11:49:27.178712  4597 caffe.cpp:501] detection_eval = 0.0355406
-I0511 11:49:27.178714  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178717  4597 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:49:27.178722  4597 caffe.cpp:501] detection_eval = 7.70565
-I0511 11:49:27.178725  4597 caffe.cpp:501] detection_eval = 8.8125
-I0511 11:49:27.178726  4597 caffe.cpp:501] detection_eval = 0.0367864
-I0511 11:49:27.178730  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178731  4597 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:49:27.178733  4597 caffe.cpp:501] detection_eval = 7.70968
-I0511 11:49:27.178735  4597 caffe.cpp:501] detection_eval = 8.82056
-I0511 11:49:27.178737  4597 caffe.cpp:501] detection_eval = 0.0366737
-I0511 11:49:27.178740  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.178741  4597 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:49:27.178743  4597 caffe.cpp:501] detection_eval = 7.71371
-I0511 11:49:27.178745  4597 caffe.cpp:501] detection_eval = 8.8246
-I0511 11:49:27.178748  4597 caffe.cpp:501] detection_eval = 0.0387977
-I0511 11:49:27.178750  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178752  4597 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:49:27.178755  4597 caffe.cpp:501] detection_eval = 7.71573
-I0511 11:49:27.178756  4597 caffe.cpp:501] detection_eval = 8.85685
-I0511 11:49:27.178758  4597 caffe.cpp:501] detection_eval = 0.0352025
-I0511 11:49:27.178761  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178762  4597 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:49:27.178764  4597 caffe.cpp:501] detection_eval = 7.70161
-I0511 11:49:27.178766  4597 caffe.cpp:501] detection_eval = 8.87903
-I0511 11:49:27.178768  4597 caffe.cpp:501] detection_eval = 0.0441723
-I0511 11:49:27.178771  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.178773  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178776  4597 caffe.cpp:501] detection_eval = 7.68548
-I0511 11:49:27.178777  4597 caffe.cpp:501] detection_eval = 8.89718
-I0511 11:49:27.178779  4597 caffe.cpp:501] detection_eval = 0.0351511
-I0511 11:49:27.178781  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178783  4597 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:49:27.178786  4597 caffe.cpp:501] detection_eval = 7.68952
-I0511 11:49:27.178788  4597 caffe.cpp:501] detection_eval = 8.8871
-I0511 11:49:27.178791  4597 caffe.cpp:501] detection_eval = 0.0427881
-I0511 11:49:27.178792  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178794  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178797  4597 caffe.cpp:501] detection_eval = 7.68952
-I0511 11:49:27.178798  4597 caffe.cpp:501] detection_eval = 8.97984
-I0511 11:49:27.178800  4597 caffe.cpp:501] detection_eval = 0.0378922
-I0511 11:49:27.178802  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178804  4597 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:49:27.178807  4597 caffe.cpp:501] detection_eval = 7.69153
-I0511 11:49:27.178809  4597 caffe.cpp:501] detection_eval = 9.00202
-I0511 11:49:27.178812  4597 caffe.cpp:501] detection_eval = 0.0416262
-I0511 11:49:27.178813  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178815  4597 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:49:27.178817  4597 caffe.cpp:501] detection_eval = 7.69556
-I0511 11:49:27.178819  4597 caffe.cpp:501] detection_eval = 9.03226
-I0511 11:49:27.178822  4597 caffe.cpp:501] detection_eval = 0.0384373
-I0511 11:49:27.178823  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178825  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178828  4597 caffe.cpp:501] detection_eval = 7.68145
-I0511 11:49:27.178830  4597 caffe.cpp:501] detection_eval = 9.02218
-I0511 11:49:27.178833  4597 caffe.cpp:501] detection_eval = 0.0400031
-I0511 11:49:27.178834  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178836  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178838  4597 caffe.cpp:501] detection_eval = 7.6875
-I0511 11:49:27.178840  4597 caffe.cpp:501] detection_eval = 9.00403
-I0511 11:49:27.178843  4597 caffe.cpp:501] detection_eval = 0.0396534
-I0511 11:49:27.178844  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178846  4597 caffe.cpp:501] detection_eval = 0.91129
-I0511 11:49:27.178851  4597 caffe.cpp:501] detection_eval = 7.69153
-I0511 11:49:27.178854  4597 caffe.cpp:501] detection_eval = 9.10081
-I0511 11:49:27.178856  4597 caffe.cpp:501] detection_eval = 0.0392174
-I0511 11:49:27.178858  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178860  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178863  4597 caffe.cpp:501] detection_eval = 7.67742
-I0511 11:49:27.178864  4597 caffe.cpp:501] detection_eval = 9.09476
-I0511 11:49:27.178866  4597 caffe.cpp:501] detection_eval = 0.0422733
-I0511 11:49:27.178869  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178870  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178874  4597 caffe.cpp:501] detection_eval = 7.68347
-I0511 11:49:27.178875  4597 caffe.cpp:501] detection_eval = 9.08266
-I0511 11:49:27.178877  4597 caffe.cpp:501] detection_eval = 0.0434857
-I0511 11:49:27.178879  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178881  4597 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:49:27.178884  4597 caffe.cpp:501] detection_eval = 7.66532
-I0511 11:49:27.178885  4597 caffe.cpp:501] detection_eval = 9.09677
-I0511 11:49:27.178887  4597 caffe.cpp:501] detection_eval = 0.0416815
-I0511 11:49:27.178889  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178891  4597 caffe.cpp:501] detection_eval = 0.903226
-I0511 11:49:27.178894  4597 caffe.cpp:501] detection_eval = 7.67339
-I0511 11:49:27.178896  4597 caffe.cpp:501] detection_eval = 9.02419
-I0511 11:49:27.178899  4597 caffe.cpp:501] detection_eval = 0.0396996
-I0511 11:49:27.178900  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178902  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178905  4597 caffe.cpp:501] detection_eval = 7.6754
-I0511 11:49:27.178906  4597 caffe.cpp:501] detection_eval = 9.09476
-I0511 11:49:27.178908  4597 caffe.cpp:501] detection_eval = 0.0444098
-I0511 11:49:27.178911  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178913  4597 caffe.cpp:501] detection_eval = 0.895161
-I0511 11:49:27.178915  4597 caffe.cpp:501] detection_eval = 7.67944
-I0511 11:49:27.178917  4597 caffe.cpp:501] detection_eval = 9.125
-I0511 11:49:27.178920  4597 caffe.cpp:501] detection_eval = 0.0412734
-I0511 11:49:27.178921  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178923  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178925  4597 caffe.cpp:501] detection_eval = 7.68145
-I0511 11:49:27.178927  4597 caffe.cpp:501] detection_eval = 9.19355
-I0511 11:49:27.178930  4597 caffe.cpp:501] detection_eval = 0.0384269
-I0511 11:49:27.178931  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178934  4597 caffe.cpp:501] detection_eval = 0.899194
-I0511 11:49:27.178936  4597 caffe.cpp:501] detection_eval = 7.66532
-I0511 11:49:27.178938  4597 caffe.cpp:501] detection_eval = 9.19355
-I0511 11:49:27.178941  4597 caffe.cpp:501] detection_eval = 0.0394395
-I0511 11:49:27.178942  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178944  4597 caffe.cpp:501] detection_eval = 0.891129
-I0511 11:49:27.178946  4597 caffe.cpp:501] detection_eval = 7.64919
-I0511 11:49:27.178948  4597 caffe.cpp:501] detection_eval = 9.24194
-I0511 11:49:27.178951  4597 caffe.cpp:501] detection_eval = 0.0448292
-I0511 11:49:27.178952  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178954  4597 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:49:27.178957  4597 caffe.cpp:501] detection_eval = 7.63508
-I0511 11:49:27.178961  4597 caffe.cpp:501] detection_eval = 9.25403
-I0511 11:49:27.178964  4597 caffe.cpp:501] detection_eval = 0.0433481
-I0511 11:49:27.178967  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178972  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178974  4597 caffe.cpp:501] detection_eval = 7.6371
-I0511 11:49:27.178978  4597 caffe.cpp:501] detection_eval = 9.27823
-I0511 11:49:27.178982  4597 caffe.cpp:501] detection_eval = 0.0414829
-I0511 11:49:27.178984  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178992  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178997  4597 caffe.cpp:501] detection_eval = 7.6371
-I0511 11:49:27.178998  4597 caffe.cpp:501] detection_eval = 9.32863
-I0511 11:49:27.179000  4597 caffe.cpp:501] detection_eval = 0.0429957
-I0511 11:49:27.179003  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179005  4597 caffe.cpp:501] detection_eval = 0.899194
-I0511 11:49:27.179008  4597 caffe.cpp:501] detection_eval = 7.6371
-I0511 11:49:27.179009  4597 caffe.cpp:501] detection_eval = 9.37903
-I0511 11:49:27.179011  4597 caffe.cpp:501] detection_eval = 0.038854
-I0511 11:49:27.179013  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179015  4597 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:49:27.179018  4597 caffe.cpp:501] detection_eval = 7.62097
-I0511 11:49:27.179019  4597 caffe.cpp:501] detection_eval = 9.38911
-I0511 11:49:27.179021  4597 caffe.cpp:501] detection_eval = 0.0417525
-I0511 11:49:27.179023  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179026  4597 caffe.cpp:501] detection_eval = 0.899194
-I0511 11:49:27.179028  4597 caffe.cpp:501] detection_eval = 7.60685
-I0511 11:49:27.179030  4597 caffe.cpp:501] detection_eval = 9.33871
-I0511 11:49:27.179033  4597 caffe.cpp:501] detection_eval = 0.0358288
-I0511 11:49:27.179034  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.179036  4597 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:49:27.179039  4597 caffe.cpp:501] detection_eval = 7.61089
-I0511 11:49:27.179040  4597 caffe.cpp:501] detection_eval = 9.34879
-I0511 11:49:27.179042  4597 caffe.cpp:501] detection_eval = 0.0433477
-I0511 11:49:27.179045  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.179047  4597 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:49:27.179049  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.179051  4597 caffe.cpp:501] detection_eval = 9.34677
-I0511 11:49:27.179054  4597 caffe.cpp:501] detection_eval = 0.0463951
-I0511 11:49:27.179055  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.179057  4597 caffe.cpp:501] detection_eval = 0.891129
-I0511 11:49:27.179060  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.179062  4597 caffe.cpp:501] detection_eval = 9.40524
-I0511 11:49:27.179064  4597 caffe.cpp:501] detection_eval = 0.038952
-I0511 11:49:27.179066  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.179069  4597 caffe.cpp:501] detection_eval = 0.887097
-I0511 11:49:27.179070  4597 caffe.cpp:501] detection_eval = 7.60282
-I0511 11:49:27.179072  4597 caffe.cpp:501] detection_eval = 9.41734
-I0511 11:49:27.179075  4597 caffe.cpp:501] detection_eval = 0.0382986
-I0511 11:49:27.179076  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179078  4597 caffe.cpp:501] detection_eval = 0.90121
-I0511 11:49:27.179080  4597 caffe.cpp:501] detection_eval = 7.58871
-I0511 11:49:27.179082  4597 caffe.cpp:501] detection_eval = 9.39516
-I0511 11:49:27.179085  4597 caffe.cpp:501] detection_eval = 0.039604
-I0511 11:49:27.179086  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.179088  4597 caffe.cpp:501] detection_eval = 0.885081
-I0511 11:49:27.179091  4597 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:49:27.179093  4597 caffe.cpp:501] detection_eval = 9.46774
-I0511 11:49:27.179095  4597 caffe.cpp:501] detection_eval = 0.0412622
-I0511 11:49:27.179097  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.179100  4597 caffe.cpp:501] detection_eval = 0.879032
-I0511 11:49:27.179101  4597 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:49:27.179103  4597 caffe.cpp:501] detection_eval = 9.47782
-I0511 11:49:27.179105  4597 caffe.cpp:501] detection_eval = 0.0412966
-I0511 11:49:27.179107  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.179109  4597 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:49:27.179111  4597 caffe.cpp:501] detection_eval = 7.5625
-I0511 11:49:27.179113  4597 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:49:27.179116  4597 caffe.cpp:501] detection_eval = 0.0367838
-I0511 11:49:27.179117  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179122  4597 caffe.cpp:501] detection_eval = 0.895161
-I0511 11:49:27.179124  4597 caffe.cpp:501] detection_eval = 7.5504
-I0511 11:49:27.179127  4597 caffe.cpp:501] detection_eval = 9.35685
-I0511 11:49:27.179129  4597 caffe.cpp:501] detection_eval = 0.035985
-I0511 11:49:27.179131  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179133  4597 caffe.cpp:501] detection_eval = 0.885081
-I0511 11:49:27.179136  4597 caffe.cpp:501] detection_eval = 7.53427
-I0511 11:49:27.179137  4597 caffe.cpp:501] detection_eval = 9.37097
-I0511 11:49:27.179139  4597 caffe.cpp:501] detection_eval = 0.0368773
-I0511 11:49:27.179141  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179143  4597 caffe.cpp:501] detection_eval = 0.885081
-I0511 11:49:27.179145  4597 caffe.cpp:501] detection_eval = 7.54032
-I0511 11:49:27.179147  4597 caffe.cpp:501] detection_eval = 9.36492
-I0511 11:49:27.179150  4597 caffe.cpp:501] detection_eval = 0.0505551
-I0511 11:49:27.179152  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.179154  4597 caffe.cpp:501] detection_eval = 0.875
-I0511 11:49:27.179157  4597 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:49:27.179158  4597 caffe.cpp:501] detection_eval = 9.34476
-I0511 11:49:27.179160  4597 caffe.cpp:501] detection_eval = 0.0519777
-I0511 11:49:27.179162  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.179164  4597 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:49:27.179167  4597 caffe.cpp:501] detection_eval = 7.54839
-I0511 11:49:27.179168  4597 caffe.cpp:501] detection_eval = 9.42742
-I0511 11:49:27.179170  4597 caffe.cpp:501] detection_eval = 0.0499545
-I0511 11:49:27.179173  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.179175  4597 caffe.cpp:501] detection_eval = 0.872984
-I0511 11:49:27.179177  4597 caffe.cpp:501] detection_eval = 7.55242
-I0511 11:49:27.179517  4597 caffe.cpp:501] detection_eval = 9.42944
-I0511 11:49:27.179525  4597 caffe.cpp:501] detection_eval = 0.0417379
-I0511 11:49:27.179528  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.179530  4597 caffe.cpp:501] detection_eval = 0.875
-I0511 11:49:27.179533  4597 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:49:27.179535  4597 caffe.cpp:501] detection_eval = 9.45161
-I0511 11:49:27.179538  4597 caffe.cpp:501] detection_eval = 0.038692
-I0511 11:49:27.179539  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179543  4597 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:49:27.179544  4597 caffe.cpp:501] detection_eval = 7.50403
-I0511 11:49:27.179546  4597 caffe.cpp:501] detection_eval = 9.30847
-I0511 11:49:27.179548  4597 caffe.cpp:501] detection_eval = 0.0404907
-I0511 11:49:27.179550  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.179553  4597 caffe.cpp:501] detection_eval = 0.877016
-I0511 11:49:27.179555  4597 caffe.cpp:501] detection_eval = 7.48992
-I0511 11:49:27.179558  4597 caffe.cpp:501] detection_eval = 9.27419
-I0511 11:49:27.179559  4597 caffe.cpp:501] detection_eval = 0.0372388
-I0511 11:49:27.179561  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179563  4597 caffe.cpp:501] detection_eval = 0.877016
-I0511 11:49:27.179565  4597 caffe.cpp:501] detection_eval = 7.48992
-I0511 11:49:27.179567  4597 caffe.cpp:501] detection_eval = 9.3004
-I0511 11:49:27.179570  4597 caffe.cpp:501] detection_eval = 0.035991
-I0511 11:49:27.179572  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179574  4597 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:49:27.179576  4597 caffe.cpp:501] detection_eval = 7.47379
-I0511 11:49:27.179579  4597 caffe.cpp:501] detection_eval = 9.25605
-I0511 11:49:27.179580  4597 caffe.cpp:501] detection_eval = 0.0347708
-I0511 11:49:27.179584  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.179585  4597 caffe.cpp:501] detection_eval = 0.875
-I0511 11:49:27.179587  4597 caffe.cpp:501] detection_eval = 7.45968
-I0511 11:49:27.179589  4597 caffe.cpp:501] detection_eval = 9.24798
-I0511 11:49:27.179591  4597 caffe.cpp:501] detection_eval = 0.0382323
-I0511 11:49:27.179597  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179600  4597 caffe.cpp:501] detection_eval = 0.872984
-I0511 11:49:27.179602  4597 caffe.cpp:501] detection_eval = 7.45968
-I0511 11:49:27.179605  4597 caffe.cpp:501] detection_eval = 9.33669
-I0511 11:49:27.179606  4597 caffe.cpp:501] detection_eval = 0.0391961
-I0511 11:49:27.179608  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.179611  4597 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:49:27.179613  4597 caffe.cpp:501] detection_eval = 7.44556
-I0511 11:49:27.179615  4597 caffe.cpp:501] detection_eval = 9.33468
-I0511 11:49:27.179617  4597 caffe.cpp:501] detection_eval = 0.0406414
-I0511 11:49:27.179620  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179621  4597 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:49:27.179623  4597 caffe.cpp:501] detection_eval = 7.44556
-I0511 11:49:27.179625  4597 caffe.cpp:501] detection_eval = 9.39919
-I0511 11:49:27.179628  4597 caffe.cpp:501] detection_eval = 0.040219
-I0511 11:49:27.179630  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.179632  4597 caffe.cpp:501] detection_eval = 0.862903
-I0511 11:49:27.179635  4597 caffe.cpp:501] detection_eval = 7.4496
-I0511 11:49:27.179636  4597 caffe.cpp:501] detection_eval = 9.41129
-I0511 11:49:27.179638  4597 caffe.cpp:501] detection_eval = 0.0395767
-I0511 11:49:27.179641  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.179642  4597 caffe.cpp:501] detection_eval = 0.862903
-I0511 11:49:27.179644  4597 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:49:27.179647  4597 caffe.cpp:501] detection_eval = 9.41734
-I0511 11:49:27.179649  4597 caffe.cpp:501] detection_eval = 0.0368327
-I0511 11:49:27.179651  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179653  4597 caffe.cpp:501] detection_eval = 0.872984
-I0511 11:49:27.179656  4597 caffe.cpp:501] detection_eval = 7.45766
-I0511 11:49:27.179657  4597 caffe.cpp:501] detection_eval = 9.41935
-I0511 11:49:27.179659  4597 caffe.cpp:501] detection_eval = 0.0374821
-I0511 11:49:27.179662  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179664  4597 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:49:27.179666  4597 caffe.cpp:501] detection_eval = 7.43952
-I0511 11:49:27.179668  4597 caffe.cpp:501] detection_eval = 9.45766
-I0511 11:49:27.179671  4597 caffe.cpp:501] detection_eval = 0.0341754
-I0511 11:49:27.179672  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179674  4597 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:49:27.179677  4597 caffe.cpp:501] detection_eval = 7.42137
-I0511 11:49:27.179678  4597 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:49:27.179682  4597 caffe.cpp:501] detection_eval = 0.0359759
-I0511 11:49:27.179683  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179685  4597 caffe.cpp:501] detection_eval = 0.862903
-I0511 11:49:27.179687  4597 caffe.cpp:501] detection_eval = 7.4254
-I0511 11:49:27.179689  4597 caffe.cpp:501] detection_eval = 9.48992
-I0511 11:49:27.179692  4597 caffe.cpp:501] detection_eval = 0.0382348
-I0511 11:49:27.179693  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179695  4597 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:49:27.179697  4597 caffe.cpp:501] detection_eval = 7.39315
-I0511 11:49:27.179700  4597 caffe.cpp:501] detection_eval = 9.41129
-I0511 11:49:27.179702  4597 caffe.cpp:501] detection_eval = 0.0360208
-I0511 11:49:27.179704  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.179706  4597 caffe.cpp:501] detection_eval = 0.856855
-I0511 11:49:27.179708  4597 caffe.cpp:501] detection_eval = 7.35685
-I0511 11:49:27.179710  4597 caffe.cpp:501] detection_eval = 9.41734
-I0511 11:49:27.179713  4597 caffe.cpp:501] detection_eval = 0.0350974
-I0511 11:49:27.179714  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.179716  4597 caffe.cpp:501] detection_eval = 0.860887
-I0511 11:49:27.179719  4597 caffe.cpp:501] detection_eval = 7.34073
-I0511 11:49:27.179721  4597 caffe.cpp:501] detection_eval = 9.43347
-I0511 11:49:27.179725  4597 caffe.cpp:501] detection_eval = 0.0383055
-I0511 11:49:27.179728  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.179730  4597 caffe.cpp:501] detection_eval = 0.852823
-I0511 11:49:27.179733  4597 caffe.cpp:501] detection_eval = 7.30645
-I0511 11:49:27.179734  4597 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:49:27.179736  4597 caffe.cpp:501] detection_eval = 0.0407837
-I0511 11:49:27.179738  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179741  4597 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:49:27.179744  4597 caffe.cpp:501] detection_eval = 7.31048
-I0511 11:49:27.179745  4597 caffe.cpp:501] detection_eval = 9.41532
-I0511 11:49:27.179747  4597 caffe.cpp:501] detection_eval = 0.0402762
-I0511 11:49:27.179749  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179751  4597 caffe.cpp:501] detection_eval = 0.850806
-I0511 11:49:27.179754  4597 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:49:27.179755  4597 caffe.cpp:501] detection_eval = 9.42137
-I0511 11:49:27.179757  4597 caffe.cpp:501] detection_eval = 0.0335361
-I0511 11:49:27.179760  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179762  4597 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:49:27.179764  4597 caffe.cpp:501] detection_eval = 7.29637
-I0511 11:49:27.179766  4597 caffe.cpp:501] detection_eval = 9.45161
-I0511 11:49:27.179769  4597 caffe.cpp:501] detection_eval = 0.037912
-I0511 11:49:27.179770  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.179772  4597 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:49:27.179774  4597 caffe.cpp:501] detection_eval = 7.29637
-I0511 11:49:27.179776  4597 caffe.cpp:501] detection_eval = 9.51613
-I0511 11:49:27.179780  4597 caffe.cpp:501] detection_eval = 0.0341082
-I0511 11:49:27.179781  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.180295  4597 caffe.cpp:501] detection_eval = 0.856855
-I0511 11:49:27.180303  4597 caffe.cpp:501] detection_eval = 7.27823
-I0511 11:49:27.180306  4597 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:49:27.180308  4597 caffe.cpp:501] detection_eval = 0.0324871
-I0511 11:49:27.180310  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.180313  4597 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:49:27.180315  4597 caffe.cpp:501] detection_eval = 7.26411
-I0511 11:49:27.180317  4597 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:49:27.180320  4597 caffe.cpp:501] detection_eval = 0.0307059
-I0511 11:49:27.180321  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.180323  4597 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:49:27.180326  4597 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:49:27.180328  4597 caffe.cpp:501] detection_eval = 9.47984
-I0511 11:49:27.180330  4597 caffe.cpp:501] detection_eval = 0.0358411
-I0511 11:49:27.180332  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.180335  4597 caffe.cpp:501] detection_eval = 0.842742
-I0511 11:49:27.180336  4597 caffe.cpp:501] detection_eval = 7.24798
-I0511 11:49:27.180338  4597 caffe.cpp:501] detection_eval = 9.48387
-I0511 11:49:27.180341  4597 caffe.cpp:501] detection_eval = 0.0337295
-I0511 11:49:27.180343  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.180346  4597 caffe.cpp:501] detection_eval = 0.852823
-I0511 11:49:27.180347  4597 caffe.cpp:501] detection_eval = 7.21774
-I0511 11:49:27.180349  4597 caffe.cpp:501] detection_eval = 9.38911
-I0511 11:49:27.180351  4597 caffe.cpp:501] detection_eval = 0.0364457
-I0511 11:49:27.180353  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180356  4597 caffe.cpp:501] detection_eval = 0.840726
-I0511 11:49:27.180357  4597 caffe.cpp:501] detection_eval = 7.21774
-I0511 11:49:27.180359  4597 caffe.cpp:501] detection_eval = 9.42944
-I0511 11:49:27.180362  4597 caffe.cpp:501] detection_eval = 0.0339522
-I0511 11:49:27.180364  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.180366  4597 caffe.cpp:501] detection_eval = 0.844758
-I0511 11:49:27.180368  4597 caffe.cpp:501] detection_eval = 7.21774
-I0511 11:49:27.180371  4597 caffe.cpp:501] detection_eval = 9.46573
-I0511 11:49:27.180377  4597 caffe.cpp:501] detection_eval = 0.0348179
-I0511 11:49:27.180378  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.180380  4597 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:49:27.180382  4597 caffe.cpp:501] detection_eval = 7.21976
-I0511 11:49:27.180385  4597 caffe.cpp:501] detection_eval = 9.48589
-I0511 11:49:27.180387  4597 caffe.cpp:501] detection_eval = 0.0332978
-I0511 11:49:27.180389  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.180392  4597 caffe.cpp:501] detection_eval = 0.842742
-I0511 11:49:27.180393  4597 caffe.cpp:501] detection_eval = 7.20766
-I0511 11:49:27.180395  4597 caffe.cpp:501] detection_eval = 9.41935
-I0511 11:49:27.180397  4597 caffe.cpp:501] detection_eval = 0.0338939
-I0511 11:49:27.180399  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180402  4597 caffe.cpp:501] detection_eval = 0.836694
-I0511 11:49:27.180404  4597 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:49:27.180407  4597 caffe.cpp:501] detection_eval = 9.45565
-I0511 11:49:27.180408  4597 caffe.cpp:501] detection_eval = 0.0335557
-I0511 11:49:27.180410  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.180413  4597 caffe.cpp:501] detection_eval = 0.836694
-I0511 11:49:27.180414  4597 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:49:27.180416  4597 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:49:27.180418  4597 caffe.cpp:501] detection_eval = 0.0340941
-I0511 11:49:27.180421  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.180423  4597 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:49:27.180425  4597 caffe.cpp:501] detection_eval = 7.21169
-I0511 11:49:27.180428  4597 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:49:27.180429  4597 caffe.cpp:501] detection_eval = 0.0310222
-I0511 11:49:27.180431  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180433  4597 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:49:27.180436  4597 caffe.cpp:501] detection_eval = 7.21371
-I0511 11:49:27.180438  4597 caffe.cpp:501] detection_eval = 9.57661
-I0511 11:49:27.180440  4597 caffe.cpp:501] detection_eval = 0.0336776
-I0511 11:49:27.180443  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.180444  4597 caffe.cpp:501] detection_eval = 0.836694
-I0511 11:49:27.180446  4597 caffe.cpp:501] detection_eval = 7.21371
-I0511 11:49:27.180449  4597 caffe.cpp:501] detection_eval = 9.64919
-I0511 11:49:27.180450  4597 caffe.cpp:501] detection_eval = 0.0354826
-I0511 11:49:27.180454  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180455  4597 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:49:27.180457  4597 caffe.cpp:501] detection_eval = 7.21573
-I0511 11:49:27.180459  4597 caffe.cpp:501] detection_eval = 9.68952
-I0511 11:49:27.180461  4597 caffe.cpp:501] detection_eval = 0.0353965
-I0511 11:49:27.180464  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.180465  4597 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:49:27.180467  4597 caffe.cpp:501] detection_eval = 7.20161
-I0511 11:49:27.180470  4597 caffe.cpp:501] detection_eval = 9.66734
-I0511 11:49:27.180472  4597 caffe.cpp:501] detection_eval = 0.0352699
-I0511 11:49:27.180474  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.180476  4597 caffe.cpp:501] detection_eval = 0.830645
-I0511 11:49:27.180479  4597 caffe.cpp:501] detection_eval = 7.20161
-I0511 11:49:27.180480  4597 caffe.cpp:501] detection_eval = 9.7621
-I0511 11:49:27.180482  4597 caffe.cpp:501] detection_eval = 0.0368593
-I0511 11:49:27.180485  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.180486  4597 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:49:27.180490  4597 caffe.cpp:501] detection_eval = 7.16734
-I0511 11:49:27.180491  4597 caffe.cpp:501] detection_eval = 9.71371
-I0511 11:49:27.180493  4597 caffe.cpp:501] detection_eval = 0.0397446
-I0511 11:49:27.180495  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.180497  4597 caffe.cpp:501] detection_eval = 0.826613
-I0511 11:49:27.180500  4597 caffe.cpp:501] detection_eval = 7.15121
-I0511 11:49:27.180505  4597 caffe.cpp:501] detection_eval = 9.70565
-I0511 11:49:27.180506  4597 caffe.cpp:501] detection_eval = 0.0369758
-I0511 11:49:27.180508  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.180511  4597 caffe.cpp:501] detection_eval = 0.828629
-I0511 11:49:27.180513  4597 caffe.cpp:501] detection_eval = 7.15121
-I0511 11:49:27.180516  4597 caffe.cpp:501] detection_eval = 9.78629
-I0511 11:49:27.180517  4597 caffe.cpp:501] detection_eval = 0.0347746
-I0511 11:49:27.180519  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.180521  4597 caffe.cpp:501] detection_eval = 0.830645
-I0511 11:49:27.180541  4597 caffe.cpp:501] detection_eval = 7.11895
-I0511 11:49:27.180544  4597 caffe.cpp:501] detection_eval = 9.73387
-I0511 11:49:27.180547  4597 caffe.cpp:501] detection_eval = 0.0392505
-I0511 11:49:27.180550  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.180552  4597 caffe.cpp:501] detection_eval = 0.814516
-I0511 11:49:27.180554  4597 caffe.cpp:501] detection_eval = 7.10282
-I0511 11:49:27.180557  4597 caffe.cpp:501] detection_eval = 9.72379
-I0511 11:49:27.180558  4597 caffe.cpp:501] detection_eval = 0.0338769
-I0511 11:49:27.180560  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.180562  4597 caffe.cpp:501] detection_eval = 0.828629
-I0511 11:49:27.180564  4597 caffe.cpp:501] detection_eval = 7.10484
-I0511 11:49:27.180567  4597 caffe.cpp:501] detection_eval = 9.7621
-I0511 11:49:27.180569  4597 caffe.cpp:501] detection_eval = 0.0340421
-I0511 11:49:27.180572  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180573  4597 caffe.cpp:501] detection_eval = 0.826613
-I0511 11:49:27.180575  4597 caffe.cpp:501] detection_eval = 7.10685
-I0511 11:49:27.180577  4597 caffe.cpp:501] detection_eval = 9.82056
-I0511 11:49:27.181082  4597 caffe.cpp:501] detection_eval = 0.0402648
-I0511 11:49:27.181089  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181092  4597 caffe.cpp:501] detection_eval = 0.822581
-I0511 11:49:27.181094  4597 caffe.cpp:501] detection_eval = 7.1129
-I0511 11:49:27.181097  4597 caffe.cpp:501] detection_eval = 9.78226
-I0511 11:49:27.181099  4597 caffe.cpp:501] detection_eval = 0.0347552
-I0511 11:49:27.181102  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.181103  4597 caffe.cpp:501] detection_eval = 0.824597
-I0511 11:49:27.181105  4597 caffe.cpp:501] detection_eval = 7.06452
-I0511 11:49:27.181108  4597 caffe.cpp:501] detection_eval = 9.68145
-I0511 11:49:27.181110  4597 caffe.cpp:501] detection_eval = 0.0383627
-I0511 11:49:27.181113  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.181114  4597 caffe.cpp:501] detection_eval = 0.810484
-I0511 11:49:27.181116  4597 caffe.cpp:501] detection_eval = 7.06452
-I0511 11:49:27.181118  4597 caffe.cpp:501] detection_eval = 9.7621
-I0511 11:49:27.181120  4597 caffe.cpp:501] detection_eval = 0.035053
-I0511 11:49:27.181123  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181125  4597 caffe.cpp:501] detection_eval = 0.814516
-I0511 11:49:27.181128  4597 caffe.cpp:501] detection_eval = 7.03024
-I0511 11:49:27.181129  4597 caffe.cpp:501] detection_eval = 9.75
-I0511 11:49:27.181131  4597 caffe.cpp:501] detection_eval = 0.0352481
-I0511 11:49:27.181133  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.181135  4597 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:49:27.181138  4597 caffe.cpp:501] detection_eval = 7.03226
-I0511 11:49:27.181140  4597 caffe.cpp:501] detection_eval = 9.8004
-I0511 11:49:27.181143  4597 caffe.cpp:501] detection_eval = 0.0372214
-I0511 11:49:27.181144  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181146  4597 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:49:27.181149  4597 caffe.cpp:501] detection_eval = 7.02218
-I0511 11:49:27.181150  4597 caffe.cpp:501] detection_eval = 9.69758
-I0511 11:49:27.181154  4597 caffe.cpp:501] detection_eval = 0.03344
-I0511 11:49:27.181155  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181157  4597 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:49:27.181159  4597 caffe.cpp:501] detection_eval = 7.02419
-I0511 11:49:27.181165  4597 caffe.cpp:501] detection_eval = 9.70968
-I0511 11:49:27.181169  4597 caffe.cpp:501] detection_eval = 0.0327785
-I0511 11:49:27.181170  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181172  4597 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:49:27.181174  4597 caffe.cpp:501] detection_eval = 7.01008
-I0511 11:49:27.181176  4597 caffe.cpp:501] detection_eval = 9.68145
-I0511 11:49:27.181179  4597 caffe.cpp:501] detection_eval = 0.0364491
-I0511 11:49:27.181180  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181183  4597 caffe.cpp:501] detection_eval = 0.804435
-I0511 11:49:27.181185  4597 caffe.cpp:501] detection_eval = 6.99597
-I0511 11:49:27.181187  4597 caffe.cpp:501] detection_eval = 9.61694
-I0511 11:49:27.181190  4597 caffe.cpp:501] detection_eval = 0.0331811
-I0511 11:49:27.181191  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.181193  4597 caffe.cpp:501] detection_eval = 0.804435
-I0511 11:49:27.181195  4597 caffe.cpp:501] detection_eval = 6.97782
-I0511 11:49:27.181197  4597 caffe.cpp:501] detection_eval = 9.68548
-I0511 11:49:27.181200  4597 caffe.cpp:501] detection_eval = 0.0387094
-I0511 11:49:27.181202  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.181205  4597 caffe.cpp:501] detection_eval = 0.798387
-I0511 11:49:27.181206  4597 caffe.cpp:501] detection_eval = 6.97984
-I0511 11:49:27.181208  4597 caffe.cpp:501] detection_eval = 9.72177
-I0511 11:49:27.181210  4597 caffe.cpp:501] detection_eval = 0.0393089
-I0511 11:49:27.181212  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181215  4597 caffe.cpp:501] detection_eval = 0.800403
-I0511 11:49:27.181216  4597 caffe.cpp:501] detection_eval = 6.98589
-I0511 11:49:27.181219  4597 caffe.cpp:501] detection_eval = 9.6754
-I0511 11:49:27.181221  4597 caffe.cpp:501] detection_eval = 0.0372463
-I0511 11:49:27.181223  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.181226  4597 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:49:27.181227  4597 caffe.cpp:501] detection_eval = 6.96774
-I0511 11:49:27.181229  4597 caffe.cpp:501] detection_eval = 9.70363
-I0511 11:49:27.181231  4597 caffe.cpp:501] detection_eval = 0.0344107
-I0511 11:49:27.181234  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181236  4597 caffe.cpp:501] detection_eval = 0.806452
-I0511 11:49:27.181238  4597 caffe.cpp:501] detection_eval = 6.97379
-I0511 11:49:27.181241  4597 caffe.cpp:501] detection_eval = 9.65726
-I0511 11:49:27.181242  4597 caffe.cpp:501] detection_eval = 0.0359498
-I0511 11:49:27.181244  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181246  4597 caffe.cpp:501] detection_eval = 0.800403
-I0511 11:49:27.181249  4597 caffe.cpp:501] detection_eval = 6.95766
-I0511 11:49:27.181252  4597 caffe.cpp:501] detection_eval = 9.67137
-I0511 11:49:27.181253  4597 caffe.cpp:501] detection_eval = 0.0368076
-I0511 11:49:27.181255  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.181257  4597 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:49:27.181259  4597 caffe.cpp:501] detection_eval = 6.92339
-I0511 11:49:27.181262  4597 caffe.cpp:501] detection_eval = 9.62097
-I0511 11:49:27.181263  4597 caffe.cpp:501] detection_eval = 0.0362358
-I0511 11:49:27.181267  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181268  4597 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:49:27.181270  4597 caffe.cpp:501] detection_eval = 6.92742
-I0511 11:49:27.181272  4597 caffe.cpp:501] detection_eval = 9.61895
-I0511 11:49:27.181274  4597 caffe.cpp:501] detection_eval = 0.0322296
-I0511 11:49:27.181277  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181278  4597 caffe.cpp:501] detection_eval = 0.798387
-I0511 11:49:27.181280  4597 caffe.cpp:501] detection_eval = 6.92742
-I0511 11:49:27.181282  4597 caffe.cpp:501] detection_eval = 9.71573
-I0511 11:49:27.181284  4597 caffe.cpp:501] detection_eval = 0.0376627
-I0511 11:49:27.181288  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.181289  4597 caffe.cpp:501] detection_eval = 0.78629
-I0511 11:49:27.181293  4597 caffe.cpp:501] detection_eval = 6.89315
-I0511 11:49:27.181296  4597 caffe.cpp:501] detection_eval = 9.68548
-I0511 11:49:27.181298  4597 caffe.cpp:501] detection_eval = 0.0382296
-I0511 11:49:27.181300  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181303  4597 caffe.cpp:501] detection_eval = 0.788306
-I0511 11:49:27.181304  4597 caffe.cpp:501] detection_eval = 6.87903
-I0511 11:49:27.181306  4597 caffe.cpp:501] detection_eval = 9.63306
-I0511 11:49:27.181308  4597 caffe.cpp:501] detection_eval = 0.0326784
-I0511 11:49:27.181311  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181313  4597 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:49:27.181315  4597 caffe.cpp:501] detection_eval = 6.87903
-I0511 11:49:27.181318  4597 caffe.cpp:501] detection_eval = 9.71169
-I0511 11:49:27.181319  4597 caffe.cpp:501] detection_eval = 0.0341897
-I0511 11:49:27.181321  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.181324  4597 caffe.cpp:501] detection_eval = 0.790323
-I0511 11:49:27.181325  4597 caffe.cpp:501] detection_eval = 6.88306
-I0511 11:49:27.181327  4597 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:49:27.181330  4597 caffe.cpp:501] detection_eval = 0.031211
-I0511 11:49:27.181332  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181334  4597 caffe.cpp:501] detection_eval = 0.794355
-I0511 11:49:27.181336  4597 caffe.cpp:501] detection_eval = 6.88508
-I0511 11:49:27.181339  4597 caffe.cpp:501] detection_eval = 9.75605
-I0511 11:49:27.181340  4597 caffe.cpp:501] detection_eval = 0.0357487
-I0511 11:49:27.181342  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181344  4597 caffe.cpp:501] detection_eval = 0.78629
-I0511 11:49:27.181859  4597 caffe.cpp:501] detection_eval = 6.84879
-I0511 11:49:27.181867  4597 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:49:27.181870  4597 caffe.cpp:501] detection_eval = 0.0373732
-I0511 11:49:27.181874  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181875  4597 caffe.cpp:501] detection_eval = 0.782258
-I0511 11:49:27.181877  4597 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:49:27.181879  4597 caffe.cpp:501] detection_eval = 9.63105
-I0511 11:49:27.181882  4597 caffe.cpp:501] detection_eval = 0.0330568
-I0511 11:49:27.181885  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181886  4597 caffe.cpp:501] detection_eval = 0.782258
-I0511 11:49:27.181888  4597 caffe.cpp:501] detection_eval = 6.80242
-I0511 11:49:27.181890  4597 caffe.cpp:501] detection_eval = 9.66532
-I0511 11:49:27.181892  4597 caffe.cpp:501] detection_eval = 0.0361717
-I0511 11:49:27.181895  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181897  4597 caffe.cpp:501] detection_eval = 0.774194
-I0511 11:49:27.181900  4597 caffe.cpp:501] detection_eval = 6.80444
-I0511 11:49:27.181901  4597 caffe.cpp:501] detection_eval = 9.67339
-I0511 11:49:27.181903  4597 caffe.cpp:501] detection_eval = 0.0313601
-I0511 11:49:27.181905  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181908  4597 caffe.cpp:501] detection_eval = 0.788306
-I0511 11:49:27.181910  4597 caffe.cpp:501] detection_eval = 6.75
-I0511 11:49:27.181912  4597 caffe.cpp:501] detection_eval = 9.59476
-I0511 11:49:27.181915  4597 caffe.cpp:501] detection_eval = 0.0277536
-I0511 11:49:27.181916  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181918  4597 caffe.cpp:501] detection_eval = 0.778226
-I0511 11:49:27.181921  4597 caffe.cpp:501] detection_eval = 6.73387
-I0511 11:49:27.181923  4597 caffe.cpp:501] detection_eval = 9.59677
-I0511 11:49:27.181926  4597 caffe.cpp:501] detection_eval = 0.0289066
-I0511 11:49:27.181927  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181929  4597 caffe.cpp:501] detection_eval = 0.778226
-I0511 11:49:27.181931  4597 caffe.cpp:501] detection_eval = 6.74194
-I0511 11:49:27.181933  4597 caffe.cpp:501] detection_eval = 9.51815
-I0511 11:49:27.181936  4597 caffe.cpp:501] detection_eval = 0.0267913
-I0511 11:49:27.181938  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181943  4597 caffe.cpp:501] detection_eval = 0.778226
-I0511 11:49:27.181946  4597 caffe.cpp:501] detection_eval = 6.74194
-I0511 11:49:27.181948  4597 caffe.cpp:501] detection_eval = 9.57056
-I0511 11:49:27.181951  4597 caffe.cpp:501] detection_eval = 0.0279466
-I0511 11:49:27.181952  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181954  4597 caffe.cpp:501] detection_eval = 0.774194
-I0511 11:49:27.181957  4597 caffe.cpp:501] detection_eval = 6.72581
-I0511 11:49:27.181959  4597 caffe.cpp:501] detection_eval = 9.53831
-I0511 11:49:27.181962  4597 caffe.cpp:501] detection_eval = 0.0318604
-I0511 11:49:27.181963  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181965  4597 caffe.cpp:501] detection_eval = 0.772177
-I0511 11:49:27.181967  4597 caffe.cpp:501] detection_eval = 6.72782
-I0511 11:49:27.181969  4597 caffe.cpp:501] detection_eval = 9.60081
-I0511 11:49:27.181972  4597 caffe.cpp:501] detection_eval = 0.0274806
-I0511 11:49:27.181973  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181977  4597 caffe.cpp:501] detection_eval = 0.778226
-I0511 11:49:27.181978  4597 caffe.cpp:501] detection_eval = 6.69556
-I0511 11:49:27.181980  4597 caffe.cpp:501] detection_eval = 9.50605
-I0511 11:49:27.181982  4597 caffe.cpp:501] detection_eval = 0.0277608
-I0511 11:49:27.181984  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181987  4597 caffe.cpp:501] detection_eval = 0.774194
-I0511 11:49:27.181988  4597 caffe.cpp:501] detection_eval = 6.70161
-I0511 11:49:27.181991  4597 caffe.cpp:501] detection_eval = 9.48589
-I0511 11:49:27.181993  4597 caffe.cpp:501] detection_eval = 0.0303468
-I0511 11:49:27.181995  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181998  4597 caffe.cpp:501] detection_eval = 0.772177
-I0511 11:49:27.181999  4597 caffe.cpp:501] detection_eval = 6.70161
-I0511 11:49:27.182001  4597 caffe.cpp:501] detection_eval = 9.55444
-I0511 11:49:27.182004  4597 caffe.cpp:501] detection_eval = 0.0327595
-I0511 11:49:27.182006  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182008  4597 caffe.cpp:501] detection_eval = 0.768145
-I0511 11:49:27.182010  4597 caffe.cpp:501] detection_eval = 6.70766
-I0511 11:49:27.182013  4597 caffe.cpp:501] detection_eval = 9.51815
-I0511 11:49:27.182014  4597 caffe.cpp:501] detection_eval = 0.029785
-I0511 11:49:27.182016  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182018  4597 caffe.cpp:501] detection_eval = 0.774194
-I0511 11:49:27.182021  4597 caffe.cpp:501] detection_eval = 6.69556
-I0511 11:49:27.182024  4597 caffe.cpp:501] detection_eval = 9.44758
-I0511 11:49:27.182025  4597 caffe.cpp:501] detection_eval = 0.0328393
-I0511 11:49:27.182027  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182029  4597 caffe.cpp:501] detection_eval = 0.762097
-I0511 11:49:27.182031  4597 caffe.cpp:501] detection_eval = 6.67944
-I0511 11:49:27.182034  4597 caffe.cpp:501] detection_eval = 9.43347
-I0511 11:49:27.182035  4597 caffe.cpp:501] detection_eval = 0.0325699
-I0511 11:49:27.182037  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182040  4597 caffe.cpp:501] detection_eval = 0.764113
-I0511 11:49:27.182042  4597 caffe.cpp:501] detection_eval = 6.64315
-I0511 11:49:27.182044  4597 caffe.cpp:501] detection_eval = 9.40927
-I0511 11:49:27.182046  4597 caffe.cpp:501] detection_eval = 0.0298599
-I0511 11:49:27.182049  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182050  4597 caffe.cpp:501] detection_eval = 0.762097
-I0511 11:49:27.182052  4597 caffe.cpp:501] detection_eval = 6.64315
-I0511 11:49:27.182054  4597 caffe.cpp:501] detection_eval = 9.49597
-I0511 11:49:27.182057  4597 caffe.cpp:501] detection_eval = 0.0361235
-I0511 11:49:27.182060  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182061  4597 caffe.cpp:501] detection_eval = 0.756048
-I0511 11:49:27.182063  4597 caffe.cpp:501] detection_eval = 6.61089
-I0511 11:49:27.182065  4597 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:49:27.182067  4597 caffe.cpp:501] detection_eval = 0.034698
-I0511 11:49:27.182070  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182075  4597 caffe.cpp:501] detection_eval = 0.756048
-I0511 11:49:27.182077  4597 caffe.cpp:501] detection_eval = 6.61089
-I0511 11:49:27.182080  4597 caffe.cpp:501] detection_eval = 9.47984
-I0511 11:49:27.182081  4597 caffe.cpp:501] detection_eval = 0.0287569
-I0511 11:49:27.182083  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182085  4597 caffe.cpp:501] detection_eval = 0.762097
-I0511 11:49:27.182087  4597 caffe.cpp:501] detection_eval = 6.59476
-I0511 11:49:27.182090  4597 caffe.cpp:501] detection_eval = 9.47984
-I0511 11:49:27.182092  4597 caffe.cpp:501] detection_eval = 0.0304031
-I0511 11:49:27.182094  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182096  4597 caffe.cpp:501] detection_eval = 0.758065
-I0511 11:49:27.182098  4597 caffe.cpp:501] detection_eval = 6.58468
-I0511 11:49:27.182101  4597 caffe.cpp:501] detection_eval = 9.3629
-I0511 11:49:27.182102  4597 caffe.cpp:501] detection_eval = 0.0284584
-I0511 11:49:27.182104  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182107  4597 caffe.cpp:501] detection_eval = 0.754032
-I0511 11:49:27.182109  4597 caffe.cpp:501] detection_eval = 6.56855
-I0511 11:49:27.182111  4597 caffe.cpp:501] detection_eval = 9.33266
-I0511 11:49:27.182113  4597 caffe.cpp:501] detection_eval = 0.0278271
-I0511 11:49:27.182116  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.182117  4597 caffe.cpp:501] detection_eval = 0.756048
-I0511 11:49:27.182119  4597 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:49:27.182122  4597 caffe.cpp:501] detection_eval = 9.34677
-I0511 11:49:27.182124  4597 caffe.cpp:501] detection_eval = 0.0331575
-I0511 11:49:27.182631  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182638  4597 caffe.cpp:501] detection_eval = 0.745968
-I0511 11:49:27.182641  4597 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:49:27.182643  4597 caffe.cpp:501] detection_eval = 9.26613
-I0511 11:49:27.182646  4597 caffe.cpp:501] detection_eval = 0.0300592
-I0511 11:49:27.182648  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182651  4597 caffe.cpp:501] detection_eval = 0.741935
-I0511 11:49:27.182652  4597 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:49:27.182654  4597 caffe.cpp:501] detection_eval = 9.30242
-I0511 11:49:27.182657  4597 caffe.cpp:501] detection_eval = 0.0260824
-I0511 11:49:27.182659  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.182662  4597 caffe.cpp:501] detection_eval = 0.752016
-I0511 11:49:27.182663  4597 caffe.cpp:501] detection_eval = 6.50202
-I0511 11:49:27.182665  4597 caffe.cpp:501] detection_eval = 9.31653
-I0511 11:49:27.182667  4597 caffe.cpp:501] detection_eval = 0.0286702
-I0511 11:49:27.182670  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182672  4597 caffe.cpp:501] detection_eval = 0.741935
-I0511 11:49:27.182674  4597 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:49:27.182677  4597 caffe.cpp:501] detection_eval = 9.21976
-I0511 11:49:27.182678  4597 caffe.cpp:501] detection_eval = 0.0263043
-I0511 11:49:27.182680  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.182683  4597 caffe.cpp:501] detection_eval = 0.741935
-I0511 11:49:27.182685  4597 caffe.cpp:501] detection_eval = 6.45161
-I0511 11:49:27.182687  4597 caffe.cpp:501] detection_eval = 9.24194
-I0511 11:49:27.182689  4597 caffe.cpp:501] detection_eval = 0.0275095
-I0511 11:49:27.182691  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182693  4597 caffe.cpp:501] detection_eval = 0.737903
-I0511 11:49:27.182695  4597 caffe.cpp:501] detection_eval = 6.43347
-I0511 11:49:27.182698  4597 caffe.cpp:501] detection_eval = 9.30847
-I0511 11:49:27.182700  4597 caffe.cpp:501] detection_eval = 0.03099
-I0511 11:49:27.182703  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182704  4597 caffe.cpp:501] detection_eval = 0.731855
-I0511 11:49:27.182706  4597 caffe.cpp:501] detection_eval = 6.4375
-I0511 11:49:27.182708  4597 caffe.cpp:501] detection_eval = 9.27419
-I0511 11:49:27.182710  4597 caffe.cpp:501] detection_eval = 0.0284238
-I0511 11:49:27.182716  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182719  4597 caffe.cpp:501] detection_eval = 0.737903
-I0511 11:49:27.182721  4597 caffe.cpp:501] detection_eval = 6.42339
-I0511 11:49:27.182723  4597 caffe.cpp:501] detection_eval = 9.20363
-I0511 11:49:27.182725  4597 caffe.cpp:501] detection_eval = 0.0305747
-I0511 11:49:27.182727  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182730  4597 caffe.cpp:501] detection_eval = 0.733871
-I0511 11:49:27.182732  4597 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:49:27.182734  4597 caffe.cpp:501] detection_eval = 9.18952
-I0511 11:49:27.182736  4597 caffe.cpp:501] detection_eval = 0.0271628
-I0511 11:49:27.182739  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182740  4597 caffe.cpp:501] detection_eval = 0.733871
-I0511 11:49:27.182742  4597 caffe.cpp:501] detection_eval = 6.36895
-I0511 11:49:27.182745  4597 caffe.cpp:501] detection_eval = 9.20968
-I0511 11:49:27.182747  4597 caffe.cpp:501] detection_eval = 0.0313459
-I0511 11:49:27.182749  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182751  4597 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:49:27.182754  4597 caffe.cpp:501] detection_eval = 6.35887
-I0511 11:49:27.182755  4597 caffe.cpp:501] detection_eval = 9.11089
-I0511 11:49:27.182757  4597 caffe.cpp:501] detection_eval = 0.0295643
-I0511 11:49:27.182760  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182761  4597 caffe.cpp:501] detection_eval = 0.725806
-I0511 11:49:27.182765  4597 caffe.cpp:501] detection_eval = 6.34073
-I0511 11:49:27.182766  4597 caffe.cpp:501] detection_eval = 9.14113
-I0511 11:49:27.182768  4597 caffe.cpp:501] detection_eval = 0.0305493
-I0511 11:49:27.182770  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182772  4597 caffe.cpp:501] detection_eval = 0.725806
-I0511 11:49:27.182775  4597 caffe.cpp:501] detection_eval = 6.34476
-I0511 11:49:27.182777  4597 caffe.cpp:501] detection_eval = 9.10484
-I0511 11:49:27.182780  4597 caffe.cpp:501] detection_eval = 0.0297302
-I0511 11:49:27.182781  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182783  4597 caffe.cpp:501] detection_eval = 0.725806
-I0511 11:49:27.182785  4597 caffe.cpp:501] detection_eval = 6.32863
-I0511 11:49:27.182787  4597 caffe.cpp:501] detection_eval = 9.08468
-I0511 11:49:27.182790  4597 caffe.cpp:501] detection_eval = 0.0293979
-I0511 11:49:27.182791  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182795  4597 caffe.cpp:501] detection_eval = 0.721774
-I0511 11:49:27.182796  4597 caffe.cpp:501] detection_eval = 6.31452
-I0511 11:49:27.182798  4597 caffe.cpp:501] detection_eval = 9.04435
-I0511 11:49:27.182801  4597 caffe.cpp:501] detection_eval = 0.0291608
-I0511 11:49:27.182802  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182804  4597 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:49:27.182806  4597 caffe.cpp:501] detection_eval = 6.31653
-I0511 11:49:27.182808  4597 caffe.cpp:501] detection_eval = 9.08669
-I0511 11:49:27.182811  4597 caffe.cpp:501] detection_eval = 0.0270491
-I0511 11:49:27.182813  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.182816  4597 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:49:27.182817  4597 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:49:27.182819  4597 caffe.cpp:501] detection_eval = 9.03831
-I0511 11:49:27.182821  4597 caffe.cpp:501] detection_eval = 0.0289935
-I0511 11:49:27.182823  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182826  4597 caffe.cpp:501] detection_eval = 0.715726
-I0511 11:49:27.182828  4597 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:49:27.182831  4597 caffe.cpp:501] detection_eval = 9.09476
-I0511 11:49:27.182832  4597 caffe.cpp:501] detection_eval = 0.0290409
-I0511 11:49:27.182834  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182837  4597 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:49:27.182838  4597 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:49:27.182840  4597 caffe.cpp:501] detection_eval = 9.15524
-I0511 11:49:27.182845  4597 caffe.cpp:501] detection_eval = 0.030946
-I0511 11:49:27.182848  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182850  4597 caffe.cpp:501] detection_eval = 0.71371
-I0511 11:49:27.182852  4597 caffe.cpp:501] detection_eval = 6.28629
-I0511 11:49:27.182854  4597 caffe.cpp:501] detection_eval = 9.14516
-I0511 11:49:27.182857  4597 caffe.cpp:501] detection_eval = 0.0287102
-I0511 11:49:27.182858  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182862  4597 caffe.cpp:501] detection_eval = 0.715726
-I0511 11:49:27.182863  4597 caffe.cpp:501] detection_eval = 6.29032
-I0511 11:49:27.182865  4597 caffe.cpp:501] detection_eval = 9.13911
-I0511 11:49:27.182868  4597 caffe.cpp:501] detection_eval = 0.0277487
-I0511 11:49:27.182869  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182871  4597 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:49:27.182873  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.182875  4597 caffe.cpp:501] detection_eval = 9.1875
-I0511 11:49:27.182878  4597 caffe.cpp:501] detection_eval = 0.0340422
-I0511 11:49:27.182880  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182883  4597 caffe.cpp:501] detection_eval = 0.705645
-I0511 11:49:27.182884  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.182886  4597 caffe.cpp:501] detection_eval = 9.24194
-I0511 11:49:27.182888  4597 caffe.cpp:501] detection_eval = 0.0291747
-I0511 11:49:27.182890  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182893  4597 caffe.cpp:501] detection_eval = 0.715726
-I0511 11:49:27.182895  4597 caffe.cpp:501] detection_eval = 6.27621
-I0511 11:49:27.183416  4597 caffe.cpp:501] detection_eval = 9.26411
-I0511 11:49:27.183423  4597 caffe.cpp:501] detection_eval = 0.0270842
-I0511 11:49:27.183426  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183429  4597 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:49:27.183431  4597 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:49:27.183434  4597 caffe.cpp:501] detection_eval = 9.2621
-I0511 11:49:27.183435  4597 caffe.cpp:501] detection_eval = 0.0255036
-I0511 11:49:27.183439  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.183440  4597 caffe.cpp:501] detection_eval = 0.71371
-I0511 11:49:27.183442  4597 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:49:27.183444  4597 caffe.cpp:501] detection_eval = 9.24597
-I0511 11:49:27.183446  4597 caffe.cpp:501] detection_eval = 0.0281904
-I0511 11:49:27.183449  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183451  4597 caffe.cpp:501] detection_eval = 0.707661
-I0511 11:49:27.183454  4597 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:49:27.183455  4597 caffe.cpp:501] detection_eval = 9.28226
-I0511 11:49:27.183457  4597 caffe.cpp:501] detection_eval = 0.0245895
-I0511 11:49:27.183459  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183461  4597 caffe.cpp:501] detection_eval = 0.71371
-I0511 11:49:27.183465  4597 caffe.cpp:501] detection_eval = 6.19153
-I0511 11:49:27.183466  4597 caffe.cpp:501] detection_eval = 9.20766
-I0511 11:49:27.183468  4597 caffe.cpp:501] detection_eval = 0.0313816
-I0511 11:49:27.183470  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.183472  4597 caffe.cpp:501] detection_eval = 0.697581
-I0511 11:49:27.183475  4597 caffe.cpp:501] detection_eval = 6.1754
-I0511 11:49:27.183476  4597 caffe.cpp:501] detection_eval = 9.18145
-I0511 11:49:27.183480  4597 caffe.cpp:501] detection_eval = 0.0300773
-I0511 11:49:27.183481  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183483  4597 caffe.cpp:501] detection_eval = 0.701613
-I0511 11:49:27.183485  4597 caffe.cpp:501] detection_eval = 6.17944
-I0511 11:49:27.183487  4597 caffe.cpp:501] detection_eval = 9.19758
-I0511 11:49:27.183490  4597 caffe.cpp:501] detection_eval = 0.0237437
-I0511 11:49:27.183491  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183493  4597 caffe.cpp:501] detection_eval = 0.707661
-I0511 11:49:27.183496  4597 caffe.cpp:501] detection_eval = 6.17944
-I0511 11:49:27.183498  4597 caffe.cpp:501] detection_eval = 9.27823
-I0511 11:49:27.183503  4597 caffe.cpp:501] detection_eval = 0.0252186
-I0511 11:49:27.183506  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183508  4597 caffe.cpp:501] detection_eval = 0.707661
-I0511 11:49:27.183511  4597 caffe.cpp:501] detection_eval = 6.14516
-I0511 11:49:27.183512  4597 caffe.cpp:501] detection_eval = 9.30645
-I0511 11:49:27.183514  4597 caffe.cpp:501] detection_eval = 0.0272303
-I0511 11:49:27.183517  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183519  4597 caffe.cpp:501] detection_eval = 0.693548
-I0511 11:49:27.183521  4597 caffe.cpp:501] detection_eval = 6.12903
-I0511 11:49:27.183523  4597 caffe.cpp:501] detection_eval = 9.36895
-I0511 11:49:27.183526  4597 caffe.cpp:501] detection_eval = 0.0286934
-I0511 11:49:27.183527  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183531  4597 caffe.cpp:501] detection_eval = 0.691532
-I0511 11:49:27.183532  4597 caffe.cpp:501] detection_eval = 6.07661
-I0511 11:49:27.183534  4597 caffe.cpp:501] detection_eval = 9.36089
-I0511 11:49:27.183537  4597 caffe.cpp:501] detection_eval = 0.0270058
-I0511 11:49:27.183538  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.183540  4597 caffe.cpp:501] detection_eval = 0.683468
-I0511 11:49:27.183542  4597 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:49:27.183544  4597 caffe.cpp:501] detection_eval = 6.17944
-I0511 11:49:27.183547  4597 caffe.cpp:501] detection_eval = 0.0486907
-I0511 11:49:27.183549  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.183552  4597 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:49:27.183553  4597 caffe.cpp:501] detection_eval = 6.16935
-I0511 11:49:27.183555  4597 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:49:27.183557  4597 caffe.cpp:501] detection_eval = 0.0444843
-I0511 11:49:27.183559  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.183562  4597 caffe.cpp:501] detection_eval = 0.663306
-I0511 11:49:27.183564  4597 caffe.cpp:501] detection_eval = 6.15121
-I0511 11:49:27.183567  4597 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:49:27.183568  4597 caffe.cpp:501] detection_eval = 0.0409148
-I0511 11:49:27.183570  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.183573  4597 caffe.cpp:501] detection_eval = 0.663306
-I0511 11:49:27.183574  4597 caffe.cpp:501] detection_eval = 6.11492
-I0511 11:49:27.183576  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.183579  4597 caffe.cpp:501] detection_eval = 0.0335623
-I0511 11:49:27.183581  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.183583  4597 caffe.cpp:501] detection_eval = 0.665323
-I0511 11:49:27.183585  4597 caffe.cpp:501] detection_eval = 6.07863
-I0511 11:49:27.183588  4597 caffe.cpp:501] detection_eval = 6.24194
-I0511 11:49:27.183589  4597 caffe.cpp:501] detection_eval = 0.0342348
-I0511 11:49:27.183591  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.183593  4597 caffe.cpp:501] detection_eval = 0.66129
-I0511 11:49:27.183596  4597 caffe.cpp:501] detection_eval = 6.07863
-I0511 11:49:27.183598  4597 caffe.cpp:501] detection_eval = 6.31048
-I0511 11:49:27.183600  4597 caffe.cpp:501] detection_eval = 0.0318322
-I0511 11:49:27.183603  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.183604  4597 caffe.cpp:501] detection_eval = 0.66129
-I0511 11:49:27.183606  4597 caffe.cpp:501] detection_eval = 6.06048
-I0511 11:49:27.183609  4597 caffe.cpp:501] detection_eval = 6.30444
-I0511 11:49:27.183610  4597 caffe.cpp:501] detection_eval = 0.0259541
-I0511 11:49:27.183612  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.183615  4597 caffe.cpp:501] detection_eval = 0.667339
-I0511 11:49:27.183617  4597 caffe.cpp:501] detection_eval = 6.00605
-I0511 11:49:27.183619  4597 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:49:27.183621  4597 caffe.cpp:501] detection_eval = 0.031006
-I0511 11:49:27.183624  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.183625  4597 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:49:27.183627  4597 caffe.cpp:501] detection_eval = 5.93347
-I0511 11:49:27.183632  4597 caffe.cpp:501] detection_eval = 6.19355
-I0511 11:49:27.183634  4597 caffe.cpp:501] detection_eval = 0.0311044
-I0511 11:49:27.183637  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.183640  4597 caffe.cpp:501] detection_eval = 0.643145
-I0511 11:49:27.183641  4597 caffe.cpp:501] detection_eval = 5.89718
-I0511 11:49:27.183643  4597 caffe.cpp:501] detection_eval = 6.14919
-I0511 11:49:27.183645  4597 caffe.cpp:501] detection_eval = 0.0279176
-I0511 11:49:27.183647  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183650  4597 caffe.cpp:501] detection_eval = 0.647177
-I0511 11:49:27.183652  4597 caffe.cpp:501] detection_eval = 5.89718
-I0511 11:49:27.183655  4597 caffe.cpp:501] detection_eval = 6.19153
-I0511 11:49:27.183656  4597 caffe.cpp:501] detection_eval = 0.0303933
-I0511 11:49:27.183658  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.183660  4597 caffe.cpp:501] detection_eval = 0.641129
-I0511 11:49:27.183662  4597 caffe.cpp:501] detection_eval = 5.89718
-I0511 11:49:27.183665  4597 caffe.cpp:501] detection_eval = 6.21573
-I0511 11:49:27.183666  4597 caffe.cpp:501] detection_eval = 0.024151
-I0511 11:49:27.183668  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183671  4597 caffe.cpp:501] detection_eval = 0.65121
-I0511 11:49:27.183673  4597 caffe.cpp:501] detection_eval = 5.87903
-I0511 11:49:27.183676  4597 caffe.cpp:501] detection_eval = 6.21169
-I0511 11:49:27.183677  4597 caffe.cpp:501] detection_eval = 0.0252697
-I0511 11:49:27.183679  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184206  4597 caffe.cpp:501] detection_eval = 0.647177
-I0511 11:49:27.184212  4597 caffe.cpp:501] detection_eval = 5.87903
-I0511 11:49:27.184216  4597 caffe.cpp:501] detection_eval = 6.26613
-I0511 11:49:27.184218  4597 caffe.cpp:501] detection_eval = 0.0259765
-I0511 11:49:27.184221  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184222  4597 caffe.cpp:501] detection_eval = 0.645161
-I0511 11:49:27.184224  4597 caffe.cpp:501] detection_eval = 5.87903
-I0511 11:49:27.184227  4597 caffe.cpp:501] detection_eval = 6.33065
-I0511 11:49:27.184229  4597 caffe.cpp:501] detection_eval = 0.0280103
-I0511 11:49:27.184231  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.184233  4597 caffe.cpp:501] detection_eval = 0.645161
-I0511 11:49:27.184236  4597 caffe.cpp:501] detection_eval = 5.86089
-I0511 11:49:27.184237  4597 caffe.cpp:501] detection_eval = 6.34677
-I0511 11:49:27.184240  4597 caffe.cpp:501] detection_eval = 0.0285469
-I0511 11:49:27.184242  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.184244  4597 caffe.cpp:501] detection_eval = 0.643145
-I0511 11:49:27.184247  4597 caffe.cpp:501] detection_eval = 5.84274
-I0511 11:49:27.184248  4597 caffe.cpp:501] detection_eval = 6.36089
-I0511 11:49:27.184250  4597 caffe.cpp:501] detection_eval = 0.02545
-I0511 11:49:27.184252  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184255  4597 caffe.cpp:501] detection_eval = 0.643145
-I0511 11:49:27.184257  4597 caffe.cpp:501] detection_eval = 5.84274
-I0511 11:49:27.184259  4597 caffe.cpp:501] detection_eval = 6.38911
-I0511 11:49:27.184262  4597 caffe.cpp:501] detection_eval = 0.0254611
-I0511 11:49:27.184263  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184265  4597 caffe.cpp:501] detection_eval = 0.645161
-I0511 11:49:27.184267  4597 caffe.cpp:501] detection_eval = 5.78831
-I0511 11:49:27.184270  4597 caffe.cpp:501] detection_eval = 6.32661
-I0511 11:49:27.184273  4597 caffe.cpp:501] detection_eval = 0.0267105
-I0511 11:49:27.184274  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184276  4597 caffe.cpp:501] detection_eval = 0.637097
-I0511 11:49:27.184278  4597 caffe.cpp:501] detection_eval = 5.75202
-I0511 11:49:27.184280  4597 caffe.cpp:501] detection_eval = 6.28831
-I0511 11:49:27.184283  4597 caffe.cpp:501] detection_eval = 0.0250424
-I0511 11:49:27.184284  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.184288  4597 caffe.cpp:501] detection_eval = 0.631048
-I0511 11:49:27.184294  4597 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:49:27.184296  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.184298  4597 caffe.cpp:501] detection_eval = 0.0268295
-I0511 11:49:27.184300  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184303  4597 caffe.cpp:501] detection_eval = 0.631048
-I0511 11:49:27.184305  4597 caffe.cpp:501] detection_eval = 5.69758
-I0511 11:49:27.184307  4597 caffe.cpp:501] detection_eval = 6.29435
-I0511 11:49:27.184309  4597 caffe.cpp:501] detection_eval = 0.0259999
-I0511 11:49:27.184311  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184314  4597 caffe.cpp:501] detection_eval = 0.627016
-I0511 11:49:27.184315  4597 caffe.cpp:501] detection_eval = 5.66129
-I0511 11:49:27.184317  4597 caffe.cpp:501] detection_eval = 6.28024
-I0511 11:49:27.184319  4597 caffe.cpp:501] detection_eval = 0.0225302
-I0511 11:49:27.184322  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.184324  4597 caffe.cpp:501] detection_eval = 0.627016
-I0511 11:49:27.184326  4597 caffe.cpp:501] detection_eval = 5.57056
-I0511 11:49:27.184329  4597 caffe.cpp:501] detection_eval = 6.12903
-I0511 11:49:27.184330  4597 caffe.cpp:501] detection_eval = 0.025236
-I0511 11:49:27.184334  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184335  4597 caffe.cpp:501] detection_eval = 0.606855
-I0511 11:49:27.184337  4597 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:49:27.184340  4597 caffe.cpp:501] detection_eval = 6.14919
-I0511 11:49:27.184341  4597 caffe.cpp:501] detection_eval = 0.0235622
-I0511 11:49:27.184345  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184346  4597 caffe.cpp:501] detection_eval = 0.612903
-I0511 11:49:27.184348  4597 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:49:27.184350  4597 caffe.cpp:501] detection_eval = 6.15323
-I0511 11:49:27.184352  4597 caffe.cpp:501] detection_eval = 0.0286466
-I0511 11:49:27.184355  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184356  4597 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:49:27.184360  4597 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:49:27.184361  4597 caffe.cpp:501] detection_eval = 6.20363
-I0511 11:49:27.184363  4597 caffe.cpp:501] detection_eval = 0.0239786
-I0511 11:49:27.184365  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184367  4597 caffe.cpp:501] detection_eval = 0.608871
-I0511 11:49:27.184370  4597 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:49:27.184371  4597 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:49:27.184373  4597 caffe.cpp:501] detection_eval = 0.021609
-I0511 11:49:27.184376  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.184378  4597 caffe.cpp:501] detection_eval = 0.610887
-I0511 11:49:27.184381  4597 caffe.cpp:501] detection_eval = 5.51613
-I0511 11:49:27.184382  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.184384  4597 caffe.cpp:501] detection_eval = 0.0248316
-I0511 11:49:27.184386  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184388  4597 caffe.cpp:501] detection_eval = 0.596774
-I0511 11:49:27.184391  4597 caffe.cpp:501] detection_eval = 5.49798
-I0511 11:49:27.184392  4597 caffe.cpp:501] detection_eval = 6.29234
-I0511 11:49:27.184394  4597 caffe.cpp:501] detection_eval = 0.0259911
-I0511 11:49:27.184397  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184399  4597 caffe.cpp:501] detection_eval = 0.600806
-I0511 11:49:27.184401  4597 caffe.cpp:501] detection_eval = 5.46169
-I0511 11:49:27.184403  4597 caffe.cpp:501] detection_eval = 6.23992
-I0511 11:49:27.184406  4597 caffe.cpp:501] detection_eval = 0.0234384
-I0511 11:49:27.184407  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184409  4597 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:49:27.184412  4597 caffe.cpp:501] detection_eval = 5.4254
-I0511 11:49:27.184414  4597 caffe.cpp:501] detection_eval = 6.27823
-I0511 11:49:27.184417  4597 caffe.cpp:501] detection_eval = 0.0310337
-I0511 11:49:27.184418  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.184423  4597 caffe.cpp:501] detection_eval = 0.58871
-I0511 11:49:27.184427  4597 caffe.cpp:501] detection_eval = 5.37097
-I0511 11:49:27.184428  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.184430  4597 caffe.cpp:501] detection_eval = 0.0281657
-I0511 11:49:27.184432  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.184434  4597 caffe.cpp:501] detection_eval = 0.582661
-I0511 11:49:27.184437  4597 caffe.cpp:501] detection_eval = 5.35282
-I0511 11:49:27.184438  4597 caffe.cpp:501] detection_eval = 6.2379
-I0511 11:49:27.184440  4597 caffe.cpp:501] detection_eval = 0.0223501
-I0511 11:49:27.184443  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184445  4597 caffe.cpp:501] detection_eval = 0.58871
-I0511 11:49:27.184448  4597 caffe.cpp:501] detection_eval = 5.29839
-I0511 11:49:27.184449  4597 caffe.cpp:501] detection_eval = 6.1996
-I0511 11:49:27.184451  4597 caffe.cpp:501] detection_eval = 0.0255929
-I0511 11:49:27.184453  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184455  4597 caffe.cpp:501] detection_eval = 0.584677
-I0511 11:49:27.184458  4597 caffe.cpp:501] detection_eval = 5.28024
-I0511 11:49:27.184460  4597 caffe.cpp:501] detection_eval = 6.22581
-I0511 11:49:27.184463  4597 caffe.cpp:501] detection_eval = 0.0251907
-I0511 11:49:27.184464  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184466  4597 caffe.cpp:501] detection_eval = 0.576613
-I0511 11:49:27.184468  4597 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:49:27.184470  4597 caffe.cpp:501] detection_eval = 6.16129
-I0511 11:49:27.184978  4597 caffe.cpp:501] detection_eval = 0.0210612
-I0511 11:49:27.184985  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.184988  4597 caffe.cpp:501] detection_eval = 0.578629
-I0511 11:49:27.184990  4597 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:49:27.184993  4597 caffe.cpp:501] detection_eval = 6.20161
-I0511 11:49:27.184994  4597 caffe.cpp:501] detection_eval = 0.0208977
-I0511 11:49:27.184996  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.184999  4597 caffe.cpp:501] detection_eval = 0.572581
-I0511 11:49:27.185001  4597 caffe.cpp:501] detection_eval = 5.18952
-I0511 11:49:27.185003  4597 caffe.cpp:501] detection_eval = 6.13508
-I0511 11:49:27.185005  4597 caffe.cpp:501] detection_eval = 0.0219971
-I0511 11:49:27.185008  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.185009  4597 caffe.cpp:501] detection_eval = 0.570565
-I0511 11:49:27.185012  4597 caffe.cpp:501] detection_eval = 5.15323
-I0511 11:49:27.185014  4597 caffe.cpp:501] detection_eval = 6.08871
-I0511 11:49:27.185016  4597 caffe.cpp:501] detection_eval = 0.0227967
-I0511 11:49:27.185019  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.185020  4597 caffe.cpp:501] detection_eval = 0.568548
-I0511 11:49:27.185022  4597 caffe.cpp:501] detection_eval = 5.11694
-I0511 11:49:27.185024  4597 caffe.cpp:501] detection_eval = 6.10484
-I0511 11:49:27.185027  4597 caffe.cpp:501] detection_eval = 0.023998
-I0511 11:49:27.185029  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.185031  4597 caffe.cpp:501] detection_eval = 0.556452
-I0511 11:49:27.185034  4597 caffe.cpp:501] detection_eval = 5.08065
-I0511 11:49:27.185035  4597 caffe.cpp:501] detection_eval = 6.06452
-I0511 11:49:27.185037  4597 caffe.cpp:501] detection_eval = 0.0238617
-I0511 11:49:27.185040  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.185042  4597 caffe.cpp:501] detection_eval = 0.558468
-I0511 11:49:27.185045  4597 caffe.cpp:501] detection_eval = 5.04435
-I0511 11:49:27.185046  4597 caffe.cpp:501] detection_eval = 6.04839
-I0511 11:49:27.185048  4597 caffe.cpp:501] detection_eval = 0.0233311
-I0511 11:49:27.185050  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.185052  4597 caffe.cpp:501] detection_eval = 0.554435
-I0511 11:49:27.185055  4597 caffe.cpp:501] detection_eval = 5.00806
-I0511 11:49:27.185057  4597 caffe.cpp:501] detection_eval = 6.0121
-I0511 11:49:27.185060  4597 caffe.cpp:501] detection_eval = 0.0228293
-I0511 11:49:27.185061  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.185068  4597 caffe.cpp:501] detection_eval = 0.546371
-I0511 11:49:27.185070  4597 caffe.cpp:501] detection_eval = 4.97177
-I0511 11:49:27.185073  4597 caffe.cpp:501] detection_eval = 5.98185
-I0511 11:49:27.185075  4597 caffe.cpp:501] detection_eval = 0.0257397
-I0511 11:49:27.185077  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.185079  4597 caffe.cpp:501] detection_eval = 0.542339
-I0511 11:49:27.185081  4597 caffe.cpp:501] detection_eval = 4.97177
-I0511 11:49:27.185083  4597 caffe.cpp:501] detection_eval = 6.05847
-I0511 11:49:27.185086  4597 caffe.cpp:501] detection_eval = 0.0266467
-I0511 11:49:27.185087  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.185091  4597 caffe.cpp:501] detection_eval = 0.532258
-I0511 11:49:27.185092  4597 caffe.cpp:501] detection_eval = 4.93548
-I0511 11:49:27.185094  4597 caffe.cpp:501] detection_eval = 6.03831
-I0511 11:49:27.185096  4597 caffe.cpp:501] detection_eval = 0.0265504
-I0511 11:49:27.185098  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.185101  4597 caffe.cpp:501] detection_eval = 0.53629
-I0511 11:49:27.185102  4597 caffe.cpp:501] detection_eval = 4.91734
-I0511 11:49:27.185104  4597 caffe.cpp:501] detection_eval = 6.03024
-I0511 11:49:27.185106  4597 caffe.cpp:501] detection_eval = 0.0236068
-I0511 11:49:27.185109  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.185111  4597 caffe.cpp:501] detection_eval = 0.53629
-I0511 11:49:27.185113  4597 caffe.cpp:501] detection_eval = 4.88105
-I0511 11:49:27.185115  4597 caffe.cpp:501] detection_eval = 6.01008
-I0511 11:49:27.185117  4597 caffe.cpp:501] detection_eval = 0.0230098
-I0511 11:49:27.185120  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.185122  4597 caffe.cpp:501] detection_eval = 0.53629
-I0511 11:49:27.186365  4597 caffe.cpp:546] class AP 1: 0.651434
-I0511 11:49:27.186940  4597 caffe.cpp:546] class AP 2: 0.730767
-I0511 11:49:27.195986  4597 caffe.cpp:546] class AP 3: 0.555641
-I0511 11:49:27.201273  4597 caffe.cpp:546] class AP 4: 0.5085
-I0511 11:49:27.221433  4597 caffe.cpp:546] class AP 5: 0.337752
-I0511 11:49:27.221793  4597 caffe.cpp:546] class AP 6: 0.737833
-I0511 11:49:27.230624  4597 caffe.cpp:546] class AP 7: 0.70404
-I0511 11:49:27.231215  4597 caffe.cpp:546] class AP 8: 0.815221
-I0511 11:49:27.250205  4597 caffe.cpp:546] class AP 9: 0.431295
-I0511 11:49:27.250967  4597 caffe.cpp:546] class AP 10: 0.638275
-I0511 11:49:27.251662  4597 caffe.cpp:546] class AP 11: 0.596563
-I0511 11:49:27.252665  4597 caffe.cpp:546] class AP 12: 0.724503
-I0511 11:49:27.253118  4597 caffe.cpp:546] class AP 13: 0.799232
-I0511 11:49:27.253480  4597 caffe.cpp:546] class AP 14: 0.746535
-I0511 11:49:27.301280  4597 caffe.cpp:546] class AP 15: 0.727107
-I0511 11:49:27.307509  4597 caffe.cpp:546] class AP 16: 0.366775
-I0511 11:49:27.309844  4597 caffe.cpp:546] class AP 17: 0.600392
-I0511 11:49:27.310420  4597 caffe.cpp:546] class AP 18: 0.60817
-I0511 11:49:27.311082  4597 caffe.cpp:546] class AP 19: 0.75051
-I0511 11:49:27.312469  4597 caffe.cpp:546] class AP 20: 0.6172
-I0511 11:49:27.312475  4597 caffe.cpp:552] Test net output mAP #0: detection_eval = 0.632387
-I0511 11:49:27.312480  4597 caffe.cpp:556] =========================
-I0511 11:49:27.312484  4597 caffe.cpp:557] Sparsity of the test net:
-I0511 11:49:27.314363  4597 net.cpp:2452] Num Params(47), Sparsity (zero_weights/count): 
-I0511 11:49:27.314370  4597 net.cpp:2463] conv1_param_0(0) 
-I0511 11:49:27.314380  4597 net.cpp:2463] conv2_1/dw_param_0(0) 
-I0511 11:49:27.314394  4597 net.cpp:2463] conv2_1/sep_param_0(0) 
-I0511 11:49:27.314400  4597 net.cpp:2463] conv2_2/dw_param_0(0) 
-I0511 11:49:27.314409  4597 net.cpp:2463] conv2_2/sep_param_0(0) 
-I0511 11:49:27.314414  4597 net.cpp:2463] conv3_1/dw_param_0(0) 
-I0511 11:49:27.314417  4597 net.cpp:2463] conv3_1/sep_param_0(0) 
-I0511 11:49:27.314426  4597 net.cpp:2463] conv3_2/dw_param_0(0) 
-I0511 11:49:27.314431  4597 net.cpp:2463] conv3_2/sep_param_0(0) 
-I0511 11:49:27.314435  4597 net.cpp:2463] conv4_1/dw_param_0(0) 
-I0511 11:49:27.314442  4597 net.cpp:2463] conv4_1/sep_param_0(0) 
-I0511 11:49:27.314458  4597 net.cpp:2463] conv4_2/dw_param_0(0) 
-I0511 11:49:27.314462  4597 net.cpp:2463] conv4_2/sep_param_0(0) 
-I0511 11:49:27.314471  4597 net.cpp:2463] conv5_1/dw_param_0(0) 
-I0511 11:49:27.314481  4597 net.cpp:2463] conv5_1/sep_param_0(0) 
-I0511 11:49:27.314486  4597 net.cpp:2463] conv5_2/dw_param_0(0) 
-I0511 11:49:27.314489  4597 net.cpp:2463] conv5_2/sep_param_0(0) 
-I0511 11:49:27.314497  4597 net.cpp:2463] conv5_3/dw_param_0(0) 
-I0511 11:49:27.314502  4597 net.cpp:2463] conv5_3/sep_param_0(0) 
-I0511 11:49:27.314505  4597 net.cpp:2463] conv5_4/dw_param_0(0) 
-I0511 11:49:27.314513  4597 net.cpp:2463] conv5_4/sep_param_0(0) 
-I0511 11:49:27.314517  4597 net.cpp:2463] conv5_5/dw_param_0(0) 
-I0511 11:49:27.314525  4597 net.cpp:2463] conv5_5/sep_param_0(0) 
-I0511 11:49:27.314530  4597 net.cpp:2463] conv5_6/dw_param_0(0) 
-I0511 11:49:27.314538  4597 net.cpp:2463] conv5_6/sep_param_0(0) 
-I0511 11:49:27.314543  4597 net.cpp:2463] conv6/dw_param_0(0) 
-I0511 11:49:27.314550  4597 net.cpp:2463] conv6/sep_param_0(0) 
-I0511 11:49:27.314558  4597 net.cpp:2463] ctx_output1/1x1_param_0(0) 
-I0511 11:49:27.314563  4597 net.cpp:2463] ctx_output1/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314571  4597 net.cpp:2463] ctx_output1/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314575  4597 net.cpp:2463] ctx_output1_param_0(0) 
-I0511 11:49:27.314584  4597 net.cpp:2463] ctx_output2/1x1_param_0(0) 
-I0511 11:49:27.314587  4597 net.cpp:2463] ctx_output2/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314595  4597 net.cpp:2463] ctx_output2/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314600  4597 net.cpp:2463] ctx_output2_param_0(0) 
-I0511 11:49:27.314607  4597 net.cpp:2463] ctx_output3/1x1_param_0(0) 
-I0511 11:49:27.314616  4597 net.cpp:2463] ctx_output3/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314621  4597 net.cpp:2463] ctx_output3/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314630  4597 net.cpp:2463] ctx_output3_param_0(0) 
-I0511 11:49:27.314633  4597 net.cpp:2463] ctx_output4/1x1_param_0(0) 
-I0511 11:49:27.314641  4597 net.cpp:2463] ctx_output4/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314646  4597 net.cpp:2463] ctx_output4/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314653  4597 net.cpp:2463] ctx_output4_param_0(0) 
-I0511 11:49:27.314657  4597 net.cpp:2463] ctx_output5/1x1_param_0(0) 
-I0511 11:49:27.314666  4597 net.cpp:2463] ctx_output5/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314669  4597 net.cpp:2463] ctx_output5/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314677  4597 net.cpp:2463] ctx_output5_param_0(0) 
-I0511 11:49:27.314682  4597 net.cpp:2467] Total Sparsity (zero_weights/count) =  (0/2.31754e+06) 0
-I0511 11:49:27.314703  4597 caffe.cpp:559] =========================

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/run.sh b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/run.sh
deleted file mode 100755 (executable)
index df8999f..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/run.sh
+++ /dev/null
@@ -1,6 +0,0 @@
-/user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin test_detection \
---model="training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test/test.prototxt" \
---iterations="496" \
---display_sparsity=1 \
---weights="training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel" \
---gpu "0" 2>&1 | tee training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test/run.log

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/solver.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/solver.prototxt
deleted file mode 100755 (executable)
index 2dc4625..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/solver.prototxt
+++ /dev/null
@@ -1,33 +0,0 @@
-train_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test/train.prototxt"
-test_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test/test.prototxt"
-test_iter: 496
-test_interval: 2000
-base_lr: 0.01
-display: 100
-max_iter: 120000
-lr_policy: "multistep"
-gamma: 0.1
-power: 1.0
-momentum: 0.9
-weight_decay: 1e-05
-snapshot: 2000
-snapshot_prefix: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test/voc0712_mobiledetnet-0.5"
-solver_mode: GPU
-device_id: 0
-random_seed: 33
-debug_info: false
-snapshot_after_train: true
-regularization_type: "L1"
-test_initialization: true
-average_loss: 10
-stepvalue: 60000
-stepvalue: 90000
-stepvalue: 300000
-iter_size: 2
-type: "SGD"
-display_sparsity: 1000
-sparse_mode: SPARSE_UPDATE
-eval_type: "detection"
-ap_version: "11point"
-show_per_class_result: true
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/test.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/test.prototxt
deleted file mode 100755 (executable)
index c06b6f6..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/test.prototxt
+++ /dev/null
@@ -1,2419 +0,0 @@
-name: "mobiledetnet-0.5_test"
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 10
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    pad: 0
-    kernel_size: 1
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-    weight_filler {
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
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-  type: "Scale"
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-  top: "conv6/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
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-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
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-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
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-    kernel_size: 3
-    stride: 1
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-  }
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-layer {
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-  top: "ctx_output1/1x1"
-  param {
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-layer {
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-  top: "ctx_output1/1x1"
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-layer {
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-  top: "ctx_output1/1x1"
-}
-layer {
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-  top: "ctx_output1"
-  param {
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-  param {
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-  convolution_param {
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-    }
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-layer {
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-layer {
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-  top: "ctx_output1"
-}
-layer {
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-  top: "ctx_output2/1x1"
-  param {
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-  param {
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-layer {
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-  top: "ctx_output2/1x1"
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-layer {
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-  top: "ctx_output2/1x1"
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-layer {
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-  top: "ctx_output2"
-  param {
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-  param {
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-    decay_mult: 0
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-  convolution_param {
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-layer {
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-layer {
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-  top: "ctx_output2"
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-layer {
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-  top: "ctx_output3/1x1"
-  param {
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-  param {
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-    decay_mult: 0
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-layer {
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-  top: "ctx_output3/1x1"
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-layer {
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-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
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-layer {
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-  top: "ctx_output3"
-  param {
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-  param {
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-    decay_mult: 0
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-layer {
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-  top: "ctx_output3"
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-layer {
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-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
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-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
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-    pad: 0
-    kernel_size: 1
-    group: 1
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-    weight_filler {
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-      value: 0
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-    dilation: 1
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-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19.0
-    max_size: 88.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output2"
-  bottom: "data"
-  top: "ctx_output2/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 88.0
-    max_size: 157.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_loc"
-  top: "ctx_output3/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_loc_perm"
-  top: "ctx_output3/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_conf"
-  top: "ctx_output3/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_conf_perm"
-  top: "ctx_output3/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output3"
-  bottom: "data"
-  top: "ctx_output3/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 157.0
-    max_size: 226.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_loc"
-  top: "ctx_output4/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_loc_perm"
-  top: "ctx_output4/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_conf"
-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_conf_perm"
-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output4"
-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 226.0
-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_reshape"
-  type: "Reshape"
-  bottom: "mbox_conf"
-  top: "mbox_conf_reshape"
-  reshape_param {
-    shape {
-      dim: 0
-      dim: -1
-      dim: 21
-    }
-  }
-}
-layer {
-  name: "mbox_conf_softmax"
-  type: "Softmax"
-  bottom: "mbox_conf_reshape"
-  top: "mbox_conf_softmax"
-  softmax_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_flatten"
-  type: "Flatten"
-  bottom: "mbox_conf_softmax"
-  top: "mbox_conf_flatten"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "detection_out"
-  type: "DetectionOutput"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf_flatten"
-  bottom: "mbox_priorbox"
-  top: "detection_out"
-  include {
-    phase: TEST
-  }
-  detection_output_param {
-    num_classes: 21
-    share_location: true
-    background_label_id: 0
-    nms_param {
-      nms_threshold: 0.45
-      top_k: 400
-    }
-    save_output_param {
-      output_directory: ""
-      output_name_prefix: "comp4_det_test_"
-      output_format: "VOC"
-      label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-      name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-      num_test_image: 4952
-    }
-    code_type: CENTER_SIZE
-    keep_top_k: 200
-    confidence_threshold: 0.01
-  }
-}
-layer {
-  name: "detection_eval"
-  type: "DetectionEvaluate"
-  bottom: "detection_out"
-  bottom: "label"
-  top: "detection_eval"
-  include {
-    phase: TEST
-  }
-  detection_evaluate_param {
-    num_classes: 21
-    background_label_id: 0
-    overlap_threshold: 0.5
-    evaluate_difficult_gt: false
-    name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/train.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/train.prototxt
deleted file mode 100755 (executable)
index 63b33c1..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/train.prototxt
+++ /dev/null
@@ -1,2482 +0,0 @@
-name: "mobiledetnet-0.5"
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TRAIN
-  }
-  transform_param {
-    mirror: true
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-      interp_mode: AREA
-      interp_mode: NEAREST
-      interp_mode: CUBIC
-      interp_mode: LANCZOS4
-    }
-    emit_constraint {
-      emit_type: CENTER
-    }
-    crop_h: 256
-    crop_w: 512
-    distort_param {
-      brightness_prob: 0.5
-      brightness_delta: 32
-      contrast_prob: 0.5
-      contrast_lower: 0.5
-      contrast_upper: 1.5
-      hue_prob: 0.5
-      hue_delta: 18
-      saturation_prob: 0.5
-      saturation_lower: 0.5
-      saturation_upper: 1.5
-      random_order_prob: 0.0
-    }
-    expand_param {
-      prob: 0.5
-      max_expand_ratio: 4.0
-    }
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb"
-    batch_size: 16
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-      max_sample: 1
-      max_trials: 1
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.1
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.3
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.5
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.7
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.9
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        max_jaccard_overlap: 1.0
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
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-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
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-    decay_mult: 1
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-    group: 1
-    stride: 2
-    weight_filler {
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
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-  }
-}
-layer {
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-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
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-  param {
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-    decay_mult: 0.01
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-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
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-layer {
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-layer {
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-  type: "Scale"
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-  scale_param {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/dw/scale"
-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
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-  convolution_param {
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-    weight_filler {
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-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-    dilation: 1
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
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-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-      value: 0
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-    dilation: 1
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-layer {
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-  type: "BatchNorm"
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-  top: "ctx_output3/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 1
-    kernel_size: 3
-    group: 512
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-    weight_filler {
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-    }
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-    dilation: 1
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-layer {
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-  top: "ctx_output3"
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-  }
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-layer {
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-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
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-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 0
-    kernel_size: 1
-    group: 1
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-    weight_filler {
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-    }
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-    dilation: 1
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-layer {
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-  top: "ctx_output4/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
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-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
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-    kernel_size: 3
-    group: 512
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-    weight_filler {
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-    }
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-layer {
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-  top: "ctx_output4"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
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-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19.0
-    max_size: 88.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output2"
-  bottom: "data"
-  top: "ctx_output2/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 88.0
-    max_size: 157.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_loc"
-  top: "ctx_output3/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_loc_perm"
-  top: "ctx_output3/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_conf"
-  top: "ctx_output3/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_conf_perm"
-  top: "ctx_output3/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output3"
-  bottom: "data"
-  top: "ctx_output3/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 157.0
-    max_size: 226.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_loc"
-  top: "ctx_output4/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_loc_perm"
-  top: "ctx_output4/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_conf"
-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_conf_perm"
-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output4"
-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 226.0
-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_loss"
-  type: "MultiBoxLoss"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf"
-  bottom: "mbox_priorbox"
-  bottom: "label"
-  top: "mbox_loss"
-  include {
-    phase: TRAIN
-  }
-  propagate_down: true
-  propagate_down: true
-  propagate_down: false
-  propagate_down: false
-  loss_param {
-    normalization: VALID
-  }
-  multibox_loss_param {
-    loc_loss_type: SMOOTH_L1
-    conf_loss_type: SOFTMAX
-    loc_weight: 1.0
-    num_classes: 21
-    share_location: true
-    match_type: PER_PREDICTION
-    overlap_threshold: 0.5
-    use_prior_for_matching: true
-    background_label_id: 0
-    use_difficult_gt: true
-    neg_pos_ratio: 3.0
-    neg_overlap: 0.5
-    code_type: CENTER_SIZE
-    ignore_cross_boundary_bbox: false
-    mining_type: MAX_NEGATIVE
-    ignore_difficult_gt: false
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/train_image_object_detection.sh b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/train_image_object_detection.sh
deleted file mode 100755 (executable)
index c08e0b4..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test/train_image_object_detection.sh
+++ /dev/null
@@ -1,360 +0,0 @@
-#!/bin/bash
-
-#-------------------------------------------------------
-DATE_TIME=`date +'%Y%m%d_%H-%M'`
-#-------------------------------------------------------
-
-#------------------------------------------------
-gpus="0" #"0,1" #"0,1,2"   #IMPORTANT: change this to "0" if you have only one GPU and adjust batch_size (below) accordingly
-
-#-------------------------------------------------------
-model_name=ssdJacintoNetV2       #ssdJacintoNetV2  #mobiledetnet-0.5     
-dataset=voc0712                  #voc0712,ti-custom-cfg1,ti-custom-cfg2
-#------------------------------------------------
-
-#Download the pretrained weights
-weights_dst="../trained/image_classification/imagenet_jacintonet11v2/initial/imagenet_jacintonet11v2_iter_320000.caffemodel"
-
-#------------------------------------------------
-#ssd-size:'512x512', '300x300','256x256'
-ssd_size='512x512'
-
-#0:[1,2,1/2] for each reg head, 1:like orig SSD
-aspect_ratios_type=1
-
-#max donwsampling factor: 16,32
-ds_fac=32
-
-#down sampling type: 'DFLT', 'PSP'
-ds_type='PSP'
-
-#regression head at downsamling 8 layer: 0,1 
-reg_head_at_ds8=1
-
-#use concat layers for regression heads
-concat_reg_head=0
-
-#kernel size for mbox_loc, mbox_conf conv
-ker_mbox_loc_conf=3
-
-#if unintialized value: Average of W,H will be used as min dim
-min_dim=-1
-
-#1:model tuned for small objects, 0:model tuned for moderate size object like PASCAL VOC
-small_objs=0
-
-#"step", "multistep", "poly"
-lr_policy="multistep"
-
-#needed for coco training for gray scale images
-force_color=0
-stepvalue3=300000 
-
-#num op ch for mbox layers = num_intermediate/2
-num_intermediate=512
-rhead_name_non_linear=0
-
-#1: difficult GT will be used for eval, 0: difficult GT will not be used for evaluation
-evaluate_difficult_gt=0
-
-#:Experimntal option. Does not have  any effect now.
-ignore_difficult_gt=0
-
-#set to True for VOC0712
-use_difficult_gt=1
-
-#"poly","multistep"
-lr_policy="multistep"
-
-#set it to 4.0 for poly
-power=1.0
-
-#0.0005 (orignal SSD), 0.0001
-weight_decay_L2=0.0001
-
-#0:linear,1:log,2:like original SSD (min/max ratio will be recomputed)
-log_space_steps=2
-min_ratio=10
-max_ratio=90
-
-#1:FC layer like originalk SSD, 0: no FC layer
-fully_conv_at_end=0
-
-#1: connect 3 head in base n/w. Experimental. set it to 0
-base_nw_3_head=0
-
-#1:first head num of op channel same as other layers, 0: first hd double the number of op channel
-first_hd_same_op_ch=1
-
-#To chop of last few heads. It will make max/min size computed based on original number of heads
-chop_num_heads=0
-
-#known issue - use_image_list=0 && shuffle=1 => hang.
-use_image_list=0 
-
-#Note shuffle is used only in training
-shuffle=0        
-
-#sparsity will be induced gradually starting from this value
-sparsity_start_factor=0.5
-#-------------------------------------------------------
-if [ $dataset = "voc0712" ]
-then
-
-  train_data="../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
- 
-  num_test_image=4952
-  num_classes=21
-
-  min_dim=512
-  
-  resize_width=512
-  resize_height=512
-  crop_width=512
-  crop_height=512
-  batch_size=16    #32    #16
-
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=120000    #120000  #64000   #32000
-  stepvalue1=60000   #60000   #32000   #16000
-  stepvalue2=90000   #90000   #48000   #24000
-  base_lr=1e-2       #1e-2    #1e-4    #1e-3
-  
-  #use batch norm ofr mbox layer1:enable,0:disable
-  use_batchnorm_mbox=1
-
-  sparsity_start_factor=0.25 
-
-elif [ $dataset = "ti-custom-cfg1" ]
-then
-  #In V2 removed V153,154(part of TI Demo) and V002(anno has been corrected so no need to use VGG generated)     
- 
-  train_data="../../caffe-jacinto/examples/ti-custom-cfg1/ti-custom-cfg1_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/ti-custom-cfg1/ti-custom-cfg1_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/ti-custom-cfg1/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/ti-custom-cfg1/labelmap.prototxt"
- 
-  num_test_image=3609
-  num_classes=4
-
-  min_dim=368
- 
-  resize_width=720
-  resize_height=368
-  crop_width=720
-  crop_height=368
-  use_difficult_gt=0
-  small_objs=1
-  ker_mbox_loc_conf=1
-  batch_size=16      #32    #16
-
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=120000    #120000  #64000   #32000
-  stepvalue1=30000   #60000   #32000   #16000
-  stepvalue2=45000   #90000   #48000   #24000
-  base_lr=1e-3       #1e-2    #1e-4    #1e-3
-  lr_policy="poly"
-  #set it to 4.0 for poly
-  power=4.0
-
-  #0.0005 (orignal SSD), 0.0001
-  weight_decay_L2=0.0005
-  use_batchnorm_mbox=0
-elif [ $dataset = "ti-custom-cfg2" ]
-then
-  train_data="../../caffe-jacinto/examples/ti-custom-cfg2/ti-custom-cfg2_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/ti-custom-cfg2/ti-custom-cfg2_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/ti-custom-cfg2/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/ti-custom-cfg2/labelmap.prototxt"
-
-  num_test_image=294
-  num_classes=3 
-
-  min_dim=256
-  ssd_size='512x512'
- 
-  resize_width=512
-  resize_height=256
-  crop_width=512
-  crop_height=256
-  small_objs=0
-  ker_mbox_loc_conf=1
-  batch_size=16      #32    #16
-
-  #ignore lables are marked as diff in TI dataset 
-  use_difficult_gt=1
-  
-  #solver params
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=50000     #120000  #64000   #32000
-  stepvalue1=30000   #60000   #32000   #16000
-  stepvalue2=40000   #90000   #48000   #24000
-  base_lr=1e-2       #1e-2    #1e-4    #1e-3
-  #set it to 4.0 for poly
-  power=1.0
-
-  #0.0005 (orignal SSD), 0.0001
-  weight_decay_L2=0.0001
-  use_batchnorm_mbox=1
-else
-  echo "Invalid dataset name"
-  exit
-fi
-
-model_name_to_print=$model_name 
-if [ $model_name = 'ssdJacintoNetV2' ]
-then
-  model_name_to_print="JDetNet" 
-fi  
-
-folder_name=training/"$dataset"/"$model_name_to_print"/"$DATE_TIME"_"ds_PSP_dsFac_32_hdDS8_1";mkdir training/"$dataset";mkdir training/"$dataset"/"$model_name_to_print";mkdir $folder_name
-
-#------------------------------------------------
-LOG=$folder_name/train-log_"$DATE_TIME".txt
-exec &> >(tee -a "$LOG")
-echo Logging output to "$LOG"
-
-#-------------------------------------------------------
-#Initial training
-stage="initial"
-weights=$weights_dst
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],'weight_decay':$weight_decay_L2}"
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,\
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,\
-'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type',\
-'rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,\
-'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#l1 regularized training before sparsification
-stage="l1reg"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_"$max_iter".caffemodel
-
-max_iter=60000
-stepvalue1=30000
-stepvalue2=45000
-base_lr=1e-3       #1e-2    #1e-4    #1e-3
-l1reg_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$l1reg_solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#incremental sparsification and finetuning
-stage="sparse"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-#Using more than one GPU for this step gives strange results. Imbalanced accuracy between the GPUs.
-gpus="0" #"0,1,2"
-batch_size=8
-lr_policy="poly"
-#set it to 4.0 for poly
-power=4.0
-base_lr=1e-3       #1e-2    #1e-4    #1e-3
-sparse_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':2000,\
-'sparsity_target':0.70,'sparsity_start_iter':0,'sparsity_start_factor':$sparsity_start_factor,\
-'sparsity_step_iter':2000,'sparsity_step_factor':0.05,'sparsity_itr_increment_bfr_applying':1,'sparsity_threshold_maxratio':0.2,\
-'sparsity_threshold_value_max':0.2}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox, 'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$sparse_solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#test
-stage="test"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-test_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':1000}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'test_batch_size':10,'caffe_cmd':'test_detection','display_sparsity':1,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$test_solver_param
-#config_name_prev=$config_name
-
-#-------------------------------------------------------
-#test_quantize
-stage="test_quantize"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-test_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':1000}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'test_batch_size':10,'caffe_cmd':'test_detection',\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,\
-'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,\
-'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$test_solver_param
-
-echo "quantize: true" > $config_name/deploy_new.prototxt
-cat $config_name/deploy.prototxt >> $config_name/deploy_new.prototxt
-mv --force $config_name/deploy_new.prototxt $config_name/deploy.prototxt
-
-echo "quantize: true" > $config_name/test_new.prototxt
-cat $config_name/test.prototxt >> $config_name/test_new.prototxt
-mv --force $config_name/test_new.prototxt $config_name/test.prototxt
-
-#-------------------------------------------------------
-#run
-list_dirs=`command ls -d1 "$folder_name"/*/ | command cut -f5 -d/`
-for f in $list_dirs; do "$folder_name"/$f/run.sh; done

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/deploy.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/deploy.prototxt
deleted file mode 100755 (executable)
index f9768ce..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/deploy.prototxt
+++ /dev/null
@@ -1,2374 +0,0 @@
-quantize: true
-name: "mobiledetnet-0.5_deploy"
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 256
-  dim: 512
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_1/sep/scale"
-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/dw/scale"
-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
-  name: "ctx_output1"
-  type: "Convolution"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
-  name: "ctx_output2/1x1"
-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
-  name: "ctx_output2"
-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/relu"
-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
-  name: "ctx_output3/1x1"
-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
-  name: "ctx_output3"
-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/relu"
-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19.0
-    max_size: 88.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output2"
-  bottom: "data"
-  top: "ctx_output2/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 88.0
-    max_size: 157.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_loc"
-  top: "ctx_output3/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_loc_perm"
-  top: "ctx_output3/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_conf"
-  top: "ctx_output3/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_conf_perm"
-  top: "ctx_output3/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output3"
-  bottom: "data"
-  top: "ctx_output3/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 157.0
-    max_size: 226.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_loc"
-  top: "ctx_output4/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_loc_perm"
-  top: "ctx_output4/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_conf"
-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_conf_perm"
-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output4"
-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 226.0
-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_reshape"
-  type: "Reshape"
-  bottom: "mbox_conf"
-  top: "mbox_conf_reshape"
-  reshape_param {
-    shape {
-      dim: 0
-      dim: -1
-      dim: 21
-    }
-  }
-}
-layer {
-  name: "mbox_conf_softmax"
-  type: "Softmax"
-  bottom: "mbox_conf_reshape"
-  top: "mbox_conf_softmax"
-  softmax_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_flatten"
-  type: "Flatten"
-  bottom: "mbox_conf_softmax"
-  top: "mbox_conf_flatten"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "detection_out"
-  type: "DetectionOutput"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf_flatten"
-  bottom: "mbox_priorbox"
-  top: "detection_out"
-  include {
-    phase: TEST
-  }
-  detection_output_param {
-    num_classes: 21
-    share_location: true
-    background_label_id: 0
-    nms_param {
-      nms_threshold: 0.45
-      top_k: 400
-    }
-    save_output_param {
-      output_directory: ""
-      output_name_prefix: "comp4_det_test_"
-      output_format: "VOC"
-      label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-      name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-      num_test_image: 4952
-    }
-    code_type: CENTER_SIZE
-    keep_top_k: 200
-    confidence_threshold: 0.01
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/image_object_detection.py b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/image_object_detection.py
deleted file mode 100755 (executable)
index 88b0dae..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/image_object_detection.py
+++ /dev/null
@@ -1,986 +0,0 @@
-from __future__ import print_function
-import caffe
-from google.protobuf import text_format
-import ast
-from models.model_libs import *
-import models.jacintonet_v2
-import models.mobilenet
-import numpy as np
-import math
-import os
-import shutil
-import stat
-import subprocess
-import sys
-import argparse
-from collections import OrderedDict
-
-
-def set_min_max_sizes(config_param):
-  # in percent %
-  min_ratio = 15
-  if config_param.ssd_size == '512x512':
-    min_ratio = 15
-  elif (config_param.ssd_size == '300x300') or(config_param.ssd_size == '256x256'):
-    min_ratio = 20
-  
-  if config_param.small_objs: 
-    min_ratio = min_ratio - 5
-   
-  max_ratio = 90
-  step = int(math.floor((max_ratio - min_ratio) / (config_param.num_steps - 2)))
-
-  min_sizes = []
-  max_sizes = []
-
-  for ratio in xrange(min_ratio, max_ratio + 1, step):
-    min_sizes.append(config_param.min_dim * ratio / 100.)
-    max_sizes.append(config_param.min_dim * (ratio + step) / 100.)
-
-  print('ratio_step_size:', step)   
-  
-  min_size_mul = 7
-  max_size_mul = 15
-  if config_param.ssd_size == '512x512':
-    if config_param.small_objs:
-      min_size_mul = 4 
-      max_size_mul = 10
-    else:  
-      min_size_mul = 7
-      max_size_mul = 15 
-  elif (config_param.ssd_size == '300x300') or (config_param.ssd_size == '256x256'):
-    if config_param.small_objs:
-      min_size_mul = 7
-      max_size_mul = 15 
-    else:
-      min_size_mul = 10
-      max_size_mul = 20
-  
-  min_sizes = [config_param.min_dim * min_size_mul / 100.] + min_sizes
-  max_sizes = [config_param.min_dim * max_size_mul / 100.] + max_sizes
-  
-  #print('min_sizes:', min_sizes)   
-  #print('max_sizes:', max_sizes)  
-
-  return min_sizes, max_sizes  
-
-def CreateAnnotatedDataLayer(source, batch_size=32, backend=P.Data.LMDB,
-        output_label=True, train=True, label_map_file='', anno_type=None,
-        transform_param={}, batch_sampler=[{}], threads=1):
-    if train:
-        kwargs = {
-                'include': dict(phase=caffe_pb2.Phase.Value('TRAIN')),
-                'transform_param': transform_param,
-                }
-    else:
-        kwargs = {
-                'include': dict(phase=caffe_pb2.Phase.Value('TEST')),
-                'transform_param': transform_param,
-                }
-    ntop = 1
-    if output_label:
-        ntop = 2
-    annotated_data_param = {
-        'label_map_file': label_map_file,
-        'batch_sampler': batch_sampler,
-        }
-    if anno_type is not None:
-        annotated_data_param.update({'anno_type': anno_type})
-    return L.AnnotatedData(name="data", annotated_data_param=annotated_data_param,
-        data_param=dict(batch_size=batch_size, backend=backend, source=source, parser_threads=threads, threads=threads),
-        ntop=ntop, **kwargs)
-        
-def CreateMultiBoxHead(net, data_layer="data", num_classes=[], from_layers=[],
-        use_objectness=False, normalizations=[], use_batchnorm=True, lr_mult=1,
-        use_scale=True, min_sizes=[], max_sizes=[], prior_variance = [0.1],
-        aspect_ratios=[], steps=[], img_height=0, img_width=0, share_location=True,
-        flip=True, clip=True, offset=0.5, inter_layer_depth=[], kernel_size=1, pad=0,
-        conf_postfix='', loc_postfix='', **bn_param):
-    assert num_classes, "must provide num_classes"
-    assert num_classes > 0, "num_classes must be positive number"
-    if normalizations:
-        assert len(from_layers) == len(normalizations), "from_layers and normalizations should have same length"
-    assert len(from_layers) == len(min_sizes), "from_layers and min_sizes should have same length"
-    if max_sizes:
-        assert len(from_layers) == len(max_sizes), "from_layers and max_sizes should have same length"
-    if aspect_ratios:
-        assert len(from_layers) == len(aspect_ratios), "from_layers and aspect_ratios should have same length"
-    if steps:
-        assert len(from_layers) == len(steps), "from_layers and steps should have same length"
-    net_layers = net.keys()
-    assert data_layer in net_layers, "data_layer is not in net's layers"
-    if inter_layer_depth:
-        assert len(from_layers) == len(inter_layer_depth), "from_layers and inter_layer_depth should have same length"
-
-    num = len(from_layers)
-    priorbox_layers = []
-    loc_layers = []
-    conf_layers = []
-    objectness_layers = []
-    for i in range(0, num):
-        from_layer = from_layers[i]
-
-        # Get the normalize value.
-        if normalizations:
-            if normalizations[i] != -1:
-                norm_name = "{}_norm".format(from_layer)
-                net[norm_name] = L.Normalize(net[from_layer], scale_filler=dict(type="constant", value=normalizations[i]),
-                    across_spatial=False, channel_shared=False)
-                from_layer = norm_name
-
-        # Add intermediate layers.
-        if inter_layer_depth:
-            if inter_layer_depth[i] > 0:
-                inter_name = "{}_inter".format(from_layer)
-                ConvBNLayerSSD(net, from_layer, inter_name, use_bn=use_batchnorm, use_relu=True, lr_mult=lr_mult,
-                      num_output=inter_layer_depth[i], kernel_size=3, pad=1, stride=1, use_scale=use_scale, **bn_param)
-                from_layer = inter_name
-
-        # Estimate number of priors per location given provided parameters.
-        min_size = min_sizes[i]
-        if type(min_size) is not list:
-            min_size = [min_size]
-        aspect_ratio = []
-        if len(aspect_ratios) > i:
-            aspect_ratio = aspect_ratios[i]
-            if type(aspect_ratio) is not list:
-                aspect_ratio = [aspect_ratio]
-        max_size = []
-        if len(max_sizes) > i:
-            max_size = max_sizes[i]
-            if type(max_size) is not list:
-                max_size = [max_size]
-            if max_size:
-                assert len(max_size) == len(min_size), "max_size and min_size should have same length."
-        if max_size:
-            num_priors_per_location = (2 + len(aspect_ratio)) * len(min_size)
-        else:
-            num_priors_per_location = (1 + len(aspect_ratio)) * len(min_size)
-        if flip:
-            num_priors_per_location += len(aspect_ratio) * len(min_size)
-        step = []
-        if len(steps) > i:
-            step = steps[i]
-
-        # Create location prediction layer.
-        name = "{}_mbox_loc{}".format(from_layer, loc_postfix)
-        num_loc_output = num_priors_per_location * 4;
-        if not share_location:
-            num_loc_output *= num_classes
-       
-        dilation=1
-        pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-        ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-            num_output=num_loc_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-        permute_name = "{}_perm".format(name)
-        net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-        flatten_name = "{}_flat".format(name)
-        net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-        loc_layers.append(net[flatten_name])
-
-        # Create confidence prediction layer.
-        name = "{}_mbox_conf{}".format(from_layer, conf_postfix)
-        num_conf_output = num_priors_per_location * num_classes;
-
-        dilation=1
-        pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-        ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-            num_output=num_conf_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-        permute_name = "{}_perm".format(name)
-        net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-        flatten_name = "{}_flat".format(name)
-        net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-        conf_layers.append(net[flatten_name])
-
-        # Create prior generation layer.
-        name = "{}_mbox_priorbox".format(from_layer)
-        net[name] = L.PriorBox(net[from_layer], net[data_layer], min_size=min_size,
-                clip=clip, variance=prior_variance, offset=offset)
-        if max_size:
-            net.update(name, {'max_size': max_size})
-        if aspect_ratio:
-            net.update(name, {'aspect_ratio': aspect_ratio, 'flip': flip})
-        if step:
-            net.update(name, {'step': step})
-        if img_height != 0 and img_width != 0:
-            if img_height == img_width:
-                net.update(name, {'img_size': img_height})
-            else:
-                net.update(name, {'img_h': img_height, 'img_w': img_width})
-        priorbox_layers.append(net[name])
-
-        # Create objectness prediction layer.
-        if use_objectness:
-            name = "{}_mbox_objectness".format(from_layer)
-            num_obj_output = num_priors_per_location * 2;
-            dilation=1
-            pad = int((kernel_size + (dilation - 1) * (kernel_size - 1)) - 1) / 2
-            ConvBNLayerSSD(net, from_layer, name, use_bn=use_batchnorm, use_relu=False, lr_mult=lr_mult,
-                num_output=num_obj_output, kernel_size=kernel_size, pad=pad, stride=1, use_scale=use_scale, **bn_param)
-            permute_name = "{}_perm".format(name)
-            net[permute_name] = L.Permute(net[name], order=[0, 2, 3, 1])
-            flatten_name = "{}_flat".format(name)
-            net[flatten_name] = L.Flatten(net[permute_name], axis=1)
-            objectness_layers.append(net[flatten_name])
-
-    # Concatenate priorbox, loc, and conf layers.
-    mbox_layers = []
-    name = "mbox_loc"
-    net[name] = L.Concat(*loc_layers, axis=1)
-    mbox_layers.append(net[name])
-    name = "mbox_conf"
-    net[name] = L.Concat(*conf_layers, axis=1)
-    mbox_layers.append(net[name])
-    name = "mbox_priorbox"
-    net[name] = L.Concat(*priorbox_layers, axis=2)
-    mbox_layers.append(net[name])
-    if use_objectness:
-        name = "mbox_objectness"
-        net[name] = L.Concat(*objectness_layers, axis=1)
-        mbox_layers.append(net[name])
-
-    return mbox_layers
-
-
-def CoreNetwork(config_param, net, from_layer):
-    if config_param.model_name == 'jdetnet21v2':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)
-    elif config_param.model_name == 'jdetnet21v2-s8':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21_s8(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)              
-    elif config_param.model_name == 'jdetnet21v2-fpn':
-        out_layer, out_layer_names = models.jacintonet_v2.jdetnet21_fpn(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride)
-    elif config_param.model_name == 'ssdJacintoNetV2':
-        out_layer, out_layer_names = models.jacintonet_v2.ssdJacintoNetV2(net, from_layer=from_layer,\
-          num_output=config_param.num_feature,stride_list=config_param.stride_list,\
-          dilation_list=config_param.dilation_list,\
-          freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride,\
-          ds_type=config_param.ds_type, use_batchnorm_mbox=config_param.use_batchnorm_mbox,fully_conv_at_end=config_param.fully_conv_at_end, 
-          reg_head_at_ds8=config_param.reg_head_at_ds8, concat_reg_head=config_param.concat_reg_head,
-          base_nw_3_head=config_param.base_nw_3_head, first_hd_same_op_ch=config_param.first_hd_same_op_ch,
-          num_intermediate=config_param.num_intermediate, rhead_name_non_linear=config_param.rhead_name_non_linear,
-          chop_num_heads=config_param.chop_num_heads)
-    elif 'mobiledetnet' in config_param.model_name:
-        #out_layer = models.mobilenet.mobiledetnet(net, from_layer=from_layer,\
-        #  num_output=config_param.num_feature,stride_list=config_param.stride_list,dilation_list=config_param.dilation_list,\
-        #  freeze_layers=config_param.freeze_layers, output_stride=config_param.feature_stride, wide_factor=wide_factor)
-        wide_factor = float(config_param.model_name.split('-')[1])
-        out_layer, out_layer_names = models.mobilenet.mobiledetnet(net, from_layer=from_layer, wide_factor=wide_factor, num_intermediate=config_param.num_intermediate)
-    else:
-        ValueError("Invalid model name")
-
-    return net, out_layer, out_layer_names
-
-
-def get_arguments():
-    parser = argparse.ArgumentParser()   
-    parser.add_argument('--config_param', type=str, default=None, help='Extra config parameters')      
-    parser.add_argument('--solver_param', type=str, default=None, help='Extra solver parameters')        
-    return parser.parse_args()
-      
-def main(): 
-    args = get_arguments()
-   
-    if args.solver_param != None:
-      print(args.solver_param)
-      args.solver_param = ast.literal_eval(args.solver_param) 
-            
-    if args.config_param != None:
-      print(args.config_param)
-      args.config_param = ast.literal_eval(args.config_param) 
-            
-    #Start populating config_param
-    config_param = OrderedDict()
-  
-    #Names
-    config_param.config_name = 'image-objdet'
-    config_param.model_name = "jacintonet11"
-    config_param.dataset = "nodataset"       
-    config_param.pretrain_model = None
-                          
-    ### Modify the following parameters accordingly ###
-    # The directory which contains the caffe code.
-    # We assume you are running the script at the CAFFE_ROOT.
-    config_param.caffe_root = os.environ['CAFFE_ROOT'] if 'CAFFE_ROOT' in os.environ else None
-    if config_param.caffe_root == None:
-      config_param.caffe_root = os.environ['CAFFE_HOME'] if 'CAFFE_HOME' in os.environ else None
-    if config_param.caffe_root != None:
-      config_param.caffe_root = config_param.caffe_root + '/build/tools/caffe.bin'
-    config_param.caffe_cmd = 'train'
-
-    print("caffe_root = : ",  config_param.caffe_root)
-
-    # Set true if you want to start training right after generating all files.
-    config_param.run_soon = False
-    # Set true if you want to load from most recently saved snapshot.
-    # Otherwise, we will load from the pretrain_model defined below.
-    config_param.resume_training = True
-    # If true, Remove old model files.
-    config_param.remove_old_models = False
-    config_param.display_sparsity = False
-    
-    # Specify the batch sampler.
-    config_param.resize_width = 512
-    config_param.resize_height = 512
-    config_param.crop_width = config_param.resize_width
-    config_param.crop_height = config_param.resize_height
-
-    #feature stride can be 16, 32. 32 provides the best radeoff
-    config_param.feature_stride = 32
-    config_param.num_feature = 512 #number of feature channels
-    config_param.threads = 4
-    # The database file for training data. Created by data/VOC0712/create_data.sh
-    config_param.train_data = "/data/hdd/datasets/object-detect/other/pascal-voc/VOCdevkit/VOC0712/lmdb/VOC0712_trainval_lmdb"
-    # The database file for testing data. Created by data/VOC0712/create_data.sh
-    config_param.test_data = "/data/hdd/datasets/object-detect/other/pascal-voc/VOCdevkit/VOC0712/lmdb/VOC0712_test_lmdb"
-
-    config_param.stride_list = None
-    config_param.dilation_list = None
-
-    config_param.mean_value = 128 #used in a bias layer in the net.
-
-    
-    # If true, use batch norm for all newly added layers.
-    # Currently only the non batch norm version has been tested.
-    config_param.use_batchnorm = False
-    config_param.use_scale = False
-    
-    config_param.lr_mult = 1
-
-    # Which layers to freeze (no backward) during training.
-    config_param.freeze_layers = []
-    # Defining which GPUs to use.
-    config_param.gpus = "0,1" #gpus = "0"  
-
-    config_param.batch_size = 32
-    config_param.accum_batch_size = 32
-
-    # Evaluate on whole test set.
-    config_param.num_test_image = 4952
-    config_param.test_batch_size = 8
-    
-    # Stores the test image names and sizes. Created by data/VOC0712/create_list.sh
-    config_param.name_size_file = "/user/a0393608/files/work/code/vision/github/weiliu89_ssd/caffe/data/VOC0712/test_name_size.txt"
-    # Stores LabelMapItem.
-    config_param.label_map_file = "/user/a0393608/files/work/code/vision/github/weiliu89_ssd/caffe/data/VOC0712/labelmap_voc.prototxt"
-
-    # minimum dimension of input image
-    config_param.log_space_steps = False #True
-    config_param.min_ratio = 10 #5 #20     # in percent %
-    config_param.max_ratio = 90            # in percent %
-    config_param.num_classes = 21
-    
-    # MultiBoxLoss parameters initialization.
-    config_param.share_location = True
-    config_param.background_label_id=0
-    config_param.use_difficult_gt = True
-    config_param.ignore_difficult_gt = False
-    config_param.evaluate_difficult_gt = False
-    config_param.normalization_mode = P.Loss.VALID
-    config_param.code_type = P.PriorBox.CENTER_SIZE
-    config_param.ignore_cross_boundary_bbox = False
-    config_param.mining_type = P.MultiBoxLoss.MAX_NEGATIVE
-    config_param.neg_pos_ratio = 3.
-    config_param.loc_weight = (config_param.neg_pos_ratio + 1.) / 4.
-    config_param.min_dim = -1
-    config_param.aspect_ratios_type=0
-    #need it for COCO which may have gray scale image
-    config_param.force_color = 0 
-
-    #Update from params given from outside
-    #if args.config_param != None:
-    #  config_param.update(args.config_param)   
-    if args.config_param != None: 
-      for k in args.config_param.keys():
-        config_param.__setattr__(k,args.config_param[k])
-        config_param.__setitem__(k,args.config_param[k])
-
-    if config_param.min_dim == -1:
-      config_param.min_dim = int((config_param.crop_width + config_param.crop_height)/2)
-
-    if config_param.ds_fac == 16: 
-      config_param.stride_list = [2,2,2,2,1]
-      config_param.dilation_list = [1,1,1,1,2]
-      config_param.feature_stride = 16
-    elif config_param.ds_fac == 32: 
-      config_param.stride_list = [2,2,2,2,2]
-      config_param.dilation_list = [1,1,1,1,1]
-      config_param.feature_stride = 32
-   
-    print("config_param.ds_fac :", config_param.ds_fac)
-    print("config_param.stride_list :", config_param.stride_list)
-    resize = "{}x{}".format(config_param.resize_width, config_param.resize_height)
-    config_param.batch_sampler = [
-            {
-                    'sampler': {
-                            },
-                    'max_trials': 1,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.1,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.3,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.5,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.7,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'min_jaccard_overlap': 0.9,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            {
-                    'sampler': {
-                            'min_scale': 0.3,
-                            'max_scale': 1.0,
-                            'min_aspect_ratio': 0.5,
-                            'max_aspect_ratio': 2.0,
-                            },
-                    'sample_constraint': {
-                            'max_jaccard_overlap': 1.0,
-                            },
-                    'max_trials': 50,
-                    'max_sample': 1,
-            },
-            ]
-    config_param.train_transform_param = {
-            'mirror': True,
-            'mean_value': [0, 0, 0],
-            'force_color':config_param.force_color,
-            'resize_param': {
-                    'prob': 1,
-                    'resize_mode': P.Resize.WARP,
-                    'height': config_param.resize_height,
-                    'width': config_param.resize_width,
-                    'interp_mode': [
-                            P.Resize.LINEAR,
-                            P.Resize.AREA,
-                            P.Resize.NEAREST,
-                            P.Resize.CUBIC,
-                            P.Resize.LANCZOS4,
-                            ],
-                    },
-            'distort_param': {
-                    'brightness_prob': 0.5,
-                    'brightness_delta': 32,
-                    'contrast_prob': 0.5,
-                    'contrast_lower': 0.5,
-                    'contrast_upper': 1.5,
-                    'hue_prob': 0.5,
-                    'hue_delta': 18,
-                    'saturation_prob': 0.5,
-                    'saturation_lower': 0.5,
-                    'saturation_upper': 1.5,
-                    'random_order_prob': 0.0,
-                    },
-            'expand_param': {
-                    'prob': 0.5,
-                    'max_expand_ratio': 4.0,
-                    },
-            'emit_constraint': {
-                'emit_type': caffe_pb2.EmitConstraint.CENTER,
-                },
-      'crop_h': config_param.crop_height,
-      'crop_w': config_param.crop_width
-            }
-    config_param.test_transform_param = {
-            'mean_value': [0, 0, 0],
-            'force_color':config_param.force_color,
-            'resize_param': {
-                    'prob': 1,
-                    'resize_mode': P.Resize.WARP,
-                    'height': config_param.resize_height,
-                    'width': config_param.resize_width,
-                    'interp_mode': [P.Resize.LINEAR],
-                    },
-      'crop_h': config_param.crop_height,
-      'crop_w': config_param.crop_width          
-            }
-
-        
-    # Modify the job name if you want.
-    #print("config_name is {}".format(config_param.config_name))
-    config_param.base_name = config_param.config_name
-    config_param.job_name = config_param.base_name
-
-    # Base dir
-    config_param.base_dir = config_param.job_name
-    # Directory which stores the model .prototxt file.
-    config_param.save_dir = config_param.job_name
-    # Directory which stores the snapshot of models.
-    config_param.snapshot_dir = config_param.job_name
-    # Directory which stores the job script and log file.
-    config_param.job_dir = config_param.job_name
-    # Directory which stores the detection results.
-    config_param.output_result_dir = "" #"{}/results".format(config_param.job_name)
-        
-    # model definition files.
-    config_param.train_net_file = "{}/train.prototxt".format(config_param.save_dir)
-    config_param.test_net_file = "{}/test.prototxt".format(config_param.save_dir)
-    config_param.deploy_net_file = "{}/deploy.prototxt".format(config_param.save_dir)
-    config_param.solver_file = "{}/solver.prototxt".format(config_param.save_dir)
-    # snapshot prefix.
-    config_param.snapshot_prefix = "{}/{}_{}".format(config_param.snapshot_dir, config_param.dataset, config_param.model_name)
-    # job script path.
-    job_file_base_name = 'run' 
-    config_param.job_file_base = "{}/{}".format(config_param.job_dir, job_file_base_name)
-    config_param.log_file = "{}.log".format(config_param.job_file_base)    
-    config_param.job_file = "{}.sh".format(config_param.job_file_base)
-   
-    # MultiBoxLoss parameters.
-    multibox_loss_param = {
-        'loc_loss_type': P.MultiBoxLoss.SMOOTH_L1,
-        'conf_loss_type': P.MultiBoxLoss.SOFTMAX,
-        'loc_weight': config_param.loc_weight,
-        'num_classes': config_param.num_classes,
-        'share_location': config_param.share_location,
-        'match_type': P.MultiBoxLoss.PER_PREDICTION,
-        'overlap_threshold': 0.5,
-        'use_prior_for_matching': True,
-        'background_label_id': config_param.background_label_id,
-        'use_difficult_gt': config_param.use_difficult_gt,
-        'ignore_difficult_gt': config_param.ignore_difficult_gt,
-        'mining_type': config_param.mining_type,
-        'neg_pos_ratio': config_param.neg_pos_ratio,
-        'neg_overlap': 0.5,
-        'code_type': config_param.code_type,
-        'ignore_cross_boundary_bbox': config_param.ignore_cross_boundary_bbox,
-        }
-    loss_param = {
-        'normalization': config_param.normalization_mode,
-        }
-
-    if config_param.feature_stride != 16 and config_param.feature_stride != 32:
-        ValueError("config_param.feature_stride {} is incorrect".format(config_param.feature_stride))
-    
-
-    config_param.flip = True
-    config_param.clip = False
-
-    # Solver parameters.
-    # Defining which GPUs to use.
-    config_param.gpulist = config_param.gpus.split(",")
-    config_param.num_gpus = len(config_param.gpulist)
-   
-    # Divide the mini-batch to different GPUs.
-    iter_size = int(math.ceil(config_param.accum_batch_size/config_param.batch_size))
-    solver_mode = P.Solver.CPU
-    device_id = 0
-    batch_size_per_device = config_param.batch_size
-    if config_param.num_gpus > 0:
-      batch_size_per_device = int(math.ceil(float(config_param.batch_size) / config_param.num_gpus))
-      iter_size = int(math.ceil(float(config_param.accum_batch_size) / (batch_size_per_device * config_param.num_gpus)))
-      solver_mode = P.Solver.GPU
-      device_id = int(config_param.gpulist[0])
-
-    # Ideally test_batch_size should be divisible by num_test_image,
-    # otherwise mAP will be slightly off the true value.
-    test_iter = int(math.ceil(float(config_param.num_test_image) / config_param.test_batch_size))
-
-    solver_param = {
-        # Train parameters
-        'type': "SGD",
-        'base_lr': 1e-3,
-        'max_iter': 32000, 
-        'weight_decay': 0.0005,
-        'lr_policy': "multistep",
-        'power': 1.0,
-        'stepvalue': [24000, 30000, 32000],
-        'gamma': 0.1,
-        'momentum': 0.9,
-        'iter_size': iter_size,
-        'snapshot': 2000,
-        'display': 100,
-        'average_loss': 10,
-        'type': "SGD",
-        'solver_mode': solver_mode,
-        'device_id': device_id,
-        'debug_info': False,
-        'snapshot_after_train': True,
-        # Test parameters
-        'test_iter': [test_iter],
-        'test_interval': 2000,
-        'eval_type': "detection",
-        'ap_version': "11point",
-        'test_initialization': True,
-        'random_seed': 33,
-        'show_per_class_result': True,
-        }
-
-    #if args.solver_param != None:
-    #  solver_param.update(args.solver_param)       
-    if args.solver_param != None: 
-      for k in args.solver_param.keys():
-        solver_param.__setitem__(k,args.solver_param[k])    
-        #solver_param.__setattr__(k,args.solver_param[k])
-    
-    # parameters for generating detection output.
-    det_out_param = {
-        'num_classes': config_param.num_classes,
-        'share_location': config_param.share_location,
-        'background_label_id': config_param.background_label_id,
-        'nms_param': {'nms_threshold': 0.45, 'top_k': 400},
-        'save_output_param': {
-            'output_directory': config_param.output_result_dir,
-            'output_name_prefix': "comp4_det_test_",
-            'output_format': "VOC",
-            'label_map_file': config_param.label_map_file,
-            'name_size_file': config_param.name_size_file,
-            'num_test_image': config_param.num_test_image,
-            },
-        'keep_top_k': 200,
-        'confidence_threshold': 0.01,
-        'code_type': config_param.code_type,
-        }
-
-    # parameters for evaluating detection results.
-    det_eval_param = {
-        'num_classes': config_param.num_classes,
-        'background_label_id': config_param.background_label_id,
-        'overlap_threshold': 0.5,
-        'evaluate_difficult_gt': config_param.evaluate_difficult_gt,
-        'name_size_file': config_param.name_size_file,
-        }
-
-    ### Hopefully you don't need to change the following ###
-    # Check file.
-    check_if_exist(config_param.train_data)
-    check_if_exist(config_param.test_data)
-    check_if_exist(config_param.label_map_file)
-    if config_param.pretrain_model != None:    
-      check_if_exist(config_param.pretrain_model)
-    make_if_not_exist(config_param.base_dir)  
-    make_if_not_exist(config_param.save_dir)
-    make_if_not_exist(config_param.job_dir)
-    make_if_not_exist(config_param.snapshot_dir)
-
-    # Create train net.
-    net = caffe.NetSpec()
-    net.data, net.label = CreateAnnotatedDataLayer(config_param.train_data, batch_size=config_param.batch_size,
-            train=True, output_label=True, label_map_file=config_param.label_map_file,
-            transform_param=config_param.train_transform_param, batch_sampler=config_param.batch_sampler, 
-            threads=config_param.threads)
-
-    out_layer = 'data'
-    bias_kwargs = { #fixed value with lr_mult=0
-        'param': [dict(lr_mult=0, decay_mult=0)],
-        'filler': dict(type='constant', value=(-config_param.mean_value)),
-        }       
-    net['data/bias'] = L.Bias(net[out_layer], in_place=False, **bias_kwargs)
-    out_layer = 'data/bias'           
-
-    net, out_layer, out_layer_names = CoreNetwork(config_param, net, out_layer)
-
-    if (config_param.model_name == 'jdetnet21v2'):
-        config_param.steps = [] #[16, 32, 64, 128]
-        config_param.mbox_source_layers = out_layer_names
-    elif (config_param.model_name == 'jdetnet21v2-s8'):
-        config_param.steps = [] #[8, 16, 32, 64, 128, 256]
-        config_param.mbox_source_layers = out_layer_names
-    elif (config_param.model_name == 'jdetnet21v2-fpn'):
-        config_param.steps = [] #[16, 16, 32, 64, 128, 256]
-        config_param.mbox_source_layers = out_layer_names
-    if (config_param.model_name == 'ssdJacintoNetV2'):
-      config_param.mbox_source_layers = out_layer_names
-      config_param.steps = []
-      if config_param.ds_type == 'DFLT':
-        #config_param.mbox_source_layers = ['res3a_branch2b/relu', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2', 'conv10_2']
-        config_param.mbox_source_layers = out_layer_names
-        if config_param.base_nw_3_head:
-          config_param.mbox_source_layers.append('ctx_output{}/relu'.format(len(config_param.mbox_source_layers)+1))
-    elif config_param.model_name == 'vgg16':
-        # conv4_3 ==> 38 x 38
-        # fc7 ==> 19 x 19
-        # conv6_2 ==> 10 x 10
-        # conv7_2 ==> 5 x 5
-        # conv8_2 ==> 3 x 3
-        # conv9_2 ==> 1 x 1
-        config_param.mbox_source_layers = ['conv4_3', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2']
-        config_param.steps = [8, 16, 32, 64, 100, 300]
-    elif 'mobiledetnet' in config_param.model_name:
-        config_param.mbox_source_layers = out_layer_names
-        config_param.steps = [] #[16, 32, 64, 128, 256] #[8, 16, 32, 64, 128, 256]
-    else:
-        print("Unknown detection network. Assuming default step sizes")
-        config_param.steps = []
-        config_param.mbox_source_layers = out_layer_names
-    
-    #-------------------------------------------------------------------
-    # parameters for generating priors.
-    config_param.num_steps = len(config_param.mbox_source_layers)  
-    config_param.step = int(math.floor((config_param.max_ratio - config_param.min_ratio) / config_param.num_steps))
-    config_param.min_sizes = []
-    config_param.max_sizes = []
-      
-    print("min_dim = {}".format(config_param.min_dim))
-    min_dim_to_use = config_param.min_ratio*config_param.min_dim/100
-    max_dim_to_use = config_param.max_ratio*config_param.min_dim/100
-    if config_param.log_space_steps == 1:
-      #log
-      min_max_sizes = np.logspace(np.log2(min_dim_to_use), np.log2(max_dim_to_use), num=config_param.num_steps+1, base=2)
-      config_param.min_sizes = list(min_max_sizes[0:config_param.num_steps])
-      config_param.max_sizes = list(min_max_sizes[1:config_param.num_steps+1])
-    elif config_param.log_space_steps == 0:
-      #linear
-      min_max_sizes = np.linspace(min_dim_to_use, max_dim_to_use, num=config_param.num_steps+1)
-      config_param.min_sizes = list(min_max_sizes[0:config_param.num_steps])
-      config_param.max_sizes = list(min_max_sizes[1:config_param.num_steps+1])
-    else:
-      #like original SSD
-      config_param.min_sizes, config_param.max_sizes = set_min_max_sizes(config_param)
-  
-    print("minsizes = {}".format(config_param.min_sizes))
-    print("maxsizes = {}".format(config_param.max_sizes))
-   
-    if config_param.aspect_ratios_type == 0:
-      config_param.aspect_ratios = [[2]]*config_param.num_steps 
-    else:
-      #like original SSD
-      config_param.aspect_ratios = [[2,3]]*config_param.num_steps
-      config_param.aspect_ratios[0] = [2]
-      config_param.aspect_ratios[-1] = [2]
-      config_param.aspect_ratios[-2] = [2]
-           
-    print("ARs:",config_param.aspect_ratios)
-    # L2 normalize conv4_3.
-    config_param.normalizations = [-1]*config_param.num_steps #[20, -1, -1, -1, -1, -1]
-    # variance used to encode/decode prior bboxes.
-    if config_param.code_type == P.PriorBox.CENTER_SIZE:
-      config_param.prior_variance = [0.1, 0.1, 0.2, 0.2]
-    else:
-      config_param.prior_variance = [0.1]
-
-    if config_param.chop_num_heads > 0:
-      print("Chopping heads")
-      del config_param.min_sizes[-config_param.chop_num_heads:]
-      del config_param.max_sizes[-config_param.chop_num_heads:]
-      del config_param.aspect_ratios[-config_param.chop_num_heads:]
-      del config_param.normalizations[-config_param.chop_num_heads:]
-      del config_param.mbox_source_layers[-config_param.chop_num_heads:]
-
-      print("minsizes = {}".format(config_param.min_sizes))
-      print("maxsizes = {}".format(config_param.max_sizes))
-      print("aspect_ratios = {}".format(config_param.aspect_ratios))
-      print(config_param.mbox_source_layers)
-    
-    
-    mbox_layers = CreateMultiBoxHead(net, data_layer='data', from_layers=config_param.mbox_source_layers,
-            use_batchnorm=config_param.use_batchnorm, use_scale=config_param.use_scale, min_sizes=config_param.min_sizes, max_sizes=config_param.max_sizes,
-            aspect_ratios=config_param.aspect_ratios, steps=config_param.steps, normalizations=config_param.normalizations,
-            num_classes=config_param.num_classes, share_location=config_param.share_location, flip=config_param.flip, clip=config_param.clip,
-            prior_variance=config_param.prior_variance, kernel_size=config_param.ker_mbox_loc_conf, pad=1, lr_mult=config_param.lr_mult)
-
-    # Create the MultiBoxLossLayer.
-    name = "mbox_loss"
-    mbox_layers.append(net.label)
-    net[name] = L.MultiBoxLoss(*mbox_layers, multibox_loss_param=multibox_loss_param,
-            loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')),
-            propagate_down=[True, True, False, False])
-
-    with open(config_param.train_net_file, 'w') as f:
-        print(config_param.train_net_file)
-        print('name: "{}"'.format(config_param.model_name), file=f)
-        print(net.to_proto(), file=f)
-    #shutil.copy(train_net_file, job_dir)
-
-
-    #-------------------------------------------------------------------
-    # Create test net.
-    net = caffe.NetSpec()
-    net.data, net.label = CreateAnnotatedDataLayer(config_param.test_data, batch_size=config_param.test_batch_size,
-            train=False, output_label=True, label_map_file=config_param.label_map_file,
-            transform_param=config_param.test_transform_param, threads=config_param.threads)
-
-    out_layer = 'data'
-    bias_kwargs = { #fixed value with lr_mult=0
-        'param': [dict(lr_mult=0, decay_mult=0)],
-        'filler': dict(type='constant', value=(-config_param.mean_value)),
-        }       
-    net['data/bias'] = L.Bias(net[out_layer], in_place=False, **bias_kwargs)
-    out_layer = 'data/bias'    
-    
-    net, out_layer, out_layer_names = CoreNetwork(config_param, net, out_layer)
-    
-    mbox_layers = CreateMultiBoxHead(net, data_layer='data', from_layers=config_param.mbox_source_layers,
-            use_batchnorm=config_param.use_batchnorm, use_scale=config_param.use_scale, min_sizes=config_param.min_sizes, max_sizes=config_param.max_sizes,
-            aspect_ratios=config_param.aspect_ratios, steps=config_param.steps, normalizations=config_param.normalizations,
-            num_classes=config_param.num_classes, share_location=config_param.share_location, flip=config_param.flip, clip=config_param.clip,
-            prior_variance=config_param.prior_variance, kernel_size=config_param.ker_mbox_loc_conf, pad=1, lr_mult=config_param.lr_mult)
-
-    conf_name = "mbox_conf"
-    if multibox_loss_param["conf_loss_type"] == P.MultiBoxLoss.SOFTMAX:
-      reshape_name = "{}_reshape".format(conf_name)
-      net[reshape_name] = L.Reshape(net[conf_name], shape=dict(dim=[0, -1, config_param.num_classes]))
-      softmax_name = "{}_softmax".format(conf_name)
-      net[softmax_name] = L.Softmax(net[reshape_name], axis=2)
-      flatten_name = "{}_flatten".format(conf_name)
-      net[flatten_name] = L.Flatten(net[softmax_name], axis=1)
-      mbox_layers[1] = net[flatten_name]
-    elif multibox_loss_param["conf_loss_type"] == P.MultiBoxLoss.LOGISTIC:
-      sigmoid_name = "{}_sigmoid".format(conf_name)
-      net[sigmoid_name] = L.Sigmoid(net[conf_name])
-      mbox_layers[1] = net[sigmoid_name]
-
-    net.detection_out = L.DetectionOutput(*mbox_layers,
-        detection_output_param=det_out_param,
-        include=dict(phase=caffe_pb2.Phase.Value('TEST')))
-    net.detection_eval = L.DetectionEvaluate(net.detection_out, net.label,
-        detection_evaluate_param=det_eval_param,
-        include=dict(phase=caffe_pb2.Phase.Value('TEST')))
-
-    with open(config_param.test_net_file, 'w') as f:
-        print('name: "{}_test"'.format(config_param.model_name), file=f)
-        print(net.to_proto(verbose=False), file=f)
-    if config_param.save_dir!=config_param.job_dir:
-      shutil.copy(config_param.test_net_file, config_param.job_dir)
-
-    # Create deploy net.
-    # Remove the first and last layer from test net.
-    deploy_net = net
-    with open(config_param.deploy_net_file, 'w') as f:
-        net_param = deploy_net.to_proto()
-        # Remove the first (AnnotatedData) and last (DetectionEvaluate) layer from test net.
-        del net_param.layer[0]
-        del net_param.layer[-1]
-        net_param.name = '{}_deploy'.format(config_param.model_name)
-        net_param.input.extend(['data'])
-        net_param.input_shape.extend([
-            caffe_pb2.BlobShape(dim=[1, 3, config_param.resize_height, config_param.resize_width])])
-        print(net_param, file=f)
-    if config_param.save_dir!=config_param.job_dir:        
-      shutil.copy(config_param.deploy_net_file, config_param.job_dir)
-
-    # Create solver.
-    solver = caffe_pb2.SolverParameter(
-            train_net=config_param.train_net_file,
-            test_net=[config_param.test_net_file],
-            snapshot_prefix=config_param.snapshot_prefix,
-            **solver_param)
-            
-    with open(config_param.solver_file, 'w') as f:
-        print(solver, file=f)
-    if config_param.save_dir!=config_param.job_dir:        
-      shutil.copy(solver_file, job_dir)
-
-    max_iter = 0
-    # Find most recent snapshot.
-    for file in os.listdir(config_param.snapshot_dir):
-      if file.endswith(".solverstate"):
-        basename = os.path.splitext(file)[0]
-        iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-        if iter > max_iter:
-          max_iter = iter
-
-    train_src_param = None
-    if config_param.pretrain_model != None:
-      train_src_param = '--weights="{}" \\\n'.format(config_param.pretrain_model)
-    if config_param.resume_training:
-      if max_iter > 0:
-        train_src_param = '--snapshot="{}_iter_{}.solverstate" \\\n'.format(config_param.snapshot_prefix, max_iter)
-
-    if config_param.remove_old_models:
-      # Remove any snapshots smaller than max_iter.
-      for file in os.listdir(config_param.snapshot_dir):
-        if file.endswith(".solverstate"):
-          basename = os.path.splitext(file)[0]
-          iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-          if max_iter > iter:
-            os.remove("{}/{}".format(config_param.snapshot_dir, file))
-        if file.endswith(".caffemodel"):
-          basename = os.path.splitext(file)[0]
-          iter = int(basename.split("{}_iter_".format(config_param.model_name))[1])
-          if max_iter > iter:
-            os.remove("{}/{}".format(config_param.snapshot_dir, file))
-
-    # Create job file.
-    with open(config_param.job_file, 'w') as f:
-      #f.write('cd {}\n'.format(config_param.caffe_root))
-      f.write('{} {} \\\n'.format(config_param.caffe_root, config_param.caffe_cmd))    
-      if(config_param.caffe_cmd == 'test' or config_param.caffe_cmd == 'test_detection'):
-        f.write('--model="{}" \\\n'.format(config_param.test_net_file))
-        f.write('--iterations="{}" \\\n'.format(solver_param['test_iter'][0]))       
-        if config_param.display_sparsity:
-          f.write('--display_sparsity=1 \\\n')
-      else:
-        f.write('--solver="{}" \\\n'.format(config_param.solver_file))      
-      if train_src_param != None:
-        f.write(train_src_param)
-      if solver_param['solver_mode'] == P.Solver.GPU:
-        f.write('--gpu "{}" 2>&1 | tee {}\n'.format(config_param.gpus, config_param.log_file))
-      else:
-        f.write('2>&1 | tee {}\n'.format(config_param.log_file))
-
-    # Copy the python script to job_dir.
-    py_file = os.path.abspath(__file__)
-    shutil.copy(py_file, config_param.job_dir)
-    
-    #copy some other utils scripts
-    shutil.copy(os.getcwd() + '/train_image_object_detection.sh', config_param.job_dir)
-    shutil.copy(os.getcwd() + '/models/jacintonet_v2.py', config_param.job_dir)
-
-    # Run the job.
-    os.chmod(config_param.job_file, stat.S_IRWXU)
-    if config_param.run_soon:
-      subprocess.call(config_param.job_file, shell=True)
-  
-  
-if __name__ == "__main__":
-  main()  

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/jacintonet_v2.py b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/jacintonet_v2.py
deleted file mode 100755 (executable)
index a19b4d4..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/jacintonet_v2.py
+++ /dev/null
@@ -1,703 +0,0 @@
-from __future__ import print_function
-import caffe
-from models.model_libs import *
-
-def jacintonet11_base(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=1000, stride_list=None, dilation_list=None, freeze_layers=None, in_place=True):  
-   #Top and Bottom blobs must be different for NVCaffe BN caffe-0.15 (in_place=False), but no such constraint for caffe-0.16
-   
-   #--     
-   stage=0
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]   
-   
-   out_layer = 'conv1a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=32, kernel_size=[5,5], pad=2*dilation, stride=stride, group=1, dilation=dilation, in_place=in_place)  
-   
-   from_layer = out_layer
-   out_layer = 'conv1b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=32, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)       
-   
-   #--     
-   stage=1
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]   
-        
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool1'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)       
-      
-   from_layer = out_layer
-   out_layer = 'res2a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res2a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)     
-     
-   #--     
-   stage=2
-   stride=stride_list[stage]
-   dilation=dilation_list[stage] 
-        
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}       
-   from_layer = out_layer
-   out_layer = 'pool2'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)     
-         
-   from_layer = out_layer
-   out_layer = 'res3a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=128, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res3a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=128, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)    
-   
-   #--       
-   stage=3
-   stride=stride_list[stage]
-   dilation=dilation_list[stage] 
-      
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool3'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)         
-         
-   from_layer = out_layer
-   out_layer = 'res4a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer 
-   out_layer = 'res4a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place)        
-      
-   #--      
-   stage=4
-   stride=stride_list[stage]
-   dilation=dilation_list[stage]         
-   
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':stride, 'stride':stride}   
-   from_layer = out_layer
-   out_layer = 'pool4'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)     
-
-   from_layer = out_layer
-   out_layer = 'res5a_branch2a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=512, kernel_size=[3,3], pad=dilation, stride=1, group=1, dilation=dilation, in_place=in_place)   
-   
-   from_layer = out_layer
-   out_layer = 'res5a_branch2b'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=512, kernel_size=[3,3], pad=dilation, stride=1, group=4, dilation=dilation, in_place=in_place) 
-   
-   return out_layer
-  
-  
-def jacintonet11(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=1000, stride_list=None, dilation_list=None, freeze_layers=None):  
-   if stride_list == None:
-     stride_list = [2,2,2,2,2]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1]
-   
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #--   
-   # Add global pooling layer.
-   from_layer = out_layer
-   out_layer = 'pool5'
-   net[out_layer] = L.Pooling(net[from_layer], pool=P.Pooling.AVE, global_pooling=True)
-       
-   from_layer = out_layer 
-   out_layer = 'fc'+str(num_output)
-   kwargs = { 'num_output': num_output, 
-     'param': [{'lr_mult': 1, 'decay_mult': 1}, {'lr_mult': 2, 'decay_mult': 0}], 
-     'inner_product_param': { 
-         'weight_filler': { 'type': 'msra' }, 
-         'bias_filler': { 'type': 'constant', 'value': 0 }   
-     },
-   }
-   net[out_layer] = L.InnerProduct(net[from_layer], **kwargs)    
-   
-   return out_layer
-   
-   
-def jsegnet21(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=True): 
-   in_place = True
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #--   
-   from_layer = out_layer
-   out_layer = 'out5a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=2, dilation=4) 
-   
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'out5a_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 64, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 64, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)    
-   
-   from_layer = 'res3a_branch2b' if in_place else 'res3a_branch2b/bn'
-   out_layer = 'out3a'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=1, stride=1, group=2, dilation=1) 
-   
-   from_layer = out_layer   
-   out_layer = 'out3_out5_combined'
-   net[out_layer] = L.Eltwise(net['out5a_up2'], net[from_layer])
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv1'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1) 
-      
-   from_layer = out_layer
-   out_layer = 'ctx_conv2'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv3'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-   
-   from_layer = out_layer
-   out_layer = 'ctx_conv4'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=64, kernel_size=[3,3], pad=4, stride=1, group=1, dilation=4) 
-       
-   from_layer = out_layer
-   out_layer = 'ctx_final'
-   conv_kwargs = {
-        'param': [dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)],
-        'weight_filler': dict(type='msra'),
-        'bias_term': True, 
-        'bias_filler': dict(type='constant', value=0) }   
-   net[out_layer] = L.Convolution(net[from_layer], num_output=num_output, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, **conv_kwargs) 
-         
-   from_layer = out_layer
-   out_layer = 'ctx_final/relu'
-   net[out_layer] = L.ReLU(net[from_layer], in_place=True) 
-               
-   #frozen upsampling layer   
-   if upsample:      
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up2'   
-       deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-           'convolution_param': { 'num_output': num_output, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': num_output, 'stride': 2, 
-           'weight_filler': { 'type': 'bilinear' } } }       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-               
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up4'       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs) 
-       
-       from_layer = out_layer
-       out_layer = 'out_deconv_final_up8'       
-       net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)     
-                            
-   return out_layer    
-
-
-def jdetnet21(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-      
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   
-   #---------------------------        
-   out_layer_names = []
-  
-   from_layer = 'res5a_branch2b/relu'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7'
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-
-def jdetnet21_s8(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,2] #[2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1] #[1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-
-   from_layer = 'res5a_branch2b/relu'
-   out_layer = 'conv6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=1024, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1)
-      
-   from_layer = out_layer
-   out_layer = 'conv7'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=1024, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)
-
-   #---------------------------       
-   out_layer = 'res3a_branch2b/concat'    
-   net[out_layer] = L.Concat(net['res3a_branch2a/relu'], net['res3a_branch2b/relu'])  
-         
-   out_layer = 'res4a_branch2b/concat'    
-   net[out_layer] = L.Concat(net['res4a_branch2a/relu'], net['res4a_branch2b/relu'])  
-            
-   #out_layer = 'res5a_branch2b/concat'    
-   #net[out_layer] = L.Concat(net['res5a_branch2a/relu'], net['res5a_branch2b/relu'])  
-               
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = 'conv7/relu' #'res5a_branch2b/concat' #
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':2, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':1, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   #---------------------------       
-   out_layer_names = []
-   
-   from_layer = 'res3a_branch2b/concat'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)  
-   out_layer_names += [out_layer]
-   
-   from_layer = 'res4a_branch2b/concat'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1) 
-   out_layer_names += [out_layer]
-   
-   from_layer = 'conv7/relu' #'res5a_branch2b/concat' #
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7'
-   out_layer = 'ctx_output5'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-
-#To match configuration used by original SSD script
-def ssdJacintoNetV2(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32, use_batchnorm_mbox=True, ds_type='PSP', fully_conv_at_end=True, reg_head_at_ds8=True, 
-   concat_reg_head=False, base_nw_3_head=False, first_hd_same_op_ch=False,
-   rhead_name_non_linear=False, chop_num_heads=0): 
-   
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,1]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,2]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-
-   last_base_layer_name = out_layer
-
-   if concat_reg_head:
-     out_layer = 'res4a_branch2b/concat'    
-     net[out_layer] = L.Concat(net['res4a_branch2a/relu'], net['res4a_branch2b/relu']) 
-                           
-     out_layer = 'res5a_branch2b/concat'    
-     net[out_layer] = L.Concat(net['res5a_branch2a/relu'], net['res5a_branch2b/relu'])  
-     last_base_layer_name = out_layer
-
-   if fully_conv_at_end:
-     from_layer = last_base_layer_name 
-     out_layer = 'fc6'
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=1024, kernel_size=[3,3], pad=6, stride=1, group=1, dilation=6)
-        
-     from_layer = out_layer
-     out_layer = 'fc7'
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=1024, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)
-     last_base_layer_name = out_layer
-      
-   #---------------------------     
-   out_layer_names = []
-  
-   #PSP style pool down
-   if ds_type == 'PSP':
-     if chop_num_heads < 4:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool6'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-     
-     #--
-     if chop_num_heads < 3:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool7'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if chop_num_heads < 2:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool8'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if chop_num_heads < 1:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool9'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-     #--
-     if stride_list[4] == 1:
-       pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':1, 'pad':0}      
-       from_layer = out_layer
-       out_layer = 'pool10'
-       net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   
-     #mbox_source_layers = ['res3a_branch2b_relu', 'fc7', 'conv6_2', 'conv7_2', 'conv8_2', 'conv9_2','conv10_2']
-     if rhead_name_non_linear:
-       reg_head_idx=6
-     else:
-       reg_head_idx=1
-
-     if reg_head_at_ds8:
-       from_layer = 'res3a_branch2b/relu'
-     else: 
-       if concat_reg_head:
-         from_layer = 'res4a_branch2b/concat'
-       else:  
-         from_layer = 'res4a_branch2b/relu'
-
-     out_layer = 'ctx_output{}'.format(reg_head_idx)
-
-     if rhead_name_non_linear:
-       reg_head_idx=0
-
-     reg_head_idx += 1
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>first_hd_same_op_ch, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)              
-     out_layer_names += [out_layer]
-     
-     from_layer = last_base_layer_name 
-     out_layer = 'ctx_output{}'.format(reg_head_idx)
-     reg_head_idx += 1
-     out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-     out_layer_names += [out_layer]
-    
-     if chop_num_heads < 4:
-       from_layer = 'pool6'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 3:
-       from_layer = 'pool7'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 2:
-       from_layer = 'pool8'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if chop_num_heads < 1:
-       from_layer = 'pool9'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if stride_list[4] == 1:
-       from_layer = 'pool10'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     if base_nw_3_head:
-       #by default 2 heads are connected in base n/w are at res3a and res5a (at the end of base n/w)
-       from_layer = 'res4a_branch2b/relu'
-       out_layer = 'ctx_output{}'.format(reg_head_idx)
-       reg_head_idx += 1
-       out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_output=num_intermediate>>1, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-       out_layer_names += [out_layer]
-    
-     return out_layer, out_layer_names
-   else:
-     out_layer_names += ['res3a_branch2b/relu']
-     if fully_conv_at_end:
-       out_layer_names += ['fc7']
-     
-     ssd_size = '512x512'
-     training_type = 'SSD'
-     if (ssd_size == '512x512') and (training_type == 'SSD'):
-                       #32x32    #16x16    #8x8      #4x4      #2x2
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,   1,   4,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,   1,   1,]
-     elif (ssd_size == '300x300') and (training_type == 'SSD'):
-                      #19x19     #10x10    #5x5      #3x3
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   0,   0,   0,]
-       strides=       [  1,   2,   1,   2,   1,   1,   1,   1,]
-     elif (ssd_size == '256x256') and (training_type == 'SSD'):
-                      #16x16     #8x8    #8x8      #4x4
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   0,   0,   0,]
-       strides=       [  1,   2,   1,   1,   1,   1,   1,   1,]
-     elif (ssd_size == '512x512') and (training_type == 'IMGNET'):
-                       #16x16    #8x8      #4x4      #2x2
-       num_outputs =  [256, 512, 128, 256, 128, 256, 128, 256,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,]
-     elif (ssd_size == '300x300') and (training_type == 'IMGNET'):
-                       #10x10    #5x5      #3x3       #2x2   
-       num_outputs =  [256, 512, 128, 256, 128, 256,  64, 128,]
-       kernel_sizes = [  1,   3,   1,   3,   1,   3,   1,   3,]
-       pads =         [  0,   1,   0,   1,   0,   1,   0,   1,]
-       strides=       [  1,   2,   1,   2,   1,   2,   1,   2,]
-
-     # index of first additional layer after base network
-     first_idx = 6
-     from_layer = net.keys()[-1]
-     blk_idx = first_idx
-     lr_mult = 1 
-     bn_postfix='/bn'
-     scale_postfix='/scale'
-     print("num_outputs: ", num_outputs) 
-     for idx in range (0, len(num_outputs)):
-       print("blk_index: ", blk_idx)
-       # TODO(weiliu89): Construct the name using the last layer to avoid duplication.
-       one_or_two = (idx%2) + 1
-       out_layer = "conv{}_{}".format(blk_idx, one_or_two)
-       ConvBNLayer(net, from_layer, out_layer, use_batchnorm_mbox, use_relu, num_outputs[idx],
-           kernel_sizes[idx], pads[idx], strides[idx], lr_mult=lr_mult, bn_postfix=bn_postfix,
-           scale_postfix=scale_postfix)
-       out_layer_names += [out_layer]
-       from_layer = out_layer
-       if one_or_two == 2:
-         blk_idx = blk_idx + 1
-
-     return out_layer, out_layer_names
-   #---------------------------       
-
-   
-   
-def jdetnet21_fpn(net, from_layer=None, use_batchnorm=True, use_relu=True, num_output=20, stride_list=None, dilation_list=None, freeze_layers=None, 
-   upsample=False, num_intermediate=512, output_stride=32): 
-   in_place = True   
-   eltwise_final = False
-   if stride_list == None:
-     stride_list = [2,2,2,2,2]
-   if dilation_list == None:
-     dilation_list = [1,1,1,1,1]
-
-   out_layer = jacintonet11_base(net, from_layer=from_layer, use_batchnorm=use_batchnorm, use_relu=use_relu, \
-      num_output=num_output, stride_list=stride_list, dilation_list=dilation_list, freeze_layers=freeze_layers)
-   
-   #---------------------------     
-   #PSP style pool down
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-   from_layer = out_layer
-   out_layer = 'pool6'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param) 
-   
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':2, 'stride':2, 'pad':0}      
-   from_layer = out_layer
-   out_layer = 'pool7'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-   #--
-   pooling_param = {'pool':P.Pooling.MAX, 'kernel_size':3, 'stride':1, 'pad':1}      
-   from_layer = out_layer
-   out_layer = 'pool8'
-   net[out_layer] = L.Pooling(net[from_layer], pooling_param=pooling_param)  
-
-   #---------------------------   
-   #FPN layers start here  
-   #---------------------------  512->256  
-   from_layer = out_layer
-   out_layer = 'pool8_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-   
-   out_layer_1x1 = 'pool7_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'pool7', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)    
-            
-   from_layer = out_layer   
-   out_layer = 'pool7_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-              
-   #---------------------------  512->256  
-   from_layer = out_layer
-   out_layer = 'pool7_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'pool7_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-            
-   out_layer_1x1 = 'pool6_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'pool6', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)     
-            
-   from_layer = out_layer   
-   out_layer = 'pool6_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-          
-   #---------------------------  512->256   
-   from_layer = out_layer
-   out_layer = 'pool6_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'pool6_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-            
-   out_layer_1x1 = 'res5a_branch2b_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res5a_branch2b/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)         
-        
-   from_layer = out_layer   
-   out_layer = 'res5a_branch2b_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-              
-   #---------------------------   256->256 
-   from_layer = out_layer
-   out_layer = 'res5a_branch2b_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place) 
-      
-   #frozen upsampling layer
-   from_layer = out_layer 
-   out_layer = 'res5a_branch2a_up2'  
-   deconv_kwargs = {  'param': { 'lr_mult': 0, 'decay_mult': 0 },
-       'convolution_param': { 'num_output': 256, 'bias_term': False, 'pad': 1, 'kernel_size': 4, 'group': 256, 'stride': 2, 
-       'weight_filler': { 'type': 'bilinear' } } }
-   net[out_layer] = L.Deconvolution(net[from_layer], **deconv_kwargs)   
-       
-   out_layer_1x1 = 'res4a_branch2b_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res4a_branch2b/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)  
-                         
-   from_layer = out_layer   
-   out_layer = 'res4a_branch2b_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-          
-   #---------------------------   256->256 
-   from_layer = out_layer
-   out_layer = 'res4a_branch2b_upconv'
-   out_layer = ConvBNLayer(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=256, kernel_size=[3,3], pad=1, stride=1, group=1, dilation=1, in_place=in_place)    
-       
-   out_layer_1x1 = 'res4a_branch2a_1x1'   
-   out_layer_1x1 = ConvBNLayer(net, 'res4a_branch2a/relu', out_layer_1x1, use_batchnorm, use_relu, num_output=256, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1, in_place=in_place)   
-                      
-   from_layer = out_layer   
-   out_layer = 'res4a_branch2a_plus'
-   net[out_layer] = L.Eltwise(net[out_layer_1x1], net[from_layer])
-                              
-   #---------------------------  
-   out_layer_names = []
-   
-   #SSD heads start here
-   from_layer = 'res4a_branch2a_plus'
-   out_layer = 'ctx_output1'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)   
-   out_layer_names += [out_layer]
-
-   from_layer = 'res4a_branch2b_plus'
-   out_layer = 'ctx_output2'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)          
-   out_layer_names += [out_layer]
-   
-   from_layer = 'res5a_branch2b_plus'
-   out_layer = 'ctx_output3'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool6_plus'
-   out_layer = 'ctx_output4'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool7_plus'
-   out_layer = 'ctx_output5'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   from_layer = 'pool8'
-   out_layer = 'ctx_output6'
-   out_layer = ConvBNLayerSSD(net, from_layer, out_layer, use_batchnorm, use_relu, num_output=num_intermediate, kernel_size=[1,1], pad=0, stride=1, group=1, dilation=1)        
-   out_layer_names += [out_layer]
-   
-   return out_layer, out_layer_names
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/run.log b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/run.log
deleted file mode 100755 (executable)
index 2585e7d..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/run.log
+++ /dev/null
@@ -1,13743 +0,0 @@
-I0511 11:49:27.915685  5581 caffe.cpp:902] This is NVCaffe 0.17.0 started at Fri May 11 11:49:27 2018
-I0511 11:49:27.915874  5581 caffe.cpp:904] CuDNN version: 7003
-I0511 11:49:27.915879  5581 caffe.cpp:905] CuBLAS version: 9000
-I0511 11:49:27.915882  5581 caffe.cpp:906] CUDA version: 9000
-I0511 11:49:27.915885  5581 caffe.cpp:907] CUDA driver version: 9000
-I0511 11:49:27.915890  5581 caffe.cpp:908] Arguments: 
-[0]: /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-[1]: test_detection
-[2]: --model=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize/test.prototxt
-[3]: --iterations=496
-[4]: --weights=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel
-[5]: --gpu
-[6]: 0
-I0511 11:49:27.944636  5581 gpu_memory.cpp:105] GPUMemory::Manager initialized
-I0511 11:49:27.945523  5581 gpu_memory.cpp:107] Total memory: 11713708032, Free: 11223957504, dev_info[0]: total=11713708032 free=11223957504
-I0511 11:49:27.945531  5581 caffe.cpp:406] Use GPU with device ID 0
-I0511 11:49:27.946121  5581 caffe.cpp:409] GPU device name: GeForce GTX 1080 Ti
-I0511 11:49:27.962272  5581 net.cpp:80] Initializing net from parameters: 
-name: "mobiledetnet-0.5_test"
-state {
-  phase: TEST
-  level: 0
-}
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 10
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_1/sep/scale"
-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/dw/scale"
-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
-  name: "ctx_output1"
-  type: "Convolution"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
-  name: "ctx_output2/1x1"
-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
-  name: "ctx_output2"
-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/relu"
-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
-  name: "ctx_output3/1x1"
-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
-  name: "ctx_output3"
-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/relu"
-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19
-    max_size: 88
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx
-I0511 11:49:27.962703  5581 net.cpp:110] Using FLOAT as default forward math type
-I0511 11:49:27.962710  5581 net.cpp:116] Using FLOAT as default backward math type
-I0511 11:49:27.962715  5581 layer_factory.hpp:172] Creating layer 'data' of type 'AnnotatedData'
-I0511 11:49:27.962719  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:27.963043  5581 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:49:27.963100  5581 net.cpp:200] Created Layer data (0)
-I0511 11:49:27.963106  5581 net.cpp:542] data -> data
-I0511 11:49:27.963117  5581 net.cpp:542] data -> label
-I0511 11:49:27.963129  5581 data_reader.cpp:58] Data Reader threads: 1, out queues: 1, depth: 10
-I0511 11:49:27.963138  5581 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:49:27.965538  5599 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0511 11:49:27.966433  5600 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb
-I0511 11:49:27.968072  5581 annotated_data_layer.cpp:105] output data size: 10,3,256,512
-I0511 11:49:27.968124  5581 annotated_data_layer.cpp:150] (0) Output data size: 10, 3, 256, 512
-I0511 11:49:27.968178  5581 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:49:27.968207  5581 net.cpp:260] Setting up data
-I0511 11:49:27.969072  5601 data_layer.cpp:105] (0) Parser threads: 1
-I0511 11:49:27.969077  5581 net.cpp:267] TEST Top shape for layer 0 'data' 10 3 256 512 (3932160)
-I0511 11:49:27.969082  5601 data_layer.cpp:107] (0) Transformer threads: 1
-I0511 11:49:27.969090  5581 net.cpp:267] TEST Top shape for layer 0 'data' 1 1 2 8 (16)
-I0511 11:49:27.969120  5581 layer_factory.hpp:172] Creating layer 'data_data_0_split' of type 'Split'
-I0511 11:49:27.969127  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:27.969143  5581 net.cpp:200] Created Layer data_data_0_split (1)
-I0511 11:49:27.969152  5581 net.cpp:572] data_data_0_split <- data
-I0511 11:49:27.969171  5581 net.cpp:542] data_data_0_split -> data_data_0_split_0
-I0511 11:49:27.969178  5581 net.cpp:542] data_data_0_split -> data_data_0_split_1
-I0511 11:49:27.969185  5581 net.cpp:542] data_data_0_split -> data_data_0_split_2
-I0511 11:49:27.969194  5581 net.cpp:542] data_data_0_split -> data_data_0_split_3
-I0511 11:49:27.969200  5581 net.cpp:542] data_data_0_split -> data_data_0_split_4
-I0511 11:49:27.969207  5581 net.cpp:542] data_data_0_split -> data_data_0_split_5
-I0511 11:49:27.969292  5581 net.cpp:260] Setting up data_data_0_split
-I0511 11:49:27.969300  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969305  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969310  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969314  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969318  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969322  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969326  5581 layer_factory.hpp:172] Creating layer 'data/bias' of type 'Bias'
-I0511 11:49:27.969332  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:27.969341  5581 net.cpp:200] Created Layer data/bias (2)
-I0511 11:49:27.969346  5581 net.cpp:572] data/bias <- data_data_0_split_0
-I0511 11:49:27.969350  5581 net.cpp:542] data/bias -> data/bias
-I0511 11:49:27.970402  5581 net.cpp:260] Setting up data/bias
-I0511 11:49:27.970420  5581 net.cpp:267] TEST Top shape for layer 2 'data/bias' 10 3 256 512 (3932160)
-I0511 11:49:27.970438  5581 layer_factory.hpp:172] Creating layer 'conv1' of type 'Convolution'
-I0511 11:49:27.970444  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:27.970474  5581 net.cpp:200] Created Layer conv1 (3)
-I0511 11:49:27.970479  5581 net.cpp:572] conv1 <- data/bias
-I0511 11:49:27.970485  5581 net.cpp:542] conv1 -> conv1
-I0511 11:49:28.457382  5581 net.cpp:260] Setting up conv1
-I0511 11:49:28.457409  5581 net.cpp:267] TEST Top shape for layer 3 'conv1' 10 16 128 256 (5242880)
-I0511 11:49:28.457423  5581 layer_factory.hpp:172] Creating layer 'conv1/bn' of type 'BatchNorm'
-I0511 11:49:28.457432  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.457450  5581 net.cpp:200] Created Layer conv1/bn (4)
-I0511 11:49:28.457458  5581 net.cpp:572] conv1/bn <- conv1
-I0511 11:49:28.457474  5581 net.cpp:527] conv1/bn -> conv1 (in-place)
-I0511 11:49:28.458456  5581 net.cpp:260] Setting up conv1/bn
-I0511 11:49:28.458472  5581 net.cpp:267] TEST Top shape for layer 4 'conv1/bn' 10 16 128 256 (5242880)
-I0511 11:49:28.458489  5581 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Scale'
-I0511 11:49:28.458511  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.458524  5581 net.cpp:200] Created Layer conv1/scale (5)
-I0511 11:49:28.458535  5581 net.cpp:572] conv1/scale <- conv1
-I0511 11:49:28.458544  5581 net.cpp:527] conv1/scale -> conv1 (in-place)
-I0511 11:49:28.458587  5581 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Bias'
-I0511 11:49:28.458595  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.458706  5581 net.cpp:260] Setting up conv1/scale
-I0511 11:49:28.458714  5581 net.cpp:267] TEST Top shape for layer 5 'conv1/scale' 10 16 128 256 (5242880)
-I0511 11:49:28.458745  5581 layer_factory.hpp:172] Creating layer 'relu1' of type 'ReLU'
-I0511 11:49:28.458750  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.458756  5581 net.cpp:200] Created Layer relu1 (6)
-I0511 11:49:28.458762  5581 net.cpp:572] relu1 <- conv1
-I0511 11:49:28.458767  5581 net.cpp:527] relu1 -> conv1 (in-place)
-I0511 11:49:28.458786  5581 net.cpp:260] Setting up relu1
-I0511 11:49:28.458792  5581 net.cpp:267] TEST Top shape for layer 6 'relu1' 10 16 128 256 (5242880)
-I0511 11:49:28.458797  5581 layer_factory.hpp:172] Creating layer 'conv2_1/dw' of type 'Convolution'
-I0511 11:49:28.458802  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.458815  5581 net.cpp:200] Created Layer conv2_1/dw (7)
-I0511 11:49:28.458822  5581 net.cpp:572] conv2_1/dw <- conv1
-I0511 11:49:28.458827  5581 net.cpp:542] conv2_1/dw -> conv2_1/dw
-I0511 11:49:28.459959  5581 net.cpp:260] Setting up conv2_1/dw
-I0511 11:49:28.459969  5581 net.cpp:267] TEST Top shape for layer 7 'conv2_1/dw' 10 16 128 256 (5242880)
-I0511 11:49:28.459975  5581 layer_factory.hpp:172] Creating layer 'conv2_1/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.459987  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.459997  5581 net.cpp:200] Created Layer conv2_1/dw/bn (8)
-I0511 11:49:28.460002  5581 net.cpp:572] conv2_1/dw/bn <- conv2_1/dw
-I0511 11:49:28.460012  5581 net.cpp:527] conv2_1/dw/bn -> conv2_1/dw (in-place)
-I0511 11:49:28.460278  5581 net.cpp:260] Setting up conv2_1/dw/bn
-I0511 11:49:28.460285  5581 net.cpp:267] TEST Top shape for layer 8 'conv2_1/dw/bn' 10 16 128 256 (5242880)
-I0511 11:49:28.460301  5581 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Scale'
-I0511 11:49:28.460306  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460314  5581 net.cpp:200] Created Layer conv2_1/dw/scale (9)
-I0511 11:49:28.460322  5581 net.cpp:572] conv2_1/dw/scale <- conv2_1/dw
-I0511 11:49:28.460330  5581 net.cpp:527] conv2_1/dw/scale -> conv2_1/dw (in-place)
-I0511 11:49:28.460362  5581 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Bias'
-I0511 11:49:28.460368  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460477  5581 net.cpp:260] Setting up conv2_1/dw/scale
-I0511 11:49:28.460484  5581 net.cpp:267] TEST Top shape for layer 9 'conv2_1/dw/scale' 10 16 128 256 (5242880)
-I0511 11:49:28.460496  5581 layer_factory.hpp:172] Creating layer 'relu2_1/dw' of type 'ReLU'
-I0511 11:49:28.460502  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460507  5581 net.cpp:200] Created Layer relu2_1/dw (10)
-I0511 11:49:28.460516  5581 net.cpp:572] relu2_1/dw <- conv2_1/dw
-I0511 11:49:28.460535  5581 net.cpp:527] relu2_1/dw -> conv2_1/dw (in-place)
-I0511 11:49:28.460547  5581 net.cpp:260] Setting up relu2_1/dw
-I0511 11:49:28.460554  5581 net.cpp:267] TEST Top shape for layer 10 'relu2_1/dw' 10 16 128 256 (5242880)
-I0511 11:49:28.460564  5581 layer_factory.hpp:172] Creating layer 'conv2_1/sep' of type 'Convolution'
-I0511 11:49:28.460569  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460583  5581 net.cpp:200] Created Layer conv2_1/sep (11)
-I0511 11:49:28.460587  5581 net.cpp:572] conv2_1/sep <- conv2_1/dw
-I0511 11:49:28.460592  5581 net.cpp:542] conv2_1/sep -> conv2_1/sep
-I0511 11:49:28.460750  5581 net.cpp:260] Setting up conv2_1/sep
-I0511 11:49:28.460758  5581 net.cpp:267] TEST Top shape for layer 11 'conv2_1/sep' 10 32 128 256 (10485760)
-I0511 11:49:28.460770  5581 layer_factory.hpp:172] Creating layer 'conv2_1/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.460775  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460781  5581 net.cpp:200] Created Layer conv2_1/sep/bn (12)
-I0511 11:49:28.460799  5581 net.cpp:572] conv2_1/sep/bn <- conv2_1/sep
-I0511 11:49:28.460805  5581 net.cpp:527] conv2_1/sep/bn -> conv2_1/sep (in-place)
-I0511 11:49:28.461089  5581 net.cpp:260] Setting up conv2_1/sep/bn
-I0511 11:49:28.461097  5581 net.cpp:267] TEST Top shape for layer 12 'conv2_1/sep/bn' 10 32 128 256 (10485760)
-I0511 11:49:28.461117  5581 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Scale'
-I0511 11:49:28.461122  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461134  5581 net.cpp:200] Created Layer conv2_1/sep/scale (13)
-I0511 11:49:28.461139  5581 net.cpp:572] conv2_1/sep/scale <- conv2_1/sep
-I0511 11:49:28.461144  5581 net.cpp:527] conv2_1/sep/scale -> conv2_1/sep (in-place)
-I0511 11:49:28.461177  5581 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Bias'
-I0511 11:49:28.461182  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461292  5581 net.cpp:260] Setting up conv2_1/sep/scale
-I0511 11:49:28.461299  5581 net.cpp:267] TEST Top shape for layer 13 'conv2_1/sep/scale' 10 32 128 256 (10485760)
-I0511 11:49:28.461311  5581 layer_factory.hpp:172] Creating layer 'relu2_1/sep' of type 'ReLU'
-I0511 11:49:28.461318  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461323  5581 net.cpp:200] Created Layer relu2_1/sep (14)
-I0511 11:49:28.461333  5581 net.cpp:572] relu2_1/sep <- conv2_1/sep
-I0511 11:49:28.461343  5581 net.cpp:527] relu2_1/sep -> conv2_1/sep (in-place)
-I0511 11:49:28.461349  5581 net.cpp:260] Setting up relu2_1/sep
-I0511 11:49:28.461359  5581 net.cpp:267] TEST Top shape for layer 14 'relu2_1/sep' 10 32 128 256 (10485760)
-I0511 11:49:28.461364  5581 layer_factory.hpp:172] Creating layer 'conv2_2/dw' of type 'Convolution'
-I0511 11:49:28.461374  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461383  5581 net.cpp:200] Created Layer conv2_2/dw (15)
-I0511 11:49:28.461390  5581 net.cpp:572] conv2_2/dw <- conv2_1/sep
-I0511 11:49:28.461398  5581 net.cpp:542] conv2_2/dw -> conv2_2/dw
-I0511 11:49:28.461545  5581 net.cpp:260] Setting up conv2_2/dw
-I0511 11:49:28.461553  5581 net.cpp:267] TEST Top shape for layer 15 'conv2_2/dw' 10 32 64 128 (2621440)
-I0511 11:49:28.461565  5581 layer_factory.hpp:172] Creating layer 'conv2_2/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.461571  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461582  5581 net.cpp:200] Created Layer conv2_2/dw/bn (16)
-I0511 11:49:28.461587  5581 net.cpp:572] conv2_2/dw/bn <- conv2_2/dw
-I0511 11:49:28.461596  5581 net.cpp:527] conv2_2/dw/bn -> conv2_2/dw (in-place)
-I0511 11:49:28.462540  5581 net.cpp:260] Setting up conv2_2/dw/bn
-I0511 11:49:28.462553  5581 net.cpp:267] TEST Top shape for layer 16 'conv2_2/dw/bn' 10 32 64 128 (2621440)
-I0511 11:49:28.462561  5581 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Scale'
-I0511 11:49:28.462574  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.462584  5581 net.cpp:200] Created Layer conv2_2/dw/scale (17)
-I0511 11:49:28.462594  5581 net.cpp:572] conv2_2/dw/scale <- conv2_2/dw
-I0511 11:49:28.462600  5581 net.cpp:527] conv2_2/dw/scale -> conv2_2/dw (in-place)
-I0511 11:49:28.462636  5581 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Bias'
-I0511 11:49:28.462641  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.462726  5581 net.cpp:260] Setting up conv2_2/dw/scale
-I0511 11:49:28.462733  5581 net.cpp:267] TEST Top shape for layer 17 'conv2_2/dw/scale' 10 32 64 128 (2621440)
-I0511 11:49:28.462746  5581 layer_factory.hpp:172] Creating layer 'relu2_2/dw' of type 'ReLU'
-I0511 11:49:28.462752  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.462766  5581 net.cpp:200] Created Layer relu2_2/dw (18)
-I0511 11:49:28.462775  5581 net.cpp:572] relu2_2/dw <- conv2_2/dw
-I0511 11:49:28.462785  5581 net.cpp:527] relu2_2/dw -> conv2_2/dw (in-place)
-I0511 11:49:28.462795  5581 net.cpp:260] Setting up relu2_2/dw
-I0511 11:49:28.462806  5581 net.cpp:267] TEST Top shape for layer 18 'relu2_2/dw' 10 32 64 128 (2621440)
-I0511 11:49:28.462811  5581 layer_factory.hpp:172] Creating layer 'conv2_2/sep' of type 'Convolution'
-I0511 11:49:28.462821  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.462831  5581 net.cpp:200] Created Layer conv2_2/sep (19)
-I0511 11:49:28.462836  5581 net.cpp:572] conv2_2/sep <- conv2_2/dw
-I0511 11:49:28.462844  5581 net.cpp:542] conv2_2/sep -> conv2_2/sep
-I0511 11:49:28.463678  5581 net.cpp:260] Setting up conv2_2/sep
-I0511 11:49:28.463695  5581 net.cpp:267] TEST Top shape for layer 19 'conv2_2/sep' 10 64 64 128 (5242880)
-I0511 11:49:28.463708  5581 layer_factory.hpp:172] Creating layer 'conv2_2/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.463716  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.463727  5581 net.cpp:200] Created Layer conv2_2/sep/bn (20)
-I0511 11:49:28.463732  5581 net.cpp:572] conv2_2/sep/bn <- conv2_2/sep
-I0511 11:49:28.463742  5581 net.cpp:527] conv2_2/sep/bn -> conv2_2/sep (in-place)
-I0511 11:49:28.464006  5581 net.cpp:260] Setting up conv2_2/sep/bn
-I0511 11:49:28.464015  5581 net.cpp:267] TEST Top shape for layer 20 'conv2_2/sep/bn' 10 64 64 128 (5242880)
-I0511 11:49:28.464028  5581 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Scale'
-I0511 11:49:28.464035  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.464046  5581 net.cpp:200] Created Layer conv2_2/sep/scale (21)
-I0511 11:49:28.464051  5581 net.cpp:572] conv2_2/sep/scale <- conv2_2/sep
-I0511 11:49:28.464061  5581 net.cpp:527] conv2_2/sep/scale -> conv2_2/sep (in-place)
-I0511 11:49:28.464095  5581 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Bias'
-I0511 11:49:28.464100  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.464193  5581 net.cpp:260] Setting up conv2_2/sep/scale
-I0511 11:49:28.464200  5581 net.cpp:267] TEST Top shape for layer 21 'conv2_2/sep/scale' 10 64 64 128 (5242880)
-I0511 11:49:28.464213  5581 layer_factory.hpp:172] Creating layer 'relu2_2/sep' of type 'ReLU'
-I0511 11:49:28.464220  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.464229  5581 net.cpp:200] Created Layer relu2_2/sep (22)
-I0511 11:49:28.464236  5581 net.cpp:572] relu2_2/sep <- conv2_2/sep
-I0511 11:49:28.464244  5581 net.cpp:527] relu2_2/sep -> conv2_2/sep (in-place)
-I0511 11:49:28.464252  5581 net.cpp:260] Setting up relu2_2/sep
-I0511 11:49:28.464262  5581 net.cpp:267] TEST Top shape for layer 22 'relu2_2/sep' 10 64 64 128 (5242880)
-I0511 11:49:28.464268  5581 layer_factory.hpp:172] Creating layer 'conv3_1/dw' of type 'Convolution'
-I0511 11:49:28.464277  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.464292  5581 net.cpp:200] Created Layer conv3_1/dw (23)
-I0511 11:49:28.464296  5581 net.cpp:572] conv3_1/dw <- conv2_2/sep
-I0511 11:49:28.464305  5581 net.cpp:542] conv3_1/dw -> conv3_1/dw
-I0511 11:49:28.465170  5581 net.cpp:260] Setting up conv3_1/dw
-I0511 11:49:28.465180  5581 net.cpp:267] TEST Top shape for layer 23 'conv3_1/dw' 10 64 64 128 (5242880)
-I0511 11:49:28.465186  5581 layer_factory.hpp:172] Creating layer 'conv3_1/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.465198  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465211  5581 net.cpp:200] Created Layer conv3_1/dw/bn (24)
-I0511 11:49:28.465217  5581 net.cpp:572] conv3_1/dw/bn <- conv3_1/dw
-I0511 11:49:28.465226  5581 net.cpp:527] conv3_1/dw/bn -> conv3_1/dw (in-place)
-I0511 11:49:28.465489  5581 net.cpp:260] Setting up conv3_1/dw/bn
-I0511 11:49:28.465505  5581 net.cpp:267] TEST Top shape for layer 24 'conv3_1/dw/bn' 10 64 64 128 (5242880)
-I0511 11:49:28.465523  5581 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Scale'
-I0511 11:49:28.465528  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465540  5581 net.cpp:200] Created Layer conv3_1/dw/scale (25)
-I0511 11:49:28.465545  5581 net.cpp:572] conv3_1/dw/scale <- conv3_1/dw
-I0511 11:49:28.465554  5581 net.cpp:527] conv3_1/dw/scale -> conv3_1/dw (in-place)
-I0511 11:49:28.465587  5581 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Bias'
-I0511 11:49:28.465592  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465680  5581 net.cpp:260] Setting up conv3_1/dw/scale
-I0511 11:49:28.465687  5581 net.cpp:267] TEST Top shape for layer 25 'conv3_1/dw/scale' 10 64 64 128 (5242880)
-I0511 11:49:28.465700  5581 layer_factory.hpp:172] Creating layer 'relu3_1/dw' of type 'ReLU'
-I0511 11:49:28.465706  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465716  5581 net.cpp:200] Created Layer relu3_1/dw (26)
-I0511 11:49:28.465721  5581 net.cpp:572] relu3_1/dw <- conv3_1/dw
-I0511 11:49:28.465730  5581 net.cpp:527] relu3_1/dw -> conv3_1/dw (in-place)
-I0511 11:49:28.465739  5581 net.cpp:260] Setting up relu3_1/dw
-I0511 11:49:28.465749  5581 net.cpp:267] TEST Top shape for layer 26 'relu3_1/dw' 10 64 64 128 (5242880)
-I0511 11:49:28.465754  5581 layer_factory.hpp:172] Creating layer 'conv3_1/sep' of type 'Convolution'
-I0511 11:49:28.465762  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465777  5581 net.cpp:200] Created Layer conv3_1/sep (27)
-I0511 11:49:28.465781  5581 net.cpp:572] conv3_1/sep <- conv3_1/dw
-I0511 11:49:28.465791  5581 net.cpp:542] conv3_1/sep -> conv3_1/sep
-I0511 11:49:28.466006  5581 net.cpp:260] Setting up conv3_1/sep
-I0511 11:49:28.466013  5581 net.cpp:267] TEST Top shape for layer 27 'conv3_1/sep' 10 64 64 128 (5242880)
-I0511 11:49:28.466025  5581 layer_factory.hpp:172] Creating layer 'conv3_1/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.466030  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466042  5581 net.cpp:200] Created Layer conv3_1/sep/bn (28)
-I0511 11:49:28.466048  5581 net.cpp:572] conv3_1/sep/bn <- conv3_1/sep
-I0511 11:49:28.466056  5581 net.cpp:527] conv3_1/sep/bn -> conv3_1/sep (in-place)
-I0511 11:49:28.466300  5581 net.cpp:260] Setting up conv3_1/sep/bn
-I0511 11:49:28.466307  5581 net.cpp:267] TEST Top shape for layer 28 'conv3_1/sep/bn' 10 64 64 128 (5242880)
-I0511 11:49:28.466320  5581 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Scale'
-I0511 11:49:28.466327  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466338  5581 net.cpp:200] Created Layer conv3_1/sep/scale (29)
-I0511 11:49:28.466343  5581 net.cpp:572] conv3_1/sep/scale <- conv3_1/sep
-I0511 11:49:28.466352  5581 net.cpp:527] conv3_1/sep/scale -> conv3_1/sep (in-place)
-I0511 11:49:28.466385  5581 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Bias'
-I0511 11:49:28.466390  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466478  5581 net.cpp:260] Setting up conv3_1/sep/scale
-I0511 11:49:28.466485  5581 net.cpp:267] TEST Top shape for layer 29 'conv3_1/sep/scale' 10 64 64 128 (5242880)
-I0511 11:49:28.466497  5581 layer_factory.hpp:172] Creating layer 'relu3_1/sep' of type 'ReLU'
-I0511 11:49:28.466503  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466508  5581 net.cpp:200] Created Layer relu3_1/sep (30)
-I0511 11:49:28.466517  5581 net.cpp:572] relu3_1/sep <- conv3_1/sep
-I0511 11:49:28.466529  5581 net.cpp:527] relu3_1/sep -> conv3_1/sep (in-place)
-I0511 11:49:28.466540  5581 net.cpp:260] Setting up relu3_1/sep
-I0511 11:49:28.466552  5581 net.cpp:267] TEST Top shape for layer 30 'relu3_1/sep' 10 64 64 128 (5242880)
-I0511 11:49:28.466557  5581 layer_factory.hpp:172] Creating layer 'conv3_2/dw' of type 'Convolution'
-I0511 11:49:28.466565  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466574  5581 net.cpp:200] Created Layer conv3_2/dw (31)
-I0511 11:49:28.466579  5581 net.cpp:572] conv3_2/dw <- conv3_1/sep
-I0511 11:49:28.466589  5581 net.cpp:542] conv3_2/dw -> conv3_2/dw
-I0511 11:49:28.466734  5581 net.cpp:260] Setting up conv3_2/dw
-I0511 11:49:28.466743  5581 net.cpp:267] TEST Top shape for layer 31 'conv3_2/dw' 10 64 32 64 (1310720)
-I0511 11:49:28.466755  5581 layer_factory.hpp:172] Creating layer 'conv3_2/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.466760  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466773  5581 net.cpp:200] Created Layer conv3_2/dw/bn (32)
-I0511 11:49:28.466778  5581 net.cpp:572] conv3_2/dw/bn <- conv3_2/dw
-I0511 11:49:28.466786  5581 net.cpp:527] conv3_2/dw/bn -> conv3_2/dw (in-place)
-I0511 11:49:28.467030  5581 net.cpp:260] Setting up conv3_2/dw/bn
-I0511 11:49:28.467036  5581 net.cpp:267] TEST Top shape for layer 32 'conv3_2/dw/bn' 10 64 32 64 (1310720)
-I0511 11:49:28.467049  5581 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Scale'
-I0511 11:49:28.467056  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467067  5581 net.cpp:200] Created Layer conv3_2/dw/scale (33)
-I0511 11:49:28.467072  5581 net.cpp:572] conv3_2/dw/scale <- conv3_2/dw
-I0511 11:49:28.467080  5581 net.cpp:527] conv3_2/dw/scale -> conv3_2/dw (in-place)
-I0511 11:49:28.467116  5581 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Bias'
-I0511 11:49:28.467121  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467201  5581 net.cpp:260] Setting up conv3_2/dw/scale
-I0511 11:49:28.467208  5581 net.cpp:267] TEST Top shape for layer 33 'conv3_2/dw/scale' 10 64 32 64 (1310720)
-I0511 11:49:28.467221  5581 layer_factory.hpp:172] Creating layer 'relu3_2/dw' of type 'ReLU'
-I0511 11:49:28.467226  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467236  5581 net.cpp:200] Created Layer relu3_2/dw (34)
-I0511 11:49:28.467242  5581 net.cpp:572] relu3_2/dw <- conv3_2/dw
-I0511 11:49:28.467250  5581 net.cpp:527] relu3_2/dw -> conv3_2/dw (in-place)
-I0511 11:49:28.467257  5581 net.cpp:260] Setting up relu3_2/dw
-I0511 11:49:28.467267  5581 net.cpp:267] TEST Top shape for layer 34 'relu3_2/dw' 10 64 32 64 (1310720)
-I0511 11:49:28.467272  5581 layer_factory.hpp:172] Creating layer 'conv3_2/sep' of type 'Convolution'
-I0511 11:49:28.467281  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467294  5581 net.cpp:200] Created Layer conv3_2/sep (35)
-I0511 11:49:28.467298  5581 net.cpp:572] conv3_2/sep <- conv3_2/dw
-I0511 11:49:28.467308  5581 net.cpp:542] conv3_2/sep -> conv3_2/sep
-I0511 11:49:28.467595  5581 net.cpp:260] Setting up conv3_2/sep
-I0511 11:49:28.467602  5581 net.cpp:267] TEST Top shape for layer 35 'conv3_2/sep' 10 128 32 64 (2621440)
-I0511 11:49:28.467614  5581 layer_factory.hpp:172] Creating layer 'conv3_2/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.467620  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467631  5581 net.cpp:200] Created Layer conv3_2/sep/bn (36)
-I0511 11:49:28.467636  5581 net.cpp:572] conv3_2/sep/bn <- conv3_2/sep
-I0511 11:49:28.467645  5581 net.cpp:527] conv3_2/sep/bn -> conv3_2/sep (in-place)
-I0511 11:49:28.467877  5581 net.cpp:260] Setting up conv3_2/sep/bn
-I0511 11:49:28.467885  5581 net.cpp:267] TEST Top shape for layer 36 'conv3_2/sep/bn' 10 128 32 64 (2621440)
-I0511 11:49:28.467901  5581 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Scale'
-I0511 11:49:28.467913  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467933  5581 net.cpp:200] Created Layer conv3_2/sep/scale (37)
-I0511 11:49:28.467938  5581 net.cpp:572] conv3_2/sep/scale <- conv3_2/sep
-I0511 11:49:28.467948  5581 net.cpp:527] conv3_2/sep/scale -> conv3_2/sep (in-place)
-I0511 11:49:28.467980  5581 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Bias'
-I0511 11:49:28.467985  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468057  5581 net.cpp:260] Setting up conv3_2/sep/scale
-I0511 11:49:28.468065  5581 net.cpp:267] TEST Top shape for layer 37 'conv3_2/sep/scale' 10 128 32 64 (2621440)
-I0511 11:49:28.468072  5581 layer_factory.hpp:172] Creating layer 'relu3_2/sep' of type 'ReLU'
-I0511 11:49:28.468077  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468083  5581 net.cpp:200] Created Layer relu3_2/sep (38)
-I0511 11:49:28.468088  5581 net.cpp:572] relu3_2/sep <- conv3_2/sep
-I0511 11:49:28.468092  5581 net.cpp:527] relu3_2/sep -> conv3_2/sep (in-place)
-I0511 11:49:28.468099  5581 net.cpp:260] Setting up relu3_2/sep
-I0511 11:49:28.468106  5581 net.cpp:267] TEST Top shape for layer 38 'relu3_2/sep' 10 128 32 64 (2621440)
-I0511 11:49:28.468111  5581 layer_factory.hpp:172] Creating layer 'conv4_1/dw' of type 'Convolution'
-I0511 11:49:28.468116  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468128  5581 net.cpp:200] Created Layer conv4_1/dw (39)
-I0511 11:49:28.468132  5581 net.cpp:572] conv4_1/dw <- conv3_2/sep
-I0511 11:49:28.468137  5581 net.cpp:542] conv4_1/dw -> conv4_1/dw
-I0511 11:49:28.468284  5581 net.cpp:260] Setting up conv4_1/dw
-I0511 11:49:28.468291  5581 net.cpp:267] TEST Top shape for layer 39 'conv4_1/dw' 10 128 32 64 (2621440)
-I0511 11:49:28.468297  5581 layer_factory.hpp:172] Creating layer 'conv4_1/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.468299  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468305  5581 net.cpp:200] Created Layer conv4_1/dw/bn (40)
-I0511 11:49:28.468310  5581 net.cpp:572] conv4_1/dw/bn <- conv4_1/dw
-I0511 11:49:28.468315  5581 net.cpp:527] conv4_1/dw/bn -> conv4_1/dw (in-place)
-I0511 11:49:28.468911  5581 net.cpp:260] Setting up conv4_1/dw/bn
-I0511 11:49:28.468920  5581 net.cpp:267] TEST Top shape for layer 40 'conv4_1/dw/bn' 10 128 32 64 (2621440)
-I0511 11:49:28.468927  5581 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Scale'
-I0511 11:49:28.468933  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468940  5581 net.cpp:200] Created Layer conv4_1/dw/scale (41)
-I0511 11:49:28.468945  5581 net.cpp:572] conv4_1/dw/scale <- conv4_1/dw
-I0511 11:49:28.468947  5581 net.cpp:527] conv4_1/dw/scale -> conv4_1/dw (in-place)
-I0511 11:49:28.468979  5581 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Bias'
-I0511 11:49:28.468986  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469060  5581 net.cpp:260] Setting up conv4_1/dw/scale
-I0511 11:49:28.469066  5581 net.cpp:267] TEST Top shape for layer 41 'conv4_1/dw/scale' 10 128 32 64 (2621440)
-I0511 11:49:28.469071  5581 layer_factory.hpp:172] Creating layer 'relu4_1/dw' of type 'ReLU'
-I0511 11:49:28.469074  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469079  5581 net.cpp:200] Created Layer relu4_1/dw (42)
-I0511 11:49:28.469084  5581 net.cpp:572] relu4_1/dw <- conv4_1/dw
-I0511 11:49:28.469087  5581 net.cpp:527] relu4_1/dw -> conv4_1/dw (in-place)
-I0511 11:49:28.469094  5581 net.cpp:260] Setting up relu4_1/dw
-I0511 11:49:28.469099  5581 net.cpp:267] TEST Top shape for layer 42 'relu4_1/dw' 10 128 32 64 (2621440)
-I0511 11:49:28.469100  5581 layer_factory.hpp:172] Creating layer 'conv4_1/sep' of type 'Convolution'
-I0511 11:49:28.469108  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469115  5581 net.cpp:200] Created Layer conv4_1/sep (43)
-I0511 11:49:28.469117  5581 net.cpp:572] conv4_1/sep <- conv4_1/dw
-I0511 11:49:28.469120  5581 net.cpp:542] conv4_1/sep -> conv4_1/sep
-I0511 11:49:28.469573  5581 net.cpp:260] Setting up conv4_1/sep
-I0511 11:49:28.469579  5581 net.cpp:267] TEST Top shape for layer 43 'conv4_1/sep' 10 128 32 64 (2621440)
-I0511 11:49:28.469584  5581 layer_factory.hpp:172] Creating layer 'conv4_1/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.469589  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469596  5581 net.cpp:200] Created Layer conv4_1/sep/bn (44)
-I0511 11:49:28.469600  5581 net.cpp:572] conv4_1/sep/bn <- conv4_1/sep
-I0511 11:49:28.469604  5581 net.cpp:527] conv4_1/sep/bn -> conv4_1/sep (in-place)
-I0511 11:49:28.469838  5581 net.cpp:260] Setting up conv4_1/sep/bn
-I0511 11:49:28.469844  5581 net.cpp:267] TEST Top shape for layer 44 'conv4_1/sep/bn' 10 128 32 64 (2621440)
-I0511 11:49:28.469856  5581 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Scale'
-I0511 11:49:28.469862  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469869  5581 net.cpp:200] Created Layer conv4_1/sep/scale (45)
-I0511 11:49:28.469872  5581 net.cpp:572] conv4_1/sep/scale <- conv4_1/sep
-I0511 11:49:28.469875  5581 net.cpp:527] conv4_1/sep/scale -> conv4_1/sep (in-place)
-I0511 11:49:28.469916  5581 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Bias'
-I0511 11:49:28.469923  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469997  5581 net.cpp:260] Setting up conv4_1/sep/scale
-I0511 11:49:28.470003  5581 net.cpp:267] TEST Top shape for layer 45 'conv4_1/sep/scale' 10 128 32 64 (2621440)
-I0511 11:49:28.470010  5581 layer_factory.hpp:172] Creating layer 'relu4_1/sep' of type 'ReLU'
-I0511 11:49:28.470015  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470021  5581 net.cpp:200] Created Layer relu4_1/sep (46)
-I0511 11:49:28.470023  5581 net.cpp:572] relu4_1/sep <- conv4_1/sep
-I0511 11:49:28.470026  5581 net.cpp:527] relu4_1/sep -> conv4_1/sep (in-place)
-I0511 11:49:28.470029  5581 net.cpp:260] Setting up relu4_1/sep
-I0511 11:49:28.470032  5581 net.cpp:267] TEST Top shape for layer 46 'relu4_1/sep' 10 128 32 64 (2621440)
-I0511 11:49:28.470034  5581 layer_factory.hpp:172] Creating layer 'conv4_2/dw' of type 'Convolution'
-I0511 11:49:28.470037  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470048  5581 net.cpp:200] Created Layer conv4_2/dw (47)
-I0511 11:49:28.470054  5581 net.cpp:572] conv4_2/dw <- conv4_1/sep
-I0511 11:49:28.470058  5581 net.cpp:542] conv4_2/dw -> conv4_2/dw
-I0511 11:49:28.470216  5581 net.cpp:260] Setting up conv4_2/dw
-I0511 11:49:28.470223  5581 net.cpp:267] TEST Top shape for layer 47 'conv4_2/dw' 10 128 16 32 (655360)
-I0511 11:49:28.470228  5581 layer_factory.hpp:172] Creating layer 'conv4_2/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.470233  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470239  5581 net.cpp:200] Created Layer conv4_2/dw/bn (48)
-I0511 11:49:28.470243  5581 net.cpp:572] conv4_2/dw/bn <- conv4_2/dw
-I0511 11:49:28.470247  5581 net.cpp:527] conv4_2/dw/bn -> conv4_2/dw (in-place)
-I0511 11:49:28.470497  5581 net.cpp:260] Setting up conv4_2/dw/bn
-I0511 11:49:28.470504  5581 net.cpp:267] TEST Top shape for layer 48 'conv4_2/dw/bn' 10 128 16 32 (655360)
-I0511 11:49:28.470510  5581 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Scale'
-I0511 11:49:28.470515  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470522  5581 net.cpp:200] Created Layer conv4_2/dw/scale (49)
-I0511 11:49:28.470530  5581 net.cpp:572] conv4_2/dw/scale <- conv4_2/dw
-I0511 11:49:28.470533  5581 net.cpp:527] conv4_2/dw/scale -> conv4_2/dw (in-place)
-I0511 11:49:28.470569  5581 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Bias'
-I0511 11:49:28.470574  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470649  5581 net.cpp:260] Setting up conv4_2/dw/scale
-I0511 11:49:28.470655  5581 net.cpp:267] TEST Top shape for layer 49 'conv4_2/dw/scale' 10 128 16 32 (655360)
-I0511 11:49:28.470662  5581 layer_factory.hpp:172] Creating layer 'relu4_2/dw' of type 'ReLU'
-I0511 11:49:28.470667  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470674  5581 net.cpp:200] Created Layer relu4_2/dw (50)
-I0511 11:49:28.470679  5581 net.cpp:572] relu4_2/dw <- conv4_2/dw
-I0511 11:49:28.470682  5581 net.cpp:527] relu4_2/dw -> conv4_2/dw (in-place)
-I0511 11:49:28.470690  5581 net.cpp:260] Setting up relu4_2/dw
-I0511 11:49:28.470696  5581 net.cpp:267] TEST Top shape for layer 50 'relu4_2/dw' 10 128 16 32 (655360)
-I0511 11:49:28.470701  5581 layer_factory.hpp:172] Creating layer 'conv4_2/sep' of type 'Convolution'
-I0511 11:49:28.470706  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470715  5581 net.cpp:200] Created Layer conv4_2/sep (51)
-I0511 11:49:28.470718  5581 net.cpp:572] conv4_2/sep <- conv4_2/dw
-I0511 11:49:28.470722  5581 net.cpp:542] conv4_2/sep -> conv4_2/sep
-I0511 11:49:28.471474  5581 net.cpp:260] Setting up conv4_2/sep
-I0511 11:49:28.471482  5581 net.cpp:267] TEST Top shape for layer 51 'conv4_2/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.471487  5581 layer_factory.hpp:172] Creating layer 'conv4_2/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.471491  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471498  5581 net.cpp:200] Created Layer conv4_2/sep/bn (52)
-I0511 11:49:28.471503  5581 net.cpp:572] conv4_2/sep/bn <- conv4_2/sep
-I0511 11:49:28.471508  5581 net.cpp:527] conv4_2/sep/bn -> conv4_2/sep (in-place)
-I0511 11:49:28.471745  5581 net.cpp:260] Setting up conv4_2/sep/bn
-I0511 11:49:28.471751  5581 net.cpp:267] TEST Top shape for layer 52 'conv4_2/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.471757  5581 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Scale'
-I0511 11:49:28.471763  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471771  5581 net.cpp:200] Created Layer conv4_2/sep/scale (53)
-I0511 11:49:28.471776  5581 net.cpp:572] conv4_2/sep/scale <- conv4_2/sep
-I0511 11:49:28.471781  5581 net.cpp:527] conv4_2/sep/scale -> conv4_2/sep (in-place)
-I0511 11:49:28.471813  5581 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Bias'
-I0511 11:49:28.471818  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471889  5581 net.cpp:260] Setting up conv4_2/sep/scale
-I0511 11:49:28.471895  5581 net.cpp:267] TEST Top shape for layer 53 'conv4_2/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.471902  5581 layer_factory.hpp:172] Creating layer 'relu4_2/sep' of type 'ReLU'
-I0511 11:49:28.471907  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471913  5581 net.cpp:200] Created Layer relu4_2/sep (54)
-I0511 11:49:28.471920  5581 net.cpp:572] relu4_2/sep <- conv4_2/sep
-I0511 11:49:28.471925  5581 net.cpp:527] relu4_2/sep -> conv4_2/sep (in-place)
-I0511 11:49:28.471931  5581 net.cpp:260] Setting up relu4_2/sep
-I0511 11:49:28.471936  5581 net.cpp:267] TEST Top shape for layer 54 'relu4_2/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.471941  5581 layer_factory.hpp:172] Creating layer 'conv5_1/dw' of type 'Convolution'
-I0511 11:49:28.471946  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471962  5581 net.cpp:200] Created Layer conv5_1/dw (55)
-I0511 11:49:28.471971  5581 net.cpp:572] conv5_1/dw <- conv4_2/sep
-I0511 11:49:28.471976  5581 net.cpp:542] conv5_1/dw -> conv5_1/dw
-I0511 11:49:28.472154  5581 net.cpp:260] Setting up conv5_1/dw
-I0511 11:49:28.472162  5581 net.cpp:267] TEST Top shape for layer 55 'conv5_1/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.472167  5581 layer_factory.hpp:172] Creating layer 'conv5_1/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.472173  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472180  5581 net.cpp:200] Created Layer conv5_1/dw/bn (56)
-I0511 11:49:28.472185  5581 net.cpp:572] conv5_1/dw/bn <- conv5_1/dw
-I0511 11:49:28.472190  5581 net.cpp:527] conv5_1/dw/bn -> conv5_1/dw (in-place)
-I0511 11:49:28.472412  5581 net.cpp:260] Setting up conv5_1/dw/bn
-I0511 11:49:28.472419  5581 net.cpp:267] TEST Top shape for layer 56 'conv5_1/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.472426  5581 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Scale'
-I0511 11:49:28.472432  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472440  5581 net.cpp:200] Created Layer conv5_1/dw/scale (57)
-I0511 11:49:28.472445  5581 net.cpp:572] conv5_1/dw/scale <- conv5_1/dw
-I0511 11:49:28.472450  5581 net.cpp:527] conv5_1/dw/scale -> conv5_1/dw (in-place)
-I0511 11:49:28.472481  5581 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Bias'
-I0511 11:49:28.472484  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472581  5581 net.cpp:260] Setting up conv5_1/dw/scale
-I0511 11:49:28.472589  5581 net.cpp:267] TEST Top shape for layer 57 'conv5_1/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.472595  5581 layer_factory.hpp:172] Creating layer 'relu5_1/dw' of type 'ReLU'
-I0511 11:49:28.472600  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472604  5581 net.cpp:200] Created Layer relu5_1/dw (58)
-I0511 11:49:28.472607  5581 net.cpp:572] relu5_1/dw <- conv5_1/dw
-I0511 11:49:28.472609  5581 net.cpp:527] relu5_1/dw -> conv5_1/dw (in-place)
-I0511 11:49:28.472614  5581 net.cpp:260] Setting up relu5_1/dw
-I0511 11:49:28.472616  5581 net.cpp:267] TEST Top shape for layer 58 'relu5_1/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.472620  5581 layer_factory.hpp:172] Creating layer 'conv5_1/sep' of type 'Convolution'
-I0511 11:49:28.472625  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472632  5581 net.cpp:200] Created Layer conv5_1/sep (59)
-I0511 11:49:28.472637  5581 net.cpp:572] conv5_1/sep <- conv5_1/dw
-I0511 11:49:28.472641  5581 net.cpp:542] conv5_1/sep -> conv5_1/sep
-I0511 11:49:28.474005  5581 net.cpp:260] Setting up conv5_1/sep
-I0511 11:49:28.474012  5581 net.cpp:267] TEST Top shape for layer 59 'conv5_1/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.474017  5581 layer_factory.hpp:172] Creating layer 'conv5_1/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.474022  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474028  5581 net.cpp:200] Created Layer conv5_1/sep/bn (60)
-I0511 11:49:28.474032  5581 net.cpp:572] conv5_1/sep/bn <- conv5_1/sep
-I0511 11:49:28.474035  5581 net.cpp:527] conv5_1/sep/bn -> conv5_1/sep (in-place)
-I0511 11:49:28.474267  5581 net.cpp:260] Setting up conv5_1/sep/bn
-I0511 11:49:28.474273  5581 net.cpp:267] TEST Top shape for layer 60 'conv5_1/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.474280  5581 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Scale'
-I0511 11:49:28.474287  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474298  5581 net.cpp:200] Created Layer conv5_1/sep/scale (61)
-I0511 11:49:28.474303  5581 net.cpp:572] conv5_1/sep/scale <- conv5_1/sep
-I0511 11:49:28.474308  5581 net.cpp:527] conv5_1/sep/scale -> conv5_1/sep (in-place)
-I0511 11:49:28.474347  5581 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Bias'
-I0511 11:49:28.474362  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474467  5581 net.cpp:260] Setting up conv5_1/sep/scale
-I0511 11:49:28.474475  5581 net.cpp:267] TEST Top shape for layer 61 'conv5_1/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.474483  5581 layer_factory.hpp:172] Creating layer 'relu5_1/sep' of type 'ReLU'
-I0511 11:49:28.474488  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474493  5581 net.cpp:200] Created Layer relu5_1/sep (62)
-I0511 11:49:28.474498  5581 net.cpp:572] relu5_1/sep <- conv5_1/sep
-I0511 11:49:28.474503  5581 net.cpp:527] relu5_1/sep -> conv5_1/sep (in-place)
-I0511 11:49:28.474510  5581 net.cpp:260] Setting up relu5_1/sep
-I0511 11:49:28.474517  5581 net.cpp:267] TEST Top shape for layer 62 'relu5_1/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.474522  5581 layer_factory.hpp:172] Creating layer 'conv5_2/dw' of type 'Convolution'
-I0511 11:49:28.474526  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474541  5581 net.cpp:200] Created Layer conv5_2/dw (63)
-I0511 11:49:28.474546  5581 net.cpp:572] conv5_2/dw <- conv5_1/sep
-I0511 11:49:28.474551  5581 net.cpp:542] conv5_2/dw -> conv5_2/dw
-I0511 11:49:28.474815  5581 net.cpp:260] Setting up conv5_2/dw
-I0511 11:49:28.474825  5581 net.cpp:267] TEST Top shape for layer 63 'conv5_2/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.474833  5581 layer_factory.hpp:172] Creating layer 'conv5_2/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.474836  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474845  5581 net.cpp:200] Created Layer conv5_2/dw/bn (64)
-I0511 11:49:28.474850  5581 net.cpp:572] conv5_2/dw/bn <- conv5_2/dw
-I0511 11:49:28.474856  5581 net.cpp:527] conv5_2/dw/bn -> conv5_2/dw (in-place)
-I0511 11:49:28.475193  5581 net.cpp:260] Setting up conv5_2/dw/bn
-I0511 11:49:28.475201  5581 net.cpp:267] TEST Top shape for layer 64 'conv5_2/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.475210  5581 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Scale'
-I0511 11:49:28.475215  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.475222  5581 net.cpp:200] Created Layer conv5_2/dw/scale (65)
-I0511 11:49:28.475227  5581 net.cpp:572] conv5_2/dw/scale <- conv5_2/dw
-I0511 11:49:28.475234  5581 net.cpp:527] conv5_2/dw/scale -> conv5_2/dw (in-place)
-I0511 11:49:28.475276  5581 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Bias'
-I0511 11:49:28.475282  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.475384  5581 net.cpp:260] Setting up conv5_2/dw/scale
-I0511 11:49:28.475394  5581 net.cpp:267] TEST Top shape for layer 65 'conv5_2/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.475401  5581 layer_factory.hpp:172] Creating layer 'relu5_2/dw' of type 'ReLU'
-I0511 11:49:28.475406  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.475415  5581 net.cpp:200] Created Layer relu5_2/dw (66)
-I0511 11:49:28.475421  5581 net.cpp:572] relu5_2/dw <- conv5_2/dw
-I0511 11:49:28.475426  5581 net.cpp:527] relu5_2/dw -> conv5_2/dw (in-place)
-I0511 11:49:28.475433  5581 net.cpp:260] Setting up relu5_2/dw
-I0511 11:49:28.475440  5581 net.cpp:267] TEST Top shape for layer 66 'relu5_2/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.475445  5581 layer_factory.hpp:172] Creating layer 'conv5_2/sep' of type 'Convolution'
-I0511 11:49:28.475450  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.475458  5581 net.cpp:200] Created Layer conv5_2/sep (67)
-I0511 11:49:28.475463  5581 net.cpp:572] conv5_2/sep <- conv5_2/dw
-I0511 11:49:28.475468  5581 net.cpp:542] conv5_2/sep -> conv5_2/sep
-I0511 11:49:28.477046  5581 net.cpp:260] Setting up conv5_2/sep
-I0511 11:49:28.477087  5581 net.cpp:267] TEST Top shape for layer 67 'conv5_2/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.477098  5581 layer_factory.hpp:172] Creating layer 'conv5_2/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.477108  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477123  5581 net.cpp:200] Created Layer conv5_2/sep/bn (68)
-I0511 11:49:28.477130  5581 net.cpp:572] conv5_2/sep/bn <- conv5_2/sep
-I0511 11:49:28.477138  5581 net.cpp:527] conv5_2/sep/bn -> conv5_2/sep (in-place)
-I0511 11:49:28.477432  5581 net.cpp:260] Setting up conv5_2/sep/bn
-I0511 11:49:28.477438  5581 net.cpp:267] TEST Top shape for layer 68 'conv5_2/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.477447  5581 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Scale'
-I0511 11:49:28.477452  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477466  5581 net.cpp:200] Created Layer conv5_2/sep/scale (69)
-I0511 11:49:28.477470  5581 net.cpp:572] conv5_2/sep/scale <- conv5_2/sep
-I0511 11:49:28.477474  5581 net.cpp:527] conv5_2/sep/scale -> conv5_2/sep (in-place)
-I0511 11:49:28.477512  5581 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Bias'
-I0511 11:49:28.477519  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477600  5581 net.cpp:260] Setting up conv5_2/sep/scale
-I0511 11:49:28.477607  5581 net.cpp:267] TEST Top shape for layer 69 'conv5_2/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.477613  5581 layer_factory.hpp:172] Creating layer 'relu5_2/sep' of type 'ReLU'
-I0511 11:49:28.477618  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477624  5581 net.cpp:200] Created Layer relu5_2/sep (70)
-I0511 11:49:28.477629  5581 net.cpp:572] relu5_2/sep <- conv5_2/sep
-I0511 11:49:28.477634  5581 net.cpp:527] relu5_2/sep -> conv5_2/sep (in-place)
-I0511 11:49:28.477641  5581 net.cpp:260] Setting up relu5_2/sep
-I0511 11:49:28.477648  5581 net.cpp:267] TEST Top shape for layer 70 'relu5_2/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.477651  5581 layer_factory.hpp:172] Creating layer 'conv5_3/dw' of type 'Convolution'
-I0511 11:49:28.477656  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477669  5581 net.cpp:200] Created Layer conv5_3/dw (71)
-I0511 11:49:28.477674  5581 net.cpp:572] conv5_3/dw <- conv5_2/sep
-I0511 11:49:28.477676  5581 net.cpp:542] conv5_3/dw -> conv5_3/dw
-I0511 11:49:28.477857  5581 net.cpp:260] Setting up conv5_3/dw
-I0511 11:49:28.477864  5581 net.cpp:267] TEST Top shape for layer 71 'conv5_3/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.477870  5581 layer_factory.hpp:172] Creating layer 'conv5_3/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.477876  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477882  5581 net.cpp:200] Created Layer conv5_3/dw/bn (72)
-I0511 11:49:28.477887  5581 net.cpp:572] conv5_3/dw/bn <- conv5_3/dw
-I0511 11:49:28.477893  5581 net.cpp:527] conv5_3/dw/bn -> conv5_3/dw (in-place)
-I0511 11:49:28.478126  5581 net.cpp:260] Setting up conv5_3/dw/bn
-I0511 11:49:28.478132  5581 net.cpp:267] TEST Top shape for layer 72 'conv5_3/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.478139  5581 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Scale'
-I0511 11:49:28.478145  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.478153  5581 net.cpp:200] Created Layer conv5_3/dw/scale (73)
-I0511 11:49:28.478157  5581 net.cpp:572] conv5_3/dw/scale <- conv5_3/dw
-I0511 11:49:28.478161  5581 net.cpp:527] conv5_3/dw/scale -> conv5_3/dw (in-place)
-I0511 11:49:28.478193  5581 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Bias'
-I0511 11:49:28.478196  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.478271  5581 net.cpp:260] Setting up conv5_3/dw/scale
-I0511 11:49:28.478281  5581 net.cpp:267] TEST Top shape for layer 73 'conv5_3/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.478288  5581 layer_factory.hpp:172] Creating layer 'relu5_3/dw' of type 'ReLU'
-I0511 11:49:28.478294  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.478298  5581 net.cpp:200] Created Layer relu5_3/dw (74)
-I0511 11:49:28.478302  5581 net.cpp:572] relu5_3/dw <- conv5_3/dw
-I0511 11:49:28.478307  5581 net.cpp:527] relu5_3/dw -> conv5_3/dw (in-place)
-I0511 11:49:28.478319  5581 net.cpp:260] Setting up relu5_3/dw
-I0511 11:49:28.478323  5581 net.cpp:267] TEST Top shape for layer 74 'relu5_3/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.478327  5581 layer_factory.hpp:172] Creating layer 'conv5_3/sep' of type 'Convolution'
-I0511 11:49:28.478332  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.478340  5581 net.cpp:200] Created Layer conv5_3/sep (75)
-I0511 11:49:28.478344  5581 net.cpp:572] conv5_3/sep <- conv5_3/dw
-I0511 11:49:28.478348  5581 net.cpp:542] conv5_3/sep -> conv5_3/sep
-I0511 11:49:28.479776  5581 net.cpp:260] Setting up conv5_3/sep
-I0511 11:49:28.479785  5581 net.cpp:267] TEST Top shape for layer 75 'conv5_3/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.479792  5581 layer_factory.hpp:172] Creating layer 'conv5_3/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.479797  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.479802  5581 net.cpp:200] Created Layer conv5_3/sep/bn (76)
-I0511 11:49:28.479805  5581 net.cpp:572] conv5_3/sep/bn <- conv5_3/sep
-I0511 11:49:28.479809  5581 net.cpp:527] conv5_3/sep/bn -> conv5_3/sep (in-place)
-I0511 11:49:28.480049  5581 net.cpp:260] Setting up conv5_3/sep/bn
-I0511 11:49:28.480057  5581 net.cpp:267] TEST Top shape for layer 76 'conv5_3/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.480064  5581 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Scale'
-I0511 11:49:28.480069  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480074  5581 net.cpp:200] Created Layer conv5_3/sep/scale (77)
-I0511 11:49:28.480079  5581 net.cpp:572] conv5_3/sep/scale <- conv5_3/sep
-I0511 11:49:28.480085  5581 net.cpp:527] conv5_3/sep/scale -> conv5_3/sep (in-place)
-I0511 11:49:28.480114  5581 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Bias'
-I0511 11:49:28.480119  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480186  5581 net.cpp:260] Setting up conv5_3/sep/scale
-I0511 11:49:28.480191  5581 net.cpp:267] TEST Top shape for layer 77 'conv5_3/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.480198  5581 layer_factory.hpp:172] Creating layer 'relu5_3/sep' of type 'ReLU'
-I0511 11:49:28.480203  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480211  5581 net.cpp:200] Created Layer relu5_3/sep (78)
-I0511 11:49:28.480216  5581 net.cpp:572] relu5_3/sep <- conv5_3/sep
-I0511 11:49:28.480221  5581 net.cpp:527] relu5_3/sep -> conv5_3/sep (in-place)
-I0511 11:49:28.480227  5581 net.cpp:260] Setting up relu5_3/sep
-I0511 11:49:28.480232  5581 net.cpp:267] TEST Top shape for layer 78 'relu5_3/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.480238  5581 layer_factory.hpp:172] Creating layer 'conv5_4/dw' of type 'Convolution'
-I0511 11:49:28.480243  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480252  5581 net.cpp:200] Created Layer conv5_4/dw (79)
-I0511 11:49:28.480257  5581 net.cpp:572] conv5_4/dw <- conv5_3/sep
-I0511 11:49:28.480260  5581 net.cpp:542] conv5_4/dw -> conv5_4/dw
-I0511 11:49:28.480432  5581 net.cpp:260] Setting up conv5_4/dw
-I0511 11:49:28.480439  5581 net.cpp:267] TEST Top shape for layer 79 'conv5_4/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.480445  5581 layer_factory.hpp:172] Creating layer 'conv5_4/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.480458  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480463  5581 net.cpp:200] Created Layer conv5_4/dw/bn (80)
-I0511 11:49:28.480469  5581 net.cpp:572] conv5_4/dw/bn <- conv5_4/dw
-I0511 11:49:28.480474  5581 net.cpp:527] conv5_4/dw/bn -> conv5_4/dw (in-place)
-I0511 11:49:28.480720  5581 net.cpp:260] Setting up conv5_4/dw/bn
-I0511 11:49:28.480726  5581 net.cpp:267] TEST Top shape for layer 80 'conv5_4/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.480734  5581 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Scale'
-I0511 11:49:28.480739  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480746  5581 net.cpp:200] Created Layer conv5_4/dw/scale (81)
-I0511 11:49:28.480751  5581 net.cpp:572] conv5_4/dw/scale <- conv5_4/dw
-I0511 11:49:28.480756  5581 net.cpp:527] conv5_4/dw/scale -> conv5_4/dw (in-place)
-I0511 11:49:28.480792  5581 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Bias'
-I0511 11:49:28.480796  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480865  5581 net.cpp:260] Setting up conv5_4/dw/scale
-I0511 11:49:28.480870  5581 net.cpp:267] TEST Top shape for layer 81 'conv5_4/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.480877  5581 layer_factory.hpp:172] Creating layer 'relu5_4/dw' of type 'ReLU'
-I0511 11:49:28.480882  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480888  5581 net.cpp:200] Created Layer relu5_4/dw (82)
-I0511 11:49:28.480893  5581 net.cpp:572] relu5_4/dw <- conv5_4/dw
-I0511 11:49:28.480898  5581 net.cpp:527] relu5_4/dw -> conv5_4/dw (in-place)
-I0511 11:49:28.480904  5581 net.cpp:260] Setting up relu5_4/dw
-I0511 11:49:28.480911  5581 net.cpp:267] TEST Top shape for layer 82 'relu5_4/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.480916  5581 layer_factory.hpp:172] Creating layer 'conv5_4/sep' of type 'Convolution'
-I0511 11:49:28.480919  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480933  5581 net.cpp:200] Created Layer conv5_4/sep (83)
-I0511 11:49:28.480937  5581 net.cpp:572] conv5_4/sep <- conv5_4/dw
-I0511 11:49:28.480940  5581 net.cpp:542] conv5_4/sep -> conv5_4/sep
-I0511 11:49:28.482995  5581 net.cpp:260] Setting up conv5_4/sep
-I0511 11:49:28.483008  5581 net.cpp:267] TEST Top shape for layer 83 'conv5_4/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.483016  5581 layer_factory.hpp:172] Creating layer 'conv5_4/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.483022  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483032  5581 net.cpp:200] Created Layer conv5_4/sep/bn (84)
-I0511 11:49:28.483036  5581 net.cpp:572] conv5_4/sep/bn <- conv5_4/sep
-I0511 11:49:28.483042  5581 net.cpp:527] conv5_4/sep/bn -> conv5_4/sep (in-place)
-I0511 11:49:28.483292  5581 net.cpp:260] Setting up conv5_4/sep/bn
-I0511 11:49:28.483299  5581 net.cpp:267] TEST Top shape for layer 84 'conv5_4/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.483309  5581 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Scale'
-I0511 11:49:28.483314  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483325  5581 net.cpp:200] Created Layer conv5_4/sep/scale (85)
-I0511 11:49:28.483330  5581 net.cpp:572] conv5_4/sep/scale <- conv5_4/sep
-I0511 11:49:28.483333  5581 net.cpp:527] conv5_4/sep/scale -> conv5_4/sep (in-place)
-I0511 11:49:28.483366  5581 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Bias'
-I0511 11:49:28.483369  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483444  5581 net.cpp:260] Setting up conv5_4/sep/scale
-I0511 11:49:28.483450  5581 net.cpp:267] TEST Top shape for layer 85 'conv5_4/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.483458  5581 layer_factory.hpp:172] Creating layer 'relu5_4/sep' of type 'ReLU'
-I0511 11:49:28.483470  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483477  5581 net.cpp:200] Created Layer relu5_4/sep (86)
-I0511 11:49:28.483482  5581 net.cpp:572] relu5_4/sep <- conv5_4/sep
-I0511 11:49:28.483487  5581 net.cpp:527] relu5_4/sep -> conv5_4/sep (in-place)
-I0511 11:49:28.483494  5581 net.cpp:260] Setting up relu5_4/sep
-I0511 11:49:28.483500  5581 net.cpp:267] TEST Top shape for layer 86 'relu5_4/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.483506  5581 layer_factory.hpp:172] Creating layer 'conv5_5/dw' of type 'Convolution'
-I0511 11:49:28.483511  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483520  5581 net.cpp:200] Created Layer conv5_5/dw (87)
-I0511 11:49:28.483525  5581 net.cpp:572] conv5_5/dw <- conv5_4/sep
-I0511 11:49:28.483528  5581 net.cpp:542] conv5_5/dw -> conv5_5/dw
-I0511 11:49:28.483711  5581 net.cpp:260] Setting up conv5_5/dw
-I0511 11:49:28.483718  5581 net.cpp:267] TEST Top shape for layer 87 'conv5_5/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.483726  5581 layer_factory.hpp:172] Creating layer 'conv5_5/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.483731  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483736  5581 net.cpp:200] Created Layer conv5_5/dw/bn (88)
-I0511 11:49:28.483738  5581 net.cpp:572] conv5_5/dw/bn <- conv5_5/dw
-I0511 11:49:28.483741  5581 net.cpp:527] conv5_5/dw/bn -> conv5_5/dw (in-place)
-I0511 11:49:28.483975  5581 net.cpp:260] Setting up conv5_5/dw/bn
-I0511 11:49:28.483981  5581 net.cpp:267] TEST Top shape for layer 88 'conv5_5/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.483999  5581 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Scale'
-I0511 11:49:28.484004  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.484014  5581 net.cpp:200] Created Layer conv5_5/dw/scale (89)
-I0511 11:49:28.484019  5581 net.cpp:572] conv5_5/dw/scale <- conv5_5/dw
-I0511 11:49:28.484021  5581 net.cpp:527] conv5_5/dw/scale -> conv5_5/dw (in-place)
-I0511 11:49:28.484050  5581 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Bias'
-I0511 11:49:28.484055  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.484128  5581 net.cpp:260] Setting up conv5_5/dw/scale
-I0511 11:49:28.484134  5581 net.cpp:267] TEST Top shape for layer 89 'conv5_5/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.484141  5581 layer_factory.hpp:172] Creating layer 'relu5_5/dw' of type 'ReLU'
-I0511 11:49:28.484146  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.484150  5581 net.cpp:200] Created Layer relu5_5/dw (90)
-I0511 11:49:28.484155  5581 net.cpp:572] relu5_5/dw <- conv5_5/dw
-I0511 11:49:28.484161  5581 net.cpp:527] relu5_5/dw -> conv5_5/dw (in-place)
-I0511 11:49:28.484169  5581 net.cpp:260] Setting up relu5_5/dw
-I0511 11:49:28.484174  5581 net.cpp:267] TEST Top shape for layer 90 'relu5_5/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.484179  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep' of type 'Convolution'
-I0511 11:49:28.484184  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.484192  5581 net.cpp:200] Created Layer conv5_5/sep (91)
-I0511 11:49:28.484197  5581 net.cpp:572] conv5_5/sep <- conv5_5/dw
-I0511 11:49:28.484201  5581 net.cpp:542] conv5_5/sep -> conv5_5/sep
-I0511 11:49:28.485569  5581 net.cpp:260] Setting up conv5_5/sep
-I0511 11:49:28.485576  5581 net.cpp:267] TEST Top shape for layer 91 'conv5_5/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.485584  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.485589  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.485596  5581 net.cpp:200] Created Layer conv5_5/sep/bn (92)
-I0511 11:49:28.485610  5581 net.cpp:572] conv5_5/sep/bn <- conv5_5/sep
-I0511 11:49:28.485615  5581 net.cpp:527] conv5_5/sep/bn -> conv5_5/sep (in-place)
-I0511 11:49:28.485862  5581 net.cpp:260] Setting up conv5_5/sep/bn
-I0511 11:49:28.485868  5581 net.cpp:267] TEST Top shape for layer 92 'conv5_5/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.485877  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Scale'
-I0511 11:49:28.485882  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.485889  5581 net.cpp:200] Created Layer conv5_5/sep/scale (93)
-I0511 11:49:28.485894  5581 net.cpp:572] conv5_5/sep/scale <- conv5_5/sep
-I0511 11:49:28.485899  5581 net.cpp:527] conv5_5/sep/scale -> conv5_5/sep (in-place)
-I0511 11:49:28.485930  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Bias'
-I0511 11:49:28.485935  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486006  5581 net.cpp:260] Setting up conv5_5/sep/scale
-I0511 11:49:28.486011  5581 net.cpp:267] TEST Top shape for layer 93 'conv5_5/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.486018  5581 layer_factory.hpp:172] Creating layer 'relu5_5/sep' of type 'ReLU'
-I0511 11:49:28.486023  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486029  5581 net.cpp:200] Created Layer relu5_5/sep (94)
-I0511 11:49:28.486034  5581 net.cpp:572] relu5_5/sep <- conv5_5/sep
-I0511 11:49:28.486038  5581 net.cpp:527] relu5_5/sep -> conv5_5/sep (in-place)
-I0511 11:49:28.486047  5581 net.cpp:260] Setting up relu5_5/sep
-I0511 11:49:28.486052  5581 net.cpp:267] TEST Top shape for layer 94 'relu5_5/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.486054  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep_relu5_5/sep_0_split' of type 'Split'
-I0511 11:49:28.486060  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486068  5581 net.cpp:200] Created Layer conv5_5/sep_relu5_5/sep_0_split (95)
-I0511 11:49:28.486073  5581 net.cpp:572] conv5_5/sep_relu5_5/sep_0_split <- conv5_5/sep
-I0511 11:49:28.486076  5581 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_0
-I0511 11:49:28.486084  5581 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_1
-I0511 11:49:28.486119  5581 net.cpp:260] Setting up conv5_5/sep_relu5_5/sep_0_split
-I0511 11:49:28.486125  5581 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 10 256 16 32 (1310720)
-I0511 11:49:28.486131  5581 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 10 256 16 32 (1310720)
-I0511 11:49:28.486136  5581 layer_factory.hpp:172] Creating layer 'conv5_6/dw' of type 'Convolution'
-I0511 11:49:28.486141  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486155  5581 net.cpp:200] Created Layer conv5_6/dw (96)
-I0511 11:49:28.486160  5581 net.cpp:572] conv5_6/dw <- conv5_5/sep_relu5_5/sep_0_split_0
-I0511 11:49:28.486163  5581 net.cpp:542] conv5_6/dw -> conv5_6/dw
-I0511 11:49:28.486348  5581 net.cpp:260] Setting up conv5_6/dw
-I0511 11:49:28.486354  5581 net.cpp:267] TEST Top shape for layer 96 'conv5_6/dw' 10 256 8 16 (327680)
-I0511 11:49:28.486361  5581 layer_factory.hpp:172] Creating layer 'conv5_6/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.486367  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486372  5581 net.cpp:200] Created Layer conv5_6/dw/bn (97)
-I0511 11:49:28.486377  5581 net.cpp:572] conv5_6/dw/bn <- conv5_6/dw
-I0511 11:49:28.486382  5581 net.cpp:527] conv5_6/dw/bn -> conv5_6/dw (in-place)
-I0511 11:49:28.486614  5581 net.cpp:260] Setting up conv5_6/dw/bn
-I0511 11:49:28.486621  5581 net.cpp:267] TEST Top shape for layer 97 'conv5_6/dw/bn' 10 256 8 16 (327680)
-I0511 11:49:28.486629  5581 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Scale'
-I0511 11:49:28.486634  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486646  5581 net.cpp:200] Created Layer conv5_6/dw/scale (98)
-I0511 11:49:28.486651  5581 net.cpp:572] conv5_6/dw/scale <- conv5_6/dw
-I0511 11:49:28.486656  5581 net.cpp:527] conv5_6/dw/scale -> conv5_6/dw (in-place)
-I0511 11:49:28.486686  5581 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Bias'
-I0511 11:49:28.486691  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486759  5581 net.cpp:260] Setting up conv5_6/dw/scale
-I0511 11:49:28.486765  5581 net.cpp:267] TEST Top shape for layer 98 'conv5_6/dw/scale' 10 256 8 16 (327680)
-I0511 11:49:28.486783  5581 layer_factory.hpp:172] Creating layer 'relu5_6/dw' of type 'ReLU'
-I0511 11:49:28.486788  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486793  5581 net.cpp:200] Created Layer relu5_6/dw (99)
-I0511 11:49:28.486804  5581 net.cpp:572] relu5_6/dw <- conv5_6/dw
-I0511 11:49:28.486809  5581 net.cpp:527] relu5_6/dw -> conv5_6/dw (in-place)
-I0511 11:49:28.486819  5581 net.cpp:260] Setting up relu5_6/dw
-I0511 11:49:28.486824  5581 net.cpp:267] TEST Top shape for layer 99 'relu5_6/dw' 10 256 8 16 (327680)
-I0511 11:49:28.486834  5581 layer_factory.hpp:172] Creating layer 'conv5_6/sep' of type 'Convolution'
-I0511 11:49:28.486837  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486855  5581 net.cpp:200] Created Layer conv5_6/sep (100)
-I0511 11:49:28.486860  5581 net.cpp:572] conv5_6/sep <- conv5_6/dw
-I0511 11:49:28.486868  5581 net.cpp:542] conv5_6/sep -> conv5_6/sep
-I0511 11:49:28.489506  5581 net.cpp:260] Setting up conv5_6/sep
-I0511 11:49:28.489519  5581 net.cpp:267] TEST Top shape for layer 100 'conv5_6/sep' 10 512 8 16 (655360)
-I0511 11:49:28.489526  5581 layer_factory.hpp:172] Creating layer 'conv5_6/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.489532  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.489542  5581 net.cpp:200] Created Layer conv5_6/sep/bn (101)
-I0511 11:49:28.489545  5581 net.cpp:572] conv5_6/sep/bn <- conv5_6/sep
-I0511 11:49:28.489550  5581 net.cpp:527] conv5_6/sep/bn -> conv5_6/sep (in-place)
-I0511 11:49:28.489810  5581 net.cpp:260] Setting up conv5_6/sep/bn
-I0511 11:49:28.489819  5581 net.cpp:267] TEST Top shape for layer 101 'conv5_6/sep/bn' 10 512 8 16 (655360)
-I0511 11:49:28.489828  5581 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Scale'
-I0511 11:49:28.489832  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.489840  5581 net.cpp:200] Created Layer conv5_6/sep/scale (102)
-I0511 11:49:28.489843  5581 net.cpp:572] conv5_6/sep/scale <- conv5_6/sep
-I0511 11:49:28.489848  5581 net.cpp:527] conv5_6/sep/scale -> conv5_6/sep (in-place)
-I0511 11:49:28.489881  5581 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Bias'
-I0511 11:49:28.489886  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.489965  5581 net.cpp:260] Setting up conv5_6/sep/scale
-I0511 11:49:28.489971  5581 net.cpp:267] TEST Top shape for layer 102 'conv5_6/sep/scale' 10 512 8 16 (655360)
-I0511 11:49:28.489979  5581 layer_factory.hpp:172] Creating layer 'relu5_6/sep' of type 'ReLU'
-I0511 11:49:28.489982  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.489989  5581 net.cpp:200] Created Layer relu5_6/sep (103)
-I0511 11:49:28.489992  5581 net.cpp:572] relu5_6/sep <- conv5_6/sep
-I0511 11:49:28.489996  5581 net.cpp:527] relu5_6/sep -> conv5_6/sep (in-place)
-I0511 11:49:28.490003  5581 net.cpp:260] Setting up relu5_6/sep
-I0511 11:49:28.490008  5581 net.cpp:267] TEST Top shape for layer 103 'relu5_6/sep' 10 512 8 16 (655360)
-I0511 11:49:28.490013  5581 layer_factory.hpp:172] Creating layer 'conv6/dw' of type 'Convolution'
-I0511 11:49:28.490017  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490032  5581 net.cpp:200] Created Layer conv6/dw (104)
-I0511 11:49:28.490036  5581 net.cpp:572] conv6/dw <- conv5_6/sep
-I0511 11:49:28.490042  5581 net.cpp:542] conv6/dw -> conv6/dw
-I0511 11:49:28.490264  5581 net.cpp:260] Setting up conv6/dw
-I0511 11:49:28.490272  5581 net.cpp:267] TEST Top shape for layer 104 'conv6/dw' 10 512 8 16 (655360)
-I0511 11:49:28.490278  5581 layer_factory.hpp:172] Creating layer 'conv6/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.490283  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490289  5581 net.cpp:200] Created Layer conv6/dw/bn (105)
-I0511 11:49:28.490293  5581 net.cpp:572] conv6/dw/bn <- conv6/dw
-I0511 11:49:28.490298  5581 net.cpp:527] conv6/dw/bn -> conv6/dw (in-place)
-I0511 11:49:28.490540  5581 net.cpp:260] Setting up conv6/dw/bn
-I0511 11:49:28.490547  5581 net.cpp:267] TEST Top shape for layer 105 'conv6/dw/bn' 10 512 8 16 (655360)
-I0511 11:49:28.490556  5581 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Scale'
-I0511 11:49:28.490559  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490569  5581 net.cpp:200] Created Layer conv6/dw/scale (106)
-I0511 11:49:28.490573  5581 net.cpp:572] conv6/dw/scale <- conv6/dw
-I0511 11:49:28.490578  5581 net.cpp:527] conv6/dw/scale -> conv6/dw (in-place)
-I0511 11:49:28.490607  5581 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Bias'
-I0511 11:49:28.490612  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490687  5581 net.cpp:260] Setting up conv6/dw/scale
-I0511 11:49:28.490694  5581 net.cpp:267] TEST Top shape for layer 106 'conv6/dw/scale' 10 512 8 16 (655360)
-I0511 11:49:28.490701  5581 layer_factory.hpp:172] Creating layer 'relu6/dw' of type 'ReLU'
-I0511 11:49:28.490705  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490711  5581 net.cpp:200] Created Layer relu6/dw (107)
-I0511 11:49:28.490715  5581 net.cpp:572] relu6/dw <- conv6/dw
-I0511 11:49:28.490720  5581 net.cpp:527] relu6/dw -> conv6/dw (in-place)
-I0511 11:49:28.490725  5581 net.cpp:260] Setting up relu6/dw
-I0511 11:49:28.490731  5581 net.cpp:267] TEST Top shape for layer 107 'relu6/dw' 10 512 8 16 (655360)
-I0511 11:49:28.490736  5581 layer_factory.hpp:172] Creating layer 'conv6/sep' of type 'Convolution'
-I0511 11:49:28.490741  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490748  5581 net.cpp:200] Created Layer conv6/sep (108)
-I0511 11:49:28.490752  5581 net.cpp:572] conv6/sep <- conv6/dw
-I0511 11:49:28.490757  5581 net.cpp:542] conv6/sep -> conv6/sep
-I0511 11:49:28.495813  5581 net.cpp:260] Setting up conv6/sep
-I0511 11:49:28.495831  5581 net.cpp:267] TEST Top shape for layer 108 'conv6/sep' 10 512 8 16 (655360)
-I0511 11:49:28.495841  5581 layer_factory.hpp:172] Creating layer 'conv6/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.495862  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.495872  5581 net.cpp:200] Created Layer conv6/sep/bn (109)
-I0511 11:49:28.495878  5581 net.cpp:572] conv6/sep/bn <- conv6/sep
-I0511 11:49:28.495884  5581 net.cpp:527] conv6/sep/bn -> conv6/sep (in-place)
-I0511 11:49:28.496156  5581 net.cpp:260] Setting up conv6/sep/bn
-I0511 11:49:28.496163  5581 net.cpp:267] TEST Top shape for layer 109 'conv6/sep/bn' 10 512 8 16 (655360)
-I0511 11:49:28.496171  5581 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Scale'
-I0511 11:49:28.496176  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496187  5581 net.cpp:200] Created Layer conv6/sep/scale (110)
-I0511 11:49:28.496191  5581 net.cpp:572] conv6/sep/scale <- conv6/sep
-I0511 11:49:28.496196  5581 net.cpp:527] conv6/sep/scale -> conv6/sep (in-place)
-I0511 11:49:28.496235  5581 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Bias'
-I0511 11:49:28.496240  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496492  5581 net.cpp:260] Setting up conv6/sep/scale
-I0511 11:49:28.496501  5581 net.cpp:267] TEST Top shape for layer 110 'conv6/sep/scale' 10 512 8 16 (655360)
-I0511 11:49:28.496510  5581 layer_factory.hpp:172] Creating layer 'relu6/sep' of type 'ReLU'
-I0511 11:49:28.496513  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496520  5581 net.cpp:200] Created Layer relu6/sep (111)
-I0511 11:49:28.496529  5581 net.cpp:572] relu6/sep <- conv6/sep
-I0511 11:49:28.496534  5581 net.cpp:527] relu6/sep -> conv6/sep (in-place)
-I0511 11:49:28.496541  5581 net.cpp:260] Setting up relu6/sep
-I0511 11:49:28.496546  5581 net.cpp:267] TEST Top shape for layer 111 'relu6/sep' 10 512 8 16 (655360)
-I0511 11:49:28.496551  5581 layer_factory.hpp:172] Creating layer 'conv6/sep_relu6/sep_0_split' of type 'Split'
-I0511 11:49:28.496556  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496564  5581 net.cpp:200] Created Layer conv6/sep_relu6/sep_0_split (112)
-I0511 11:49:28.496567  5581 net.cpp:572] conv6/sep_relu6/sep_0_split <- conv6/sep
-I0511 11:49:28.496572  5581 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_0
-I0511 11:49:28.496579  5581 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_1
-I0511 11:49:28.496610  5581 net.cpp:260] Setting up conv6/sep_relu6/sep_0_split
-I0511 11:49:28.496616  5581 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.496623  5581 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.496628  5581 layer_factory.hpp:172] Creating layer 'pool6' of type 'Pooling'
-I0511 11:49:28.496631  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496641  5581 net.cpp:200] Created Layer pool6 (113)
-I0511 11:49:28.496645  5581 net.cpp:572] pool6 <- conv6/sep_relu6/sep_0_split_0
-I0511 11:49:28.496651  5581 net.cpp:542] pool6 -> pool6
-I0511 11:49:28.496702  5581 net.cpp:260] Setting up pool6
-I0511 11:49:28.496708  5581 net.cpp:267] TEST Top shape for layer 113 'pool6' 10 512 5 9 (230400)
-I0511 11:49:28.496713  5581 layer_factory.hpp:172] Creating layer 'pool6_pool6_0_split' of type 'Split'
-I0511 11:49:28.496718  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496723  5581 net.cpp:200] Created Layer pool6_pool6_0_split (114)
-I0511 11:49:28.496728  5581 net.cpp:572] pool6_pool6_0_split <- pool6
-I0511 11:49:28.496733  5581 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_0
-I0511 11:49:28.496738  5581 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_1
-I0511 11:49:28.496763  5581 net.cpp:260] Setting up pool6_pool6_0_split
-I0511 11:49:28.496768  5581 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.496774  5581 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.496779  5581 layer_factory.hpp:172] Creating layer 'pool7' of type 'Pooling'
-I0511 11:49:28.496784  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496790  5581 net.cpp:200] Created Layer pool7 (115)
-I0511 11:49:28.496794  5581 net.cpp:572] pool7 <- pool6_pool6_0_split_0
-I0511 11:49:28.496799  5581 net.cpp:542] pool7 -> pool7
-I0511 11:49:28.496832  5581 net.cpp:260] Setting up pool7
-I0511 11:49:28.496839  5581 net.cpp:267] TEST Top shape for layer 115 'pool7' 10 512 3 5 (76800)
-I0511 11:49:28.496842  5581 layer_factory.hpp:172] Creating layer 'pool7_pool7_0_split' of type 'Split'
-I0511 11:49:28.496847  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496860  5581 net.cpp:200] Created Layer pool7_pool7_0_split (116)
-I0511 11:49:28.496863  5581 net.cpp:572] pool7_pool7_0_split <- pool7
-I0511 11:49:28.496868  5581 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_0
-I0511 11:49:28.496875  5581 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_1
-I0511 11:49:28.496903  5581 net.cpp:260] Setting up pool7_pool7_0_split
-I0511 11:49:28.496909  5581 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.496915  5581 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.496919  5581 layer_factory.hpp:172] Creating layer 'pool8' of type 'Pooling'
-I0511 11:49:28.496924  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496930  5581 net.cpp:200] Created Layer pool8 (117)
-I0511 11:49:28.496935  5581 net.cpp:572] pool8 <- pool7_pool7_0_split_0
-I0511 11:49:28.496939  5581 net.cpp:542] pool8 -> pool8
-I0511 11:49:28.496978  5581 net.cpp:260] Setting up pool8
-I0511 11:49:28.496984  5581 net.cpp:267] TEST Top shape for layer 117 'pool8' 10 512 3 5 (76800)
-I0511 11:49:28.496989  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1' of type 'Convolution'
-I0511 11:49:28.496994  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.497009  5581 net.cpp:200] Created Layer ctx_output1/1x1 (118)
-I0511 11:49:28.497012  5581 net.cpp:572] ctx_output1/1x1 <- conv5_5/sep_relu5_5/sep_0_split_1
-I0511 11:49:28.497018  5581 net.cpp:542] ctx_output1/1x1 -> ctx_output1/1x1
-I0511 11:49:28.500376  5581 net.cpp:260] Setting up ctx_output1/1x1
-I0511 11:49:28.500396  5581 net.cpp:267] TEST Top shape for layer 118 'ctx_output1/1x1' 10 512 16 32 (2621440)
-I0511 11:49:28.500404  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.500411  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.500422  5581 net.cpp:200] Created Layer ctx_output1/1x1/bn (119)
-I0511 11:49:28.500427  5581 net.cpp:572] ctx_output1/1x1/bn <- ctx_output1/1x1
-I0511 11:49:28.500433  5581 net.cpp:527] ctx_output1/1x1/bn -> ctx_output1/1x1 (in-place)
-I0511 11:49:28.500695  5581 net.cpp:260] Setting up ctx_output1/1x1/bn
-I0511 11:49:28.500704  5581 net.cpp:267] TEST Top shape for layer 119 'ctx_output1/1x1/bn' 10 512 16 32 (2621440)
-I0511 11:49:28.500713  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/relu' of type 'ReLU'
-I0511 11:49:28.500717  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.500725  5581 net.cpp:200] Created Layer ctx_output1/1x1/relu (120)
-I0511 11:49:28.500728  5581 net.cpp:572] ctx_output1/1x1/relu <- ctx_output1/1x1
-I0511 11:49:28.500733  5581 net.cpp:527] ctx_output1/1x1/relu -> ctx_output1/1x1 (in-place)
-I0511 11:49:28.500739  5581 net.cpp:260] Setting up ctx_output1/1x1/relu
-I0511 11:49:28.500744  5581 net.cpp:267] TEST Top shape for layer 120 'ctx_output1/1x1/relu' 10 512 16 32 (2621440)
-I0511 11:49:28.500749  5581 layer_factory.hpp:172] Creating layer 'ctx_output1' of type 'Convolution'
-I0511 11:49:28.500754  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.500763  5581 net.cpp:200] Created Layer ctx_output1 (121)
-I0511 11:49:28.500767  5581 net.cpp:572] ctx_output1 <- ctx_output1/1x1
-I0511 11:49:28.500772  5581 net.cpp:542] ctx_output1 -> ctx_output1
-I0511 11:49:28.501034  5581 net.cpp:260] Setting up ctx_output1
-I0511 11:49:28.501040  5581 net.cpp:267] TEST Top shape for layer 121 'ctx_output1' 10 512 16 32 (2621440)
-I0511 11:49:28.501049  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/bn' of type 'BatchNorm'
-I0511 11:49:28.501052  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.501060  5581 net.cpp:200] Created Layer ctx_output1/bn (122)
-I0511 11:49:28.501063  5581 net.cpp:572] ctx_output1/bn <- ctx_output1
-I0511 11:49:28.501076  5581 net.cpp:527] ctx_output1/bn -> ctx_output1 (in-place)
-I0511 11:49:28.501315  5581 net.cpp:260] Setting up ctx_output1/bn
-I0511 11:49:28.501322  5581 net.cpp:267] TEST Top shape for layer 122 'ctx_output1/bn' 10 512 16 32 (2621440)
-I0511 11:49:28.501332  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu' of type 'ReLU'
-I0511 11:49:28.501336  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.501343  5581 net.cpp:200] Created Layer ctx_output1/relu (123)
-I0511 11:49:28.501346  5581 net.cpp:572] ctx_output1/relu <- ctx_output1
-I0511 11:49:28.501351  5581 net.cpp:527] ctx_output1/relu -> ctx_output1 (in-place)
-I0511 11:49:28.501358  5581 net.cpp:260] Setting up ctx_output1/relu
-I0511 11:49:28.501363  5581 net.cpp:267] TEST Top shape for layer 123 'ctx_output1/relu' 10 512 16 32 (2621440)
-I0511 11:49:28.501366  5581 layer_factory.hpp:172] Creating layer 'ctx_output1_ctx_output1/relu_0_split' of type 'Split'
-I0511 11:49:28.501371  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.501377  5581 net.cpp:200] Created Layer ctx_output1_ctx_output1/relu_0_split (124)
-I0511 11:49:28.501381  5581 net.cpp:572] ctx_output1_ctx_output1/relu_0_split <- ctx_output1
-I0511 11:49:28.501386  5581 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_0
-I0511 11:49:28.501392  5581 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_1
-I0511 11:49:28.501399  5581 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_2
-I0511 11:49:28.501437  5581 net.cpp:260] Setting up ctx_output1_ctx_output1/relu_0_split
-I0511 11:49:28.501443  5581 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:49:28.501449  5581 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:49:28.501454  5581 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:49:28.501459  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1' of type 'Convolution'
-I0511 11:49:28.501464  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.501477  5581 net.cpp:200] Created Layer ctx_output2/1x1 (125)
-I0511 11:49:28.501482  5581 net.cpp:572] ctx_output2/1x1 <- conv6/sep_relu6/sep_0_split_1
-I0511 11:49:28.501487  5581 net.cpp:542] ctx_output2/1x1 -> ctx_output2/1x1
-I0511 11:49:28.506613  5581 net.cpp:260] Setting up ctx_output2/1x1
-I0511 11:49:28.506633  5581 net.cpp:267] TEST Top shape for layer 125 'ctx_output2/1x1' 10 512 8 16 (655360)
-I0511 11:49:28.506640  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.506654  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.506664  5581 net.cpp:200] Created Layer ctx_output2/1x1/bn (126)
-I0511 11:49:28.506670  5581 net.cpp:572] ctx_output2/1x1/bn <- ctx_output2/1x1
-I0511 11:49:28.506676  5581 net.cpp:527] ctx_output2/1x1/bn -> ctx_output2/1x1 (in-place)
-I0511 11:49:28.506932  5581 net.cpp:260] Setting up ctx_output2/1x1/bn
-I0511 11:49:28.506938  5581 net.cpp:267] TEST Top shape for layer 126 'ctx_output2/1x1/bn' 10 512 8 16 (655360)
-I0511 11:49:28.506948  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/relu' of type 'ReLU'
-I0511 11:49:28.506953  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.506958  5581 net.cpp:200] Created Layer ctx_output2/1x1/relu (127)
-I0511 11:49:28.506963  5581 net.cpp:572] ctx_output2/1x1/relu <- ctx_output2/1x1
-I0511 11:49:28.506966  5581 net.cpp:527] ctx_output2/1x1/relu -> ctx_output2/1x1 (in-place)
-I0511 11:49:28.506973  5581 net.cpp:260] Setting up ctx_output2/1x1/relu
-I0511 11:49:28.506978  5581 net.cpp:267] TEST Top shape for layer 127 'ctx_output2/1x1/relu' 10 512 8 16 (655360)
-I0511 11:49:28.506991  5581 layer_factory.hpp:172] Creating layer 'ctx_output2' of type 'Convolution'
-I0511 11:49:28.506996  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507007  5581 net.cpp:200] Created Layer ctx_output2 (128)
-I0511 11:49:28.507011  5581 net.cpp:572] ctx_output2 <- ctx_output2/1x1
-I0511 11:49:28.507016  5581 net.cpp:542] ctx_output2 -> ctx_output2
-I0511 11:49:28.507282  5581 net.cpp:260] Setting up ctx_output2
-I0511 11:49:28.507288  5581 net.cpp:267] TEST Top shape for layer 128 'ctx_output2' 10 512 8 16 (655360)
-I0511 11:49:28.507297  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/bn' of type 'BatchNorm'
-I0511 11:49:28.507300  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507308  5581 net.cpp:200] Created Layer ctx_output2/bn (129)
-I0511 11:49:28.507311  5581 net.cpp:572] ctx_output2/bn <- ctx_output2
-I0511 11:49:28.507316  5581 net.cpp:527] ctx_output2/bn -> ctx_output2 (in-place)
-I0511 11:49:28.507547  5581 net.cpp:260] Setting up ctx_output2/bn
-I0511 11:49:28.507555  5581 net.cpp:267] TEST Top shape for layer 129 'ctx_output2/bn' 10 512 8 16 (655360)
-I0511 11:49:28.507565  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu' of type 'ReLU'
-I0511 11:49:28.507568  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507573  5581 net.cpp:200] Created Layer ctx_output2/relu (130)
-I0511 11:49:28.507577  5581 net.cpp:572] ctx_output2/relu <- ctx_output2
-I0511 11:49:28.507582  5581 net.cpp:527] ctx_output2/relu -> ctx_output2 (in-place)
-I0511 11:49:28.507588  5581 net.cpp:260] Setting up ctx_output2/relu
-I0511 11:49:28.507593  5581 net.cpp:267] TEST Top shape for layer 130 'ctx_output2/relu' 10 512 8 16 (655360)
-I0511 11:49:28.507598  5581 layer_factory.hpp:172] Creating layer 'ctx_output2_ctx_output2/relu_0_split' of type 'Split'
-I0511 11:49:28.507603  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507609  5581 net.cpp:200] Created Layer ctx_output2_ctx_output2/relu_0_split (131)
-I0511 11:49:28.507613  5581 net.cpp:572] ctx_output2_ctx_output2/relu_0_split <- ctx_output2
-I0511 11:49:28.507618  5581 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_0
-I0511 11:49:28.507623  5581 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_1
-I0511 11:49:28.507629  5581 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_2
-I0511 11:49:28.507668  5581 net.cpp:260] Setting up ctx_output2_ctx_output2/relu_0_split
-I0511 11:49:28.507673  5581 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.507679  5581 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.507684  5581 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.507689  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1' of type 'Convolution'
-I0511 11:49:28.507694  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507705  5581 net.cpp:200] Created Layer ctx_output3/1x1 (132)
-I0511 11:49:28.507710  5581 net.cpp:572] ctx_output3/1x1 <- pool6_pool6_0_split_1
-I0511 11:49:28.507716  5581 net.cpp:542] ctx_output3/1x1 -> ctx_output3/1x1
-I0511 11:49:28.513507  5581 net.cpp:260] Setting up ctx_output3/1x1
-I0511 11:49:28.513531  5581 net.cpp:267] TEST Top shape for layer 132 'ctx_output3/1x1' 10 512 5 9 (230400)
-I0511 11:49:28.513540  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.513566  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.513588  5581 net.cpp:200] Created Layer ctx_output3/1x1/bn (133)
-I0511 11:49:28.513608  5581 net.cpp:572] ctx_output3/1x1/bn <- ctx_output3/1x1
-I0511 11:49:28.513620  5581 net.cpp:527] ctx_output3/1x1/bn -> ctx_output3/1x1 (in-place)
-I0511 11:49:28.514001  5581 net.cpp:260] Setting up ctx_output3/1x1/bn
-I0511 11:49:28.514010  5581 net.cpp:267] TEST Top shape for layer 133 'ctx_output3/1x1/bn' 10 512 5 9 (230400)
-I0511 11:49:28.514020  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/relu' of type 'ReLU'
-I0511 11:49:28.514025  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.514031  5581 net.cpp:200] Created Layer ctx_output3/1x1/relu (134)
-I0511 11:49:28.514035  5581 net.cpp:572] ctx_output3/1x1/relu <- ctx_output3/1x1
-I0511 11:49:28.514048  5581 net.cpp:527] ctx_output3/1x1/relu -> ctx_output3/1x1 (in-place)
-I0511 11:49:28.514061  5581 net.cpp:260] Setting up ctx_output3/1x1/relu
-I0511 11:49:28.514071  5581 net.cpp:267] TEST Top shape for layer 134 'ctx_output3/1x1/relu' 10 512 5 9 (230400)
-I0511 11:49:28.514081  5581 layer_factory.hpp:172] Creating layer 'ctx_output3' of type 'Convolution'
-I0511 11:49:28.514091  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.514107  5581 net.cpp:200] Created Layer ctx_output3 (135)
-I0511 11:49:28.514117  5581 net.cpp:572] ctx_output3 <- ctx_output3/1x1
-I0511 11:49:28.514127  5581 net.cpp:542] ctx_output3 -> ctx_output3
-I0511 11:49:28.514535  5581 net.cpp:260] Setting up ctx_output3
-I0511 11:49:28.514545  5581 net.cpp:267] TEST Top shape for layer 135 'ctx_output3' 10 512 5 9 (230400)
-I0511 11:49:28.514552  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/bn' of type 'BatchNorm'
-I0511 11:49:28.514565  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.514577  5581 net.cpp:200] Created Layer ctx_output3/bn (136)
-I0511 11:49:28.514587  5581 net.cpp:572] ctx_output3/bn <- ctx_output3
-I0511 11:49:28.514597  5581 net.cpp:527] ctx_output3/bn -> ctx_output3 (in-place)
-I0511 11:49:28.514950  5581 net.cpp:260] Setting up ctx_output3/bn
-I0511 11:49:28.514957  5581 net.cpp:267] TEST Top shape for layer 136 'ctx_output3/bn' 10 512 5 9 (230400)
-I0511 11:49:28.514967  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu' of type 'ReLU'
-I0511 11:49:28.514972  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.514989  5581 net.cpp:200] Created Layer ctx_output3/relu (137)
-I0511 11:49:28.514999  5581 net.cpp:572] ctx_output3/relu <- ctx_output3
-I0511 11:49:28.515009  5581 net.cpp:527] ctx_output3/relu -> ctx_output3 (in-place)
-I0511 11:49:28.515020  5581 net.cpp:260] Setting up ctx_output3/relu
-I0511 11:49:28.515031  5581 net.cpp:267] TEST Top shape for layer 137 'ctx_output3/relu' 10 512 5 9 (230400)
-I0511 11:49:28.515041  5581 layer_factory.hpp:172] Creating layer 'ctx_output3_ctx_output3/relu_0_split' of type 'Split'
-I0511 11:49:28.515051  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.515061  5581 net.cpp:200] Created Layer ctx_output3_ctx_output3/relu_0_split (138)
-I0511 11:49:28.515071  5581 net.cpp:572] ctx_output3_ctx_output3/relu_0_split <- ctx_output3
-I0511 11:49:28.515081  5581 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_0
-I0511 11:49:28.515092  5581 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_1
-I0511 11:49:28.515102  5581 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_2
-I0511 11:49:28.515156  5581 net.cpp:260] Setting up ctx_output3_ctx_output3/relu_0_split
-I0511 11:49:28.515163  5581 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.515169  5581 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.515184  5581 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.515199  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1' of type 'Convolution'
-I0511 11:49:28.515209  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.515228  5581 net.cpp:200] Created Layer ctx_output4/1x1 (139)
-I0511 11:49:28.515239  5581 net.cpp:572] ctx_output4/1x1 <- pool7_pool7_0_split_1
-I0511 11:49:28.515249  5581 net.cpp:542] ctx_output4/1x1 -> ctx_output4/1x1
-I0511 11:49:28.523124  5581 net.cpp:260] Setting up ctx_output4/1x1
-I0511 11:49:28.523154  5581 net.cpp:267] TEST Top shape for layer 139 'ctx_output4/1x1' 10 512 3 5 (76800)
-I0511 11:49:28.523164  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.523170  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.523181  5581 net.cpp:200] Created Layer ctx_output4/1x1/bn (140)
-I0511 11:49:28.523187  5581 net.cpp:572] ctx_output4/1x1/bn <- ctx_output4/1x1
-I0511 11:49:28.523193  5581 net.cpp:527] ctx_output4/1x1/bn -> ctx_output4/1x1 (in-place)
-I0511 11:49:28.523564  5581 net.cpp:260] Setting up ctx_output4/1x1/bn
-I0511 11:49:28.523573  5581 net.cpp:267] TEST Top shape for layer 140 'ctx_output4/1x1/bn' 10 512 3 5 (76800)
-I0511 11:49:28.523582  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/relu' of type 'ReLU'
-I0511 11:49:28.523587  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.523592  5581 net.cpp:200] Created Layer ctx_output4/1x1/relu (141)
-I0511 11:49:28.523597  5581 net.cpp:572] ctx_output4/1x1/relu <- ctx_output4/1x1
-I0511 11:49:28.523600  5581 net.cpp:527] ctx_output4/1x1/relu -> ctx_output4/1x1 (in-place)
-I0511 11:49:28.523605  5581 net.cpp:260] Setting up ctx_output4/1x1/relu
-I0511 11:49:28.523617  5581 net.cpp:267] TEST Top shape for layer 141 'ctx_output4/1x1/relu' 10 512 3 5 (76800)
-I0511 11:49:28.523635  5581 layer_factory.hpp:172] Creating layer 'ctx_output4' of type 'Convolution'
-I0511 11:49:28.523646  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.523663  5581 net.cpp:200] Created Layer ctx_output4 (142)
-I0511 11:49:28.523672  5581 net.cpp:572] ctx_output4 <- ctx_output4/1x1
-I0511 11:49:28.523682  5581 net.cpp:542] ctx_output4 -> ctx_output4
-I0511 11:49:28.524089  5581 net.cpp:260] Setting up ctx_output4
-I0511 11:49:28.524098  5581 net.cpp:267] TEST Top shape for layer 142 'ctx_output4' 10 512 3 5 (76800)
-I0511 11:49:28.524106  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/bn' of type 'BatchNorm'
-I0511 11:49:28.524109  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.524116  5581 net.cpp:200] Created Layer ctx_output4/bn (143)
-I0511 11:49:28.524121  5581 net.cpp:572] ctx_output4/bn <- ctx_output4
-I0511 11:49:28.524125  5581 net.cpp:527] ctx_output4/bn -> ctx_output4 (in-place)
-I0511 11:49:28.524469  5581 net.cpp:260] Setting up ctx_output4/bn
-I0511 11:49:28.524477  5581 net.cpp:267] TEST Top shape for layer 143 'ctx_output4/bn' 10 512 3 5 (76800)
-I0511 11:49:28.524487  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu' of type 'ReLU'
-I0511 11:49:28.524492  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.524508  5581 net.cpp:200] Created Layer ctx_output4/relu (144)
-I0511 11:49:28.524519  5581 net.cpp:572] ctx_output4/relu <- ctx_output4
-I0511 11:49:28.524538  5581 net.cpp:527] ctx_output4/relu -> ctx_output4 (in-place)
-I0511 11:49:28.524552  5581 net.cpp:260] Setting up ctx_output4/relu
-I0511 11:49:28.524565  5581 net.cpp:267] TEST Top shape for layer 144 'ctx_output4/relu' 10 512 3 5 (76800)
-I0511 11:49:28.524577  5581 layer_factory.hpp:172] Creating layer 'ctx_output4_ctx_output4/relu_0_split' of type 'Split'
-I0511 11:49:28.524590  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.524610  5581 net.cpp:200] Created Layer ctx_output4_ctx_output4/relu_0_split (145)
-I0511 11:49:28.524616  5581 net.cpp:572] ctx_output4_ctx_output4/relu_0_split <- ctx_output4
-I0511 11:49:28.524621  5581 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_0
-I0511 11:49:28.524628  5581 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_1
-I0511 11:49:28.524634  5581 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_2
-I0511 11:49:28.524685  5581 net.cpp:260] Setting up ctx_output4_ctx_output4/relu_0_split
-I0511 11:49:28.524694  5581 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.524701  5581 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.524716  5581 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.524729  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1' of type 'Convolution'
-I0511 11:49:28.524740  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.524761  5581 net.cpp:200] Created Layer ctx_output5/1x1 (146)
-I0511 11:49:28.524773  5581 net.cpp:572] ctx_output5/1x1 <- pool8
-I0511 11:49:28.524785  5581 net.cpp:542] ctx_output5/1x1 -> ctx_output5/1x1
-I0511 11:49:28.533604  5581 net.cpp:260] Setting up ctx_output5/1x1
-I0511 11:49:28.533640  5581 net.cpp:267] TEST Top shape for layer 146 'ctx_output5/1x1' 10 512 3 5 (76800)
-I0511 11:49:28.533653  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.533661  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.533675  5581 net.cpp:200] Created Layer ctx_output5/1x1/bn (147)
-I0511 11:49:28.533682  5581 net.cpp:572] ctx_output5/1x1/bn <- ctx_output5/1x1
-I0511 11:49:28.533689  5581 net.cpp:527] ctx_output5/1x1/bn -> ctx_output5/1x1 (in-place)
-I0511 11:49:28.534118  5581 net.cpp:260] Setting up ctx_output5/1x1/bn
-I0511 11:49:28.534127  5581 net.cpp:267] TEST Top shape for layer 147 'ctx_output5/1x1/bn' 10 512 3 5 (76800)
-I0511 11:49:28.534138  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/relu' of type 'ReLU'
-I0511 11:49:28.534144  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.534152  5581 net.cpp:200] Created Layer ctx_output5/1x1/relu (148)
-I0511 11:49:28.534171  5581 net.cpp:572] ctx_output5/1x1/relu <- ctx_output5/1x1
-I0511 11:49:28.534184  5581 net.cpp:527] ctx_output5/1x1/relu -> ctx_output5/1x1 (in-place)
-I0511 11:49:28.534205  5581 net.cpp:260] Setting up ctx_output5/1x1/relu
-I0511 11:49:28.534217  5581 net.cpp:267] TEST Top shape for layer 148 'ctx_output5/1x1/relu' 10 512 3 5 (76800)
-I0511 11:49:28.534229  5581 layer_factory.hpp:172] Creating layer 'ctx_output5' of type 'Convolution'
-I0511 11:49:28.534240  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.534258  5581 net.cpp:200] Created Layer ctx_output5 (149)
-I0511 11:49:28.534268  5581 net.cpp:572] ctx_output5 <- ctx_output5/1x1
-I0511 11:49:28.534279  5581 net.cpp:542] ctx_output5 -> ctx_output5
-I0511 11:49:28.534817  5581 net.cpp:260] Setting up ctx_output5
-I0511 11:49:28.534828  5581 net.cpp:267] TEST Top shape for layer 149 'ctx_output5' 10 512 3 5 (76800)
-I0511 11:49:28.534837  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/bn' of type 'BatchNorm'
-I0511 11:49:28.534842  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.534858  5581 net.cpp:200] Created Layer ctx_output5/bn (150)
-I0511 11:49:28.534869  5581 net.cpp:572] ctx_output5/bn <- ctx_output5
-I0511 11:49:28.534880  5581 net.cpp:527] ctx_output5/bn -> ctx_output5 (in-place)
-I0511 11:49:28.535284  5581 net.cpp:260] Setting up ctx_output5/bn
-I0511 11:49:28.535295  5581 net.cpp:267] TEST Top shape for layer 150 'ctx_output5/bn' 10 512 3 5 (76800)
-I0511 11:49:28.535315  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu' of type 'ReLU'
-I0511 11:49:28.535320  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.535334  5581 net.cpp:200] Created Layer ctx_output5/relu (151)
-I0511 11:49:28.535346  5581 net.cpp:572] ctx_output5/relu <- ctx_output5
-I0511 11:49:28.535357  5581 net.cpp:527] ctx_output5/relu -> ctx_output5 (in-place)
-I0511 11:49:28.535370  5581 net.cpp:260] Setting up ctx_output5/relu
-I0511 11:49:28.535382  5581 net.cpp:267] TEST Top shape for layer 151 'ctx_output5/relu' 10 512 3 5 (76800)
-I0511 11:49:28.535392  5581 layer_factory.hpp:172] Creating layer 'ctx_output5_ctx_output5/relu_0_split' of type 'Split'
-I0511 11:49:28.535403  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.535420  5581 net.cpp:200] Created Layer ctx_output5_ctx_output5/relu_0_split (152)
-I0511 11:49:28.535431  5581 net.cpp:572] ctx_output5_ctx_output5/relu_0_split <- ctx_output5
-I0511 11:49:28.535442  5581 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_0
-I0511 11:49:28.535454  5581 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_1
-I0511 11:49:28.535466  5581 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_2
-I0511 11:49:28.535522  5581 net.cpp:260] Setting up ctx_output5_ctx_output5/relu_0_split
-I0511 11:49:28.535531  5581 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.535537  5581 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.535549  5581 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.535560  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.535570  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.535585  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc (153)
-I0511 11:49:28.535598  5581 net.cpp:572] ctx_output1/relu_mbox_loc <- ctx_output1_ctx_output1/relu_0_split_0
-I0511 11:49:28.535609  5581 net.cpp:542] ctx_output1/relu_mbox_loc -> ctx_output1/relu_mbox_loc
-I0511 11:49:28.536129  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_loc
-I0511 11:49:28.536139  5581 net.cpp:267] TEST Top shape for layer 153 'ctx_output1/relu_mbox_loc' 10 16 16 32 (81920)
-I0511 11:49:28.536147  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.536154  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.536178  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_perm (154)
-I0511 11:49:28.536190  5581 net.cpp:572] ctx_output1/relu_mbox_loc_perm <- ctx_output1/relu_mbox_loc
-I0511 11:49:28.536201  5581 net.cpp:542] ctx_output1/relu_mbox_loc_perm -> ctx_output1/relu_mbox_loc_perm
-I0511 11:49:28.536312  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_perm
-I0511 11:49:28.536321  5581 net.cpp:267] TEST Top shape for layer 154 'ctx_output1/relu_mbox_loc_perm' 10 16 32 16 (81920)
-I0511 11:49:28.536334  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.536345  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.536358  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_flat (155)
-I0511 11:49:28.536370  5581 net.cpp:572] ctx_output1/relu_mbox_loc_flat <- ctx_output1/relu_mbox_loc_perm
-I0511 11:49:28.536381  5581 net.cpp:542] ctx_output1/relu_mbox_loc_flat -> ctx_output1/relu_mbox_loc_flat
-I0511 11:49:28.536516  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_flat
-I0511 11:49:28.536536  5581 net.cpp:267] TEST Top shape for layer 155 'ctx_output1/relu_mbox_loc_flat' 10 8192 (81920)
-I0511 11:49:28.536554  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.536567  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.536584  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf (156)
-I0511 11:49:28.536595  5581 net.cpp:572] ctx_output1/relu_mbox_conf <- ctx_output1_ctx_output1/relu_0_split_1
-I0511 11:49:28.536607  5581 net.cpp:542] ctx_output1/relu_mbox_conf -> ctx_output1/relu_mbox_conf
-I0511 11:49:28.538188  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_conf
-I0511 11:49:28.538213  5581 net.cpp:267] TEST Top shape for layer 156 'ctx_output1/relu_mbox_conf' 10 84 16 32 (430080)
-I0511 11:49:28.538221  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.538239  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.538259  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_perm (157)
-I0511 11:49:28.538271  5581 net.cpp:572] ctx_output1/relu_mbox_conf_perm <- ctx_output1/relu_mbox_conf
-I0511 11:49:28.538283  5581 net.cpp:542] ctx_output1/relu_mbox_conf_perm -> ctx_output1/relu_mbox_conf_perm
-I0511 11:49:28.538386  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_perm
-I0511 11:49:28.538395  5581 net.cpp:267] TEST Top shape for layer 157 'ctx_output1/relu_mbox_conf_perm' 10 16 32 84 (430080)
-I0511 11:49:28.538408  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.538419  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.538430  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_flat (158)
-I0511 11:49:28.538441  5581 net.cpp:572] ctx_output1/relu_mbox_conf_flat <- ctx_output1/relu_mbox_conf_perm
-I0511 11:49:28.538452  5581 net.cpp:542] ctx_output1/relu_mbox_conf_flat -> ctx_output1/relu_mbox_conf_flat
-I0511 11:49:28.541393  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_flat
-I0511 11:49:28.541440  5581 net.cpp:267] TEST Top shape for layer 158 'ctx_output1/relu_mbox_conf_flat' 10 43008 (430080)
-I0511 11:49:28.541450  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.541458  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.541483  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_priorbox (159)
-I0511 11:49:28.541492  5581 net.cpp:572] ctx_output1/relu_mbox_priorbox <- ctx_output1_ctx_output1/relu_0_split_2
-I0511 11:49:28.541508  5581 net.cpp:572] ctx_output1/relu_mbox_priorbox <- data_data_0_split_1
-I0511 11:49:28.541517  5581 net.cpp:542] ctx_output1/relu_mbox_priorbox -> ctx_output1/relu_mbox_priorbox
-I0511 11:49:28.541589  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_priorbox
-I0511 11:49:28.541599  5581 net.cpp:267] TEST Top shape for layer 159 'ctx_output1/relu_mbox_priorbox' 1 2 8192 (16384)
-I0511 11:49:28.541610  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.541615  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.541645  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc (160)
-I0511 11:49:28.541651  5581 net.cpp:572] ctx_output2/relu_mbox_loc <- ctx_output2_ctx_output2/relu_0_split_0
-I0511 11:49:28.541656  5581 net.cpp:542] ctx_output2/relu_mbox_loc -> ctx_output2/relu_mbox_loc
-I0511 11:49:28.542155  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_loc
-I0511 11:49:28.542165  5581 net.cpp:267] TEST Top shape for layer 160 'ctx_output2/relu_mbox_loc' 10 24 8 16 (30720)
-I0511 11:49:28.542181  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.542186  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.542207  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_perm (161)
-I0511 11:49:28.542212  5581 net.cpp:572] ctx_output2/relu_mbox_loc_perm <- ctx_output2/relu_mbox_loc
-I0511 11:49:28.542218  5581 net.cpp:542] ctx_output2/relu_mbox_loc_perm -> ctx_output2/relu_mbox_loc_perm
-I0511 11:49:28.542297  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_perm
-I0511 11:49:28.542305  5581 net.cpp:267] TEST Top shape for layer 161 'ctx_output2/relu_mbox_loc_perm' 10 8 16 24 (30720)
-I0511 11:49:28.542315  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.542321  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.542332  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_flat (162)
-I0511 11:49:28.542337  5581 net.cpp:572] ctx_output2/relu_mbox_loc_flat <- ctx_output2/relu_mbox_loc_perm
-I0511 11:49:28.542346  5581 net.cpp:542] ctx_output2/relu_mbox_loc_flat -> ctx_output2/relu_mbox_loc_flat
-I0511 11:49:28.542423  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_flat
-I0511 11:49:28.542430  5581 net.cpp:267] TEST Top shape for layer 162 'ctx_output2/relu_mbox_loc_flat' 10 3072 (30720)
-I0511 11:49:28.542440  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.542445  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.542459  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf (163)
-I0511 11:49:28.542464  5581 net.cpp:572] ctx_output2/relu_mbox_conf <- ctx_output2_ctx_output2/relu_0_split_1
-I0511 11:49:28.542474  5581 net.cpp:542] ctx_output2/relu_mbox_conf -> ctx_output2/relu_mbox_conf
-I0511 11:49:28.543903  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_conf
-I0511 11:49:28.543917  5581 net.cpp:267] TEST Top shape for layer 163 'ctx_output2/relu_mbox_conf' 10 126 8 16 (161280)
-I0511 11:49:28.543934  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.543941  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.543952  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_perm (164)
-I0511 11:49:28.543958  5581 net.cpp:572] ctx_output2/relu_mbox_conf_perm <- ctx_output2/relu_mbox_conf
-I0511 11:49:28.543968  5581 net.cpp:542] ctx_output2/relu_mbox_conf_perm -> ctx_output2/relu_mbox_conf_perm
-I0511 11:49:28.544045  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_perm
-I0511 11:49:28.544052  5581 net.cpp:267] TEST Top shape for layer 164 'ctx_output2/relu_mbox_conf_perm' 10 8 16 126 (161280)
-I0511 11:49:28.544062  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.544067  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.544078  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_flat (165)
-I0511 11:49:28.544085  5581 net.cpp:572] ctx_output2/relu_mbox_conf_flat <- ctx_output2/relu_mbox_conf_perm
-I0511 11:49:28.544095  5581 net.cpp:542] ctx_output2/relu_mbox_conf_flat -> ctx_output2/relu_mbox_conf_flat
-I0511 11:49:28.545334  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_flat
-I0511 11:49:28.545356  5581 net.cpp:267] TEST Top shape for layer 165 'ctx_output2/relu_mbox_conf_flat' 10 16128 (161280)
-I0511 11:49:28.545362  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.545377  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.545393  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_priorbox (166)
-I0511 11:49:28.545399  5581 net.cpp:572] ctx_output2/relu_mbox_priorbox <- ctx_output2_ctx_output2/relu_0_split_2
-I0511 11:49:28.545411  5581 net.cpp:572] ctx_output2/relu_mbox_priorbox <- data_data_0_split_2
-I0511 11:49:28.545418  5581 net.cpp:542] ctx_output2/relu_mbox_priorbox -> ctx_output2/relu_mbox_priorbox
-I0511 11:49:28.545473  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_priorbox
-I0511 11:49:28.545481  5581 net.cpp:267] TEST Top shape for layer 166 'ctx_output2/relu_mbox_priorbox' 1 2 3072 (6144)
-I0511 11:49:28.545492  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.545497  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.545521  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc (167)
-I0511 11:49:28.545527  5581 net.cpp:572] ctx_output3/relu_mbox_loc <- ctx_output3_ctx_output3/relu_0_split_0
-I0511 11:49:28.545537  5581 net.cpp:542] ctx_output3/relu_mbox_loc -> ctx_output3/relu_mbox_loc
-I0511 11:49:28.546008  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_loc
-I0511 11:49:28.546016  5581 net.cpp:267] TEST Top shape for layer 167 'ctx_output3/relu_mbox_loc' 10 24 5 9 (10800)
-I0511 11:49:28.546030  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.546036  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.546047  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_perm (168)
-I0511 11:49:28.546052  5581 net.cpp:572] ctx_output3/relu_mbox_loc_perm <- ctx_output3/relu_mbox_loc
-I0511 11:49:28.546061  5581 net.cpp:542] ctx_output3/relu_mbox_loc_perm -> ctx_output3/relu_mbox_loc_perm
-I0511 11:49:28.546142  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_perm
-I0511 11:49:28.546149  5581 net.cpp:267] TEST Top shape for layer 168 'ctx_output3/relu_mbox_loc_perm' 10 5 9 24 (10800)
-I0511 11:49:28.546159  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.546164  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.546176  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_flat (169)
-I0511 11:49:28.546180  5581 net.cpp:572] ctx_output3/relu_mbox_loc_flat <- ctx_output3/relu_mbox_loc_perm
-I0511 11:49:28.546190  5581 net.cpp:542] ctx_output3/relu_mbox_loc_flat -> ctx_output3/relu_mbox_loc_flat
-I0511 11:49:28.546272  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_flat
-I0511 11:49:28.546278  5581 net.cpp:267] TEST Top shape for layer 169 'ctx_output3/relu_mbox_loc_flat' 10 1080 (10800)
-I0511 11:49:28.546288  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.546293  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.546313  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf (170)
-I0511 11:49:28.546319  5581 net.cpp:572] ctx_output3/relu_mbox_conf <- ctx_output3_ctx_output3/relu_0_split_1
-I0511 11:49:28.546329  5581 net.cpp:542] ctx_output3/relu_mbox_conf -> ctx_output3/relu_mbox_conf
-I0511 11:49:28.547796  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_conf
-I0511 11:49:28.547819  5581 net.cpp:267] TEST Top shape for layer 170 'ctx_output3/relu_mbox_conf' 10 126 5 9 (56700)
-I0511 11:49:28.547828  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.547842  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.547854  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_perm (171)
-I0511 11:49:28.547860  5581 net.cpp:572] ctx_output3/relu_mbox_conf_perm <- ctx_output3/relu_mbox_conf
-I0511 11:49:28.547873  5581 net.cpp:542] ctx_output3/relu_mbox_conf_perm -> ctx_output3/relu_mbox_conf_perm
-I0511 11:49:28.547966  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_perm
-I0511 11:49:28.547972  5581 net.cpp:267] TEST Top shape for layer 171 'ctx_output3/relu_mbox_conf_perm' 10 5 9 126 (56700)
-I0511 11:49:28.547984  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.547989  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548012  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_flat (172)
-I0511 11:49:28.548018  5581 net.cpp:572] ctx_output3/relu_mbox_conf_flat <- ctx_output3/relu_mbox_conf_perm
-I0511 11:49:28.548029  5581 net.cpp:542] ctx_output3/relu_mbox_conf_flat -> ctx_output3/relu_mbox_conf_flat
-I0511 11:49:28.548180  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_flat
-I0511 11:49:28.548187  5581 net.cpp:267] TEST Top shape for layer 172 'ctx_output3/relu_mbox_conf_flat' 10 5670 (56700)
-I0511 11:49:28.548197  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.548203  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548215  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_priorbox (173)
-I0511 11:49:28.548219  5581 net.cpp:572] ctx_output3/relu_mbox_priorbox <- ctx_output3_ctx_output3/relu_0_split_2
-I0511 11:49:28.548230  5581 net.cpp:572] ctx_output3/relu_mbox_priorbox <- data_data_0_split_3
-I0511 11:49:28.548238  5581 net.cpp:542] ctx_output3/relu_mbox_priorbox -> ctx_output3/relu_mbox_priorbox
-I0511 11:49:28.548266  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_priorbox
-I0511 11:49:28.548272  5581 net.cpp:267] TEST Top shape for layer 173 'ctx_output3/relu_mbox_priorbox' 1 2 1080 (2160)
-I0511 11:49:28.548282  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.548288  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548312  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc (174)
-I0511 11:49:28.548317  5581 net.cpp:572] ctx_output4/relu_mbox_loc <- ctx_output4_ctx_output4/relu_0_split_0
-I0511 11:49:28.548328  5581 net.cpp:542] ctx_output4/relu_mbox_loc -> ctx_output4/relu_mbox_loc
-I0511 11:49:28.548722  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_loc
-I0511 11:49:28.548732  5581 net.cpp:267] TEST Top shape for layer 174 'ctx_output4/relu_mbox_loc' 10 16 3 5 (2400)
-I0511 11:49:28.548738  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.548750  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548758  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_perm (175)
-I0511 11:49:28.548764  5581 net.cpp:572] ctx_output4/relu_mbox_loc_perm <- ctx_output4/relu_mbox_loc
-I0511 11:49:28.548774  5581 net.cpp:542] ctx_output4/relu_mbox_loc_perm -> ctx_output4/relu_mbox_loc_perm
-I0511 11:49:28.548852  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_perm
-I0511 11:49:28.548859  5581 net.cpp:267] TEST Top shape for layer 175 'ctx_output4/relu_mbox_loc_perm' 10 3 5 16 (2400)
-I0511 11:49:28.548869  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.548876  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548880  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_flat (176)
-I0511 11:49:28.548890  5581 net.cpp:572] ctx_output4/relu_mbox_loc_flat <- ctx_output4/relu_mbox_loc_perm
-I0511 11:49:28.548895  5581 net.cpp:542] ctx_output4/relu_mbox_loc_flat -> ctx_output4/relu_mbox_loc_flat
-I0511 11:49:28.548956  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_flat
-I0511 11:49:28.548964  5581 net.cpp:267] TEST Top shape for layer 176 'ctx_output4/relu_mbox_loc_flat' 10 240 (2400)
-I0511 11:49:28.548974  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.548979  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548992  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf (177)
-I0511 11:49:28.548997  5581 net.cpp:572] ctx_output4/relu_mbox_conf <- ctx_output4_ctx_output4/relu_0_split_1
-I0511 11:49:28.549010  5581 net.cpp:542] ctx_output4/relu_mbox_conf -> ctx_output4/relu_mbox_conf
-I0511 11:49:28.550056  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_conf
-I0511 11:49:28.550068  5581 net.cpp:267] TEST Top shape for layer 177 'ctx_output4/relu_mbox_conf' 10 84 3 5 (12600)
-I0511 11:49:28.550076  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.550089  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550099  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_perm (178)
-I0511 11:49:28.550106  5581 net.cpp:572] ctx_output4/relu_mbox_conf_perm <- ctx_output4/relu_mbox_conf
-I0511 11:49:28.550117  5581 net.cpp:542] ctx_output4/relu_mbox_conf_perm -> ctx_output4/relu_mbox_conf_perm
-I0511 11:49:28.550205  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_perm
-I0511 11:49:28.550212  5581 net.cpp:267] TEST Top shape for layer 178 'ctx_output4/relu_mbox_conf_perm' 10 3 5 84 (12600)
-I0511 11:49:28.550222  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.550227  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550237  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_flat (179)
-I0511 11:49:28.550242  5581 net.cpp:572] ctx_output4/relu_mbox_conf_flat <- ctx_output4/relu_mbox_conf_perm
-I0511 11:49:28.550252  5581 net.cpp:542] ctx_output4/relu_mbox_conf_flat -> ctx_output4/relu_mbox_conf_flat
-I0511 11:49:28.550349  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_flat
-I0511 11:49:28.550356  5581 net.cpp:267] TEST Top shape for layer 179 'ctx_output4/relu_mbox_conf_flat' 10 1260 (12600)
-I0511 11:49:28.550367  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.550372  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550384  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_priorbox (180)
-I0511 11:49:28.550388  5581 net.cpp:572] ctx_output4/relu_mbox_priorbox <- ctx_output4_ctx_output4/relu_0_split_2
-I0511 11:49:28.550400  5581 net.cpp:572] ctx_output4/relu_mbox_priorbox <- data_data_0_split_4
-I0511 11:49:28.550405  5581 net.cpp:542] ctx_output4/relu_mbox_priorbox -> ctx_output4/relu_mbox_priorbox
-I0511 11:49:28.550434  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_priorbox
-I0511 11:49:28.550441  5581 net.cpp:267] TEST Top shape for layer 180 'ctx_output4/relu_mbox_priorbox' 1 2 240 (480)
-I0511 11:49:28.550451  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.550456  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550469  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc (181)
-I0511 11:49:28.550474  5581 net.cpp:572] ctx_output5/relu_mbox_loc <- ctx_output5_ctx_output5/relu_0_split_0
-I0511 11:49:28.550484  5581 net.cpp:542] ctx_output5/relu_mbox_loc -> ctx_output5/relu_mbox_loc
-I0511 11:49:28.550839  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_loc
-I0511 11:49:28.550848  5581 net.cpp:267] TEST Top shape for layer 181 'ctx_output5/relu_mbox_loc' 10 16 3 5 (2400)
-I0511 11:49:28.550860  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.550865  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550876  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_perm (182)
-I0511 11:49:28.550881  5581 net.cpp:572] ctx_output5/relu_mbox_loc_perm <- ctx_output5/relu_mbox_loc
-I0511 11:49:28.550891  5581 net.cpp:542] ctx_output5/relu_mbox_loc_perm -> ctx_output5/relu_mbox_loc_perm
-I0511 11:49:28.550966  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_perm
-I0511 11:49:28.550972  5581 net.cpp:267] TEST Top shape for layer 182 'ctx_output5/relu_mbox_loc_perm' 10 3 5 16 (2400)
-I0511 11:49:28.550987  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.550997  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.551007  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_flat (183)
-I0511 11:49:28.551012  5581 net.cpp:572] ctx_output5/relu_mbox_loc_flat <- ctx_output5/relu_mbox_loc_perm
-I0511 11:49:28.551020  5581 net.cpp:542] ctx_output5/relu_mbox_loc_flat -> ctx_output5/relu_mbox_loc_flat
-I0511 11:49:28.551079  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_flat
-I0511 11:49:28.551085  5581 net.cpp:267] TEST Top shape for layer 183 'ctx_output5/relu_mbox_loc_flat' 10 240 (2400)
-I0511 11:49:28.551095  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.551100  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.551118  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf (184)
-I0511 11:49:28.551123  5581 net.cpp:572] ctx_output5/relu_mbox_conf <- ctx_output5_ctx_output5/relu_0_split_1
-I0511 11:49:28.551133  5581 net.cpp:542] ctx_output5/relu_mbox_conf -> ctx_output5/relu_mbox_conf
-I0511 11:49:28.552150  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_conf
-I0511 11:49:28.552160  5581 net.cpp:267] TEST Top shape for layer 184 'ctx_output5/relu_mbox_conf' 10 84 3 5 (12600)
-I0511 11:49:28.552175  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.552181  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552191  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_perm (185)
-I0511 11:49:28.552196  5581 net.cpp:572] ctx_output5/relu_mbox_conf_perm <- ctx_output5/relu_mbox_conf
-I0511 11:49:28.552206  5581 net.cpp:542] ctx_output5/relu_mbox_conf_perm -> ctx_output5/relu_mbox_conf_perm
-I0511 11:49:28.552289  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_perm
-I0511 11:49:28.552295  5581 net.cpp:267] TEST Top shape for layer 185 'ctx_output5/relu_mbox_conf_perm' 10 3 5 84 (12600)
-I0511 11:49:28.552305  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.552310  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552321  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_flat (186)
-I0511 11:49:28.552325  5581 net.cpp:572] ctx_output5/relu_mbox_conf_flat <- ctx_output5/relu_mbox_conf_perm
-I0511 11:49:28.552335  5581 net.cpp:542] ctx_output5/relu_mbox_conf_flat -> ctx_output5/relu_mbox_conf_flat
-I0511 11:49:28.552394  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_flat
-I0511 11:49:28.552400  5581 net.cpp:267] TEST Top shape for layer 186 'ctx_output5/relu_mbox_conf_flat' 10 1260 (12600)
-I0511 11:49:28.552410  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.552422  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552433  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_priorbox (187)
-I0511 11:49:28.552438  5581 net.cpp:572] ctx_output5/relu_mbox_priorbox <- ctx_output5_ctx_output5/relu_0_split_2
-I0511 11:49:28.552448  5581 net.cpp:572] ctx_output5/relu_mbox_priorbox <- data_data_0_split_5
-I0511 11:49:28.552453  5581 net.cpp:542] ctx_output5/relu_mbox_priorbox -> ctx_output5/relu_mbox_priorbox
-I0511 11:49:28.552481  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_priorbox
-I0511 11:49:28.552489  5581 net.cpp:267] TEST Top shape for layer 187 'ctx_output5/relu_mbox_priorbox' 1 2 240 (480)
-I0511 11:49:28.552498  5581 layer_factory.hpp:172] Creating layer 'mbox_loc' of type 'Concat'
-I0511 11:49:28.552502  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552515  5581 net.cpp:200] Created Layer mbox_loc (188)
-I0511 11:49:28.552520  5581 net.cpp:572] mbox_loc <- ctx_output1/relu_mbox_loc_flat
-I0511 11:49:28.552533  5581 net.cpp:572] mbox_loc <- ctx_output2/relu_mbox_loc_flat
-I0511 11:49:28.552552  5581 net.cpp:572] mbox_loc <- ctx_output3/relu_mbox_loc_flat
-I0511 11:49:28.552557  5581 net.cpp:572] mbox_loc <- ctx_output4/relu_mbox_loc_flat
-I0511 11:49:28.552562  5581 net.cpp:572] mbox_loc <- ctx_output5/relu_mbox_loc_flat
-I0511 11:49:28.552568  5581 net.cpp:542] mbox_loc -> mbox_loc
-I0511 11:49:28.552592  5581 net.cpp:260] Setting up mbox_loc
-I0511 11:49:28.552598  5581 net.cpp:267] TEST Top shape for layer 188 'mbox_loc' 10 12824 (128240)
-I0511 11:49:28.552603  5581 layer_factory.hpp:172] Creating layer 'mbox_conf' of type 'Concat'
-I0511 11:49:28.552608  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552614  5581 net.cpp:200] Created Layer mbox_conf (189)
-I0511 11:49:28.552618  5581 net.cpp:572] mbox_conf <- ctx_output1/relu_mbox_conf_flat
-I0511 11:49:28.552624  5581 net.cpp:572] mbox_conf <- ctx_output2/relu_mbox_conf_flat
-I0511 11:49:28.552630  5581 net.cpp:572] mbox_conf <- ctx_output3/relu_mbox_conf_flat
-I0511 11:49:28.552635  5581 net.cpp:572] mbox_conf <- ctx_output4/relu_mbox_conf_flat
-I0511 11:49:28.552640  5581 net.cpp:572] mbox_conf <- ctx_output5/relu_mbox_conf_flat
-I0511 11:49:28.552645  5581 net.cpp:542] mbox_conf -> mbox_conf
-I0511 11:49:28.552670  5581 net.cpp:260] Setting up mbox_conf
-I0511 11:49:28.552676  5581 net.cpp:267] TEST Top shape for layer 189 'mbox_conf' 10 67326 (673260)
-I0511 11:49:28.552681  5581 layer_factory.hpp:172] Creating layer 'mbox_priorbox' of type 'Concat'
-I0511 11:49:28.552685  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552691  5581 net.cpp:200] Created Layer mbox_priorbox (190)
-I0511 11:49:28.552695  5581 net.cpp:572] mbox_priorbox <- ctx_output1/relu_mbox_priorbox
-I0511 11:49:28.552700  5581 net.cpp:572] mbox_priorbox <- ctx_output2/relu_mbox_priorbox
-I0511 11:49:28.552706  5581 net.cpp:572] mbox_priorbox <- ctx_output3/relu_mbox_priorbox
-I0511 11:49:28.552711  5581 net.cpp:572] mbox_priorbox <- ctx_output4/relu_mbox_priorbox
-I0511 11:49:28.552716  5581 net.cpp:572] mbox_priorbox <- ctx_output5/relu_mbox_priorbox
-I0511 11:49:28.552721  5581 net.cpp:542] mbox_priorbox -> mbox_priorbox
-I0511 11:49:28.552738  5581 net.cpp:260] Setting up mbox_priorbox
-I0511 11:49:28.552744  5581 net.cpp:267] TEST Top shape for layer 190 'mbox_priorbox' 1 2 12824 (25648)
-I0511 11:49:28.552749  5581 layer_factory.hpp:172] Creating layer 'mbox_conf_reshape' of type 'Reshape'
-I0511 11:49:28.552754  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552763  5581 net.cpp:200] Created Layer mbox_conf_reshape (191)
-I0511 11:49:28.552767  5581 net.cpp:572] mbox_conf_reshape <- mbox_conf
-I0511 11:49:28.552772  5581 net.cpp:542] mbox_conf_reshape -> mbox_conf_reshape
-I0511 11:49:28.552793  5581 net.cpp:260] Setting up mbox_conf_reshape
-I0511 11:49:28.552798  5581 net.cpp:267] TEST Top shape for layer 191 'mbox_conf_reshape' 10 3206 21 (673260)
-I0511 11:49:28.552803  5581 layer_factory.hpp:172] Creating layer 'mbox_conf_softmax' of type 'Softmax'
-I0511 11:49:28.552808  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552822  5581 net.cpp:200] Created Layer mbox_conf_softmax (192)
-I0511 11:49:28.552826  5581 net.cpp:572] mbox_conf_softmax <- mbox_conf_reshape
-I0511 11:49:28.552831  5581 net.cpp:542] mbox_conf_softmax -> mbox_conf_softmax
-I0511 11:49:28.552882  5581 net.cpp:260] Setting up mbox_conf_softmax
-I0511 11:49:28.552888  5581 net.cpp:267] TEST Top shape for layer 192 'mbox_conf_softmax' 10 3206 21 (673260)
-I0511 11:49:28.552893  5581 layer_factory.hpp:172] Creating layer 'mbox_conf_flatten' of type 'Flatten'
-I0511 11:49:28.552897  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552903  5581 net.cpp:200] Created Layer mbox_conf_flatten (193)
-I0511 11:49:28.552908  5581 net.cpp:572] mbox_conf_flatten <- mbox_conf_softmax
-I0511 11:49:28.552918  5581 net.cpp:542] mbox_conf_flatten -> mbox_conf_flatten
-I0511 11:49:28.565068  5581 net.cpp:260] Setting up mbox_conf_flatten
-I0511 11:49:28.565095  5581 net.cpp:267] TEST Top shape for layer 193 'mbox_conf_flatten' 10 67326 (673260)
-I0511 11:49:28.565104  5581 layer_factory.hpp:172] Creating layer 'detection_out' of type 'DetectionOutput'
-I0511 11:49:28.565111  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.565136  5581 net.cpp:200] Created Layer detection_out (194)
-I0511 11:49:28.565143  5581 net.cpp:572] detection_out <- mbox_loc
-I0511 11:49:28.565151  5581 net.cpp:572] detection_out <- mbox_conf_flatten
-I0511 11:49:28.565156  5581 net.cpp:572] detection_out <- mbox_priorbox
-I0511 11:49:28.565161  5581 net.cpp:542] detection_out -> detection_out
-I0511 11:49:28.566352  5581 net.cpp:260] Setting up detection_out
-I0511 11:49:28.566362  5581 net.cpp:267] TEST Top shape for layer 194 'detection_out' 1 1 1 7 (7)
-I0511 11:49:28.566367  5581 layer_factory.hpp:172] Creating layer 'detection_eval' of type 'DetectionEvaluate'
-I0511 11:49:28.566373  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.566382  5581 net.cpp:200] Created Layer detection_eval (195)
-I0511 11:49:28.566387  5581 net.cpp:572] detection_eval <- detection_out
-I0511 11:49:28.566392  5581 net.cpp:572] detection_eval <- label
-I0511 11:49:28.566399  5581 net.cpp:542] detection_eval -> detection_eval
-I0511 11:49:28.567126  5581 net.cpp:260] Setting up detection_eval
-I0511 11:49:28.567133  5581 net.cpp:267] TEST Top shape for layer 195 'detection_eval' 1 1 21 5 (105)
-I0511 11:49:28.567139  5581 net.cpp:338] detection_eval does not need backward computation.
-I0511 11:49:28.567143  5581 net.cpp:338] detection_out does not need backward computation.
-I0511 11:49:28.567149  5581 net.cpp:338] mbox_conf_flatten does not need backward computation.
-I0511 11:49:28.567153  5581 net.cpp:338] mbox_conf_softmax does not need backward computation.
-I0511 11:49:28.567157  5581 net.cpp:338] mbox_conf_reshape does not need backward computation.
-I0511 11:49:28.567162  5581 net.cpp:338] mbox_priorbox does not need backward computation.
-I0511 11:49:28.567168  5581 net.cpp:338] mbox_conf does not need backward computation.
-I0511 11:49:28.567173  5581 net.cpp:338] mbox_loc does not need backward computation.
-I0511 11:49:28.567178  5581 net.cpp:338] ctx_output5/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567183  5581 net.cpp:338] ctx_output5/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567188  5581 net.cpp:338] ctx_output5/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567191  5581 net.cpp:338] ctx_output5/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567196  5581 net.cpp:338] ctx_output5/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567200  5581 net.cpp:338] ctx_output5/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567204  5581 net.cpp:338] ctx_output5/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567209  5581 net.cpp:338] ctx_output4/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567214  5581 net.cpp:338] ctx_output4/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567219  5581 net.cpp:338] ctx_output4/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567222  5581 net.cpp:338] ctx_output4/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567226  5581 net.cpp:338] ctx_output4/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567231  5581 net.cpp:338] ctx_output4/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567236  5581 net.cpp:338] ctx_output4/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567240  5581 net.cpp:338] ctx_output3/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567245  5581 net.cpp:338] ctx_output3/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567261  5581 net.cpp:338] ctx_output3/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567266  5581 net.cpp:338] ctx_output3/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567271  5581 net.cpp:338] ctx_output3/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567276  5581 net.cpp:338] ctx_output3/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567279  5581 net.cpp:338] ctx_output3/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567283  5581 net.cpp:338] ctx_output2/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567288  5581 net.cpp:338] ctx_output2/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567292  5581 net.cpp:338] ctx_output2/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567296  5581 net.cpp:338] ctx_output2/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567301  5581 net.cpp:338] ctx_output2/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567304  5581 net.cpp:338] ctx_output2/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567309  5581 net.cpp:338] ctx_output2/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567313  5581 net.cpp:338] ctx_output1/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567318  5581 net.cpp:338] ctx_output1/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567322  5581 net.cpp:338] ctx_output1/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567327  5581 net.cpp:338] ctx_output1/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567330  5581 net.cpp:338] ctx_output1/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567335  5581 net.cpp:338] ctx_output1/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567339  5581 net.cpp:338] ctx_output1/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567344  5581 net.cpp:338] ctx_output5_ctx_output5/relu_0_split does not need backward computation.
-I0511 11:49:28.567348  5581 net.cpp:338] ctx_output5/relu does not need backward computation.
-I0511 11:49:28.567353  5581 net.cpp:338] ctx_output5/bn does not need backward computation.
-I0511 11:49:28.567358  5581 net.cpp:338] ctx_output5 does not need backward computation.
-I0511 11:49:28.567363  5581 net.cpp:338] ctx_output5/1x1/relu does not need backward computation.
-I0511 11:49:28.567366  5581 net.cpp:338] ctx_output5/1x1/bn does not need backward computation.
-I0511 11:49:28.567370  5581 net.cpp:338] ctx_output5/1x1 does not need backward computation.
-I0511 11:49:28.567375  5581 net.cpp:338] ctx_output4_ctx_output4/relu_0_split does not need backward computation.
-I0511 11:49:28.567379  5581 net.cpp:338] ctx_output4/relu does not need backward computation.
-I0511 11:49:28.567384  5581 net.cpp:338] ctx_output4/bn does not need backward computation.
-I0511 11:49:28.567389  5581 net.cpp:338] ctx_output4 does not need backward computation.
-I0511 11:49:28.567392  5581 net.cpp:338] ctx_output4/1x1/relu does not need backward computation.
-I0511 11:49:28.567397  5581 net.cpp:338] ctx_output4/1x1/bn does not need backward computation.
-I0511 11:49:28.567401  5581 net.cpp:338] ctx_output4/1x1 does not need backward computation.
-I0511 11:49:28.567405  5581 net.cpp:338] ctx_output3_ctx_output3/relu_0_split does not need backward computation.
-I0511 11:49:28.567410  5581 net.cpp:338] ctx_output3/relu does not need backward computation.
-I0511 11:49:28.567414  5581 net.cpp:338] ctx_output3/bn does not need backward computation.
-I0511 11:49:28.567418  5581 net.cpp:338] ctx_output3 does not need backward computation.
-I0511 11:49:28.567423  5581 net.cpp:338] ctx_output3/1x1/relu does not need backward computation.
-I0511 11:49:28.567427  5581 net.cpp:338] ctx_output3/1x1/bn does not need backward computation.
-I0511 11:49:28.567431  5581 net.cpp:338] ctx_output3/1x1 does not need backward computation.
-I0511 11:49:28.567440  5581 net.cpp:338] ctx_output2_ctx_output2/relu_0_split does not need backward computation.
-I0511 11:49:28.567445  5581 net.cpp:338] ctx_output2/relu does not need backward computation.
-I0511 11:49:28.567448  5581 net.cpp:338] ctx_output2/bn does not need backward computation.
-I0511 11:49:28.567453  5581 net.cpp:338] ctx_output2 does not need backward computation.
-I0511 11:49:28.567457  5581 net.cpp:338] ctx_output2/1x1/relu does not need backward computation.
-I0511 11:49:28.567461  5581 net.cpp:338] ctx_output2/1x1/bn does not need backward computation.
-I0511 11:49:28.567466  5581 net.cpp:338] ctx_output2/1x1 does not need backward computation.
-I0511 11:49:28.567471  5581 net.cpp:338] ctx_output1_ctx_output1/relu_0_split does not need backward computation.
-I0511 11:49:28.567474  5581 net.cpp:338] ctx_output1/relu does not need backward computation.
-I0511 11:49:28.567479  5581 net.cpp:338] ctx_output1/bn does not need backward computation.
-I0511 11:49:28.567483  5581 net.cpp:338] ctx_output1 does not need backward computation.
-I0511 11:49:28.567488  5581 net.cpp:338] ctx_output1/1x1/relu does not need backward computation.
-I0511 11:49:28.567492  5581 net.cpp:338] ctx_output1/1x1/bn does not need backward computation.
-I0511 11:49:28.567497  5581 net.cpp:338] ctx_output1/1x1 does not need backward computation.
-I0511 11:49:28.567500  5581 net.cpp:338] pool8 does not need backward computation.
-I0511 11:49:28.567505  5581 net.cpp:338] pool7_pool7_0_split does not need backward computation.
-I0511 11:49:28.567509  5581 net.cpp:338] pool7 does not need backward computation.
-I0511 11:49:28.567514  5581 net.cpp:338] pool6_pool6_0_split does not need backward computation.
-I0511 11:49:28.567518  5581 net.cpp:338] pool6 does not need backward computation.
-I0511 11:49:28.567523  5581 net.cpp:338] conv6/sep_relu6/sep_0_split does not need backward computation.
-I0511 11:49:28.567528  5581 net.cpp:338] relu6/sep does not need backward computation.
-I0511 11:49:28.567533  5581 net.cpp:338] conv6/sep/scale does not need backward computation.
-I0511 11:49:28.567536  5581 net.cpp:338] conv6/sep/bn does not need backward computation.
-I0511 11:49:28.567540  5581 net.cpp:338] conv6/sep does not need backward computation.
-I0511 11:49:28.567545  5581 net.cpp:338] relu6/dw does not need backward computation.
-I0511 11:49:28.567549  5581 net.cpp:338] conv6/dw/scale does not need backward computation.
-I0511 11:49:28.567554  5581 net.cpp:338] conv6/dw/bn does not need backward computation.
-I0511 11:49:28.567557  5581 net.cpp:338] conv6/dw does not need backward computation.
-I0511 11:49:28.567562  5581 net.cpp:338] relu5_6/sep does not need backward computation.
-I0511 11:49:28.567566  5581 net.cpp:338] conv5_6/sep/scale does not need backward computation.
-I0511 11:49:28.567570  5581 net.cpp:338] conv5_6/sep/bn does not need backward computation.
-I0511 11:49:28.567575  5581 net.cpp:338] conv5_6/sep does not need backward computation.
-I0511 11:49:28.567579  5581 net.cpp:338] relu5_6/dw does not need backward computation.
-I0511 11:49:28.567584  5581 net.cpp:338] conv5_6/dw/scale does not need backward computation.
-I0511 11:49:28.567587  5581 net.cpp:338] conv5_6/dw/bn does not need backward computation.
-I0511 11:49:28.567591  5581 net.cpp:338] conv5_6/dw does not need backward computation.
-I0511 11:49:28.567597  5581 net.cpp:338] conv5_5/sep_relu5_5/sep_0_split does not need backward computation.
-I0511 11:49:28.567601  5581 net.cpp:338] relu5_5/sep does not need backward computation.
-I0511 11:49:28.567605  5581 net.cpp:338] conv5_5/sep/scale does not need backward computation.
-I0511 11:49:28.567610  5581 net.cpp:338] conv5_5/sep/bn does not need backward computation.
-I0511 11:49:28.567613  5581 net.cpp:338] conv5_5/sep does not need backward computation.
-I0511 11:49:28.567617  5581 net.cpp:338] relu5_5/dw does not need backward computation.
-I0511 11:49:28.567622  5581 net.cpp:338] conv5_5/dw/scale does not need backward computation.
-I0511 11:49:28.567626  5581 net.cpp:338] conv5_5/dw/bn does not need backward computation.
-I0511 11:49:28.567633  5581 net.cpp:338] conv5_5/dw does not need backward computation.
-I0511 11:49:28.567638  5581 net.cpp:338] relu5_4/sep does not need backward computation.
-I0511 11:49:28.567643  5581 net.cpp:338] conv5_4/sep/scale does not need backward computation.
-I0511 11:49:28.567647  5581 net.cpp:338] conv5_4/sep/bn does not need backward computation.
-I0511 11:49:28.567651  5581 net.cpp:338] conv5_4/sep does not need backward computation.
-I0511 11:49:28.567656  5581 net.cpp:338] relu5_4/dw does not need backward computation.
-I0511 11:49:28.567659  5581 net.cpp:338] conv5_4/dw/scale does not need backward computation.
-I0511 11:49:28.567663  5581 net.cpp:338] conv5_4/dw/bn does not need backward computation.
-I0511 11:49:28.567668  5581 net.cpp:338] conv5_4/dw does not need backward computation.
-I0511 11:49:28.567672  5581 net.cpp:338] relu5_3/sep does not need backward computation.
-I0511 11:49:28.567677  5581 net.cpp:338] conv5_3/sep/scale does not need backward computation.
-I0511 11:49:28.567680  5581 net.cpp:338] conv5_3/sep/bn does not need backward computation.
-I0511 11:49:28.567684  5581 net.cpp:338] conv5_3/sep does not need backward computation.
-I0511 11:49:28.567689  5581 net.cpp:338] relu5_3/dw does not need backward computation.
-I0511 11:49:28.567693  5581 net.cpp:338] conv5_3/dw/scale does not need backward computation.
-I0511 11:49:28.567698  5581 net.cpp:338] conv5_3/dw/bn does not need backward computation.
-I0511 11:49:28.567701  5581 net.cpp:338] conv5_3/dw does not need backward computation.
-I0511 11:49:28.567706  5581 net.cpp:338] relu5_2/sep does not need backward computation.
-I0511 11:49:28.567710  5581 net.cpp:338] conv5_2/sep/scale does not need backward computation.
-I0511 11:49:28.567714  5581 net.cpp:338] conv5_2/sep/bn does not need backward computation.
-I0511 11:49:28.567718  5581 net.cpp:338] conv5_2/sep does not need backward computation.
-I0511 11:49:28.567723  5581 net.cpp:338] relu5_2/dw does not need backward computation.
-I0511 11:49:28.567726  5581 net.cpp:338] conv5_2/dw/scale does not need backward computation.
-I0511 11:49:28.567730  5581 net.cpp:338] conv5_2/dw/bn does not need backward computation.
-I0511 11:49:28.567735  5581 net.cpp:338] conv5_2/dw does not need backward computation.
-I0511 11:49:28.567739  5581 net.cpp:338] relu5_1/sep does not need backward computation.
-I0511 11:49:28.567744  5581 net.cpp:338] conv5_1/sep/scale does not need backward computation.
-I0511 11:49:28.567747  5581 net.cpp:338] conv5_1/sep/bn does not need backward computation.
-I0511 11:49:28.567751  5581 net.cpp:338] conv5_1/sep does not need backward computation.
-I0511 11:49:28.567756  5581 net.cpp:338] relu5_1/dw does not need backward computation.
-I0511 11:49:28.567760  5581 net.cpp:338] conv5_1/dw/scale does not need backward computation.
-I0511 11:49:28.567764  5581 net.cpp:338] conv5_1/dw/bn does not need backward computation.
-I0511 11:49:28.567768  5581 net.cpp:338] conv5_1/dw does not need backward computation.
-I0511 11:49:28.567772  5581 net.cpp:338] relu4_2/sep does not need backward computation.
-I0511 11:49:28.567777  5581 net.cpp:338] conv4_2/sep/scale does not need backward computation.
-I0511 11:49:28.567781  5581 net.cpp:338] conv4_2/sep/bn does not need backward computation.
-I0511 11:49:28.567785  5581 net.cpp:338] conv4_2/sep does not need backward computation.
-I0511 11:49:28.567790  5581 net.cpp:338] relu4_2/dw does not need backward computation.
-I0511 11:49:28.567793  5581 net.cpp:338] conv4_2/dw/scale does not need backward computation.
-I0511 11:49:28.567798  5581 net.cpp:338] conv4_2/dw/bn does not need backward computation.
-I0511 11:49:28.567802  5581 net.cpp:338] conv4_2/dw does not need backward computation.
-I0511 11:49:28.567806  5581 net.cpp:338] relu4_1/sep does not need backward computation.
-I0511 11:49:28.567811  5581 net.cpp:338] conv4_1/sep/scale does not need backward computation.
-I0511 11:49:28.567814  5581 net.cpp:338] conv4_1/sep/bn does not need backward computation.
-I0511 11:49:28.567818  5581 net.cpp:338] conv4_1/sep does not need backward computation.
-I0511 11:49:28.567823  5581 net.cpp:338] relu4_1/dw does not need backward computation.
-I0511 11:49:28.567831  5581 net.cpp:338] conv4_1/dw/scale does not need backward computation.
-I0511 11:49:28.567834  5581 net.cpp:338] conv4_1/dw/bn does not need backward computation.
-I0511 11:49:28.567838  5581 net.cpp:338] conv4_1/dw does not need backward computation.
-I0511 11:49:28.567843  5581 net.cpp:338] relu3_2/sep does not need backward computation.
-I0511 11:49:28.567847  5581 net.cpp:338] conv3_2/sep/scale does not need backward computation.
-I0511 11:49:28.567852  5581 net.cpp:338] conv3_2/sep/bn does not need backward computation.
-I0511 11:49:28.567857  5581 net.cpp:338] conv3_2/sep does not need backward computation.
-I0511 11:49:28.567860  5581 net.cpp:338] relu3_2/dw does not need backward computation.
-I0511 11:49:28.567865  5581 net.cpp:338] conv3_2/dw/scale does not need backward computation.
-I0511 11:49:28.567869  5581 net.cpp:338] conv3_2/dw/bn does not need backward computation.
-I0511 11:49:28.567874  5581 net.cpp:338] conv3_2/dw does not need backward computation.
-I0511 11:49:28.567879  5581 net.cpp:338] relu3_1/sep does not need backward computation.
-I0511 11:49:28.567883  5581 net.cpp:338] conv3_1/sep/scale does not need backward computation.
-I0511 11:49:28.567888  5581 net.cpp:338] conv3_1/sep/bn does not need backward computation.
-I0511 11:49:28.567891  5581 net.cpp:338] conv3_1/sep does not need backward computation.
-I0511 11:49:28.567896  5581 net.cpp:338] relu3_1/dw does not need backward computation.
-I0511 11:49:28.567900  5581 net.cpp:338] conv3_1/dw/scale does not need backward computation.
-I0511 11:49:28.567904  5581 net.cpp:338] conv3_1/dw/bn does not need backward computation.
-I0511 11:49:28.567909  5581 net.cpp:338] conv3_1/dw does not need backward computation.
-I0511 11:49:28.567914  5581 net.cpp:338] relu2_2/sep does not need backward computation.
-I0511 11:49:28.567917  5581 net.cpp:338] conv2_2/sep/scale does not need backward computation.
-I0511 11:49:28.567922  5581 net.cpp:338] conv2_2/sep/bn does not need backward computation.
-I0511 11:49:28.567927  5581 net.cpp:338] conv2_2/sep does not need backward computation.
-I0511 11:49:28.567931  5581 net.cpp:338] relu2_2/dw does not need backward computation.
-I0511 11:49:28.567935  5581 net.cpp:338] conv2_2/dw/scale does not need backward computation.
-I0511 11:49:28.567939  5581 net.cpp:338] conv2_2/dw/bn does not need backward computation.
-I0511 11:49:28.567945  5581 net.cpp:338] conv2_2/dw does not need backward computation.
-I0511 11:49:28.567950  5581 net.cpp:338] relu2_1/sep does not need backward computation.
-I0511 11:49:28.567953  5581 net.cpp:338] conv2_1/sep/scale does not need backward computation.
-I0511 11:49:28.567957  5581 net.cpp:338] conv2_1/sep/bn does not need backward computation.
-I0511 11:49:28.567961  5581 net.cpp:338] conv2_1/sep does not need backward computation.
-I0511 11:49:28.567966  5581 net.cpp:338] relu2_1/dw does not need backward computation.
-I0511 11:49:28.567971  5581 net.cpp:338] conv2_1/dw/scale does not need backward computation.
-I0511 11:49:28.567975  5581 net.cpp:338] conv2_1/dw/bn does not need backward computation.
-I0511 11:49:28.567979  5581 net.cpp:338] conv2_1/dw does not need backward computation.
-I0511 11:49:28.567984  5581 net.cpp:338] relu1 does not need backward computation.
-I0511 11:49:28.567988  5581 net.cpp:338] conv1/scale does not need backward computation.
-I0511 11:49:28.567992  5581 net.cpp:338] conv1/bn does not need backward computation.
-I0511 11:49:28.567997  5581 net.cpp:338] conv1 does not need backward computation.
-I0511 11:49:28.568002  5581 net.cpp:338] data/bias does not need backward computation.
-I0511 11:49:28.568007  5581 net.cpp:338] data_data_0_split does not need backward computation.
-I0511 11:49:28.568012  5581 net.cpp:338] data does not need backward computation.
-I0511 11:49:28.568017  5581 net.cpp:380] This network produces output detection_eval
-I0511 11:49:28.568183  5581 net.cpp:403] Top memory (TEST) required for data: 1352267864 diff: 1352267864
-I0511 11:49:28.568188  5581 net.cpp:406] Bottom memory (TEST) required for data: 1352267440 diff: 1352267440
-I0511 11:49:28.568198  5581 net.cpp:409] Shared (in-place) memory (TEST) by data: 848936960 diff: 848936960
-I0511 11:49:28.568203  5581 net.cpp:412] Parameters memory (TEST) required for data: 9462808 diff: 9462808
-I0511 11:49:28.568207  5581 net.cpp:415] Parameters shared memory (TEST) by data: 0 diff: 0
-I0511 11:49:28.568212  5581 net.cpp:421] Network initialization done.
-I0511 11:49:28.574254  5581 net.cpp:1144] Copying source layer data Type:AnnotatedData #blobs=0
-I0511 11:49:28.574291  5581 net.cpp:1144] Copying source layer data_data_0_split Type:Split #blobs=0
-I0511 11:49:28.574295  5581 net.cpp:1144] Copying source layer data/bias Type:Bias #blobs=1
-I0511 11:49:28.574371  5581 net.cpp:1144] Copying source layer conv1 Type:Convolution #blobs=1
-I0511 11:49:28.574388  5581 net.cpp:1144] Copying source layer conv1/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574414  5581 net.cpp:1144] Copying source layer conv1/scale Type:Scale #blobs=2
-I0511 11:49:28.574429  5581 net.cpp:1144] Copying source layer relu1 Type:ReLU #blobs=0
-I0511 11:49:28.574432  5581 net.cpp:1144] Copying source layer conv2_1/dw Type:Convolution #blobs=1
-I0511 11:49:28.574441  5581 net.cpp:1144] Copying source layer conv2_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574456  5581 net.cpp:1144] Copying source layer conv2_1/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574470  5581 net.cpp:1144] Copying source layer relu2_1/dw Type:ReLU #blobs=0
-I0511 11:49:28.574473  5581 net.cpp:1144] Copying source layer conv2_1/sep Type:Convolution #blobs=1
-I0511 11:49:28.574481  5581 net.cpp:1144] Copying source layer conv2_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574496  5581 net.cpp:1144] Copying source layer conv2_1/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574507  5581 net.cpp:1144] Copying source layer relu2_1/sep Type:ReLU #blobs=0
-I0511 11:49:28.574512  5581 net.cpp:1144] Copying source layer conv2_2/dw Type:Convolution #blobs=1
-I0511 11:49:28.574520  5581 net.cpp:1144] Copying source layer conv2_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574534  5581 net.cpp:1144] Copying source layer conv2_2/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574548  5581 net.cpp:1144] Copying source layer relu2_2/dw Type:ReLU #blobs=0
-I0511 11:49:28.574551  5581 net.cpp:1144] Copying source layer conv2_2/sep Type:Convolution #blobs=1
-I0511 11:49:28.574561  5581 net.cpp:1144] Copying source layer conv2_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574576  5581 net.cpp:1144] Copying source layer conv2_2/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574589  5581 net.cpp:1144] Copying source layer relu2_2/sep Type:ReLU #blobs=0
-I0511 11:49:28.574592  5581 net.cpp:1144] Copying source layer conv3_1/dw Type:Convolution #blobs=1
-I0511 11:49:28.574601  5581 net.cpp:1144] Copying source layer conv3_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574616  5581 net.cpp:1144] Copying source layer conv3_1/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574627  5581 net.cpp:1144] Copying source layer relu3_1/dw Type:ReLU #blobs=0
-I0511 11:49:28.574632  5581 net.cpp:1144] Copying source layer conv3_1/sep Type:Convolution #blobs=1
-I0511 11:49:28.574642  5581 net.cpp:1144] Copying source layer conv3_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574656  5581 net.cpp:1144] Copying source layer conv3_1/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574667  5581 net.cpp:1144] Copying source layer relu3_1/sep Type:ReLU #blobs=0
-I0511 11:49:28.574671  5581 net.cpp:1144] Copying source layer conv3_2/dw Type:Convolution #blobs=1
-I0511 11:49:28.574681  5581 net.cpp:1144] Copying source layer conv3_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574697  5581 net.cpp:1144] Copying source layer conv3_2/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574708  5581 net.cpp:1144] Copying source layer relu3_2/dw Type:ReLU #blobs=0
-I0511 11:49:28.574712  5581 net.cpp:1144] Copying source layer conv3_2/sep Type:Convolution #blobs=1
-I0511 11:49:28.574726  5581 net.cpp:1144] Copying source layer conv3_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574743  5581 net.cpp:1144] Copying source layer conv3_2/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574766  5581 net.cpp:1144] Copying source layer relu3_2/sep Type:ReLU #blobs=0
-I0511 11:49:28.574771  5581 net.cpp:1144] Copying source layer conv4_1/dw Type:Convolution #blobs=1
-I0511 11:49:28.574780  5581 net.cpp:1144] Copying source layer conv4_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574795  5581 net.cpp:1144] Copying source layer conv4_1/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574807  5581 net.cpp:1144] Copying source layer relu4_1/dw Type:ReLU #blobs=0
-I0511 11:49:28.574811  5581 net.cpp:1144] Copying source layer conv4_1/sep Type:Convolution #blobs=1
-I0511 11:49:28.574828  5581 net.cpp:1144] Copying source layer conv4_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574844  5581 net.cpp:1144] Copying source layer conv4_1/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574856  5581 net.cpp:1144] Copying source layer relu4_1/sep Type:ReLU #blobs=0
-I0511 11:49:28.574859  5581 net.cpp:1144] Copying source layer conv4_2/dw Type:Convolution #blobs=1
-I0511 11:49:28.574869  5581 net.cpp:1144] Copying source layer conv4_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574883  5581 net.cpp:1144] Copying source layer conv4_2/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574896  5581 net.cpp:1144] Copying source layer relu4_2/dw Type:ReLU #blobs=0
-I0511 11:49:28.574899  5581 net.cpp:1144] Copying source layer conv4_2/sep Type:Convolution #blobs=1
-I0511 11:49:28.574925  5581 net.cpp:1144] Copying source layer conv4_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574941  5581 net.cpp:1144] Copying source layer conv4_2/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574954  5581 net.cpp:1144] Copying source layer relu4_2/sep Type:ReLU #blobs=0
-I0511 11:49:28.574957  5581 net.cpp:1144] Copying source layer conv5_1/dw Type:Convolution #blobs=1
-I0511 11:49:28.574967  5581 net.cpp:1144] Copying source layer conv5_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574981  5581 net.cpp:1144] Copying source layer conv5_1/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574993  5581 net.cpp:1144] Copying source layer relu5_1/dw Type:ReLU #blobs=0
-I0511 11:49:28.574997  5581 net.cpp:1144] Copying source layer conv5_1/sep Type:Convolution #blobs=1
-I0511 11:49:28.575040  5581 net.cpp:1144] Copying source layer conv5_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575055  5581 net.cpp:1144] Copying source layer conv5_1/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575068  5581 net.cpp:1144] Copying source layer relu5_1/sep Type:ReLU #blobs=0
-I0511 11:49:28.575073  5581 net.cpp:1144] Copying source layer conv5_2/dw Type:Convolution #blobs=1
-I0511 11:49:28.575081  5581 net.cpp:1144] Copying source layer conv5_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575095  5581 net.cpp:1144] Copying source layer conv5_2/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575109  5581 net.cpp:1144] Copying source layer relu5_2/dw Type:ReLU #blobs=0
-I0511 11:49:28.575112  5581 net.cpp:1144] Copying source layer conv5_2/sep Type:Convolution #blobs=1
-I0511 11:49:28.575153  5581 net.cpp:1144] Copying source layer conv5_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575168  5581 net.cpp:1144] Copying source layer conv5_2/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575181  5581 net.cpp:1144] Copying source layer relu5_2/sep Type:ReLU #blobs=0
-I0511 11:49:28.575184  5581 net.cpp:1144] Copying source layer conv5_3/dw Type:Convolution #blobs=1
-I0511 11:49:28.575194  5581 net.cpp:1144] Copying source layer conv5_3/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575209  5581 net.cpp:1144] Copying source layer conv5_3/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575222  5581 net.cpp:1144] Copying source layer relu5_3/dw Type:ReLU #blobs=0
-I0511 11:49:28.575225  5581 net.cpp:1144] Copying source layer conv5_3/sep Type:Convolution #blobs=1
-I0511 11:49:28.575268  5581 net.cpp:1144] Copying source layer conv5_3/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575284  5581 net.cpp:1144] Copying source layer conv5_3/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575296  5581 net.cpp:1144] Copying source layer relu5_3/sep Type:ReLU #blobs=0
-I0511 11:49:28.575306  5581 net.cpp:1144] Copying source layer conv5_4/dw Type:Convolution #blobs=1
-I0511 11:49:28.575317  5581 net.cpp:1144] Copying source layer conv5_4/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575332  5581 net.cpp:1144] Copying source layer conv5_4/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575345  5581 net.cpp:1144] Copying source layer relu5_4/dw Type:ReLU #blobs=0
-I0511 11:49:28.575348  5581 net.cpp:1144] Copying source layer conv5_4/sep Type:Convolution #blobs=1
-I0511 11:49:28.575393  5581 net.cpp:1144] Copying source layer conv5_4/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575409  5581 net.cpp:1144] Copying source layer conv5_4/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575422  5581 net.cpp:1144] Copying source layer relu5_4/sep Type:ReLU #blobs=0
-I0511 11:49:28.575426  5581 net.cpp:1144] Copying source layer conv5_5/dw Type:Convolution #blobs=1
-I0511 11:49:28.575435  5581 net.cpp:1144] Copying source layer conv5_5/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575450  5581 net.cpp:1144] Copying source layer conv5_5/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575462  5581 net.cpp:1144] Copying source layer relu5_5/dw Type:ReLU #blobs=0
-I0511 11:49:28.575466  5581 net.cpp:1144] Copying source layer conv5_5/sep Type:Convolution #blobs=1
-I0511 11:49:28.575508  5581 net.cpp:1144] Copying source layer conv5_5/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575525  5581 net.cpp:1144] Copying source layer conv5_5/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575536  5581 net.cpp:1144] Copying source layer relu5_5/sep Type:ReLU #blobs=0
-I0511 11:49:28.575541  5581 net.cpp:1144] Copying source layer conv5_5/sep_relu5_5/sep_0_split Type:Split #blobs=0
-I0511 11:49:28.575546  5581 net.cpp:1144] Copying source layer conv5_6/dw Type:Convolution #blobs=1
-I0511 11:49:28.575556  5581 net.cpp:1144] Copying source layer conv5_6/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575570  5581 net.cpp:1144] Copying source layer conv5_6/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575582  5581 net.cpp:1144] Copying source layer relu5_6/dw Type:ReLU #blobs=0
-I0511 11:49:28.575587  5581 net.cpp:1144] Copying source layer conv5_6/sep Type:Convolution #blobs=1
-I0511 11:49:28.575659  5581 net.cpp:1144] Copying source layer conv5_6/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575675  5581 net.cpp:1144] Copying source layer conv5_6/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575688  5581 net.cpp:1144] Copying source layer relu5_6/sep Type:ReLU #blobs=0
-I0511 11:49:28.575692  5581 net.cpp:1144] Copying source layer conv6/dw Type:Convolution #blobs=1
-I0511 11:49:28.575703  5581 net.cpp:1144] Copying source layer conv6/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575717  5581 net.cpp:1144] Copying source layer conv6/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575731  5581 net.cpp:1144] Copying source layer relu6/dw Type:ReLU #blobs=0
-I0511 11:49:28.575734  5581 net.cpp:1144] Copying source layer conv6/sep Type:Convolution #blobs=1
-I0511 11:49:28.575876  5581 net.cpp:1144] Copying source layer conv6/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575892  5581 net.cpp:1144] Copying source layer conv6/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575904  5581 net.cpp:1144] Copying source layer relu6/sep Type:ReLU #blobs=0
-I0511 11:49:28.575909  5581 net.cpp:1144] Copying source layer conv6/sep_relu6/sep_0_split Type:Split #blobs=0
-I0511 11:49:28.575913  5581 net.cpp:1144] Copying source layer pool6 Type:Pooling #blobs=0
-I0511 11:49:28.575917  5581 net.cpp:1144] Copying source layer pool6_pool6_0_split Type:Split #blobs=0
-I0511 11:49:28.575922  5581 net.cpp:1144] Copying source layer pool7 Type:Pooling #blobs=0
-I0511 11:49:28.575927  5581 net.cpp:1144] Copying source layer pool7_pool7_0_split Type:Split #blobs=0
-I0511 11:49:28.575930  5581 net.cpp:1144] Copying source layer pool8 Type:Pooling #blobs=0
-I0511 11:49:28.575934  5581 net.cpp:1144] Copying source layer ctx_output1/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576009  5581 net.cpp:1144] Copying source layer ctx_output1/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576037  5581 net.cpp:1144] Copying source layer ctx_output1/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576042  5581 net.cpp:1144] Copying source layer ctx_output1 Type:Convolution #blobs=2
-I0511 11:49:28.576057  5581 net.cpp:1144] Copying source layer ctx_output1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576077  5581 net.cpp:1144] Copying source layer ctx_output1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576081  5581 net.cpp:1144] Copying source layer ctx_output1_ctx_output1/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576086  5581 net.cpp:1144] Copying source layer ctx_output2/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576217  5581 net.cpp:1144] Copying source layer ctx_output2/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576239  5581 net.cpp:1144] Copying source layer ctx_output2/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576243  5581 net.cpp:1144] Copying source layer ctx_output2 Type:Convolution #blobs=2
-I0511 11:49:28.576257  5581 net.cpp:1144] Copying source layer ctx_output2/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576280  5581 net.cpp:1144] Copying source layer ctx_output2/relu Type:ReLU #blobs=0
-I0511 11:49:28.576284  5581 net.cpp:1144] Copying source layer ctx_output2_ctx_output2/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576288  5581 net.cpp:1144] Copying source layer ctx_output3/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576441  5581 net.cpp:1144] Copying source layer ctx_output3/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576462  5581 net.cpp:1144] Copying source layer ctx_output3/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576467  5581 net.cpp:1144] Copying source layer ctx_output3 Type:Convolution #blobs=2
-I0511 11:49:28.576480  5581 net.cpp:1144] Copying source layer ctx_output3/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576500  5581 net.cpp:1144] Copying source layer ctx_output3/relu Type:ReLU #blobs=0
-I0511 11:49:28.576504  5581 net.cpp:1144] Copying source layer ctx_output3_ctx_output3/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576508  5581 net.cpp:1144] Copying source layer ctx_output4/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576669  5581 net.cpp:1144] Copying source layer ctx_output4/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576692  5581 net.cpp:1144] Copying source layer ctx_output4/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576697  5581 net.cpp:1144] Copying source layer ctx_output4 Type:Convolution #blobs=2
-I0511 11:49:28.576711  5581 net.cpp:1144] Copying source layer ctx_output4/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576732  5581 net.cpp:1144] Copying source layer ctx_output4/relu Type:ReLU #blobs=0
-I0511 11:49:28.576736  5581 net.cpp:1144] Copying source layer ctx_output4_ctx_output4/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576741  5581 net.cpp:1144] Copying source layer ctx_output5/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576867  5581 net.cpp:1144] Copying source layer ctx_output5/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576889  5581 net.cpp:1144] Copying source layer ctx_output5/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576894  5581 net.cpp:1144] Copying source layer ctx_output5 Type:Convolution #blobs=2
-I0511 11:49:28.576910  5581 net.cpp:1144] Copying source layer ctx_output5/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576931  5581 net.cpp:1144] Copying source layer ctx_output5/relu Type:ReLU #blobs=0
-I0511 11:49:28.576936  5581 net.cpp:1144] Copying source layer ctx_output5_ctx_output5/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576941  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.576957  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.576962  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.576967  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577008  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577013  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577024  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577029  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.577047  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.577051  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.577056  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577100  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577105  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577111  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577114  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.577131  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.577136  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.577141  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577185  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577190  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577194  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577199  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.577217  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.577221  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.577225  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577258  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577263  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577267  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577272  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.577286  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.577291  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.577296  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577332  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577337  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577340  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577344  5581 net.cpp:1144] Copying source layer mbox_loc Type:Concat #blobs=0
-I0511 11:49:28.577348  5581 net.cpp:1144] Copying source layer mbox_conf Type:Concat #blobs=0
-I0511 11:49:28.577353  5581 net.cpp:1144] Copying source layer mbox_priorbox Type:Concat #blobs=0
-I0511 11:49:28.577358  5581 net.cpp:1136] Ignoring source layer mbox_loss
-I0511 11:49:28.577541  5581 caffe.cpp:419] Running for 496 iterations.
-I0511 11:49:28.821983  5581 caffe.cpp:449] Batch 0
-I0511 11:49:28.822185  5581 net.cpp:1765] Enabling quantization flag in quantization_param at infer/iter index: 1
-I0511 11:49:28.822203  5581 net.cpp:1998] Enabling quantization at output of: AnnotatedData data
-I0511 11:49:28.822218  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu1
-I0511 11:49:28.822222  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu2_1/dw
-I0511 11:49:28.822226  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu2_1/sep
-I0511 11:49:28.822228  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu2_2/dw
-I0511 11:49:28.822232  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu2_2/sep
-I0511 11:49:28.822233  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu3_1/dw
-I0511 11:49:28.822237  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu3_1/sep
-I0511 11:49:28.822239  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu3_2/dw
-I0511 11:49:28.822242  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu3_2/sep
-I0511 11:49:28.822245  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu4_1/dw
-I0511 11:49:28.822248  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu4_1/sep
-I0511 11:49:28.822250  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu4_2/dw
-I0511 11:49:28.822253  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu4_2/sep
-I0511 11:49:28.822257  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_1/dw
-I0511 11:49:28.822258  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_1/sep
-I0511 11:49:28.822262  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_2/dw
-I0511 11:49:28.822264  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_2/sep
-I0511 11:49:28.822268  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_3/dw
-I0511 11:49:28.822270  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_3/sep
-I0511 11:49:28.822273  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_4/dw
-I0511 11:49:28.822275  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_4/sep
-I0511 11:49:28.822278  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_5/dw
-I0511 11:49:28.822281  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_5/sep
-I0511 11:49:28.822284  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_6/dw
-I0511 11:49:28.822288  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_6/sep
-I0511 11:49:28.822290  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu6/dw
-I0511 11:49:28.822293  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu6/sep
-I0511 11:49:28.822298  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output1/1x1/relu
-I0511 11:49:28.822300  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output1/relu
-I0511 11:49:28.822304  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output2/1x1/relu
-I0511 11:49:28.822305  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output2/relu
-I0511 11:49:28.822309  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output3/1x1/relu
-I0511 11:49:28.822311  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output3/relu
-I0511 11:49:28.822314  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output4/1x1/relu
-I0511 11:49:28.822316  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output4/relu
-I0511 11:49:28.822319  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output5/1x1/relu
-I0511 11:49:28.822322  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output5/relu
-I0511 11:49:28.822324  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output1/relu_mbox_loc
-I0511 11:49:28.822327  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output1/relu_mbox_conf
-I0511 11:49:28.822330  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output2/relu_mbox_loc
-I0511 11:49:28.822332  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output2/relu_mbox_conf
-I0511 11:49:28.822336  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output3/relu_mbox_loc
-I0511 11:49:28.822343  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output3/relu_mbox_conf
-I0511 11:49:28.822346  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output4/relu_mbox_loc
-I0511 11:49:28.822350  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output4/relu_mbox_conf
-I0511 11:49:28.822352  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output5/relu_mbox_loc
-I0511 11:49:28.822355  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output5/relu_mbox_conf
-I0511 11:49:28.822358  5581 net.cpp:1998] Enabling quantization at output of: Concat mbox_loc
-I0511 11:49:28.822360  5581 net.cpp:1998] Enabling quantization at output of: Concat mbox_conf
-I0511 11:49:28.822362  5581 net.cpp:1998] Enabling quantization at output of: Concat mbox_priorbox
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-I0511 11:50:54.946440  5581 caffe.cpp:449] Batch 491
-I0511 11:50:54.957875  5600 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:50:55.121860  5581 caffe.cpp:449] Batch 492
-I0511 11:50:55.303601  5581 caffe.cpp:449] Batch 493
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-I0511 11:50:55.638821  5581 caffe.cpp:449] Batch 495
-I0511 11:50:55.638908  5581 caffe.cpp:483] Loss: 0
-I0511 11:50:55.638947  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638953  5581 caffe.cpp:501] detection_eval = 1
-I0511 11:50:55.638958  5581 caffe.cpp:501] detection_eval = 0.574597
-I0511 11:50:55.638964  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638968  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638972  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638978  5581 caffe.cpp:501] detection_eval = 2
-I0511 11:50:55.638981  5581 caffe.cpp:501] detection_eval = 0.679435
-I0511 11:50:55.638985  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638990  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638993  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638996  5581 caffe.cpp:501] detection_eval = 3
-I0511 11:50:55.639000  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.639004  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639010  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639014  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639019  5581 caffe.cpp:501] detection_eval = 4
-I0511 11:50:55.639024  5581 caffe.cpp:501] detection_eval = 0.530242
-I0511 11:50:55.639027  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639031  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639036  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639040  5581 caffe.cpp:501] detection_eval = 5
-I0511 11:50:55.639045  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.639050  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639053  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639057  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639065  5581 caffe.cpp:501] detection_eval = 6
-I0511 11:50:55.639070  5581 caffe.cpp:501] detection_eval = 0.429435
-I0511 11:50:55.639073  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639077  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639082  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639087  5581 caffe.cpp:501] detection_eval = 7
-I0511 11:50:55.639093  5581 caffe.cpp:501] detection_eval = 2.43548
-I0511 11:50:55.639097  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639102  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639106  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639111  5581 caffe.cpp:501] detection_eval = 8
-I0511 11:50:55.639117  5581 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:50:55.639122  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639127  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639130  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639135  5581 caffe.cpp:501] detection_eval = 9
-I0511 11:50:55.639139  5581 caffe.cpp:501] detection_eval = 1.53226
-I0511 11:50:55.639144  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639148  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639153  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639158  5581 caffe.cpp:501] detection_eval = 10
-I0511 11:50:55.639163  5581 caffe.cpp:501] detection_eval = 0.491935
-I0511 11:50:55.639168  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639171  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639175  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639179  5581 caffe.cpp:501] detection_eval = 11
-I0511 11:50:55.639184  5581 caffe.cpp:501] detection_eval = 0.417339
-I0511 11:50:55.639189  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639194  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639197  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639202  5581 caffe.cpp:501] detection_eval = 12
-I0511 11:50:55.639206  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.639211  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639215  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639219  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639225  5581 caffe.cpp:501] detection_eval = 13
-I0511 11:50:55.639230  5581 caffe.cpp:501] detection_eval = 0.703629
-I0511 11:50:55.639236  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639258  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639267  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639272  5581 caffe.cpp:501] detection_eval = 14
-I0511 11:50:55.639277  5581 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:50:55.639282  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639287  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639292  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639297  5581 caffe.cpp:501] detection_eval = 15
-I0511 11:50:55.639302  5581 caffe.cpp:501] detection_eval = 9.13306
-I0511 11:50:55.639305  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639310  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639314  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639319  5581 caffe.cpp:501] detection_eval = 16
-I0511 11:50:55.639324  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.639329  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639334  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639339  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639343  5581 caffe.cpp:501] detection_eval = 17
-I0511 11:50:55.639348  5581 caffe.cpp:501] detection_eval = 0.487903
-I0511 11:50:55.639353  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639358  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639364  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639367  5581 caffe.cpp:501] detection_eval = 18
-I0511 11:50:55.639372  5581 caffe.cpp:501] detection_eval = 0.483871
-I0511 11:50:55.639377  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639381  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639386  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639390  5581 caffe.cpp:501] detection_eval = 19
-I0511 11:50:55.639394  5581 caffe.cpp:501] detection_eval = 0.570565
-I0511 11:50:55.639400  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639403  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639407  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639412  5581 caffe.cpp:501] detection_eval = 20
-I0511 11:50:55.639416  5581 caffe.cpp:501] detection_eval = 0.620968
-I0511 11:50:55.639421  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639426  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639430  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639434  5581 caffe.cpp:501] detection_eval = 3.25202
-I0511 11:50:55.639438  5581 caffe.cpp:501] detection_eval = 0.164725
-I0511 11:50:55.639442  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.639447  5581 caffe.cpp:501] detection_eval = 0.872984
-I0511 11:50:55.639451  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639456  5581 caffe.cpp:501] detection_eval = 3.65323
-I0511 11:50:55.639461  5581 caffe.cpp:501] detection_eval = 0.104809
-I0511 11:50:55.639466  5581 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:50:55.639470  5581 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:50:55.639474  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639479  5581 caffe.cpp:501] detection_eval = 3.84677
-I0511 11:50:55.639483  5581 caffe.cpp:501] detection_eval = 0.0762525
-I0511 11:50:55.639488  5581 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:50:55.639492  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.639497  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639503  5581 caffe.cpp:501] detection_eval = 4
-I0511 11:50:55.639508  5581 caffe.cpp:501] detection_eval = 0.0660003
-I0511 11:50:55.639511  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.639516  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.639520  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639525  5581 caffe.cpp:501] detection_eval = 4.14718
-I0511 11:50:55.639529  5581 caffe.cpp:501] detection_eval = 0.0605915
-I0511 11:50:55.639534  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.639539  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.639544  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639551  5581 caffe.cpp:501] detection_eval = 4.23589
-I0511 11:50:55.639556  5581 caffe.cpp:501] detection_eval = 0.0589541
-I0511 11:50:55.639561  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.639565  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.639569  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639575  5581 caffe.cpp:501] detection_eval = 4.34677
-I0511 11:50:55.639578  5581 caffe.cpp:501] detection_eval = 0.0533733
-I0511 11:50:55.639583  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.639588  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.639592  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639597  5581 caffe.cpp:501] detection_eval = 4.43347
-I0511 11:50:55.639602  5581 caffe.cpp:501] detection_eval = 0.0445817
-I0511 11:50:55.639606  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639611  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.639616  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639621  5581 caffe.cpp:501] detection_eval = 4.5121
-I0511 11:50:55.639624  5581 caffe.cpp:501] detection_eval = 0.0445154
-I0511 11:50:55.639629  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.639634  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.639639  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639644  5581 caffe.cpp:501] detection_eval = 4.59073
-I0511 11:50:55.639648  5581 caffe.cpp:501] detection_eval = 0.0476314
-I0511 11:50:55.639653  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639658  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.639662  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639667  5581 caffe.cpp:501] detection_eval = 4.65323
-I0511 11:50:55.639672  5581 caffe.cpp:501] detection_eval = 0.0438739
-I0511 11:50:55.639677  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.639680  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.639685  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639689  5581 caffe.cpp:501] detection_eval = 4.70968
-I0511 11:50:55.639694  5581 caffe.cpp:501] detection_eval = 0.0465306
-I0511 11:50:55.639698  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.639703  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.639708  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639713  5581 caffe.cpp:501] detection_eval = 4.79435
-I0511 11:50:55.639717  5581 caffe.cpp:501] detection_eval = 0.041596
-I0511 11:50:55.639721  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639726  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.639730  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639735  5581 caffe.cpp:501] detection_eval = 4.85484
-I0511 11:50:55.639740  5581 caffe.cpp:501] detection_eval = 0.0488618
-I0511 11:50:55.639744  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639750  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.639753  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639757  5581 caffe.cpp:501] detection_eval = 4.89315
-I0511 11:50:55.639762  5581 caffe.cpp:501] detection_eval = 0.043171
-I0511 11:50:55.639767  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639771  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.639776  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639781  5581 caffe.cpp:501] detection_eval = 4.98185
-I0511 11:50:55.639786  5581 caffe.cpp:501] detection_eval = 0.0431476
-I0511 11:50:55.639791  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639794  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.639799  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639804  5581 caffe.cpp:501] detection_eval = 5.08871
-I0511 11:50:55.639811  5581 caffe.cpp:501] detection_eval = 0.0481148
-I0511 11:50:55.639814  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.639819  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.639828  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639834  5581 caffe.cpp:501] detection_eval = 5.14718
-I0511 11:50:55.639839  5581 caffe.cpp:501] detection_eval = 0.0433028
-I0511 11:50:55.639844  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.639849  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.639854  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639859  5581 caffe.cpp:501] detection_eval = 5.22984
-I0511 11:50:55.639863  5581 caffe.cpp:501] detection_eval = 0.0444779
-I0511 11:50:55.639868  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639873  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.639878  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639883  5581 caffe.cpp:501] detection_eval = 5.27823
-I0511 11:50:55.639886  5581 caffe.cpp:501] detection_eval = 0.0408055
-I0511 11:50:55.639891  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.639896  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.639900  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.639905  5581 caffe.cpp:501] detection_eval = 5.33065
-I0511 11:50:55.639909  5581 caffe.cpp:501] detection_eval = 0.045186
-I0511 11:50:55.639914  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.639919  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.639924  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.639927  5581 caffe.cpp:501] detection_eval = 5.39919
-I0511 11:50:55.639933  5581 caffe.cpp:501] detection_eval = 0.0447129
-I0511 11:50:55.639937  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.639942  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.639946  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.639951  5581 caffe.cpp:501] detection_eval = 5.47379
-I0511 11:50:55.639955  5581 caffe.cpp:501] detection_eval = 0.0434004
-I0511 11:50:55.639961  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.639964  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.639969  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.639974  5581 caffe.cpp:501] detection_eval = 5.53024
-I0511 11:50:55.639979  5581 caffe.cpp:501] detection_eval = 0.0489237
-I0511 11:50:55.639983  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.639988  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.639992  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639997  5581 caffe.cpp:501] detection_eval = 5.57258
-I0511 11:50:55.640002  5581 caffe.cpp:501] detection_eval = 0.0410275
-I0511 11:50:55.640007  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640010  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.640015  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640019  5581 caffe.cpp:501] detection_eval = 5.61895
-I0511 11:50:55.640024  5581 caffe.cpp:501] detection_eval = 0.0423506
-I0511 11:50:55.640028  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.640033  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640038  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640043  5581 caffe.cpp:501] detection_eval = 5.69355
-I0511 11:50:55.640046  5581 caffe.cpp:501] detection_eval = 0.0451725
-I0511 11:50:55.640051  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640055  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.640060  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640064  5581 caffe.cpp:501] detection_eval = 5.73185
-I0511 11:50:55.640069  5581 caffe.cpp:501] detection_eval = 0.0393402
-I0511 11:50:55.640074  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640079  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640084  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640087  5581 caffe.cpp:501] detection_eval = 5.86694
-I0511 11:50:55.640091  5581 caffe.cpp:501] detection_eval = 0.0424488
-I0511 11:50:55.640096  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640106  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640111  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640116  5581 caffe.cpp:501] detection_eval = 5.91734
-I0511 11:50:55.640121  5581 caffe.cpp:501] detection_eval = 0.0435992
-I0511 11:50:55.640125  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.640130  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.640135  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640138  5581 caffe.cpp:501] detection_eval = 6.01008
-I0511 11:50:55.640143  5581 caffe.cpp:501] detection_eval = 0.0480477
-I0511 11:50:55.640148  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640153  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640157  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640162  5581 caffe.cpp:501] detection_eval = 6.08871
-I0511 11:50:55.640167  5581 caffe.cpp:501] detection_eval = 0.0412229
-I0511 11:50:55.640172  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640177  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640180  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640185  5581 caffe.cpp:501] detection_eval = 6.11694
-I0511 11:50:55.640190  5581 caffe.cpp:501] detection_eval = 0.0411029
-I0511 11:50:55.640195  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640200  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.640204  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640209  5581 caffe.cpp:501] detection_eval = 6.26815
-I0511 11:50:55.640213  5581 caffe.cpp:501] detection_eval = 0.0398907
-I0511 11:50:55.640218  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640223  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640226  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640230  5581 caffe.cpp:501] detection_eval = 6.33468
-I0511 11:50:55.640235  5581 caffe.cpp:501] detection_eval = 0.0437772
-I0511 11:50:55.640240  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640245  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640250  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640254  5581 caffe.cpp:501] detection_eval = 6.42339
-I0511 11:50:55.640259  5581 caffe.cpp:501] detection_eval = 0.039532
-I0511 11:50:55.640264  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.640269  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640274  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640277  5581 caffe.cpp:501] detection_eval = 6.49597
-I0511 11:50:55.640281  5581 caffe.cpp:501] detection_eval = 0.0400402
-I0511 11:50:55.640286  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.640290  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640295  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640300  5581 caffe.cpp:501] detection_eval = 6.6371
-I0511 11:50:55.640305  5581 caffe.cpp:501] detection_eval = 0.048498
-I0511 11:50:55.640310  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640313  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.640318  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640323  5581 caffe.cpp:501] detection_eval = 6.65121
-I0511 11:50:55.640328  5581 caffe.cpp:501] detection_eval = 0.0427957
-I0511 11:50:55.640332  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640337  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.640341  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640347  5581 caffe.cpp:501] detection_eval = 6.75806
-I0511 11:50:55.640352  5581 caffe.cpp:501] detection_eval = 0.0484034
-I0511 11:50:55.640357  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640360  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.640365  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640369  5581 caffe.cpp:501] detection_eval = 6.83065
-I0511 11:50:55.640373  5581 caffe.cpp:501] detection_eval = 0.0446842
-I0511 11:50:55.640383  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640388  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640393  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640398  5581 caffe.cpp:501] detection_eval = 6.90323
-I0511 11:50:55.640403  5581 caffe.cpp:501] detection_eval = 0.0414079
-I0511 11:50:55.640408  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640413  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640416  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640421  5581 caffe.cpp:501] detection_eval = 6.95161
-I0511 11:50:55.640425  5581 caffe.cpp:501] detection_eval = 0.0429655
-I0511 11:50:55.640430  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640434  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640439  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640449  5581 caffe.cpp:501] detection_eval = 6.9879
-I0511 11:50:55.640453  5581 caffe.cpp:501] detection_eval = 0.0390551
-I0511 11:50:55.640457  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640462  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640467  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640472  5581 caffe.cpp:501] detection_eval = 7.08468
-I0511 11:50:55.640477  5581 caffe.cpp:501] detection_eval = 0.0442344
-I0511 11:50:55.640482  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640486  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640491  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640496  5581 caffe.cpp:501] detection_eval = 7.15121
-I0511 11:50:55.640499  5581 caffe.cpp:501] detection_eval = 0.0426983
-I0511 11:50:55.640504  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640509  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.640514  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640518  5581 caffe.cpp:501] detection_eval = 7.24798
-I0511 11:50:55.640522  5581 caffe.cpp:501] detection_eval = 0.0426494
-I0511 11:50:55.640533  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640537  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640544  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640565  5581 caffe.cpp:501] detection_eval = 7.35484
-I0511 11:50:55.640583  5581 caffe.cpp:501] detection_eval = 0.0417271
-I0511 11:50:55.640594  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640602  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640607  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640612  5581 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:50:55.640616  5581 caffe.cpp:501] detection_eval = 0.0406579
-I0511 11:50:55.640621  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640625  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.640630  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640640  5581 caffe.cpp:501] detection_eval = 7.49597
-I0511 11:50:55.640650  5581 caffe.cpp:501] detection_eval = 0.0428491
-I0511 11:50:55.640662  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640673  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640686  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640697  5581 caffe.cpp:501] detection_eval = 7.58669
-I0511 11:50:55.640708  5581 caffe.cpp:501] detection_eval = 0.0414093
-I0511 11:50:55.640714  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640719  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640724  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640729  5581 caffe.cpp:501] detection_eval = 7.63508
-I0511 11:50:55.640734  5581 caffe.cpp:501] detection_eval = 0.037889
-I0511 11:50:55.640739  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.640744  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.640749  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640754  5581 caffe.cpp:501] detection_eval = 7.75806
-I0511 11:50:55.640765  5581 caffe.cpp:501] detection_eval = 0.0415663
-I0511 11:50:55.640777  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640789  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640799  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640810  5581 caffe.cpp:501] detection_eval = 7.86895
-I0511 11:50:55.640818  5581 caffe.cpp:501] detection_eval = 0.0495166
-I0511 11:50:55.640823  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640828  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.640832  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640837  5581 caffe.cpp:501] detection_eval = 7.97782
-I0511 11:50:55.640842  5581 caffe.cpp:501] detection_eval = 0.0460135
-I0511 11:50:55.640847  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640852  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640857  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640862  5581 caffe.cpp:501] detection_eval = 8.05444
-I0511 11:50:55.640867  5581 caffe.cpp:501] detection_eval = 0.0421181
-I0511 11:50:55.640872  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640877  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.640882  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640887  5581 caffe.cpp:501] detection_eval = 8.14919
-I0511 11:50:55.640892  5581 caffe.cpp:501] detection_eval = 0.0403573
-I0511 11:50:55.640897  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640902  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.640907  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640915  5581 caffe.cpp:501] detection_eval = 8.24597
-I0511 11:50:55.640924  5581 caffe.cpp:501] detection_eval = 0.0420401
-I0511 11:50:55.640933  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640942  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640949  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640956  5581 caffe.cpp:501] detection_eval = 8.34476
-I0511 11:50:55.640961  5581 caffe.cpp:501] detection_eval = 0.0467141
-I0511 11:50:55.640970  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640976  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.640981  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.640990  5581 caffe.cpp:501] detection_eval = 8.39315
-I0511 11:50:55.640998  5581 caffe.cpp:501] detection_eval = 0.0470415
-I0511 11:50:55.641005  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.641012  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.641018  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.641026  5581 caffe.cpp:501] detection_eval = 8.44758
-I0511 11:50:55.641032  5581 caffe.cpp:501] detection_eval = 0.0435731
-I0511 11:50:55.641041  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.641047  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641054  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.641060  5581 caffe.cpp:501] detection_eval = 8.52218
-I0511 11:50:55.641068  5581 caffe.cpp:501] detection_eval = 0.0439346
-I0511 11:50:55.641074  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.641083  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.641088  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.641093  5581 caffe.cpp:501] detection_eval = 8.65323
-I0511 11:50:55.641098  5581 caffe.cpp:501] detection_eval = 0.045293
-I0511 11:50:55.641103  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.641108  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.641113  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.641119  5581 caffe.cpp:501] detection_eval = 8.72379
-I0511 11:50:55.641124  5581 caffe.cpp:501] detection_eval = 0.0451606
-I0511 11:50:55.641129  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.641134  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.641139  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641149  5581 caffe.cpp:501] detection_eval = 8.76411
-I0511 11:50:55.641155  5581 caffe.cpp:501] detection_eval = 0.0453022
-I0511 11:50:55.641158  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.641163  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.641168  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641173  5581 caffe.cpp:501] detection_eval = 8.79839
-I0511 11:50:55.641178  5581 caffe.cpp:501] detection_eval = 0.0459531
-I0511 11:50:55.641183  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.641187  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.641191  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641196  5581 caffe.cpp:501] detection_eval = 8.84879
-I0511 11:50:55.641201  5581 caffe.cpp:501] detection_eval = 0.0440237
-I0511 11:50:55.641206  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.641211  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.641216  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641219  5581 caffe.cpp:501] detection_eval = 8.91129
-I0511 11:50:55.641224  5581 caffe.cpp:501] detection_eval = 0.0421023
-I0511 11:50:55.641229  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641234  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.641238  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641243  5581 caffe.cpp:501] detection_eval = 8.97782
-I0511 11:50:55.641247  5581 caffe.cpp:501] detection_eval = 0.0424941
-I0511 11:50:55.641252  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641257  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641261  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641266  5581 caffe.cpp:501] detection_eval = 9.06048
-I0511 11:50:55.641271  5581 caffe.cpp:501] detection_eval = 0.0413233
-I0511 11:50:55.641275  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641280  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641285  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641290  5581 caffe.cpp:501] detection_eval = 9.14113
-I0511 11:50:55.641294  5581 caffe.cpp:501] detection_eval = 0.0394532
-I0511 11:50:55.641299  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.641304  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641314  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641319  5581 caffe.cpp:501] detection_eval = 9.28427
-I0511 11:50:55.641324  5581 caffe.cpp:501] detection_eval = 0.0466154
-I0511 11:50:55.641329  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641333  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641340  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641345  5581 caffe.cpp:501] detection_eval = 9.33065
-I0511 11:50:55.641355  5581 caffe.cpp:501] detection_eval = 0.0391784
-I0511 11:50:55.641366  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.641376  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641386  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641397  5581 caffe.cpp:501] detection_eval = 9.41935
-I0511 11:50:55.641407  5581 caffe.cpp:501] detection_eval = 0.0399461
-I0511 11:50:55.641412  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.641417  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.641422  5581 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:50:55.641427  5581 caffe.cpp:501] detection_eval = 9.45363
-I0511 11:50:55.641433  5581 caffe.cpp:501] detection_eval = 0.0418448
-I0511 11:50:55.641438  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.641441  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641446  5581 caffe.cpp:501] detection_eval = 0.0342742
-I0511 11:50:55.641451  5581 caffe.cpp:501] detection_eval = 9.53629
-I0511 11:50:55.641456  5581 caffe.cpp:501] detection_eval = 0.0411611
-I0511 11:50:55.641461  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641466  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.641475  5581 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:50:55.641481  5581 caffe.cpp:501] detection_eval = 9.56855
-I0511 11:50:55.641487  5581 caffe.cpp:501] detection_eval = 0.0487977
-I0511 11:50:55.641492  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641501  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.641506  5581 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:50:55.641511  5581 caffe.cpp:501] detection_eval = 9.64516
-I0511 11:50:55.641515  5581 caffe.cpp:501] detection_eval = 0.0457145
-I0511 11:50:55.641520  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641525  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641530  5581 caffe.cpp:501] detection_eval = 0.0403226
-I0511 11:50:55.641535  5581 caffe.cpp:501] detection_eval = 9.66935
-I0511 11:50:55.641541  5581 caffe.cpp:501] detection_eval = 0.043002
-I0511 11:50:55.641546  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.641551  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641554  5581 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:50:55.641559  5581 caffe.cpp:501] detection_eval = 9.71371
-I0511 11:50:55.641564  5581 caffe.cpp:501] detection_eval = 0.0434862
-I0511 11:50:55.641571  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641580  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641592  5581 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:50:55.641602  5581 caffe.cpp:501] detection_eval = 9.76815
-I0511 11:50:55.641613  5581 caffe.cpp:501] detection_eval = 0.0448317
-I0511 11:50:55.641623  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.641634  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641644  5581 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:50:55.641651  5581 caffe.cpp:501] detection_eval = 9.84274
-I0511 11:50:55.641656  5581 caffe.cpp:501] detection_eval = 0.0405645
-I0511 11:50:55.641661  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641665  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641670  5581 caffe.cpp:501] detection_eval = 0.0443548
-I0511 11:50:55.641675  5581 caffe.cpp:501] detection_eval = 9.86492
-I0511 11:50:55.641680  5581 caffe.cpp:501] detection_eval = 0.0451478
-I0511 11:50:55.641685  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.641690  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641695  5581 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:50:55.641700  5581 caffe.cpp:501] detection_eval = 9.86492
-I0511 11:50:55.641705  5581 caffe.cpp:501] detection_eval = 0.0396386
-I0511 11:50:55.641710  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641715  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641724  5581 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:50:55.641736  5581 caffe.cpp:501] detection_eval = 9.93952
-I0511 11:50:55.641746  5581 caffe.cpp:501] detection_eval = 0.0448263
-I0511 11:50:55.641757  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641767  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641772  5581 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:50:55.641777  5581 caffe.cpp:501] detection_eval = 10.0323
-I0511 11:50:55.641783  5581 caffe.cpp:501] detection_eval = 0.0429454
-I0511 11:50:55.641790  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641798  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.641803  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641808  5581 caffe.cpp:501] detection_eval = 10.0464
-I0511 11:50:55.641813  5581 caffe.cpp:501] detection_eval = 0.0451522
-I0511 11:50:55.641819  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641830  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641840  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641851  5581 caffe.cpp:501] detection_eval = 10.121
-I0511 11:50:55.641862  5581 caffe.cpp:501] detection_eval = 0.0435291
-I0511 11:50:55.641873  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641890  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641894  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641899  5581 caffe.cpp:501] detection_eval = 10.2218
-I0511 11:50:55.641904  5581 caffe.cpp:501] detection_eval = 0.0490495
-I0511 11:50:55.641909  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.641916  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.641921  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641924  5581 caffe.cpp:501] detection_eval = 10.2702
-I0511 11:50:55.641929  5581 caffe.cpp:501] detection_eval = 0.0389256
-I0511 11:50:55.641934  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.641939  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641944  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641949  5581 caffe.cpp:501] detection_eval = 10.3589
-I0511 11:50:55.641954  5581 caffe.cpp:501] detection_eval = 0.0411403
-I0511 11:50:55.641958  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641963  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641968  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.641973  5581 caffe.cpp:501] detection_eval = 10.4476
-I0511 11:50:55.641983  5581 caffe.cpp:501] detection_eval = 0.0496988
-I0511 11:50:55.641991  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642001  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.642012  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642021  5581 caffe.cpp:501] detection_eval = 10.5161
-I0511 11:50:55.642030  5581 caffe.cpp:501] detection_eval = 0.0399565
-I0511 11:50:55.642035  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.642040  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642045  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642050  5581 caffe.cpp:501] detection_eval = 10.5948
-I0511 11:50:55.642055  5581 caffe.cpp:501] detection_eval = 0.0397837
-I0511 11:50:55.642060  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.642063  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.642068  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642073  5581 caffe.cpp:501] detection_eval = 10.6895
-I0511 11:50:55.642077  5581 caffe.cpp:501] detection_eval = 0.0466224
-I0511 11:50:55.642082  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.642088  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.642097  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642107  5581 caffe.cpp:501] detection_eval = 10.7742
-I0511 11:50:55.642117  5581 caffe.cpp:501] detection_eval = 0.0444724
-I0511 11:50:55.642127  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642138  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642146  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642155  5581 caffe.cpp:501] detection_eval = 10.8851
-I0511 11:50:55.642165  5581 caffe.cpp:501] detection_eval = 0.0498522
-I0511 11:50:55.642175  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.642184  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.642190  5581 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:50:55.642195  5581 caffe.cpp:501] detection_eval = 10.9012
-I0511 11:50:55.642200  5581 caffe.cpp:501] detection_eval = 0.0456841
-I0511 11:50:55.642204  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642210  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.642213  5581 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:50:55.642218  5581 caffe.cpp:501] detection_eval = 10.996
-I0511 11:50:55.642223  5581 caffe.cpp:501] detection_eval = 0.0469158
-I0511 11:50:55.642227  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.642232  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.642237  5581 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:50:55.642247  5581 caffe.cpp:501] detection_eval = 11.0847
-I0511 11:50:55.642252  5581 caffe.cpp:501] detection_eval = 0.0454253
-I0511 11:50:55.642261  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.642271  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.642278  5581 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:50:55.642288  5581 caffe.cpp:501] detection_eval = 11.121
-I0511 11:50:55.642300  5581 caffe.cpp:501] detection_eval = 0.0476964
-I0511 11:50:55.642310  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642318  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.642328  5581 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:50:55.642331  5581 caffe.cpp:501] detection_eval = 11.2056
-I0511 11:50:55.642340  5581 caffe.cpp:501] detection_eval = 0.0415643
-I0511 11:50:55.642344  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642352  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.642356  5581 caffe.cpp:501] detection_eval = 0.0564516
-I0511 11:50:55.642364  5581 caffe.cpp:501] detection_eval = 11.25
-I0511 11:50:55.642369  5581 caffe.cpp:501] detection_eval = 0.0445424
-I0511 11:50:55.642377  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642381  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642390  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642395  5581 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:50:55.642403  5581 caffe.cpp:501] detection_eval = 0.0435517
-I0511 11:50:55.642408  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.642412  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.642416  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642424  5581 caffe.cpp:501] detection_eval = 11.3367
-I0511 11:50:55.642428  5581 caffe.cpp:501] detection_eval = 0.0463047
-I0511 11:50:55.642437  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.642441  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.642449  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642453  5581 caffe.cpp:501] detection_eval = 11.4052
-I0511 11:50:55.642462  5581 caffe.cpp:501] detection_eval = 0.0468383
-I0511 11:50:55.642467  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.642474  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.642478  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642487  5581 caffe.cpp:501] detection_eval = 11.4677
-I0511 11:50:55.642491  5581 caffe.cpp:501] detection_eval = 0.0410226
-I0511 11:50:55.642499  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.642506  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642514  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642518  5581 caffe.cpp:501] detection_eval = 11.502
-I0511 11:50:55.642526  5581 caffe.cpp:501] detection_eval = 0.0382867
-I0511 11:50:55.642531  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642540  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642549  5581 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:50:55.642558  5581 caffe.cpp:501] detection_eval = 11.5484
-I0511 11:50:55.642568  5581 caffe.cpp:501] detection_eval = 0.0419781
-I0511 11:50:55.642577  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642587  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642597  5581 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:50:55.642606  5581 caffe.cpp:501] detection_eval = 11.5948
-I0511 11:50:55.642616  5581 caffe.cpp:501] detection_eval = 0.0414562
-I0511 11:50:55.642626  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642634  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642643  5581 caffe.cpp:501] detection_eval = 0.0625
-I0511 11:50:55.642653  5581 caffe.cpp:501] detection_eval = 11.6331
-I0511 11:50:55.642663  5581 caffe.cpp:501] detection_eval = 0.0410472
-I0511 11:50:55.642673  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642683  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642693  5581 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:50:55.642702  5581 caffe.cpp:501] detection_eval = 11.6855
-I0511 11:50:55.642714  5581 caffe.cpp:501] detection_eval = 0.0405388
-I0511 11:50:55.642724  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.642729  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.642736  5581 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:50:55.642742  5581 caffe.cpp:501] detection_eval = 11.754
-I0511 11:50:55.642751  5581 caffe.cpp:501] detection_eval = 0.0414713
-I0511 11:50:55.642756  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.642765  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.642768  5581 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:50:55.642776  5581 caffe.cpp:501] detection_eval = 11.8347
-I0511 11:50:55.642782  5581 caffe.cpp:501] detection_eval = 0.0419868
-I0511 11:50:55.642791  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.642802  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.642812  5581 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:50:55.642820  5581 caffe.cpp:501] detection_eval = 11.8952
-I0511 11:50:55.642830  5581 caffe.cpp:501] detection_eval = 0.0380018
-I0511 11:50:55.642840  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.642850  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.642860  5581 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:50:55.642869  5581 caffe.cpp:501] detection_eval = 12.0161
-I0511 11:50:55.642879  5581 caffe.cpp:501] detection_eval = 0.0432168
-I0511 11:50:55.642890  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642895  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.642904  5581 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:50:55.642909  5581 caffe.cpp:501] detection_eval = 12.0565
-I0511 11:50:55.642916  5581 caffe.cpp:501] detection_eval = 0.0387167
-I0511 11:50:55.642921  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642930  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642933  5581 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:50:55.642941  5581 caffe.cpp:501] detection_eval = 12.1149
-I0511 11:50:55.642946  5581 caffe.cpp:501] detection_eval = 0.0401728
-I0511 11:50:55.642954  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642958  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642967  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.642972  5581 caffe.cpp:501] detection_eval = 12.131
-I0511 11:50:55.642980  5581 caffe.cpp:501] detection_eval = 0.0417049
-I0511 11:50:55.642984  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.642992  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.642997  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.643005  5581 caffe.cpp:501] detection_eval = 12.1855
-I0511 11:50:55.643009  5581 caffe.cpp:501] detection_eval = 0.0408608
-I0511 11:50:55.643018  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.643021  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643029  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.643034  5581 caffe.cpp:501] detection_eval = 12.244
-I0511 11:50:55.643043  5581 caffe.cpp:501] detection_eval = 0.0384291
-I0511 11:50:55.643048  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.643057  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.643065  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.643074  5581 caffe.cpp:501] detection_eval = 12.3125
-I0511 11:50:55.643079  5581 caffe.cpp:501] detection_eval = 0.0450185
-I0511 11:50:55.643087  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.643091  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.643100  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.643103  5581 caffe.cpp:501] detection_eval = 12.3609
-I0511 11:50:55.643111  5581 caffe.cpp:501] detection_eval = 0.0436057
-I0511 11:50:55.643116  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643124  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.643128  5581 caffe.cpp:501] detection_eval = 0.0745968
-I0511 11:50:55.643137  5581 caffe.cpp:501] detection_eval = 12.3528
-I0511 11:50:55.643147  5581 caffe.cpp:501] detection_eval = 0.0433886
-I0511 11:50:55.643152  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.643160  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643165  5581 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:50:55.643174  5581 caffe.cpp:501] detection_eval = 12.381
-I0511 11:50:55.643179  5581 caffe.cpp:501] detection_eval = 0.04524
-I0511 11:50:55.643187  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643191  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.643200  5581 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:50:55.643205  5581 caffe.cpp:501] detection_eval = 12.4335
-I0511 11:50:55.643213  5581 caffe.cpp:501] detection_eval = 0.0384115
-I0511 11:50:55.643218  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643226  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643230  5581 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:50:55.643239  5581 caffe.cpp:501] detection_eval = 12.4677
-I0511 11:50:55.643242  5581 caffe.cpp:501] detection_eval = 0.0406575
-I0511 11:50:55.643247  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643251  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643256  5581 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:50:55.643261  5581 caffe.cpp:501] detection_eval = 12.5302
-I0511 11:50:55.643265  5581 caffe.cpp:501] detection_eval = 0.0391606
-I0511 11:50:55.643270  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.643275  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.643281  5581 caffe.cpp:501] detection_eval = 0.0806452
-I0511 11:50:55.643285  5581 caffe.cpp:501] detection_eval = 12.6129
-I0511 11:50:55.643291  5581 caffe.cpp:501] detection_eval = 0.0460983
-I0511 11:50:55.643297  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.643304  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643309  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643314  5581 caffe.cpp:501] detection_eval = 12.7198
-I0511 11:50:55.643319  5581 caffe.cpp:501] detection_eval = 0.0505505
-I0511 11:50:55.643323  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.643328  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.643333  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643337  5581 caffe.cpp:501] detection_eval = 12.8266
-I0511 11:50:55.643343  5581 caffe.cpp:501] detection_eval = 0.0519473
-I0511 11:50:55.643348  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643352  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643358  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643363  5581 caffe.cpp:501] detection_eval = 12.8992
-I0511 11:50:55.643368  5581 caffe.cpp:501] detection_eval = 0.0499161
-I0511 11:50:55.643373  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.643378  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.643384  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643394  5581 caffe.cpp:501] detection_eval = 12.9415
-I0511 11:50:55.643405  5581 caffe.cpp:501] detection_eval = 0.0458294
-I0511 11:50:55.643416  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643427  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.643437  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643448  5581 caffe.cpp:501] detection_eval = 13.0242
-I0511 11:50:55.643456  5581 caffe.cpp:501] detection_eval = 0.0417185
-I0511 11:50:55.643461  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643466  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.643471  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643476  5581 caffe.cpp:501] detection_eval = 13.0645
-I0511 11:50:55.643481  5581 caffe.cpp:501] detection_eval = 0.0405417
-I0511 11:50:55.643486  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643491  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643501  5581 caffe.cpp:501] detection_eval = 0.0866935
-I0511 11:50:55.643518  5581 caffe.cpp:501] detection_eval = 13.0423
-I0511 11:50:55.643530  5581 caffe.cpp:501] detection_eval = 0.0371573
-I0511 11:50:55.643540  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.643553  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.643563  5581 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:50:55.643571  5581 caffe.cpp:501] detection_eval = 13.0827
-I0511 11:50:55.643576  5581 caffe.cpp:501] detection_eval = 0.0410347
-I0511 11:50:55.643585  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.643590  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.643601  5581 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:50:55.643610  5581 caffe.cpp:501] detection_eval = 13.1431
-I0511 11:50:55.643621  5581 caffe.cpp:501] detection_eval = 0.0439197
-I0511 11:50:55.643633  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.643645  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.643654  5581 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:50:55.643663  5581 caffe.cpp:501] detection_eval = 13.1794
-I0511 11:50:55.643668  5581 caffe.cpp:501] detection_eval = 0.0455159
-I0511 11:50:55.643676  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643682  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643694  5581 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:50:55.643699  5581 caffe.cpp:501] detection_eval = 13.2339
-I0511 11:50:55.643703  5581 caffe.cpp:501] detection_eval = 0.0469671
-I0511 11:50:55.643712  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643724  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.643733  5581 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:50:55.643744  5581 caffe.cpp:501] detection_eval = 13.3044
-I0511 11:50:55.643755  5581 caffe.cpp:501] detection_eval = 0.0425159
-I0511 11:50:55.643766  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643777  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643788  5581 caffe.cpp:501] detection_eval = 0.0927419
-I0511 11:50:55.643800  5581 caffe.cpp:501] detection_eval = 13.3327
-I0511 11:50:55.643810  5581 caffe.cpp:501] detection_eval = 0.0395842
-I0511 11:50:55.643821  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.643832  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.643843  5581 caffe.cpp:501] detection_eval = 0.0927419
-I0511 11:50:55.643853  5581 caffe.cpp:501] detection_eval = 13.3992
-I0511 11:50:55.643862  5581 caffe.cpp:501] detection_eval = 0.0415257
-I0511 11:50:55.643867  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643877  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643882  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.643890  5581 caffe.cpp:501] detection_eval = 13.4395
-I0511 11:50:55.643895  5581 caffe.cpp:501] detection_eval = 0.0437205
-I0511 11:50:55.643904  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.643909  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643918  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.643924  5581 caffe.cpp:501] detection_eval = 13.4758
-I0511 11:50:55.643934  5581 caffe.cpp:501] detection_eval = 0.037161
-I0511 11:50:55.643939  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.643946  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.643952  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.643960  5581 caffe.cpp:501] detection_eval = 13.5282
-I0511 11:50:55.643966  5581 caffe.cpp:501] detection_eval = 0.0394226
-I0511 11:50:55.643975  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643985  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.643995  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.644006  5581 caffe.cpp:501] detection_eval = 13.5706
-I0511 11:50:55.644017  5581 caffe.cpp:501] detection_eval = 0.0361466
-I0511 11:50:55.644027  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644038  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.644049  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.644059  5581 caffe.cpp:501] detection_eval = 13.625
-I0511 11:50:55.644064  5581 caffe.cpp:501] detection_eval = 0.0402962
-I0511 11:50:55.644073  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.644083  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.644088  5581 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:50:55.644098  5581 caffe.cpp:501] detection_eval = 13.6532
-I0511 11:50:55.644102  5581 caffe.cpp:501] detection_eval = 0.0436865
-I0511 11:50:55.644111  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.644117  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.644125  5581 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:50:55.644131  5581 caffe.cpp:501] detection_eval = 13.6835
-I0511 11:50:55.644140  5581 caffe.cpp:501] detection_eval = 0.0398312
-I0511 11:50:55.644148  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644158  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.644170  5581 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:50:55.644181  5581 caffe.cpp:501] detection_eval = 13.7258
-I0511 11:50:55.644191  5581 caffe.cpp:501] detection_eval = 0.0427413
-I0511 11:50:55.644202  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.644215  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.644232  5581 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:50:55.644240  5581 caffe.cpp:501] detection_eval = 13.7944
-I0511 11:50:55.644253  5581 caffe.cpp:501] detection_eval = 0.038353
-I0511 11:50:55.644263  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.644273  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.644279  5581 caffe.cpp:501] detection_eval = 0.0987903
-I0511 11:50:55.644289  5581 caffe.cpp:501] detection_eval = 13.7964
-I0511 11:50:55.644294  5581 caffe.cpp:501] detection_eval = 0.0400739
-I0511 11:50:55.644302  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644309  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.644317  5581 caffe.cpp:501] detection_eval = 0.0987903
-I0511 11:50:55.644322  5581 caffe.cpp:501] detection_eval = 13.8649
-I0511 11:50:55.644332  5581 caffe.cpp:501] detection_eval = 0.0441469
-I0511 11:50:55.644337  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.644345  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.644351  5581 caffe.cpp:501] detection_eval = 0.100806
-I0511 11:50:55.644361  5581 caffe.cpp:501] detection_eval = 13.9173
-I0511 11:50:55.644366  5581 caffe.cpp:501] detection_eval = 0.0413464
-I0511 11:50:55.644374  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.644381  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.644389  5581 caffe.cpp:501] detection_eval = 0.100806
-I0511 11:50:55.644394  5581 caffe.cpp:501] detection_eval = 13.9556
-I0511 11:50:55.644403  5581 caffe.cpp:501] detection_eval = 0.0382349
-I0511 11:50:55.644409  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.644418  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.644423  5581 caffe.cpp:501] detection_eval = 0.100806
-I0511 11:50:55.644433  5581 caffe.cpp:501] detection_eval = 14.002
-I0511 11:50:55.644438  5581 caffe.cpp:501] detection_eval = 0.0338957
-I0511 11:50:55.644446  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644453  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644460  5581 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:50:55.644466  5581 caffe.cpp:501] detection_eval = 13.996
-I0511 11:50:55.644475  5581 caffe.cpp:501] detection_eval = 0.0405347
-I0511 11:50:55.644480  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.644490  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.644495  5581 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:50:55.644503  5581 caffe.cpp:501] detection_eval = 14.0383
-I0511 11:50:55.644510  5581 caffe.cpp:501] detection_eval = 0.0392191
-I0511 11:50:55.644517  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.644546  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.644556  5581 caffe.cpp:501] detection_eval = 0.106855
-I0511 11:50:55.644562  5581 caffe.cpp:501] detection_eval = 14.0464
-I0511 11:50:55.644570  5581 caffe.cpp:501] detection_eval = 0.0358572
-I0511 11:50:55.644580  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644585  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644594  5581 caffe.cpp:501] detection_eval = 0.106855
-I0511 11:50:55.644603  5581 caffe.cpp:501] detection_eval = 14.1028
-I0511 11:50:55.644611  5581 caffe.cpp:501] detection_eval = 0.0331913
-I0511 11:50:55.644616  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.644625  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644630  5581 caffe.cpp:501] detection_eval = 0.106855
-I0511 11:50:55.644639  5581 caffe.cpp:501] detection_eval = 14.125
-I0511 11:50:55.644644  5581 caffe.cpp:501] detection_eval = 0.0355084
-I0511 11:50:55.644659  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644668  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644680  5581 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:50:55.644690  5581 caffe.cpp:501] detection_eval = 14.1391
-I0511 11:50:55.644701  5581 caffe.cpp:501] detection_eval = 0.043656
-I0511 11:50:55.644709  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.644724  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.644728  5581 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:50:55.644732  5581 caffe.cpp:501] detection_eval = 14.1694
-I0511 11:50:55.644742  5581 caffe.cpp:501] detection_eval = 0.0400982
-I0511 11:50:55.644747  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.644757  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.644765  5581 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:50:55.644770  5581 caffe.cpp:501] detection_eval = 14.2157
-I0511 11:50:55.644779  5581 caffe.cpp:501] detection_eval = 0.0381633
-I0511 11:50:55.644784  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644793  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644800  5581 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:50:55.644809  5581 caffe.cpp:501] detection_eval = 14.2641
-I0511 11:50:55.644817  5581 caffe.cpp:501] detection_eval = 0.0326405
-I0511 11:50:55.644824  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.644835  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644845  5581 caffe.cpp:501] detection_eval = 0.112903
-I0511 11:50:55.644856  5581 caffe.cpp:501] detection_eval = 14.2399
-I0511 11:50:55.644867  5581 caffe.cpp:501] detection_eval = 0.0350096
-I0511 11:50:55.644878  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644886  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644896  5581 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:50:55.644901  5581 caffe.cpp:501] detection_eval = 14.2661
-I0511 11:50:55.644909  5581 caffe.cpp:501] detection_eval = 0.0319027
-I0511 11:50:55.644915  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.644923  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.644929  5581 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:50:55.644937  5581 caffe.cpp:501] detection_eval = 14.3085
-I0511 11:50:55.644943  5581 caffe.cpp:501] detection_eval = 0.0341428
-I0511 11:50:55.644953  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644958  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644965  5581 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:50:55.644974  5581 caffe.cpp:501] detection_eval = 14.3327
-I0511 11:50:55.644980  5581 caffe.cpp:501] detection_eval = 0.0308989
-I0511 11:50:55.644994  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644999  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.645007  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645014  5581 caffe.cpp:501] detection_eval = 14.3387
-I0511 11:50:55.645022  5581 caffe.cpp:501] detection_eval = 0.034269
-I0511 11:50:55.645032  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645041  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645051  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645062  5581 caffe.cpp:501] detection_eval = 14.377
-I0511 11:50:55.645078  5581 caffe.cpp:501] detection_eval = 0.0313198
-I0511 11:50:55.645093  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.645104  5581 caffe.cpp:501] detection_eval = 1
-I0511 11:50:55.645115  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645126  5581 caffe.cpp:501] detection_eval = 14.4274
-I0511 11:50:55.645138  5581 caffe.cpp:501] detection_eval = 0.0345124
-I0511 11:50:55.645148  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.645157  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.645164  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645170  5581 caffe.cpp:501] detection_eval = 14.4597
-I0511 11:50:55.645179  5581 caffe.cpp:501] detection_eval = 0.0330961
-I0511 11:50:55.645184  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645191  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645196  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645205  5581 caffe.cpp:501] detection_eval = 14.506
-I0511 11:50:55.645210  5581 caffe.cpp:501] detection_eval = 0.0319597
-I0511 11:50:55.645220  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645236  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645242  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645253  5581 caffe.cpp:501] detection_eval = 14.5585
-I0511 11:50:55.645258  5581 caffe.cpp:501] detection_eval = 0.0339037
-I0511 11:50:55.645267  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645272  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645282  5581 caffe.cpp:501] detection_eval = 0.120968
-I0511 11:50:55.645287  5581 caffe.cpp:501] detection_eval = 14.5827
-I0511 11:50:55.645295  5581 caffe.cpp:501] detection_eval = 0.0324709
-I0511 11:50:55.645305  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645316  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645326  5581 caffe.cpp:501] detection_eval = 0.120968
-I0511 11:50:55.645337  5581 caffe.cpp:501] detection_eval = 14.619
-I0511 11:50:55.645349  5581 caffe.cpp:501] detection_eval = 0.034883
-I0511 11:50:55.645359  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.645370  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645380  5581 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:50:55.645387  5581 caffe.cpp:501] detection_eval = 14.6089
-I0511 11:50:55.645396  5581 caffe.cpp:501] detection_eval = 0.0312104
-I0511 11:50:55.645406  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.645411  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645421  5581 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:50:55.645426  5581 caffe.cpp:501] detection_eval = 14.6573
-I0511 11:50:55.645434  5581 caffe.cpp:501] detection_eval = 0.0334001
-I0511 11:50:55.645440  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645449  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.645454  5581 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:50:55.645465  5581 caffe.cpp:501] detection_eval = 14.7117
-I0511 11:50:55.645474  5581 caffe.cpp:501] detection_eval = 0.0315325
-I0511 11:50:55.645485  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.645495  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.645506  5581 caffe.cpp:501] detection_eval = 0.125
-I0511 11:50:55.645516  5581 caffe.cpp:501] detection_eval = 14.7097
-I0511 11:50:55.645529  5581 caffe.cpp:501] detection_eval = 0.0336649
-I0511 11:50:55.645539  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645548  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645553  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645562  5581 caffe.cpp:501] detection_eval = 14.7117
-I0511 11:50:55.645571  5581 caffe.cpp:501] detection_eval = 0.0368732
-I0511 11:50:55.645581  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.645586  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645594  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645603  5581 caffe.cpp:501] detection_eval = 14.7641
-I0511 11:50:55.645609  5581 caffe.cpp:501] detection_eval = 0.0349081
-I0511 11:50:55.645617  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645623  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645632  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645637  5581 caffe.cpp:501] detection_eval = 14.8427
-I0511 11:50:55.645645  5581 caffe.cpp:501] detection_eval = 0.0354973
-I0511 11:50:55.645650  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645659  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645664  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645673  5581 caffe.cpp:501] detection_eval = 14.9052
-I0511 11:50:55.645679  5581 caffe.cpp:501] detection_eval = 0.0350628
-I0511 11:50:55.645687  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645694  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.645701  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645706  5581 caffe.cpp:501] detection_eval = 14.9819
-I0511 11:50:55.645718  5581 caffe.cpp:501] detection_eval = 0.0350495
-I0511 11:50:55.645723  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.645727  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.645735  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645745  5581 caffe.cpp:501] detection_eval = 15.0827
-I0511 11:50:55.645750  5581 caffe.cpp:501] detection_eval = 0.0356054
-I0511 11:50:55.645757  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645763  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.645771  5581 caffe.cpp:501] detection_eval = 0.131048
-I0511 11:50:55.645776  5581 caffe.cpp:501] detection_eval = 15.1109
-I0511 11:50:55.645786  5581 caffe.cpp:501] detection_eval = 0.0375291
-I0511 11:50:55.645790  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.645799  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.645804  5581 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:50:55.645813  5581 caffe.cpp:501] detection_eval = 15.0867
-I0511 11:50:55.645820  5581 caffe.cpp:501] detection_eval = 0.0346692
-I0511 11:50:55.645829  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.645834  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.645843  5581 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:50:55.645848  5581 caffe.cpp:501] detection_eval = 15.1774
-I0511 11:50:55.645856  5581 caffe.cpp:501] detection_eval = 0.0387023
-I0511 11:50:55.645862  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.645870  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.645876  5581 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:50:55.645884  5581 caffe.cpp:501] detection_eval = 15.2782
-I0511 11:50:55.645890  5581 caffe.cpp:501] detection_eval = 0.0381264
-I0511 11:50:55.645901  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.645910  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.645921  5581 caffe.cpp:501] detection_eval = 0.139113
-I0511 11:50:55.645928  5581 caffe.cpp:501] detection_eval = 15.3145
-I0511 11:50:55.645936  5581 caffe.cpp:501] detection_eval = 0.0370335
-I0511 11:50:55.645942  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645951  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.645956  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.645967  5581 caffe.cpp:501] detection_eval = 15.4133
-I0511 11:50:55.645977  5581 caffe.cpp:501] detection_eval = 0.0354428
-I0511 11:50:55.645987  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645998  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.646008  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.646028  5581 caffe.cpp:501] detection_eval = 15.5927
-I0511 11:50:55.646040  5581 caffe.cpp:501] detection_eval = 0.0402357
-I0511 11:50:55.646050  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.646062  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.646071  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.646077  5581 caffe.cpp:501] detection_eval = 15.7621
-I0511 11:50:55.646086  5581 caffe.cpp:501] detection_eval = 0.0409724
-I0511 11:50:55.646091  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.646100  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.646109  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.646118  5581 caffe.cpp:501] detection_eval = 15.9133
-I0511 11:50:55.646131  5581 caffe.cpp:501] detection_eval = 0.0364343
-I0511 11:50:55.646138  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.646149  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.646160  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.646170  5581 caffe.cpp:501] detection_eval = 16.1734
-I0511 11:50:55.646181  5581 caffe.cpp:501] detection_eval = 0.0399021
-I0511 11:50:55.646193  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.646203  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.646214  5581 caffe.cpp:501] detection_eval = 0.145161
-I0511 11:50:55.646224  5581 caffe.cpp:501] detection_eval = 16.4274
-I0511 11:50:55.646236  5581 caffe.cpp:501] detection_eval = 0.0425502
-I0511 11:50:55.646246  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.646257  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.646268  5581 caffe.cpp:501] detection_eval = 0.149194
-I0511 11:50:55.646279  5581 caffe.cpp:501] detection_eval = 16.9194
-I0511 11:50:55.646289  5581 caffe.cpp:501] detection_eval = 0.0322777
-I0511 11:50:55.646299  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.646304  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.646312  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646322  5581 caffe.cpp:501] detection_eval = 4.15323
-I0511 11:50:55.646330  5581 caffe.cpp:501] detection_eval = 0.162295
-I0511 11:50:55.646340  5581 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:50:55.646351  5581 caffe.cpp:501] detection_eval = 0.862903
-I0511 11:50:55.646363  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646373  5581 caffe.cpp:501] detection_eval = 4.44355
-I0511 11:50:55.646385  5581 caffe.cpp:501] detection_eval = 0.0833618
-I0511 11:50:55.646397  5581 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:50:55.646409  5581 caffe.cpp:501] detection_eval = 0.941532
-I0511 11:50:55.646420  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646428  5581 caffe.cpp:501] detection_eval = 4.62903
-I0511 11:50:55.646437  5581 caffe.cpp:501] detection_eval = 0.0740181
-I0511 11:50:55.646442  5581 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:50:55.646453  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.646458  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646466  5581 caffe.cpp:501] detection_eval = 4.82863
-I0511 11:50:55.646471  5581 caffe.cpp:501] detection_eval = 0.0657454
-I0511 11:50:55.646481  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.646486  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.646494  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646503  5581 caffe.cpp:501] detection_eval = 4.97177
-I0511 11:50:55.646514  5581 caffe.cpp:501] detection_eval = 0.0525329
-I0511 11:50:55.646525  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.646538  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.646548  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646558  5581 caffe.cpp:501] detection_eval = 5.08266
-I0511 11:50:55.646569  5581 caffe.cpp:501] detection_eval = 0.0577359
-I0511 11:50:55.646579  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.646589  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.646600  5581 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:50:55.646613  5581 caffe.cpp:501] detection_eval = 5.16129
-I0511 11:50:55.646622  5581 caffe.cpp:501] detection_eval = 0.0573572
-I0511 11:50:55.646631  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.646641  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.646649  5581 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:50:55.646659  5581 caffe.cpp:501] detection_eval = 5.2621
-I0511 11:50:55.646670  5581 caffe.cpp:501] detection_eval = 0.0510652
-I0511 11:50:55.646680  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.646690  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.646701  5581 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:50:55.646713  5581 caffe.cpp:501] detection_eval = 5.34879
-I0511 11:50:55.646723  5581 caffe.cpp:501] detection_eval = 0.0441459
-I0511 11:50:55.646733  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.646744  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.646754  5581 caffe.cpp:501] detection_eval = 1.01411
-I0511 11:50:55.646764  5581 caffe.cpp:501] detection_eval = 5.4254
-I0511 11:50:55.646775  5581 caffe.cpp:501] detection_eval = 0.047929
-I0511 11:50:55.646785  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.646795  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.646802  5581 caffe.cpp:501] detection_eval = 1.01613
-I0511 11:50:55.646816  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.646826  5581 caffe.cpp:501] detection_eval = 0.0461593
-I0511 11:50:55.646836  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.646845  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.646850  5581 caffe.cpp:501] detection_eval = 1.01613
-I0511 11:50:55.646858  5581 caffe.cpp:501] detection_eval = 5.53024
-I0511 11:50:55.646863  5581 caffe.cpp:501] detection_eval = 0.0461314
-I0511 11:50:55.646872  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.646878  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.646888  5581 caffe.cpp:501] detection_eval = 1.01815
-I0511 11:50:55.646893  5581 caffe.cpp:501] detection_eval = 5.57056
-I0511 11:50:55.646900  5581 caffe.cpp:501] detection_eval = 0.0440755
-I0511 11:50:55.646906  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.646914  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.646920  5581 caffe.cpp:501] detection_eval = 1.02218
-I0511 11:50:55.646929  5581 caffe.cpp:501] detection_eval = 5.59274
-I0511 11:50:55.646937  5581 caffe.cpp:501] detection_eval = 0.0506842
-I0511 11:50:55.646942  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.646951  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.646956  5581 caffe.cpp:501] detection_eval = 1.02218
-I0511 11:50:55.646965  5581 caffe.cpp:501] detection_eval = 5.67944
-I0511 11:50:55.646970  5581 caffe.cpp:501] detection_eval = 0.0473503
-I0511 11:50:55.646978  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.646984  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.646992  5581 caffe.cpp:501] detection_eval = 1.02218
-I0511 11:50:55.646997  5581 caffe.cpp:501] detection_eval = 5.75605
-I0511 11:50:55.647006  5581 caffe.cpp:501] detection_eval = 0.0442622
-I0511 11:50:55.647011  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.647020  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.647025  5581 caffe.cpp:501] detection_eval = 1.02419
-I0511 11:50:55.647033  5581 caffe.cpp:501] detection_eval = 5.81653
-I0511 11:50:55.647039  5581 caffe.cpp:501] detection_eval = 0.0437179
-I0511 11:50:55.647047  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647053  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.647061  5581 caffe.cpp:501] detection_eval = 1.02419
-I0511 11:50:55.647066  5581 caffe.cpp:501] detection_eval = 5.89919
-I0511 11:50:55.647075  5581 caffe.cpp:501] detection_eval = 0.0422151
-I0511 11:50:55.647080  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647089  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.647099  5581 caffe.cpp:501] detection_eval = 1.02419
-I0511 11:50:55.647107  5581 caffe.cpp:501] detection_eval = 5.97379
-I0511 11:50:55.647116  5581 caffe.cpp:501] detection_eval = 0.0397156
-I0511 11:50:55.647125  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.647135  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.647141  5581 caffe.cpp:501] detection_eval = 1.02621
-I0511 11:50:55.647152  5581 caffe.cpp:501] detection_eval = 6.03831
-I0511 11:50:55.647162  5581 caffe.cpp:501] detection_eval = 0.0410696
-I0511 11:50:55.647173  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647184  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647194  5581 caffe.cpp:501] detection_eval = 1.02823
-I0511 11:50:55.647203  5581 caffe.cpp:501] detection_eval = 6.05242
-I0511 11:50:55.647213  5581 caffe.cpp:501] detection_eval = 0.0445519
-I0511 11:50:55.647218  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.647227  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.647235  5581 caffe.cpp:501] detection_eval = 1.02823
-I0511 11:50:55.647240  5581 caffe.cpp:501] detection_eval = 6.11492
-I0511 11:50:55.647249  5581 caffe.cpp:501] detection_eval = 0.041272
-I0511 11:50:55.647255  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647267  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.647276  5581 caffe.cpp:501] detection_eval = 1.03024
-I0511 11:50:55.647292  5581 caffe.cpp:501] detection_eval = 6.18145
-I0511 11:50:55.647301  5581 caffe.cpp:501] detection_eval = 0.0424877
-I0511 11:50:55.647311  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647322  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.647327  5581 caffe.cpp:501] detection_eval = 1.03226
-I0511 11:50:55.647336  5581 caffe.cpp:501] detection_eval = 6.24194
-I0511 11:50:55.647341  5581 caffe.cpp:501] detection_eval = 0.0409147
-I0511 11:50:55.647349  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647356  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.647367  5581 caffe.cpp:501] detection_eval = 1.03427
-I0511 11:50:55.647377  5581 caffe.cpp:501] detection_eval = 6.31048
-I0511 11:50:55.647387  5581 caffe.cpp:501] detection_eval = 0.043412
-I0511 11:50:55.647397  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.647408  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.647418  5581 caffe.cpp:501] detection_eval = 1.03629
-I0511 11:50:55.647426  5581 caffe.cpp:501] detection_eval = 6.41935
-I0511 11:50:55.647431  5581 caffe.cpp:501] detection_eval = 0.0427416
-I0511 11:50:55.647439  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.647445  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.647454  5581 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:50:55.647459  5581 caffe.cpp:501] detection_eval = 6.41935
-I0511 11:50:55.647467  5581 caffe.cpp:501] detection_eval = 0.0435719
-I0511 11:50:55.647473  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.647481  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.647487  5581 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:50:55.647495  5581 caffe.cpp:501] detection_eval = 6.50605
-I0511 11:50:55.647500  5581 caffe.cpp:501] detection_eval = 0.0387101
-I0511 11:50:55.647508  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647514  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.647524  5581 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:50:55.647534  5581 caffe.cpp:501] detection_eval = 6.5746
-I0511 11:50:55.647544  5581 caffe.cpp:501] detection_eval = 0.0392613
-I0511 11:50:55.647555  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647565  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.647577  5581 caffe.cpp:501] detection_eval = 1.04435
-I0511 11:50:55.647586  5581 caffe.cpp:501] detection_eval = 6.57863
-I0511 11:50:55.647596  5581 caffe.cpp:501] detection_eval = 0.0379121
-I0511 11:50:55.647603  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647615  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647620  5581 caffe.cpp:501] detection_eval = 1.04435
-I0511 11:50:55.647629  5581 caffe.cpp:501] detection_eval = 6.625
-I0511 11:50:55.647634  5581 caffe.cpp:501] detection_eval = 0.0442701
-I0511 11:50:55.647650  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647658  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.647668  5581 caffe.cpp:501] detection_eval = 1.04637
-I0511 11:50:55.647680  5581 caffe.cpp:501] detection_eval = 6.70565
-I0511 11:50:55.647689  5581 caffe.cpp:501] detection_eval = 0.0376735
-I0511 11:50:55.647699  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647711  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647722  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647729  5581 caffe.cpp:501] detection_eval = 6.73185
-I0511 11:50:55.647734  5581 caffe.cpp:501] detection_eval = 0.0395867
-I0511 11:50:55.647743  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647748  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647756  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647763  5581 caffe.cpp:501] detection_eval = 6.83669
-I0511 11:50:55.647770  5581 caffe.cpp:501] detection_eval = 0.040853
-I0511 11:50:55.647776  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647789  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647797  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647809  5581 caffe.cpp:501] detection_eval = 6.93347
-I0511 11:50:55.647819  5581 caffe.cpp:501] detection_eval = 0.0420755
-I0511 11:50:55.647830  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.647838  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.647843  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647852  5581 caffe.cpp:501] detection_eval = 6.98589
-I0511 11:50:55.647857  5581 caffe.cpp:501] detection_eval = 0.0422012
-I0511 11:50:55.647866  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.647871  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.647879  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647888  5581 caffe.cpp:501] detection_eval = 7.06855
-I0511 11:50:55.647893  5581 caffe.cpp:501] detection_eval = 0.0381115
-I0511 11:50:55.647902  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.647907  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.647917  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647922  5581 caffe.cpp:501] detection_eval = 7.15323
-I0511 11:50:55.647933  5581 caffe.cpp:501] detection_eval = 0.048996
-I0511 11:50:55.647943  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647953  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647963  5581 caffe.cpp:501] detection_eval = 1.05242
-I0511 11:50:55.647971  5581 caffe.cpp:501] detection_eval = 7.20161
-I0511 11:50:55.647979  5581 caffe.cpp:501] detection_eval = 0.0458926
-I0511 11:50:55.647989  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.648000  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.648010  5581 caffe.cpp:501] detection_eval = 1.05444
-I0511 11:50:55.648020  5581 caffe.cpp:501] detection_eval = 7.26815
-I0511 11:50:55.648030  5581 caffe.cpp:501] detection_eval = 0.0430835
-I0511 11:50:55.648041  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648051  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648062  5581 caffe.cpp:501] detection_eval = 1.05444
-I0511 11:50:55.648072  5581 caffe.cpp:501] detection_eval = 7.42137
-I0511 11:50:55.648083  5581 caffe.cpp:501] detection_eval = 0.0464151
-I0511 11:50:55.648093  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.648103  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.648111  5581 caffe.cpp:501] detection_eval = 1.05444
-I0511 11:50:55.648118  5581 caffe.cpp:501] detection_eval = 7.47581
-I0511 11:50:55.648125  5581 caffe.cpp:501] detection_eval = 0.0399444
-I0511 11:50:55.648130  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.648140  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.648149  5581 caffe.cpp:501] detection_eval = 1.05645
-I0511 11:50:55.648154  5581 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:50:55.648164  5581 caffe.cpp:501] detection_eval = 0.0454342
-I0511 11:50:55.648175  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.648185  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.648196  5581 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:50:55.648206  5581 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:50:55.648217  5581 caffe.cpp:501] detection_eval = 0.0434764
-I0511 11:50:55.648227  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.648238  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.648248  5581 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:50:55.648259  5581 caffe.cpp:501] detection_eval = 7.61895
-I0511 11:50:55.648269  5581 caffe.cpp:501] detection_eval = 0.0371605
-I0511 11:50:55.648280  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.648291  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.648300  5581 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:50:55.648309  5581 caffe.cpp:501] detection_eval = 7.6875
-I0511 11:50:55.648314  5581 caffe.cpp:501] detection_eval = 0.0416036
-I0511 11:50:55.648324  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648331  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648335  5581 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:50:55.648344  5581 caffe.cpp:501] detection_eval = 7.78024
-I0511 11:50:55.648355  5581 caffe.cpp:501] detection_eval = 0.0401231
-I0511 11:50:55.648365  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.648376  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.648387  5581 caffe.cpp:501] detection_eval = 1.0625
-I0511 11:50:55.648398  5581 caffe.cpp:501] detection_eval = 7.83669
-I0511 11:50:55.648407  5581 caffe.cpp:501] detection_eval = 0.0427721
-I0511 11:50:55.648416  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648422  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.648432  5581 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:50:55.648437  5581 caffe.cpp:501] detection_eval = 7.87097
-I0511 11:50:55.648444  5581 caffe.cpp:501] detection_eval = 0.0395211
-I0511 11:50:55.648454  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.648459  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.648468  5581 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:50:55.648478  5581 caffe.cpp:501] detection_eval = 7.94758
-I0511 11:50:55.648488  5581 caffe.cpp:501] detection_eval = 0.0378073
-I0511 11:50:55.648499  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.648509  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.648520  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648538  5581 caffe.cpp:501] detection_eval = 7.99597
-I0511 11:50:55.648555  5581 caffe.cpp:501] detection_eval = 0.0381689
-I0511 11:50:55.648563  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648573  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648582  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648588  5581 caffe.cpp:501] detection_eval = 8.06855
-I0511 11:50:55.648597  5581 caffe.cpp:501] detection_eval = 0.0425882
-I0511 11:50:55.648602  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.648610  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.648615  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648624  5581 caffe.cpp:501] detection_eval = 8.11492
-I0511 11:50:55.648630  5581 caffe.cpp:501] detection_eval = 0.0383515
-I0511 11:50:55.648638  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.648644  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.648653  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648658  5581 caffe.cpp:501] detection_eval = 8.16331
-I0511 11:50:55.648667  5581 caffe.cpp:501] detection_eval = 0.0415489
-I0511 11:50:55.648679  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.648687  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.648696  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648705  5581 caffe.cpp:501] detection_eval = 8.25806
-I0511 11:50:55.648715  5581 caffe.cpp:501] detection_eval = 0.0427888
-I0511 11:50:55.648720  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648728  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.648735  5581 caffe.cpp:501] detection_eval = 1.07056
-I0511 11:50:55.648742  5581 caffe.cpp:501] detection_eval = 8.31048
-I0511 11:50:55.648748  5581 caffe.cpp:501] detection_eval = 0.0417843
-I0511 11:50:55.648759  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648768  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648779  5581 caffe.cpp:501] detection_eval = 1.07258
-I0511 11:50:55.648789  5581 caffe.cpp:501] detection_eval = 8.38306
-I0511 11:50:55.648799  5581 caffe.cpp:501] detection_eval = 0.0434073
-I0511 11:50:55.648810  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648820  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.648825  5581 caffe.cpp:501] detection_eval = 1.07258
-I0511 11:50:55.648834  5581 caffe.cpp:501] detection_eval = 8.4879
-I0511 11:50:55.648839  5581 caffe.cpp:501] detection_eval = 0.0444408
-I0511 11:50:55.648850  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648855  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648864  5581 caffe.cpp:501] detection_eval = 1.0746
-I0511 11:50:55.648869  5581 caffe.cpp:501] detection_eval = 8.54234
-I0511 11:50:55.648877  5581 caffe.cpp:501] detection_eval = 0.0404407
-I0511 11:50:55.648882  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.648891  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.648896  5581 caffe.cpp:501] detection_eval = 1.07661
-I0511 11:50:55.648905  5581 caffe.cpp:501] detection_eval = 8.57258
-I0511 11:50:55.648910  5581 caffe.cpp:501] detection_eval = 0.0421837
-I0511 11:50:55.648919  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648924  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648933  5581 caffe.cpp:501] detection_eval = 1.07863
-I0511 11:50:55.648938  5581 caffe.cpp:501] detection_eval = 8.6371
-I0511 11:50:55.648947  5581 caffe.cpp:501] detection_eval = 0.0382398
-I0511 11:50:55.648952  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.648962  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.648967  5581 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:50:55.648974  5581 caffe.cpp:501] detection_eval = 8.71976
-I0511 11:50:55.648980  5581 caffe.cpp:501] detection_eval = 0.0412205
-I0511 11:50:55.648989  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648994  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649003  5581 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:50:55.649008  5581 caffe.cpp:501] detection_eval = 8.83669
-I0511 11:50:55.649016  5581 caffe.cpp:501] detection_eval = 0.0449207
-I0511 11:50:55.649022  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.649030  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.649039  5581 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:50:55.649044  5581 caffe.cpp:501] detection_eval = 8.9254
-I0511 11:50:55.649053  5581 caffe.cpp:501] detection_eval = 0.0446503
-I0511 11:50:55.649060  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.649068  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.649073  5581 caffe.cpp:501] detection_eval = 1.08468
-I0511 11:50:55.649081  5581 caffe.cpp:501] detection_eval = 8.98589
-I0511 11:50:55.649086  5581 caffe.cpp:501] detection_eval = 0.0438332
-I0511 11:50:55.649096  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649101  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.649109  5581 caffe.cpp:501] detection_eval = 1.08468
-I0511 11:50:55.649114  5581 caffe.cpp:501] detection_eval = 9.09879
-I0511 11:50:55.649122  5581 caffe.cpp:501] detection_eval = 0.0409492
-I0511 11:50:55.649132  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.649144  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649154  5581 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:50:55.649170  5581 caffe.cpp:501] detection_eval = 9.16532
-I0511 11:50:55.649179  5581 caffe.cpp:501] detection_eval = 0.0465822
-I0511 11:50:55.649190  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.649201  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649211  5581 caffe.cpp:501] detection_eval = 1.08871
-I0511 11:50:55.649221  5581 caffe.cpp:501] detection_eval = 9.22379
-I0511 11:50:55.649227  5581 caffe.cpp:501] detection_eval = 0.0373351
-I0511 11:50:55.649235  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.649240  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649250  5581 caffe.cpp:501] detection_eval = 1.09073
-I0511 11:50:55.649255  5581 caffe.cpp:501] detection_eval = 9.30847
-I0511 11:50:55.649262  5581 caffe.cpp:501] detection_eval = 0.0483995
-I0511 11:50:55.649267  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.649276  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.649284  5581 caffe.cpp:501] detection_eval = 1.09274
-I0511 11:50:55.649294  5581 caffe.cpp:501] detection_eval = 9.36694
-I0511 11:50:55.649305  5581 caffe.cpp:501] detection_eval = 0.045512
-I0511 11:50:55.649315  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.649327  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649334  5581 caffe.cpp:501] detection_eval = 1.09476
-I0511 11:50:55.649344  5581 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:50:55.649351  5581 caffe.cpp:501] detection_eval = 0.0479182
-I0511 11:50:55.649359  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.649365  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.649374  5581 caffe.cpp:501] detection_eval = 1.09677
-I0511 11:50:55.649379  5581 caffe.cpp:501] detection_eval = 9.50403
-I0511 11:50:55.649387  5581 caffe.cpp:501] detection_eval = 0.0436144
-I0511 11:50:55.649394  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649401  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.649407  5581 caffe.cpp:501] detection_eval = 1.09879
-I0511 11:50:55.649417  5581 caffe.cpp:501] detection_eval = 9.54637
-I0511 11:50:55.649426  5581 caffe.cpp:501] detection_eval = 0.0455071
-I0511 11:50:55.649437  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.649449  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649459  5581 caffe.cpp:501] detection_eval = 1.09879
-I0511 11:50:55.649471  5581 caffe.cpp:501] detection_eval = 9.66129
-I0511 11:50:55.649479  5581 caffe.cpp:501] detection_eval = 0.0471619
-I0511 11:50:55.649484  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.649492  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649498  5581 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:50:55.649507  5581 caffe.cpp:501] detection_eval = 9.71976
-I0511 11:50:55.649515  5581 caffe.cpp:501] detection_eval = 0.0502448
-I0511 11:50:55.649524  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.649534  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.649545  5581 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:50:55.649555  5581 caffe.cpp:501] detection_eval = 9.84879
-I0511 11:50:55.649566  5581 caffe.cpp:501] detection_eval = 0.054421
-I0511 11:50:55.649577  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.649587  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.649592  5581 caffe.cpp:501] detection_eval = 1.10484
-I0511 11:50:55.649600  5581 caffe.cpp:501] detection_eval = 9.89315
-I0511 11:50:55.649606  5581 caffe.cpp:501] detection_eval = 0.0514542
-I0511 11:50:55.649615  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649621  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649628  5581 caffe.cpp:501] detection_eval = 1.10685
-I0511 11:50:55.649634  5581 caffe.cpp:501] detection_eval = 9.92137
-I0511 11:50:55.649647  5581 caffe.cpp:501] detection_eval = 0.0478509
-I0511 11:50:55.649652  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.649662  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.649670  5581 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:50:55.649682  5581 caffe.cpp:501] detection_eval = 9.94355
-I0511 11:50:55.649693  5581 caffe.cpp:501] detection_eval = 0.0418964
-I0511 11:50:55.649703  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649713  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649724  5581 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:50:55.649734  5581 caffe.cpp:501] detection_eval = 10.0202
-I0511 11:50:55.649739  5581 caffe.cpp:501] detection_eval = 0.0441931
-I0511 11:50:55.649747  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.649754  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.649761  5581 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:50:55.649767  5581 caffe.cpp:501] detection_eval = 10.0806
-I0511 11:50:55.649776  5581 caffe.cpp:501] detection_eval = 0.0413312
-I0511 11:50:55.649781  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.649791  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.649799  5581 caffe.cpp:501] detection_eval = 1.11089
-I0511 11:50:55.649804  5581 caffe.cpp:501] detection_eval = 10.1512
-I0511 11:50:55.649822  5581 caffe.cpp:501] detection_eval = 0.0473174
-I0511 11:50:55.649832  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.649842  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.649853  5581 caffe.cpp:501] detection_eval = 1.1129
-I0511 11:50:55.649861  5581 caffe.cpp:501] detection_eval = 10.2077
-I0511 11:50:55.649870  5581 caffe.cpp:501] detection_eval = 0.041972
-I0511 11:50:55.649875  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.649884  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649890  5581 caffe.cpp:501] detection_eval = 1.11694
-I0511 11:50:55.649899  5581 caffe.cpp:501] detection_eval = 10.2581
-I0511 11:50:55.649904  5581 caffe.cpp:501] detection_eval = 0.0428795
-I0511 11:50:55.649912  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649919  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.649926  5581 caffe.cpp:501] detection_eval = 1.11895
-I0511 11:50:55.649931  5581 caffe.cpp:501] detection_eval = 10.2964
-I0511 11:50:55.649942  5581 caffe.cpp:501] detection_eval = 0.0449703
-I0511 11:50:55.649950  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.649961  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649971  5581 caffe.cpp:501] detection_eval = 1.11895
-I0511 11:50:55.649981  5581 caffe.cpp:501] detection_eval = 10.3891
-I0511 11:50:55.649993  5581 caffe.cpp:501] detection_eval = 0.0461663
-I0511 11:50:55.650003  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650012  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.650020  5581 caffe.cpp:501] detection_eval = 1.12097
-I0511 11:50:55.650025  5581 caffe.cpp:501] detection_eval = 10.4496
-I0511 11:50:55.650034  5581 caffe.cpp:501] detection_eval = 0.0472882
-I0511 11:50:55.650039  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650048  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.650053  5581 caffe.cpp:501] detection_eval = 1.12298
-I0511 11:50:55.650063  5581 caffe.cpp:501] detection_eval = 10.4839
-I0511 11:50:55.650068  5581 caffe.cpp:501] detection_eval = 0.0490379
-I0511 11:50:55.650076  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.650082  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650090  5581 caffe.cpp:501] detection_eval = 1.125
-I0511 11:50:55.650095  5581 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:50:55.650104  5581 caffe.cpp:501] detection_eval = 0.0433475
-I0511 11:50:55.650110  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.650118  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.650123  5581 caffe.cpp:501] detection_eval = 1.125
-I0511 11:50:55.650140  5581 caffe.cpp:501] detection_eval = 10.6411
-I0511 11:50:55.650149  5581 caffe.cpp:501] detection_eval = 0.0465548
-I0511 11:50:55.650161  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.650171  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.650182  5581 caffe.cpp:501] detection_eval = 1.125
-I0511 11:50:55.650192  5581 caffe.cpp:501] detection_eval = 10.6996
-I0511 11:50:55.650200  5581 caffe.cpp:501] detection_eval = 0.0447184
-I0511 11:50:55.650205  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.650214  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.650219  5581 caffe.cpp:501] detection_eval = 1.12903
-I0511 11:50:55.650228  5581 caffe.cpp:501] detection_eval = 10.7319
-I0511 11:50:55.650233  5581 caffe.cpp:501] detection_eval = 0.0495963
-I0511 11:50:55.650241  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.650247  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.650255  5581 caffe.cpp:501] detection_eval = 1.12903
-I0511 11:50:55.650260  5581 caffe.cpp:501] detection_eval = 10.8407
-I0511 11:50:55.650269  5581 caffe.cpp:501] detection_eval = 0.041825
-I0511 11:50:55.650279  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.650287  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650295  5581 caffe.cpp:501] detection_eval = 1.13306
-I0511 11:50:55.650301  5581 caffe.cpp:501] detection_eval = 10.8448
-I0511 11:50:55.650305  5581 caffe.cpp:501] detection_eval = 0.0408316
-I0511 11:50:55.650315  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.650322  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.650327  5581 caffe.cpp:501] detection_eval = 1.13508
-I0511 11:50:55.650336  5581 caffe.cpp:501] detection_eval = 10.9738
-I0511 11:50:55.650341  5581 caffe.cpp:501] detection_eval = 0.0480057
-I0511 11:50:55.650354  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.650362  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.650373  5581 caffe.cpp:501] detection_eval = 1.13508
-I0511 11:50:55.650383  5581 caffe.cpp:501] detection_eval = 11.0746
-I0511 11:50:55.650394  5581 caffe.cpp:501] detection_eval = 0.0489584
-I0511 11:50:55.650405  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.650416  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.650426  5581 caffe.cpp:501] detection_eval = 1.13508
-I0511 11:50:55.650436  5581 caffe.cpp:501] detection_eval = 11.1794
-I0511 11:50:55.650447  5581 caffe.cpp:501] detection_eval = 0.0542728
-I0511 11:50:55.650458  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.650467  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.650475  5581 caffe.cpp:501] detection_eval = 1.1371
-I0511 11:50:55.650480  5581 caffe.cpp:501] detection_eval = 11.2218
-I0511 11:50:55.650490  5581 caffe.cpp:501] detection_eval = 0.0456568
-I0511 11:50:55.650496  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650503  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.650509  5581 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:50:55.650517  5581 caffe.cpp:501] detection_eval = 11.2581
-I0511 11:50:55.650523  5581 caffe.cpp:501] detection_eval = 0.0453398
-I0511 11:50:55.650532  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650537  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650547  5581 caffe.cpp:501] detection_eval = 1.14113
-I0511 11:50:55.650552  5581 caffe.cpp:501] detection_eval = 11.2661
-I0511 11:50:55.650560  5581 caffe.cpp:501] detection_eval = 0.0411792
-I0511 11:50:55.650569  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.650578  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.650583  5581 caffe.cpp:501] detection_eval = 1.14516
-I0511 11:50:55.650590  5581 caffe.cpp:501] detection_eval = 11.2944
-I0511 11:50:55.650596  5581 caffe.cpp:501] detection_eval = 0.0449004
-I0511 11:50:55.650605  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.650610  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650619  5581 caffe.cpp:501] detection_eval = 1.14919
-I0511 11:50:55.650629  5581 caffe.cpp:501] detection_eval = 11.3004
-I0511 11:50:55.650637  5581 caffe.cpp:501] detection_eval = 0.0497927
-I0511 11:50:55.650642  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.650651  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.650661  5581 caffe.cpp:501] detection_eval = 1.14919
-I0511 11:50:55.650666  5581 caffe.cpp:501] detection_eval = 11.3589
-I0511 11:50:55.650677  5581 caffe.cpp:501] detection_eval = 0.043157
-I0511 11:50:55.650687  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.650698  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.650708  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650719  5581 caffe.cpp:501] detection_eval = 11.3891
-I0511 11:50:55.650730  5581 caffe.cpp:501] detection_eval = 0.0432482
-I0511 11:50:55.650738  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.650748  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.650753  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650761  5581 caffe.cpp:501] detection_eval = 11.4617
-I0511 11:50:55.650768  5581 caffe.cpp:501] detection_eval = 0.0400496
-I0511 11:50:55.650775  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.650781  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.650789  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650794  5581 caffe.cpp:501] detection_eval = 11.5544
-I0511 11:50:55.650799  5581 caffe.cpp:501] detection_eval = 0.0485405
-I0511 11:50:55.650809  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.650817  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.650823  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650831  5581 caffe.cpp:501] detection_eval = 11.623
-I0511 11:50:55.650837  5581 caffe.cpp:501] detection_eval = 0.044955
-I0511 11:50:55.650846  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.650851  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.650859  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650866  5581 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:50:55.650873  5581 caffe.cpp:501] detection_eval = 0.0465296
-I0511 11:50:55.650879  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.650887  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.650893  5581 caffe.cpp:501] detection_eval = 1.15524
-I0511 11:50:55.650902  5581 caffe.cpp:501] detection_eval = 11.744
-I0511 11:50:55.650907  5581 caffe.cpp:501] detection_eval = 0.0429926
-I0511 11:50:55.650915  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.650921  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.650929  5581 caffe.cpp:501] detection_eval = 1.15726
-I0511 11:50:55.650934  5581 caffe.cpp:501] detection_eval = 11.7823
-I0511 11:50:55.650943  5581 caffe.cpp:501] detection_eval = 0.0445645
-I0511 11:50:55.650949  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650957  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650966  5581 caffe.cpp:501] detection_eval = 1.15927
-I0511 11:50:55.650971  5581 caffe.cpp:501] detection_eval = 11.8125
-I0511 11:50:55.650980  5581 caffe.cpp:501] detection_eval = 0.0394349
-I0511 11:50:55.650985  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650996  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.651001  5581 caffe.cpp:501] detection_eval = 1.16331
-I0511 11:50:55.651010  5581 caffe.cpp:501] detection_eval = 11.8286
-I0511 11:50:55.651015  5581 caffe.cpp:501] detection_eval = 0.0394802
-I0511 11:50:55.651023  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.651028  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.651037  5581 caffe.cpp:501] detection_eval = 1.16331
-I0511 11:50:55.651042  5581 caffe.cpp:501] detection_eval = 11.8891
-I0511 11:50:55.651057  5581 caffe.cpp:501] detection_eval = 0.0437617
-I0511 11:50:55.651064  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.651075  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651093  5581 caffe.cpp:501] detection_eval = 1.16331
-I0511 11:50:55.651103  5581 caffe.cpp:501] detection_eval = 11.9395
-I0511 11:50:55.651113  5581 caffe.cpp:501] detection_eval = 0.0452932
-I0511 11:50:55.651118  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651125  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651134  5581 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:50:55.651141  5581 caffe.cpp:501] detection_eval = 11.9859
-I0511 11:50:55.651150  5581 caffe.cpp:501] detection_eval = 0.0494409
-I0511 11:50:55.651156  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651165  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651170  5581 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:50:55.651181  5581 caffe.cpp:501] detection_eval = 12.0726
-I0511 11:50:55.651190  5581 caffe.cpp:501] detection_eval = 0.0507496
-I0511 11:50:55.651201  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651212  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.651219  5581 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:50:55.651232  5581 caffe.cpp:501] detection_eval = 12.1331
-I0511 11:50:55.651237  5581 caffe.cpp:501] detection_eval = 0.046769
-I0511 11:50:55.651247  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651252  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.651262  5581 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:50:55.651268  5581 caffe.cpp:501] detection_eval = 12.2016
-I0511 11:50:55.651279  5581 caffe.cpp:501] detection_eval = 0.0454815
-I0511 11:50:55.651290  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.651301  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.651311  5581 caffe.cpp:501] detection_eval = 1.16935
-I0511 11:50:55.651322  5581 caffe.cpp:501] detection_eval = 12.1774
-I0511 11:50:55.651331  5581 caffe.cpp:501] detection_eval = 0.0420104
-I0511 11:50:55.651345  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651350  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.651358  5581 caffe.cpp:501] detection_eval = 1.17137
-I0511 11:50:55.651367  5581 caffe.cpp:501] detection_eval = 12.2077
-I0511 11:50:55.651372  5581 caffe.cpp:501] detection_eval = 0.0409585
-I0511 11:50:55.651381  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.651387  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.651396  5581 caffe.cpp:501] detection_eval = 1.17339
-I0511 11:50:55.651403  5581 caffe.cpp:501] detection_eval = 12.2641
-I0511 11:50:55.651413  5581 caffe.cpp:501] detection_eval = 0.0436587
-I0511 11:50:55.651424  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.651435  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.651445  5581 caffe.cpp:501] detection_eval = 1.17339
-I0511 11:50:55.651455  5581 caffe.cpp:501] detection_eval = 12.2903
-I0511 11:50:55.651468  5581 caffe.cpp:501] detection_eval = 0.0377398
-I0511 11:50:55.651477  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.651489  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.651499  5581 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:50:55.651510  5581 caffe.cpp:501] detection_eval = 12.3347
-I0511 11:50:55.651520  5581 caffe.cpp:501] detection_eval = 0.0434924
-I0511 11:50:55.651531  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651545  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.651553  5581 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:50:55.651567  5581 caffe.cpp:501] detection_eval = 12.4093
-I0511 11:50:55.651576  5581 caffe.cpp:501] detection_eval = 0.0381849
-I0511 11:50:55.651587  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651598  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.651615  5581 caffe.cpp:501] detection_eval = 1.17742
-I0511 11:50:55.651624  5581 caffe.cpp:501] detection_eval = 12.4637
-I0511 11:50:55.651635  5581 caffe.cpp:501] detection_eval = 0.0420042
-I0511 11:50:55.651645  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.651665  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.651676  5581 caffe.cpp:501] detection_eval = 1.17742
-I0511 11:50:55.651687  5581 caffe.cpp:501] detection_eval = 12.5444
-I0511 11:50:55.651700  5581 caffe.cpp:501] detection_eval = 0.0419976
-I0511 11:50:55.651718  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.651723  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.651733  5581 caffe.cpp:501] detection_eval = 1.17944
-I0511 11:50:55.651738  5581 caffe.cpp:501] detection_eval = 12.5766
-I0511 11:50:55.651749  5581 caffe.cpp:501] detection_eval = 0.0431548
-I0511 11:50:55.651760  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651772  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.651782  5581 caffe.cpp:501] detection_eval = 1.18145
-I0511 11:50:55.651799  5581 caffe.cpp:501] detection_eval = 12.6048
-I0511 11:50:55.651809  5581 caffe.cpp:501] detection_eval = 0.0490637
-I0511 11:50:55.651821  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.651834  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651844  5581 caffe.cpp:501] detection_eval = 1.18347
-I0511 11:50:55.651856  5581 caffe.cpp:501] detection_eval = 12.6532
-I0511 11:50:55.651868  5581 caffe.cpp:501] detection_eval = 0.0482764
-I0511 11:50:55.651880  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651892  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651912  5581 caffe.cpp:501] detection_eval = 1.18347
-I0511 11:50:55.651921  5581 caffe.cpp:501] detection_eval = 12.7319
-I0511 11:50:55.651933  5581 caffe.cpp:501] detection_eval = 0.0433545
-I0511 11:50:55.651945  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651955  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.651967  5581 caffe.cpp:501] detection_eval = 1.1875
-I0511 11:50:55.651974  5581 caffe.cpp:501] detection_eval = 12.7298
-I0511 11:50:55.651983  5581 caffe.cpp:501] detection_eval = 0.047096
-I0511 11:50:55.651988  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651998  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.652007  5581 caffe.cpp:501] detection_eval = 1.1875
-I0511 11:50:55.652019  5581 caffe.cpp:501] detection_eval = 12.7944
-I0511 11:50:55.652029  5581 caffe.cpp:501] detection_eval = 0.0487267
-I0511 11:50:55.652040  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.652051  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.652062  5581 caffe.cpp:501] detection_eval = 1.1875
-I0511 11:50:55.652073  5581 caffe.cpp:501] detection_eval = 12.8387
-I0511 11:50:55.652084  5581 caffe.cpp:501] detection_eval = 0.0468088
-I0511 11:50:55.652096  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.652112  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.652122  5581 caffe.cpp:501] detection_eval = 1.18952
-I0511 11:50:55.652137  5581 caffe.cpp:501] detection_eval = 12.8528
-I0511 11:50:55.652146  5581 caffe.cpp:501] detection_eval = 0.0444437
-I0511 11:50:55.652156  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652161  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652170  5581 caffe.cpp:501] detection_eval = 1.19355
-I0511 11:50:55.652175  5581 caffe.cpp:501] detection_eval = 12.8226
-I0511 11:50:55.652184  5581 caffe.cpp:501] detection_eval = 0.0398538
-I0511 11:50:55.652191  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652200  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652206  5581 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:50:55.652215  5581 caffe.cpp:501] detection_eval = 12.8185
-I0511 11:50:55.652225  5581 caffe.cpp:501] detection_eval = 0.0389354
-I0511 11:50:55.652235  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652245  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652254  5581 caffe.cpp:501] detection_eval = 1.20161
-I0511 11:50:55.652266  5581 caffe.cpp:501] detection_eval = 12.877
-I0511 11:50:55.652277  5581 caffe.cpp:501] detection_eval = 0.0419467
-I0511 11:50:55.652288  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652307  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652318  5581 caffe.cpp:501] detection_eval = 1.20363
-I0511 11:50:55.652329  5581 caffe.cpp:501] detection_eval = 12.9173
-I0511 11:50:55.652340  5581 caffe.cpp:501] detection_eval = 0.0398573
-I0511 11:50:55.652359  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652369  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652380  5581 caffe.cpp:501] detection_eval = 1.20565
-I0511 11:50:55.652391  5581 caffe.cpp:501] detection_eval = 12.9476
-I0511 11:50:55.652402  5581 caffe.cpp:501] detection_eval = 0.0379745
-I0511 11:50:55.652413  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652426  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.652436  5581 caffe.cpp:501] detection_eval = 1.20766
-I0511 11:50:55.652446  5581 caffe.cpp:501] detection_eval = 12.996
-I0511 11:50:55.652452  5581 caffe.cpp:501] detection_eval = 0.0404742
-I0511 11:50:55.652462  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.652467  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.652474  5581 caffe.cpp:501] detection_eval = 1.20766
-I0511 11:50:55.652483  5581 caffe.cpp:501] detection_eval = 13.0887
-I0511 11:50:55.652489  5581 caffe.cpp:501] detection_eval = 0.0445697
-I0511 11:50:55.652498  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652509  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.652514  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652523  5581 caffe.cpp:501] detection_eval = 13.0282
-I0511 11:50:55.652539  5581 caffe.cpp:501] detection_eval = 0.0402824
-I0511 11:50:55.652549  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652557  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652564  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652571  5581 caffe.cpp:501] detection_eval = 13.0927
-I0511 11:50:55.652577  5581 caffe.cpp:501] detection_eval = 0.0440938
-I0511 11:50:55.652585  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652591  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652600  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652606  5581 caffe.cpp:501] detection_eval = 13.1734
-I0511 11:50:55.652614  5581 caffe.cpp:501] detection_eval = 0.0431589
-I0511 11:50:55.652621  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.652628  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.652634  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652642  5581 caffe.cpp:501] detection_eval = 13.2379
-I0511 11:50:55.652652  5581 caffe.cpp:501] detection_eval = 0.0415992
-I0511 11:50:55.652657  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652667  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652671  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652679  5581 caffe.cpp:501] detection_eval = 13.2681
-I0511 11:50:55.652685  5581 caffe.cpp:501] detection_eval = 0.0385722
-I0511 11:50:55.652694  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652699  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652707  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652716  5581 caffe.cpp:501] detection_eval = 13.3226
-I0511 11:50:55.652722  5581 caffe.cpp:501] detection_eval = 0.0384585
-I0511 11:50:55.652730  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.652736  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652745  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652750  5581 caffe.cpp:501] detection_eval = 13.4516
-I0511 11:50:55.652760  5581 caffe.cpp:501] detection_eval = 0.0401032
-I0511 11:50:55.652765  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652773  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.652779  5581 caffe.cpp:501] detection_eval = 1.21976
-I0511 11:50:55.652787  5581 caffe.cpp:501] detection_eval = 13.4133
-I0511 11:50:55.652793  5581 caffe.cpp:501] detection_eval = 0.03765
-I0511 11:50:55.652803  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652813  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.652818  5581 caffe.cpp:501] detection_eval = 1.21976
-I0511 11:50:55.652827  5581 caffe.cpp:501] detection_eval = 13.4778
-I0511 11:50:55.652837  5581 caffe.cpp:501] detection_eval = 0.0384597
-I0511 11:50:55.652842  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652850  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652859  5581 caffe.cpp:501] detection_eval = 1.22379
-I0511 11:50:55.652865  5581 caffe.cpp:501] detection_eval = 13.4879
-I0511 11:50:55.652873  5581 caffe.cpp:501] detection_eval = 0.042613
-I0511 11:50:55.652879  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652889  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652894  5581 caffe.cpp:501] detection_eval = 1.22379
-I0511 11:50:55.652902  5581 caffe.cpp:501] detection_eval = 13.5323
-I0511 11:50:55.652909  5581 caffe.cpp:501] detection_eval = 0.040689
-I0511 11:50:55.652916  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652922  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.652930  5581 caffe.cpp:501] detection_eval = 1.22581
-I0511 11:50:55.652937  5581 caffe.cpp:501] detection_eval = 13.5423
-I0511 11:50:55.652946  5581 caffe.cpp:501] detection_eval = 0.0396034
-I0511 11:50:55.652952  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652956  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652966  5581 caffe.cpp:501] detection_eval = 1.22984
-I0511 11:50:55.652973  5581 caffe.cpp:501] detection_eval = 13.504
-I0511 11:50:55.652979  5581 caffe.cpp:501] detection_eval = 0.039439
-I0511 11:50:55.652987  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.652997  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653005  5581 caffe.cpp:501] detection_eval = 1.23387
-I0511 11:50:55.653010  5581 caffe.cpp:501] detection_eval = 13.506
-I0511 11:50:55.653020  5581 caffe.cpp:501] detection_eval = 0.0414768
-I0511 11:50:55.653025  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.653034  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653039  5581 caffe.cpp:501] detection_eval = 1.23387
-I0511 11:50:55.653048  5581 caffe.cpp:501] detection_eval = 13.5544
-I0511 11:50:55.653055  5581 caffe.cpp:501] detection_eval = 0.0392363
-I0511 11:50:55.653066  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653077  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653087  5581 caffe.cpp:501] detection_eval = 1.23387
-I0511 11:50:55.653095  5581 caffe.cpp:501] detection_eval = 13.5786
-I0511 11:50:55.653106  5581 caffe.cpp:501] detection_eval = 0.034826
-I0511 11:50:55.653116  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653126  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653141  5581 caffe.cpp:501] detection_eval = 1.23992
-I0511 11:50:55.653149  5581 caffe.cpp:501] detection_eval = 13.5202
-I0511 11:50:55.653161  5581 caffe.cpp:501] detection_eval = 0.0353811
-I0511 11:50:55.653172  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653182  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653192  5581 caffe.cpp:501] detection_eval = 1.23992
-I0511 11:50:55.653197  5581 caffe.cpp:501] detection_eval = 13.5464
-I0511 11:50:55.653205  5581 caffe.cpp:501] detection_eval = 0.0334824
-I0511 11:50:55.653211  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.653219  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.653225  5581 caffe.cpp:501] detection_eval = 1.24194
-I0511 11:50:55.653234  5581 caffe.cpp:501] detection_eval = 13.5383
-I0511 11:50:55.653239  5581 caffe.cpp:501] detection_eval = 0.0353618
-I0511 11:50:55.653247  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653254  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653261  5581 caffe.cpp:501] detection_eval = 1.24194
-I0511 11:50:55.653266  5581 caffe.cpp:501] detection_eval = 13.5907
-I0511 11:50:55.653275  5581 caffe.cpp:501] detection_eval = 0.0379702
-I0511 11:50:55.653293  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653304  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.653314  5581 caffe.cpp:501] detection_eval = 1.24194
-I0511 11:50:55.653323  5581 caffe.cpp:501] detection_eval = 13.6169
-I0511 11:50:55.653328  5581 caffe.cpp:501] detection_eval = 0.0366723
-I0511 11:50:55.653337  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653342  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653349  5581 caffe.cpp:501] detection_eval = 1.24395
-I0511 11:50:55.653354  5581 caffe.cpp:501] detection_eval = 13.625
-I0511 11:50:55.653363  5581 caffe.cpp:501] detection_eval = 0.0349927
-I0511 11:50:55.653368  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.653378  5581 caffe.cpp:501] detection_eval = 1
-I0511 11:50:55.653383  5581 caffe.cpp:501] detection_eval = 1.24597
-I0511 11:50:55.653391  5581 caffe.cpp:501] detection_eval = 13.621
-I0511 11:50:55.653400  5581 caffe.cpp:501] detection_eval = 0.0325302
-I0511 11:50:55.653405  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653416  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.653421  5581 caffe.cpp:501] detection_eval = 1.24798
-I0511 11:50:55.653434  5581 caffe.cpp:501] detection_eval = 13.6532
-I0511 11:50:55.653443  5581 caffe.cpp:501] detection_eval = 0.0358958
-I0511 11:50:55.653455  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653471  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653481  5581 caffe.cpp:501] detection_eval = 1.24798
-I0511 11:50:55.653491  5581 caffe.cpp:501] detection_eval = 13.6915
-I0511 11:50:55.653503  5581 caffe.cpp:501] detection_eval = 0.0352341
-I0511 11:50:55.653513  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653518  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653527  5581 caffe.cpp:501] detection_eval = 1.25605
-I0511 11:50:55.653532  5581 caffe.cpp:501] detection_eval = 13.6593
-I0511 11:50:55.653545  5581 caffe.cpp:501] detection_eval = 0.0399494
-I0511 11:50:55.653555  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.653565  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653576  5581 caffe.cpp:501] detection_eval = 1.26613
-I0511 11:50:55.653586  5581 caffe.cpp:501] detection_eval = 13.5544
-I0511 11:50:55.653597  5581 caffe.cpp:501] detection_eval = 0.0439208
-I0511 11:50:55.653609  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.653620  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653630  5581 caffe.cpp:501] detection_eval = 1.26815
-I0511 11:50:55.653641  5581 caffe.cpp:501] detection_eval = 13.5524
-I0511 11:50:55.653652  5581 caffe.cpp:501] detection_eval = 0.0342003
-I0511 11:50:55.653663  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.653672  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.653682  5581 caffe.cpp:501] detection_eval = 1.26815
-I0511 11:50:55.653692  5581 caffe.cpp:501] detection_eval = 13.6069
-I0511 11:50:55.653702  5581 caffe.cpp:501] detection_eval = 0.0357598
-I0511 11:50:55.653712  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653722  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653730  5581 caffe.cpp:501] detection_eval = 1.27419
-I0511 11:50:55.653740  5581 caffe.cpp:501] detection_eval = 13.5847
-I0511 11:50:55.653750  5581 caffe.cpp:501] detection_eval = 0.0395496
-I0511 11:50:55.653760  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.653770  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653779  5581 caffe.cpp:501] detection_eval = 1.27823
-I0511 11:50:55.653789  5581 caffe.cpp:501] detection_eval = 13.5827
-I0511 11:50:55.653800  5581 caffe.cpp:501] detection_eval = 0.0364555
-I0511 11:50:55.653810  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.653820  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.653831  5581 caffe.cpp:501] detection_eval = 1.28024
-I0511 11:50:55.653841  5581 caffe.cpp:501] detection_eval = 13.6008
-I0511 11:50:55.653857  5581 caffe.cpp:501] detection_eval = 0.0366828
-I0511 11:50:55.653867  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.653874  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653883  5581 caffe.cpp:501] detection_eval = 1.28024
-I0511 11:50:55.653890  5581 caffe.cpp:501] detection_eval = 13.621
-I0511 11:50:55.653899  5581 caffe.cpp:501] detection_eval = 0.0368157
-I0511 11:50:55.653908  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653915  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653923  5581 caffe.cpp:501] detection_eval = 1.28024
-I0511 11:50:55.653931  5581 caffe.cpp:501] detection_eval = 13.6714
-I0511 11:50:55.653939  5581 caffe.cpp:501] detection_eval = 0.0372316
-I0511 11:50:55.653944  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.653950  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653959  5581 caffe.cpp:501] detection_eval = 1.28226
-I0511 11:50:55.653965  5581 caffe.cpp:501] detection_eval = 13.6815
-I0511 11:50:55.653973  5581 caffe.cpp:501] detection_eval = 0.0366134
-I0511 11:50:55.653981  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653988  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.653996  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654003  5581 caffe.cpp:501] detection_eval = 13.6815
-I0511 11:50:55.654011  5581 caffe.cpp:501] detection_eval = 0.0336653
-I0511 11:50:55.654021  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654029  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654037  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654044  5581 caffe.cpp:501] detection_eval = 13.7157
-I0511 11:50:55.654052  5581 caffe.cpp:501] detection_eval = 0.0369443
-I0511 11:50:55.654060  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654068  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654076  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654083  5581 caffe.cpp:501] detection_eval = 13.7681
-I0511 11:50:55.654091  5581 caffe.cpp:501] detection_eval = 0.0362468
-I0511 11:50:55.654098  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.654108  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.654114  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654121  5581 caffe.cpp:501] detection_eval = 13.8185
-I0511 11:50:55.654130  5581 caffe.cpp:501] detection_eval = 0.0366433
-I0511 11:50:55.654137  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654145  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654151  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654158  5581 caffe.cpp:501] detection_eval = 13.8972
-I0511 11:50:55.654165  5581 caffe.cpp:501] detection_eval = 0.0377793
-I0511 11:50:55.654172  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.654181  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654187  5581 caffe.cpp:501] detection_eval = 1.28629
-I0511 11:50:55.654196  5581 caffe.cpp:501] detection_eval = 13.9556
-I0511 11:50:55.654203  5581 caffe.cpp:501] detection_eval = 0.037428
-I0511 11:50:55.654211  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654219  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654227  5581 caffe.cpp:501] detection_eval = 1.28831
-I0511 11:50:55.654235  5581 caffe.cpp:501] detection_eval = 14.006
-I0511 11:50:55.654243  5581 caffe.cpp:501] detection_eval = 0.0395422
-I0511 11:50:55.654251  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654258  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654265  5581 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:50:55.654273  5581 caffe.cpp:501] detection_eval = 14
-I0511 11:50:55.654281  5581 caffe.cpp:501] detection_eval = 0.0390295
-I0511 11:50:55.654289  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654297  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654304  5581 caffe.cpp:501] detection_eval = 1.29637
-I0511 11:50:55.654320  5581 caffe.cpp:501] detection_eval = 14
-I0511 11:50:55.654328  5581 caffe.cpp:501] detection_eval = 0.0362773
-I0511 11:50:55.654335  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654343  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654350  5581 caffe.cpp:501] detection_eval = 1.29637
-I0511 11:50:55.654358  5581 caffe.cpp:501] detection_eval = 14.1008
-I0511 11:50:55.654366  5581 caffe.cpp:501] detection_eval = 0.0387912
-I0511 11:50:55.654374  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654382  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654389  5581 caffe.cpp:501] detection_eval = 1.29839
-I0511 11:50:55.654397  5581 caffe.cpp:501] detection_eval = 14.1331
-I0511 11:50:55.654405  5581 caffe.cpp:501] detection_eval = 0.0373136
-I0511 11:50:55.654413  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.654420  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.654428  5581 caffe.cpp:501] detection_eval = 1.3004
-I0511 11:50:55.654433  5581 caffe.cpp:501] detection_eval = 14.1815
-I0511 11:50:55.654439  5581 caffe.cpp:501] detection_eval = 0.0376101
-I0511 11:50:55.654446  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654453  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654460  5581 caffe.cpp:501] detection_eval = 1.30645
-I0511 11:50:55.654465  5581 caffe.cpp:501] detection_eval = 14.1976
-I0511 11:50:55.654474  5581 caffe.cpp:501] detection_eval = 0.0438003
-I0511 11:50:55.654484  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.654491  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.654498  5581 caffe.cpp:501] detection_eval = 1.31048
-I0511 11:50:55.654506  5581 caffe.cpp:501] detection_eval = 14.2238
-I0511 11:50:55.654515  5581 caffe.cpp:501] detection_eval = 0.041372
-I0511 11:50:55.654521  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.654530  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.654537  5581 caffe.cpp:501] detection_eval = 1.3125
-I0511 11:50:55.654546  5581 caffe.cpp:501] detection_eval = 14.2702
-I0511 11:50:55.654552  5581 caffe.cpp:501] detection_eval = 0.0381121
-I0511 11:50:55.654561  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654568  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.654575  5581 caffe.cpp:501] detection_eval = 1.3125
-I0511 11:50:55.654583  5581 caffe.cpp:501] detection_eval = 14.3427
-I0511 11:50:55.654592  5581 caffe.cpp:501] detection_eval = 0.0411211
-I0511 11:50:55.654599  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654606  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.654614  5581 caffe.cpp:501] detection_eval = 1.3125
-I0511 11:50:55.654623  5581 caffe.cpp:501] detection_eval = 14.4194
-I0511 11:50:55.654630  5581 caffe.cpp:501] detection_eval = 0.0381935
-I0511 11:50:55.654637  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654645  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.654652  5581 caffe.cpp:501] detection_eval = 1.31452
-I0511 11:50:55.654661  5581 caffe.cpp:501] detection_eval = 14.496
-I0511 11:50:55.654667  5581 caffe.cpp:501] detection_eval = 0.0416936
-I0511 11:50:55.654672  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.654680  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.654685  5581 caffe.cpp:501] detection_eval = 1.32056
-I0511 11:50:55.654690  5581 caffe.cpp:501] detection_eval = 14.5141
-I0511 11:50:55.654695  5581 caffe.cpp:501] detection_eval = 0.0391074
-I0511 11:50:55.654700  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654703  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654708  5581 caffe.cpp:501] detection_eval = 1.32056
-I0511 11:50:55.654712  5581 caffe.cpp:501] detection_eval = 14.5665
-I0511 11:50:55.654717  5581 caffe.cpp:501] detection_eval = 0.0356851
-I0511 11:50:55.654724  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.654731  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654739  5581 caffe.cpp:501] detection_eval = 1.32056
-I0511 11:50:55.654752  5581 caffe.cpp:501] detection_eval = 14.7419
-I0511 11:50:55.654762  5581 caffe.cpp:501] detection_eval = 0.0367648
-I0511 11:50:55.654769  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.654778  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654785  5581 caffe.cpp:501] detection_eval = 1.32056
-I0511 11:50:55.654793  5581 caffe.cpp:501] detection_eval = 14.9657
-I0511 11:50:55.654800  5581 caffe.cpp:501] detection_eval = 0.0389562
-I0511 11:50:55.654808  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654815  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654824  5581 caffe.cpp:501] detection_eval = 1.3246
-I0511 11:50:55.654831  5581 caffe.cpp:501] detection_eval = 15.1835
-I0511 11:50:55.654839  5581 caffe.cpp:501] detection_eval = 0.0328463
-I0511 11:50:55.654847  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654855  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654862  5581 caffe.cpp:501] detection_eval = 1.32661
-I0511 11:50:55.654870  5581 caffe.cpp:501] detection_eval = 15.5343
-I0511 11:50:55.654878  5581 caffe.cpp:501] detection_eval = 0.0305074
-I0511 11:50:55.654886  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.654893  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654901  5581 caffe.cpp:501] detection_eval = 2.03226
-I0511 11:50:55.654909  5581 caffe.cpp:501] detection_eval = 5.1129
-I0511 11:50:55.654917  5581 caffe.cpp:501] detection_eval = 0.132968
-I0511 11:50:55.654925  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.654933  5581 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:50:55.654940  5581 caffe.cpp:501] detection_eval = 2.03226
-I0511 11:50:55.654948  5581 caffe.cpp:501] detection_eval = 5.41532
-I0511 11:50:55.654958  5581 caffe.cpp:501] detection_eval = 0.0767423
-I0511 11:50:55.654970  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.654974  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.654979  5581 caffe.cpp:501] detection_eval = 2.03226
-I0511 11:50:55.654983  5581 caffe.cpp:501] detection_eval = 5.6371
-I0511 11:50:55.654989  5581 caffe.cpp:501] detection_eval = 0.0650996
-I0511 11:50:55.654992  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.654997  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.655001  5581 caffe.cpp:501] detection_eval = 2.03629
-I0511 11:50:55.655006  5581 caffe.cpp:501] detection_eval = 5.74194
-I0511 11:50:55.655010  5581 caffe.cpp:501] detection_eval = 0.046285
-I0511 11:50:55.655014  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655019  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655023  5581 caffe.cpp:501] detection_eval = 2.03831
-I0511 11:50:55.655028  5581 caffe.cpp:501] detection_eval = 5.83468
-I0511 11:50:55.655032  5581 caffe.cpp:501] detection_eval = 0.0510127
-I0511 11:50:55.655036  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.655041  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.655045  5581 caffe.cpp:501] detection_eval = 2.03831
-I0511 11:50:55.655050  5581 caffe.cpp:501] detection_eval = 6.02621
-I0511 11:50:55.655055  5581 caffe.cpp:501] detection_eval = 0.0508325
-I0511 11:50:55.655059  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.655063  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.655067  5581 caffe.cpp:501] detection_eval = 2.04032
-I0511 11:50:55.655072  5581 caffe.cpp:501] detection_eval = 6.06653
-I0511 11:50:55.655076  5581 caffe.cpp:501] detection_eval = 0.0428764
-I0511 11:50:55.655081  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655086  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655091  5581 caffe.cpp:501] detection_eval = 2.04032
-I0511 11:50:55.655094  5581 caffe.cpp:501] detection_eval = 6.14718
-I0511 11:50:55.655098  5581 caffe.cpp:501] detection_eval = 0.0447347
-I0511 11:50:55.655103  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.655107  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655117  5581 caffe.cpp:501] detection_eval = 2.04234
-I0511 11:50:55.655120  5581 caffe.cpp:501] detection_eval = 6.25
-I0511 11:50:55.655125  5581 caffe.cpp:501] detection_eval = 0.0436314
-I0511 11:50:55.655129  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655134  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.655138  5581 caffe.cpp:501] detection_eval = 2.04839
-I0511 11:50:55.655143  5581 caffe.cpp:501] detection_eval = 6.2621
-I0511 11:50:55.655148  5581 caffe.cpp:501] detection_eval = 0.0444333
-I0511 11:50:55.655153  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655156  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655161  5581 caffe.cpp:501] detection_eval = 2.0504
-I0511 11:50:55.655165  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.655169  5581 caffe.cpp:501] detection_eval = 0.0379169
-I0511 11:50:55.655174  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655179  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655184  5581 caffe.cpp:501] detection_eval = 2.0504
-I0511 11:50:55.655187  5581 caffe.cpp:501] detection_eval = 6.42137
-I0511 11:50:55.655192  5581 caffe.cpp:501] detection_eval = 0.0442222
-I0511 11:50:55.655196  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.655200  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655205  5581 caffe.cpp:501] detection_eval = 2.05444
-I0511 11:50:55.655210  5581 caffe.cpp:501] detection_eval = 6.46371
-I0511 11:50:55.655213  5581 caffe.cpp:501] detection_eval = 0.0433093
-I0511 11:50:55.655218  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.655222  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655227  5581 caffe.cpp:501] detection_eval = 2.05847
-I0511 11:50:55.655231  5581 caffe.cpp:501] detection_eval = 6.52419
-I0511 11:50:55.655236  5581 caffe.cpp:501] detection_eval = 0.0444015
-I0511 11:50:55.655241  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655244  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.655249  5581 caffe.cpp:501] detection_eval = 2.05847
-I0511 11:50:55.655253  5581 caffe.cpp:501] detection_eval = 6.60887
-I0511 11:50:55.655258  5581 caffe.cpp:501] detection_eval = 0.0375061
-I0511 11:50:55.655262  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655267  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.655272  5581 caffe.cpp:501] detection_eval = 2.05847
-I0511 11:50:55.655275  5581 caffe.cpp:501] detection_eval = 6.68347
-I0511 11:50:55.655280  5581 caffe.cpp:501] detection_eval = 0.0366371
-I0511 11:50:55.655284  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.655289  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655293  5581 caffe.cpp:501] detection_eval = 2.06452
-I0511 11:50:55.655297  5581 caffe.cpp:501] detection_eval = 6.6754
-I0511 11:50:55.655303  5581 caffe.cpp:501] detection_eval = 0.0425301
-I0511 11:50:55.655306  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.655311  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655315  5581 caffe.cpp:501] detection_eval = 2.06855
-I0511 11:50:55.655319  5581 caffe.cpp:501] detection_eval = 6.71774
-I0511 11:50:55.655324  5581 caffe.cpp:501] detection_eval = 0.0502925
-I0511 11:50:55.655328  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.655333  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.655338  5581 caffe.cpp:501] detection_eval = 2.07056
-I0511 11:50:55.655341  5581 caffe.cpp:501] detection_eval = 6.74194
-I0511 11:50:55.655346  5581 caffe.cpp:501] detection_eval = 0.0441572
-I0511 11:50:55.655350  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.655355  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.655359  5581 caffe.cpp:501] detection_eval = 2.07258
-I0511 11:50:55.655364  5581 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:50:55.655369  5581 caffe.cpp:501] detection_eval = 0.0410851
-I0511 11:50:55.655372  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655377  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655385  5581 caffe.cpp:501] detection_eval = 2.0746
-I0511 11:50:55.655390  5581 caffe.cpp:501] detection_eval = 6.89315
-I0511 11:50:55.655393  5581 caffe.cpp:501] detection_eval = 0.0467197
-I0511 11:50:55.655398  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.655402  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.655407  5581 caffe.cpp:501] detection_eval = 2.0746
-I0511 11:50:55.655411  5581 caffe.cpp:501] detection_eval = 6.98589
-I0511 11:50:55.655416  5581 caffe.cpp:501] detection_eval = 0.0467414
-I0511 11:50:55.655421  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.655424  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.655429  5581 caffe.cpp:501] detection_eval = 2.07661
-I0511 11:50:55.655433  5581 caffe.cpp:501] detection_eval = 7.03427
-I0511 11:50:55.655437  5581 caffe.cpp:501] detection_eval = 0.0414753
-I0511 11:50:55.655442  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655447  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655452  5581 caffe.cpp:501] detection_eval = 2.08065
-I0511 11:50:55.655455  5581 caffe.cpp:501] detection_eval = 7.05444
-I0511 11:50:55.655460  5581 caffe.cpp:501] detection_eval = 0.0484892
-I0511 11:50:55.655464  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.655468  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.655473  5581 caffe.cpp:501] detection_eval = 2.08468
-I0511 11:50:55.655478  5581 caffe.cpp:501] detection_eval = 7.09677
-I0511 11:50:55.655481  5581 caffe.cpp:501] detection_eval = 0.0469197
-I0511 11:50:55.655486  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.655490  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.655495  5581 caffe.cpp:501] detection_eval = 2.08468
-I0511 11:50:55.655499  5581 caffe.cpp:501] detection_eval = 7.17742
-I0511 11:50:55.655503  5581 caffe.cpp:501] detection_eval = 0.0450967
-I0511 11:50:55.655508  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655513  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.655517  5581 caffe.cpp:501] detection_eval = 2.08871
-I0511 11:50:55.655521  5581 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:50:55.655525  5581 caffe.cpp:501] detection_eval = 0.0410055
-I0511 11:50:55.655530  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.655534  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.655539  5581 caffe.cpp:501] detection_eval = 2.08871
-I0511 11:50:55.655544  5581 caffe.cpp:501] detection_eval = 7.32056
-I0511 11:50:55.655547  5581 caffe.cpp:501] detection_eval = 0.0405258
-I0511 11:50:55.655552  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655556  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655561  5581 caffe.cpp:501] detection_eval = 2.09274
-I0511 11:50:55.655565  5581 caffe.cpp:501] detection_eval = 7.32863
-I0511 11:50:55.655570  5581 caffe.cpp:501] detection_eval = 0.0397538
-I0511 11:50:55.655575  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655578  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655583  5581 caffe.cpp:501] detection_eval = 2.09476
-I0511 11:50:55.655587  5581 caffe.cpp:501] detection_eval = 7.38306
-I0511 11:50:55.655591  5581 caffe.cpp:501] detection_eval = 0.0413817
-I0511 11:50:55.655596  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.655601  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655606  5581 caffe.cpp:501] detection_eval = 2.09879
-I0511 11:50:55.655609  5581 caffe.cpp:501] detection_eval = 7.375
-I0511 11:50:55.655613  5581 caffe.cpp:501] detection_eval = 0.0433942
-I0511 11:50:55.655618  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655622  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.655627  5581 caffe.cpp:501] detection_eval = 2.10081
-I0511 11:50:55.655632  5581 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:50:55.655637  5581 caffe.cpp:501] detection_eval = 0.0413281
-I0511 11:50:55.655640  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655647  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.655652  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655656  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.655661  5581 caffe.cpp:501] detection_eval = 0.0418032
-I0511 11:50:55.655665  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655670  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655674  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655678  5581 caffe.cpp:501] detection_eval = 7.49597
-I0511 11:50:55.655683  5581 caffe.cpp:501] detection_eval = 0.0442379
-I0511 11:50:55.655688  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.655692  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.655696  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655701  5581 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:50:55.655705  5581 caffe.cpp:501] detection_eval = 0.0417567
-I0511 11:50:55.655710  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655714  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655719  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655724  5581 caffe.cpp:501] detection_eval = 7.62903
-I0511 11:50:55.655727  5581 caffe.cpp:501] detection_eval = 0.0417958
-I0511 11:50:55.655732  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655736  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655741  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655745  5581 caffe.cpp:501] detection_eval = 7.67944
-I0511 11:50:55.655750  5581 caffe.cpp:501] detection_eval = 0.0386043
-I0511 11:50:55.655753  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.655758  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.655762  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655767  5581 caffe.cpp:501] detection_eval = 7.75806
-I0511 11:50:55.655771  5581 caffe.cpp:501] detection_eval = 0.0407014
-I0511 11:50:55.655776  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655781  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655784  5581 caffe.cpp:501] detection_eval = 2.10887
-I0511 11:50:55.655789  5581 caffe.cpp:501] detection_eval = 7.73589
-I0511 11:50:55.655793  5581 caffe.cpp:501] detection_eval = 0.0427375
-I0511 11:50:55.655797  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655802  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655807  5581 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:50:55.655810  5581 caffe.cpp:501] detection_eval = 7.79435
-I0511 11:50:55.655815  5581 caffe.cpp:501] detection_eval = 0.0348502
-I0511 11:50:55.655819  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.655824  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.655828  5581 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:50:55.655833  5581 caffe.cpp:501] detection_eval = 7.89718
-I0511 11:50:55.655838  5581 caffe.cpp:501] detection_eval = 0.0354301
-I0511 11:50:55.655841  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.655846  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.655850  5581 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:50:55.655855  5581 caffe.cpp:501] detection_eval = 7.96169
-I0511 11:50:55.655859  5581 caffe.cpp:501] detection_eval = 0.0419408
-I0511 11:50:55.655864  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655869  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.655874  5581 caffe.cpp:501] detection_eval = 2.1129
-I0511 11:50:55.655877  5581 caffe.cpp:501] detection_eval = 8.02823
-I0511 11:50:55.655882  5581 caffe.cpp:501] detection_eval = 0.0383237
-I0511 11:50:55.655886  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655890  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.655895  5581 caffe.cpp:501] detection_eval = 2.11694
-I0511 11:50:55.655900  5581 caffe.cpp:501] detection_eval = 8.05847
-I0511 11:50:55.655905  5581 caffe.cpp:501] detection_eval = 0.0404135
-I0511 11:50:55.655911  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655916  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655920  5581 caffe.cpp:501] detection_eval = 2.11895
-I0511 11:50:55.655925  5581 caffe.cpp:501] detection_eval = 8.10484
-I0511 11:50:55.655930  5581 caffe.cpp:501] detection_eval = 0.0386075
-I0511 11:50:55.655933  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655938  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.655942  5581 caffe.cpp:501] detection_eval = 2.12097
-I0511 11:50:55.655947  5581 caffe.cpp:501] detection_eval = 8.15726
-I0511 11:50:55.655951  5581 caffe.cpp:501] detection_eval = 0.0353515
-I0511 11:50:55.655956  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655961  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.655966  5581 caffe.cpp:501] detection_eval = 2.12097
-I0511 11:50:55.655969  5581 caffe.cpp:501] detection_eval = 8.28427
-I0511 11:50:55.655974  5581 caffe.cpp:501] detection_eval = 0.0456017
-I0511 11:50:55.655978  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.655982  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.655987  5581 caffe.cpp:501] detection_eval = 2.12298
-I0511 11:50:55.655992  5581 caffe.cpp:501] detection_eval = 8.35685
-I0511 11:50:55.655997  5581 caffe.cpp:501] detection_eval = 0.0364799
-I0511 11:50:55.656000  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.656004  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.656009  5581 caffe.cpp:501] detection_eval = 2.12903
-I0511 11:50:55.656013  5581 caffe.cpp:501] detection_eval = 8.36895
-I0511 11:50:55.656018  5581 caffe.cpp:501] detection_eval = 0.0499687
-I0511 11:50:55.656023  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.656026  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656031  5581 caffe.cpp:501] detection_eval = 2.13306
-I0511 11:50:55.656035  5581 caffe.cpp:501] detection_eval = 8.42339
-I0511 11:50:55.656040  5581 caffe.cpp:501] detection_eval = 0.0447311
-I0511 11:50:55.656044  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656049  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656054  5581 caffe.cpp:501] detection_eval = 2.13508
-I0511 11:50:55.656057  5581 caffe.cpp:501] detection_eval = 8.43952
-I0511 11:50:55.656062  5581 caffe.cpp:501] detection_eval = 0.0376752
-I0511 11:50:55.656066  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656071  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.656075  5581 caffe.cpp:501] detection_eval = 2.1371
-I0511 11:50:55.656080  5581 caffe.cpp:501] detection_eval = 8.48185
-I0511 11:50:55.656085  5581 caffe.cpp:501] detection_eval = 0.0475302
-I0511 11:50:55.656090  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.656093  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.656098  5581 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:50:55.656102  5581 caffe.cpp:501] detection_eval = 8.52823
-I0511 11:50:55.656107  5581 caffe.cpp:501] detection_eval = 0.0420878
-I0511 11:50:55.656111  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656116  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656121  5581 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:50:55.656126  5581 caffe.cpp:501] detection_eval = 8.64718
-I0511 11:50:55.656129  5581 caffe.cpp:501] detection_eval = 0.0512985
-I0511 11:50:55.656134  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.656138  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.656143  5581 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:50:55.656147  5581 caffe.cpp:501] detection_eval = 8.7621
-I0511 11:50:55.656152  5581 caffe.cpp:501] detection_eval = 0.0481503
-I0511 11:50:55.656157  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.656162  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656165  5581 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:50:55.656169  5581 caffe.cpp:501] detection_eval = 8.83871
-I0511 11:50:55.656174  5581 caffe.cpp:501] detection_eval = 0.0419182
-I0511 11:50:55.656181  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656186  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656190  5581 caffe.cpp:501] detection_eval = 2.14315
-I0511 11:50:55.656195  5581 caffe.cpp:501] detection_eval = 8.83266
-I0511 11:50:55.656199  5581 caffe.cpp:501] detection_eval = 0.0370229
-I0511 11:50:55.656204  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656208  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.656213  5581 caffe.cpp:501] detection_eval = 2.14315
-I0511 11:50:55.656217  5581 caffe.cpp:501] detection_eval = 8.90726
-I0511 11:50:55.656221  5581 caffe.cpp:501] detection_eval = 0.0399283
-I0511 11:50:55.656226  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656230  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656235  5581 caffe.cpp:501] detection_eval = 2.14516
-I0511 11:50:55.656239  5581 caffe.cpp:501] detection_eval = 8.96371
-I0511 11:50:55.656244  5581 caffe.cpp:501] detection_eval = 0.0429597
-I0511 11:50:55.656249  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656253  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.656257  5581 caffe.cpp:501] detection_eval = 2.14718
-I0511 11:50:55.656261  5581 caffe.cpp:501] detection_eval = 8.99798
-I0511 11:50:55.656266  5581 caffe.cpp:501] detection_eval = 0.0425507
-I0511 11:50:55.656270  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656275  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.656280  5581 caffe.cpp:501] detection_eval = 2.14919
-I0511 11:50:55.656283  5581 caffe.cpp:501] detection_eval = 9.04637
-I0511 11:50:55.656288  5581 caffe.cpp:501] detection_eval = 0.0384549
-I0511 11:50:55.656292  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656297  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656301  5581 caffe.cpp:501] detection_eval = 2.15323
-I0511 11:50:55.656306  5581 caffe.cpp:501] detection_eval = 9.11694
-I0511 11:50:55.656311  5581 caffe.cpp:501] detection_eval = 0.0420552
-I0511 11:50:55.656316  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656319  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656323  5581 caffe.cpp:501] detection_eval = 2.15323
-I0511 11:50:55.656328  5581 caffe.cpp:501] detection_eval = 9.25202
-I0511 11:50:55.656332  5581 caffe.cpp:501] detection_eval = 0.0472095
-I0511 11:50:55.656337  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.656342  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.656345  5581 caffe.cpp:501] detection_eval = 2.15524
-I0511 11:50:55.656350  5581 caffe.cpp:501] detection_eval = 9.32661
-I0511 11:50:55.656354  5581 caffe.cpp:501] detection_eval = 0.0473926
-I0511 11:50:55.656359  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656363  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.656368  5581 caffe.cpp:501] detection_eval = 2.15726
-I0511 11:50:55.656373  5581 caffe.cpp:501] detection_eval = 9.41129
-I0511 11:50:55.656378  5581 caffe.cpp:501] detection_eval = 0.0481998
-I0511 11:50:55.656381  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.656386  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656390  5581 caffe.cpp:501] detection_eval = 2.15927
-I0511 11:50:55.656394  5581 caffe.cpp:501] detection_eval = 9.4496
-I0511 11:50:55.656399  5581 caffe.cpp:501] detection_eval = 0.0434614
-I0511 11:50:55.656404  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.656409  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656412  5581 caffe.cpp:501] detection_eval = 2.15927
-I0511 11:50:55.656417  5581 caffe.cpp:501] detection_eval = 9.5
-I0511 11:50:55.656421  5581 caffe.cpp:501] detection_eval = 0.044086
-I0511 11:50:55.656426  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656430  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656435  5581 caffe.cpp:501] detection_eval = 2.15927
-I0511 11:50:55.656440  5581 caffe.cpp:501] detection_eval = 9.60081
-I0511 11:50:55.656446  5581 caffe.cpp:501] detection_eval = 0.0431457
-I0511 11:50:55.656451  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.656456  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.656461  5581 caffe.cpp:501] detection_eval = 2.15927
-I0511 11:50:55.656464  5581 caffe.cpp:501] detection_eval = 9.6875
-I0511 11:50:55.656469  5581 caffe.cpp:501] detection_eval = 0.0463762
-I0511 11:50:55.656473  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656478  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656483  5581 caffe.cpp:501] detection_eval = 2.16331
-I0511 11:50:55.656487  5581 caffe.cpp:501] detection_eval = 9.72177
-I0511 11:50:55.656491  5581 caffe.cpp:501] detection_eval = 0.0428794
-I0511 11:50:55.656497  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656500  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656505  5581 caffe.cpp:501] detection_eval = 2.16532
-I0511 11:50:55.656509  5581 caffe.cpp:501] detection_eval = 9.79234
-I0511 11:50:55.656514  5581 caffe.cpp:501] detection_eval = 0.0423227
-I0511 11:50:55.656518  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.656523  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656533  5581 caffe.cpp:501] detection_eval = 2.16734
-I0511 11:50:55.656536  5581 caffe.cpp:501] detection_eval = 9.82863
-I0511 11:50:55.656539  5581 caffe.cpp:501] detection_eval = 0.0416507
-I0511 11:50:55.656543  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.656548  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656551  5581 caffe.cpp:501] detection_eval = 2.17137
-I0511 11:50:55.656556  5581 caffe.cpp:501] detection_eval = 9.85484
-I0511 11:50:55.656560  5581 caffe.cpp:501] detection_eval = 0.0412244
-I0511 11:50:55.656565  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656569  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.656574  5581 caffe.cpp:501] detection_eval = 2.17137
-I0511 11:50:55.656579  5581 caffe.cpp:501] detection_eval = 9.92944
-I0511 11:50:55.656584  5581 caffe.cpp:501] detection_eval = 0.0419297
-I0511 11:50:55.656587  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.656592  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656596  5581 caffe.cpp:501] detection_eval = 2.17339
-I0511 11:50:55.656601  5581 caffe.cpp:501] detection_eval = 10.0101
-I0511 11:50:55.656605  5581 caffe.cpp:501] detection_eval = 0.0429888
-I0511 11:50:55.656610  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656615  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656620  5581 caffe.cpp:501] detection_eval = 2.17339
-I0511 11:50:55.656623  5581 caffe.cpp:501] detection_eval = 10.0706
-I0511 11:50:55.656628  5581 caffe.cpp:501] detection_eval = 0.0388895
-I0511 11:50:55.656632  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.656637  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656641  5581 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:50:55.656646  5581 caffe.cpp:501] detection_eval = 10.1411
-I0511 11:50:55.656651  5581 caffe.cpp:501] detection_eval = 0.0401069
-I0511 11:50:55.656656  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656661  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656664  5581 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:50:55.656668  5581 caffe.cpp:501] detection_eval = 10.2177
-I0511 11:50:55.656673  5581 caffe.cpp:501] detection_eval = 0.0438226
-I0511 11:50:55.656678  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.656682  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656687  5581 caffe.cpp:501] detection_eval = 2.17944
-I0511 11:50:55.656692  5581 caffe.cpp:501] detection_eval = 10.3024
-I0511 11:50:55.656695  5581 caffe.cpp:501] detection_eval = 0.0466152
-I0511 11:50:55.656700  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.656704  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656709  5581 caffe.cpp:501] detection_eval = 2.18145
-I0511 11:50:55.656713  5581 caffe.cpp:501] detection_eval = 10.3488
-I0511 11:50:55.656723  5581 caffe.cpp:501] detection_eval = 0.0422544
-I0511 11:50:55.656726  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.656731  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.656736  5581 caffe.cpp:501] detection_eval = 2.18347
-I0511 11:50:55.656740  5581 caffe.cpp:501] detection_eval = 10.377
-I0511 11:50:55.656745  5581 caffe.cpp:501] detection_eval = 0.0389843
-I0511 11:50:55.656749  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656754  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.656759  5581 caffe.cpp:501] detection_eval = 2.18548
-I0511 11:50:55.656764  5581 caffe.cpp:501] detection_eval = 10.4536
-I0511 11:50:55.656767  5581 caffe.cpp:501] detection_eval = 0.0482508
-I0511 11:50:55.656772  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.656776  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.656781  5581 caffe.cpp:501] detection_eval = 2.18952
-I0511 11:50:55.656785  5581 caffe.cpp:501] detection_eval = 10.4819
-I0511 11:50:55.656790  5581 caffe.cpp:501] detection_eval = 0.0443439
-I0511 11:50:55.656795  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656800  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656803  5581 caffe.cpp:501] detection_eval = 2.19355
-I0511 11:50:55.656807  5581 caffe.cpp:501] detection_eval = 10.4879
-I0511 11:50:55.656812  5581 caffe.cpp:501] detection_eval = 0.0382944
-I0511 11:50:55.656816  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656821  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.656826  5581 caffe.cpp:501] detection_eval = 2.19556
-I0511 11:50:55.656831  5581 caffe.cpp:501] detection_eval = 10.5141
-I0511 11:50:55.656834  5581 caffe.cpp:501] detection_eval = 0.0436659
-I0511 11:50:55.656839  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656843  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656848  5581 caffe.cpp:501] detection_eval = 2.19556
-I0511 11:50:55.656852  5581 caffe.cpp:501] detection_eval = 10.5585
-I0511 11:50:55.656857  5581 caffe.cpp:501] detection_eval = 0.0429225
-I0511 11:50:55.656862  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.656867  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.656870  5581 caffe.cpp:501] detection_eval = 2.20161
-I0511 11:50:55.656875  5581 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:50:55.656879  5581 caffe.cpp:501] detection_eval = 0.043948
-I0511 11:50:55.656884  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.656888  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.656893  5581 caffe.cpp:501] detection_eval = 2.20161
-I0511 11:50:55.656898  5581 caffe.cpp:501] detection_eval = 10.627
-I0511 11:50:55.656903  5581 caffe.cpp:501] detection_eval = 0.0418339
-I0511 11:50:55.656908  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.656911  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.656915  5581 caffe.cpp:501] detection_eval = 2.20363
-I0511 11:50:55.656920  5581 caffe.cpp:501] detection_eval = 10.6331
-I0511 11:50:55.656925  5581 caffe.cpp:501] detection_eval = 0.0455964
-I0511 11:50:55.656929  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.656934  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.656939  5581 caffe.cpp:501] detection_eval = 2.20363
-I0511 11:50:55.656942  5581 caffe.cpp:501] detection_eval = 10.6875
-I0511 11:50:55.656947  5581 caffe.cpp:501] detection_eval = 0.0433667
-I0511 11:50:55.656952  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.656956  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656961  5581 caffe.cpp:501] detection_eval = 2.20363
-I0511 11:50:55.656965  5581 caffe.cpp:501] detection_eval = 10.7722
-I0511 11:50:55.656970  5581 caffe.cpp:501] detection_eval = 0.0418561
-I0511 11:50:55.656975  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.656980  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.656985  5581 caffe.cpp:501] detection_eval = 2.20968
-I0511 11:50:55.656991  5581 caffe.cpp:501] detection_eval = 10.8004
-I0511 11:50:55.656996  5581 caffe.cpp:501] detection_eval = 0.0499823
-I0511 11:50:55.657001  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.657006  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657011  5581 caffe.cpp:501] detection_eval = 2.21169
-I0511 11:50:55.657014  5581 caffe.cpp:501] detection_eval = 10.8387
-I0511 11:50:55.657019  5581 caffe.cpp:501] detection_eval = 0.0439527
-I0511 11:50:55.657023  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657028  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657032  5581 caffe.cpp:501] detection_eval = 2.21573
-I0511 11:50:55.657037  5581 caffe.cpp:501] detection_eval = 10.8448
-I0511 11:50:55.657042  5581 caffe.cpp:501] detection_eval = 0.0450626
-I0511 11:50:55.657047  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.657050  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.657055  5581 caffe.cpp:501] detection_eval = 2.21976
-I0511 11:50:55.657059  5581 caffe.cpp:501] detection_eval = 10.871
-I0511 11:50:55.657064  5581 caffe.cpp:501] detection_eval = 0.0397917
-I0511 11:50:55.657068  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657073  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.657078  5581 caffe.cpp:501] detection_eval = 2.22177
-I0511 11:50:55.657083  5581 caffe.cpp:501] detection_eval = 10.9173
-I0511 11:50:55.657088  5581 caffe.cpp:501] detection_eval = 0.0396326
-I0511 11:50:55.657093  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657096  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657101  5581 caffe.cpp:501] detection_eval = 2.22177
-I0511 11:50:55.657105  5581 caffe.cpp:501] detection_eval = 10.9798
-I0511 11:50:55.657110  5581 caffe.cpp:501] detection_eval = 0.0403599
-I0511 11:50:55.657115  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.657119  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657124  5581 caffe.cpp:501] detection_eval = 2.22984
-I0511 11:50:55.657129  5581 caffe.cpp:501] detection_eval = 10.9617
-I0511 11:50:55.657133  5581 caffe.cpp:501] detection_eval = 0.0476307
-I0511 11:50:55.657137  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657142  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657147  5581 caffe.cpp:501] detection_eval = 2.23185
-I0511 11:50:55.657151  5581 caffe.cpp:501] detection_eval = 10.9819
-I0511 11:50:55.657156  5581 caffe.cpp:501] detection_eval = 0.0392576
-I0511 11:50:55.657160  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657166  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657171  5581 caffe.cpp:501] detection_eval = 2.23992
-I0511 11:50:55.657174  5581 caffe.cpp:501] detection_eval = 11.006
-I0511 11:50:55.657179  5581 caffe.cpp:501] detection_eval = 0.0496554
-I0511 11:50:55.657183  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.657188  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.657192  5581 caffe.cpp:501] detection_eval = 2.24597
-I0511 11:50:55.657197  5581 caffe.cpp:501] detection_eval = 10.9476
-I0511 11:50:55.657202  5581 caffe.cpp:501] detection_eval = 0.0398903
-I0511 11:50:55.657207  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657210  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657215  5581 caffe.cpp:501] detection_eval = 2.25
-I0511 11:50:55.657220  5581 caffe.cpp:501] detection_eval = 10.9617
-I0511 11:50:55.657225  5581 caffe.cpp:501] detection_eval = 0.0407143
-I0511 11:50:55.657230  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657234  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657239  5581 caffe.cpp:501] detection_eval = 2.25202
-I0511 11:50:55.657243  5581 caffe.cpp:501] detection_eval = 11.0262
-I0511 11:50:55.657248  5581 caffe.cpp:501] detection_eval = 0.0404579
-I0511 11:50:55.657253  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657258  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.657268  5581 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:50:55.657272  5581 caffe.cpp:501] detection_eval = 11.0585
-I0511 11:50:55.657277  5581 caffe.cpp:501] detection_eval = 0.0486328
-I0511 11:50:55.657282  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.657286  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657291  5581 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:50:55.657296  5581 caffe.cpp:501] detection_eval = 11.1452
-I0511 11:50:55.657301  5581 caffe.cpp:501] detection_eval = 0.0444327
-I0511 11:50:55.657305  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657311  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657315  5581 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:50:55.657320  5581 caffe.cpp:501] detection_eval = 11.1976
-I0511 11:50:55.657325  5581 caffe.cpp:501] detection_eval = 0.0420833
-I0511 11:50:55.657331  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657336  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657341  5581 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:50:55.657344  5581 caffe.cpp:501] detection_eval = 11.2581
-I0511 11:50:55.657349  5581 caffe.cpp:501] detection_eval = 0.0406848
-I0511 11:50:55.657354  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.657359  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657362  5581 caffe.cpp:501] detection_eval = 2.25806
-I0511 11:50:55.657366  5581 caffe.cpp:501] detection_eval = 11.2964
-I0511 11:50:55.657372  5581 caffe.cpp:501] detection_eval = 0.0420972
-I0511 11:50:55.657377  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657382  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657387  5581 caffe.cpp:501] detection_eval = 2.26008
-I0511 11:50:55.657390  5581 caffe.cpp:501] detection_eval = 11.3589
-I0511 11:50:55.657395  5581 caffe.cpp:501] detection_eval = 0.0446766
-I0511 11:50:55.657399  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657404  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657408  5581 caffe.cpp:501] detection_eval = 2.2621
-I0511 11:50:55.657413  5581 caffe.cpp:501] detection_eval = 11.4093
-I0511 11:50:55.657418  5581 caffe.cpp:501] detection_eval = 0.0477488
-I0511 11:50:55.657423  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.657428  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.657433  5581 caffe.cpp:501] detection_eval = 2.26613
-I0511 11:50:55.657436  5581 caffe.cpp:501] detection_eval = 11.4254
-I0511 11:50:55.657441  5581 caffe.cpp:501] detection_eval = 0.0441837
-I0511 11:50:55.657446  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.657450  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657455  5581 caffe.cpp:501] detection_eval = 2.27016
-I0511 11:50:55.657459  5581 caffe.cpp:501] detection_eval = 11.4073
-I0511 11:50:55.657464  5581 caffe.cpp:501] detection_eval = 0.0433764
-I0511 11:50:55.657469  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657474  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657479  5581 caffe.cpp:501] detection_eval = 2.27016
-I0511 11:50:55.657482  5581 caffe.cpp:501] detection_eval = 11.4919
-I0511 11:50:55.657487  5581 caffe.cpp:501] detection_eval = 0.0418392
-I0511 11:50:55.657491  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.657496  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657500  5581 caffe.cpp:501] detection_eval = 2.27016
-I0511 11:50:55.657505  5581 caffe.cpp:501] detection_eval = 11.5464
-I0511 11:50:55.657510  5581 caffe.cpp:501] detection_eval = 0.0392405
-I0511 11:50:55.657515  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.657519  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.657524  5581 caffe.cpp:501] detection_eval = 2.27218
-I0511 11:50:55.657528  5581 caffe.cpp:501] detection_eval = 11.5867
-I0511 11:50:55.657533  5581 caffe.cpp:501] detection_eval = 0.0387267
-I0511 11:50:55.657537  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.657542  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657550  5581 caffe.cpp:501] detection_eval = 2.27218
-I0511 11:50:55.657555  5581 caffe.cpp:501] detection_eval = 11.6351
-I0511 11:50:55.657560  5581 caffe.cpp:501] detection_eval = 0.0385455
-I0511 11:50:55.657564  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.657569  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.657574  5581 caffe.cpp:501] detection_eval = 2.27419
-I0511 11:50:55.657579  5581 caffe.cpp:501] detection_eval = 11.6593
-I0511 11:50:55.657584  5581 caffe.cpp:501] detection_eval = 0.0409101
-I0511 11:50:55.657588  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657593  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.657598  5581 caffe.cpp:501] detection_eval = 2.27419
-I0511 11:50:55.657601  5581 caffe.cpp:501] detection_eval = 11.7036
-I0511 11:50:55.657606  5581 caffe.cpp:501] detection_eval = 0.0402169
-I0511 11:50:55.657611  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657615  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657620  5581 caffe.cpp:501] detection_eval = 2.27823
-I0511 11:50:55.657624  5581 caffe.cpp:501] detection_eval = 11.6875
-I0511 11:50:55.657629  5581 caffe.cpp:501] detection_eval = 0.0424572
-I0511 11:50:55.657634  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657639  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657644  5581 caffe.cpp:501] detection_eval = 2.28024
-I0511 11:50:55.657647  5581 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:50:55.657652  5581 caffe.cpp:501] detection_eval = 0.036214
-I0511 11:50:55.657656  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657661  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657665  5581 caffe.cpp:501] detection_eval = 2.28226
-I0511 11:50:55.657670  5581 caffe.cpp:501] detection_eval = 11.756
-I0511 11:50:55.657675  5581 caffe.cpp:501] detection_eval = 0.0399918
-I0511 11:50:55.657680  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657685  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.657688  5581 caffe.cpp:501] detection_eval = 2.28427
-I0511 11:50:55.657693  5581 caffe.cpp:501] detection_eval = 11.7782
-I0511 11:50:55.657697  5581 caffe.cpp:501] detection_eval = 0.0351907
-I0511 11:50:55.657702  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.657706  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.657711  5581 caffe.cpp:501] detection_eval = 2.28831
-I0511 11:50:55.657716  5581 caffe.cpp:501] detection_eval = 11.8246
-I0511 11:50:55.657721  5581 caffe.cpp:501] detection_eval = 0.0411504
-I0511 11:50:55.657724  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657729  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.657733  5581 caffe.cpp:501] detection_eval = 2.28831
-I0511 11:50:55.657738  5581 caffe.cpp:501] detection_eval = 11.9435
-I0511 11:50:55.657742  5581 caffe.cpp:501] detection_eval = 0.0389682
-I0511 11:50:55.657747  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.657752  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657757  5581 caffe.cpp:501] detection_eval = 2.29234
-I0511 11:50:55.657760  5581 caffe.cpp:501] detection_eval = 11.9274
-I0511 11:50:55.657765  5581 caffe.cpp:501] detection_eval = 0.0338678
-I0511 11:50:55.657769  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657774  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657778  5581 caffe.cpp:501] detection_eval = 2.29234
-I0511 11:50:55.657783  5581 caffe.cpp:501] detection_eval = 12.002
-I0511 11:50:55.657788  5581 caffe.cpp:501] detection_eval = 0.035592
-I0511 11:50:55.657793  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.657796  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.657801  5581 caffe.cpp:501] detection_eval = 2.29435
-I0511 11:50:55.657805  5581 caffe.cpp:501] detection_eval = 12.0464
-I0511 11:50:55.657810  5581 caffe.cpp:501] detection_eval = 0.0399416
-I0511 11:50:55.657815  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657822  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657827  5581 caffe.cpp:501] detection_eval = 2.29839
-I0511 11:50:55.657831  5581 caffe.cpp:501] detection_eval = 12.0484
-I0511 11:50:55.657836  5581 caffe.cpp:501] detection_eval = 0.0391435
-I0511 11:50:55.657840  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657845  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.657850  5581 caffe.cpp:501] detection_eval = 2.30242
-I0511 11:50:55.657855  5581 caffe.cpp:501] detection_eval = 12.0625
-I0511 11:50:55.657860  5581 caffe.cpp:501] detection_eval = 0.0390239
-I0511 11:50:55.657863  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657867  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657872  5581 caffe.cpp:501] detection_eval = 2.30242
-I0511 11:50:55.657876  5581 caffe.cpp:501] detection_eval = 12.2036
-I0511 11:50:55.657881  5581 caffe.cpp:501] detection_eval = 0.0462124
-I0511 11:50:55.657886  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657891  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657894  5581 caffe.cpp:501] detection_eval = 2.30645
-I0511 11:50:55.657899  5581 caffe.cpp:501] detection_eval = 12.2077
-I0511 11:50:55.657904  5581 caffe.cpp:501] detection_eval = 0.046275
-I0511 11:50:55.657908  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.657913  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657917  5581 caffe.cpp:501] detection_eval = 2.30645
-I0511 11:50:55.657922  5581 caffe.cpp:501] detection_eval = 12.2722
-I0511 11:50:55.657927  5581 caffe.cpp:501] detection_eval = 0.0449226
-I0511 11:50:55.657932  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657935  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657940  5581 caffe.cpp:501] detection_eval = 2.30847
-I0511 11:50:55.657944  5581 caffe.cpp:501] detection_eval = 12.3125
-I0511 11:50:55.657949  5581 caffe.cpp:501] detection_eval = 0.0419957
-I0511 11:50:55.657953  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657958  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657963  5581 caffe.cpp:501] detection_eval = 2.3125
-I0511 11:50:55.657966  5581 caffe.cpp:501] detection_eval = 12.3367
-I0511 11:50:55.657971  5581 caffe.cpp:501] detection_eval = 0.0450801
-I0511 11:50:55.657976  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.657980  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.657985  5581 caffe.cpp:501] detection_eval = 2.31653
-I0511 11:50:55.657989  5581 caffe.cpp:501] detection_eval = 12.3306
-I0511 11:50:55.657994  5581 caffe.cpp:501] detection_eval = 0.0447295
-I0511 11:50:55.657999  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658002  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658007  5581 caffe.cpp:501] detection_eval = 2.32258
-I0511 11:50:55.658011  5581 caffe.cpp:501] detection_eval = 12.3629
-I0511 11:50:55.658016  5581 caffe.cpp:501] detection_eval = 0.0393389
-I0511 11:50:55.658021  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658025  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658030  5581 caffe.cpp:501] detection_eval = 2.32661
-I0511 11:50:55.658035  5581 caffe.cpp:501] detection_eval = 12.4032
-I0511 11:50:55.658040  5581 caffe.cpp:501] detection_eval = 0.0446266
-I0511 11:50:55.658043  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.658048  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.658053  5581 caffe.cpp:501] detection_eval = 2.32863
-I0511 11:50:55.658057  5581 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:50:55.658062  5581 caffe.cpp:501] detection_eval = 0.0412649
-I0511 11:50:55.658066  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658071  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658076  5581 caffe.cpp:501] detection_eval = 2.33065
-I0511 11:50:55.658080  5581 caffe.cpp:501] detection_eval = 12.4355
-I0511 11:50:55.658084  5581 caffe.cpp:501] detection_eval = 0.0417905
-I0511 11:50:55.658092  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658097  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658102  5581 caffe.cpp:501] detection_eval = 2.33266
-I0511 11:50:55.658105  5581 caffe.cpp:501] detection_eval = 12.4415
-I0511 11:50:55.658110  5581 caffe.cpp:501] detection_eval = 0.0390862
-I0511 11:50:55.658115  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658119  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658124  5581 caffe.cpp:501] detection_eval = 2.33468
-I0511 11:50:55.658128  5581 caffe.cpp:501] detection_eval = 12.4859
-I0511 11:50:55.658133  5581 caffe.cpp:501] detection_eval = 0.0435713
-I0511 11:50:55.658138  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658143  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658146  5581 caffe.cpp:501] detection_eval = 2.34274
-I0511 11:50:55.658151  5581 caffe.cpp:501] detection_eval = 12.4516
-I0511 11:50:55.658155  5581 caffe.cpp:501] detection_eval = 0.0425151
-I0511 11:50:55.658160  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658164  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658169  5581 caffe.cpp:501] detection_eval = 2.34274
-I0511 11:50:55.658174  5581 caffe.cpp:501] detection_eval = 12.5444
-I0511 11:50:55.658179  5581 caffe.cpp:501] detection_eval = 0.0444467
-I0511 11:50:55.658182  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658186  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658191  5581 caffe.cpp:501] detection_eval = 2.34274
-I0511 11:50:55.658195  5581 caffe.cpp:501] detection_eval = 12.5927
-I0511 11:50:55.658200  5581 caffe.cpp:501] detection_eval = 0.0420531
-I0511 11:50:55.658205  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658210  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658213  5581 caffe.cpp:501] detection_eval = 2.34274
-I0511 11:50:55.658218  5581 caffe.cpp:501] detection_eval = 12.6976
-I0511 11:50:55.658222  5581 caffe.cpp:501] detection_eval = 0.0379126
-I0511 11:50:55.658227  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658231  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658236  5581 caffe.cpp:501] detection_eval = 2.34476
-I0511 11:50:55.658241  5581 caffe.cpp:501] detection_eval = 12.6855
-I0511 11:50:55.658246  5581 caffe.cpp:501] detection_eval = 0.0379459
-I0511 11:50:55.658249  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.658254  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658258  5581 caffe.cpp:501] detection_eval = 2.34476
-I0511 11:50:55.658263  5581 caffe.cpp:501] detection_eval = 12.7359
-I0511 11:50:55.658267  5581 caffe.cpp:501] detection_eval = 0.039052
-I0511 11:50:55.658272  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658277  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658282  5581 caffe.cpp:501] detection_eval = 2.34677
-I0511 11:50:55.658285  5581 caffe.cpp:501] detection_eval = 12.7359
-I0511 11:50:55.658290  5581 caffe.cpp:501] detection_eval = 0.0387269
-I0511 11:50:55.658294  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658299  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658303  5581 caffe.cpp:501] detection_eval = 2.35282
-I0511 11:50:55.658308  5581 caffe.cpp:501] detection_eval = 12.6976
-I0511 11:50:55.658313  5581 caffe.cpp:501] detection_eval = 0.0426419
-I0511 11:50:55.658318  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.658321  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.658325  5581 caffe.cpp:501] detection_eval = 2.35282
-I0511 11:50:55.658330  5581 caffe.cpp:501] detection_eval = 12.7601
-I0511 11:50:55.658335  5581 caffe.cpp:501] detection_eval = 0.0395139
-I0511 11:50:55.658339  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658344  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658349  5581 caffe.cpp:501] detection_eval = 2.35685
-I0511 11:50:55.658352  5581 caffe.cpp:501] detection_eval = 12.7742
-I0511 11:50:55.658357  5581 caffe.cpp:501] detection_eval = 0.0397158
-I0511 11:50:55.658365  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658370  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658373  5581 caffe.cpp:501] detection_eval = 2.36089
-I0511 11:50:55.658378  5581 caffe.cpp:501] detection_eval = 12.8044
-I0511 11:50:55.658383  5581 caffe.cpp:501] detection_eval = 0.04272
-I0511 11:50:55.658387  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658392  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658396  5581 caffe.cpp:501] detection_eval = 2.3629
-I0511 11:50:55.658401  5581 caffe.cpp:501] detection_eval = 12.8992
-I0511 11:50:55.658406  5581 caffe.cpp:501] detection_eval = 0.0471257
-I0511 11:50:55.658411  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658414  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658419  5581 caffe.cpp:501] detection_eval = 2.36694
-I0511 11:50:55.658423  5581 caffe.cpp:501] detection_eval = 12.8952
-I0511 11:50:55.658428  5581 caffe.cpp:501] detection_eval = 0.0426985
-I0511 11:50:55.658432  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658437  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658442  5581 caffe.cpp:501] detection_eval = 2.37702
-I0511 11:50:55.658447  5581 caffe.cpp:501] detection_eval = 12.8185
-I0511 11:50:55.658450  5581 caffe.cpp:501] detection_eval = 0.0428066
-I0511 11:50:55.658455  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.658459  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.658463  5581 caffe.cpp:501] detection_eval = 2.38508
-I0511 11:50:55.658468  5581 caffe.cpp:501] detection_eval = 12.744
-I0511 11:50:55.658473  5581 caffe.cpp:501] detection_eval = 0.0429672
-I0511 11:50:55.658478  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658481  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658486  5581 caffe.cpp:501] detection_eval = 2.38508
-I0511 11:50:55.658490  5581 caffe.cpp:501] detection_eval = 12.7964
-I0511 11:50:55.658495  5581 caffe.cpp:501] detection_eval = 0.0365405
-I0511 11:50:55.658499  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.658504  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.658509  5581 caffe.cpp:501] detection_eval = 2.38911
-I0511 11:50:55.658514  5581 caffe.cpp:501] detection_eval = 12.7641
-I0511 11:50:55.658519  5581 caffe.cpp:501] detection_eval = 0.0361698
-I0511 11:50:55.658522  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.658527  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.658531  5581 caffe.cpp:501] detection_eval = 2.38911
-I0511 11:50:55.658536  5581 caffe.cpp:501] detection_eval = 12.8044
-I0511 11:50:55.658540  5581 caffe.cpp:501] detection_eval = 0.0351099
-I0511 11:50:55.658545  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.658550  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.658555  5581 caffe.cpp:501] detection_eval = 2.39113
-I0511 11:50:55.658558  5581 caffe.cpp:501] detection_eval = 12.8468
-I0511 11:50:55.658563  5581 caffe.cpp:501] detection_eval = 0.0407372
-I0511 11:50:55.658567  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658572  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658577  5581 caffe.cpp:501] detection_eval = 2.39315
-I0511 11:50:55.658581  5581 caffe.cpp:501] detection_eval = 12.881
-I0511 11:50:55.658587  5581 caffe.cpp:501] detection_eval = 0.038156
-I0511 11:50:55.658591  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658597  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658602  5581 caffe.cpp:501] detection_eval = 2.39315
-I0511 11:50:55.658607  5581 caffe.cpp:501] detection_eval = 12.9516
-I0511 11:50:55.658612  5581 caffe.cpp:501] detection_eval = 0.0393703
-I0511 11:50:55.658617  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658620  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658625  5581 caffe.cpp:501] detection_eval = 2.39516
-I0511 11:50:55.658629  5581 caffe.cpp:501] detection_eval = 12.9597
-I0511 11:50:55.658639  5581 caffe.cpp:501] detection_eval = 0.0410465
-I0511 11:50:55.658645  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.658649  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.658654  5581 caffe.cpp:501] detection_eval = 2.39718
-I0511 11:50:55.658658  5581 caffe.cpp:501] detection_eval = 12.9657
-I0511 11:50:55.658663  5581 caffe.cpp:501] detection_eval = 0.0372105
-I0511 11:50:55.658668  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658671  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658676  5581 caffe.cpp:501] detection_eval = 2.39718
-I0511 11:50:55.658680  5581 caffe.cpp:501] detection_eval = 13.0605
-I0511 11:50:55.658685  5581 caffe.cpp:501] detection_eval = 0.0395689
-I0511 11:50:55.658690  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658695  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658699  5581 caffe.cpp:501] detection_eval = 2.40121
-I0511 11:50:55.658704  5581 caffe.cpp:501] detection_eval = 13.0847
-I0511 11:50:55.658710  5581 caffe.cpp:501] detection_eval = 0.0402218
-I0511 11:50:55.658713  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658718  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.658722  5581 caffe.cpp:501] detection_eval = 2.40927
-I0511 11:50:55.658727  5581 caffe.cpp:501] detection_eval = 13.0565
-I0511 11:50:55.658732  5581 caffe.cpp:501] detection_eval = 0.0486767
-I0511 11:50:55.658736  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.658740  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.658746  5581 caffe.cpp:501] detection_eval = 2.41532
-I0511 11:50:55.658749  5581 caffe.cpp:501] detection_eval = 13.0403
-I0511 11:50:55.658754  5581 caffe.cpp:501] detection_eval = 0.0441381
-I0511 11:50:55.658758  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658763  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658767  5581 caffe.cpp:501] detection_eval = 2.41532
-I0511 11:50:55.658772  5581 caffe.cpp:501] detection_eval = 13.0685
-I0511 11:50:55.658777  5581 caffe.cpp:501] detection_eval = 0.0379605
-I0511 11:50:55.658782  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658787  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658790  5581 caffe.cpp:501] detection_eval = 2.41532
-I0511 11:50:55.658795  5581 caffe.cpp:501] detection_eval = 13.119
-I0511 11:50:55.658799  5581 caffe.cpp:501] detection_eval = 0.0366211
-I0511 11:50:55.658804  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658809  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658813  5581 caffe.cpp:501] detection_eval = 2.42137
-I0511 11:50:55.658818  5581 caffe.cpp:501] detection_eval = 13.1169
-I0511 11:50:55.658823  5581 caffe.cpp:501] detection_eval = 0.0412391
-I0511 11:50:55.658828  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658831  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658836  5581 caffe.cpp:501] detection_eval = 2.42742
-I0511 11:50:55.658840  5581 caffe.cpp:501] detection_eval = 13.0766
-I0511 11:50:55.658845  5581 caffe.cpp:501] detection_eval = 0.0404661
-I0511 11:50:55.658849  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658854  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.658859  5581 caffe.cpp:501] detection_eval = 2.42944
-I0511 11:50:55.658862  5581 caffe.cpp:501] detection_eval = 13.0948
-I0511 11:50:55.658867  5581 caffe.cpp:501] detection_eval = 0.0379305
-I0511 11:50:55.658871  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658876  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658880  5581 caffe.cpp:501] detection_eval = 2.43145
-I0511 11:50:55.658885  5581 caffe.cpp:501] detection_eval = 13.1069
-I0511 11:50:55.658890  5581 caffe.cpp:501] detection_eval = 0.033756
-I0511 11:50:55.658895  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.658898  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.658903  5581 caffe.cpp:501] detection_eval = 2.43145
-I0511 11:50:55.658911  5581 caffe.cpp:501] detection_eval = 13.2097
-I0511 11:50:55.658916  5581 caffe.cpp:501] detection_eval = 0.0418653
-I0511 11:50:55.658921  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658926  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658929  5581 caffe.cpp:501] detection_eval = 2.43347
-I0511 11:50:55.658934  5581 caffe.cpp:501] detection_eval = 13.2258
-I0511 11:50:55.658939  5581 caffe.cpp:501] detection_eval = 0.0382543
-I0511 11:50:55.658943  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658948  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.658952  5581 caffe.cpp:501] detection_eval = 2.43548
-I0511 11:50:55.658957  5581 caffe.cpp:501] detection_eval = 13.2601
-I0511 11:50:55.658962  5581 caffe.cpp:501] detection_eval = 0.0409673
-I0511 11:50:55.658967  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658972  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.658977  5581 caffe.cpp:501] detection_eval = 2.43548
-I0511 11:50:55.658980  5581 caffe.cpp:501] detection_eval = 13.3125
-I0511 11:50:55.658985  5581 caffe.cpp:501] detection_eval = 0.0370747
-I0511 11:50:55.658989  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658994  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658998  5581 caffe.cpp:501] detection_eval = 2.4375
-I0511 11:50:55.659003  5581 caffe.cpp:501] detection_eval = 13.3468
-I0511 11:50:55.659008  5581 caffe.cpp:501] detection_eval = 0.0370443
-I0511 11:50:55.659011  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659016  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.659020  5581 caffe.cpp:501] detection_eval = 2.43952
-I0511 11:50:55.659025  5581 caffe.cpp:501] detection_eval = 13.3589
-I0511 11:50:55.659029  5581 caffe.cpp:501] detection_eval = 0.0330922
-I0511 11:50:55.659034  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.659039  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.659044  5581 caffe.cpp:501] detection_eval = 2.43952
-I0511 11:50:55.659047  5581 caffe.cpp:501] detection_eval = 13.3992
-I0511 11:50:55.659052  5581 caffe.cpp:501] detection_eval = 0.0354148
-I0511 11:50:55.659056  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659061  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659065  5581 caffe.cpp:501] detection_eval = 2.44153
-I0511 11:50:55.659070  5581 caffe.cpp:501] detection_eval = 13.4274
-I0511 11:50:55.659075  5581 caffe.cpp:501] detection_eval = 0.0369373
-I0511 11:50:55.659080  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659085  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.659088  5581 caffe.cpp:501] detection_eval = 2.44355
-I0511 11:50:55.659093  5581 caffe.cpp:501] detection_eval = 13.4315
-I0511 11:50:55.659097  5581 caffe.cpp:501] detection_eval = 0.0333409
-I0511 11:50:55.659102  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.659107  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.659111  5581 caffe.cpp:501] detection_eval = 2.44758
-I0511 11:50:55.659116  5581 caffe.cpp:501] detection_eval = 13.4355
-I0511 11:50:55.659121  5581 caffe.cpp:501] detection_eval = 0.0351842
-I0511 11:50:55.659126  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.659129  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.659134  5581 caffe.cpp:501] detection_eval = 2.4496
-I0511 11:50:55.659138  5581 caffe.cpp:501] detection_eval = 13.4597
-I0511 11:50:55.659143  5581 caffe.cpp:501] detection_eval = 0.033905
-I0511 11:50:55.659148  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659152  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659157  5581 caffe.cpp:501] detection_eval = 2.45161
-I0511 11:50:55.659162  5581 caffe.cpp:501] detection_eval = 13.5302
-I0511 11:50:55.659166  5581 caffe.cpp:501] detection_eval = 0.0374625
-I0511 11:50:55.659171  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659175  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.659180  5581 caffe.cpp:501] detection_eval = 2.45363
-I0511 11:50:55.659188  5581 caffe.cpp:501] detection_eval = 13.5645
-I0511 11:50:55.659193  5581 caffe.cpp:501] detection_eval = 0.0368777
-I0511 11:50:55.659198  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659202  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.659207  5581 caffe.cpp:501] detection_eval = 2.45363
-I0511 11:50:55.659211  5581 caffe.cpp:501] detection_eval = 13.629
-I0511 11:50:55.659217  5581 caffe.cpp:501] detection_eval = 0.0410905
-I0511 11:50:55.659221  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659226  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.659230  5581 caffe.cpp:501] detection_eval = 2.45968
-I0511 11:50:55.659235  5581 caffe.cpp:501] detection_eval = 13.6411
-I0511 11:50:55.659240  5581 caffe.cpp:501] detection_eval = 0.0418434
-I0511 11:50:55.659245  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.659248  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.659253  5581 caffe.cpp:501] detection_eval = 2.46573
-I0511 11:50:55.659257  5581 caffe.cpp:501] detection_eval = 13.6532
-I0511 11:50:55.659262  5581 caffe.cpp:501] detection_eval = 0.0353083
-I0511 11:50:55.659266  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659271  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.659276  5581 caffe.cpp:501] detection_eval = 2.46976
-I0511 11:50:55.659281  5581 caffe.cpp:501] detection_eval = 13.7077
-I0511 11:50:55.659284  5581 caffe.cpp:501] detection_eval = 0.0469151
-I0511 11:50:55.659288  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.659293  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.659298  5581 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:50:55.659302  5581 caffe.cpp:501] detection_eval = 13.7742
-I0511 11:50:55.659307  5581 caffe.cpp:501] detection_eval = 0.0435944
-I0511 11:50:55.659312  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659317  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.659320  5581 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:50:55.659324  5581 caffe.cpp:501] detection_eval = 13.881
-I0511 11:50:55.659329  5581 caffe.cpp:501] detection_eval = 0.0363762
-I0511 11:50:55.659334  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.659338  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659343  5581 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:50:55.659348  5581 caffe.cpp:501] detection_eval = 13.9738
-I0511 11:50:55.659353  5581 caffe.cpp:501] detection_eval = 0.0417812
-I0511 11:50:55.659356  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659361  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659365  5581 caffe.cpp:501] detection_eval = 2.47581
-I0511 11:50:55.659370  5581 caffe.cpp:501] detection_eval = 14.0081
-I0511 11:50:55.659375  5581 caffe.cpp:501] detection_eval = 0.0403118
-I0511 11:50:55.659379  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659384  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.659389  5581 caffe.cpp:501] detection_eval = 2.47581
-I0511 11:50:55.659394  5581 caffe.cpp:501] detection_eval = 14.1331
-I0511 11:50:55.659397  5581 caffe.cpp:501] detection_eval = 0.0433493
-I0511 11:50:55.659402  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.659406  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.659411  5581 caffe.cpp:501] detection_eval = 2.47782
-I0511 11:50:55.659415  5581 caffe.cpp:501] detection_eval = 14.3024
-I0511 11:50:55.659420  5581 caffe.cpp:501] detection_eval = 0.0381602
-I0511 11:50:55.659425  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.659430  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.659435  5581 caffe.cpp:501] detection_eval = 2.47984
-I0511 11:50:55.659438  5581 caffe.cpp:501] detection_eval = 14.4335
-I0511 11:50:55.659443  5581 caffe.cpp:501] detection_eval = 0.0360524
-I0511 11:50:55.659448  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.659453  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.659461  5581 caffe.cpp:501] detection_eval = 2.48387
-I0511 11:50:55.659466  5581 caffe.cpp:501] detection_eval = 14.6069
-I0511 11:50:55.659471  5581 caffe.cpp:501] detection_eval = 0.040243
-I0511 11:50:55.659474  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.659479  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659483  5581 caffe.cpp:501] detection_eval = 2.48589
-I0511 11:50:55.659488  5581 caffe.cpp:501] detection_eval = 14.9657
-I0511 11:50:55.659492  5581 caffe.cpp:501] detection_eval = 0.0352473
-I0511 11:50:55.659497  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.659502  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659507  5581 caffe.cpp:501] detection_eval = 3.07056
-I0511 11:50:55.659510  5581 caffe.cpp:501] detection_eval = 6.3004
-I0511 11:50:55.659515  5581 caffe.cpp:501] detection_eval = 0.123152
-I0511 11:50:55.659519  5581 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:50:55.659524  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.659528  5581 caffe.cpp:501] detection_eval = 3.07258
-I0511 11:50:55.659533  5581 caffe.cpp:501] detection_eval = 6.53024
-I0511 11:50:55.659538  5581 caffe.cpp:501] detection_eval = 0.0802531
-I0511 11:50:55.659543  5581 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:50:55.659546  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.659550  5581 caffe.cpp:501] detection_eval = 3.07258
-I0511 11:50:55.659555  5581 caffe.cpp:501] detection_eval = 6.67944
-I0511 11:50:55.659559  5581 caffe.cpp:501] detection_eval = 0.0610168
-I0511 11:50:55.659564  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.659569  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.659574  5581 caffe.cpp:501] detection_eval = 3.07661
-I0511 11:50:55.659577  5581 caffe.cpp:501] detection_eval = 6.79032
-I0511 11:50:55.659581  5581 caffe.cpp:501] detection_eval = 0.0696688
-I0511 11:50:55.659586  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.659590  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.659595  5581 caffe.cpp:501] detection_eval = 3.08065
-I0511 11:50:55.659600  5581 caffe.cpp:501] detection_eval = 6.82661
-I0511 11:50:55.659605  5581 caffe.cpp:501] detection_eval = 0.0640188
-I0511 11:50:55.659608  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.659612  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.659617  5581 caffe.cpp:501] detection_eval = 3.08065
-I0511 11:50:55.659621  5581 caffe.cpp:501] detection_eval = 6.93145
-I0511 11:50:55.659626  5581 caffe.cpp:501] detection_eval = 0.054402
-I0511 11:50:55.659631  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.659636  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.659639  5581 caffe.cpp:501] detection_eval = 3.08266
-I0511 11:50:55.659644  5581 caffe.cpp:501] detection_eval = 6.98992
-I0511 11:50:55.659648  5581 caffe.cpp:501] detection_eval = 0.0485258
-I0511 11:50:55.659652  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.659657  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.659662  5581 caffe.cpp:501] detection_eval = 3.08468
-I0511 11:50:55.659667  5581 caffe.cpp:501] detection_eval = 7.09274
-I0511 11:50:55.659670  5581 caffe.cpp:501] detection_eval = 0.047552
-I0511 11:50:55.659675  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.659679  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.659684  5581 caffe.cpp:501] detection_eval = 3.08468
-I0511 11:50:55.659688  5581 caffe.cpp:501] detection_eval = 7.18952
-I0511 11:50:55.659693  5581 caffe.cpp:501] detection_eval = 0.0483895
-I0511 11:50:55.659698  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.659701  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.659706  5581 caffe.cpp:501] detection_eval = 3.09274
-I0511 11:50:55.659710  5581 caffe.cpp:501] detection_eval = 7.16935
-I0511 11:50:55.659715  5581 caffe.cpp:501] detection_eval = 0.0472736
-I0511 11:50:55.659719  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.659727  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.659732  5581 caffe.cpp:501] detection_eval = 3.09476
-I0511 11:50:55.659736  5581 caffe.cpp:501] detection_eval = 7.1875
-I0511 11:50:55.659741  5581 caffe.cpp:501] detection_eval = 0.0440118
-I0511 11:50:55.659745  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.659750  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659754  5581 caffe.cpp:501] detection_eval = 3.09476
-I0511 11:50:55.659759  5581 caffe.cpp:501] detection_eval = 7.2379
-I0511 11:50:55.659763  5581 caffe.cpp:501] detection_eval = 0.0420377
-I0511 11:50:55.659768  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659772  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659777  5581 caffe.cpp:501] detection_eval = 3.09879
-I0511 11:50:55.659781  5581 caffe.cpp:501] detection_eval = 7.26411
-I0511 11:50:55.659785  5581 caffe.cpp:501] detection_eval = 0.0442456
-I0511 11:50:55.659790  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659795  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659799  5581 caffe.cpp:501] detection_eval = 3.10081
-I0511 11:50:55.659803  5581 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:50:55.659808  5581 caffe.cpp:501] detection_eval = 0.0434348
-I0511 11:50:55.659812  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.659817  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659821  5581 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:50:55.659826  5581 caffe.cpp:501] detection_eval = 7.32258
-I0511 11:50:55.659831  5581 caffe.cpp:501] detection_eval = 0.0425304
-I0511 11:50:55.659835  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659839  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659844  5581 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:50:55.659848  5581 caffe.cpp:501] detection_eval = 7.42944
-I0511 11:50:55.659853  5581 caffe.cpp:501] detection_eval = 0.0481387
-I0511 11:50:55.659857  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.659862  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.659867  5581 caffe.cpp:501] detection_eval = 3.10887
-I0511 11:50:55.659871  5581 caffe.cpp:501] detection_eval = 7.39718
-I0511 11:50:55.659875  5581 caffe.cpp:501] detection_eval = 0.0475778
-I0511 11:50:55.659880  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.659884  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.659889  5581 caffe.cpp:501] detection_eval = 3.11089
-I0511 11:50:55.659893  5581 caffe.cpp:501] detection_eval = 7.44153
-I0511 11:50:55.659898  5581 caffe.cpp:501] detection_eval = 0.0461505
-I0511 11:50:55.659903  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659906  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659911  5581 caffe.cpp:501] detection_eval = 3.1129
-I0511 11:50:55.659915  5581 caffe.cpp:501] detection_eval = 7.50605
-I0511 11:50:55.659919  5581 caffe.cpp:501] detection_eval = 0.0481217
-I0511 11:50:55.659924  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.659929  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.659934  5581 caffe.cpp:501] detection_eval = 3.11492
-I0511 11:50:55.659937  5581 caffe.cpp:501] detection_eval = 7.56855
-I0511 11:50:55.659942  5581 caffe.cpp:501] detection_eval = 0.0483339
-I0511 11:50:55.659946  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.659951  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.659956  5581 caffe.cpp:501] detection_eval = 3.11694
-I0511 11:50:55.659960  5581 caffe.cpp:501] detection_eval = 7.63105
-I0511 11:50:55.659965  5581 caffe.cpp:501] detection_eval = 0.0495814
-I0511 11:50:55.659970  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.659973  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.659978  5581 caffe.cpp:501] detection_eval = 3.11694
-I0511 11:50:55.659982  5581 caffe.cpp:501] detection_eval = 7.70565
-I0511 11:50:55.659986  5581 caffe.cpp:501] detection_eval = 0.0476704
-I0511 11:50:55.659991  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.659998  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.660003  5581 caffe.cpp:501] detection_eval = 3.11895
-I0511 11:50:55.660008  5581 caffe.cpp:501] detection_eval = 7.73185
-I0511 11:50:55.660012  5581 caffe.cpp:501] detection_eval = 0.0407552
-I0511 11:50:55.660017  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.660022  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.660027  5581 caffe.cpp:501] detection_eval = 3.12298
-I0511 11:50:55.660030  5581 caffe.cpp:501] detection_eval = 7.76815
-I0511 11:50:55.660035  5581 caffe.cpp:501] detection_eval = 0.0423516
-I0511 11:50:55.660039  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660044  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660048  5581 caffe.cpp:501] detection_eval = 3.12702
-I0511 11:50:55.660053  5581 caffe.cpp:501] detection_eval = 7.78024
-I0511 11:50:55.660058  5581 caffe.cpp:501] detection_eval = 0.0395827
-I0511 11:50:55.660061  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.660066  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.660070  5581 caffe.cpp:501] detection_eval = 3.12903
-I0511 11:50:55.660075  5581 caffe.cpp:501] detection_eval = 7.82056
-I0511 11:50:55.660079  5581 caffe.cpp:501] detection_eval = 0.0398919
-I0511 11:50:55.660084  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660089  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660092  5581 caffe.cpp:501] detection_eval = 3.13105
-I0511 11:50:55.660097  5581 caffe.cpp:501] detection_eval = 7.86895
-I0511 11:50:55.660101  5581 caffe.cpp:501] detection_eval = 0.0429695
-I0511 11:50:55.660106  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660110  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660115  5581 caffe.cpp:501] detection_eval = 3.13105
-I0511 11:50:55.660120  5581 caffe.cpp:501] detection_eval = 7.9375
-I0511 11:50:55.660125  5581 caffe.cpp:501] detection_eval = 0.039879
-I0511 11:50:55.660128  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660133  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660137  5581 caffe.cpp:501] detection_eval = 3.1371
-I0511 11:50:55.660142  5581 caffe.cpp:501] detection_eval = 7.92339
-I0511 11:50:55.660146  5581 caffe.cpp:501] detection_eval = 0.0446489
-I0511 11:50:55.660151  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660156  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660161  5581 caffe.cpp:501] detection_eval = 3.13911
-I0511 11:50:55.660164  5581 caffe.cpp:501] detection_eval = 7.98387
-I0511 11:50:55.660169  5581 caffe.cpp:501] detection_eval = 0.0406522
-I0511 11:50:55.660173  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660178  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660182  5581 caffe.cpp:501] detection_eval = 3.14113
-I0511 11:50:55.660187  5581 caffe.cpp:501] detection_eval = 8.0504
-I0511 11:50:55.660192  5581 caffe.cpp:501] detection_eval = 0.0431023
-I0511 11:50:55.660195  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.660200  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660204  5581 caffe.cpp:501] detection_eval = 3.14315
-I0511 11:50:55.660209  5581 caffe.cpp:501] detection_eval = 8.11089
-I0511 11:50:55.660213  5581 caffe.cpp:501] detection_eval = 0.0458252
-I0511 11:50:55.660218  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660223  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.660226  5581 caffe.cpp:501] detection_eval = 3.14718
-I0511 11:50:55.660231  5581 caffe.cpp:501] detection_eval = 8.14516
-I0511 11:50:55.660235  5581 caffe.cpp:501] detection_eval = 0.0506663
-I0511 11:50:55.660240  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660244  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.660249  5581 caffe.cpp:501] detection_eval = 3.14919
-I0511 11:50:55.660254  5581 caffe.cpp:501] detection_eval = 8.16129
-I0511 11:50:55.660259  5581 caffe.cpp:501] detection_eval = 0.0450997
-I0511 11:50:55.660266  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.660270  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.660275  5581 caffe.cpp:501] detection_eval = 3.14919
-I0511 11:50:55.660279  5581 caffe.cpp:501] detection_eval = 8.24395
-I0511 11:50:55.660284  5581 caffe.cpp:501] detection_eval = 0.0406565
-I0511 11:50:55.660289  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660293  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660297  5581 caffe.cpp:501] detection_eval = 3.15121
-I0511 11:50:55.660302  5581 caffe.cpp:501] detection_eval = 8.27016
-I0511 11:50:55.660306  5581 caffe.cpp:501] detection_eval = 0.0396103
-I0511 11:50:55.660310  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660315  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660320  5581 caffe.cpp:501] detection_eval = 3.15323
-I0511 11:50:55.660324  5581 caffe.cpp:501] detection_eval = 8.27016
-I0511 11:50:55.660328  5581 caffe.cpp:501] detection_eval = 0.0415813
-I0511 11:50:55.660333  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660337  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660342  5581 caffe.cpp:501] detection_eval = 3.15323
-I0511 11:50:55.660346  5581 caffe.cpp:501] detection_eval = 8.34879
-I0511 11:50:55.660351  5581 caffe.cpp:501] detection_eval = 0.040227
-I0511 11:50:55.660356  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660359  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660363  5581 caffe.cpp:501] detection_eval = 3.15524
-I0511 11:50:55.660368  5581 caffe.cpp:501] detection_eval = 8.40524
-I0511 11:50:55.660372  5581 caffe.cpp:501] detection_eval = 0.043475
-I0511 11:50:55.660377  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.660382  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.660387  5581 caffe.cpp:501] detection_eval = 3.15927
-I0511 11:50:55.660392  5581 caffe.cpp:501] detection_eval = 8.41331
-I0511 11:50:55.660395  5581 caffe.cpp:501] detection_eval = 0.0437719
-I0511 11:50:55.660400  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660404  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.660409  5581 caffe.cpp:501] detection_eval = 3.15927
-I0511 11:50:55.660413  5581 caffe.cpp:501] detection_eval = 8.46169
-I0511 11:50:55.660418  5581 caffe.cpp:501] detection_eval = 0.0393098
-I0511 11:50:55.660423  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660426  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660431  5581 caffe.cpp:501] detection_eval = 3.15927
-I0511 11:50:55.660435  5581 caffe.cpp:501] detection_eval = 8.54637
-I0511 11:50:55.660440  5581 caffe.cpp:501] detection_eval = 0.0413076
-I0511 11:50:55.660444  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.660449  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.660454  5581 caffe.cpp:501] detection_eval = 3.16532
-I0511 11:50:55.660459  5581 caffe.cpp:501] detection_eval = 8.56048
-I0511 11:50:55.660462  5581 caffe.cpp:501] detection_eval = 0.0432862
-I0511 11:50:55.660466  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.660471  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.660475  5581 caffe.cpp:501] detection_eval = 3.16935
-I0511 11:50:55.660480  5581 caffe.cpp:501] detection_eval = 8.56452
-I0511 11:50:55.660485  5581 caffe.cpp:501] detection_eval = 0.0434875
-I0511 11:50:55.660490  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660493  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660498  5581 caffe.cpp:501] detection_eval = 3.17137
-I0511 11:50:55.660502  5581 caffe.cpp:501] detection_eval = 8.63911
-I0511 11:50:55.660507  5581 caffe.cpp:501] detection_eval = 0.0415305
-I0511 11:50:55.660511  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660516  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.660521  5581 caffe.cpp:501] detection_eval = 3.17339
-I0511 11:50:55.660544  5581 caffe.cpp:501] detection_eval = 8.65927
-I0511 11:50:55.660548  5581 caffe.cpp:501] detection_eval = 0.0445828
-I0511 11:50:55.660558  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660563  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660567  5581 caffe.cpp:501] detection_eval = 3.17339
-I0511 11:50:55.660573  5581 caffe.cpp:501] detection_eval = 8.76008
-I0511 11:50:55.660576  5581 caffe.cpp:501] detection_eval = 0.0437319
-I0511 11:50:55.660581  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.660585  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660590  5581 caffe.cpp:501] detection_eval = 3.17742
-I0511 11:50:55.660594  5581 caffe.cpp:501] detection_eval = 8.8125
-I0511 11:50:55.660599  5581 caffe.cpp:501] detection_eval = 0.0456554
-I0511 11:50:55.660604  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.660609  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.660612  5581 caffe.cpp:501] detection_eval = 3.18347
-I0511 11:50:55.660616  5581 caffe.cpp:501] detection_eval = 8.79435
-I0511 11:50:55.660620  5581 caffe.cpp:501] detection_eval = 0.0465603
-I0511 11:50:55.660625  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660629  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.660634  5581 caffe.cpp:501] detection_eval = 3.1875
-I0511 11:50:55.660639  5581 caffe.cpp:501] detection_eval = 8.86089
-I0511 11:50:55.660643  5581 caffe.cpp:501] detection_eval = 0.0500802
-I0511 11:50:55.660647  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.660652  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.660656  5581 caffe.cpp:501] detection_eval = 3.18952
-I0511 11:50:55.660660  5581 caffe.cpp:501] detection_eval = 8.86694
-I0511 11:50:55.660665  5581 caffe.cpp:501] detection_eval = 0.0397763
-I0511 11:50:55.660668  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.660673  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660677  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660682  5581 caffe.cpp:501] detection_eval = 8.93145
-I0511 11:50:55.660687  5581 caffe.cpp:501] detection_eval = 0.0455478
-I0511 11:50:55.660691  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660696  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660701  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660706  5581 caffe.cpp:501] detection_eval = 9.02823
-I0511 11:50:55.660709  5581 caffe.cpp:501] detection_eval = 0.0453798
-I0511 11:50:55.660714  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660718  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.660723  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660727  5581 caffe.cpp:501] detection_eval = 9.10685
-I0511 11:50:55.660732  5581 caffe.cpp:501] detection_eval = 0.0421948
-I0511 11:50:55.660737  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.660742  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660745  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660749  5581 caffe.cpp:501] detection_eval = 9.17137
-I0511 11:50:55.660754  5581 caffe.cpp:501] detection_eval = 0.0399903
-I0511 11:50:55.660759  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660763  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660768  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660773  5581 caffe.cpp:501] detection_eval = 9.23992
-I0511 11:50:55.660778  5581 caffe.cpp:501] detection_eval = 0.0410463
-I0511 11:50:55.660781  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660786  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660790  5581 caffe.cpp:501] detection_eval = 3.19556
-I0511 11:50:55.660794  5581 caffe.cpp:501] detection_eval = 9.28629
-I0511 11:50:55.660799  5581 caffe.cpp:501] detection_eval = 0.0421853
-I0511 11:50:55.660804  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660809  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660814  5581 caffe.cpp:501] detection_eval = 3.1996
-I0511 11:50:55.660817  5581 caffe.cpp:501] detection_eval = 9.33468
-I0511 11:50:55.660826  5581 caffe.cpp:501] detection_eval = 0.0469477
-I0511 11:50:55.660831  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660836  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.660840  5581 caffe.cpp:501] detection_eval = 3.20161
-I0511 11:50:55.660845  5581 caffe.cpp:501] detection_eval = 9.39113
-I0511 11:50:55.660851  5581 caffe.cpp:501] detection_eval = 0.0419991
-I0511 11:50:55.660854  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.660859  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.660863  5581 caffe.cpp:501] detection_eval = 3.20565
-I0511 11:50:55.660868  5581 caffe.cpp:501] detection_eval = 9.41129
-I0511 11:50:55.660872  5581 caffe.cpp:501] detection_eval = 0.0423253
-I0511 11:50:55.660877  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660881  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660887  5581 caffe.cpp:501] detection_eval = 3.20766
-I0511 11:50:55.660892  5581 caffe.cpp:501] detection_eval = 9.46371
-I0511 11:50:55.660895  5581 caffe.cpp:501] detection_eval = 0.0410735
-I0511 11:50:55.660900  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.660904  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660909  5581 caffe.cpp:501] detection_eval = 3.21169
-I0511 11:50:55.660913  5581 caffe.cpp:501] detection_eval = 9.51411
-I0511 11:50:55.660918  5581 caffe.cpp:501] detection_eval = 0.0425367
-I0511 11:50:55.660923  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660926  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660931  5581 caffe.cpp:501] detection_eval = 3.21371
-I0511 11:50:55.660935  5581 caffe.cpp:501] detection_eval = 9.58266
-I0511 11:50:55.660940  5581 caffe.cpp:501] detection_eval = 0.0459977
-I0511 11:50:55.660945  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.660949  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.660953  5581 caffe.cpp:501] detection_eval = 3.21774
-I0511 11:50:55.660959  5581 caffe.cpp:501] detection_eval = 9.63508
-I0511 11:50:55.660962  5581 caffe.cpp:501] detection_eval = 0.039977
-I0511 11:50:55.660967  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.660972  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660976  5581 caffe.cpp:501] detection_eval = 3.21774
-I0511 11:50:55.660981  5581 caffe.cpp:501] detection_eval = 9.71573
-I0511 11:50:55.660985  5581 caffe.cpp:501] detection_eval = 0.0402232
-I0511 11:50:55.660990  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660995  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.661000  5581 caffe.cpp:501] detection_eval = 3.21976
-I0511 11:50:55.661005  5581 caffe.cpp:501] detection_eval = 9.75
-I0511 11:50:55.661008  5581 caffe.cpp:501] detection_eval = 0.0414932
-I0511 11:50:55.661013  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.661017  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661022  5581 caffe.cpp:501] detection_eval = 3.21976
-I0511 11:50:55.661026  5581 caffe.cpp:501] detection_eval = 9.82056
-I0511 11:50:55.661031  5581 caffe.cpp:501] detection_eval = 0.0441414
-I0511 11:50:55.661036  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661041  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661044  5581 caffe.cpp:501] detection_eval = 3.21976
-I0511 11:50:55.661049  5581 caffe.cpp:501] detection_eval = 9.90524
-I0511 11:50:55.661053  5581 caffe.cpp:501] detection_eval = 0.0406413
-I0511 11:50:55.661058  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661062  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661067  5581 caffe.cpp:501] detection_eval = 3.22177
-I0511 11:50:55.661072  5581 caffe.cpp:501] detection_eval = 9.97782
-I0511 11:50:55.661077  5581 caffe.cpp:501] detection_eval = 0.0446964
-I0511 11:50:55.661080  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661085  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661089  5581 caffe.cpp:501] detection_eval = 3.22984
-I0511 11:50:55.661098  5581 caffe.cpp:501] detection_eval = 9.95766
-I0511 11:50:55.661103  5581 caffe.cpp:501] detection_eval = 0.0467316
-I0511 11:50:55.661108  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661113  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.661118  5581 caffe.cpp:501] detection_eval = 3.23185
-I0511 11:50:55.661121  5581 caffe.cpp:501] detection_eval = 9.97581
-I0511 11:50:55.661125  5581 caffe.cpp:501] detection_eval = 0.0449375
-I0511 11:50:55.661130  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661134  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661139  5581 caffe.cpp:501] detection_eval = 3.23387
-I0511 11:50:55.661144  5581 caffe.cpp:501] detection_eval = 10.0202
-I0511 11:50:55.661149  5581 caffe.cpp:501] detection_eval = 0.0404493
-I0511 11:50:55.661154  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661157  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661162  5581 caffe.cpp:501] detection_eval = 3.23992
-I0511 11:50:55.661166  5581 caffe.cpp:501] detection_eval = 10.006
-I0511 11:50:55.661171  5581 caffe.cpp:501] detection_eval = 0.0474648
-I0511 11:50:55.661175  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661180  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.661185  5581 caffe.cpp:501] detection_eval = 3.23992
-I0511 11:50:55.661190  5581 caffe.cpp:501] detection_eval = 10.0766
-I0511 11:50:55.661193  5581 caffe.cpp:501] detection_eval = 0.0429031
-I0511 11:50:55.661198  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661202  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661207  5581 caffe.cpp:501] detection_eval = 3.24395
-I0511 11:50:55.661212  5581 caffe.cpp:501] detection_eval = 10.0746
-I0511 11:50:55.661216  5581 caffe.cpp:501] detection_eval = 0.0419923
-I0511 11:50:55.661221  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661226  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661231  5581 caffe.cpp:501] detection_eval = 3.24597
-I0511 11:50:55.661236  5581 caffe.cpp:501] detection_eval = 10.0948
-I0511 11:50:55.661239  5581 caffe.cpp:501] detection_eval = 0.0425072
-I0511 11:50:55.661244  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661248  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.661253  5581 caffe.cpp:501] detection_eval = 3.25
-I0511 11:50:55.661257  5581 caffe.cpp:501] detection_eval = 10.1532
-I0511 11:50:55.661262  5581 caffe.cpp:501] detection_eval = 0.044023
-I0511 11:50:55.661267  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.661272  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.661276  5581 caffe.cpp:501] detection_eval = 3.25202
-I0511 11:50:55.661280  5581 caffe.cpp:501] detection_eval = 10.2258
-I0511 11:50:55.661285  5581 caffe.cpp:501] detection_eval = 0.0487238
-I0511 11:50:55.661290  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661294  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661299  5581 caffe.cpp:501] detection_eval = 3.25403
-I0511 11:50:55.661303  5581 caffe.cpp:501] detection_eval = 10.2661
-I0511 11:50:55.661309  5581 caffe.cpp:501] detection_eval = 0.0422363
-I0511 11:50:55.661312  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661317  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661321  5581 caffe.cpp:501] detection_eval = 3.25605
-I0511 11:50:55.661326  5581 caffe.cpp:501] detection_eval = 10.2984
-I0511 11:50:55.661330  5581 caffe.cpp:501] detection_eval = 0.0439842
-I0511 11:50:55.661335  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661339  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661345  5581 caffe.cpp:501] detection_eval = 3.25605
-I0511 11:50:55.661348  5581 caffe.cpp:501] detection_eval = 10.3488
-I0511 11:50:55.661353  5581 caffe.cpp:501] detection_eval = 0.0402993
-I0511 11:50:55.661357  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.661362  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661366  5581 caffe.cpp:501] detection_eval = 3.26008
-I0511 11:50:55.661375  5581 caffe.cpp:501] detection_eval = 10.373
-I0511 11:50:55.661379  5581 caffe.cpp:501] detection_eval = 0.0436663
-I0511 11:50:55.661383  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661388  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661392  5581 caffe.cpp:501] detection_eval = 3.26411
-I0511 11:50:55.661397  5581 caffe.cpp:501] detection_eval = 10.3609
-I0511 11:50:55.661401  5581 caffe.cpp:501] detection_eval = 0.0465564
-I0511 11:50:55.661406  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661411  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661415  5581 caffe.cpp:501] detection_eval = 3.26815
-I0511 11:50:55.661420  5581 caffe.cpp:501] detection_eval = 10.3851
-I0511 11:50:55.661424  5581 caffe.cpp:501] detection_eval = 0.0454225
-I0511 11:50:55.661429  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661433  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661438  5581 caffe.cpp:501] detection_eval = 3.27419
-I0511 11:50:55.661442  5581 caffe.cpp:501] detection_eval = 10.3629
-I0511 11:50:55.661448  5581 caffe.cpp:501] detection_eval = 0.040721
-I0511 11:50:55.661451  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.661456  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661461  5581 caffe.cpp:501] detection_eval = 3.27419
-I0511 11:50:55.661465  5581 caffe.cpp:501] detection_eval = 10.4355
-I0511 11:50:55.661469  5581 caffe.cpp:501] detection_eval = 0.0432446
-I0511 11:50:55.661474  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661478  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661484  5581 caffe.cpp:501] detection_eval = 3.28226
-I0511 11:50:55.661487  5581 caffe.cpp:501] detection_eval = 10.3629
-I0511 11:50:55.661492  5581 caffe.cpp:501] detection_eval = 0.0393292
-I0511 11:50:55.661496  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661501  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661505  5581 caffe.cpp:501] detection_eval = 3.28427
-I0511 11:50:55.661509  5581 caffe.cpp:501] detection_eval = 10.4274
-I0511 11:50:55.661514  5581 caffe.cpp:501] detection_eval = 0.0394937
-I0511 11:50:55.661518  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.661523  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661527  5581 caffe.cpp:501] detection_eval = 3.28629
-I0511 11:50:55.661532  5581 caffe.cpp:501] detection_eval = 10.4577
-I0511 11:50:55.661536  5581 caffe.cpp:501] detection_eval = 0.0450987
-I0511 11:50:55.661541  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661545  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661550  5581 caffe.cpp:501] detection_eval = 3.28629
-I0511 11:50:55.661554  5581 caffe.cpp:501] detection_eval = 10.5423
-I0511 11:50:55.661559  5581 caffe.cpp:501] detection_eval = 0.0466144
-I0511 11:50:55.661563  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.661568  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.661573  5581 caffe.cpp:501] detection_eval = 3.28831
-I0511 11:50:55.661577  5581 caffe.cpp:501] detection_eval = 10.5968
-I0511 11:50:55.661582  5581 caffe.cpp:501] detection_eval = 0.0461445
-I0511 11:50:55.661587  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.661592  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.661595  5581 caffe.cpp:501] detection_eval = 3.29234
-I0511 11:50:55.661600  5581 caffe.cpp:501] detection_eval = 10.6069
-I0511 11:50:55.661604  5581 caffe.cpp:501] detection_eval = 0.0418586
-I0511 11:50:55.661609  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661613  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661618  5581 caffe.cpp:501] detection_eval = 3.29435
-I0511 11:50:55.661623  5581 caffe.cpp:501] detection_eval = 10.6452
-I0511 11:50:55.661628  5581 caffe.cpp:501] detection_eval = 0.0422106
-I0511 11:50:55.661631  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.661636  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.661643  5581 caffe.cpp:501] detection_eval = 3.29839
-I0511 11:50:55.661648  5581 caffe.cpp:501] detection_eval = 10.621
-I0511 11:50:55.661653  5581 caffe.cpp:501] detection_eval = 0.0417796
-I0511 11:50:55.661658  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661662  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661666  5581 caffe.cpp:501] detection_eval = 3.30242
-I0511 11:50:55.661671  5581 caffe.cpp:501] detection_eval = 10.6391
-I0511 11:50:55.661675  5581 caffe.cpp:501] detection_eval = 0.0372237
-I0511 11:50:55.661680  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.661685  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661689  5581 caffe.cpp:501] detection_eval = 3.30444
-I0511 11:50:55.661695  5581 caffe.cpp:501] detection_eval = 10.7016
-I0511 11:50:55.661698  5581 caffe.cpp:501] detection_eval = 0.0478853
-I0511 11:50:55.661703  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.661707  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661712  5581 caffe.cpp:501] detection_eval = 3.30645
-I0511 11:50:55.661716  5581 caffe.cpp:501] detection_eval = 10.744
-I0511 11:50:55.661721  5581 caffe.cpp:501] detection_eval = 0.0507787
-I0511 11:50:55.661725  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.661731  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.661734  5581 caffe.cpp:501] detection_eval = 3.31452
-I0511 11:50:55.661739  5581 caffe.cpp:501] detection_eval = 10.6875
-I0511 11:50:55.661743  5581 caffe.cpp:501] detection_eval = 0.0448198
-I0511 11:50:55.661748  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661752  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661756  5581 caffe.cpp:501] detection_eval = 3.31653
-I0511 11:50:55.661761  5581 caffe.cpp:501] detection_eval = 10.7762
-I0511 11:50:55.661767  5581 caffe.cpp:501] detection_eval = 0.0447045
-I0511 11:50:55.661770  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661775  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661779  5581 caffe.cpp:501] detection_eval = 3.3246
-I0511 11:50:55.661784  5581 caffe.cpp:501] detection_eval = 10.7218
-I0511 11:50:55.661788  5581 caffe.cpp:501] detection_eval = 0.0442786
-I0511 11:50:55.661793  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661798  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661803  5581 caffe.cpp:501] detection_eval = 3.33266
-I0511 11:50:55.661806  5581 caffe.cpp:501] detection_eval = 10.6835
-I0511 11:50:55.661811  5581 caffe.cpp:501] detection_eval = 0.0508508
-I0511 11:50:55.661815  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.661820  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.661824  5581 caffe.cpp:501] detection_eval = 3.33669
-I0511 11:50:55.661828  5581 caffe.cpp:501] detection_eval = 10.7278
-I0511 11:50:55.661834  5581 caffe.cpp:501] detection_eval = 0.0502371
-I0511 11:50:55.661839  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.661842  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.661847  5581 caffe.cpp:501] detection_eval = 3.34073
-I0511 11:50:55.661851  5581 caffe.cpp:501] detection_eval = 10.7298
-I0511 11:50:55.661856  5581 caffe.cpp:501] detection_eval = 0.0473864
-I0511 11:50:55.661860  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661865  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661870  5581 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:50:55.661875  5581 caffe.cpp:501] detection_eval = 10.7419
-I0511 11:50:55.661878  5581 caffe.cpp:501] detection_eval = 0.0492456
-I0511 11:50:55.661883  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.661887  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.661892  5581 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:50:55.661896  5581 caffe.cpp:501] detection_eval = 10.7782
-I0511 11:50:55.661901  5581 caffe.cpp:501] detection_eval = 0.0470619
-I0511 11:50:55.661906  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.661912  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.661917  5581 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:50:55.661922  5581 caffe.cpp:501] detection_eval = 10.8327
-I0511 11:50:55.661927  5581 caffe.cpp:501] detection_eval = 0.0473917
-I0511 11:50:55.661931  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661936  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661940  5581 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:50:55.661944  5581 caffe.cpp:501] detection_eval = 10.881
-I0511 11:50:55.661949  5581 caffe.cpp:501] detection_eval = 0.0412994
-I0511 11:50:55.661954  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.661958  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661963  5581 caffe.cpp:501] detection_eval = 3.34677
-I0511 11:50:55.661967  5581 caffe.cpp:501] detection_eval = 10.9073
-I0511 11:50:55.661972  5581 caffe.cpp:501] detection_eval = 0.0389469
-I0511 11:50:55.661976  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.661981  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661985  5581 caffe.cpp:501] detection_eval = 3.34677
-I0511 11:50:55.661990  5581 caffe.cpp:501] detection_eval = 10.9718
-I0511 11:50:55.661994  5581 caffe.cpp:501] detection_eval = 0.0423717
-I0511 11:50:55.661999  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662003  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662009  5581 caffe.cpp:501] detection_eval = 3.34879
-I0511 11:50:55.662012  5581 caffe.cpp:501] detection_eval = 11.0161
-I0511 11:50:55.662017  5581 caffe.cpp:501] detection_eval = 0.0474591
-I0511 11:50:55.662021  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.662026  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.662030  5581 caffe.cpp:501] detection_eval = 3.35282
-I0511 11:50:55.662035  5581 caffe.cpp:501] detection_eval = 10.9899
-I0511 11:50:55.662039  5581 caffe.cpp:501] detection_eval = 0.0420343
-I0511 11:50:55.662045  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.662048  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662053  5581 caffe.cpp:501] detection_eval = 3.35685
-I0511 11:50:55.662057  5581 caffe.cpp:501] detection_eval = 10.9859
-I0511 11:50:55.662062  5581 caffe.cpp:501] detection_eval = 0.0453503
-I0511 11:50:55.662066  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662071  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662075  5581 caffe.cpp:501] detection_eval = 3.35685
-I0511 11:50:55.662081  5581 caffe.cpp:501] detection_eval = 11.0464
-I0511 11:50:55.662084  5581 caffe.cpp:501] detection_eval = 0.0403172
-I0511 11:50:55.662089  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662093  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662098  5581 caffe.cpp:501] detection_eval = 3.35685
-I0511 11:50:55.662102  5581 caffe.cpp:501] detection_eval = 11.1129
-I0511 11:50:55.662107  5581 caffe.cpp:501] detection_eval = 0.0402488
-I0511 11:50:55.662111  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.662117  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.662120  5581 caffe.cpp:501] detection_eval = 3.35887
-I0511 11:50:55.662125  5581 caffe.cpp:501] detection_eval = 11.1855
-I0511 11:50:55.662130  5581 caffe.cpp:501] detection_eval = 0.0435009
-I0511 11:50:55.662134  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.662139  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.662143  5581 caffe.cpp:501] detection_eval = 3.36089
-I0511 11:50:55.662148  5581 caffe.cpp:501] detection_eval = 11.246
-I0511 11:50:55.662153  5581 caffe.cpp:501] detection_eval = 0.0444329
-I0511 11:50:55.662158  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662163  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662168  5581 caffe.cpp:501] detection_eval = 3.3629
-I0511 11:50:55.662171  5581 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:50:55.662176  5581 caffe.cpp:501] detection_eval = 0.0411983
-I0511 11:50:55.662180  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662190  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662195  5581 caffe.cpp:501] detection_eval = 3.3629
-I0511 11:50:55.662199  5581 caffe.cpp:501] detection_eval = 11.3669
-I0511 11:50:55.662204  5581 caffe.cpp:501] detection_eval = 0.0414894
-I0511 11:50:55.662209  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662214  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662217  5581 caffe.cpp:501] detection_eval = 3.36492
-I0511 11:50:55.662222  5581 caffe.cpp:501] detection_eval = 11.4435
-I0511 11:50:55.662226  5581 caffe.cpp:501] detection_eval = 0.04472
-I0511 11:50:55.662231  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662235  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662240  5581 caffe.cpp:501] detection_eval = 3.36492
-I0511 11:50:55.662245  5581 caffe.cpp:501] detection_eval = 11.504
-I0511 11:50:55.662250  5581 caffe.cpp:501] detection_eval = 0.0420281
-I0511 11:50:55.662255  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662258  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662263  5581 caffe.cpp:501] detection_eval = 3.36895
-I0511 11:50:55.662267  5581 caffe.cpp:501] detection_eval = 11.5544
-I0511 11:50:55.662272  5581 caffe.cpp:501] detection_eval = 0.0472357
-I0511 11:50:55.662276  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.662281  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.662286  5581 caffe.cpp:501] detection_eval = 3.37097
-I0511 11:50:55.662289  5581 caffe.cpp:501] detection_eval = 11.6048
-I0511 11:50:55.662294  5581 caffe.cpp:501] detection_eval = 0.0450204
-I0511 11:50:55.662298  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.662303  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.662307  5581 caffe.cpp:501] detection_eval = 3.375
-I0511 11:50:55.662312  5581 caffe.cpp:501] detection_eval = 11.6048
-I0511 11:50:55.662317  5581 caffe.cpp:501] detection_eval = 0.0401472
-I0511 11:50:55.662322  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662326  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662331  5581 caffe.cpp:501] detection_eval = 3.37702
-I0511 11:50:55.662335  5581 caffe.cpp:501] detection_eval = 11.6855
-I0511 11:50:55.662340  5581 caffe.cpp:501] detection_eval = 0.0452125
-I0511 11:50:55.662344  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662349  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662354  5581 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:50:55.662358  5581 caffe.cpp:501] detection_eval = 11.7137
-I0511 11:50:55.662364  5581 caffe.cpp:501] detection_eval = 0.0457496
-I0511 11:50:55.662367  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662372  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662376  5581 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:50:55.662381  5581 caffe.cpp:501] detection_eval = 11.8145
-I0511 11:50:55.662385  5581 caffe.cpp:501] detection_eval = 0.0522002
-I0511 11:50:55.662390  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.662395  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.662400  5581 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:50:55.662403  5581 caffe.cpp:501] detection_eval = 11.9173
-I0511 11:50:55.662408  5581 caffe.cpp:501] detection_eval = 0.0508763
-I0511 11:50:55.662413  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.662417  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.662422  5581 caffe.cpp:501] detection_eval = 3.38306
-I0511 11:50:55.662426  5581 caffe.cpp:501] detection_eval = 11.9819
-I0511 11:50:55.662431  5581 caffe.cpp:501] detection_eval = 0.0544258
-I0511 11:50:55.662436  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.662441  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.662444  5581 caffe.cpp:501] detection_eval = 3.3871
-I0511 11:50:55.662449  5581 caffe.cpp:501] detection_eval = 11.9798
-I0511 11:50:55.662454  5581 caffe.cpp:501] detection_eval = 0.0399811
-I0511 11:50:55.662464  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662470  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662474  5581 caffe.cpp:501] detection_eval = 3.3871
-I0511 11:50:55.662479  5581 caffe.cpp:501] detection_eval = 12.0625
-I0511 11:50:55.662483  5581 caffe.cpp:501] detection_eval = 0.0451576
-I0511 11:50:55.662488  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662493  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662497  5581 caffe.cpp:501] detection_eval = 3.39113
-I0511 11:50:55.662501  5581 caffe.cpp:501] detection_eval = 12.0847
-I0511 11:50:55.662506  5581 caffe.cpp:501] detection_eval = 0.0407882
-I0511 11:50:55.662510  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.662515  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662520  5581 caffe.cpp:501] detection_eval = 3.39113
-I0511 11:50:55.662524  5581 caffe.cpp:501] detection_eval = 12.125
-I0511 11:50:55.662529  5581 caffe.cpp:501] detection_eval = 0.0444575
-I0511 11:50:55.662533  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662539  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662544  5581 caffe.cpp:501] detection_eval = 3.39315
-I0511 11:50:55.662547  5581 caffe.cpp:501] detection_eval = 12.1411
-I0511 11:50:55.662552  5581 caffe.cpp:501] detection_eval = 0.038277
-I0511 11:50:55.662557  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662561  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662565  5581 caffe.cpp:501] detection_eval = 3.39718
-I0511 11:50:55.662570  5581 caffe.cpp:501] detection_eval = 12.1331
-I0511 11:50:55.662575  5581 caffe.cpp:501] detection_eval = 0.0387226
-I0511 11:50:55.662580  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.662583  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.662588  5581 caffe.cpp:501] detection_eval = 3.40323
-I0511 11:50:55.662592  5581 caffe.cpp:501] detection_eval = 12.1048
-I0511 11:50:55.662597  5581 caffe.cpp:501] detection_eval = 0.039161
-I0511 11:50:55.662601  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662606  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.662611  5581 caffe.cpp:501] detection_eval = 3.40524
-I0511 11:50:55.662616  5581 caffe.cpp:501] detection_eval = 12.1573
-I0511 11:50:55.662619  5581 caffe.cpp:501] detection_eval = 0.0400443
-I0511 11:50:55.662624  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662628  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662633  5581 caffe.cpp:501] detection_eval = 3.40726
-I0511 11:50:55.662637  5581 caffe.cpp:501] detection_eval = 12.1956
-I0511 11:50:55.662642  5581 caffe.cpp:501] detection_eval = 0.0410004
-I0511 11:50:55.662647  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662652  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662657  5581 caffe.cpp:501] detection_eval = 3.40927
-I0511 11:50:55.662660  5581 caffe.cpp:501] detection_eval = 12.2077
-I0511 11:50:55.662665  5581 caffe.cpp:501] detection_eval = 0.0385639
-I0511 11:50:55.662670  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.662674  5581 caffe.cpp:501] detection_eval = 1
-I0511 11:50:55.662679  5581 caffe.cpp:501] detection_eval = 3.41129
-I0511 11:50:55.662684  5581 caffe.cpp:501] detection_eval = 12.2339
-I0511 11:50:55.662688  5581 caffe.cpp:501] detection_eval = 0.0432004
-I0511 11:50:55.662693  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662698  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662703  5581 caffe.cpp:501] detection_eval = 3.41331
-I0511 11:50:55.662706  5581 caffe.cpp:501] detection_eval = 12.2944
-I0511 11:50:55.662711  5581 caffe.cpp:501] detection_eval = 0.0436488
-I0511 11:50:55.662715  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662720  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662724  5581 caffe.cpp:501] detection_eval = 3.41734
-I0511 11:50:55.662729  5581 caffe.cpp:501] detection_eval = 12.3226
-I0511 11:50:55.662734  5581 caffe.cpp:501] detection_eval = 0.0417765
-I0511 11:50:55.662741  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662746  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662751  5581 caffe.cpp:501] detection_eval = 3.4254
-I0511 11:50:55.662755  5581 caffe.cpp:501] detection_eval = 12.2258
-I0511 11:50:55.662760  5581 caffe.cpp:501] detection_eval = 0.0403891
-I0511 11:50:55.662765  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662770  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662773  5581 caffe.cpp:501] detection_eval = 3.4254
-I0511 11:50:55.662777  5581 caffe.cpp:501] detection_eval = 12.2681
-I0511 11:50:55.662782  5581 caffe.cpp:501] detection_eval = 0.0386823
-I0511 11:50:55.662787  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662791  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662796  5581 caffe.cpp:501] detection_eval = 3.4254
-I0511 11:50:55.662801  5581 caffe.cpp:501] detection_eval = 12.2964
-I0511 11:50:55.662806  5581 caffe.cpp:501] detection_eval = 0.0396935
-I0511 11:50:55.662809  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662814  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662819  5581 caffe.cpp:501] detection_eval = 3.4254
-I0511 11:50:55.662823  5581 caffe.cpp:501] detection_eval = 12.3649
-I0511 11:50:55.662828  5581 caffe.cpp:501] detection_eval = 0.0426829
-I0511 11:50:55.662832  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662837  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.662842  5581 caffe.cpp:501] detection_eval = 3.42742
-I0511 11:50:55.662845  5581 caffe.cpp:501] detection_eval = 12.4294
-I0511 11:50:55.662850  5581 caffe.cpp:501] detection_eval = 0.0410268
-I0511 11:50:55.662855  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662860  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662864  5581 caffe.cpp:501] detection_eval = 3.42742
-I0511 11:50:55.662868  5581 caffe.cpp:501] detection_eval = 12.502
-I0511 11:50:55.662873  5581 caffe.cpp:501] detection_eval = 0.041119
-I0511 11:50:55.662878  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662883  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662888  5581 caffe.cpp:501] detection_eval = 3.43145
-I0511 11:50:55.662891  5581 caffe.cpp:501] detection_eval = 12.5645
-I0511 11:50:55.662896  5581 caffe.cpp:501] detection_eval = 0.0471057
-I0511 11:50:55.662901  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662905  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.662911  5581 caffe.cpp:501] detection_eval = 3.43548
-I0511 11:50:55.662915  5581 caffe.cpp:501] detection_eval = 12.5948
-I0511 11:50:55.662920  5581 caffe.cpp:501] detection_eval = 0.0487928
-I0511 11:50:55.662925  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.662930  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.662933  5581 caffe.cpp:501] detection_eval = 3.4375
-I0511 11:50:55.662938  5581 caffe.cpp:501] detection_eval = 12.6331
-I0511 11:50:55.662943  5581 caffe.cpp:501] detection_eval = 0.0462303
-I0511 11:50:55.662948  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662952  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.662957  5581 caffe.cpp:501] detection_eval = 3.43952
-I0511 11:50:55.662961  5581 caffe.cpp:501] detection_eval = 12.6593
-I0511 11:50:55.662966  5581 caffe.cpp:501] detection_eval = 0.0423336
-I0511 11:50:55.662971  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662976  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662979  5581 caffe.cpp:501] detection_eval = 3.44556
-I0511 11:50:55.662983  5581 caffe.cpp:501] detection_eval = 12.631
-I0511 11:50:55.662988  5581 caffe.cpp:501] detection_eval = 0.0434904
-I0511 11:50:55.662993  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662997  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.663002  5581 caffe.cpp:501] detection_eval = 3.4496
-I0511 11:50:55.663007  5581 caffe.cpp:501] detection_eval = 12.6331
-I0511 11:50:55.663014  5581 caffe.cpp:501] detection_eval = 0.0369244
-I0511 11:50:55.663018  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663023  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663028  5581 caffe.cpp:501] detection_eval = 3.45363
-I0511 11:50:55.663033  5581 caffe.cpp:501] detection_eval = 12.6411
-I0511 11:50:55.663038  5581 caffe.cpp:501] detection_eval = 0.0398743
-I0511 11:50:55.663041  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663046  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.663050  5581 caffe.cpp:501] detection_eval = 3.46169
-I0511 11:50:55.663054  5581 caffe.cpp:501] detection_eval = 12.5726
-I0511 11:50:55.663059  5581 caffe.cpp:501] detection_eval = 0.0438739
-I0511 11:50:55.663064  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.663069  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.663072  5581 caffe.cpp:501] detection_eval = 3.46976
-I0511 11:50:55.663077  5581 caffe.cpp:501] detection_eval = 12.5161
-I0511 11:50:55.663082  5581 caffe.cpp:501] detection_eval = 0.0385053
-I0511 11:50:55.663086  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663091  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.663095  5581 caffe.cpp:501] detection_eval = 3.46976
-I0511 11:50:55.663100  5581 caffe.cpp:501] detection_eval = 12.5706
-I0511 11:50:55.663105  5581 caffe.cpp:501] detection_eval = 0.0371973
-I0511 11:50:55.663108  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663113  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663117  5581 caffe.cpp:501] detection_eval = 3.47177
-I0511 11:50:55.663121  5581 caffe.cpp:501] detection_eval = 12.5786
-I0511 11:50:55.663126  5581 caffe.cpp:501] detection_eval = 0.037234
-I0511 11:50:55.663130  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663136  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.663139  5581 caffe.cpp:501] detection_eval = 3.47177
-I0511 11:50:55.663144  5581 caffe.cpp:501] detection_eval = 12.6129
-I0511 11:50:55.663148  5581 caffe.cpp:501] detection_eval = 0.0371231
-I0511 11:50:55.663153  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663157  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663162  5581 caffe.cpp:501] detection_eval = 3.47581
-I0511 11:50:55.663166  5581 caffe.cpp:501] detection_eval = 12.5867
-I0511 11:50:55.663172  5581 caffe.cpp:501] detection_eval = 0.0363783
-I0511 11:50:55.663175  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663180  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663184  5581 caffe.cpp:501] detection_eval = 3.47581
-I0511 11:50:55.663189  5581 caffe.cpp:501] detection_eval = 12.6411
-I0511 11:50:55.663193  5581 caffe.cpp:501] detection_eval = 0.0411364
-I0511 11:50:55.663198  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663203  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.663208  5581 caffe.cpp:501] detection_eval = 3.47782
-I0511 11:50:55.663211  5581 caffe.cpp:501] detection_eval = 12.7056
-I0511 11:50:55.663216  5581 caffe.cpp:501] detection_eval = 0.0376425
-I0511 11:50:55.663221  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663225  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663230  5581 caffe.cpp:501] detection_eval = 3.47984
-I0511 11:50:55.663235  5581 caffe.cpp:501] detection_eval = 12.7177
-I0511 11:50:55.663239  5581 caffe.cpp:501] detection_eval = 0.0359646
-I0511 11:50:55.663244  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663249  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663254  5581 caffe.cpp:501] detection_eval = 3.48589
-I0511 11:50:55.663259  5581 caffe.cpp:501] detection_eval = 12.6754
-I0511 11:50:55.663262  5581 caffe.cpp:501] detection_eval = 0.0359471
-I0511 11:50:55.663267  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.663271  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.663276  5581 caffe.cpp:501] detection_eval = 3.48589
-I0511 11:50:55.663280  5581 caffe.cpp:501] detection_eval = 12.7238
-I0511 11:50:55.663288  5581 caffe.cpp:501] detection_eval = 0.0384166
-I0511 11:50:55.663293  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663298  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663303  5581 caffe.cpp:501] detection_eval = 3.48992
-I0511 11:50:55.663307  5581 caffe.cpp:501] detection_eval = 12.7157
-I0511 11:50:55.663312  5581 caffe.cpp:501] detection_eval = 0.0378033
-I0511 11:50:55.663316  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663321  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663326  5581 caffe.cpp:501] detection_eval = 3.49597
-I0511 11:50:55.663331  5581 caffe.cpp:501] detection_eval = 12.6472
-I0511 11:50:55.663336  5581 caffe.cpp:501] detection_eval = 0.0381147
-I0511 11:50:55.663339  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.663344  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.663348  5581 caffe.cpp:501] detection_eval = 3.5
-I0511 11:50:55.663353  5581 caffe.cpp:501] detection_eval = 12.6593
-I0511 11:50:55.663358  5581 caffe.cpp:501] detection_eval = 0.033748
-I0511 11:50:55.663362  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663367  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663372  5581 caffe.cpp:501] detection_eval = 3.5
-I0511 11:50:55.663377  5581 caffe.cpp:501] detection_eval = 12.6895
-I0511 11:50:55.663380  5581 caffe.cpp:501] detection_eval = 0.0337718
-I0511 11:50:55.663385  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663389  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663393  5581 caffe.cpp:501] detection_eval = 3.5
-I0511 11:50:55.663398  5581 caffe.cpp:501] detection_eval = 12.746
-I0511 11:50:55.663403  5581 caffe.cpp:501] detection_eval = 0.0341012
-I0511 11:50:55.663408  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663413  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663416  5581 caffe.cpp:501] detection_eval = 3.50605
-I0511 11:50:55.663421  5581 caffe.cpp:501] detection_eval = 12.7782
-I0511 11:50:55.663425  5581 caffe.cpp:501] detection_eval = 0.0367891
-I0511 11:50:55.663430  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663434  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663439  5581 caffe.cpp:501] detection_eval = 3.51008
-I0511 11:50:55.663444  5581 caffe.cpp:501] detection_eval = 12.7601
-I0511 11:50:55.663450  5581 caffe.cpp:501] detection_eval = 0.0369924
-I0511 11:50:55.663453  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.663458  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663462  5581 caffe.cpp:501] detection_eval = 3.51411
-I0511 11:50:55.663468  5581 caffe.cpp:501] detection_eval = 12.752
-I0511 11:50:55.663473  5581 caffe.cpp:501] detection_eval = 0.0390217
-I0511 11:50:55.663477  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.663481  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.663486  5581 caffe.cpp:501] detection_eval = 3.51613
-I0511 11:50:55.663491  5581 caffe.cpp:501] detection_eval = 12.8407
-I0511 11:50:55.663496  5581 caffe.cpp:501] detection_eval = 0.0383866
-I0511 11:50:55.663501  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663506  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663509  5581 caffe.cpp:501] detection_eval = 3.51815
-I0511 11:50:55.663514  5581 caffe.cpp:501] detection_eval = 12.8548
-I0511 11:50:55.663518  5581 caffe.cpp:501] detection_eval = 0.042047
-I0511 11:50:55.663523  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663527  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.663532  5581 caffe.cpp:501] detection_eval = 3.52016
-I0511 11:50:55.663537  5581 caffe.cpp:501] detection_eval = 12.881
-I0511 11:50:55.663542  5581 caffe.cpp:501] detection_eval = 0.0372107
-I0511 11:50:55.663545  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663550  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663555  5581 caffe.cpp:501] detection_eval = 3.52218
-I0511 11:50:55.663563  5581 caffe.cpp:501] detection_eval = 12.8931
-I0511 11:50:55.663568  5581 caffe.cpp:501] detection_eval = 0.0364517
-I0511 11:50:55.663573  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663576  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663581  5581 caffe.cpp:501] detection_eval = 3.52218
-I0511 11:50:55.663585  5581 caffe.cpp:501] detection_eval = 12.9657
-I0511 11:50:55.663590  5581 caffe.cpp:501] detection_eval = 0.0351007
-I0511 11:50:55.663594  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.663599  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.663604  5581 caffe.cpp:501] detection_eval = 3.52621
-I0511 11:50:55.663609  5581 caffe.cpp:501] detection_eval = 12.9556
-I0511 11:50:55.663614  5581 caffe.cpp:501] detection_eval = 0.0346564
-I0511 11:50:55.663619  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663622  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663627  5581 caffe.cpp:501] detection_eval = 3.52823
-I0511 11:50:55.663631  5581 caffe.cpp:501] detection_eval = 12.9899
-I0511 11:50:55.663636  5581 caffe.cpp:501] detection_eval = 0.0356952
-I0511 11:50:55.663640  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663645  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663650  5581 caffe.cpp:501] detection_eval = 3.52823
-I0511 11:50:55.663655  5581 caffe.cpp:501] detection_eval = 13.0565
-I0511 11:50:55.663658  5581 caffe.cpp:501] detection_eval = 0.0364956
-I0511 11:50:55.663663  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663667  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663672  5581 caffe.cpp:501] detection_eval = 3.53226
-I0511 11:50:55.663676  5581 caffe.cpp:501] detection_eval = 13.0343
-I0511 11:50:55.663681  5581 caffe.cpp:501] detection_eval = 0.0377902
-I0511 11:50:55.663686  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663691  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.663694  5581 caffe.cpp:501] detection_eval = 3.53427
-I0511 11:50:55.663698  5581 caffe.cpp:501] detection_eval = 13.0444
-I0511 11:50:55.663703  5581 caffe.cpp:501] detection_eval = 0.0378157
-I0511 11:50:55.663707  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663712  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663717  5581 caffe.cpp:501] detection_eval = 3.53831
-I0511 11:50:55.663722  5581 caffe.cpp:501] detection_eval = 13.0827
-I0511 11:50:55.663725  5581 caffe.cpp:501] detection_eval = 0.0363094
-I0511 11:50:55.663730  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663734  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663739  5581 caffe.cpp:501] detection_eval = 3.53831
-I0511 11:50:55.663743  5581 caffe.cpp:501] detection_eval = 13.1532
-I0511 11:50:55.663748  5581 caffe.cpp:501] detection_eval = 0.0387398
-I0511 11:50:55.663753  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663756  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663761  5581 caffe.cpp:501] detection_eval = 3.54032
-I0511 11:50:55.663765  5581 caffe.cpp:501] detection_eval = 13.2298
-I0511 11:50:55.663770  5581 caffe.cpp:501] detection_eval = 0.0371919
-I0511 11:50:55.663774  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663779  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663784  5581 caffe.cpp:501] detection_eval = 3.54435
-I0511 11:50:55.663789  5581 caffe.cpp:501] detection_eval = 13.25
-I0511 11:50:55.663794  5581 caffe.cpp:501] detection_eval = 0.0400435
-I0511 11:50:55.663797  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663802  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663806  5581 caffe.cpp:501] detection_eval = 3.54435
-I0511 11:50:55.663810  5581 caffe.cpp:501] detection_eval = 13.3387
-I0511 11:50:55.663815  5581 caffe.cpp:501] detection_eval = 0.0379552
-I0511 11:50:55.663820  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663825  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663833  5581 caffe.cpp:501] detection_eval = 3.5504
-I0511 11:50:55.663838  5581 caffe.cpp:501] detection_eval = 13.3125
-I0511 11:50:55.663842  5581 caffe.cpp:501] detection_eval = 0.0364762
-I0511 11:50:55.663847  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663851  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663856  5581 caffe.cpp:501] detection_eval = 3.55645
-I0511 11:50:55.663861  5581 caffe.cpp:501] detection_eval = 13.2581
-I0511 11:50:55.663866  5581 caffe.cpp:501] detection_eval = 0.0388246
-I0511 11:50:55.663869  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663874  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663878  5581 caffe.cpp:501] detection_eval = 3.56048
-I0511 11:50:55.663883  5581 caffe.cpp:501] detection_eval = 13.3145
-I0511 11:50:55.663887  5581 caffe.cpp:501] detection_eval = 0.0419986
-I0511 11:50:55.663892  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663897  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.663902  5581 caffe.cpp:501] detection_eval = 3.56048
-I0511 11:50:55.663905  5581 caffe.cpp:501] detection_eval = 13.3891
-I0511 11:50:55.663910  5581 caffe.cpp:501] detection_eval = 0.03772
-I0511 11:50:55.663914  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663919  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663923  5581 caffe.cpp:501] detection_eval = 3.5625
-I0511 11:50:55.663928  5581 caffe.cpp:501] detection_eval = 13.4597
-I0511 11:50:55.663933  5581 caffe.cpp:501] detection_eval = 0.0409735
-I0511 11:50:55.663938  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663942  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663947  5581 caffe.cpp:501] detection_eval = 3.5625
-I0511 11:50:55.663951  5581 caffe.cpp:501] detection_eval = 13.6008
-I0511 11:50:55.663956  5581 caffe.cpp:501] detection_eval = 0.0356702
-I0511 11:50:55.663960  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663965  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.663969  5581 caffe.cpp:501] detection_eval = 3.56855
-I0511 11:50:55.663975  5581 caffe.cpp:501] detection_eval = 13.6613
-I0511 11:50:55.663980  5581 caffe.cpp:501] detection_eval = 0.0413387
-I0511 11:50:55.663983  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.663988  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.663992  5581 caffe.cpp:501] detection_eval = 3.56855
-I0511 11:50:55.663996  5581 caffe.cpp:501] detection_eval = 13.7762
-I0511 11:50:55.664001  5581 caffe.cpp:501] detection_eval = 0.0366315
-I0511 11:50:55.664006  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664011  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.664014  5581 caffe.cpp:501] detection_eval = 3.57056
-I0511 11:50:55.664019  5581 caffe.cpp:501] detection_eval = 13.9234
-I0511 11:50:55.664024  5581 caffe.cpp:501] detection_eval = 0.0361069
-I0511 11:50:55.664028  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664033  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664037  5581 caffe.cpp:501] detection_eval = 3.5746
-I0511 11:50:55.664041  5581 caffe.cpp:501] detection_eval = 14.004
-I0511 11:50:55.664047  5581 caffe.cpp:501] detection_eval = 0.034146
-I0511 11:50:55.664052  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664055  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664059  5581 caffe.cpp:501] detection_eval = 3.57863
-I0511 11:50:55.664064  5581 caffe.cpp:501] detection_eval = 14.1331
-I0511 11:50:55.664068  5581 caffe.cpp:501] detection_eval = 0.0357709
-I0511 11:50:55.664073  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.664077  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.664083  5581 caffe.cpp:501] detection_eval = 3.58468
-I0511 11:50:55.664086  5581 caffe.cpp:501] detection_eval = 14.2923
-I0511 11:50:55.664091  5581 caffe.cpp:501] detection_eval = 0.0329436
-I0511 11:50:55.664095  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.664100  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.664108  5581 caffe.cpp:501] detection_eval = 4.10282
-I0511 11:50:55.664113  5581 caffe.cpp:501] detection_eval = 6.76815
-I0511 11:50:55.664116  5581 caffe.cpp:501] detection_eval = 0.0905092
-I0511 11:50:55.664121  5581 caffe.cpp:501] detection_eval = 0.0685484
-I0511 11:50:55.664125  5581 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:50:55.664130  5581 caffe.cpp:501] detection_eval = 4.10484
-I0511 11:50:55.664134  5581 caffe.cpp:501] detection_eval = 6.96976
-I0511 11:50:55.664139  5581 caffe.cpp:501] detection_eval = 0.0644852
-I0511 11:50:55.664144  5581 caffe.cpp:501] detection_eval = 0.0342742
-I0511 11:50:55.664149  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.664152  5581 caffe.cpp:501] detection_eval = 4.10484
-I0511 11:50:55.664157  5581 caffe.cpp:501] detection_eval = 7.11694
-I0511 11:50:55.664161  5581 caffe.cpp:501] detection_eval = 0.0627071
-I0511 11:50:55.664166  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.664170  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.664175  5581 caffe.cpp:501] detection_eval = 4.10887
-I0511 11:50:55.664180  5581 caffe.cpp:501] detection_eval = 7.22581
-I0511 11:50:55.664183  5581 caffe.cpp:501] detection_eval = 0.0579806
-I0511 11:50:55.664188  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.664192  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.664197  5581 caffe.cpp:501] detection_eval = 4.1129
-I0511 11:50:55.664201  5581 caffe.cpp:501] detection_eval = 7.32863
-I0511 11:50:55.664206  5581 caffe.cpp:501] detection_eval = 0.0572587
-I0511 11:50:55.664211  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.664214  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.664219  5581 caffe.cpp:501] detection_eval = 4.11492
-I0511 11:50:55.664223  5581 caffe.cpp:501] detection_eval = 7.41935
-I0511 11:50:55.664227  5581 caffe.cpp:501] detection_eval = 0.0513708
-I0511 11:50:55.664232  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664237  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.664242  5581 caffe.cpp:501] detection_eval = 4.11694
-I0511 11:50:55.664245  5581 caffe.cpp:501] detection_eval = 7.44153
-I0511 11:50:55.664249  5581 caffe.cpp:501] detection_eval = 0.0486991
-I0511 11:50:55.664254  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.664258  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.664263  5581 caffe.cpp:501] detection_eval = 4.11895
-I0511 11:50:55.664268  5581 caffe.cpp:501] detection_eval = 7.51008
-I0511 11:50:55.664271  5581 caffe.cpp:501] detection_eval = 0.0435088
-I0511 11:50:55.664276  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.664280  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.664285  5581 caffe.cpp:501] detection_eval = 4.11895
-I0511 11:50:55.664289  5581 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:50:55.664294  5581 caffe.cpp:501] detection_eval = 0.0472525
-I0511 11:50:55.664299  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664304  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.664307  5581 caffe.cpp:501] detection_eval = 4.125
-I0511 11:50:55.664312  5581 caffe.cpp:501] detection_eval = 7.62903
-I0511 11:50:55.664316  5581 caffe.cpp:501] detection_eval = 0.0532138
-I0511 11:50:55.664321  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.664325  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.664330  5581 caffe.cpp:501] detection_eval = 4.12702
-I0511 11:50:55.664335  5581 caffe.cpp:501] detection_eval = 7.71774
-I0511 11:50:55.664338  5581 caffe.cpp:501] detection_eval = 0.0483561
-I0511 11:50:55.664343  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.664347  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.664352  5581 caffe.cpp:501] detection_eval = 4.12702
-I0511 11:50:55.664356  5581 caffe.cpp:501] detection_eval = 7.80444
-I0511 11:50:55.664361  5581 caffe.cpp:501] detection_eval = 0.0546764
-I0511 11:50:55.664366  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.664372  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.664377  5581 caffe.cpp:501] detection_eval = 4.12903
-I0511 11:50:55.664382  5581 caffe.cpp:501] detection_eval = 7.8629
-I0511 11:50:55.664386  5581 caffe.cpp:501] detection_eval = 0.0472698
-I0511 11:50:55.664391  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664396  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664400  5581 caffe.cpp:501] detection_eval = 4.13306
-I0511 11:50:55.664404  5581 caffe.cpp:501] detection_eval = 7.89919
-I0511 11:50:55.664408  5581 caffe.cpp:501] detection_eval = 0.0498237
-I0511 11:50:55.664413  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.664417  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.664422  5581 caffe.cpp:501] detection_eval = 4.1371
-I0511 11:50:55.664427  5581 caffe.cpp:501] detection_eval = 7.92742
-I0511 11:50:55.664432  5581 caffe.cpp:501] detection_eval = 0.0475132
-I0511 11:50:55.664435  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.664440  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.664444  5581 caffe.cpp:501] detection_eval = 4.13911
-I0511 11:50:55.664448  5581 caffe.cpp:501] detection_eval = 7.94758
-I0511 11:50:55.664453  5581 caffe.cpp:501] detection_eval = 0.0415651
-I0511 11:50:55.664458  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664463  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664466  5581 caffe.cpp:501] detection_eval = 4.14315
-I0511 11:50:55.664470  5581 caffe.cpp:501] detection_eval = 7.97379
-I0511 11:50:55.664475  5581 caffe.cpp:501] detection_eval = 0.0415416
-I0511 11:50:55.664479  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664484  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664489  5581 caffe.cpp:501] detection_eval = 4.14516
-I0511 11:50:55.664494  5581 caffe.cpp:501] detection_eval = 8.00605
-I0511 11:50:55.664497  5581 caffe.cpp:501] detection_eval = 0.0378814
-I0511 11:50:55.664502  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664506  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.664510  5581 caffe.cpp:501] detection_eval = 4.14919
-I0511 11:50:55.664515  5581 caffe.cpp:501] detection_eval = 8.03024
-I0511 11:50:55.664520  5581 caffe.cpp:501] detection_eval = 0.0385318
-I0511 11:50:55.664530  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664535  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664541  5581 caffe.cpp:501] detection_eval = 4.15121
-I0511 11:50:55.664544  5581 caffe.cpp:501] detection_eval = 8.05242
-I0511 11:50:55.664548  5581 caffe.cpp:501] detection_eval = 0.0426493
-I0511 11:50:55.664553  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664557  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664562  5581 caffe.cpp:501] detection_eval = 4.15323
-I0511 11:50:55.664566  5581 caffe.cpp:501] detection_eval = 8.08468
-I0511 11:50:55.664572  5581 caffe.cpp:501] detection_eval = 0.0418494
-I0511 11:50:55.664575  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664580  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664584  5581 caffe.cpp:501] detection_eval = 4.15323
-I0511 11:50:55.664589  5581 caffe.cpp:501] detection_eval = 8.15524
-I0511 11:50:55.664593  5581 caffe.cpp:501] detection_eval = 0.0368556
-I0511 11:50:55.664597  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664602  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664607  5581 caffe.cpp:501] detection_eval = 4.15726
-I0511 11:50:55.664611  5581 caffe.cpp:501] detection_eval = 8.16734
-I0511 11:50:55.664615  5581 caffe.cpp:501] detection_eval = 0.0369818
-I0511 11:50:55.664620  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664624  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664629  5581 caffe.cpp:501] detection_eval = 4.16532
-I0511 11:50:55.664633  5581 caffe.cpp:501] detection_eval = 8.14516
-I0511 11:50:55.664638  5581 caffe.cpp:501] detection_eval = 0.0413868
-I0511 11:50:55.664643  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664650  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664655  5581 caffe.cpp:501] detection_eval = 4.17137
-I0511 11:50:55.664659  5581 caffe.cpp:501] detection_eval = 8.14919
-I0511 11:50:55.664664  5581 caffe.cpp:501] detection_eval = 0.0452327
-I0511 11:50:55.664669  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.664672  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.664677  5581 caffe.cpp:501] detection_eval = 4.17339
-I0511 11:50:55.664681  5581 caffe.cpp:501] detection_eval = 8.21169
-I0511 11:50:55.664686  5581 caffe.cpp:501] detection_eval = 0.0418572
-I0511 11:50:55.664690  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664695  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664700  5581 caffe.cpp:501] detection_eval = 4.17742
-I0511 11:50:55.664703  5581 caffe.cpp:501] detection_eval = 8.23387
-I0511 11:50:55.664708  5581 caffe.cpp:501] detection_eval = 0.0442426
-I0511 11:50:55.664712  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664717  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664721  5581 caffe.cpp:501] detection_eval = 4.17742
-I0511 11:50:55.664726  5581 caffe.cpp:501] detection_eval = 8.30645
-I0511 11:50:55.664731  5581 caffe.cpp:501] detection_eval = 0.0407148
-I0511 11:50:55.664736  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.664739  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.664743  5581 caffe.cpp:501] detection_eval = 4.18145
-I0511 11:50:55.664747  5581 caffe.cpp:501] detection_eval = 8.30242
-I0511 11:50:55.664752  5581 caffe.cpp:501] detection_eval = 0.0422106
-I0511 11:50:55.664757  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664762  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664765  5581 caffe.cpp:501] detection_eval = 4.18347
-I0511 11:50:55.664770  5581 caffe.cpp:501] detection_eval = 8.34879
-I0511 11:50:55.664774  5581 caffe.cpp:501] detection_eval = 0.0429992
-I0511 11:50:55.664779  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664783  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.664788  5581 caffe.cpp:501] detection_eval = 4.18548
-I0511 11:50:55.664793  5581 caffe.cpp:501] detection_eval = 8.47177
-I0511 11:50:55.664796  5581 caffe.cpp:501] detection_eval = 0.0445516
-I0511 11:50:55.664801  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664805  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.664810  5581 caffe.cpp:501] detection_eval = 4.1875
-I0511 11:50:55.664814  5581 caffe.cpp:501] detection_eval = 8.50202
-I0511 11:50:55.664819  5581 caffe.cpp:501] detection_eval = 0.0383899
-I0511 11:50:55.664824  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664829  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.664832  5581 caffe.cpp:501] detection_eval = 4.19153
-I0511 11:50:55.664837  5581 caffe.cpp:501] detection_eval = 8.52823
-I0511 11:50:55.664841  5581 caffe.cpp:501] detection_eval = 0.0370178
-I0511 11:50:55.664846  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664850  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.664855  5581 caffe.cpp:501] detection_eval = 4.19355
-I0511 11:50:55.664860  5581 caffe.cpp:501] detection_eval = 8.56855
-I0511 11:50:55.664865  5581 caffe.cpp:501] detection_eval = 0.0433073
-I0511 11:50:55.664868  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664873  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664877  5581 caffe.cpp:501] detection_eval = 4.19355
-I0511 11:50:55.664881  5581 caffe.cpp:501] detection_eval = 8.65927
-I0511 11:50:55.664886  5581 caffe.cpp:501] detection_eval = 0.0473801
-I0511 11:50:55.664891  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664896  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664899  5581 caffe.cpp:501] detection_eval = 4.19556
-I0511 11:50:55.664904  5581 caffe.cpp:501] detection_eval = 8.66734
-I0511 11:50:55.664908  5581 caffe.cpp:501] detection_eval = 0.0405125
-I0511 11:50:55.664916  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664921  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664925  5581 caffe.cpp:501] detection_eval = 4.19758
-I0511 11:50:55.664929  5581 caffe.cpp:501] detection_eval = 8.72177
-I0511 11:50:55.664934  5581 caffe.cpp:501] detection_eval = 0.0375741
-I0511 11:50:55.664938  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664943  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664947  5581 caffe.cpp:501] detection_eval = 4.19758
-I0511 11:50:55.664952  5581 caffe.cpp:501] detection_eval = 8.77218
-I0511 11:50:55.664957  5581 caffe.cpp:501] detection_eval = 0.041395
-I0511 11:50:55.664961  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664965  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664970  5581 caffe.cpp:501] detection_eval = 4.1996
-I0511 11:50:55.664974  5581 caffe.cpp:501] detection_eval = 8.80847
-I0511 11:50:55.664978  5581 caffe.cpp:501] detection_eval = 0.043218
-I0511 11:50:55.664983  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664988  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664993  5581 caffe.cpp:501] detection_eval = 4.20363
-I0511 11:50:55.664996  5581 caffe.cpp:501] detection_eval = 8.80847
-I0511 11:50:55.665001  5581 caffe.cpp:501] detection_eval = 0.0418496
-I0511 11:50:55.665005  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665009  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.665014  5581 caffe.cpp:501] detection_eval = 4.20363
-I0511 11:50:55.665019  5581 caffe.cpp:501] detection_eval = 8.88508
-I0511 11:50:55.665022  5581 caffe.cpp:501] detection_eval = 0.0375474
-I0511 11:50:55.665027  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.665031  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665036  5581 caffe.cpp:501] detection_eval = 4.20363
-I0511 11:50:55.665040  5581 caffe.cpp:501] detection_eval = 8.94758
-I0511 11:50:55.665045  5581 caffe.cpp:501] detection_eval = 0.0381792
-I0511 11:50:55.665050  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665053  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665058  5581 caffe.cpp:501] detection_eval = 4.20766
-I0511 11:50:55.665062  5581 caffe.cpp:501] detection_eval = 8.9879
-I0511 11:50:55.665067  5581 caffe.cpp:501] detection_eval = 0.0396819
-I0511 11:50:55.665071  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.665076  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665081  5581 caffe.cpp:501] detection_eval = 4.21371
-I0511 11:50:55.665086  5581 caffe.cpp:501] detection_eval = 8.93952
-I0511 11:50:55.665089  5581 caffe.cpp:501] detection_eval = 0.0350682
-I0511 11:50:55.665093  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665098  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665102  5581 caffe.cpp:501] detection_eval = 4.21573
-I0511 11:50:55.665107  5581 caffe.cpp:501] detection_eval = 8.98589
-I0511 11:50:55.665112  5581 caffe.cpp:501] detection_eval = 0.0396747
-I0511 11:50:55.665115  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665120  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665124  5581 caffe.cpp:501] detection_eval = 4.21774
-I0511 11:50:55.665129  5581 caffe.cpp:501] detection_eval = 9.04435
-I0511 11:50:55.665133  5581 caffe.cpp:501] detection_eval = 0.0390687
-I0511 11:50:55.665138  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.665143  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665148  5581 caffe.cpp:501] detection_eval = 4.21774
-I0511 11:50:55.665151  5581 caffe.cpp:501] detection_eval = 9.10685
-I0511 11:50:55.665155  5581 caffe.cpp:501] detection_eval = 0.0397611
-I0511 11:50:55.665160  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665164  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665169  5581 caffe.cpp:501] detection_eval = 4.22177
-I0511 11:50:55.665174  5581 caffe.cpp:501] detection_eval = 9.1371
-I0511 11:50:55.665181  5581 caffe.cpp:501] detection_eval = 0.044734
-I0511 11:50:55.665186  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.665190  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.665195  5581 caffe.cpp:501] detection_eval = 4.22782
-I0511 11:50:55.665199  5581 caffe.cpp:501] detection_eval = 9.06855
-I0511 11:50:55.665205  5581 caffe.cpp:501] detection_eval = 0.0412259
-I0511 11:50:55.665210  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665213  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665218  5581 caffe.cpp:501] detection_eval = 4.22984
-I0511 11:50:55.665222  5581 caffe.cpp:501] detection_eval = 9.15927
-I0511 11:50:55.665226  5581 caffe.cpp:501] detection_eval = 0.0449804
-I0511 11:50:55.665231  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665235  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665241  5581 caffe.cpp:501] detection_eval = 4.23185
-I0511 11:50:55.665244  5581 caffe.cpp:501] detection_eval = 9.21976
-I0511 11:50:55.665248  5581 caffe.cpp:501] detection_eval = 0.0495442
-I0511 11:50:55.665253  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.665257  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665262  5581 caffe.cpp:501] detection_eval = 4.23387
-I0511 11:50:55.665266  5581 caffe.cpp:501] detection_eval = 9.24395
-I0511 11:50:55.665271  5581 caffe.cpp:501] detection_eval = 0.0492313
-I0511 11:50:55.665275  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.665279  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.665283  5581 caffe.cpp:501] detection_eval = 4.23387
-I0511 11:50:55.665288  5581 caffe.cpp:501] detection_eval = 9.30847
-I0511 11:50:55.665292  5581 caffe.cpp:501] detection_eval = 0.045926
-I0511 11:50:55.665297  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.665302  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665307  5581 caffe.cpp:501] detection_eval = 4.23589
-I0511 11:50:55.665310  5581 caffe.cpp:501] detection_eval = 9.39315
-I0511 11:50:55.665314  5581 caffe.cpp:501] detection_eval = 0.0468036
-I0511 11:50:55.665319  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.665323  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665328  5581 caffe.cpp:501] detection_eval = 4.23589
-I0511 11:50:55.665333  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.665338  5581 caffe.cpp:501] detection_eval = 0.0508337
-I0511 11:50:55.665341  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.665345  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.665350  5581 caffe.cpp:501] detection_eval = 4.23589
-I0511 11:50:55.665354  5581 caffe.cpp:501] detection_eval = 9.59476
-I0511 11:50:55.665359  5581 caffe.cpp:501] detection_eval = 0.0415461
-I0511 11:50:55.665364  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665369  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665372  5581 caffe.cpp:501] detection_eval = 4.2379
-I0511 11:50:55.665377  5581 caffe.cpp:501] detection_eval = 9.64516
-I0511 11:50:55.665381  5581 caffe.cpp:501] detection_eval = 0.0447107
-I0511 11:50:55.665386  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.665390  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665395  5581 caffe.cpp:501] detection_eval = 4.2379
-I0511 11:50:55.665400  5581 caffe.cpp:501] detection_eval = 9.69153
-I0511 11:50:55.665403  5581 caffe.cpp:501] detection_eval = 0.0375447
-I0511 11:50:55.665408  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665412  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.665417  5581 caffe.cpp:501] detection_eval = 4.23992
-I0511 11:50:55.665421  5581 caffe.cpp:501] detection_eval = 9.73589
-I0511 11:50:55.665426  5581 caffe.cpp:501] detection_eval = 0.0430661
-I0511 11:50:55.665431  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665434  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665439  5581 caffe.cpp:501] detection_eval = 4.24194
-I0511 11:50:55.665443  5581 caffe.cpp:501] detection_eval = 9.79435
-I0511 11:50:55.665451  5581 caffe.cpp:501] detection_eval = 0.0461263
-I0511 11:50:55.665455  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.665460  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665464  5581 caffe.cpp:501] detection_eval = 4.24395
-I0511 11:50:55.665469  5581 caffe.cpp:501] detection_eval = 9.87298
-I0511 11:50:55.665473  5581 caffe.cpp:501] detection_eval = 0.0567309
-I0511 11:50:55.665478  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.665482  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.665486  5581 caffe.cpp:501] detection_eval = 4.25
-I0511 11:50:55.665491  5581 caffe.cpp:501] detection_eval = 9.82661
-I0511 11:50:55.665495  5581 caffe.cpp:501] detection_eval = 0.0488227
-I0511 11:50:55.665500  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.665504  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.665509  5581 caffe.cpp:501] detection_eval = 4.25
-I0511 11:50:55.665513  5581 caffe.cpp:501] detection_eval = 9.86895
-I0511 11:50:55.665518  5581 caffe.cpp:501] detection_eval = 0.0474801
-I0511 11:50:55.665522  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665527  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665531  5581 caffe.cpp:501] detection_eval = 4.25605
-I0511 11:50:55.665536  5581 caffe.cpp:501] detection_eval = 9.875
-I0511 11:50:55.665540  5581 caffe.cpp:501] detection_eval = 0.0479852
-I0511 11:50:55.665544  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.665549  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665554  5581 caffe.cpp:501] detection_eval = 4.25605
-I0511 11:50:55.665557  5581 caffe.cpp:501] detection_eval = 9.92944
-I0511 11:50:55.665562  5581 caffe.cpp:501] detection_eval = 0.0425905
-I0511 11:50:55.665566  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665571  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.665575  5581 caffe.cpp:501] detection_eval = 4.25806
-I0511 11:50:55.665580  5581 caffe.cpp:501] detection_eval = 9.99798
-I0511 11:50:55.665585  5581 caffe.cpp:501] detection_eval = 0.042935
-I0511 11:50:55.665588  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665593  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665597  5581 caffe.cpp:501] detection_eval = 4.25806
-I0511 11:50:55.665602  5581 caffe.cpp:501] detection_eval = 10.1048
-I0511 11:50:55.665606  5581 caffe.cpp:501] detection_eval = 0.0455724
-I0511 11:50:55.665611  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.665616  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665621  5581 caffe.cpp:501] detection_eval = 4.25806
-I0511 11:50:55.665624  5581 caffe.cpp:501] detection_eval = 10.2056
-I0511 11:50:55.665629  5581 caffe.cpp:501] detection_eval = 0.0434433
-I0511 11:50:55.665634  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.665638  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665643  5581 caffe.cpp:501] detection_eval = 4.26008
-I0511 11:50:55.665647  5581 caffe.cpp:501] detection_eval = 10.2903
-I0511 11:50:55.665652  5581 caffe.cpp:501] detection_eval = 0.0421711
-I0511 11:50:55.665657  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665661  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.665665  5581 caffe.cpp:501] detection_eval = 4.26815
-I0511 11:50:55.665669  5581 caffe.cpp:501] detection_eval = 10.2964
-I0511 11:50:55.665674  5581 caffe.cpp:501] detection_eval = 0.0435917
-I0511 11:50:55.665679  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665683  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665688  5581 caffe.cpp:501] detection_eval = 4.27016
-I0511 11:50:55.665693  5581 caffe.cpp:501] detection_eval = 10.3609
-I0511 11:50:55.665697  5581 caffe.cpp:501] detection_eval = 0.0449169
-I0511 11:50:55.665701  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.665705  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.665710  5581 caffe.cpp:501] detection_eval = 4.28024
-I0511 11:50:55.665717  5581 caffe.cpp:501] detection_eval = 10.3024
-I0511 11:50:55.665722  5581 caffe.cpp:501] detection_eval = 0.0445046
-I0511 11:50:55.665727  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665731  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665735  5581 caffe.cpp:501] detection_eval = 4.28629
-I0511 11:50:55.665740  5581 caffe.cpp:501] detection_eval = 10.3105
-I0511 11:50:55.665745  5581 caffe.cpp:501] detection_eval = 0.0444123
-I0511 11:50:55.665750  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665753  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.665758  5581 caffe.cpp:501] detection_eval = 4.29032
-I0511 11:50:55.665762  5581 caffe.cpp:501] detection_eval = 10.3145
-I0511 11:50:55.665767  5581 caffe.cpp:501] detection_eval = 0.0398316
-I0511 11:50:55.665771  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665776  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665781  5581 caffe.cpp:501] detection_eval = 4.29435
-I0511 11:50:55.665786  5581 caffe.cpp:501] detection_eval = 10.3387
-I0511 11:50:55.665789  5581 caffe.cpp:501] detection_eval = 0.0463916
-I0511 11:50:55.665794  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665798  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665803  5581 caffe.cpp:501] detection_eval = 4.29839
-I0511 11:50:55.665807  5581 caffe.cpp:501] detection_eval = 10.371
-I0511 11:50:55.665812  5581 caffe.cpp:501] detection_eval = 0.0514975
-I0511 11:50:55.665817  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.665822  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665825  5581 caffe.cpp:501] detection_eval = 4.3004
-I0511 11:50:55.665830  5581 caffe.cpp:501] detection_eval = 10.3851
-I0511 11:50:55.665834  5581 caffe.cpp:501] detection_eval = 0.0445005
-I0511 11:50:55.665839  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665843  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665848  5581 caffe.cpp:501] detection_eval = 4.30444
-I0511 11:50:55.665853  5581 caffe.cpp:501] detection_eval = 10.4173
-I0511 11:50:55.665858  5581 caffe.cpp:501] detection_eval = 0.0444614
-I0511 11:50:55.665861  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665866  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665870  5581 caffe.cpp:501] detection_eval = 4.30645
-I0511 11:50:55.665874  5581 caffe.cpp:501] detection_eval = 10.4556
-I0511 11:50:55.665879  5581 caffe.cpp:501] detection_eval = 0.0405224
-I0511 11:50:55.665884  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665889  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665894  5581 caffe.cpp:501] detection_eval = 4.3125
-I0511 11:50:55.665897  5581 caffe.cpp:501] detection_eval = 10.4516
-I0511 11:50:55.665902  5581 caffe.cpp:501] detection_eval = 0.0424148
-I0511 11:50:55.665906  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665911  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.665915  5581 caffe.cpp:501] detection_eval = 4.31452
-I0511 11:50:55.665920  5581 caffe.cpp:501] detection_eval = 10.5101
-I0511 11:50:55.665925  5581 caffe.cpp:501] detection_eval = 0.0433033
-I0511 11:50:55.665930  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665933  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665938  5581 caffe.cpp:501] detection_eval = 4.31855
-I0511 11:50:55.665942  5581 caffe.cpp:501] detection_eval = 10.5202
-I0511 11:50:55.665946  5581 caffe.cpp:501] detection_eval = 0.0425584
-I0511 11:50:55.665951  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665956  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665961  5581 caffe.cpp:501] detection_eval = 4.32258
-I0511 11:50:55.665964  5581 caffe.cpp:501] detection_eval = 10.498
-I0511 11:50:55.665969  5581 caffe.cpp:501] detection_eval = 0.0391324
-I0511 11:50:55.665974  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665978  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665983  5581 caffe.cpp:501] detection_eval = 4.32661
-I0511 11:50:55.665990  5581 caffe.cpp:501] detection_eval = 10.5262
-I0511 11:50:55.665995  5581 caffe.cpp:501] detection_eval = 0.0420095
-I0511 11:50:55.665999  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666004  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666008  5581 caffe.cpp:501] detection_eval = 4.33669
-I0511 11:50:55.666013  5581 caffe.cpp:501] detection_eval = 10.4536
-I0511 11:50:55.666018  5581 caffe.cpp:501] detection_eval = 0.0434449
-I0511 11:50:55.666023  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666026  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666031  5581 caffe.cpp:501] detection_eval = 4.33669
-I0511 11:50:55.666035  5581 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:50:55.666040  5581 caffe.cpp:501] detection_eval = 0.0387064
-I0511 11:50:55.666044  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.666049  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.666054  5581 caffe.cpp:501] detection_eval = 4.34274
-I0511 11:50:55.666059  5581 caffe.cpp:501] detection_eval = 10.4819
-I0511 11:50:55.666062  5581 caffe.cpp:501] detection_eval = 0.0370433
-I0511 11:50:55.666067  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.666071  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.666076  5581 caffe.cpp:501] detection_eval = 4.34677
-I0511 11:50:55.666080  5581 caffe.cpp:501] detection_eval = 10.4859
-I0511 11:50:55.666085  5581 caffe.cpp:501] detection_eval = 0.0383295
-I0511 11:50:55.666090  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666093  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.666098  5581 caffe.cpp:501] detection_eval = 4.34879
-I0511 11:50:55.666102  5581 caffe.cpp:501] detection_eval = 10.5645
-I0511 11:50:55.666107  5581 caffe.cpp:501] detection_eval = 0.0456144
-I0511 11:50:55.666112  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666116  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666121  5581 caffe.cpp:501] detection_eval = 4.34879
-I0511 11:50:55.666126  5581 caffe.cpp:501] detection_eval = 10.6391
-I0511 11:50:55.666131  5581 caffe.cpp:501] detection_eval = 0.0450885
-I0511 11:50:55.666134  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666139  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666143  5581 caffe.cpp:501] detection_eval = 4.35081
-I0511 11:50:55.666148  5581 caffe.cpp:501] detection_eval = 10.7097
-I0511 11:50:55.666152  5581 caffe.cpp:501] detection_eval = 0.0424969
-I0511 11:50:55.666157  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666162  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.666167  5581 caffe.cpp:501] detection_eval = 4.35685
-I0511 11:50:55.666170  5581 caffe.cpp:501] detection_eval = 10.752
-I0511 11:50:55.666175  5581 caffe.cpp:501] detection_eval = 0.0436257
-I0511 11:50:55.666179  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666184  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666188  5581 caffe.cpp:501] detection_eval = 4.35887
-I0511 11:50:55.666193  5581 caffe.cpp:501] detection_eval = 10.7903
-I0511 11:50:55.666198  5581 caffe.cpp:501] detection_eval = 0.0431476
-I0511 11:50:55.666203  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666206  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.666211  5581 caffe.cpp:501] detection_eval = 4.3629
-I0511 11:50:55.666215  5581 caffe.cpp:501] detection_eval = 10.7843
-I0511 11:50:55.666220  5581 caffe.cpp:501] detection_eval = 0.0442008
-I0511 11:50:55.666224  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666229  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666232  5581 caffe.cpp:501] detection_eval = 4.36694
-I0511 11:50:55.666237  5581 caffe.cpp:501] detection_eval = 10.7782
-I0511 11:50:55.666241  5581 caffe.cpp:501] detection_eval = 0.0414062
-I0511 11:50:55.666246  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666250  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.666258  5581 caffe.cpp:501] detection_eval = 4.36895
-I0511 11:50:55.666262  5581 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:50:55.666267  5581 caffe.cpp:501] detection_eval = 0.041054
-I0511 11:50:55.666272  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.666276  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666281  5581 caffe.cpp:501] detection_eval = 4.37097
-I0511 11:50:55.666285  5581 caffe.cpp:501] detection_eval = 10.9012
-I0511 11:50:55.666290  5581 caffe.cpp:501] detection_eval = 0.0459491
-I0511 11:50:55.666296  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.666299  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.666303  5581 caffe.cpp:501] detection_eval = 4.37903
-I0511 11:50:55.666308  5581 caffe.cpp:501] detection_eval = 10.875
-I0511 11:50:55.666312  5581 caffe.cpp:501] detection_eval = 0.041678
-I0511 11:50:55.666317  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666321  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666326  5581 caffe.cpp:501] detection_eval = 4.38105
-I0511 11:50:55.666330  5581 caffe.cpp:501] detection_eval = 10.9294
-I0511 11:50:55.666335  5581 caffe.cpp:501] detection_eval = 0.0375598
-I0511 11:50:55.666339  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666344  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.666349  5581 caffe.cpp:501] detection_eval = 4.39113
-I0511 11:50:55.666353  5581 caffe.cpp:501] detection_eval = 10.8387
-I0511 11:50:55.666357  5581 caffe.cpp:501] detection_eval = 0.0412384
-I0511 11:50:55.666362  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666366  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666370  5581 caffe.cpp:501] detection_eval = 4.39919
-I0511 11:50:55.666375  5581 caffe.cpp:501] detection_eval = 10.7964
-I0511 11:50:55.666379  5581 caffe.cpp:501] detection_eval = 0.045887
-I0511 11:50:55.666384  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666388  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666393  5581 caffe.cpp:501] detection_eval = 4.40121
-I0511 11:50:55.666398  5581 caffe.cpp:501] detection_eval = 10.8327
-I0511 11:50:55.666402  5581 caffe.cpp:501] detection_eval = 0.0433971
-I0511 11:50:55.666407  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666411  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666416  5581 caffe.cpp:501] detection_eval = 4.40524
-I0511 11:50:55.666420  5581 caffe.cpp:501] detection_eval = 10.8992
-I0511 11:50:55.666425  5581 caffe.cpp:501] detection_eval = 0.0442976
-I0511 11:50:55.666429  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666435  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666438  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666443  5581 caffe.cpp:501] detection_eval = 10.9032
-I0511 11:50:55.666447  5581 caffe.cpp:501] detection_eval = 0.0453736
-I0511 11:50:55.666452  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.666456  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.666461  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666465  5581 caffe.cpp:501] detection_eval = 10.9698
-I0511 11:50:55.666471  5581 caffe.cpp:501] detection_eval = 0.0438347
-I0511 11:50:55.666474  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.666479  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.666483  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666488  5581 caffe.cpp:501] detection_eval = 11.0282
-I0511 11:50:55.666492  5581 caffe.cpp:501] detection_eval = 0.0439485
-I0511 11:50:55.666497  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666501  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666507  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666510  5581 caffe.cpp:501] detection_eval = 11.0887
-I0511 11:50:55.666515  5581 caffe.cpp:501] detection_eval = 0.0499174
-I0511 11:50:55.666519  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.666527  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.666532  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666537  5581 caffe.cpp:501] detection_eval = 11.1593
-I0511 11:50:55.666541  5581 caffe.cpp:501] detection_eval = 0.0429797
-I0511 11:50:55.666545  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666550  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666555  5581 caffe.cpp:501] detection_eval = 4.41331
-I0511 11:50:55.666559  5581 caffe.cpp:501] detection_eval = 11.2016
-I0511 11:50:55.666564  5581 caffe.cpp:501] detection_eval = 0.0434779
-I0511 11:50:55.666568  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666574  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666577  5581 caffe.cpp:501] detection_eval = 4.41734
-I0511 11:50:55.666582  5581 caffe.cpp:501] detection_eval = 11.1935
-I0511 11:50:55.666586  5581 caffe.cpp:501] detection_eval = 0.0429046
-I0511 11:50:55.666591  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666595  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666600  5581 caffe.cpp:501] detection_eval = 4.41935
-I0511 11:50:55.666604  5581 caffe.cpp:501] detection_eval = 11.2137
-I0511 11:50:55.666610  5581 caffe.cpp:501] detection_eval = 0.0456519
-I0511 11:50:55.666613  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666618  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666622  5581 caffe.cpp:501] detection_eval = 4.42137
-I0511 11:50:55.666626  5581 caffe.cpp:501] detection_eval = 11.2782
-I0511 11:50:55.666631  5581 caffe.cpp:501] detection_eval = 0.040348
-I0511 11:50:55.666635  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666640  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666645  5581 caffe.cpp:501] detection_eval = 4.42339
-I0511 11:50:55.666649  5581 caffe.cpp:501] detection_eval = 11.3306
-I0511 11:50:55.666653  5581 caffe.cpp:501] detection_eval = 0.0440193
-I0511 11:50:55.666658  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666662  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666667  5581 caffe.cpp:501] detection_eval = 4.42339
-I0511 11:50:55.666671  5581 caffe.cpp:501] detection_eval = 11.4153
-I0511 11:50:55.666676  5581 caffe.cpp:501] detection_eval = 0.0462135
-I0511 11:50:55.666680  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.666685  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.666689  5581 caffe.cpp:501] detection_eval = 4.4254
-I0511 11:50:55.666694  5581 caffe.cpp:501] detection_eval = 11.4274
-I0511 11:50:55.666698  5581 caffe.cpp:501] detection_eval = 0.0443372
-I0511 11:50:55.666703  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666707  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666712  5581 caffe.cpp:501] detection_eval = 4.43347
-I0511 11:50:55.666716  5581 caffe.cpp:501] detection_eval = 11.3327
-I0511 11:50:55.666721  5581 caffe.cpp:501] detection_eval = 0.0398814
-I0511 11:50:55.666725  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666730  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666734  5581 caffe.cpp:501] detection_eval = 4.43548
-I0511 11:50:55.666739  5581 caffe.cpp:501] detection_eval = 11.3508
-I0511 11:50:55.666743  5581 caffe.cpp:501] detection_eval = 0.0379586
-I0511 11:50:55.666749  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.666752  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666757  5581 caffe.cpp:501] detection_eval = 4.4375
-I0511 11:50:55.666761  5581 caffe.cpp:501] detection_eval = 11.375
-I0511 11:50:55.666766  5581 caffe.cpp:501] detection_eval = 0.0398871
-I0511 11:50:55.666770  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666775  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666779  5581 caffe.cpp:501] detection_eval = 4.44355
-I0511 11:50:55.666785  5581 caffe.cpp:501] detection_eval = 11.3407
-I0511 11:50:55.666788  5581 caffe.cpp:501] detection_eval = 0.0427237
-I0511 11:50:55.666793  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666800  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666805  5581 caffe.cpp:501] detection_eval = 4.44556
-I0511 11:50:55.666810  5581 caffe.cpp:501] detection_eval = 11.371
-I0511 11:50:55.666815  5581 caffe.cpp:501] detection_eval = 0.0427771
-I0511 11:50:55.666820  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.666823  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.666827  5581 caffe.cpp:501] detection_eval = 4.4496
-I0511 11:50:55.666832  5581 caffe.cpp:501] detection_eval = 11.3508
-I0511 11:50:55.666837  5581 caffe.cpp:501] detection_eval = 0.040328
-I0511 11:50:55.666841  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666846  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666851  5581 caffe.cpp:501] detection_eval = 4.45161
-I0511 11:50:55.666854  5581 caffe.cpp:501] detection_eval = 11.3609
-I0511 11:50:55.666859  5581 caffe.cpp:501] detection_eval = 0.0401247
-I0511 11:50:55.666864  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666868  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.666873  5581 caffe.cpp:501] detection_eval = 4.45565
-I0511 11:50:55.666877  5581 caffe.cpp:501] detection_eval = 11.4052
-I0511 11:50:55.666882  5581 caffe.cpp:501] detection_eval = 0.0399035
-I0511 11:50:55.666887  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666891  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666895  5581 caffe.cpp:501] detection_eval = 4.45968
-I0511 11:50:55.666899  5581 caffe.cpp:501] detection_eval = 11.496
-I0511 11:50:55.666904  5581 caffe.cpp:501] detection_eval = 0.0506911
-I0511 11:50:55.666908  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.666913  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.666918  5581 caffe.cpp:501] detection_eval = 4.46371
-I0511 11:50:55.666921  5581 caffe.cpp:501] detection_eval = 11.5222
-I0511 11:50:55.666926  5581 caffe.cpp:501] detection_eval = 0.0458513
-I0511 11:50:55.666931  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.666935  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.666939  5581 caffe.cpp:501] detection_eval = 4.46371
-I0511 11:50:55.666944  5581 caffe.cpp:501] detection_eval = 11.6129
-I0511 11:50:55.666949  5581 caffe.cpp:501] detection_eval = 0.0485337
-I0511 11:50:55.666954  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.666959  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.666962  5581 caffe.cpp:501] detection_eval = 4.46371
-I0511 11:50:55.666966  5581 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:50:55.666971  5581 caffe.cpp:501] detection_eval = 0.0491915
-I0511 11:50:55.666975  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666980  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666985  5581 caffe.cpp:501] detection_eval = 4.46774
-I0511 11:50:55.666990  5581 caffe.cpp:501] detection_eval = 11.7298
-I0511 11:50:55.666995  5581 caffe.cpp:501] detection_eval = 0.0518123
-I0511 11:50:55.666998  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.667002  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.667007  5581 caffe.cpp:501] detection_eval = 4.47379
-I0511 11:50:55.667011  5581 caffe.cpp:501] detection_eval = 11.6935
-I0511 11:50:55.667016  5581 caffe.cpp:501] detection_eval = 0.0429515
-I0511 11:50:55.667021  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667026  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667029  5581 caffe.cpp:501] detection_eval = 4.47581
-I0511 11:50:55.667034  5581 caffe.cpp:501] detection_eval = 11.7238
-I0511 11:50:55.667039  5581 caffe.cpp:501] detection_eval = 0.0408649
-I0511 11:50:55.667043  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.667047  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667052  5581 caffe.cpp:501] detection_eval = 4.47984
-I0511 11:50:55.667057  5581 caffe.cpp:501] detection_eval = 11.7419
-I0511 11:50:55.667062  5581 caffe.cpp:501] detection_eval = 0.0378178
-I0511 11:50:55.667068  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667073  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667078  5581 caffe.cpp:501] detection_eval = 4.48185
-I0511 11:50:55.667083  5581 caffe.cpp:501] detection_eval = 11.7722
-I0511 11:50:55.667088  5581 caffe.cpp:501] detection_eval = 0.0400242
-I0511 11:50:55.667093  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667096  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667101  5581 caffe.cpp:501] detection_eval = 4.48589
-I0511 11:50:55.667105  5581 caffe.cpp:501] detection_eval = 11.7903
-I0511 11:50:55.667110  5581 caffe.cpp:501] detection_eval = 0.0403816
-I0511 11:50:55.667115  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667120  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.667124  5581 caffe.cpp:501] detection_eval = 4.49194
-I0511 11:50:55.667129  5581 caffe.cpp:501] detection_eval = 11.7621
-I0511 11:50:55.667134  5581 caffe.cpp:501] detection_eval = 0.0395134
-I0511 11:50:55.667138  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.667142  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667147  5581 caffe.cpp:501] detection_eval = 4.49597
-I0511 11:50:55.667151  5581 caffe.cpp:501] detection_eval = 11.752
-I0511 11:50:55.667156  5581 caffe.cpp:501] detection_eval = 0.0386682
-I0511 11:50:55.667160  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667165  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667170  5581 caffe.cpp:501] detection_eval = 4.49798
-I0511 11:50:55.667174  5581 caffe.cpp:501] detection_eval = 11.8206
-I0511 11:50:55.667178  5581 caffe.cpp:501] detection_eval = 0.0428092
-I0511 11:50:55.667183  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667188  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667192  5581 caffe.cpp:501] detection_eval = 4.5
-I0511 11:50:55.667196  5581 caffe.cpp:501] detection_eval = 11.8327
-I0511 11:50:55.667201  5581 caffe.cpp:501] detection_eval = 0.0396953
-I0511 11:50:55.667207  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667210  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667214  5581 caffe.cpp:501] detection_eval = 4.50202
-I0511 11:50:55.667219  5581 caffe.cpp:501] detection_eval = 11.8629
-I0511 11:50:55.667224  5581 caffe.cpp:501] detection_eval = 0.0432461
-I0511 11:50:55.667228  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667233  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667237  5581 caffe.cpp:501] detection_eval = 4.50605
-I0511 11:50:55.667243  5581 caffe.cpp:501] detection_eval = 11.8851
-I0511 11:50:55.667246  5581 caffe.cpp:501] detection_eval = 0.0406408
-I0511 11:50:55.667251  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667256  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667260  5581 caffe.cpp:501] detection_eval = 4.51008
-I0511 11:50:55.667265  5581 caffe.cpp:501] detection_eval = 11.9234
-I0511 11:50:55.667269  5581 caffe.cpp:501] detection_eval = 0.04964
-I0511 11:50:55.667274  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.667279  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.667284  5581 caffe.cpp:501] detection_eval = 4.51008
-I0511 11:50:55.667287  5581 caffe.cpp:501] detection_eval = 11.9879
-I0511 11:50:55.667292  5581 caffe.cpp:501] detection_eval = 0.0440365
-I0511 11:50:55.667297  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667301  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667304  5581 caffe.cpp:501] detection_eval = 4.51613
-I0511 11:50:55.667306  5581 caffe.cpp:501] detection_eval = 11.9516
-I0511 11:50:55.667309  5581 caffe.cpp:501] detection_eval = 0.0413376
-I0511 11:50:55.667311  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667315  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667316  5581 caffe.cpp:501] detection_eval = 4.51613
-I0511 11:50:55.667318  5581 caffe.cpp:501] detection_eval = 12.0524
-I0511 11:50:55.667323  5581 caffe.cpp:501] detection_eval = 0.0399847
-I0511 11:50:55.667326  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.667328  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.667331  5581 caffe.cpp:501] detection_eval = 4.52016
-I0511 11:50:55.667333  5581 caffe.cpp:501] detection_eval = 12.0645
-I0511 11:50:55.667335  5581 caffe.cpp:501] detection_eval = 0.042322
-I0511 11:50:55.667337  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.667340  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.667342  5581 caffe.cpp:501] detection_eval = 4.52016
-I0511 11:50:55.667345  5581 caffe.cpp:501] detection_eval = 12.125
-I0511 11:50:55.667346  5581 caffe.cpp:501] detection_eval = 0.0411623
-I0511 11:50:55.667349  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667351  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667353  5581 caffe.cpp:501] detection_eval = 4.52419
-I0511 11:50:55.667356  5581 caffe.cpp:501] detection_eval = 12.1653
-I0511 11:50:55.667361  5581 caffe.cpp:501] detection_eval = 0.0385926
-I0511 11:50:55.667364  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667369  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.667374  5581 caffe.cpp:501] detection_eval = 4.52419
-I0511 11:50:55.667378  5581 caffe.cpp:501] detection_eval = 12.2238
-I0511 11:50:55.667383  5581 caffe.cpp:501] detection_eval = 0.0362826
-I0511 11:50:55.667387  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.667392  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.667397  5581 caffe.cpp:501] detection_eval = 4.52823
-I0511 11:50:55.667400  5581 caffe.cpp:501] detection_eval = 12.2278
-I0511 11:50:55.667405  5581 caffe.cpp:501] detection_eval = 0.0397036
-I0511 11:50:55.667410  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667414  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667418  5581 caffe.cpp:501] detection_eval = 4.53226
-I0511 11:50:55.667423  5581 caffe.cpp:501] detection_eval = 12.2359
-I0511 11:50:55.667428  5581 caffe.cpp:501] detection_eval = 0.0423725
-I0511 11:50:55.667433  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667436  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667441  5581 caffe.cpp:501] detection_eval = 4.53226
-I0511 11:50:55.667445  5581 caffe.cpp:501] detection_eval = 12.2823
-I0511 11:50:55.667450  5581 caffe.cpp:501] detection_eval = 0.040986
-I0511 11:50:55.667455  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667459  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667464  5581 caffe.cpp:501] detection_eval = 4.53427
-I0511 11:50:55.667469  5581 caffe.cpp:501] detection_eval = 12.2883
-I0511 11:50:55.667472  5581 caffe.cpp:501] detection_eval = 0.0366525
-I0511 11:50:55.667477  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667481  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.667486  5581 caffe.cpp:501] detection_eval = 4.54032
-I0511 11:50:55.667490  5581 caffe.cpp:501] detection_eval = 12.2601
-I0511 11:50:55.667495  5581 caffe.cpp:501] detection_eval = 0.0393226
-I0511 11:50:55.667500  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667505  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667508  5581 caffe.cpp:501] detection_eval = 4.54839
-I0511 11:50:55.667513  5581 caffe.cpp:501] detection_eval = 12.1754
-I0511 11:50:55.667517  5581 caffe.cpp:501] detection_eval = 0.0431251
-I0511 11:50:55.667522  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667526  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667531  5581 caffe.cpp:501] detection_eval = 4.55444
-I0511 11:50:55.667536  5581 caffe.cpp:501] detection_eval = 12.1371
-I0511 11:50:55.667541  5581 caffe.cpp:501] detection_eval = 0.0422945
-I0511 11:50:55.667544  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.667549  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667553  5581 caffe.cpp:501] detection_eval = 4.56452
-I0511 11:50:55.667557  5581 caffe.cpp:501] detection_eval = 12.127
-I0511 11:50:55.667565  5581 caffe.cpp:501] detection_eval = 0.0491096
-I0511 11:50:55.667570  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.667575  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.667579  5581 caffe.cpp:501] detection_eval = 4.57258
-I0511 11:50:55.667583  5581 caffe.cpp:501] detection_eval = 12.0565
-I0511 11:50:55.667588  5581 caffe.cpp:501] detection_eval = 0.0461282
-I0511 11:50:55.667593  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.667598  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667601  5581 caffe.cpp:501] detection_eval = 4.57258
-I0511 11:50:55.667606  5581 caffe.cpp:501] detection_eval = 12.131
-I0511 11:50:55.667610  5581 caffe.cpp:501] detection_eval = 0.044421
-I0511 11:50:55.667615  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667620  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.667624  5581 caffe.cpp:501] detection_eval = 4.5746
-I0511 11:50:55.667629  5581 caffe.cpp:501] detection_eval = 12.129
-I0511 11:50:55.667634  5581 caffe.cpp:501] detection_eval = 0.0402017
-I0511 11:50:55.667639  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667642  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.667647  5581 caffe.cpp:501] detection_eval = 4.5746
-I0511 11:50:55.667651  5581 caffe.cpp:501] detection_eval = 12.1915
-I0511 11:50:55.667656  5581 caffe.cpp:501] detection_eval = 0.0372778
-I0511 11:50:55.667660  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667665  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667670  5581 caffe.cpp:501] detection_eval = 4.57661
-I0511 11:50:55.667675  5581 caffe.cpp:501] detection_eval = 12.2359
-I0511 11:50:55.667678  5581 caffe.cpp:501] detection_eval = 0.0438748
-I0511 11:50:55.667683  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.667687  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667692  5581 caffe.cpp:501] detection_eval = 4.57661
-I0511 11:50:55.667696  5581 caffe.cpp:501] detection_eval = 12.3044
-I0511 11:50:55.667701  5581 caffe.cpp:501] detection_eval = 0.0404307
-I0511 11:50:55.667706  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667711  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667716  5581 caffe.cpp:501] detection_eval = 4.57863
-I0511 11:50:55.667719  5581 caffe.cpp:501] detection_eval = 12.3024
-I0511 11:50:55.667724  5581 caffe.cpp:501] detection_eval = 0.0437116
-I0511 11:50:55.667728  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667733  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667737  5581 caffe.cpp:501] detection_eval = 4.58065
-I0511 11:50:55.667742  5581 caffe.cpp:501] detection_eval = 12.3387
-I0511 11:50:55.667747  5581 caffe.cpp:501] detection_eval = 0.0399681
-I0511 11:50:55.667752  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667755  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.667760  5581 caffe.cpp:501] detection_eval = 4.58871
-I0511 11:50:55.667764  5581 caffe.cpp:501] detection_eval = 12.2581
-I0511 11:50:55.667769  5581 caffe.cpp:501] detection_eval = 0.0360596
-I0511 11:50:55.667773  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667778  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667783  5581 caffe.cpp:501] detection_eval = 4.58871
-I0511 11:50:55.667788  5581 caffe.cpp:501] detection_eval = 12.3125
-I0511 11:50:55.667791  5581 caffe.cpp:501] detection_eval = 0.0368753
-I0511 11:50:55.667795  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667798  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667799  5581 caffe.cpp:501] detection_eval = 4.59073
-I0511 11:50:55.667803  5581 caffe.cpp:501] detection_eval = 12.369
-I0511 11:50:55.667804  5581 caffe.cpp:501] detection_eval = 0.0376381
-I0511 11:50:55.667807  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667809  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.667811  5581 caffe.cpp:501] detection_eval = 4.59677
-I0511 11:50:55.667817  5581 caffe.cpp:501] detection_eval = 12.373
-I0511 11:50:55.667820  5581 caffe.cpp:501] detection_eval = 0.0410415
-I0511 11:50:55.667822  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.667824  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667826  5581 caffe.cpp:501] detection_eval = 4.60081
-I0511 11:50:55.667829  5581 caffe.cpp:501] detection_eval = 12.4234
-I0511 11:50:55.667831  5581 caffe.cpp:501] detection_eval = 0.0435586
-I0511 11:50:55.667834  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.667836  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667838  5581 caffe.cpp:501] detection_eval = 4.60081
-I0511 11:50:55.667840  5581 caffe.cpp:501] detection_eval = 12.4819
-I0511 11:50:55.667842  5581 caffe.cpp:501] detection_eval = 0.0419101
-I0511 11:50:55.667845  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667847  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667850  5581 caffe.cpp:501] detection_eval = 4.60081
-I0511 11:50:55.667851  5581 caffe.cpp:501] detection_eval = 12.5181
-I0511 11:50:55.667855  5581 caffe.cpp:501] detection_eval = 0.0393905
-I0511 11:50:55.667856  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667858  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.667860  5581 caffe.cpp:501] detection_eval = 4.60282
-I0511 11:50:55.667862  5581 caffe.cpp:501] detection_eval = 12.5444
-I0511 11:50:55.667865  5581 caffe.cpp:501] detection_eval = 0.0369975
-I0511 11:50:55.667867  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667870  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667871  5581 caffe.cpp:501] detection_eval = 4.60685
-I0511 11:50:55.667874  5581 caffe.cpp:501] detection_eval = 12.5343
-I0511 11:50:55.667876  5581 caffe.cpp:501] detection_eval = 0.0365329
-I0511 11:50:55.667878  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667881  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667883  5581 caffe.cpp:501] detection_eval = 4.61089
-I0511 11:50:55.667886  5581 caffe.cpp:501] detection_eval = 12.5484
-I0511 11:50:55.667887  5581 caffe.cpp:501] detection_eval = 0.0391375
-I0511 11:50:55.667889  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667891  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667894  5581 caffe.cpp:501] detection_eval = 4.6129
-I0511 11:50:55.667896  5581 caffe.cpp:501] detection_eval = 12.6008
-I0511 11:50:55.667898  5581 caffe.cpp:501] detection_eval = 0.0370847
-I0511 11:50:55.667901  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667903  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667906  5581 caffe.cpp:501] detection_eval = 4.61694
-I0511 11:50:55.667907  5581 caffe.cpp:501] detection_eval = 12.6089
-I0511 11:50:55.667909  5581 caffe.cpp:501] detection_eval = 0.0369866
-I0511 11:50:55.667912  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667914  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667917  5581 caffe.cpp:501] detection_eval = 4.61895
-I0511 11:50:55.667918  5581 caffe.cpp:501] detection_eval = 12.6351
-I0511 11:50:55.667920  5581 caffe.cpp:501] detection_eval = 0.0427287
-I0511 11:50:55.667922  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667925  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667927  5581 caffe.cpp:501] detection_eval = 4.625
-I0511 11:50:55.667929  5581 caffe.cpp:501] detection_eval = 12.5988
-I0511 11:50:55.667934  5581 caffe.cpp:501] detection_eval = 0.0338396
-I0511 11:50:55.667937  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.667939  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.667942  5581 caffe.cpp:501] detection_eval = 4.625
-I0511 11:50:55.667943  5581 caffe.cpp:501] detection_eval = 12.6754
-I0511 11:50:55.667945  5581 caffe.cpp:501] detection_eval = 0.0368577
-I0511 11:50:55.667948  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667950  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.667953  5581 caffe.cpp:501] detection_eval = 4.62903
-I0511 11:50:55.667958  5581 caffe.cpp:501] detection_eval = 12.6371
-I0511 11:50:55.667959  5581 caffe.cpp:501] detection_eval = 0.0340815
-I0511 11:50:55.667963  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667964  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667966  5581 caffe.cpp:501] detection_eval = 4.63306
-I0511 11:50:55.667968  5581 caffe.cpp:501] detection_eval = 12.6069
-I0511 11:50:55.667970  5581 caffe.cpp:501] detection_eval = 0.0356699
-I0511 11:50:55.667973  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667975  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667978  5581 caffe.cpp:501] detection_eval = 4.63306
-I0511 11:50:55.667979  5581 caffe.cpp:501] detection_eval = 12.6653
-I0511 11:50:55.667981  5581 caffe.cpp:501] detection_eval = 0.0346759
-I0511 11:50:55.667984  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667986  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667989  5581 caffe.cpp:501] detection_eval = 4.63508
-I0511 11:50:55.667990  5581 caffe.cpp:501] detection_eval = 12.6915
-I0511 11:50:55.667994  5581 caffe.cpp:501] detection_eval = 0.0398253
-I0511 11:50:55.667995  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667997  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.667999  5581 caffe.cpp:501] detection_eval = 4.6371
-I0511 11:50:55.668001  5581 caffe.cpp:501] detection_eval = 12.7258
-I0511 11:50:55.668004  5581 caffe.cpp:501] detection_eval = 0.0422131
-I0511 11:50:55.668006  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668009  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668010  5581 caffe.cpp:501] detection_eval = 4.64113
-I0511 11:50:55.668012  5581 caffe.cpp:501] detection_eval = 12.7117
-I0511 11:50:55.668015  5581 caffe.cpp:501] detection_eval = 0.0367614
-I0511 11:50:55.668017  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668020  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.668021  5581 caffe.cpp:501] detection_eval = 4.64113
-I0511 11:50:55.668023  5581 caffe.cpp:501] detection_eval = 12.748
-I0511 11:50:55.668026  5581 caffe.cpp:501] detection_eval = 0.0399707
-I0511 11:50:55.668028  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668030  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668032  5581 caffe.cpp:501] detection_eval = 4.64315
-I0511 11:50:55.668035  5581 caffe.cpp:501] detection_eval = 12.7661
-I0511 11:50:55.668037  5581 caffe.cpp:501] detection_eval = 0.0411466
-I0511 11:50:55.668040  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668041  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668043  5581 caffe.cpp:501] detection_eval = 4.64718
-I0511 11:50:55.668045  5581 caffe.cpp:501] detection_eval = 12.7742
-I0511 11:50:55.668048  5581 caffe.cpp:501] detection_eval = 0.0421279
-I0511 11:50:55.668051  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668052  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668054  5581 caffe.cpp:501] detection_eval = 4.65121
-I0511 11:50:55.668056  5581 caffe.cpp:501] detection_eval = 12.7923
-I0511 11:50:55.668059  5581 caffe.cpp:501] detection_eval = 0.0409486
-I0511 11:50:55.668061  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668063  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668066  5581 caffe.cpp:501] detection_eval = 4.65927
-I0511 11:50:55.668068  5581 caffe.cpp:501] detection_eval = 12.7399
-I0511 11:50:55.668071  5581 caffe.cpp:501] detection_eval = 0.0392662
-I0511 11:50:55.668072  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668076  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668077  5581 caffe.cpp:501] detection_eval = 4.66532
-I0511 11:50:55.668079  5581 caffe.cpp:501] detection_eval = 12.7238
-I0511 11:50:55.668081  5581 caffe.cpp:501] detection_eval = 0.0405585
-I0511 11:50:55.668083  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668087  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668090  5581 caffe.cpp:501] detection_eval = 4.66935
-I0511 11:50:55.668092  5581 caffe.cpp:501] detection_eval = 12.7278
-I0511 11:50:55.668095  5581 caffe.cpp:501] detection_eval = 0.0404869
-I0511 11:50:55.668097  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668099  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668102  5581 caffe.cpp:501] detection_eval = 4.67137
-I0511 11:50:55.668103  5581 caffe.cpp:501] detection_eval = 12.7964
-I0511 11:50:55.668107  5581 caffe.cpp:501] detection_eval = 0.0449684
-I0511 11:50:55.668108  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668110  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668112  5581 caffe.cpp:501] detection_eval = 4.67339
-I0511 11:50:55.668114  5581 caffe.cpp:501] detection_eval = 12.8347
-I0511 11:50:55.668118  5581 caffe.cpp:501] detection_eval = 0.0470513
-I0511 11:50:55.668119  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668121  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668123  5581 caffe.cpp:501] detection_eval = 4.67339
-I0511 11:50:55.668125  5581 caffe.cpp:501] detection_eval = 12.8992
-I0511 11:50:55.668128  5581 caffe.cpp:501] detection_eval = 0.0420022
-I0511 11:50:55.668130  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668133  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668135  5581 caffe.cpp:501] detection_eval = 4.67944
-I0511 11:50:55.668138  5581 caffe.cpp:501] detection_eval = 12.9435
-I0511 11:50:55.668140  5581 caffe.cpp:501] detection_eval = 0.0400056
-I0511 11:50:55.668144  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668148  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668149  5581 caffe.cpp:501] detection_eval = 4.68145
-I0511 11:50:55.668151  5581 caffe.cpp:501] detection_eval = 13
-I0511 11:50:55.668154  5581 caffe.cpp:501] detection_eval = 0.0423659
-I0511 11:50:55.668156  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668159  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668161  5581 caffe.cpp:501] detection_eval = 4.68347
-I0511 11:50:55.668164  5581 caffe.cpp:501] detection_eval = 13.1532
-I0511 11:50:55.668165  5581 caffe.cpp:501] detection_eval = 0.0435836
-I0511 11:50:55.668167  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668169  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668172  5581 caffe.cpp:501] detection_eval = 4.6875
-I0511 11:50:55.668174  5581 caffe.cpp:501] detection_eval = 13.2419
-I0511 11:50:55.668176  5581 caffe.cpp:501] detection_eval = 0.0409402
-I0511 11:50:55.668179  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668181  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668184  5581 caffe.cpp:501] detection_eval = 4.69153
-I0511 11:50:55.668185  5581 caffe.cpp:501] detection_eval = 13.377
-I0511 11:50:55.668187  5581 caffe.cpp:501] detection_eval = 0.0397732
-I0511 11:50:55.668190  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668192  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668195  5581 caffe.cpp:501] detection_eval = 4.69758
-I0511 11:50:55.668197  5581 caffe.cpp:501] detection_eval = 13.6149
-I0511 11:50:55.668200  5581 caffe.cpp:501] detection_eval = 0.0355242
-I0511 11:50:55.668201  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668203  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.668206  5581 caffe.cpp:501] detection_eval = 5.13306
-I0511 11:50:55.668208  5581 caffe.cpp:501] detection_eval = 7.21774
-I0511 11:50:55.668210  5581 caffe.cpp:501] detection_eval = 0.083593
-I0511 11:50:55.668212  5581 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:50:55.668215  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.668216  5581 caffe.cpp:501] detection_eval = 5.13508
-I0511 11:50:55.668220  5581 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:50:55.668221  5581 caffe.cpp:501] detection_eval = 0.0686604
-I0511 11:50:55.668223  5581 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:50:55.668228  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.668231  5581 caffe.cpp:501] detection_eval = 5.13508
-I0511 11:50:55.668232  5581 caffe.cpp:501] detection_eval = 7.62702
-I0511 11:50:55.668236  5581 caffe.cpp:501] detection_eval = 0.0638157
-I0511 11:50:55.668237  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.668239  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668241  5581 caffe.cpp:501] detection_eval = 5.13508
-I0511 11:50:55.668243  5581 caffe.cpp:501] detection_eval = 7.75403
-I0511 11:50:55.668246  5581 caffe.cpp:501] detection_eval = 0.0532077
-I0511 11:50:55.668248  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.668251  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.668253  5581 caffe.cpp:501] detection_eval = 5.14113
-I0511 11:50:55.668256  5581 caffe.cpp:501] detection_eval = 7.79032
-I0511 11:50:55.668257  5581 caffe.cpp:501] detection_eval = 0.0506467
-I0511 11:50:55.668259  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.668262  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668264  5581 caffe.cpp:501] detection_eval = 5.14315
-I0511 11:50:55.668267  5581 caffe.cpp:501] detection_eval = 7.85081
-I0511 11:50:55.668268  5581 caffe.cpp:501] detection_eval = 0.0490163
-I0511 11:50:55.668270  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668272  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668275  5581 caffe.cpp:501] detection_eval = 5.14516
-I0511 11:50:55.668277  5581 caffe.cpp:501] detection_eval = 7.88508
-I0511 11:50:55.668279  5581 caffe.cpp:501] detection_eval = 0.0515722
-I0511 11:50:55.668282  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.668283  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668285  5581 caffe.cpp:501] detection_eval = 5.14718
-I0511 11:50:55.668288  5581 caffe.cpp:501] detection_eval = 7.94355
-I0511 11:50:55.668290  5581 caffe.cpp:501] detection_eval = 0.0459141
-I0511 11:50:55.668292  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668294  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668296  5581 caffe.cpp:501] detection_eval = 5.14919
-I0511 11:50:55.668298  5581 caffe.cpp:501] detection_eval = 7.99194
-I0511 11:50:55.668301  5581 caffe.cpp:501] detection_eval = 0.0476944
-I0511 11:50:55.668303  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.668305  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.668308  5581 caffe.cpp:501] detection_eval = 5.15524
-I0511 11:50:55.668309  5581 caffe.cpp:501] detection_eval = 8.01613
-I0511 11:50:55.668313  5581 caffe.cpp:501] detection_eval = 0.0487789
-I0511 11:50:55.668314  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668316  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668318  5581 caffe.cpp:501] detection_eval = 5.15726
-I0511 11:50:55.668320  5581 caffe.cpp:501] detection_eval = 8.06452
-I0511 11:50:55.668323  5581 caffe.cpp:501] detection_eval = 0.0494443
-I0511 11:50:55.668325  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668328  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668329  5581 caffe.cpp:501] detection_eval = 5.15726
-I0511 11:50:55.668331  5581 caffe.cpp:501] detection_eval = 8.15726
-I0511 11:50:55.668334  5581 caffe.cpp:501] detection_eval = 0.0519537
-I0511 11:50:55.668336  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.668339  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.668340  5581 caffe.cpp:501] detection_eval = 5.15927
-I0511 11:50:55.668342  5581 caffe.cpp:501] detection_eval = 8.17339
-I0511 11:50:55.668345  5581 caffe.cpp:501] detection_eval = 0.0487953
-I0511 11:50:55.668347  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668349  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668351  5581 caffe.cpp:501] detection_eval = 5.16331
-I0511 11:50:55.668354  5581 caffe.cpp:501] detection_eval = 8.18145
-I0511 11:50:55.668355  5581 caffe.cpp:501] detection_eval = 0.0461852
-I0511 11:50:55.668359  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668362  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668365  5581 caffe.cpp:501] detection_eval = 5.16532
-I0511 11:50:55.668367  5581 caffe.cpp:501] detection_eval = 8.23589
-I0511 11:50:55.668370  5581 caffe.cpp:501] detection_eval = 0.0456467
-I0511 11:50:55.668371  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668373  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668376  5581 caffe.cpp:501] detection_eval = 5.16734
-I0511 11:50:55.668378  5581 caffe.cpp:501] detection_eval = 8.28226
-I0511 11:50:55.668380  5581 caffe.cpp:501] detection_eval = 0.0411408
-I0511 11:50:55.668383  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.668385  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.668387  5581 caffe.cpp:501] detection_eval = 5.17137
-I0511 11:50:55.668390  5581 caffe.cpp:501] detection_eval = 8.31855
-I0511 11:50:55.668392  5581 caffe.cpp:501] detection_eval = 0.0467666
-I0511 11:50:55.668395  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668396  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668400  5581 caffe.cpp:501] detection_eval = 5.17137
-I0511 11:50:55.668401  5581 caffe.cpp:501] detection_eval = 8.4254
-I0511 11:50:55.668403  5581 caffe.cpp:501] detection_eval = 0.0439995
-I0511 11:50:55.668406  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668408  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668411  5581 caffe.cpp:501] detection_eval = 5.1754
-I0511 11:50:55.668412  5581 caffe.cpp:501] detection_eval = 8.45161
-I0511 11:50:55.668414  5581 caffe.cpp:501] detection_eval = 0.0518023
-I0511 11:50:55.668417  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668419  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668421  5581 caffe.cpp:501] detection_eval = 5.17742
-I0511 11:50:55.668423  5581 caffe.cpp:501] detection_eval = 8.50605
-I0511 11:50:55.668426  5581 caffe.cpp:501] detection_eval = 0.0514247
-I0511 11:50:55.668427  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668431  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668432  5581 caffe.cpp:501] detection_eval = 5.18145
-I0511 11:50:55.668434  5581 caffe.cpp:501] detection_eval = 8.47984
-I0511 11:50:55.668437  5581 caffe.cpp:501] detection_eval = 0.0472633
-I0511 11:50:55.668439  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668442  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668443  5581 caffe.cpp:501] detection_eval = 5.18145
-I0511 11:50:55.668445  5581 caffe.cpp:501] detection_eval = 8.53629
-I0511 11:50:55.668447  5581 caffe.cpp:501] detection_eval = 0.0406202
-I0511 11:50:55.668450  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.668452  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.668454  5581 caffe.cpp:501] detection_eval = 5.18347
-I0511 11:50:55.668457  5581 caffe.cpp:501] detection_eval = 8.61895
-I0511 11:50:55.668458  5581 caffe.cpp:501] detection_eval = 0.0442999
-I0511 11:50:55.668460  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668463  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668465  5581 caffe.cpp:501] detection_eval = 5.19758
-I0511 11:50:55.668468  5581 caffe.cpp:501] detection_eval = 8.47581
-I0511 11:50:55.668470  5581 caffe.cpp:501] detection_eval = 0.0477267
-I0511 11:50:55.668473  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668474  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668478  5581 caffe.cpp:501] detection_eval = 5.20363
-I0511 11:50:55.668479  5581 caffe.cpp:501] detection_eval = 8.42944
-I0511 11:50:55.668481  5581 caffe.cpp:501] detection_eval = 0.045115
-I0511 11:50:55.668483  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668485  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668488  5581 caffe.cpp:501] detection_eval = 5.20565
-I0511 11:50:55.668490  5581 caffe.cpp:501] detection_eval = 8.51008
-I0511 11:50:55.668493  5581 caffe.cpp:501] detection_eval = 0.044696
-I0511 11:50:55.668498  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668499  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668501  5581 caffe.cpp:501] detection_eval = 5.21169
-I0511 11:50:55.668503  5581 caffe.cpp:501] detection_eval = 8.48185
-I0511 11:50:55.668506  5581 caffe.cpp:501] detection_eval = 0.0442546
-I0511 11:50:55.668509  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668510  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668512  5581 caffe.cpp:501] detection_eval = 5.21371
-I0511 11:50:55.668514  5581 caffe.cpp:501] detection_eval = 8.52218
-I0511 11:50:55.668516  5581 caffe.cpp:501] detection_eval = 0.0434062
-I0511 11:50:55.668519  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668521  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668529  5581 caffe.cpp:501] detection_eval = 5.21774
-I0511 11:50:55.668531  5581 caffe.cpp:501] detection_eval = 8.5121
-I0511 11:50:55.668534  5581 caffe.cpp:501] detection_eval = 0.0414134
-I0511 11:50:55.668535  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668537  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668540  5581 caffe.cpp:501] detection_eval = 5.22177
-I0511 11:50:55.668542  5581 caffe.cpp:501] detection_eval = 8.50403
-I0511 11:50:55.668545  5581 caffe.cpp:501] detection_eval = 0.0423669
-I0511 11:50:55.668546  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668548  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668551  5581 caffe.cpp:501] detection_eval = 5.22379
-I0511 11:50:55.668553  5581 caffe.cpp:501] detection_eval = 8.53629
-I0511 11:50:55.668555  5581 caffe.cpp:501] detection_eval = 0.0402759
-I0511 11:50:55.668557  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668560  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668562  5581 caffe.cpp:501] detection_eval = 5.22581
-I0511 11:50:55.668565  5581 caffe.cpp:501] detection_eval = 8.56855
-I0511 11:50:55.668566  5581 caffe.cpp:501] detection_eval = 0.0421297
-I0511 11:50:55.668568  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668571  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668573  5581 caffe.cpp:501] detection_eval = 5.22782
-I0511 11:50:55.668576  5581 caffe.cpp:501] detection_eval = 8.60887
-I0511 11:50:55.668577  5581 caffe.cpp:501] detection_eval = 0.0462904
-I0511 11:50:55.668579  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668582  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668584  5581 caffe.cpp:501] detection_eval = 5.22984
-I0511 11:50:55.668586  5581 caffe.cpp:501] detection_eval = 8.65726
-I0511 11:50:55.668588  5581 caffe.cpp:501] detection_eval = 0.0466748
-I0511 11:50:55.668591  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.668593  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.668596  5581 caffe.cpp:501] detection_eval = 5.22984
-I0511 11:50:55.668597  5581 caffe.cpp:501] detection_eval = 8.7379
-I0511 11:50:55.668599  5581 caffe.cpp:501] detection_eval = 0.0410906
-I0511 11:50:55.668601  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668604  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668606  5581 caffe.cpp:501] detection_eval = 5.23185
-I0511 11:50:55.668608  5581 caffe.cpp:501] detection_eval = 8.77218
-I0511 11:50:55.668611  5581 caffe.cpp:501] detection_eval = 0.0426186
-I0511 11:50:55.668612  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668615  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668617  5581 caffe.cpp:501] detection_eval = 5.23387
-I0511 11:50:55.668619  5581 caffe.cpp:501] detection_eval = 8.80645
-I0511 11:50:55.668622  5581 caffe.cpp:501] detection_eval = 0.0417548
-I0511 11:50:55.668624  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668627  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668629  5581 caffe.cpp:501] detection_eval = 5.23387
-I0511 11:50:55.668632  5581 caffe.cpp:501] detection_eval = 8.93145
-I0511 11:50:55.668637  5581 caffe.cpp:501] detection_eval = 0.0471477
-I0511 11:50:55.668639  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668642  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668643  5581 caffe.cpp:501] detection_eval = 5.2379
-I0511 11:50:55.668646  5581 caffe.cpp:501] detection_eval = 9.00806
-I0511 11:50:55.668648  5581 caffe.cpp:501] detection_eval = 0.0530266
-I0511 11:50:55.668650  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668653  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668655  5581 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:50:55.668658  5581 caffe.cpp:501] detection_eval = 8.96976
-I0511 11:50:55.668659  5581 caffe.cpp:501] detection_eval = 0.0465821
-I0511 11:50:55.668661  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668663  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668666  5581 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:50:55.668668  5581 caffe.cpp:501] detection_eval = 9.02621
-I0511 11:50:55.668670  5581 caffe.cpp:501] detection_eval = 0.0416271
-I0511 11:50:55.668673  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668675  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.668678  5581 caffe.cpp:501] detection_eval = 5.24597
-I0511 11:50:55.668679  5581 caffe.cpp:501] detection_eval = 9.10685
-I0511 11:50:55.668682  5581 caffe.cpp:501] detection_eval = 0.0442582
-I0511 11:50:55.668684  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668686  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668689  5581 caffe.cpp:501] detection_eval = 5.25
-I0511 11:50:55.668691  5581 caffe.cpp:501] detection_eval = 9.13306
-I0511 11:50:55.668694  5581 caffe.cpp:501] detection_eval = 0.0430844
-I0511 11:50:55.668695  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668699  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.668700  5581 caffe.cpp:501] detection_eval = 5.25403
-I0511 11:50:55.668702  5581 caffe.cpp:501] detection_eval = 9.17137
-I0511 11:50:55.668704  5581 caffe.cpp:501] detection_eval = 0.0411147
-I0511 11:50:55.668707  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668709  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668711  5581 caffe.cpp:501] detection_eval = 5.25403
-I0511 11:50:55.668714  5581 caffe.cpp:501] detection_eval = 9.22379
-I0511 11:50:55.668716  5581 caffe.cpp:501] detection_eval = 0.0439104
-I0511 11:50:55.668718  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668720  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668722  5581 caffe.cpp:501] detection_eval = 5.25605
-I0511 11:50:55.668725  5581 caffe.cpp:501] detection_eval = 9.33266
-I0511 11:50:55.668727  5581 caffe.cpp:501] detection_eval = 0.0474289
-I0511 11:50:55.668730  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668731  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668733  5581 caffe.cpp:501] detection_eval = 5.25605
-I0511 11:50:55.668736  5581 caffe.cpp:501] detection_eval = 9.41935
-I0511 11:50:55.668738  5581 caffe.cpp:501] detection_eval = 0.0444779
-I0511 11:50:55.668740  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668742  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668745  5581 caffe.cpp:501] detection_eval = 5.26008
-I0511 11:50:55.668747  5581 caffe.cpp:501] detection_eval = 9.44355
-I0511 11:50:55.668750  5581 caffe.cpp:501] detection_eval = 0.0479086
-I0511 11:50:55.668751  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668754  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668756  5581 caffe.cpp:501] detection_eval = 5.26613
-I0511 11:50:55.668758  5581 caffe.cpp:501] detection_eval = 9.38911
-I0511 11:50:55.668761  5581 caffe.cpp:501] detection_eval = 0.0470021
-I0511 11:50:55.668762  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668766  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668767  5581 caffe.cpp:501] detection_eval = 5.26613
-I0511 11:50:55.668769  5581 caffe.cpp:501] detection_eval = 9.4496
-I0511 11:50:55.668774  5581 caffe.cpp:501] detection_eval = 0.0433997
-I0511 11:50:55.668776  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668778  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668781  5581 caffe.cpp:501] detection_eval = 5.26815
-I0511 11:50:55.668783  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.668786  5581 caffe.cpp:501] detection_eval = 0.0450501
-I0511 11:50:55.668787  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668789  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668792  5581 caffe.cpp:501] detection_eval = 5.27218
-I0511 11:50:55.668794  5581 caffe.cpp:501] detection_eval = 9.58468
-I0511 11:50:55.668797  5581 caffe.cpp:501] detection_eval = 0.0429084
-I0511 11:50:55.668798  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668800  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668803  5581 caffe.cpp:501] detection_eval = 5.27218
-I0511 11:50:55.668805  5581 caffe.cpp:501] detection_eval = 9.64516
-I0511 11:50:55.668807  5581 caffe.cpp:501] detection_eval = 0.0422002
-I0511 11:50:55.668809  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668812  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668814  5581 caffe.cpp:501] detection_eval = 5.27823
-I0511 11:50:55.668817  5581 caffe.cpp:501] detection_eval = 9.59476
-I0511 11:50:55.668819  5581 caffe.cpp:501] detection_eval = 0.0405412
-I0511 11:50:55.668822  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668823  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668825  5581 caffe.cpp:501] detection_eval = 5.27823
-I0511 11:50:55.668828  5581 caffe.cpp:501] detection_eval = 9.68952
-I0511 11:50:55.668830  5581 caffe.cpp:501] detection_eval = 0.0440439
-I0511 11:50:55.668833  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668834  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668836  5581 caffe.cpp:501] detection_eval = 5.28024
-I0511 11:50:55.668839  5581 caffe.cpp:501] detection_eval = 9.72177
-I0511 11:50:55.668841  5581 caffe.cpp:501] detection_eval = 0.0416299
-I0511 11:50:55.668843  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668845  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668848  5581 caffe.cpp:501] detection_eval = 5.28226
-I0511 11:50:55.668849  5581 caffe.cpp:501] detection_eval = 9.80847
-I0511 11:50:55.668853  5581 caffe.cpp:501] detection_eval = 0.0423391
-I0511 11:50:55.668854  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668856  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668859  5581 caffe.cpp:501] detection_eval = 5.28226
-I0511 11:50:55.668861  5581 caffe.cpp:501] detection_eval = 9.87903
-I0511 11:50:55.668864  5581 caffe.cpp:501] detection_eval = 0.0398229
-I0511 11:50:55.668865  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668867  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.668870  5581 caffe.cpp:501] detection_eval = 5.28427
-I0511 11:50:55.668872  5581 caffe.cpp:501] detection_eval = 9.93952
-I0511 11:50:55.668875  5581 caffe.cpp:501] detection_eval = 0.0441284
-I0511 11:50:55.668877  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668879  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668882  5581 caffe.cpp:501] detection_eval = 5.28629
-I0511 11:50:55.668884  5581 caffe.cpp:501] detection_eval = 9.98992
-I0511 11:50:55.668886  5581 caffe.cpp:501] detection_eval = 0.0474331
-I0511 11:50:55.668889  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668891  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668893  5581 caffe.cpp:501] detection_eval = 5.29234
-I0511 11:50:55.668895  5581 caffe.cpp:501] detection_eval = 10.0081
-I0511 11:50:55.668898  5581 caffe.cpp:501] detection_eval = 0.0480445
-I0511 11:50:55.668900  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668902  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668905  5581 caffe.cpp:501] detection_eval = 5.29839
-I0511 11:50:55.668910  5581 caffe.cpp:501] detection_eval = 9.98185
-I0511 11:50:55.668912  5581 caffe.cpp:501] detection_eval = 0.048949
-I0511 11:50:55.668915  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668917  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668920  5581 caffe.cpp:501] detection_eval = 5.30242
-I0511 11:50:55.668921  5581 caffe.cpp:501] detection_eval = 9.98185
-I0511 11:50:55.668923  5581 caffe.cpp:501] detection_eval = 0.0434407
-I0511 11:50:55.668926  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.668928  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.668931  5581 caffe.cpp:501] detection_eval = 5.30847
-I0511 11:50:55.668933  5581 caffe.cpp:501] detection_eval = 9.97581
-I0511 11:50:55.668936  5581 caffe.cpp:501] detection_eval = 0.042905
-I0511 11:50:55.668941  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668944  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668947  5581 caffe.cpp:501] detection_eval = 5.31048
-I0511 11:50:55.668951  5581 caffe.cpp:501] detection_eval = 10.0524
-I0511 11:50:55.668952  5581 caffe.cpp:501] detection_eval = 0.0485621
-I0511 11:50:55.668954  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668956  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668958  5581 caffe.cpp:501] detection_eval = 5.31452
-I0511 11:50:55.668962  5581 caffe.cpp:501] detection_eval = 10.1008
-I0511 11:50:55.668963  5581 caffe.cpp:501] detection_eval = 0.0470324
-I0511 11:50:55.668965  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668967  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668970  5581 caffe.cpp:501] detection_eval = 5.31653
-I0511 11:50:55.668972  5581 caffe.cpp:501] detection_eval = 10.1613
-I0511 11:50:55.668974  5581 caffe.cpp:501] detection_eval = 0.043986
-I0511 11:50:55.668977  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668979  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668982  5581 caffe.cpp:501] detection_eval = 5.31653
-I0511 11:50:55.668983  5581 caffe.cpp:501] detection_eval = 10.252
-I0511 11:50:55.668985  5581 caffe.cpp:501] detection_eval = 0.047543
-I0511 11:50:55.668988  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668990  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668992  5581 caffe.cpp:501] detection_eval = 5.31855
-I0511 11:50:55.668994  5581 caffe.cpp:501] detection_eval = 10.2641
-I0511 11:50:55.668998  5581 caffe.cpp:501] detection_eval = 0.0483524
-I0511 11:50:55.668999  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669001  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669003  5581 caffe.cpp:501] detection_eval = 5.32661
-I0511 11:50:55.669005  5581 caffe.cpp:501] detection_eval = 10.248
-I0511 11:50:55.669008  5581 caffe.cpp:501] detection_eval = 0.0499154
-I0511 11:50:55.669010  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669013  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669014  5581 caffe.cpp:501] detection_eval = 5.33065
-I0511 11:50:55.669016  5581 caffe.cpp:501] detection_eval = 10.2399
-I0511 11:50:55.669019  5581 caffe.cpp:501] detection_eval = 0.0430064
-I0511 11:50:55.669021  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669023  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669025  5581 caffe.cpp:501] detection_eval = 5.34073
-I0511 11:50:55.669028  5581 caffe.cpp:501] detection_eval = 10.1734
-I0511 11:50:55.669030  5581 caffe.cpp:501] detection_eval = 0.0436573
-I0511 11:50:55.669032  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669034  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669037  5581 caffe.cpp:501] detection_eval = 5.34274
-I0511 11:50:55.669039  5581 caffe.cpp:501] detection_eval = 10.246
-I0511 11:50:55.669041  5581 caffe.cpp:501] detection_eval = 0.043249
-I0511 11:50:55.669044  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669046  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669049  5581 caffe.cpp:501] detection_eval = 5.35081
-I0511 11:50:55.669054  5581 caffe.cpp:501] detection_eval = 10.1875
-I0511 11:50:55.669057  5581 caffe.cpp:501] detection_eval = 0.0414232
-I0511 11:50:55.669059  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669061  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669064  5581 caffe.cpp:501] detection_eval = 5.35484
-I0511 11:50:55.669065  5581 caffe.cpp:501] detection_eval = 10.246
-I0511 11:50:55.669068  5581 caffe.cpp:501] detection_eval = 0.0454759
-I0511 11:50:55.669070  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.669073  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.669075  5581 caffe.cpp:501] detection_eval = 5.35887
-I0511 11:50:55.669077  5581 caffe.cpp:501] detection_eval = 10.248
-I0511 11:50:55.669080  5581 caffe.cpp:501] detection_eval = 0.0448357
-I0511 11:50:55.669081  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669085  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669086  5581 caffe.cpp:501] detection_eval = 5.36089
-I0511 11:50:55.669088  5581 caffe.cpp:501] detection_eval = 10.3145
-I0511 11:50:55.669091  5581 caffe.cpp:501] detection_eval = 0.0508685
-I0511 11:50:55.669093  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669095  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669097  5581 caffe.cpp:501] detection_eval = 5.36492
-I0511 11:50:55.669100  5581 caffe.cpp:501] detection_eval = 10.3044
-I0511 11:50:55.669102  5581 caffe.cpp:501] detection_eval = 0.0464236
-I0511 11:50:55.669104  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669106  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.669108  5581 caffe.cpp:501] detection_eval = 5.36895
-I0511 11:50:55.669111  5581 caffe.cpp:501] detection_eval = 10.2964
-I0511 11:50:55.669113  5581 caffe.cpp:501] detection_eval = 0.0446635
-I0511 11:50:55.669116  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669117  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669119  5581 caffe.cpp:501] detection_eval = 5.375
-I0511 11:50:55.669121  5581 caffe.cpp:501] detection_eval = 10.3004
-I0511 11:50:55.669124  5581 caffe.cpp:501] detection_eval = 0.0434711
-I0511 11:50:55.669126  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669128  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669131  5581 caffe.cpp:501] detection_eval = 5.37702
-I0511 11:50:55.669132  5581 caffe.cpp:501] detection_eval = 10.371
-I0511 11:50:55.669136  5581 caffe.cpp:501] detection_eval = 0.0435071
-I0511 11:50:55.669137  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669139  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669142  5581 caffe.cpp:501] detection_eval = 5.37903
-I0511 11:50:55.669144  5581 caffe.cpp:501] detection_eval = 10.4516
-I0511 11:50:55.669147  5581 caffe.cpp:501] detection_eval = 0.0447716
-I0511 11:50:55.669148  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669150  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669152  5581 caffe.cpp:501] detection_eval = 5.38508
-I0511 11:50:55.669155  5581 caffe.cpp:501] detection_eval = 10.4577
-I0511 11:50:55.669157  5581 caffe.cpp:501] detection_eval = 0.045388
-I0511 11:50:55.669159  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669162  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669164  5581 caffe.cpp:501] detection_eval = 5.38911
-I0511 11:50:55.669167  5581 caffe.cpp:501] detection_eval = 10.5242
-I0511 11:50:55.669168  5581 caffe.cpp:501] detection_eval = 0.0461074
-I0511 11:50:55.669172  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669173  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669175  5581 caffe.cpp:501] detection_eval = 5.39718
-I0511 11:50:55.669178  5581 caffe.cpp:501] detection_eval = 10.4859
-I0511 11:50:55.669180  5581 caffe.cpp:501] detection_eval = 0.0467653
-I0511 11:50:55.669183  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669184  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669189  5581 caffe.cpp:501] detection_eval = 5.39718
-I0511 11:50:55.669191  5581 caffe.cpp:501] detection_eval = 10.5927
-I0511 11:50:55.669194  5581 caffe.cpp:501] detection_eval = 0.0469085
-I0511 11:50:55.669196  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669198  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669200  5581 caffe.cpp:501] detection_eval = 5.40323
-I0511 11:50:55.669203  5581 caffe.cpp:501] detection_eval = 10.5927
-I0511 11:50:55.669205  5581 caffe.cpp:501] detection_eval = 0.0469142
-I0511 11:50:55.669208  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669209  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669211  5581 caffe.cpp:501] detection_eval = 5.40726
-I0511 11:50:55.669214  5581 caffe.cpp:501] detection_eval = 10.6169
-I0511 11:50:55.669216  5581 caffe.cpp:501] detection_eval = 0.0497463
-I0511 11:50:55.669219  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669220  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669224  5581 caffe.cpp:501] detection_eval = 5.41129
-I0511 11:50:55.669225  5581 caffe.cpp:501] detection_eval = 10.6391
-I0511 11:50:55.669229  5581 caffe.cpp:501] detection_eval = 0.0516768
-I0511 11:50:55.669230  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669232  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669234  5581 caffe.cpp:501] detection_eval = 5.41129
-I0511 11:50:55.669236  5581 caffe.cpp:501] detection_eval = 10.744
-I0511 11:50:55.669239  5581 caffe.cpp:501] detection_eval = 0.0503277
-I0511 11:50:55.669241  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669243  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669245  5581 caffe.cpp:501] detection_eval = 5.41532
-I0511 11:50:55.669248  5581 caffe.cpp:501] detection_eval = 10.756
-I0511 11:50:55.669250  5581 caffe.cpp:501] detection_eval = 0.0503253
-I0511 11:50:55.669252  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669255  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669256  5581 caffe.cpp:501] detection_eval = 5.41935
-I0511 11:50:55.669260  5581 caffe.cpp:501] detection_eval = 10.7278
-I0511 11:50:55.669261  5581 caffe.cpp:501] detection_eval = 0.0467886
-I0511 11:50:55.669263  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669265  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669268  5581 caffe.cpp:501] detection_eval = 5.42137
-I0511 11:50:55.669270  5581 caffe.cpp:501] detection_eval = 10.7702
-I0511 11:50:55.669272  5581 caffe.cpp:501] detection_eval = 0.0471315
-I0511 11:50:55.669275  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669276  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669279  5581 caffe.cpp:501] detection_eval = 5.4254
-I0511 11:50:55.669281  5581 caffe.cpp:501] detection_eval = 10.752
-I0511 11:50:55.669283  5581 caffe.cpp:501] detection_eval = 0.0403206
-I0511 11:50:55.669286  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.669288  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669291  5581 caffe.cpp:501] detection_eval = 5.43347
-I0511 11:50:55.669292  5581 caffe.cpp:501] detection_eval = 10.6895
-I0511 11:50:55.669296  5581 caffe.cpp:501] detection_eval = 0.0403499
-I0511 11:50:55.669297  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669299  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669302  5581 caffe.cpp:501] detection_eval = 5.43548
-I0511 11:50:55.669304  5581 caffe.cpp:501] detection_eval = 10.7319
-I0511 11:50:55.669306  5581 caffe.cpp:501] detection_eval = 0.0390869
-I0511 11:50:55.669308  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669312  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669313  5581 caffe.cpp:501] detection_eval = 5.4375
-I0511 11:50:55.669315  5581 caffe.cpp:501] detection_eval = 10.8004
-I0511 11:50:55.669318  5581 caffe.cpp:501] detection_eval = 0.0409101
-I0511 11:50:55.669320  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669327  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669330  5581 caffe.cpp:501] detection_eval = 5.44758
-I0511 11:50:55.669332  5581 caffe.cpp:501] detection_eval = 10.7278
-I0511 11:50:55.669334  5581 caffe.cpp:501] detection_eval = 0.0428666
-I0511 11:50:55.669337  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669339  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669342  5581 caffe.cpp:501] detection_eval = 5.45161
-I0511 11:50:55.669343  5581 caffe.cpp:501] detection_eval = 10.754
-I0511 11:50:55.669345  5581 caffe.cpp:501] detection_eval = 0.0514215
-I0511 11:50:55.669348  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669350  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669353  5581 caffe.cpp:501] detection_eval = 5.45968
-I0511 11:50:55.669354  5581 caffe.cpp:501] detection_eval = 10.6956
-I0511 11:50:55.669358  5581 caffe.cpp:501] detection_eval = 0.0517602
-I0511 11:50:55.669359  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669361  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669363  5581 caffe.cpp:501] detection_eval = 5.46976
-I0511 11:50:55.669365  5581 caffe.cpp:501] detection_eval = 10.5988
-I0511 11:50:55.669368  5581 caffe.cpp:501] detection_eval = 0.0470854
-I0511 11:50:55.669370  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669373  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669375  5581 caffe.cpp:501] detection_eval = 5.46976
-I0511 11:50:55.669379  5581 caffe.cpp:501] detection_eval = 10.6532
-I0511 11:50:55.669384  5581 caffe.cpp:501] detection_eval = 0.0442673
-I0511 11:50:55.669386  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669390  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669400  5581 caffe.cpp:501] detection_eval = 5.47379
-I0511 11:50:55.669404  5581 caffe.cpp:501] detection_eval = 10.6694
-I0511 11:50:55.669406  5581 caffe.cpp:501] detection_eval = 0.0429766
-I0511 11:50:55.669409  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669411  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669414  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.669415  5581 caffe.cpp:501] detection_eval = 10.6351
-I0511 11:50:55.669417  5581 caffe.cpp:501] detection_eval = 0.0445091
-I0511 11:50:55.669420  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669422  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669425  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.669426  5581 caffe.cpp:501] detection_eval = 10.7056
-I0511 11:50:55.669428  5581 caffe.cpp:501] detection_eval = 0.041474
-I0511 11:50:55.669431  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669433  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669435  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.669437  5581 caffe.cpp:501] detection_eval = 10.7661
-I0511 11:50:55.669440  5581 caffe.cpp:501] detection_eval = 0.0445598
-I0511 11:50:55.669442  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669445  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669446  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.669448  5581 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:50:55.669451  5581 caffe.cpp:501] detection_eval = 0.046457
-I0511 11:50:55.669453  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669456  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669457  5581 caffe.cpp:501] detection_eval = 5.48387
-I0511 11:50:55.669461  5581 caffe.cpp:501] detection_eval = 10.8589
-I0511 11:50:55.669462  5581 caffe.cpp:501] detection_eval = 0.0519797
-I0511 11:50:55.669464  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.669466  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.669469  5581 caffe.cpp:501] detection_eval = 5.48589
-I0511 11:50:55.669471  5581 caffe.cpp:501] detection_eval = 10.9032
-I0511 11:50:55.669473  5581 caffe.cpp:501] detection_eval = 0.0435595
-I0511 11:50:55.669476  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669481  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669483  5581 caffe.cpp:501] detection_eval = 5.4879
-I0511 11:50:55.669486  5581 caffe.cpp:501] detection_eval = 10.9657
-I0511 11:50:55.669487  5581 caffe.cpp:501] detection_eval = 0.0442254
-I0511 11:50:55.669489  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669492  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669494  5581 caffe.cpp:501] detection_eval = 5.48992
-I0511 11:50:55.669497  5581 caffe.cpp:501] detection_eval = 10.998
-I0511 11:50:55.669498  5581 caffe.cpp:501] detection_eval = 0.0425595
-I0511 11:50:55.669500  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669503  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669505  5581 caffe.cpp:501] detection_eval = 5.49194
-I0511 11:50:55.669507  5581 caffe.cpp:501] detection_eval = 11.0544
-I0511 11:50:55.669509  5581 caffe.cpp:501] detection_eval = 0.0436593
-I0511 11:50:55.669512  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669514  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669517  5581 caffe.cpp:501] detection_eval = 5.49395
-I0511 11:50:55.669518  5581 caffe.cpp:501] detection_eval = 11.0948
-I0511 11:50:55.669520  5581 caffe.cpp:501] detection_eval = 0.0409294
-I0511 11:50:55.669523  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669525  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669528  5581 caffe.cpp:501] detection_eval = 5.49395
-I0511 11:50:55.669529  5581 caffe.cpp:501] detection_eval = 11.1774
-I0511 11:50:55.669533  5581 caffe.cpp:501] detection_eval = 0.0480408
-I0511 11:50:55.669534  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669536  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669538  5581 caffe.cpp:501] detection_eval = 5.49798
-I0511 11:50:55.669540  5581 caffe.cpp:501] detection_eval = 11.1956
-I0511 11:50:55.669543  5581 caffe.cpp:501] detection_eval = 0.0418039
-I0511 11:50:55.669545  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669548  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669549  5581 caffe.cpp:501] detection_eval = 5.50202
-I0511 11:50:55.669551  5581 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:50:55.669554  5581 caffe.cpp:501] detection_eval = 0.0453119
-I0511 11:50:55.669556  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669559  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669560  5581 caffe.cpp:501] detection_eval = 5.50605
-I0511 11:50:55.669562  5581 caffe.cpp:501] detection_eval = 11.246
-I0511 11:50:55.669565  5581 caffe.cpp:501] detection_eval = 0.0457032
-I0511 11:50:55.669567  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669569  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669571  5581 caffe.cpp:501] detection_eval = 5.51008
-I0511 11:50:55.669574  5581 caffe.cpp:501] detection_eval = 11.2198
-I0511 11:50:55.669576  5581 caffe.cpp:501] detection_eval = 0.0436824
-I0511 11:50:55.669579  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669580  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669584  5581 caffe.cpp:501] detection_eval = 5.51613
-I0511 11:50:55.669585  5581 caffe.cpp:501] detection_eval = 11.1875
-I0511 11:50:55.669589  5581 caffe.cpp:501] detection_eval = 0.04641
-I0511 11:50:55.669590  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669592  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669595  5581 caffe.cpp:501] detection_eval = 5.52016
-I0511 11:50:55.669596  5581 caffe.cpp:501] detection_eval = 11.2137
-I0511 11:50:55.669600  5581 caffe.cpp:501] detection_eval = 0.051417
-I0511 11:50:55.669601  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.669605  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.669606  5581 caffe.cpp:501] detection_eval = 5.52419
-I0511 11:50:55.669608  5581 caffe.cpp:501] detection_eval = 11.2198
-I0511 11:50:55.669610  5581 caffe.cpp:501] detection_eval = 0.0473769
-I0511 11:50:55.669615  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669617  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669620  5581 caffe.cpp:501] detection_eval = 5.52621
-I0511 11:50:55.669622  5581 caffe.cpp:501] detection_eval = 11.2802
-I0511 11:50:55.669625  5581 caffe.cpp:501] detection_eval = 0.0477645
-I0511 11:50:55.669626  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669628  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669631  5581 caffe.cpp:501] detection_eval = 5.53024
-I0511 11:50:55.669633  5581 caffe.cpp:501] detection_eval = 11.3044
-I0511 11:50:55.669636  5581 caffe.cpp:501] detection_eval = 0.0483738
-I0511 11:50:55.669637  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669639  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669641  5581 caffe.cpp:501] detection_eval = 5.53629
-I0511 11:50:55.669644  5581 caffe.cpp:501] detection_eval = 11.2843
-I0511 11:50:55.669646  5581 caffe.cpp:501] detection_eval = 0.0479017
-I0511 11:50:55.669648  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669651  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669652  5581 caffe.cpp:501] detection_eval = 5.54032
-I0511 11:50:55.669656  5581 caffe.cpp:501] detection_eval = 11.2802
-I0511 11:50:55.669657  5581 caffe.cpp:501] detection_eval = 0.0443945
-I0511 11:50:55.669659  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669661  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669663  5581 caffe.cpp:501] detection_eval = 5.54032
-I0511 11:50:55.669667  5581 caffe.cpp:501] detection_eval = 11.3367
-I0511 11:50:55.669668  5581 caffe.cpp:501] detection_eval = 0.0423903
-I0511 11:50:55.669670  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669672  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669675  5581 caffe.cpp:501] detection_eval = 5.54032
-I0511 11:50:55.669677  5581 caffe.cpp:501] detection_eval = 11.4194
-I0511 11:50:55.669679  5581 caffe.cpp:501] detection_eval = 0.0477495
-I0511 11:50:55.669682  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669683  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669687  5581 caffe.cpp:501] detection_eval = 5.54435
-I0511 11:50:55.669688  5581 caffe.cpp:501] detection_eval = 11.4476
-I0511 11:50:55.669690  5581 caffe.cpp:501] detection_eval = 0.0473879
-I0511 11:50:55.669692  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669694  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669697  5581 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:50:55.669699  5581 caffe.cpp:501] detection_eval = 11.4194
-I0511 11:50:55.669701  5581 caffe.cpp:501] detection_eval = 0.0470163
-I0511 11:50:55.669703  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669705  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669708  5581 caffe.cpp:501] detection_eval = 5.55645
-I0511 11:50:55.669710  5581 caffe.cpp:501] detection_eval = 11.4355
-I0511 11:50:55.669713  5581 caffe.cpp:501] detection_eval = 0.0413591
-I0511 11:50:55.669714  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669718  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669720  5581 caffe.cpp:501] detection_eval = 5.56048
-I0511 11:50:55.669724  5581 caffe.cpp:501] detection_eval = 11.4556
-I0511 11:50:55.669728  5581 caffe.cpp:501] detection_eval = 0.0422115
-I0511 11:50:55.669733  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669735  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669737  5581 caffe.cpp:501] detection_eval = 5.56452
-I0511 11:50:55.669739  5581 caffe.cpp:501] detection_eval = 11.4617
-I0511 11:50:55.669742  5581 caffe.cpp:501] detection_eval = 0.0433957
-I0511 11:50:55.669744  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669746  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669749  5581 caffe.cpp:501] detection_eval = 5.57056
-I0511 11:50:55.669750  5581 caffe.cpp:501] detection_eval = 11.4859
-I0511 11:50:55.669754  5581 caffe.cpp:501] detection_eval = 0.0469743
-I0511 11:50:55.669759  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669761  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669764  5581 caffe.cpp:501] detection_eval = 5.57661
-I0511 11:50:55.669765  5581 caffe.cpp:501] detection_eval = 11.4718
-I0511 11:50:55.669769  5581 caffe.cpp:501] detection_eval = 0.0456488
-I0511 11:50:55.669770  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669772  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669775  5581 caffe.cpp:501] detection_eval = 5.58065
-I0511 11:50:55.669776  5581 caffe.cpp:501] detection_eval = 11.4819
-I0511 11:50:55.669780  5581 caffe.cpp:501] detection_eval = 0.0487595
-I0511 11:50:55.669781  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669783  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669785  5581 caffe.cpp:501] detection_eval = 5.58468
-I0511 11:50:55.669787  5581 caffe.cpp:501] detection_eval = 11.4718
-I0511 11:50:55.669790  5581 caffe.cpp:501] detection_eval = 0.0458818
-I0511 11:50:55.669792  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669795  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669796  5581 caffe.cpp:501] detection_eval = 5.58669
-I0511 11:50:55.669798  5581 caffe.cpp:501] detection_eval = 11.4778
-I0511 11:50:55.669801  5581 caffe.cpp:501] detection_eval = 0.0440891
-I0511 11:50:55.669803  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669806  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669807  5581 caffe.cpp:501] detection_eval = 5.58871
-I0511 11:50:55.669809  5581 caffe.cpp:501] detection_eval = 11.5565
-I0511 11:50:55.669812  5581 caffe.cpp:501] detection_eval = 0.0466776
-I0511 11:50:55.669814  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669816  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669818  5581 caffe.cpp:501] detection_eval = 5.59073
-I0511 11:50:55.669821  5581 caffe.cpp:501] detection_eval = 11.623
-I0511 11:50:55.669823  5581 caffe.cpp:501] detection_eval = 0.0433827
-I0511 11:50:55.669826  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669827  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669829  5581 caffe.cpp:501] detection_eval = 5.59274
-I0511 11:50:55.669831  5581 caffe.cpp:501] detection_eval = 11.6552
-I0511 11:50:55.669834  5581 caffe.cpp:501] detection_eval = 0.0483604
-I0511 11:50:55.669836  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669838  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669840  5581 caffe.cpp:501] detection_eval = 5.59274
-I0511 11:50:55.669842  5581 caffe.cpp:501] detection_eval = 11.7319
-I0511 11:50:55.669845  5581 caffe.cpp:501] detection_eval = 0.0416868
-I0511 11:50:55.669847  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669849  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669852  5581 caffe.cpp:501] detection_eval = 5.59879
-I0511 11:50:55.669853  5581 caffe.cpp:501] detection_eval = 11.7056
-I0511 11:50:55.669857  5581 caffe.cpp:501] detection_eval = 0.0412591
-I0511 11:50:55.669858  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669860  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669862  5581 caffe.cpp:501] detection_eval = 5.60282
-I0511 11:50:55.669865  5581 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:50:55.669867  5581 caffe.cpp:501] detection_eval = 0.0404898
-I0511 11:50:55.669869  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669872  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669873  5581 caffe.cpp:501] detection_eval = 5.60685
-I0511 11:50:55.669876  5581 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:50:55.669878  5581 caffe.cpp:501] detection_eval = 0.0412444
-I0511 11:50:55.669880  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669883  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669884  5581 caffe.cpp:501] detection_eval = 5.60685
-I0511 11:50:55.669888  5581 caffe.cpp:501] detection_eval = 11.7802
-I0511 11:50:55.669891  5581 caffe.cpp:501] detection_eval = 0.0403206
-I0511 11:50:55.669894  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669896  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669898  5581 caffe.cpp:501] detection_eval = 5.60887
-I0511 11:50:55.669900  5581 caffe.cpp:501] detection_eval = 11.8105
-I0511 11:50:55.669903  5581 caffe.cpp:501] detection_eval = 0.0406728
-I0511 11:50:55.669905  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669908  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669909  5581 caffe.cpp:501] detection_eval = 5.60887
-I0511 11:50:55.669911  5581 caffe.cpp:501] detection_eval = 11.9335
-I0511 11:50:55.669914  5581 caffe.cpp:501] detection_eval = 0.0443882
-I0511 11:50:55.669916  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669919  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669920  5581 caffe.cpp:501] detection_eval = 5.6129
-I0511 11:50:55.669924  5581 caffe.cpp:501] detection_eval = 11.9093
-I0511 11:50:55.669925  5581 caffe.cpp:501] detection_eval = 0.0395095
-I0511 11:50:55.669927  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669929  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669931  5581 caffe.cpp:501] detection_eval = 5.61694
-I0511 11:50:55.669934  5581 caffe.cpp:501] detection_eval = 11.873
-I0511 11:50:55.669936  5581 caffe.cpp:501] detection_eval = 0.0422343
-I0511 11:50:55.669939  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669940  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669942  5581 caffe.cpp:501] detection_eval = 5.61694
-I0511 11:50:55.669945  5581 caffe.cpp:501] detection_eval = 11.9133
-I0511 11:50:55.669947  5581 caffe.cpp:501] detection_eval = 0.0376908
-I0511 11:50:55.669950  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669951  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669955  5581 caffe.cpp:501] detection_eval = 5.62097
-I0511 11:50:55.669956  5581 caffe.cpp:501] detection_eval = 11.9355
-I0511 11:50:55.669958  5581 caffe.cpp:501] detection_eval = 0.0406901
-I0511 11:50:55.669960  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669962  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669965  5581 caffe.cpp:501] detection_eval = 5.62702
-I0511 11:50:55.669967  5581 caffe.cpp:501] detection_eval = 11.8952
-I0511 11:50:55.669970  5581 caffe.cpp:501] detection_eval = 0.0444293
-I0511 11:50:55.669971  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669973  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669975  5581 caffe.cpp:501] detection_eval = 5.63508
-I0511 11:50:55.669978  5581 caffe.cpp:501] detection_eval = 11.8427
-I0511 11:50:55.669981  5581 caffe.cpp:501] detection_eval = 0.0456376
-I0511 11:50:55.669982  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669984  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669987  5581 caffe.cpp:501] detection_eval = 5.64113
-I0511 11:50:55.669989  5581 caffe.cpp:501] detection_eval = 11.8044
-I0511 11:50:55.669991  5581 caffe.cpp:501] detection_eval = 0.0494156
-I0511 11:50:55.669993  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669996  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669998  5581 caffe.cpp:501] detection_eval = 5.64919
-I0511 11:50:55.670001  5581 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:50:55.670002  5581 caffe.cpp:501] detection_eval = 0.0463872
-I0511 11:50:55.670004  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670007  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670009  5581 caffe.cpp:501] detection_eval = 5.65927
-I0511 11:50:55.670011  5581 caffe.cpp:501] detection_eval = 11.6855
-I0511 11:50:55.670013  5581 caffe.cpp:501] detection_eval = 0.0443355
-I0511 11:50:55.670015  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670018  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670020  5581 caffe.cpp:501] detection_eval = 5.65927
-I0511 11:50:55.670024  5581 caffe.cpp:501] detection_eval = 11.7137
-I0511 11:50:55.670027  5581 caffe.cpp:501] detection_eval = 0.0426486
-I0511 11:50:55.670029  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670032  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670033  5581 caffe.cpp:501] detection_eval = 5.66129
-I0511 11:50:55.670035  5581 caffe.cpp:501] detection_eval = 11.7339
-I0511 11:50:55.670038  5581 caffe.cpp:501] detection_eval = 0.0423245
-I0511 11:50:55.670040  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670042  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670044  5581 caffe.cpp:501] detection_eval = 5.66129
-I0511 11:50:55.670047  5581 caffe.cpp:501] detection_eval = 11.7984
-I0511 11:50:55.670049  5581 caffe.cpp:501] detection_eval = 0.040463
-I0511 11:50:55.670051  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670053  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670055  5581 caffe.cpp:501] detection_eval = 5.66532
-I0511 11:50:55.670058  5581 caffe.cpp:501] detection_eval = 11.8085
-I0511 11:50:55.670060  5581 caffe.cpp:501] detection_eval = 0.0426931
-I0511 11:50:55.670063  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670064  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670066  5581 caffe.cpp:501] detection_eval = 5.66532
-I0511 11:50:55.670069  5581 caffe.cpp:501] detection_eval = 11.9032
-I0511 11:50:55.670071  5581 caffe.cpp:501] detection_eval = 0.0421257
-I0511 11:50:55.670073  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670075  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670078  5581 caffe.cpp:501] detection_eval = 5.66734
-I0511 11:50:55.670080  5581 caffe.cpp:501] detection_eval = 11.9456
-I0511 11:50:55.670083  5581 caffe.cpp:501] detection_eval = 0.0416543
-I0511 11:50:55.670084  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670086  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670089  5581 caffe.cpp:501] detection_eval = 5.66935
-I0511 11:50:55.670091  5581 caffe.cpp:501] detection_eval = 11.9919
-I0511 11:50:55.670094  5581 caffe.cpp:501] detection_eval = 0.0403842
-I0511 11:50:55.670095  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670097  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670100  5581 caffe.cpp:501] detection_eval = 5.67742
-I0511 11:50:55.670102  5581 caffe.cpp:501] detection_eval = 11.9073
-I0511 11:50:55.670104  5581 caffe.cpp:501] detection_eval = 0.0411806
-I0511 11:50:55.670106  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670109  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670111  5581 caffe.cpp:501] detection_eval = 5.67944
-I0511 11:50:55.670114  5581 caffe.cpp:501] detection_eval = 11.9234
-I0511 11:50:55.670115  5581 caffe.cpp:501] detection_eval = 0.0410597
-I0511 11:50:55.670117  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670120  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670122  5581 caffe.cpp:501] detection_eval = 5.68347
-I0511 11:50:55.670125  5581 caffe.cpp:501] detection_eval = 11.9778
-I0511 11:50:55.670126  5581 caffe.cpp:501] detection_eval = 0.0414674
-I0511 11:50:55.670130  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670131  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670133  5581 caffe.cpp:501] detection_eval = 5.69153
-I0511 11:50:55.670135  5581 caffe.cpp:501] detection_eval = 11.9133
-I0511 11:50:55.670137  5581 caffe.cpp:501] detection_eval = 0.0408694
-I0511 11:50:55.670140  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670142  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670145  5581 caffe.cpp:501] detection_eval = 5.69758
-I0511 11:50:55.670146  5581 caffe.cpp:501] detection_eval = 11.8972
-I0511 11:50:55.670148  5581 caffe.cpp:501] detection_eval = 0.0456838
-I0511 11:50:55.670151  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670153  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670156  5581 caffe.cpp:501] detection_eval = 5.6996
-I0511 11:50:55.670159  5581 caffe.cpp:501] detection_eval = 11.9113
-I0511 11:50:55.670162  5581 caffe.cpp:501] detection_eval = 0.0433706
-I0511 11:50:55.670164  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670166  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670168  5581 caffe.cpp:501] detection_eval = 5.6996
-I0511 11:50:55.670171  5581 caffe.cpp:501] detection_eval = 11.9657
-I0511 11:50:55.670173  5581 caffe.cpp:501] detection_eval = 0.0377889
-I0511 11:50:55.670176  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.670177  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.670181  5581 caffe.cpp:501] detection_eval = 5.70363
-I0511 11:50:55.670182  5581 caffe.cpp:501] detection_eval = 12.0484
-I0511 11:50:55.670184  5581 caffe.cpp:501] detection_eval = 0.0475116
-I0511 11:50:55.670186  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670188  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670192  5581 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:50:55.670193  5581 caffe.cpp:501] detection_eval = 12.0948
-I0511 11:50:55.670195  5581 caffe.cpp:501] detection_eval = 0.0430094
-I0511 11:50:55.670197  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670200  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670202  5581 caffe.cpp:501] detection_eval = 5.71169
-I0511 11:50:55.670204  5581 caffe.cpp:501] detection_eval = 12.0625
-I0511 11:50:55.670207  5581 caffe.cpp:501] detection_eval = 0.0406012
-I0511 11:50:55.670208  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670212  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.670213  5581 caffe.cpp:501] detection_eval = 5.71371
-I0511 11:50:55.670215  5581 caffe.cpp:501] detection_eval = 12.0867
-I0511 11:50:55.670217  5581 caffe.cpp:501] detection_eval = 0.0406962
-I0511 11:50:55.670219  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670222  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670224  5581 caffe.cpp:501] detection_eval = 5.71976
-I0511 11:50:55.670226  5581 caffe.cpp:501] detection_eval = 12.0302
-I0511 11:50:55.670228  5581 caffe.cpp:501] detection_eval = 0.0404774
-I0511 11:50:55.670230  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670233  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670235  5581 caffe.cpp:501] detection_eval = 5.72177
-I0511 11:50:55.670238  5581 caffe.cpp:501] detection_eval = 12.0927
-I0511 11:50:55.670239  5581 caffe.cpp:501] detection_eval = 0.0428298
-I0511 11:50:55.670241  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670244  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670246  5581 caffe.cpp:501] detection_eval = 5.72984
-I0511 11:50:55.670248  5581 caffe.cpp:501] detection_eval = 12.0383
-I0511 11:50:55.670250  5581 caffe.cpp:501] detection_eval = 0.0414953
-I0511 11:50:55.670253  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670255  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670258  5581 caffe.cpp:501] detection_eval = 5.72984
-I0511 11:50:55.670259  5581 caffe.cpp:501] detection_eval = 12.1129
-I0511 11:50:55.670262  5581 caffe.cpp:501] detection_eval = 0.0400972
-I0511 11:50:55.670264  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670266  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670269  5581 caffe.cpp:501] detection_eval = 5.73185
-I0511 11:50:55.670270  5581 caffe.cpp:501] detection_eval = 12.1512
-I0511 11:50:55.670274  5581 caffe.cpp:501] detection_eval = 0.040751
-I0511 11:50:55.670275  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670277  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670279  5581 caffe.cpp:501] detection_eval = 5.73589
-I0511 11:50:55.670281  5581 caffe.cpp:501] detection_eval = 12.1714
-I0511 11:50:55.670284  5581 caffe.cpp:501] detection_eval = 0.0410402
-I0511 11:50:55.670286  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670289  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670294  5581 caffe.cpp:501] detection_eval = 5.73589
-I0511 11:50:55.670295  5581 caffe.cpp:501] detection_eval = 12.2843
-I0511 11:50:55.670297  5581 caffe.cpp:501] detection_eval = 0.0396485
-I0511 11:50:55.670300  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.670302  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.670305  5581 caffe.cpp:501] detection_eval = 5.7379
-I0511 11:50:55.670306  5581 caffe.cpp:501] detection_eval = 12.3528
-I0511 11:50:55.670310  5581 caffe.cpp:501] detection_eval = 0.0383403
-I0511 11:50:55.670311  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670313  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670315  5581 caffe.cpp:501] detection_eval = 5.73992
-I0511 11:50:55.670317  5581 caffe.cpp:501] detection_eval = 12.3629
-I0511 11:50:55.670320  5581 caffe.cpp:501] detection_eval = 0.0364093
-I0511 11:50:55.670322  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.670325  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.670326  5581 caffe.cpp:501] detection_eval = 5.74194
-I0511 11:50:55.670328  5581 caffe.cpp:501] detection_eval = 12.3589
-I0511 11:50:55.670331  5581 caffe.cpp:501] detection_eval = 0.0348181
-I0511 11:50:55.670333  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670336  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670337  5581 caffe.cpp:501] detection_eval = 5.74194
-I0511 11:50:55.670339  5581 caffe.cpp:501] detection_eval = 12.4435
-I0511 11:50:55.670342  5581 caffe.cpp:501] detection_eval = 0.0372052
-I0511 11:50:55.670344  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.670346  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.670348  5581 caffe.cpp:501] detection_eval = 5.74395
-I0511 11:50:55.670351  5581 caffe.cpp:501] detection_eval = 12.4758
-I0511 11:50:55.670353  5581 caffe.cpp:501] detection_eval = 0.0411981
-I0511 11:50:55.670356  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670357  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670359  5581 caffe.cpp:501] detection_eval = 5.74597
-I0511 11:50:55.670361  5581 caffe.cpp:501] detection_eval = 12.5202
-I0511 11:50:55.670364  5581 caffe.cpp:501] detection_eval = 0.0401802
-I0511 11:50:55.670367  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670368  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670370  5581 caffe.cpp:501] detection_eval = 5.75
-I0511 11:50:55.670372  5581 caffe.cpp:501] detection_eval = 12.5685
-I0511 11:50:55.670375  5581 caffe.cpp:501] detection_eval = 0.0423118
-I0511 11:50:55.670377  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670379  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670382  5581 caffe.cpp:501] detection_eval = 5.75806
-I0511 11:50:55.670383  5581 caffe.cpp:501] detection_eval = 12.5544
-I0511 11:50:55.670387  5581 caffe.cpp:501] detection_eval = 0.0422818
-I0511 11:50:55.670388  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670390  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.670393  5581 caffe.cpp:501] detection_eval = 5.76411
-I0511 11:50:55.670395  5581 caffe.cpp:501] detection_eval = 12.5242
-I0511 11:50:55.670397  5581 caffe.cpp:501] detection_eval = 0.0396301
-I0511 11:50:55.670399  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670402  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670404  5581 caffe.cpp:501] detection_eval = 5.77016
-I0511 11:50:55.670406  5581 caffe.cpp:501] detection_eval = 12.502
-I0511 11:50:55.670408  5581 caffe.cpp:501] detection_eval = 0.0395042
-I0511 11:50:55.670410  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670413  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670415  5581 caffe.cpp:501] detection_eval = 5.77218
-I0511 11:50:55.670418  5581 caffe.cpp:501] detection_eval = 12.5625
-I0511 11:50:55.670419  5581 caffe.cpp:501] detection_eval = 0.0449169
-I0511 11:50:55.670421  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.670426  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670428  5581 caffe.cpp:501] detection_eval = 5.77419
-I0511 11:50:55.670430  5581 caffe.cpp:501] detection_eval = 12.6069
-I0511 11:50:55.670433  5581 caffe.cpp:501] detection_eval = 0.0452324
-I0511 11:50:55.670435  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670437  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670439  5581 caffe.cpp:501] detection_eval = 5.77419
-I0511 11:50:55.670441  5581 caffe.cpp:501] detection_eval = 12.6754
-I0511 11:50:55.670444  5581 caffe.cpp:501] detection_eval = 0.0440708
-I0511 11:50:55.670446  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.670449  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670450  5581 caffe.cpp:501] detection_eval = 5.78226
-I0511 11:50:55.670452  5581 caffe.cpp:501] detection_eval = 12.6694
-I0511 11:50:55.670455  5581 caffe.cpp:501] detection_eval = 0.0442899
-I0511 11:50:55.670457  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670459  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670461  5581 caffe.cpp:501] detection_eval = 5.78427
-I0511 11:50:55.670464  5581 caffe.cpp:501] detection_eval = 12.75
-I0511 11:50:55.670466  5581 caffe.cpp:501] detection_eval = 0.0428761
-I0511 11:50:55.670469  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670470  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670472  5581 caffe.cpp:501] detection_eval = 5.78831
-I0511 11:50:55.670475  5581 caffe.cpp:501] detection_eval = 12.7984
-I0511 11:50:55.670477  5581 caffe.cpp:501] detection_eval = 0.0431764
-I0511 11:50:55.670480  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670483  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670487  5581 caffe.cpp:501] detection_eval = 5.79234
-I0511 11:50:55.670491  5581 caffe.cpp:501] detection_eval = 12.9254
-I0511 11:50:55.670495  5581 caffe.cpp:501] detection_eval = 0.0473418
-I0511 11:50:55.670496  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670500  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670501  5581 caffe.cpp:501] detection_eval = 5.79435
-I0511 11:50:55.670503  5581 caffe.cpp:501] detection_eval = 13.1069
-I0511 11:50:55.670506  5581 caffe.cpp:501] detection_eval = 0.0430409
-I0511 11:50:55.670508  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670511  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670512  5581 caffe.cpp:501] detection_eval = 5.79839
-I0511 11:50:55.670514  5581 caffe.cpp:501] detection_eval = 13.2843
-I0511 11:50:55.670516  5581 caffe.cpp:501] detection_eval = 0.041264
-I0511 11:50:55.670519  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670521  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.670523  5581 caffe.cpp:501] detection_eval = 6.1754
-I0511 11:50:55.670526  5581 caffe.cpp:501] detection_eval = 7.66129
-I0511 11:50:55.670527  5581 caffe.cpp:501] detection_eval = 0.076982
-I0511 11:50:55.670529  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.670532  5581 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:50:55.670534  5581 caffe.cpp:501] detection_eval = 6.17742
-I0511 11:50:55.670536  5581 caffe.cpp:501] detection_eval = 7.8004
-I0511 11:50:55.670538  5581 caffe.cpp:501] detection_eval = 0.0611119
-I0511 11:50:55.670541  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.670543  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.670545  5581 caffe.cpp:501] detection_eval = 6.17742
-I0511 11:50:55.670547  5581 caffe.cpp:501] detection_eval = 7.93145
-I0511 11:50:55.670549  5581 caffe.cpp:501] detection_eval = 0.0522914
-I0511 11:50:55.670552  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.670553  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670555  5581 caffe.cpp:501] detection_eval = 6.17742
-I0511 11:50:55.670558  5581 caffe.cpp:501] detection_eval = 8.02419
-I0511 11:50:55.670560  5581 caffe.cpp:501] detection_eval = 0.0472921
-I0511 11:50:55.670562  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670567  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670569  5581 caffe.cpp:501] detection_eval = 6.18347
-I0511 11:50:55.670572  5581 caffe.cpp:501] detection_eval = 8.03629
-I0511 11:50:55.670573  5581 caffe.cpp:501] detection_eval = 0.0516428
-I0511 11:50:55.670575  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.670578  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.670580  5581 caffe.cpp:501] detection_eval = 6.18548
-I0511 11:50:55.670583  5581 caffe.cpp:501] detection_eval = 8.1371
-I0511 11:50:55.670584  5581 caffe.cpp:501] detection_eval = 0.0505285
-I0511 11:50:55.670586  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.670589  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670591  5581 caffe.cpp:501] detection_eval = 6.1875
-I0511 11:50:55.670593  5581 caffe.cpp:501] detection_eval = 8.19355
-I0511 11:50:55.670595  5581 caffe.cpp:501] detection_eval = 0.0476904
-I0511 11:50:55.670598  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.670599  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.670603  5581 caffe.cpp:501] detection_eval = 6.18952
-I0511 11:50:55.670604  5581 caffe.cpp:501] detection_eval = 8.24194
-I0511 11:50:55.670606  5581 caffe.cpp:501] detection_eval = 0.0466943
-I0511 11:50:55.670608  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.670610  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.670612  5581 caffe.cpp:501] detection_eval = 6.19153
-I0511 11:50:55.670615  5581 caffe.cpp:501] detection_eval = 8.26815
-I0511 11:50:55.670617  5581 caffe.cpp:501] detection_eval = 0.0453015
-I0511 11:50:55.670619  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670622  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670624  5581 caffe.cpp:501] detection_eval = 6.19758
-I0511 11:50:55.670626  5581 caffe.cpp:501] detection_eval = 8.23589
-I0511 11:50:55.670629  5581 caffe.cpp:501] detection_eval = 0.0449947
-I0511 11:50:55.670630  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670632  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670634  5581 caffe.cpp:501] detection_eval = 6.1996
-I0511 11:50:55.670637  5581 caffe.cpp:501] detection_eval = 8.31855
-I0511 11:50:55.670639  5581 caffe.cpp:501] detection_eval = 0.0454182
-I0511 11:50:55.670641  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670644  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670645  5581 caffe.cpp:501] detection_eval = 6.1996
-I0511 11:50:55.670647  5581 caffe.cpp:501] detection_eval = 8.37903
-I0511 11:50:55.670650  5581 caffe.cpp:501] detection_eval = 0.0448143
-I0511 11:50:55.670652  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670655  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670656  5581 caffe.cpp:501] detection_eval = 6.20161
-I0511 11:50:55.670658  5581 caffe.cpp:501] detection_eval = 8.39516
-I0511 11:50:55.670661  5581 caffe.cpp:501] detection_eval = 0.0511922
-I0511 11:50:55.670663  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.670665  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670667  5581 caffe.cpp:501] detection_eval = 6.20363
-I0511 11:50:55.670670  5581 caffe.cpp:501] detection_eval = 8.44153
-I0511 11:50:55.670672  5581 caffe.cpp:501] detection_eval = 0.0454235
-I0511 11:50:55.670675  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670676  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670678  5581 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:50:55.670680  5581 caffe.cpp:501] detection_eval = 8.51411
-I0511 11:50:55.670683  5581 caffe.cpp:501] detection_eval = 0.043053
-I0511 11:50:55.670686  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670687  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670689  5581 caffe.cpp:501] detection_eval = 6.20766
-I0511 11:50:55.670691  5581 caffe.cpp:501] detection_eval = 8.57056
-I0511 11:50:55.670693  5581 caffe.cpp:501] detection_eval = 0.0410455
-I0511 11:50:55.670698  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670701  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670703  5581 caffe.cpp:501] detection_eval = 6.20968
-I0511 11:50:55.670706  5581 caffe.cpp:501] detection_eval = 8.62298
-I0511 11:50:55.670707  5581 caffe.cpp:501] detection_eval = 0.0451681
-I0511 11:50:55.670711  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670712  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670717  5581 caffe.cpp:501] detection_eval = 6.20968
-I0511 11:50:55.670719  5581 caffe.cpp:501] detection_eval = 8.6875
-I0511 11:50:55.670722  5581 caffe.cpp:501] detection_eval = 0.0372051
-I0511 11:50:55.670728  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.670733  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.670737  5581 caffe.cpp:501] detection_eval = 6.21573
-I0511 11:50:55.670738  5581 caffe.cpp:501] detection_eval = 8.66734
-I0511 11:50:55.670740  5581 caffe.cpp:501] detection_eval = 0.0402002
-I0511 11:50:55.670742  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670745  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670747  5581 caffe.cpp:501] detection_eval = 6.21774
-I0511 11:50:55.670749  5581 caffe.cpp:501] detection_eval = 8.74395
-I0511 11:50:55.670752  5581 caffe.cpp:501] detection_eval = 0.0415073
-I0511 11:50:55.670754  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670756  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670758  5581 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:50:55.670760  5581 caffe.cpp:501] detection_eval = 8.72379
-I0511 11:50:55.670763  5581 caffe.cpp:501] detection_eval = 0.0389802
-I0511 11:50:55.670765  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670768  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670769  5581 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:50:55.670771  5581 caffe.cpp:501] detection_eval = 8.7621
-I0511 11:50:55.670773  5581 caffe.cpp:501] detection_eval = 0.0355101
-I0511 11:50:55.670776  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.670778  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670780  5581 caffe.cpp:501] detection_eval = 6.22581
-I0511 11:50:55.670783  5581 caffe.cpp:501] detection_eval = 8.83266
-I0511 11:50:55.670784  5581 caffe.cpp:501] detection_eval = 0.041855
-I0511 11:50:55.670786  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670789  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670791  5581 caffe.cpp:501] detection_eval = 6.23992
-I0511 11:50:55.670794  5581 caffe.cpp:501] detection_eval = 8.65726
-I0511 11:50:55.670795  5581 caffe.cpp:501] detection_eval = 0.0365189
-I0511 11:50:55.670797  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670800  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670802  5581 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:50:55.670804  5581 caffe.cpp:501] detection_eval = 8.70161
-I0511 11:50:55.670807  5581 caffe.cpp:501] detection_eval = 0.0387272
-I0511 11:50:55.670809  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670811  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670814  5581 caffe.cpp:501] detection_eval = 6.25202
-I0511 11:50:55.670815  5581 caffe.cpp:501] detection_eval = 8.73185
-I0511 11:50:55.670817  5581 caffe.cpp:501] detection_eval = 0.0477054
-I0511 11:50:55.670820  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.670822  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.670825  5581 caffe.cpp:501] detection_eval = 6.2621
-I0511 11:50:55.670826  5581 caffe.cpp:501] detection_eval = 8.65323
-I0511 11:50:55.670828  5581 caffe.cpp:501] detection_eval = 0.0480796
-I0511 11:50:55.670830  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670833  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670835  5581 caffe.cpp:501] detection_eval = 6.26613
-I0511 11:50:55.670837  5581 caffe.cpp:501] detection_eval = 8.63508
-I0511 11:50:55.670840  5581 caffe.cpp:501] detection_eval = 0.0421389
-I0511 11:50:55.670845  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670847  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.670850  5581 caffe.cpp:501] detection_eval = 6.27016
-I0511 11:50:55.670851  5581 caffe.cpp:501] detection_eval = 8.64113
-I0511 11:50:55.670853  5581 caffe.cpp:501] detection_eval = 0.0429365
-I0511 11:50:55.670856  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670858  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670861  5581 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:50:55.670862  5581 caffe.cpp:501] detection_eval = 8.68548
-I0511 11:50:55.670866  5581 caffe.cpp:501] detection_eval = 0.0376349
-I0511 11:50:55.670867  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670869  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670871  5581 caffe.cpp:501] detection_eval = 6.27823
-I0511 11:50:55.670873  5581 caffe.cpp:501] detection_eval = 8.70565
-I0511 11:50:55.670876  5581 caffe.cpp:501] detection_eval = 0.0425564
-I0511 11:50:55.670878  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670881  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670882  5581 caffe.cpp:501] detection_eval = 6.28024
-I0511 11:50:55.670886  5581 caffe.cpp:501] detection_eval = 8.74395
-I0511 11:50:55.670887  5581 caffe.cpp:501] detection_eval = 0.0418464
-I0511 11:50:55.670889  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670892  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670893  5581 caffe.cpp:501] detection_eval = 6.28226
-I0511 11:50:55.670897  5581 caffe.cpp:501] detection_eval = 8.77621
-I0511 11:50:55.670898  5581 caffe.cpp:501] detection_eval = 0.0413275
-I0511 11:50:55.670900  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670902  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670904  5581 caffe.cpp:501] detection_eval = 6.28427
-I0511 11:50:55.670907  5581 caffe.cpp:501] detection_eval = 8.78226
-I0511 11:50:55.670909  5581 caffe.cpp:501] detection_eval = 0.0399679
-I0511 11:50:55.670912  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670913  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670915  5581 caffe.cpp:501] detection_eval = 6.28427
-I0511 11:50:55.670917  5581 caffe.cpp:501] detection_eval = 8.85887
-I0511 11:50:55.670919  5581 caffe.cpp:501] detection_eval = 0.0441443
-I0511 11:50:55.670922  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670924  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670927  5581 caffe.cpp:501] detection_eval = 6.28629
-I0511 11:50:55.670928  5581 caffe.cpp:501] detection_eval = 8.90927
-I0511 11:50:55.670930  5581 caffe.cpp:501] detection_eval = 0.0413302
-I0511 11:50:55.670933  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670935  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670938  5581 caffe.cpp:501] detection_eval = 6.28831
-I0511 11:50:55.670939  5581 caffe.cpp:501] detection_eval = 8.94556
-I0511 11:50:55.670941  5581 caffe.cpp:501] detection_eval = 0.0397936
-I0511 11:50:55.670943  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670946  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670948  5581 caffe.cpp:501] detection_eval = 6.28831
-I0511 11:50:55.670950  5581 caffe.cpp:501] detection_eval = 9.0121
-I0511 11:50:55.670953  5581 caffe.cpp:501] detection_eval = 0.0402532
-I0511 11:50:55.670954  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670958  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670959  5581 caffe.cpp:501] detection_eval = 6.29234
-I0511 11:50:55.670961  5581 caffe.cpp:501] detection_eval = 8.99597
-I0511 11:50:55.670964  5581 caffe.cpp:501] detection_eval = 0.040991
-I0511 11:50:55.670965  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670967  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670970  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.670972  5581 caffe.cpp:501] detection_eval = 9.01411
-I0511 11:50:55.670977  5581 caffe.cpp:501] detection_eval = 0.0375293
-I0511 11:50:55.670979  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670982  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670984  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.670986  5581 caffe.cpp:501] detection_eval = 9.0746
-I0511 11:50:55.670989  5581 caffe.cpp:501] detection_eval = 0.0419776
-I0511 11:50:55.670990  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670994  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670995  5581 caffe.cpp:501] detection_eval = 6.29839
-I0511 11:50:55.670997  5581 caffe.cpp:501] detection_eval = 9.13306
-I0511 11:50:55.671000  5581 caffe.cpp:501] detection_eval = 0.0421072
-I0511 11:50:55.671001  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671005  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.671006  5581 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:50:55.671008  5581 caffe.cpp:501] detection_eval = 9.12702
-I0511 11:50:55.671010  5581 caffe.cpp:501] detection_eval = 0.0413086
-I0511 11:50:55.671013  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.671015  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.671017  5581 caffe.cpp:501] detection_eval = 6.30645
-I0511 11:50:55.671020  5581 caffe.cpp:501] detection_eval = 9.17742
-I0511 11:50:55.671022  5581 caffe.cpp:501] detection_eval = 0.0431557
-I0511 11:50:55.671025  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671026  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671028  5581 caffe.cpp:501] detection_eval = 6.30645
-I0511 11:50:55.671030  5581 caffe.cpp:501] detection_eval = 9.25605
-I0511 11:50:55.671033  5581 caffe.cpp:501] detection_eval = 0.045073
-I0511 11:50:55.671036  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671037  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.671039  5581 caffe.cpp:501] detection_eval = 6.3125
-I0511 11:50:55.671042  5581 caffe.cpp:501] detection_eval = 9.25806
-I0511 11:50:55.671044  5581 caffe.cpp:501] detection_eval = 0.0464449
-I0511 11:50:55.671046  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671048  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671051  5581 caffe.cpp:501] detection_eval = 6.3125
-I0511 11:50:55.671053  5581 caffe.cpp:501] detection_eval = 9.3629
-I0511 11:50:55.671056  5581 caffe.cpp:501] detection_eval = 0.0388863
-I0511 11:50:55.671057  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.671059  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671061  5581 caffe.cpp:501] detection_eval = 6.31653
-I0511 11:50:55.671064  5581 caffe.cpp:501] detection_eval = 9.39718
-I0511 11:50:55.671066  5581 caffe.cpp:501] detection_eval = 0.0381406
-I0511 11:50:55.671068  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671314  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671329  5581 caffe.cpp:501] detection_eval = 6.32258
-I0511 11:50:55.671330  5581 caffe.cpp:501] detection_eval = 9.37903
-I0511 11:50:55.671332  5581 caffe.cpp:501] detection_eval = 0.0403081
-I0511 11:50:55.671335  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671337  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.671339  5581 caffe.cpp:501] detection_eval = 6.32258
-I0511 11:50:55.671342  5581 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:50:55.671344  5581 caffe.cpp:501] detection_eval = 0.0435655
-I0511 11:50:55.671346  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671349  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671350  5581 caffe.cpp:501] detection_eval = 6.32258
-I0511 11:50:55.671352  5581 caffe.cpp:501] detection_eval = 9.5625
-I0511 11:50:55.671355  5581 caffe.cpp:501] detection_eval = 0.0449686
-I0511 11:50:55.671357  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.671360  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.671361  5581 caffe.cpp:501] detection_eval = 6.32661
-I0511 11:50:55.671368  5581 caffe.cpp:501] detection_eval = 9.54435
-I0511 11:50:55.671371  5581 caffe.cpp:501] detection_eval = 0.0405597
-I0511 11:50:55.671373  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671375  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.671377  5581 caffe.cpp:501] detection_eval = 6.32661
-I0511 11:50:55.671380  5581 caffe.cpp:501] detection_eval = 9.62097
-I0511 11:50:55.671382  5581 caffe.cpp:501] detection_eval = 0.0419663
-I0511 11:50:55.671385  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.671386  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.671388  5581 caffe.cpp:501] detection_eval = 6.33266
-I0511 11:50:55.671391  5581 caffe.cpp:501] detection_eval = 9.62702
-I0511 11:50:55.671393  5581 caffe.cpp:501] detection_eval = 0.0426358
-I0511 11:50:55.671396  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671397  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671399  5581 caffe.cpp:501] detection_eval = 6.33266
-I0511 11:50:55.671401  5581 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:50:55.671403  5581 caffe.cpp:501] detection_eval = 0.041483
-I0511 11:50:55.671406  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.671408  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.671411  5581 caffe.cpp:501] detection_eval = 6.33468
-I0511 11:50:55.671412  5581 caffe.cpp:501] detection_eval = 9.74194
-I0511 11:50:55.671414  5581 caffe.cpp:501] detection_eval = 0.043737
-I0511 11:50:55.671416  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671419  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.671422  5581 caffe.cpp:501] detection_eval = 6.33669
-I0511 11:50:55.671423  5581 caffe.cpp:501] detection_eval = 9.75605
-I0511 11:50:55.671425  5581 caffe.cpp:501] detection_eval = 0.0428811
-I0511 11:50:55.671427  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671429  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671432  5581 caffe.cpp:501] detection_eval = 6.33871
-I0511 11:50:55.671434  5581 caffe.cpp:501] detection_eval = 9.85282
-I0511 11:50:55.671437  5581 caffe.cpp:501] detection_eval = 0.0469635
-I0511 11:50:55.671438  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671440  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.671442  5581 caffe.cpp:501] detection_eval = 6.34073
-I0511 11:50:55.671444  5581 caffe.cpp:501] detection_eval = 9.89718
-I0511 11:50:55.671447  5581 caffe.cpp:501] detection_eval = 0.0461667
-I0511 11:50:55.671449  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671452  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671453  5581 caffe.cpp:501] detection_eval = 6.34274
-I0511 11:50:55.671455  5581 caffe.cpp:501] detection_eval = 9.95363
-I0511 11:50:55.671458  5581 caffe.cpp:501] detection_eval = 0.0466406
-I0511 11:50:55.671460  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671463  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671464  5581 caffe.cpp:501] detection_eval = 6.34879
-I0511 11:50:55.671466  5581 caffe.cpp:501] detection_eval = 9.95161
-I0511 11:50:55.671468  5581 caffe.cpp:501] detection_eval = 0.0466964
-I0511 11:50:55.671471  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.671473  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.671475  5581 caffe.cpp:501] detection_eval = 6.35282
-I0511 11:50:55.671478  5581 caffe.cpp:501] detection_eval = 9.96169
-I0511 11:50:55.671479  5581 caffe.cpp:501] detection_eval = 0.0472965
-I0511 11:50:55.671481  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.671484  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.671486  5581 caffe.cpp:501] detection_eval = 6.35484
-I0511 11:50:55.671489  5581 caffe.cpp:501] detection_eval = 10
-I0511 11:50:55.671490  5581 caffe.cpp:501] detection_eval = 0.0437015
-I0511 11:50:55.671494  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671495  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.671497  5581 caffe.cpp:501] detection_eval = 6.36089
-I0511 11:50:55.671502  5581 caffe.cpp:501] detection_eval = 9.98185
-I0511 11:50:55.671504  5581 caffe.cpp:501] detection_eval = 0.0436494
-I0511 11:50:55.671507  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.671509  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671511  5581 caffe.cpp:501] detection_eval = 6.3629
-I0511 11:50:55.671514  5581 caffe.cpp:501] detection_eval = 10.0222
-I0511 11:50:55.671516  5581 caffe.cpp:501] detection_eval = 0.0393048
-I0511 11:50:55.671519  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.671520  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.671522  5581 caffe.cpp:501] detection_eval = 6.36694
-I0511 11:50:55.671525  5581 caffe.cpp:501] detection_eval = 10.0927
-I0511 11:50:55.671527  5581 caffe.cpp:501] detection_eval = 0.0493265
-I0511 11:50:55.671530  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671531  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.671533  5581 caffe.cpp:501] detection_eval = 6.37097
-I0511 11:50:55.671535  5581 caffe.cpp:501] detection_eval = 10.1351
-I0511 11:50:55.671538  5581 caffe.cpp:501] detection_eval = 0.0468921
-I0511 11:50:55.671540  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671542  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.671545  5581 caffe.cpp:501] detection_eval = 6.37097
-I0511 11:50:55.671546  5581 caffe.cpp:501] detection_eval = 10.1976
-I0511 11:50:55.671550  5581 caffe.cpp:501] detection_eval = 0.0425419
-I0511 11:50:55.671551  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.671553  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671555  5581 caffe.cpp:501] detection_eval = 6.37097
-I0511 11:50:55.671557  5581 caffe.cpp:501] detection_eval = 10.2702
-I0511 11:50:55.671561  5581 caffe.cpp:501] detection_eval = 0.0398125
-I0511 11:50:55.671562  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.671564  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.671566  5581 caffe.cpp:501] detection_eval = 6.38105
-I0511 11:50:55.671568  5581 caffe.cpp:501] detection_eval = 10.2339
-I0511 11:50:55.671571  5581 caffe.cpp:501] detection_eval = 0.0415377
-I0511 11:50:55.671573  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671576  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671577  5581 caffe.cpp:501] detection_eval = 6.3871
-I0511 11:50:55.671579  5581 caffe.cpp:501] detection_eval = 10.2077
-I0511 11:50:55.671582  5581 caffe.cpp:501] detection_eval = 0.0431371
-I0511 11:50:55.671584  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.671586  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.671588  5581 caffe.cpp:501] detection_eval = 6.39516
-I0511 11:50:55.671591  5581 caffe.cpp:501] detection_eval = 10.2036
-I0511 11:50:55.672657  5581 caffe.cpp:501] detection_eval = 0.0418587
-I0511 11:50:55.672663  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.672667  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.672672  5581 caffe.cpp:501] detection_eval = 6.39919
-I0511 11:50:55.672675  5581 caffe.cpp:501] detection_eval = 10.2581
-I0511 11:50:55.672679  5581 caffe.cpp:501] detection_eval = 0.0437859
-I0511 11:50:55.672683  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.672686  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672689  5581 caffe.cpp:501] detection_eval = 6.40726
-I0511 11:50:55.672693  5581 caffe.cpp:501] detection_eval = 10.244
-I0511 11:50:55.672696  5581 caffe.cpp:501] detection_eval = 0.0470156
-I0511 11:50:55.672699  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.672703  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.672708  5581 caffe.cpp:501] detection_eval = 6.40927
-I0511 11:50:55.672711  5581 caffe.cpp:501] detection_eval = 10.2843
-I0511 11:50:55.672715  5581 caffe.cpp:501] detection_eval = 0.0422535
-I0511 11:50:55.672719  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.672722  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672731  5581 caffe.cpp:501] detection_eval = 6.41129
-I0511 11:50:55.672735  5581 caffe.cpp:501] detection_eval = 10.3871
-I0511 11:50:55.672739  5581 caffe.cpp:501] detection_eval = 0.0487919
-I0511 11:50:55.672742  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.672746  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.672750  5581 caffe.cpp:501] detection_eval = 6.41734
-I0511 11:50:55.672755  5581 caffe.cpp:501] detection_eval = 10.4133
-I0511 11:50:55.672757  5581 caffe.cpp:501] detection_eval = 0.0452637
-I0511 11:50:55.672761  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.672765  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.672770  5581 caffe.cpp:501] detection_eval = 6.4254
-I0511 11:50:55.672772  5581 caffe.cpp:501] detection_eval = 10.3468
-I0511 11:50:55.672776  5581 caffe.cpp:501] detection_eval = 0.0409249
-I0511 11:50:55.672780  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.672783  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.672786  5581 caffe.cpp:501] detection_eval = 6.42944
-I0511 11:50:55.672789  5581 caffe.cpp:501] detection_eval = 10.3407
-I0511 11:50:55.672794  5581 caffe.cpp:501] detection_eval = 0.0460814
-I0511 11:50:55.672797  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.672801  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.672806  5581 caffe.cpp:501] detection_eval = 6.4375
-I0511 11:50:55.672808  5581 caffe.cpp:501] detection_eval = 10.2782
-I0511 11:50:55.672812  5581 caffe.cpp:501] detection_eval = 0.0408642
-I0511 11:50:55.672816  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672821  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.672823  5581 caffe.cpp:501] detection_eval = 6.43952
-I0511 11:50:55.672827  5581 caffe.cpp:501] detection_eval = 10.3024
-I0511 11:50:55.672832  5581 caffe.cpp:501] detection_eval = 0.0417377
-I0511 11:50:55.672835  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672839  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672842  5581 caffe.cpp:501] detection_eval = 6.43952
-I0511 11:50:55.672847  5581 caffe.cpp:501] detection_eval = 10.3669
-I0511 11:50:55.672850  5581 caffe.cpp:501] detection_eval = 0.0402777
-I0511 11:50:55.672853  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.672857  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672861  5581 caffe.cpp:501] detection_eval = 6.44758
-I0511 11:50:55.672864  5581 caffe.cpp:501] detection_eval = 10.3488
-I0511 11:50:55.672868  5581 caffe.cpp:501] detection_eval = 0.0426006
-I0511 11:50:55.672871  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672874  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.672878  5581 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:50:55.672883  5581 caffe.cpp:501] detection_eval = 10.4113
-I0511 11:50:55.672886  5581 caffe.cpp:501] detection_eval = 0.0435831
-I0511 11:50:55.672890  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672894  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.672897  5581 caffe.cpp:501] detection_eval = 6.45766
-I0511 11:50:55.672901  5581 caffe.cpp:501] detection_eval = 10.3468
-I0511 11:50:55.672905  5581 caffe.cpp:501] detection_eval = 0.0409441
-I0511 11:50:55.672909  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.672912  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.672916  5581 caffe.cpp:501] detection_eval = 6.45968
-I0511 11:50:55.672920  5581 caffe.cpp:501] detection_eval = 10.3629
-I0511 11:50:55.672924  5581 caffe.cpp:501] detection_eval = 0.0370585
-I0511 11:50:55.672927  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672931  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.672935  5581 caffe.cpp:501] detection_eval = 6.46573
-I0511 11:50:55.672938  5581 caffe.cpp:501] detection_eval = 10.3831
-I0511 11:50:55.672942  5581 caffe.cpp:501] detection_eval = 0.0436748
-I0511 11:50:55.672946  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.672950  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672956  5581 caffe.cpp:501] detection_eval = 6.46976
-I0511 11:50:55.672960  5581 caffe.cpp:501] detection_eval = 10.4617
-I0511 11:50:55.672965  5581 caffe.cpp:501] detection_eval = 0.0420634
-I0511 11:50:55.672968  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.672972  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.672976  5581 caffe.cpp:501] detection_eval = 6.47177
-I0511 11:50:55.672979  5581 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:50:55.672983  5581 caffe.cpp:501] detection_eval = 0.0396105
-I0511 11:50:55.672987  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.672991  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.672994  5581 caffe.cpp:501] detection_eval = 6.47177
-I0511 11:50:55.672998  5581 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:50:55.673002  5581 caffe.cpp:501] detection_eval = 0.0455037
-I0511 11:50:55.673005  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.673009  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.673013  5581 caffe.cpp:501] detection_eval = 6.47984
-I0511 11:50:55.673017  5581 caffe.cpp:501] detection_eval = 10.5121
-I0511 11:50:55.673020  5581 caffe.cpp:501] detection_eval = 0.0397872
-I0511 11:50:55.673024  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.673028  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.673032  5581 caffe.cpp:501] detection_eval = 6.48387
-I0511 11:50:55.673035  5581 caffe.cpp:501] detection_eval = 10.5625
-I0511 11:50:55.673038  5581 caffe.cpp:501] detection_eval = 0.0478975
-I0511 11:50:55.673041  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.673045  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.673049  5581 caffe.cpp:501] detection_eval = 6.48589
-I0511 11:50:55.673053  5581 caffe.cpp:501] detection_eval = 10.5988
-I0511 11:50:55.673056  5581 caffe.cpp:501] detection_eval = 0.0457368
-I0511 11:50:55.673060  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.673064  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.673068  5581 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:50:55.673071  5581 caffe.cpp:501] detection_eval = 10.6472
-I0511 11:50:55.673075  5581 caffe.cpp:501] detection_eval = 0.0450222
-I0511 11:50:55.673079  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.673082  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.673086  5581 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:50:55.673090  5581 caffe.cpp:501] detection_eval = 10.5645
-I0511 11:50:55.673094  5581 caffe.cpp:501] detection_eval = 0.0388435
-I0511 11:50:55.673097  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.673101  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.676645  5581 caffe.cpp:501] detection_eval = 6.5
-I0511 11:50:55.676661  5581 caffe.cpp:501] detection_eval = 10.6008
-I0511 11:50:55.676666  5581 caffe.cpp:501] detection_eval = 0.0386242
-I0511 11:50:55.676671  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.676674  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.676677  5581 caffe.cpp:501] detection_eval = 6.50403
-I0511 11:50:55.676681  5581 caffe.cpp:501] detection_eval = 10.5887
-I0511 11:50:55.676686  5581 caffe.cpp:501] detection_eval = 0.0385548
-I0511 11:50:55.676689  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.676693  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.676697  5581 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:50:55.676702  5581 caffe.cpp:501] detection_eval = 10.4677
-I0511 11:50:55.676705  5581 caffe.cpp:501] detection_eval = 0.0414124
-I0511 11:50:55.676709  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.676713  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.676717  5581 caffe.cpp:501] detection_eval = 6.52218
-I0511 11:50:55.676722  5581 caffe.cpp:501] detection_eval = 10.5
-I0511 11:50:55.676725  5581 caffe.cpp:501] detection_eval = 0.0490748
-I0511 11:50:55.676730  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.676744  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.676749  5581 caffe.cpp:501] detection_eval = 6.53024
-I0511 11:50:55.676753  5581 caffe.cpp:501] detection_eval = 10.4194
-I0511 11:50:55.676757  5581 caffe.cpp:501] detection_eval = 0.0412619
-I0511 11:50:55.676761  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.676765  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.676769  5581 caffe.cpp:501] detection_eval = 6.54032
-I0511 11:50:55.676774  5581 caffe.cpp:501] detection_eval = 10.3649
-I0511 11:50:55.676777  5581 caffe.cpp:501] detection_eval = 0.0379293
-I0511 11:50:55.676781  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.676786  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676791  5581 caffe.cpp:501] detection_eval = 6.54032
-I0511 11:50:55.676796  5581 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:50:55.676801  5581 caffe.cpp:501] detection_eval = 0.0394541
-I0511 11:50:55.676807  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.676811  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676816  5581 caffe.cpp:501] detection_eval = 6.54234
-I0511 11:50:55.676821  5581 caffe.cpp:501] detection_eval = 10.5605
-I0511 11:50:55.676826  5581 caffe.cpp:501] detection_eval = 0.0442708
-I0511 11:50:55.676831  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.676834  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.676838  5581 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:50:55.676841  5581 caffe.cpp:501] detection_eval = 10.5323
-I0511 11:50:55.676846  5581 caffe.cpp:501] detection_eval = 0.0391731
-I0511 11:50:55.676849  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.676853  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676857  5581 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:50:55.676862  5581 caffe.cpp:501] detection_eval = 10.625
-I0511 11:50:55.676864  5581 caffe.cpp:501] detection_eval = 0.0472549
-I0511 11:50:55.676867  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.676869  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.676872  5581 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:50:55.676873  5581 caffe.cpp:501] detection_eval = 10.7117
-I0511 11:50:55.676875  5581 caffe.cpp:501] detection_eval = 0.0440087
-I0511 11:50:55.676878  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.676880  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.676882  5581 caffe.cpp:501] detection_eval = 6.55444
-I0511 11:50:55.676884  5581 caffe.cpp:501] detection_eval = 10.7863
-I0511 11:50:55.676887  5581 caffe.cpp:501] detection_eval = 0.0437509
-I0511 11:50:55.676889  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.676892  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.676893  5581 caffe.cpp:501] detection_eval = 6.55847
-I0511 11:50:55.676895  5581 caffe.cpp:501] detection_eval = 10.8246
-I0511 11:50:55.676898  5581 caffe.cpp:501] detection_eval = 0.0438239
-I0511 11:50:55.676900  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.676903  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.676904  5581 caffe.cpp:501] detection_eval = 6.56048
-I0511 11:50:55.676906  5581 caffe.cpp:501] detection_eval = 10.9597
-I0511 11:50:55.676909  5581 caffe.cpp:501] detection_eval = 0.0470999
-I0511 11:50:55.676911  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.676913  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.676915  5581 caffe.cpp:501] detection_eval = 6.5625
-I0511 11:50:55.676918  5581 caffe.cpp:501] detection_eval = 10.9778
-I0511 11:50:55.676920  5581 caffe.cpp:501] detection_eval = 0.0391168
-I0511 11:50:55.676923  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.676924  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676926  5581 caffe.cpp:501] detection_eval = 6.5625
-I0511 11:50:55.676928  5581 caffe.cpp:501] detection_eval = 11.0524
-I0511 11:50:55.676931  5581 caffe.cpp:501] detection_eval = 0.0409669
-I0511 11:50:55.676937  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.676940  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.676942  5581 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:50:55.676944  5581 caffe.cpp:501] detection_eval = 11.1149
-I0511 11:50:55.676946  5581 caffe.cpp:501] detection_eval = 0.0414753
-I0511 11:50:55.676949  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.676951  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.676954  5581 caffe.cpp:501] detection_eval = 6.56653
-I0511 11:50:55.676955  5581 caffe.cpp:501] detection_eval = 11.1391
-I0511 11:50:55.676957  5581 caffe.cpp:501] detection_eval = 0.0385771
-I0511 11:50:55.676960  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.676962  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676964  5581 caffe.cpp:501] detection_eval = 6.56653
-I0511 11:50:55.676966  5581 caffe.cpp:501] detection_eval = 11.2177
-I0511 11:50:55.676968  5581 caffe.cpp:501] detection_eval = 0.0447229
-I0511 11:50:55.676971  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.676973  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.676975  5581 caffe.cpp:501] detection_eval = 6.5746
-I0511 11:50:55.676977  5581 caffe.cpp:501] detection_eval = 11.2177
-I0511 11:50:55.676980  5581 caffe.cpp:501] detection_eval = 0.0430438
-I0511 11:50:55.676982  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.676985  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.676986  5581 caffe.cpp:501] detection_eval = 6.57863
-I0511 11:50:55.676988  5581 caffe.cpp:501] detection_eval = 11.2601
-I0511 11:50:55.676990  5581 caffe.cpp:501] detection_eval = 0.0434762
-I0511 11:50:55.676992  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.676995  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.676997  5581 caffe.cpp:501] detection_eval = 6.58266
-I0511 11:50:55.677000  5581 caffe.cpp:501] detection_eval = 11.2964
-I0511 11:50:55.677001  5581 caffe.cpp:501] detection_eval = 0.0451837
-I0511 11:50:55.677003  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.677006  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.677008  5581 caffe.cpp:501] detection_eval = 6.58669
-I0511 11:50:55.677011  5581 caffe.cpp:501] detection_eval = 11.3528
-I0511 11:50:55.677012  5581 caffe.cpp:501] detection_eval = 0.0427262
-I0511 11:50:55.677014  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.677017  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.677019  5581 caffe.cpp:501] detection_eval = 6.59476
-I0511 11:50:55.677021  5581 caffe.cpp:501] detection_eval = 11.3266
-I0511 11:50:55.677023  5581 caffe.cpp:501] detection_eval = 0.0412815
-I0511 11:50:55.680585  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680595  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680599  5581 caffe.cpp:501] detection_eval = 6.59879
-I0511 11:50:55.680603  5581 caffe.cpp:501] detection_eval = 11.3609
-I0511 11:50:55.680606  5581 caffe.cpp:501] detection_eval = 0.0484833
-I0511 11:50:55.680610  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.680613  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.680616  5581 caffe.cpp:501] detection_eval = 6.60081
-I0511 11:50:55.680620  5581 caffe.cpp:501] detection_eval = 11.371
-I0511 11:50:55.680624  5581 caffe.cpp:501] detection_eval = 0.0438451
-I0511 11:50:55.680627  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.680630  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.680634  5581 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:50:55.680637  5581 caffe.cpp:501] detection_eval = 11.371
-I0511 11:50:55.680640  5581 caffe.cpp:501] detection_eval = 0.0414156
-I0511 11:50:55.680644  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.680647  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.680650  5581 caffe.cpp:501] detection_eval = 6.60685
-I0511 11:50:55.680654  5581 caffe.cpp:501] detection_eval = 11.4194
-I0511 11:50:55.680657  5581 caffe.cpp:501] detection_eval = 0.037859
-I0511 11:50:55.680666  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680670  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680672  5581 caffe.cpp:501] detection_eval = 6.6129
-I0511 11:50:55.680675  5581 caffe.cpp:501] detection_eval = 11.4032
-I0511 11:50:55.680677  5581 caffe.cpp:501] detection_eval = 0.0393683
-I0511 11:50:55.680680  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680685  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680687  5581 caffe.cpp:501] detection_eval = 6.61694
-I0511 11:50:55.680691  5581 caffe.cpp:501] detection_eval = 11.4617
-I0511 11:50:55.680694  5581 caffe.cpp:501] detection_eval = 0.0462445
-I0511 11:50:55.680697  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.680701  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.680703  5581 caffe.cpp:501] detection_eval = 6.61694
-I0511 11:50:55.680706  5581 caffe.cpp:501] detection_eval = 11.5081
-I0511 11:50:55.680711  5581 caffe.cpp:501] detection_eval = 0.0451816
-I0511 11:50:55.680713  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680717  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.680721  5581 caffe.cpp:501] detection_eval = 6.61694
-I0511 11:50:55.680723  5581 caffe.cpp:501] detection_eval = 11.5383
-I0511 11:50:55.680727  5581 caffe.cpp:501] detection_eval = 0.0431461
-I0511 11:50:55.680730  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680734  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680737  5581 caffe.cpp:501] detection_eval = 6.62097
-I0511 11:50:55.680740  5581 caffe.cpp:501] detection_eval = 11.5141
-I0511 11:50:55.680743  5581 caffe.cpp:501] detection_eval = 0.0417651
-I0511 11:50:55.680747  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680750  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680753  5581 caffe.cpp:501] detection_eval = 6.62702
-I0511 11:50:55.680757  5581 caffe.cpp:501] detection_eval = 11.5242
-I0511 11:50:55.680760  5581 caffe.cpp:501] detection_eval = 0.0376938
-I0511 11:50:55.680763  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.680766  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.680770  5581 caffe.cpp:501] detection_eval = 6.63105
-I0511 11:50:55.680773  5581 caffe.cpp:501] detection_eval = 11.5867
-I0511 11:50:55.680778  5581 caffe.cpp:501] detection_eval = 0.0394057
-I0511 11:50:55.680780  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680783  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680786  5581 caffe.cpp:501] detection_eval = 6.63306
-I0511 11:50:55.680789  5581 caffe.cpp:501] detection_eval = 11.6613
-I0511 11:50:55.680794  5581 caffe.cpp:501] detection_eval = 0.0416283
-I0511 11:50:55.680797  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680800  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680804  5581 caffe.cpp:501] detection_eval = 6.63508
-I0511 11:50:55.680807  5581 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:50:55.680810  5581 caffe.cpp:501] detection_eval = 0.0394006
-I0511 11:50:55.680814  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680816  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680820  5581 caffe.cpp:501] detection_eval = 6.64113
-I0511 11:50:55.680824  5581 caffe.cpp:501] detection_eval = 11.6774
-I0511 11:50:55.680826  5581 caffe.cpp:501] detection_eval = 0.0416138
-I0511 11:50:55.680829  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680830  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.680833  5581 caffe.cpp:501] detection_eval = 6.64718
-I0511 11:50:55.680836  5581 caffe.cpp:501] detection_eval = 11.6512
-I0511 11:50:55.680840  5581 caffe.cpp:501] detection_eval = 0.0441298
-I0511 11:50:55.680843  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.680846  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.680850  5581 caffe.cpp:501] detection_eval = 6.65323
-I0511 11:50:55.680852  5581 caffe.cpp:501] detection_eval = 11.6613
-I0511 11:50:55.680860  5581 caffe.cpp:501] detection_eval = 0.040598
-I0511 11:50:55.680863  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.680867  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.680871  5581 caffe.cpp:501] detection_eval = 6.65726
-I0511 11:50:55.680873  5581 caffe.cpp:501] detection_eval = 11.6653
-I0511 11:50:55.680877  5581 caffe.cpp:501] detection_eval = 0.0421925
-I0511 11:50:55.680881  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.680883  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680886  5581 caffe.cpp:501] detection_eval = 6.66331
-I0511 11:50:55.680889  5581 caffe.cpp:501] detection_eval = 11.6331
-I0511 11:50:55.680893  5581 caffe.cpp:501] detection_eval = 0.0367033
-I0511 11:50:55.680896  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.680900  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680903  5581 caffe.cpp:501] detection_eval = 6.66532
-I0511 11:50:55.680907  5581 caffe.cpp:501] detection_eval = 11.6452
-I0511 11:50:55.680910  5581 caffe.cpp:501] detection_eval = 0.0413331
-I0511 11:50:55.680913  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.680917  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.680920  5581 caffe.cpp:501] detection_eval = 6.66734
-I0511 11:50:55.680923  5581 caffe.cpp:501] detection_eval = 11.6552
-I0511 11:50:55.680927  5581 caffe.cpp:501] detection_eval = 0.0404099
-I0511 11:50:55.680929  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.680933  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.680936  5581 caffe.cpp:501] detection_eval = 6.67137
-I0511 11:50:55.680939  5581 caffe.cpp:501] detection_eval = 11.6371
-I0511 11:50:55.680943  5581 caffe.cpp:501] detection_eval = 0.0405138
-I0511 11:50:55.680946  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680949  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.680953  5581 caffe.cpp:501] detection_eval = 6.67137
-I0511 11:50:55.680956  5581 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:50:55.680959  5581 caffe.cpp:501] detection_eval = 0.0369072
-I0511 11:50:55.680963  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680966  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680969  5581 caffe.cpp:501] detection_eval = 6.68145
-I0511 11:50:55.680974  5581 caffe.cpp:501] detection_eval = 11.6149
-I0511 11:50:55.680975  5581 caffe.cpp:501] detection_eval = 0.0393978
-I0511 11:50:55.680977  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680979  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.680984  5581 caffe.cpp:501] detection_eval = 6.68548
-I0511 11:50:55.680986  5581 caffe.cpp:501] detection_eval = 11.6472
-I0511 11:50:55.680990  5581 caffe.cpp:501] detection_eval = 0.042582
-I0511 11:50:55.680994  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.680996  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681000  5581 caffe.cpp:501] detection_eval = 6.68952
-I0511 11:50:55.681004  5581 caffe.cpp:501] detection_eval = 11.6835
-I0511 11:50:55.681007  5581 caffe.cpp:501] detection_eval = 0.0463598
-I0511 11:50:55.681010  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.681011  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.681013  5581 caffe.cpp:501] detection_eval = 6.68952
-I0511 11:50:55.681017  5581 caffe.cpp:501] detection_eval = 11.744
-I0511 11:50:55.681020  5581 caffe.cpp:501] detection_eval = 0.0451782
-I0511 11:50:55.681022  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.681025  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.681027  5581 caffe.cpp:501] detection_eval = 6.69355
-I0511 11:50:55.681030  5581 caffe.cpp:501] detection_eval = 11.7722
-I0511 11:50:55.681032  5581 caffe.cpp:501] detection_eval = 0.0414692
-I0511 11:50:55.681035  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681036  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681040  5581 caffe.cpp:501] detection_eval = 6.69355
-I0511 11:50:55.681044  5581 caffe.cpp:501] detection_eval = 11.8085
-I0511 11:50:55.681046  5581 caffe.cpp:501] detection_eval = 0.0398301
-I0511 11:50:55.681048  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681051  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681053  5581 caffe.cpp:501] detection_eval = 6.69758
-I0511 11:50:55.681056  5581 caffe.cpp:501] detection_eval = 11.8024
-I0511 11:50:55.681057  5581 caffe.cpp:501] detection_eval = 0.0399019
-I0511 11:50:55.681059  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681061  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.681064  5581 caffe.cpp:501] detection_eval = 6.70363
-I0511 11:50:55.681066  5581 caffe.cpp:501] detection_eval = 11.7863
-I0511 11:50:55.681068  5581 caffe.cpp:501] detection_eval = 0.0409525
-I0511 11:50:55.681071  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681073  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681076  5581 caffe.cpp:501] detection_eval = 6.70363
-I0511 11:50:55.681077  5581 caffe.cpp:501] detection_eval = 11.8508
-I0511 11:50:55.681079  5581 caffe.cpp:501] detection_eval = 0.0380396
-I0511 11:50:55.681082  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681084  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681087  5581 caffe.cpp:501] detection_eval = 6.70968
-I0511 11:50:55.681088  5581 caffe.cpp:501] detection_eval = 11.8165
-I0511 11:50:55.681092  5581 caffe.cpp:501] detection_eval = 0.0388819
-I0511 11:50:55.681093  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681095  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681097  5581 caffe.cpp:501] detection_eval = 6.71371
-I0511 11:50:55.681099  5581 caffe.cpp:501] detection_eval = 11.8508
-I0511 11:50:55.681102  5581 caffe.cpp:501] detection_eval = 0.0387082
-I0511 11:50:55.681104  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681107  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681108  5581 caffe.cpp:501] detection_eval = 6.72177
-I0511 11:50:55.681110  5581 caffe.cpp:501] detection_eval = 11.8367
-I0511 11:50:55.681113  5581 caffe.cpp:501] detection_eval = 0.0440489
-I0511 11:50:55.681115  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681118  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681119  5581 caffe.cpp:501] detection_eval = 6.72581
-I0511 11:50:55.681121  5581 caffe.cpp:501] detection_eval = 11.8286
-I0511 11:50:55.681124  5581 caffe.cpp:501] detection_eval = 0.0400435
-I0511 11:50:55.681126  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681128  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681130  5581 caffe.cpp:501] detection_eval = 6.73387
-I0511 11:50:55.681133  5581 caffe.cpp:501] detection_eval = 11.8105
-I0511 11:50:55.681135  5581 caffe.cpp:501] detection_eval = 0.0408022
-I0511 11:50:55.681138  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681139  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681141  5581 caffe.cpp:501] detection_eval = 6.74395
-I0511 11:50:55.681143  5581 caffe.cpp:501] detection_eval = 11.7097
-I0511 11:50:55.681146  5581 caffe.cpp:501] detection_eval = 0.0409307
-I0511 11:50:55.681149  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681150  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681152  5581 caffe.cpp:501] detection_eval = 6.74597
-I0511 11:50:55.681154  5581 caffe.cpp:501] detection_eval = 11.7016
-I0511 11:50:55.681157  5581 caffe.cpp:501] detection_eval = 0.0338636
-I0511 11:50:55.681159  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.681161  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.681164  5581 caffe.cpp:501] detection_eval = 6.75
-I0511 11:50:55.681165  5581 caffe.cpp:501] detection_eval = 11.6895
-I0511 11:50:55.681169  5581 caffe.cpp:501] detection_eval = 0.0394032
-I0511 11:50:55.681170  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681172  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681174  5581 caffe.cpp:501] detection_eval = 6.75
-I0511 11:50:55.681180  5581 caffe.cpp:501] detection_eval = 11.75
-I0511 11:50:55.681181  5581 caffe.cpp:501] detection_eval = 0.0362908
-I0511 11:50:55.681185  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681186  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681188  5581 caffe.cpp:501] detection_eval = 6.75403
-I0511 11:50:55.681190  5581 caffe.cpp:501] detection_eval = 11.754
-I0511 11:50:55.681193  5581 caffe.cpp:501] detection_eval = 0.0392379
-I0511 11:50:55.681195  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681197  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681200  5581 caffe.cpp:501] detection_eval = 6.75403
-I0511 11:50:55.681201  5581 caffe.cpp:501] detection_eval = 11.869
-I0511 11:50:55.681205  5581 caffe.cpp:501] detection_eval = 0.0458373
-I0511 11:50:55.681206  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681208  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681210  5581 caffe.cpp:501] detection_eval = 6.75605
-I0511 11:50:55.681212  5581 caffe.cpp:501] detection_eval = 11.8992
-I0511 11:50:55.681215  5581 caffe.cpp:501] detection_eval = 0.0346768
-I0511 11:50:55.681217  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681219  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681221  5581 caffe.cpp:501] detection_eval = 6.76008
-I0511 11:50:55.681223  5581 caffe.cpp:501] detection_eval = 11.875
-I0511 11:50:55.681226  5581 caffe.cpp:501] detection_eval = 0.0334062
-I0511 11:50:55.681227  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681231  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681232  5581 caffe.cpp:501] detection_eval = 6.77218
-I0511 11:50:55.681234  5581 caffe.cpp:501] detection_eval = 11.8024
-I0511 11:50:55.681236  5581 caffe.cpp:501] detection_eval = 0.0393263
-I0511 11:50:55.681238  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681241  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681243  5581 caffe.cpp:501] detection_eval = 6.77419
-I0511 11:50:55.681246  5581 caffe.cpp:501] detection_eval = 11.8185
-I0511 11:50:55.681247  5581 caffe.cpp:501] detection_eval = 0.0362455
-I0511 11:50:55.681249  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681252  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681253  5581 caffe.cpp:501] detection_eval = 6.77823
-I0511 11:50:55.681257  5581 caffe.cpp:501] detection_eval = 11.7863
-I0511 11:50:55.681258  5581 caffe.cpp:501] detection_eval = 0.0368334
-I0511 11:50:55.681260  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681263  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681265  5581 caffe.cpp:501] detection_eval = 6.79032
-I0511 11:50:55.681267  5581 caffe.cpp:501] detection_eval = 11.6734
-I0511 11:50:55.681269  5581 caffe.cpp:501] detection_eval = 0.0370783
-I0511 11:50:55.681272  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681274  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681277  5581 caffe.cpp:501] detection_eval = 6.79637
-I0511 11:50:55.681278  5581 caffe.cpp:501] detection_eval = 11.6452
-I0511 11:50:55.681280  5581 caffe.cpp:501] detection_eval = 0.0398687
-I0511 11:50:55.681282  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681285  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681288  5581 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:50:55.681289  5581 caffe.cpp:501] detection_eval = 11.6976
-I0511 11:50:55.681291  5581 caffe.cpp:501] detection_eval = 0.0381377
-I0511 11:50:55.681293  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681296  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681298  5581 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:50:55.681301  5581 caffe.cpp:501] detection_eval = 11.7903
-I0511 11:50:55.681305  5581 caffe.cpp:501] detection_eval = 0.0413339
-I0511 11:50:55.681308  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681309  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681319  5581 caffe.cpp:501] detection_eval = 6.80444
-I0511 11:50:55.681321  5581 caffe.cpp:501] detection_eval = 11.7843
-I0511 11:50:55.681324  5581 caffe.cpp:501] detection_eval = 0.0380796
-I0511 11:50:55.681326  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681329  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681330  5581 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:50:55.681332  5581 caffe.cpp:501] detection_eval = 11.7419
-I0511 11:50:55.681334  5581 caffe.cpp:501] detection_eval = 0.0394887
-I0511 11:50:55.681337  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681339  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681341  5581 caffe.cpp:501] detection_eval = 6.81653
-I0511 11:50:55.681344  5581 caffe.cpp:501] detection_eval = 11.7177
-I0511 11:50:55.681346  5581 caffe.cpp:501] detection_eval = 0.0369103
-I0511 11:50:55.681349  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681350  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681352  5581 caffe.cpp:501] detection_eval = 6.82056
-I0511 11:50:55.681354  5581 caffe.cpp:501] detection_eval = 11.7198
-I0511 11:50:55.681357  5581 caffe.cpp:501] detection_eval = 0.0381167
-I0511 11:50:55.681360  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681361  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681363  5581 caffe.cpp:501] detection_eval = 6.82863
-I0511 11:50:55.681365  5581 caffe.cpp:501] detection_eval = 11.6976
-I0511 11:50:55.681368  5581 caffe.cpp:501] detection_eval = 0.0405401
-I0511 11:50:55.681370  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681372  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681375  5581 caffe.cpp:501] detection_eval = 6.83065
-I0511 11:50:55.681377  5581 caffe.cpp:501] detection_eval = 11.7722
-I0511 11:50:55.681380  5581 caffe.cpp:501] detection_eval = 0.0391582
-I0511 11:50:55.681381  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681383  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681385  5581 caffe.cpp:501] detection_eval = 6.83669
-I0511 11:50:55.681387  5581 caffe.cpp:501] detection_eval = 11.752
-I0511 11:50:55.681391  5581 caffe.cpp:501] detection_eval = 0.0412488
-I0511 11:50:55.681392  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681394  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681396  5581 caffe.cpp:501] detection_eval = 6.83871
-I0511 11:50:55.681398  5581 caffe.cpp:501] detection_eval = 11.7944
-I0511 11:50:55.681401  5581 caffe.cpp:501] detection_eval = 0.0354297
-I0511 11:50:55.681403  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681406  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.681407  5581 caffe.cpp:501] detection_eval = 6.83871
-I0511 11:50:55.681411  5581 caffe.cpp:501] detection_eval = 11.8669
-I0511 11:50:55.681412  5581 caffe.cpp:501] detection_eval = 0.0418504
-I0511 11:50:55.681414  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681416  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681418  5581 caffe.cpp:501] detection_eval = 6.84274
-I0511 11:50:55.681421  5581 caffe.cpp:501] detection_eval = 11.8891
-I0511 11:50:55.681423  5581 caffe.cpp:501] detection_eval = 0.0377028
-I0511 11:50:55.681426  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681427  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681429  5581 caffe.cpp:501] detection_eval = 6.84274
-I0511 11:50:55.681432  5581 caffe.cpp:501] detection_eval = 11.9657
-I0511 11:50:55.681434  5581 caffe.cpp:501] detection_eval = 0.037204
-I0511 11:50:55.681437  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681438  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681440  5581 caffe.cpp:501] detection_eval = 6.84677
-I0511 11:50:55.681442  5581 caffe.cpp:501] detection_eval = 12.004
-I0511 11:50:55.681445  5581 caffe.cpp:501] detection_eval = 0.0387492
-I0511 11:50:55.681447  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681452  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681454  5581 caffe.cpp:501] detection_eval = 6.85081
-I0511 11:50:55.681457  5581 caffe.cpp:501] detection_eval = 12.0746
-I0511 11:50:55.681459  5581 caffe.cpp:501] detection_eval = 0.0480775
-I0511 11:50:55.681462  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.681463  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681465  5581 caffe.cpp:501] detection_eval = 6.85685
-I0511 11:50:55.681468  5581 caffe.cpp:501] detection_eval = 12.0867
-I0511 11:50:55.681470  5581 caffe.cpp:501] detection_eval = 0.0445336
-I0511 11:50:55.681473  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681474  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681476  5581 caffe.cpp:501] detection_eval = 6.85887
-I0511 11:50:55.681478  5581 caffe.cpp:501] detection_eval = 12.1391
-I0511 11:50:55.681480  5581 caffe.cpp:501] detection_eval = 0.0436437
-I0511 11:50:55.681483  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681485  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681488  5581 caffe.cpp:501] detection_eval = 6.8629
-I0511 11:50:55.681489  5581 caffe.cpp:501] detection_eval = 12.1754
-I0511 11:50:55.681491  5581 caffe.cpp:501] detection_eval = 0.039225
-I0511 11:50:55.681494  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681496  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681499  5581 caffe.cpp:501] detection_eval = 6.86492
-I0511 11:50:55.681500  5581 caffe.cpp:501] detection_eval = 12.2399
-I0511 11:50:55.681502  5581 caffe.cpp:501] detection_eval = 0.043345
-I0511 11:50:55.681504  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681507  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681509  5581 caffe.cpp:501] detection_eval = 6.85282
-I0511 11:50:55.681511  5581 caffe.cpp:501] detection_eval = 12.2056
-I0511 11:50:55.681514  5581 caffe.cpp:501] detection_eval = 0.0443765
-I0511 11:50:55.681515  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681519  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681520  5581 caffe.cpp:501] detection_eval = 6.86089
-I0511 11:50:55.681522  5581 caffe.cpp:501] detection_eval = 12.1391
-I0511 11:50:55.681524  5581 caffe.cpp:501] detection_eval = 0.0425658
-I0511 11:50:55.681526  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681529  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681531  5581 caffe.cpp:501] detection_eval = 6.86492
-I0511 11:50:55.681533  5581 caffe.cpp:501] detection_eval = 12.1734
-I0511 11:50:55.681535  5581 caffe.cpp:501] detection_eval = 0.0386758
-I0511 11:50:55.681537  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681540  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681542  5581 caffe.cpp:501] detection_eval = 6.87097
-I0511 11:50:55.681545  5581 caffe.cpp:501] detection_eval = 12.2117
-I0511 11:50:55.681546  5581 caffe.cpp:501] detection_eval = 0.0415744
-I0511 11:50:55.681548  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681550  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681553  5581 caffe.cpp:501] detection_eval = 6.875
-I0511 11:50:55.681555  5581 caffe.cpp:501] detection_eval = 12.2843
-I0511 11:50:55.681557  5581 caffe.cpp:501] detection_eval = 0.0469725
-I0511 11:50:55.681560  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681561  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.681565  5581 caffe.cpp:501] detection_eval = 6.87702
-I0511 11:50:55.681566  5581 caffe.cpp:501] detection_eval = 12.373
-I0511 11:50:55.681568  5581 caffe.cpp:501] detection_eval = 0.0490451
-I0511 11:50:55.681571  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.681573  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.681576  5581 caffe.cpp:501] detection_eval = 6.88105
-I0511 11:50:55.681577  5581 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:50:55.681579  5581 caffe.cpp:501] detection_eval = 0.0459364
-I0511 11:50:55.681581  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681586  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681588  5581 caffe.cpp:501] detection_eval = 6.88911
-I0511 11:50:55.681591  5581 caffe.cpp:501] detection_eval = 12.4113
-I0511 11:50:55.681593  5581 caffe.cpp:501] detection_eval = 0.0461567
-I0511 11:50:55.681596  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681597  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681599  5581 caffe.cpp:501] detection_eval = 6.89113
-I0511 11:50:55.681602  5581 caffe.cpp:501] detection_eval = 12.4859
-I0511 11:50:55.681604  5581 caffe.cpp:501] detection_eval = 0.0445998
-I0511 11:50:55.681607  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681608  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681610  5581 caffe.cpp:501] detection_eval = 6.89516
-I0511 11:50:55.681612  5581 caffe.cpp:501] detection_eval = 12.5101
-I0511 11:50:55.681615  5581 caffe.cpp:501] detection_eval = 0.0377217
-I0511 11:50:55.681617  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681619  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.681622  5581 caffe.cpp:501] detection_eval = 6.90121
-I0511 11:50:55.681624  5581 caffe.cpp:501] detection_eval = 12.6089
-I0511 11:50:55.681627  5581 caffe.cpp:501] detection_eval = 0.0414381
-I0511 11:50:55.681628  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681630  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681632  5581 caffe.cpp:501] detection_eval = 6.90524
-I0511 11:50:55.681634  5581 caffe.cpp:501] detection_eval = 12.625
-I0511 11:50:55.681638  5581 caffe.cpp:501] detection_eval = 0.0353203
-I0511 11:50:55.681639  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681641  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681643  5581 caffe.cpp:501] detection_eval = 6.90927
-I0511 11:50:55.681645  5581 caffe.cpp:501] detection_eval = 12.7198
-I0511 11:50:55.681648  5581 caffe.cpp:501] detection_eval = 0.0347852
-I0511 11:50:55.681650  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681653  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681654  5581 caffe.cpp:501] detection_eval = 7.22581
-I0511 11:50:55.681656  5581 caffe.cpp:501] detection_eval = 8.06855
-I0511 11:50:55.681658  5581 caffe.cpp:501] detection_eval = 0.0856414
-I0511 11:50:55.681661  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.681663  5581 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:50:55.681665  5581 caffe.cpp:501] detection_eval = 7.22984
-I0511 11:50:55.681668  5581 caffe.cpp:501] detection_eval = 8.21169
-I0511 11:50:55.681670  5581 caffe.cpp:501] detection_eval = 0.0634881
-I0511 11:50:55.681673  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.681674  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.681676  5581 caffe.cpp:501] detection_eval = 7.22984
-I0511 11:50:55.681679  5581 caffe.cpp:501] detection_eval = 8.29032
-I0511 11:50:55.681680  5581 caffe.cpp:501] detection_eval = 0.0491501
-I0511 11:50:55.681684  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681685  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681689  5581 caffe.cpp:501] detection_eval = 7.23185
-I0511 11:50:55.681692  5581 caffe.cpp:501] detection_eval = 8.37097
-I0511 11:50:55.681694  5581 caffe.cpp:501] detection_eval = 0.0485129
-I0511 11:50:55.681696  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681699  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681700  5581 caffe.cpp:501] detection_eval = 7.23589
-I0511 11:50:55.681704  5581 caffe.cpp:501] detection_eval = 8.44556
-I0511 11:50:55.681705  5581 caffe.cpp:501] detection_eval = 0.0500122
-I0511 11:50:55.681707  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681710  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.681711  5581 caffe.cpp:501] detection_eval = 7.23992
-I0511 11:50:55.681713  5581 caffe.cpp:501] detection_eval = 8.44758
-I0511 11:50:55.681716  5581 caffe.cpp:501] detection_eval = 0.0491981
-I0511 11:50:55.681720  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681723  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681725  5581 caffe.cpp:501] detection_eval = 7.24395
-I0511 11:50:55.681727  5581 caffe.cpp:501] detection_eval = 8.46169
-I0511 11:50:55.681730  5581 caffe.cpp:501] detection_eval = 0.0435018
-I0511 11:50:55.681732  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681735  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681736  5581 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:50:55.681738  5581 caffe.cpp:501] detection_eval = 8.49798
-I0511 11:50:55.681740  5581 caffe.cpp:501] detection_eval = 0.0455176
-I0511 11:50:55.681742  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.681744  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681747  5581 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:50:55.681749  5581 caffe.cpp:501] detection_eval = 8.5746
-I0511 11:50:55.681751  5581 caffe.cpp:501] detection_eval = 0.0454906
-I0511 11:50:55.681753  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681756  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681758  5581 caffe.cpp:501] detection_eval = 7.25
-I0511 11:50:55.681761  5581 caffe.cpp:501] detection_eval = 8.59274
-I0511 11:50:55.681762  5581 caffe.cpp:501] detection_eval = 0.0388731
-I0511 11:50:55.681764  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681766  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.681768  5581 caffe.cpp:501] detection_eval = 7.25202
-I0511 11:50:55.681771  5581 caffe.cpp:501] detection_eval = 8.64315
-I0511 11:50:55.681773  5581 caffe.cpp:501] detection_eval = 0.0439831
-I0511 11:50:55.681776  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681777  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681779  5581 caffe.cpp:501] detection_eval = 7.25403
-I0511 11:50:55.681782  5581 caffe.cpp:501] detection_eval = 8.67339
-I0511 11:50:55.681784  5581 caffe.cpp:501] detection_eval = 0.0479034
-I0511 11:50:55.681787  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681788  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.681790  5581 caffe.cpp:501] detection_eval = 7.25605
-I0511 11:50:55.681792  5581 caffe.cpp:501] detection_eval = 8.69556
-I0511 11:50:55.681794  5581 caffe.cpp:501] detection_eval = 0.0442465
-I0511 11:50:55.681797  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681798  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.681802  5581 caffe.cpp:501] detection_eval = 7.26008
-I0511 11:50:55.681803  5581 caffe.cpp:501] detection_eval = 8.73387
-I0511 11:50:55.681805  5581 caffe.cpp:501] detection_eval = 0.0396222
-I0511 11:50:55.681808  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681810  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681813  5581 caffe.cpp:501] detection_eval = 7.2621
-I0511 11:50:55.681814  5581 caffe.cpp:501] detection_eval = 8.78024
-I0511 11:50:55.681816  5581 caffe.cpp:501] detection_eval = 0.0417208
-I0511 11:50:55.681818  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681821  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681823  5581 caffe.cpp:501] detection_eval = 7.26411
-I0511 11:50:55.681825  5581 caffe.cpp:501] detection_eval = 8.81048
-I0511 11:50:55.681828  5581 caffe.cpp:501] detection_eval = 0.0406238
-I0511 11:50:55.681829  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681833  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681834  5581 caffe.cpp:501] detection_eval = 7.26613
-I0511 11:50:55.681836  5581 caffe.cpp:501] detection_eval = 8.83468
-I0511 11:50:55.681838  5581 caffe.cpp:501] detection_eval = 0.0393886
-I0511 11:50:55.681840  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681843  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681844  5581 caffe.cpp:501] detection_eval = 7.26613
-I0511 11:50:55.681848  5581 caffe.cpp:501] detection_eval = 8.91331
-I0511 11:50:55.681849  5581 caffe.cpp:501] detection_eval = 0.0400285
-I0511 11:50:55.681854  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681857  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.681859  5581 caffe.cpp:501] detection_eval = 7.27218
-I0511 11:50:55.681861  5581 caffe.cpp:501] detection_eval = 8.86492
-I0511 11:50:55.681864  5581 caffe.cpp:501] detection_eval = 0.0419766
-I0511 11:50:55.681866  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.681869  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.681870  5581 caffe.cpp:501] detection_eval = 7.27419
-I0511 11:50:55.681872  5581 caffe.cpp:501] detection_eval = 8.91734
-I0511 11:50:55.681874  5581 caffe.cpp:501] detection_eval = 0.0419344
-I0511 11:50:55.681877  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681879  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.681881  5581 caffe.cpp:501] detection_eval = 7.28024
-I0511 11:50:55.681885  5581 caffe.cpp:501] detection_eval = 8.88306
-I0511 11:50:55.681886  5581 caffe.cpp:501] detection_eval = 0.0417776
-I0511 11:50:55.681888  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681890  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681892  5581 caffe.cpp:501] detection_eval = 7.28024
-I0511 11:50:55.681895  5581 caffe.cpp:501] detection_eval = 8.96573
-I0511 11:50:55.681897  5581 caffe.cpp:501] detection_eval = 0.0458027
-I0511 11:50:55.681900  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.681901  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.681903  5581 caffe.cpp:501] detection_eval = 7.28226
-I0511 11:50:55.681906  5581 caffe.cpp:501] detection_eval = 9.01411
-I0511 11:50:55.681908  5581 caffe.cpp:501] detection_eval = 0.0483489
-I0511 11:50:55.681910  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681912  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.681915  5581 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:50:55.681917  5581 caffe.cpp:501] detection_eval = 8.90927
-I0511 11:50:55.681919  5581 caffe.cpp:501] detection_eval = 0.0468659
-I0511 11:50:55.681921  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.681923  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681926  5581 caffe.cpp:501] detection_eval = 7.29839
-I0511 11:50:55.681928  5581 caffe.cpp:501] detection_eval = 8.93952
-I0511 11:50:55.681931  5581 caffe.cpp:501] detection_eval = 0.0468604
-I0511 11:50:55.681933  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.681936  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.681938  5581 caffe.cpp:501] detection_eval = 7.30444
-I0511 11:50:55.681941  5581 caffe.cpp:501] detection_eval = 8.94153
-I0511 11:50:55.681943  5581 caffe.cpp:501] detection_eval = 0.0424661
-I0511 11:50:55.681946  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681947  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681951  5581 caffe.cpp:501] detection_eval = 7.31048
-I0511 11:50:55.681952  5581 caffe.cpp:501] detection_eval = 8.9375
-I0511 11:50:55.681954  5581 caffe.cpp:501] detection_eval = 0.0467155
-I0511 11:50:55.681957  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681959  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681962  5581 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:50:55.681963  5581 caffe.cpp:501] detection_eval = 8.99798
-I0511 11:50:55.681965  5581 caffe.cpp:501] detection_eval = 0.0462472
-I0511 11:50:55.681968  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681970  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.681973  5581 caffe.cpp:501] detection_eval = 7.29839
-I0511 11:50:55.681975  5581 caffe.cpp:501] detection_eval = 9.03226
-I0511 11:50:55.681977  5581 caffe.cpp:501] detection_eval = 0.0433089
-I0511 11:50:55.681980  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681982  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681984  5581 caffe.cpp:501] detection_eval = 7.30242
-I0511 11:50:55.681987  5581 caffe.cpp:501] detection_eval = 9.02016
-I0511 11:50:55.681993  5581 caffe.cpp:501] detection_eval = 0.039932
-I0511 11:50:55.681995  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681998  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682000  5581 caffe.cpp:501] detection_eval = 7.30645
-I0511 11:50:55.682003  5581 caffe.cpp:501] detection_eval = 9.02621
-I0511 11:50:55.682004  5581 caffe.cpp:501] detection_eval = 0.0462682
-I0511 11:50:55.682008  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682009  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682011  5581 caffe.cpp:501] detection_eval = 7.30847
-I0511 11:50:55.682014  5581 caffe.cpp:501] detection_eval = 9.06653
-I0511 11:50:55.682016  5581 caffe.cpp:501] detection_eval = 0.0449975
-I0511 11:50:55.682018  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682020  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682023  5581 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:50:55.682024  5581 caffe.cpp:501] detection_eval = 9.11089
-I0511 11:50:55.682027  5581 caffe.cpp:501] detection_eval = 0.0458093
-I0511 11:50:55.682029  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682031  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682034  5581 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:50:55.682035  5581 caffe.cpp:501] detection_eval = 9.19556
-I0511 11:50:55.682039  5581 caffe.cpp:501] detection_eval = 0.0452179
-I0511 11:50:55.682040  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682042  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682044  5581 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:50:55.682046  5581 caffe.cpp:501] detection_eval = 9.28427
-I0511 11:50:55.682049  5581 caffe.cpp:501] detection_eval = 0.0439263
-I0511 11:50:55.682050  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682054  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682055  5581 caffe.cpp:501] detection_eval = 7.31653
-I0511 11:50:55.682057  5581 caffe.cpp:501] detection_eval = 9.27016
-I0511 11:50:55.682060  5581 caffe.cpp:501] detection_eval = 0.0388889
-I0511 11:50:55.682061  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682063  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682066  5581 caffe.cpp:501] detection_eval = 7.31855
-I0511 11:50:55.682068  5581 caffe.cpp:501] detection_eval = 9.32056
-I0511 11:50:55.682070  5581 caffe.cpp:501] detection_eval = 0.0438795
-I0511 11:50:55.682271  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682279  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682282  5581 caffe.cpp:501] detection_eval = 7.31855
-I0511 11:50:55.682284  5581 caffe.cpp:501] detection_eval = 9.35282
-I0511 11:50:55.682287  5581 caffe.cpp:501] detection_eval = 0.0378971
-I0511 11:50:55.682289  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.682291  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.682293  5581 caffe.cpp:501] detection_eval = 7.31855
-I0511 11:50:55.682296  5581 caffe.cpp:501] detection_eval = 9.40927
-I0511 11:50:55.682298  5581 caffe.cpp:501] detection_eval = 0.0433352
-I0511 11:50:55.682301  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682302  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682304  5581 caffe.cpp:501] detection_eval = 7.3246
-I0511 11:50:55.682307  5581 caffe.cpp:501] detection_eval = 9.43548
-I0511 11:50:55.682309  5581 caffe.cpp:501] detection_eval = 0.040325
-I0511 11:50:55.682312  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682313  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682315  5581 caffe.cpp:501] detection_eval = 7.3246
-I0511 11:50:55.682318  5581 caffe.cpp:501] detection_eval = 9.49798
-I0511 11:50:55.682320  5581 caffe.cpp:501] detection_eval = 0.0409152
-I0511 11:50:55.682322  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682324  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682327  5581 caffe.cpp:501] detection_eval = 7.32661
-I0511 11:50:55.682334  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.682337  5581 caffe.cpp:501] detection_eval = 0.0402087
-I0511 11:50:55.682339  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682341  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682343  5581 caffe.cpp:501] detection_eval = 7.33266
-I0511 11:50:55.682345  5581 caffe.cpp:501] detection_eval = 9.47581
-I0511 11:50:55.682348  5581 caffe.cpp:501] detection_eval = 0.0378348
-I0511 11:50:55.682349  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682353  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682354  5581 caffe.cpp:501] detection_eval = 7.33468
-I0511 11:50:55.682356  5581 caffe.cpp:501] detection_eval = 9.49395
-I0511 11:50:55.682358  5581 caffe.cpp:501] detection_eval = 0.0387339
-I0511 11:50:55.682360  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682363  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682365  5581 caffe.cpp:501] detection_eval = 7.33669
-I0511 11:50:55.682368  5581 caffe.cpp:501] detection_eval = 9.52823
-I0511 11:50:55.682369  5581 caffe.cpp:501] detection_eval = 0.0410701
-I0511 11:50:55.682371  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682374  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682376  5581 caffe.cpp:501] detection_eval = 7.34073
-I0511 11:50:55.682379  5581 caffe.cpp:501] detection_eval = 9.55645
-I0511 11:50:55.682380  5581 caffe.cpp:501] detection_eval = 0.0420968
-I0511 11:50:55.682382  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682384  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682386  5581 caffe.cpp:501] detection_eval = 7.34073
-I0511 11:50:55.682389  5581 caffe.cpp:501] detection_eval = 9.58065
-I0511 11:50:55.682391  5581 caffe.cpp:501] detection_eval = 0.0384954
-I0511 11:50:55.682394  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.682395  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.682397  5581 caffe.cpp:501] detection_eval = 7.34476
-I0511 11:50:55.682400  5581 caffe.cpp:501] detection_eval = 9.6129
-I0511 11:50:55.682402  5581 caffe.cpp:501] detection_eval = 0.0406598
-I0511 11:50:55.682404  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682406  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.682409  5581 caffe.cpp:501] detection_eval = 7.35484
-I0511 11:50:55.682410  5581 caffe.cpp:501] detection_eval = 9.55645
-I0511 11:50:55.682413  5581 caffe.cpp:501] detection_eval = 0.040175
-I0511 11:50:55.682415  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682417  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682420  5581 caffe.cpp:501] detection_eval = 7.35887
-I0511 11:50:55.682421  5581 caffe.cpp:501] detection_eval = 9.57056
-I0511 11:50:55.682425  5581 caffe.cpp:501] detection_eval = 0.0418544
-I0511 11:50:55.682426  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682428  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682430  5581 caffe.cpp:501] detection_eval = 7.35887
-I0511 11:50:55.682432  5581 caffe.cpp:501] detection_eval = 9.64718
-I0511 11:50:55.682435  5581 caffe.cpp:501] detection_eval = 0.0400233
-I0511 11:50:55.682437  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682440  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682441  5581 caffe.cpp:501] detection_eval = 7.3629
-I0511 11:50:55.682443  5581 caffe.cpp:501] detection_eval = 9.63105
-I0511 11:50:55.682446  5581 caffe.cpp:501] detection_eval = 0.0385768
-I0511 11:50:55.682448  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682451  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.682452  5581 caffe.cpp:501] detection_eval = 7.3629
-I0511 11:50:55.682454  5581 caffe.cpp:501] detection_eval = 9.70565
-I0511 11:50:55.682456  5581 caffe.cpp:501] detection_eval = 0.0420802
-I0511 11:50:55.682459  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682461  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682463  5581 caffe.cpp:501] detection_eval = 7.36492
-I0511 11:50:55.682468  5581 caffe.cpp:501] detection_eval = 9.80242
-I0511 11:50:55.682471  5581 caffe.cpp:501] detection_eval = 0.0501388
-I0511 11:50:55.682472  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.682476  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.682477  5581 caffe.cpp:501] detection_eval = 7.36492
-I0511 11:50:55.682479  5581 caffe.cpp:501] detection_eval = 9.9375
-I0511 11:50:55.682482  5581 caffe.cpp:501] detection_eval = 0.0473965
-I0511 11:50:55.682483  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682485  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.682488  5581 caffe.cpp:501] detection_eval = 7.36492
-I0511 11:50:55.682490  5581 caffe.cpp:501] detection_eval = 10.0161
-I0511 11:50:55.682492  5581 caffe.cpp:501] detection_eval = 0.0437935
-I0511 11:50:55.682495  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682497  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682499  5581 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:50:55.682502  5581 caffe.cpp:501] detection_eval = 9.99597
-I0511 11:50:55.682505  5581 caffe.cpp:501] detection_eval = 0.0449916
-I0511 11:50:55.682509  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682514  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682518  5581 caffe.cpp:501] detection_eval = 7.35484
-I0511 11:50:55.682520  5581 caffe.cpp:501] detection_eval = 10.0403
-I0511 11:50:55.682523  5581 caffe.cpp:501] detection_eval = 0.0470892
-I0511 11:50:55.682524  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.682526  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.682529  5581 caffe.cpp:501] detection_eval = 7.35887
-I0511 11:50:55.682531  5581 caffe.cpp:501] detection_eval = 10.0504
-I0511 11:50:55.682533  5581 caffe.cpp:501] detection_eval = 0.0472107
-I0511 11:50:55.682535  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682538  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.682540  5581 caffe.cpp:501] detection_eval = 7.3629
-I0511 11:50:55.682543  5581 caffe.cpp:501] detection_eval = 10.0726
-I0511 11:50:55.682544  5581 caffe.cpp:501] detection_eval = 0.0453176
-I0511 11:50:55.682546  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682548  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682550  5581 caffe.cpp:501] detection_eval = 7.36694
-I0511 11:50:55.682554  5581 caffe.cpp:501] detection_eval = 10.1048
-I0511 11:50:55.682555  5581 caffe.cpp:501] detection_eval = 0.0473685
-I0511 11:50:55.682557  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682559  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682562  5581 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:50:55.682564  5581 caffe.cpp:501] detection_eval = 10.129
-I0511 11:50:55.682566  5581 caffe.cpp:501] detection_eval = 0.0509039
-I0511 11:50:55.682569  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.682570  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.682574  5581 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:50:55.682575  5581 caffe.cpp:501] detection_eval = 10.1573
-I0511 11:50:55.682577  5581 caffe.cpp:501] detection_eval = 0.0425583
-I0511 11:50:55.682579  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682582  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682585  5581 caffe.cpp:501] detection_eval = 7.38306
-I0511 11:50:55.682586  5581 caffe.cpp:501] detection_eval = 10.1956
-I0511 11:50:55.682588  5581 caffe.cpp:501] detection_eval = 0.0446588
-I0511 11:50:55.682590  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682593  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682595  5581 caffe.cpp:501] detection_eval = 7.38508
-I0511 11:50:55.682597  5581 caffe.cpp:501] detection_eval = 10.2621
-I0511 11:50:55.682600  5581 caffe.cpp:501] detection_eval = 0.0470283
-I0511 11:50:55.682601  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682605  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682610  5581 caffe.cpp:501] detection_eval = 7.38911
-I0511 11:50:55.682611  5581 caffe.cpp:501] detection_eval = 10.2903
-I0511 11:50:55.682613  5581 caffe.cpp:501] detection_eval = 0.040443
-I0511 11:50:55.682616  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682618  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682621  5581 caffe.cpp:501] detection_eval = 7.39113
-I0511 11:50:55.682622  5581 caffe.cpp:501] detection_eval = 10.3367
-I0511 11:50:55.682624  5581 caffe.cpp:501] detection_eval = 0.042165
-I0511 11:50:55.682627  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682629  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682631  5581 caffe.cpp:501] detection_eval = 7.39113
-I0511 11:50:55.682633  5581 caffe.cpp:501] detection_eval = 10.3952
-I0511 11:50:55.682636  5581 caffe.cpp:501] detection_eval = 0.0446252
-I0511 11:50:55.682638  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682641  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682642  5581 caffe.cpp:501] detection_eval = 7.39113
-I0511 11:50:55.682644  5581 caffe.cpp:501] detection_eval = 10.4879
-I0511 11:50:55.682646  5581 caffe.cpp:501] detection_eval = 0.0435957
-I0511 11:50:55.682648  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682651  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682653  5581 caffe.cpp:501] detection_eval = 7.39718
-I0511 11:50:55.682656  5581 caffe.cpp:501] detection_eval = 10.5202
-I0511 11:50:55.682657  5581 caffe.cpp:501] detection_eval = 0.0478907
-I0511 11:50:55.682659  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.682662  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.682664  5581 caffe.cpp:501] detection_eval = 7.40323
-I0511 11:50:55.682667  5581 caffe.cpp:501] detection_eval = 10.498
-I0511 11:50:55.682668  5581 caffe.cpp:501] detection_eval = 0.0469434
-I0511 11:50:55.682670  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682672  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682675  5581 caffe.cpp:501] detection_eval = 7.41532
-I0511 11:50:55.682677  5581 caffe.cpp:501] detection_eval = 10.3851
-I0511 11:50:55.682679  5581 caffe.cpp:501] detection_eval = 0.0478128
-I0511 11:50:55.682682  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682683  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682687  5581 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:50:55.682688  5581 caffe.cpp:501] detection_eval = 10.4698
-I0511 11:50:55.682690  5581 caffe.cpp:501] detection_eval = 0.0479721
-I0511 11:50:55.682693  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682694  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682698  5581 caffe.cpp:501] detection_eval = 7.4254
-I0511 11:50:55.682699  5581 caffe.cpp:501] detection_eval = 10.506
-I0511 11:50:55.682701  5581 caffe.cpp:501] detection_eval = 0.0453031
-I0511 11:50:55.682703  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682705  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682708  5581 caffe.cpp:501] detection_eval = 7.40927
-I0511 11:50:55.682710  5581 caffe.cpp:501] detection_eval = 10.494
-I0511 11:50:55.682713  5581 caffe.cpp:501] detection_eval = 0.0457791
-I0511 11:50:55.682714  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682716  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682719  5581 caffe.cpp:501] detection_eval = 7.41129
-I0511 11:50:55.682721  5581 caffe.cpp:501] detection_eval = 10.5544
-I0511 11:50:55.682723  5581 caffe.cpp:501] detection_eval = 0.0452257
-I0511 11:50:55.682725  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682727  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682729  5581 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:50:55.682731  5581 caffe.cpp:501] detection_eval = 10.5706
-I0511 11:50:55.682734  5581 caffe.cpp:501] detection_eval = 0.0516385
-I0511 11:50:55.682736  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.682739  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.682744  5581 caffe.cpp:501] detection_eval = 7.40524
-I0511 11:50:55.682746  5581 caffe.cpp:501] detection_eval = 10.5323
-I0511 11:50:55.682749  5581 caffe.cpp:501] detection_eval = 0.0446368
-I0511 11:50:55.682750  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682754  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.682755  5581 caffe.cpp:501] detection_eval = 7.39718
-I0511 11:50:55.682757  5581 caffe.cpp:501] detection_eval = 10.4778
-I0511 11:50:55.682760  5581 caffe.cpp:501] detection_eval = 0.0507295
-I0511 11:50:55.682761  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.682765  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.682766  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.682768  5581 caffe.cpp:501] detection_eval = 10.4133
-I0511 11:50:55.682770  5581 caffe.cpp:501] detection_eval = 0.053087
-I0511 11:50:55.682772  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.682775  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.682777  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.682780  5581 caffe.cpp:501] detection_eval = 10.5101
-I0511 11:50:55.682781  5581 caffe.cpp:501] detection_eval = 0.047828
-I0511 11:50:55.682783  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682785  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.682787  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.682790  5581 caffe.cpp:501] detection_eval = 10.5766
-I0511 11:50:55.682792  5581 caffe.cpp:501] detection_eval = 0.0488476
-I0511 11:50:55.682795  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.682796  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.682798  5581 caffe.cpp:501] detection_eval = 7.41532
-I0511 11:50:55.682801  5581 caffe.cpp:501] detection_eval = 10.5544
-I0511 11:50:55.682803  5581 caffe.cpp:501] detection_eval = 0.0478669
-I0511 11:50:55.682806  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682807  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.682809  5581 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:50:55.682811  5581 caffe.cpp:501] detection_eval = 10.5665
-I0511 11:50:55.682814  5581 caffe.cpp:501] detection_eval = 0.0429634
-I0511 11:50:55.682816  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.683734  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.683744  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.683748  5581 caffe.cpp:501] detection_eval = 10.4798
-I0511 11:50:55.683753  5581 caffe.cpp:501] detection_eval = 0.0412703
-I0511 11:50:55.683758  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.683763  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.683766  5581 caffe.cpp:501] detection_eval = 7.40927
-I0511 11:50:55.683769  5581 caffe.cpp:501] detection_eval = 10.5363
-I0511 11:50:55.683774  5581 caffe.cpp:501] detection_eval = 0.0458134
-I0511 11:50:55.683779  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.683782  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.683786  5581 caffe.cpp:501] detection_eval = 7.41331
-I0511 11:50:55.683790  5581 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:50:55.683794  5581 caffe.cpp:501] detection_eval = 0.0491089
-I0511 11:50:55.683799  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.683802  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.683806  5581 caffe.cpp:501] detection_eval = 7.39718
-I0511 11:50:55.683810  5581 caffe.cpp:501] detection_eval = 10.5343
-I0511 11:50:55.683815  5581 caffe.cpp:501] detection_eval = 0.0419852
-I0511 11:50:55.683818  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.683822  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.683826  5581 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:50:55.683830  5581 caffe.cpp:501] detection_eval = 10.5988
-I0511 11:50:55.683835  5581 caffe.cpp:501] detection_eval = 0.0454163
-I0511 11:50:55.683840  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.683847  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683852  5581 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:50:55.683856  5581 caffe.cpp:501] detection_eval = 10.6855
-I0511 11:50:55.683861  5581 caffe.cpp:501] detection_eval = 0.0427413
-I0511 11:50:55.683864  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.683868  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.683872  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.683876  5581 caffe.cpp:501] detection_eval = 10.6371
-I0511 11:50:55.683881  5581 caffe.cpp:501] detection_eval = 0.0447473
-I0511 11:50:55.683884  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.683888  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.683892  5581 caffe.cpp:501] detection_eval = 7.41129
-I0511 11:50:55.683897  5581 caffe.cpp:501] detection_eval = 10.6351
-I0511 11:50:55.683900  5581 caffe.cpp:501] detection_eval = 0.0411808
-I0511 11:50:55.683902  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.683904  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.683907  5581 caffe.cpp:501] detection_eval = 7.41331
-I0511 11:50:55.683909  5581 caffe.cpp:501] detection_eval = 10.6673
-I0511 11:50:55.683912  5581 caffe.cpp:501] detection_eval = 0.0455204
-I0511 11:50:55.683913  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.683915  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683918  5581 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:50:55.683920  5581 caffe.cpp:501] detection_eval = 10.6915
-I0511 11:50:55.683923  5581 caffe.cpp:501] detection_eval = 0.0404305
-I0511 11:50:55.683924  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.683928  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.683929  5581 caffe.cpp:501] detection_eval = 7.42339
-I0511 11:50:55.683931  5581 caffe.cpp:501] detection_eval = 10.6573
-I0511 11:50:55.683933  5581 caffe.cpp:501] detection_eval = 0.0409796
-I0511 11:50:55.683935  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.683938  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.683940  5581 caffe.cpp:501] detection_eval = 7.4254
-I0511 11:50:55.683943  5581 caffe.cpp:501] detection_eval = 10.6915
-I0511 11:50:55.683944  5581 caffe.cpp:501] detection_eval = 0.0417903
-I0511 11:50:55.683948  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.683949  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683951  5581 caffe.cpp:501] detection_eval = 7.43145
-I0511 11:50:55.683954  5581 caffe.cpp:501] detection_eval = 10.6431
-I0511 11:50:55.683956  5581 caffe.cpp:501] detection_eval = 0.0431551
-I0511 11:50:55.683959  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.683960  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683962  5581 caffe.cpp:501] detection_eval = 7.44355
-I0511 11:50:55.683964  5581 caffe.cpp:501] detection_eval = 10.5484
-I0511 11:50:55.683967  5581 caffe.cpp:501] detection_eval = 0.0394992
-I0511 11:50:55.683969  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.683971  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.683974  5581 caffe.cpp:501] detection_eval = 7.4496
-I0511 11:50:55.683975  5581 caffe.cpp:501] detection_eval = 10.5484
-I0511 11:50:55.683979  5581 caffe.cpp:501] detection_eval = 0.044845
-I0511 11:50:55.683980  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.683982  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.683984  5581 caffe.cpp:501] detection_eval = 7.45565
-I0511 11:50:55.683987  5581 caffe.cpp:501] detection_eval = 10.5706
-I0511 11:50:55.683990  5581 caffe.cpp:501] detection_eval = 0.0456398
-I0511 11:50:55.683991  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.683993  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683995  5581 caffe.cpp:501] detection_eval = 7.46371
-I0511 11:50:55.683998  5581 caffe.cpp:501] detection_eval = 10.5101
-I0511 11:50:55.684000  5581 caffe.cpp:501] detection_eval = 0.0438768
-I0511 11:50:55.684005  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.684007  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.684010  5581 caffe.cpp:501] detection_eval = 7.46371
-I0511 11:50:55.684012  5581 caffe.cpp:501] detection_eval = 10.5766
-I0511 11:50:55.684015  5581 caffe.cpp:501] detection_eval = 0.0471612
-I0511 11:50:55.684016  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684020  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684021  5581 caffe.cpp:501] detection_eval = 7.46774
-I0511 11:50:55.684023  5581 caffe.cpp:501] detection_eval = 10.6149
-I0511 11:50:55.684026  5581 caffe.cpp:501] detection_eval = 0.0489806
-I0511 11:50:55.684027  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.684029  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684032  5581 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:50:55.684034  5581 caffe.cpp:501] detection_eval = 10.5141
-I0511 11:50:55.684036  5581 caffe.cpp:501] detection_eval = 0.0471047
-I0511 11:50:55.684038  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.684041  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.684043  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.684046  5581 caffe.cpp:501] detection_eval = 10.5444
-I0511 11:50:55.684047  5581 caffe.cpp:501] detection_eval = 0.0454401
-I0511 11:50:55.684051  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.684053  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.684056  5581 caffe.cpp:501] detection_eval = 7.48387
-I0511 11:50:55.684059  5581 caffe.cpp:501] detection_eval = 10.5746
-I0511 11:50:55.684062  5581 caffe.cpp:501] detection_eval = 0.0470474
-I0511 11:50:55.684063  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684065  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684067  5581 caffe.cpp:501] detection_eval = 7.48589
-I0511 11:50:55.684069  5581 caffe.cpp:501] detection_eval = 10.6694
-I0511 11:50:55.684072  5581 caffe.cpp:501] detection_eval = 0.0476696
-I0511 11:50:55.684074  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.684077  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.684078  5581 caffe.cpp:501] detection_eval = 7.4879
-I0511 11:50:55.684080  5581 caffe.cpp:501] detection_eval = 10.6855
-I0511 11:50:55.684659  5581 caffe.cpp:501] detection_eval = 0.0402981
-I0511 11:50:55.684667  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.684670  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.684672  5581 caffe.cpp:501] detection_eval = 7.49194
-I0511 11:50:55.684674  5581 caffe.cpp:501] detection_eval = 10.6492
-I0511 11:50:55.684677  5581 caffe.cpp:501] detection_eval = 0.0420391
-I0511 11:50:55.684679  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.684681  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.684684  5581 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:50:55.684686  5581 caffe.cpp:501] detection_eval = 10.621
-I0511 11:50:55.684689  5581 caffe.cpp:501] detection_eval = 0.0434594
-I0511 11:50:55.684691  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684693  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.684695  5581 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:50:55.684697  5581 caffe.cpp:501] detection_eval = 10.6935
-I0511 11:50:55.684700  5581 caffe.cpp:501] detection_eval = 0.0417081
-I0511 11:50:55.684702  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.684705  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.684706  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.684710  5581 caffe.cpp:501] detection_eval = 10.7097
-I0511 11:50:55.684711  5581 caffe.cpp:501] detection_eval = 0.0412181
-I0511 11:50:55.684713  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684715  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684718  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684720  5581 caffe.cpp:501] detection_eval = 10.7379
-I0511 11:50:55.684722  5581 caffe.cpp:501] detection_eval = 0.0399339
-I0511 11:50:55.684728  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684731  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684733  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684736  5581 caffe.cpp:501] detection_eval = 10.8105
-I0511 11:50:55.684738  5581 caffe.cpp:501] detection_eval = 0.0444372
-I0511 11:50:55.684741  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.684742  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.684744  5581 caffe.cpp:501] detection_eval = 7.46573
-I0511 11:50:55.684747  5581 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:50:55.684749  5581 caffe.cpp:501] detection_eval = 0.0440735
-I0511 11:50:55.684751  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.684753  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.684756  5581 caffe.cpp:501] detection_eval = 7.46976
-I0511 11:50:55.684758  5581 caffe.cpp:501] detection_eval = 10.8065
-I0511 11:50:55.684761  5581 caffe.cpp:501] detection_eval = 0.0413515
-I0511 11:50:55.684762  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684764  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684767  5581 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:50:55.684769  5581 caffe.cpp:501] detection_eval = 10.8468
-I0511 11:50:55.684772  5581 caffe.cpp:501] detection_eval = 0.0372818
-I0511 11:50:55.684773  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.684775  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.684778  5581 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:50:55.684780  5581 caffe.cpp:501] detection_eval = 10.9173
-I0511 11:50:55.684782  5581 caffe.cpp:501] detection_eval = 0.0365128
-I0511 11:50:55.684784  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.684787  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.684789  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.684792  5581 caffe.cpp:501] detection_eval = 10.875
-I0511 11:50:55.684793  5581 caffe.cpp:501] detection_eval = 0.0408489
-I0511 11:50:55.684795  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.684798  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684800  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684803  5581 caffe.cpp:501] detection_eval = 10.9355
-I0511 11:50:55.684805  5581 caffe.cpp:501] detection_eval = 0.0390675
-I0511 11:50:55.684808  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.684809  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.684811  5581 caffe.cpp:501] detection_eval = 7.48387
-I0511 11:50:55.684814  5581 caffe.cpp:501] detection_eval = 10.9516
-I0511 11:50:55.684816  5581 caffe.cpp:501] detection_eval = 0.0401807
-I0511 11:50:55.684818  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684820  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684823  5581 caffe.cpp:501] detection_eval = 7.4879
-I0511 11:50:55.684825  5581 caffe.cpp:501] detection_eval = 10.9617
-I0511 11:50:55.684828  5581 caffe.cpp:501] detection_eval = 0.0392556
-I0511 11:50:55.684829  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.684831  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684834  5581 caffe.cpp:501] detection_eval = 7.48992
-I0511 11:50:55.684836  5581 caffe.cpp:501] detection_eval = 11.0121
-I0511 11:50:55.684839  5581 caffe.cpp:501] detection_eval = 0.0392255
-I0511 11:50:55.684841  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.684844  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.684845  5581 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:50:55.684847  5581 caffe.cpp:501] detection_eval = 10.9657
-I0511 11:50:55.684850  5581 caffe.cpp:501] detection_eval = 0.0426831
-I0511 11:50:55.684852  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684854  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.684856  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684859  5581 caffe.cpp:501] detection_eval = 10.9718
-I0511 11:50:55.684864  5581 caffe.cpp:501] detection_eval = 0.0473402
-I0511 11:50:55.684866  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684868  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.684870  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684872  5581 caffe.cpp:501] detection_eval = 11.0645
-I0511 11:50:55.684875  5581 caffe.cpp:501] detection_eval = 0.0464121
-I0511 11:50:55.684877  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.684880  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684881  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684883  5581 caffe.cpp:501] detection_eval = 11.127
-I0511 11:50:55.684886  5581 caffe.cpp:501] detection_eval = 0.0424388
-I0511 11:50:55.684888  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684890  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.684892  5581 caffe.cpp:501] detection_eval = 7.48589
-I0511 11:50:55.684895  5581 caffe.cpp:501] detection_eval = 11.1331
-I0511 11:50:55.684897  5581 caffe.cpp:501] detection_eval = 0.0401256
-I0511 11:50:55.684900  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684901  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.684903  5581 caffe.cpp:501] detection_eval = 7.47379
-I0511 11:50:55.684906  5581 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:50:55.684908  5581 caffe.cpp:501] detection_eval = 0.0425275
-I0511 11:50:55.684911  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684912  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.684914  5581 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:50:55.684916  5581 caffe.cpp:501] detection_eval = 11.1351
-I0511 11:50:55.684919  5581 caffe.cpp:501] detection_eval = 0.0435966
-I0511 11:50:55.684921  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684923  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.684926  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.684928  5581 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:50:55.684931  5581 caffe.cpp:501] detection_eval = 0.0434549
-I0511 11:50:55.684932  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.684934  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685073  5581 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:50:55.685081  5581 caffe.cpp:501] detection_eval = 11.2077
-I0511 11:50:55.685084  5581 caffe.cpp:501] detection_eval = 0.0367104
-I0511 11:50:55.685086  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685089  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685091  5581 caffe.cpp:501] detection_eval = 7.46774
-I0511 11:50:55.685093  5581 caffe.cpp:501] detection_eval = 11.1915
-I0511 11:50:55.685096  5581 caffe.cpp:501] detection_eval = 0.0421262
-I0511 11:50:55.685098  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685101  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.685102  5581 caffe.cpp:501] detection_eval = 7.47581
-I0511 11:50:55.685106  5581 caffe.cpp:501] detection_eval = 11.131
-I0511 11:50:55.685107  5581 caffe.cpp:501] detection_eval = 0.0413167
-I0511 11:50:55.685109  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685111  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.685114  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.685117  5581 caffe.cpp:501] detection_eval = 11.0867
-I0511 11:50:55.685118  5581 caffe.cpp:501] detection_eval = 0.0430667
-I0511 11:50:55.685120  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685123  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685125  5581 caffe.cpp:501] detection_eval = 7.48589
-I0511 11:50:55.685127  5581 caffe.cpp:501] detection_eval = 11.0423
-I0511 11:50:55.685129  5581 caffe.cpp:501] detection_eval = 0.04003
-I0511 11:50:55.685132  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685134  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.685137  5581 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:50:55.685138  5581 caffe.cpp:501] detection_eval = 11
-I0511 11:50:55.685144  5581 caffe.cpp:501] detection_eval = 0.0428109
-I0511 11:50:55.685148  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.685149  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685151  5581 caffe.cpp:501] detection_eval = 7.47581
-I0511 11:50:55.685154  5581 caffe.cpp:501] detection_eval = 10.9758
-I0511 11:50:55.685156  5581 caffe.cpp:501] detection_eval = 0.0399438
-I0511 11:50:55.685158  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685161  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685163  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.685165  5581 caffe.cpp:501] detection_eval = 10.9798
-I0511 11:50:55.685168  5581 caffe.cpp:501] detection_eval = 0.0389812
-I0511 11:50:55.685170  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685173  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685174  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.685176  5581 caffe.cpp:501] detection_eval = 11.0302
-I0511 11:50:55.685178  5581 caffe.cpp:501] detection_eval = 0.04282
-I0511 11:50:55.685181  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.685184  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.685185  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.685189  5581 caffe.cpp:501] detection_eval = 11.1089
-I0511 11:50:55.685190  5581 caffe.cpp:501] detection_eval = 0.0414344
-I0511 11:50:55.685192  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.685194  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685196  5581 caffe.cpp:501] detection_eval = 7.49395
-I0511 11:50:55.685199  5581 caffe.cpp:501] detection_eval = 11.0444
-I0511 11:50:55.685201  5581 caffe.cpp:501] detection_eval = 0.0440561
-I0511 11:50:55.685204  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685205  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.685207  5581 caffe.cpp:501] detection_eval = 7.49597
-I0511 11:50:55.685210  5581 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:50:55.685212  5581 caffe.cpp:501] detection_eval = 0.0436372
-I0511 11:50:55.685214  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685216  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685220  5581 caffe.cpp:501] detection_eval = 7.5
-I0511 11:50:55.685221  5581 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:50:55.685223  5581 caffe.cpp:501] detection_eval = 0.0405424
-I0511 11:50:55.685225  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685228  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685230  5581 caffe.cpp:501] detection_eval = 7.50403
-I0511 11:50:55.685232  5581 caffe.cpp:501] detection_eval = 11.0867
-I0511 11:50:55.685235  5581 caffe.cpp:501] detection_eval = 0.0439476
-I0511 11:50:55.685236  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685240  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685241  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.685243  5581 caffe.cpp:501] detection_eval = 11.0867
-I0511 11:50:55.685245  5581 caffe.cpp:501] detection_eval = 0.0410073
-I0511 11:50:55.685247  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685250  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685252  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.685254  5581 caffe.cpp:501] detection_eval = 11.1754
-I0511 11:50:55.685256  5581 caffe.cpp:501] detection_eval = 0.0386972
-I0511 11:50:55.685258  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685261  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685263  5581 caffe.cpp:501] detection_eval = 7.5121
-I0511 11:50:55.685266  5581 caffe.cpp:501] detection_eval = 11.1976
-I0511 11:50:55.685267  5581 caffe.cpp:501] detection_eval = 0.0414127
-I0511 11:50:55.685269  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685272  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685274  5581 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:50:55.685278  5581 caffe.cpp:501] detection_eval = 11.1653
-I0511 11:50:55.685281  5581 caffe.cpp:501] detection_eval = 0.0389808
-I0511 11:50:55.685283  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685286  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685288  5581 caffe.cpp:501] detection_eval = 7.5
-I0511 11:50:55.685290  5581 caffe.cpp:501] detection_eval = 11.1976
-I0511 11:50:55.685292  5581 caffe.cpp:501] detection_eval = 0.0401342
-I0511 11:50:55.685294  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685297  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685299  5581 caffe.cpp:501] detection_eval = 7.50605
-I0511 11:50:55.685302  5581 caffe.cpp:501] detection_eval = 11.2137
-I0511 11:50:55.685303  5581 caffe.cpp:501] detection_eval = 0.0410004
-I0511 11:50:55.685307  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.685308  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.685310  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.685312  5581 caffe.cpp:501] detection_eval = 11.25
-I0511 11:50:55.685314  5581 caffe.cpp:501] detection_eval = 0.0405454
-I0511 11:50:55.685317  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685319  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685322  5581 caffe.cpp:501] detection_eval = 7.51815
-I0511 11:50:55.685323  5581 caffe.cpp:501] detection_eval = 11.1411
-I0511 11:50:55.685326  5581 caffe.cpp:501] detection_eval = 0.0426148
-I0511 11:50:55.685328  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.685330  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.685333  5581 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:50:55.685334  5581 caffe.cpp:501] detection_eval = 11.1714
-I0511 11:50:55.685338  5581 caffe.cpp:501] detection_eval = 0.0390047
-I0511 11:50:55.685339  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685341  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.685343  5581 caffe.cpp:501] detection_eval = 7.52419
-I0511 11:50:55.685345  5581 caffe.cpp:501] detection_eval = 11.2157
-I0511 11:50:55.685348  5581 caffe.cpp:501] detection_eval = 0.0375133
-I0511 11:50:55.685899  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685906  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685909  5581 caffe.cpp:501] detection_eval = 7.53226
-I0511 11:50:55.685911  5581 caffe.cpp:501] detection_eval = 11.1633
-I0511 11:50:55.685914  5581 caffe.cpp:501] detection_eval = 0.0388819
-I0511 11:50:55.685916  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685919  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.685920  5581 caffe.cpp:501] detection_eval = 7.53831
-I0511 11:50:55.685923  5581 caffe.cpp:501] detection_eval = 11.1411
-I0511 11:50:55.685925  5581 caffe.cpp:501] detection_eval = 0.0386862
-I0511 11:50:55.685927  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.685930  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685932  5581 caffe.cpp:501] detection_eval = 7.54435
-I0511 11:50:55.685935  5581 caffe.cpp:501] detection_eval = 11.129
-I0511 11:50:55.685936  5581 caffe.cpp:501] detection_eval = 0.0423654
-I0511 11:50:55.685940  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685941  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685943  5581 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:50:55.685945  5581 caffe.cpp:501] detection_eval = 11.1653
-I0511 11:50:55.685948  5581 caffe.cpp:501] detection_eval = 0.0426899
-I0511 11:50:55.685950  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685952  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685955  5581 caffe.cpp:501] detection_eval = 7.54839
-I0511 11:50:55.685956  5581 caffe.cpp:501] detection_eval = 11.1875
-I0511 11:50:55.685959  5581 caffe.cpp:501] detection_eval = 0.0403573
-I0511 11:50:55.685961  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.685963  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.685969  5581 caffe.cpp:501] detection_eval = 7.54839
-I0511 11:50:55.685972  5581 caffe.cpp:501] detection_eval = 11.254
-I0511 11:50:55.685974  5581 caffe.cpp:501] detection_eval = 0.0407816
-I0511 11:50:55.685976  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685979  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685981  5581 caffe.cpp:501] detection_eval = 7.55242
-I0511 11:50:55.685983  5581 caffe.cpp:501] detection_eval = 11.2238
-I0511 11:50:55.685986  5581 caffe.cpp:501] detection_eval = 0.0359233
-I0511 11:50:55.685987  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685991  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685992  5581 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:50:55.685994  5581 caffe.cpp:501] detection_eval = 11.2399
-I0511 11:50:55.685997  5581 caffe.cpp:501] detection_eval = 0.0348085
-I0511 11:50:55.685999  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.686002  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.686003  5581 caffe.cpp:501] detection_eval = 7.56653
-I0511 11:50:55.686005  5581 caffe.cpp:501] detection_eval = 11.2137
-I0511 11:50:55.686007  5581 caffe.cpp:501] detection_eval = 0.0421677
-I0511 11:50:55.686010  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.686012  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.686014  5581 caffe.cpp:501] detection_eval = 7.56855
-I0511 11:50:55.686017  5581 caffe.cpp:501] detection_eval = 11.2762
-I0511 11:50:55.686018  5581 caffe.cpp:501] detection_eval = 0.0450314
-I0511 11:50:55.686022  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.686023  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686025  5581 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:50:55.686028  5581 caffe.cpp:501] detection_eval = 11.3044
-I0511 11:50:55.686029  5581 caffe.cpp:501] detection_eval = 0.0410906
-I0511 11:50:55.686033  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.686034  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.686036  5581 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:50:55.686038  5581 caffe.cpp:501] detection_eval = 11.1935
-I0511 11:50:55.686041  5581 caffe.cpp:501] detection_eval = 0.0495097
-I0511 11:50:55.686043  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.686045  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686048  5581 caffe.cpp:501] detection_eval = 7.59073
-I0511 11:50:55.686049  5581 caffe.cpp:501] detection_eval = 11.1552
-I0511 11:50:55.686053  5581 caffe.cpp:501] detection_eval = 0.0434247
-I0511 11:50:55.686054  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.686056  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686058  5581 caffe.cpp:501] detection_eval = 7.59274
-I0511 11:50:55.686060  5581 caffe.cpp:501] detection_eval = 11.1996
-I0511 11:50:55.686064  5581 caffe.cpp:501] detection_eval = 0.0404944
-I0511 11:50:55.686065  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686067  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.686069  5581 caffe.cpp:501] detection_eval = 7.59274
-I0511 11:50:55.686071  5581 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:50:55.686074  5581 caffe.cpp:501] detection_eval = 0.0398476
-I0511 11:50:55.686076  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.686079  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686080  5581 caffe.cpp:501] detection_eval = 7.59879
-I0511 11:50:55.686082  5581 caffe.cpp:501] detection_eval = 11.2641
-I0511 11:50:55.686085  5581 caffe.cpp:501] detection_eval = 0.0413881
-I0511 11:50:55.686087  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686089  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.686091  5581 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:50:55.686094  5581 caffe.cpp:501] detection_eval = 11.2298
-I0511 11:50:55.686096  5581 caffe.cpp:501] detection_eval = 0.0435242
-I0511 11:50:55.686098  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686100  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.686105  5581 caffe.cpp:501] detection_eval = 7.6129
-I0511 11:50:55.686108  5581 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:50:55.686110  5581 caffe.cpp:501] detection_eval = 0.0469073
-I0511 11:50:55.686112  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.686115  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686117  5581 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:50:55.686120  5581 caffe.cpp:501] detection_eval = 11.2782
-I0511 11:50:55.686121  5581 caffe.cpp:501] detection_eval = 0.0396851
-I0511 11:50:55.686123  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686126  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.686128  5581 caffe.cpp:501] detection_eval = 7.62298
-I0511 11:50:55.686131  5581 caffe.cpp:501] detection_eval = 11.25
-I0511 11:50:55.686132  5581 caffe.cpp:501] detection_eval = 0.0402459
-I0511 11:50:55.686134  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686137  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.686139  5581 caffe.cpp:501] detection_eval = 7.625
-I0511 11:50:55.686141  5581 caffe.cpp:501] detection_eval = 11.2681
-I0511 11:50:55.686143  5581 caffe.cpp:501] detection_eval = 0.0385593
-I0511 11:50:55.686146  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686148  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686151  5581 caffe.cpp:501] detection_eval = 7.62903
-I0511 11:50:55.686152  5581 caffe.cpp:501] detection_eval = 11.2742
-I0511 11:50:55.686154  5581 caffe.cpp:501] detection_eval = 0.041121
-I0511 11:50:55.686157  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.686159  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.686161  5581 caffe.cpp:501] detection_eval = 7.61089
-I0511 11:50:55.686164  5581 caffe.cpp:501] detection_eval = 11.3327
-I0511 11:50:55.686168  5581 caffe.cpp:501] detection_eval = 0.0439781
-I0511 11:50:55.686170  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.686172  5581 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:50:55.686175  5581 caffe.cpp:501] detection_eval = 7.6129
-I0511 11:50:55.688241  5581 caffe.cpp:501] detection_eval = 11.3911
-I0511 11:50:55.688256  5581 caffe.cpp:501] detection_eval = 0.0422813
-I0511 11:50:55.688261  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.688266  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688268  5581 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:50:55.688272  5581 caffe.cpp:501] detection_eval = 11.4274
-I0511 11:50:55.688275  5581 caffe.cpp:501] detection_eval = 0.0426222
-I0511 11:50:55.688279  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.688282  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.688287  5581 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:50:55.688289  5581 caffe.cpp:501] detection_eval = 11.5101
-I0511 11:50:55.688292  5581 caffe.cpp:501] detection_eval = 0.0423069
-I0511 11:50:55.688297  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688300  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688304  5581 caffe.cpp:501] detection_eval = 7.62298
-I0511 11:50:55.688308  5581 caffe.cpp:501] detection_eval = 11.4819
-I0511 11:50:55.688311  5581 caffe.cpp:501] detection_eval = 0.0420618
-I0511 11:50:55.688315  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688318  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688321  5581 caffe.cpp:501] detection_eval = 7.62702
-I0511 11:50:55.688325  5581 caffe.cpp:501] detection_eval = 11.5302
-I0511 11:50:55.688329  5581 caffe.cpp:501] detection_eval = 0.043554
-I0511 11:50:55.688333  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688338  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.688340  5581 caffe.cpp:501] detection_eval = 7.63105
-I0511 11:50:55.688344  5581 caffe.cpp:501] detection_eval = 11.5927
-I0511 11:50:55.688347  5581 caffe.cpp:501] detection_eval = 0.0423784
-I0511 11:50:55.688351  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.688361  5581 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:50:55.688365  5581 caffe.cpp:501] detection_eval = 7.63306
-I0511 11:50:55.688369  5581 caffe.cpp:501] detection_eval = 11.6089
-I0511 11:50:55.688372  5581 caffe.cpp:501] detection_eval = 0.0439374
-I0511 11:50:55.688376  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.688380  5581 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:50:55.688385  5581 caffe.cpp:501] detection_eval = 7.61895
-I0511 11:50:55.688388  5581 caffe.cpp:501] detection_eval = 11.5645
-I0511 11:50:55.688391  5581 caffe.cpp:501] detection_eval = 0.0409858
-I0511 11:50:55.688395  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.688400  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688402  5581 caffe.cpp:501] detection_eval = 7.62097
-I0511 11:50:55.688405  5581 caffe.cpp:501] detection_eval = 11.5887
-I0511 11:50:55.688410  5581 caffe.cpp:501] detection_eval = 0.0433036
-I0511 11:50:55.688412  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688416  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.688421  5581 caffe.cpp:501] detection_eval = 7.62702
-I0511 11:50:55.688423  5581 caffe.cpp:501] detection_eval = 11.5665
-I0511 11:50:55.688427  5581 caffe.cpp:501] detection_eval = 0.0424148
-I0511 11:50:55.688431  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.688434  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688438  5581 caffe.cpp:501] detection_eval = 7.59879
-I0511 11:50:55.688441  5581 caffe.cpp:501] detection_eval = 11.4597
-I0511 11:50:55.688446  5581 caffe.cpp:501] detection_eval = 0.0412049
-I0511 11:50:55.688448  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688452  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.688457  5581 caffe.cpp:501] detection_eval = 7.60282
-I0511 11:50:55.688459  5581 caffe.cpp:501] detection_eval = 11.4899
-I0511 11:50:55.688463  5581 caffe.cpp:501] detection_eval = 0.0375759
-I0511 11:50:55.688467  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.688470  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.688474  5581 caffe.cpp:501] detection_eval = 7.58669
-I0511 11:50:55.688477  5581 caffe.cpp:501] detection_eval = 11.5081
-I0511 11:50:55.688482  5581 caffe.cpp:501] detection_eval = 0.042409
-I0511 11:50:55.688484  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688488  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.688493  5581 caffe.cpp:501] detection_eval = 7.58871
-I0511 11:50:55.688495  5581 caffe.cpp:501] detection_eval = 11.5484
-I0511 11:50:55.688499  5581 caffe.cpp:501] detection_eval = 0.0379165
-I0511 11:50:55.688503  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688506  5581 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:50:55.688509  5581 caffe.cpp:501] detection_eval = 7.57661
-I0511 11:50:55.688513  5581 caffe.cpp:501] detection_eval = 11.4919
-I0511 11:50:55.688518  5581 caffe.cpp:501] detection_eval = 0.0370752
-I0511 11:50:55.688520  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.688539  5581 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:50:55.688544  5581 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:50:55.688547  5581 caffe.cpp:501] detection_eval = 11.4839
-I0511 11:50:55.688551  5581 caffe.cpp:501] detection_eval = 0.0377361
-I0511 11:50:55.688555  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.688558  5581 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:50:55.688561  5581 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:50:55.688565  5581 caffe.cpp:501] detection_eval = 11.4556
-I0511 11:50:55.688568  5581 caffe.cpp:501] detection_eval = 0.0405849
-I0511 11:50:55.688572  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.688575  5581 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:50:55.688580  5581 caffe.cpp:501] detection_eval = 7.57258
-I0511 11:50:55.688582  5581 caffe.cpp:501] detection_eval = 11.4758
-I0511 11:50:55.688586  5581 caffe.cpp:501] detection_eval = 0.037887
-I0511 11:50:55.688591  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.688601  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.688606  5581 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:50:55.688609  5581 caffe.cpp:501] detection_eval = 11.5605
-I0511 11:50:55.688613  5581 caffe.cpp:501] detection_eval = 0.0378704
-I0511 11:50:55.688617  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.688621  5581 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:50:55.688625  5581 caffe.cpp:501] detection_eval = 7.56048
-I0511 11:50:55.688629  5581 caffe.cpp:501] detection_eval = 11.5847
-I0511 11:50:55.688633  5581 caffe.cpp:501] detection_eval = 0.0387462
-I0511 11:50:55.688637  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.688642  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.688645  5581 caffe.cpp:501] detection_eval = 7.56653
-I0511 11:50:55.688648  5581 caffe.cpp:501] detection_eval = 11.6573
-I0511 11:50:55.688653  5581 caffe.cpp:501] detection_eval = 0.0348863
-I0511 11:50:55.688663  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688666  5581 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:50:55.688670  5581 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:50:55.688674  5581 caffe.cpp:501] detection_eval = 11.8044
-I0511 11:50:55.688678  5581 caffe.cpp:501] detection_eval = 0.0350609
-I0511 11:50:55.688683  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.688686  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.688690  5581 caffe.cpp:501] detection_eval = 7.83266
-I0511 11:50:55.688694  5581 caffe.cpp:501] detection_eval = 7.9254
-I0511 11:50:55.688699  5581 caffe.cpp:501] detection_eval = 0.0567618
-I0511 11:50:55.688701  5581 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:50:55.688705  5581 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:50:55.688709  5581 caffe.cpp:501] detection_eval = 7.81653
-I0511 11:50:55.688711  5581 caffe.cpp:501] detection_eval = 7.99597
-I0511 11:50:55.688715  5581 caffe.cpp:501] detection_eval = 0.0480278
-I0511 11:50:55.688719  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688725  5581 caffe.cpp:501] detection_eval = 0.935484
-I0511 11:50:55.688729  5581 caffe.cpp:501] detection_eval = 7.81653
-I0511 11:50:55.688732  5581 caffe.cpp:501] detection_eval = 8.10282
-I0511 11:50:55.688735  5581 caffe.cpp:501] detection_eval = 0.0471522
-I0511 11:50:55.688740  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.688742  5581 caffe.cpp:501] detection_eval = 0.927419
-I0511 11:50:55.688746  5581 caffe.cpp:501] detection_eval = 7.79839
-I0511 11:50:55.688750  5581 caffe.cpp:501] detection_eval = 8.20968
-I0511 11:50:55.688752  5581 caffe.cpp:501] detection_eval = 0.0480241
-I0511 11:50:55.688756  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.688760  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.688765  5581 caffe.cpp:501] detection_eval = 7.8004
-I0511 11:50:55.688767  5581 caffe.cpp:501] detection_eval = 8.27016
-I0511 11:50:55.688771  5581 caffe.cpp:501] detection_eval = 0.0514556
-I0511 11:50:55.688774  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.688778  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.688782  5581 caffe.cpp:501] detection_eval = 7.80444
-I0511 11:50:55.688786  5581 caffe.cpp:501] detection_eval = 8.29637
-I0511 11:50:55.688789  5581 caffe.cpp:501] detection_eval = 0.0425682
-I0511 11:50:55.688793  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.688797  5581 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:50:55.688802  5581 caffe.cpp:501] detection_eval = 7.78831
-I0511 11:50:55.688804  5581 caffe.cpp:501] detection_eval = 8.32056
-I0511 11:50:55.688808  5581 caffe.cpp:501] detection_eval = 0.0429682
-I0511 11:50:55.688812  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.688817  5581 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:50:55.688820  5581 caffe.cpp:501] detection_eval = 7.79032
-I0511 11:50:55.688823  5581 caffe.cpp:501] detection_eval = 8.36694
-I0511 11:50:55.688827  5581 caffe.cpp:501] detection_eval = 0.0469394
-I0511 11:50:55.688838  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688843  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.688846  5581 caffe.cpp:501] detection_eval = 7.79032
-I0511 11:50:55.688850  5581 caffe.cpp:501] detection_eval = 8.40323
-I0511 11:50:55.688854  5581 caffe.cpp:501] detection_eval = 0.0435947
-I0511 11:50:55.688858  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.688863  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.688866  5581 caffe.cpp:501] detection_eval = 7.79435
-I0511 11:50:55.688870  5581 caffe.cpp:501] detection_eval = 8.39113
-I0511 11:50:55.688874  5581 caffe.cpp:501] detection_eval = 0.0455785
-I0511 11:50:55.688879  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688881  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.688885  5581 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:50:55.688889  5581 caffe.cpp:501] detection_eval = 8.40927
-I0511 11:50:55.688894  5581 caffe.cpp:501] detection_eval = 0.0375263
-I0511 11:50:55.688897  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688901  5581 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:50:55.688905  5581 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:50:55.688908  5581 caffe.cpp:501] detection_eval = 8.49395
-I0511 11:50:55.688912  5581 caffe.cpp:501] detection_eval = 0.0382623
-I0511 11:50:55.688916  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.688920  5581 caffe.cpp:501] detection_eval = 0.939516
-I0511 11:50:55.688925  5581 caffe.cpp:501] detection_eval = 7.75806
-I0511 11:50:55.688930  5581 caffe.cpp:501] detection_eval = 8.49597
-I0511 11:50:55.688933  5581 caffe.cpp:501] detection_eval = 0.0384884
-I0511 11:50:55.688937  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.688941  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.688946  5581 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:50:55.688948  5581 caffe.cpp:501] detection_eval = 8.4879
-I0511 11:50:55.688952  5581 caffe.cpp:501] detection_eval = 0.0394526
-I0511 11:50:55.688956  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688959  5581 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:50:55.688963  5581 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:50:55.688966  5581 caffe.cpp:501] detection_eval = 8.56653
-I0511 11:50:55.688971  5581 caffe.cpp:501] detection_eval = 0.0439014
-I0511 11:50:55.688973  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.688977  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.688982  5581 caffe.cpp:501] detection_eval = 7.76815
-I0511 11:50:55.688985  5581 caffe.cpp:501] detection_eval = 8.53226
-I0511 11:50:55.688988  5581 caffe.cpp:501] detection_eval = 0.044634
-I0511 11:50:55.688992  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.688997  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.688999  5581 caffe.cpp:501] detection_eval = 7.77016
-I0511 11:50:55.689003  5581 caffe.cpp:501] detection_eval = 8.5625
-I0511 11:50:55.689007  5581 caffe.cpp:501] detection_eval = 0.0422691
-I0511 11:50:55.689011  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.689015  5581 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:50:55.689018  5581 caffe.cpp:501] detection_eval = 7.77016
-I0511 11:50:55.689023  5581 caffe.cpp:501] detection_eval = 8.65323
-I0511 11:50:55.689025  5581 caffe.cpp:501] detection_eval = 0.0407678
-I0511 11:50:55.689029  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.689033  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.689036  5581 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:50:55.689040  5581 caffe.cpp:501] detection_eval = 8.65323
-I0511 11:50:55.689044  5581 caffe.cpp:501] detection_eval = 0.0451118
-I0511 11:50:55.689054  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.689059  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.689062  5581 caffe.cpp:501] detection_eval = 7.77823
-I0511 11:50:55.689066  5581 caffe.cpp:501] detection_eval = 8.65524
-I0511 11:50:55.689070  5581 caffe.cpp:501] detection_eval = 0.0421557
-I0511 11:50:55.689079  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.689085  5581 caffe.cpp:501] detection_eval = 0.927419
-I0511 11:50:55.689088  5581 caffe.cpp:501] detection_eval = 7.74395
-I0511 11:50:55.689092  5581 caffe.cpp:501] detection_eval = 8.64113
-I0511 11:50:55.689096  5581 caffe.cpp:501] detection_eval = 0.0414038
-I0511 11:50:55.689100  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.689103  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.689107  5581 caffe.cpp:501] detection_eval = 7.74395
-I0511 11:50:55.689111  5581 caffe.cpp:501] detection_eval = 8.72379
-I0511 11:50:55.689116  5581 caffe.cpp:501] detection_eval = 0.0421193
-I0511 11:50:55.689119  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.689123  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.689127  5581 caffe.cpp:501] detection_eval = 7.74597
-I0511 11:50:55.689131  5581 caffe.cpp:501] detection_eval = 8.78024
-I0511 11:50:55.689136  5581 caffe.cpp:501] detection_eval = 0.042194
-I0511 11:50:55.689139  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.689143  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.689147  5581 caffe.cpp:501] detection_eval = 7.7379
-I0511 11:50:55.689152  5581 caffe.cpp:501] detection_eval = 8.70161
-I0511 11:50:55.689155  5581 caffe.cpp:501] detection_eval = 0.0456673
-I0511 11:50:55.689159  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.689163  5581 caffe.cpp:501] detection_eval = 0.903226
-I0511 11:50:55.689167  5581 caffe.cpp:501] detection_eval = 7.74194
-I0511 11:50:55.689172  5581 caffe.cpp:501] detection_eval = 8.75202
-I0511 11:50:55.689175  5581 caffe.cpp:501] detection_eval = 0.0475273
-I0511 11:50:55.689179  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.689183  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.689188  5581 caffe.cpp:501] detection_eval = 7.75
-I0511 11:50:55.689191  5581 caffe.cpp:501] detection_eval = 8.72782
-I0511 11:50:55.690340  5581 caffe.cpp:501] detection_eval = 0.044641
-I0511 11:50:55.690354  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.690359  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.690364  5581 caffe.cpp:501] detection_eval = 7.73589
-I0511 11:50:55.690368  5581 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:50:55.690372  5581 caffe.cpp:501] detection_eval = 0.0392837
-I0511 11:50:55.690377  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690381  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.690384  5581 caffe.cpp:501] detection_eval = 7.73992
-I0511 11:50:55.690388  5581 caffe.cpp:501] detection_eval = 8.6996
-I0511 11:50:55.690393  5581 caffe.cpp:501] detection_eval = 0.0397084
-I0511 11:50:55.690397  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690402  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.690405  5581 caffe.cpp:501] detection_eval = 7.74597
-I0511 11:50:55.690409  5581 caffe.cpp:501] detection_eval = 8.69556
-I0511 11:50:55.690413  5581 caffe.cpp:501] detection_eval = 0.0382193
-I0511 11:50:55.690418  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.690421  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.690425  5581 caffe.cpp:501] detection_eval = 7.72782
-I0511 11:50:55.690429  5581 caffe.cpp:501] detection_eval = 8.81855
-I0511 11:50:55.690434  5581 caffe.cpp:501] detection_eval = 0.0478034
-I0511 11:50:55.690438  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.690443  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.690446  5581 caffe.cpp:501] detection_eval = 7.73185
-I0511 11:50:55.690450  5581 caffe.cpp:501] detection_eval = 8.85887
-I0511 11:50:55.690454  5581 caffe.cpp:501] detection_eval = 0.0492688
-I0511 11:50:55.690459  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.690462  5581 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:50:55.690466  5581 caffe.cpp:501] detection_eval = 7.73387
-I0511 11:50:55.690470  5581 caffe.cpp:501] detection_eval = 8.92742
-I0511 11:50:55.690481  5581 caffe.cpp:501] detection_eval = 0.0427398
-I0511 11:50:55.690487  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.690491  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690495  5581 caffe.cpp:501] detection_eval = 7.71573
-I0511 11:50:55.690500  5581 caffe.cpp:501] detection_eval = 8.96371
-I0511 11:50:55.690503  5581 caffe.cpp:501] detection_eval = 0.0459545
-I0511 11:50:55.690507  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.690510  5581 caffe.cpp:501] detection_eval = 0.91129
-I0511 11:50:55.690515  5581 caffe.cpp:501] detection_eval = 7.71573
-I0511 11:50:55.690518  5581 caffe.cpp:501] detection_eval = 8.99798
-I0511 11:50:55.690522  5581 caffe.cpp:501] detection_eval = 0.0397742
-I0511 11:50:55.690526  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690531  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.690536  5581 caffe.cpp:501] detection_eval = 7.71774
-I0511 11:50:55.690539  5581 caffe.cpp:501] detection_eval = 9.01815
-I0511 11:50:55.690543  5581 caffe.cpp:501] detection_eval = 0.0382935
-I0511 11:50:55.690547  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690551  5581 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:50:55.690556  5581 caffe.cpp:501] detection_eval = 7.72177
-I0511 11:50:55.690559  5581 caffe.cpp:501] detection_eval = 9.02016
-I0511 11:50:55.690563  5581 caffe.cpp:501] detection_eval = 0.0397945
-I0511 11:50:55.690567  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690572  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690575  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690579  5581 caffe.cpp:501] detection_eval = 9.09274
-I0511 11:50:55.690583  5581 caffe.cpp:501] detection_eval = 0.0408245
-I0511 11:50:55.690587  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690590  5581 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:50:55.690594  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690598  5581 caffe.cpp:501] detection_eval = 9.13508
-I0511 11:50:55.690603  5581 caffe.cpp:501] detection_eval = 0.0388966
-I0511 11:50:55.690606  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690610  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.690615  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690619  5581 caffe.cpp:501] detection_eval = 9.18347
-I0511 11:50:55.690623  5581 caffe.cpp:501] detection_eval = 0.0381993
-I0511 11:50:55.690627  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690630  5581 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:50:55.690635  5581 caffe.cpp:501] detection_eval = 7.72782
-I0511 11:50:55.690639  5581 caffe.cpp:501] detection_eval = 9.19153
-I0511 11:50:55.690642  5581 caffe.cpp:501] detection_eval = 0.0365985
-I0511 11:50:55.690647  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.690651  5581 caffe.cpp:501] detection_eval = 0.923387
-I0511 11:50:55.690655  5581 caffe.cpp:501] detection_eval = 7.72782
-I0511 11:50:55.690659  5581 caffe.cpp:501] detection_eval = 9.28226
-I0511 11:50:55.690663  5581 caffe.cpp:501] detection_eval = 0.0398854
-I0511 11:50:55.690667  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690671  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690675  5581 caffe.cpp:501] detection_eval = 7.72984
-I0511 11:50:55.690680  5581 caffe.cpp:501] detection_eval = 9.31855
-I0511 11:50:55.690683  5581 caffe.cpp:501] detection_eval = 0.0395933
-I0511 11:50:55.690687  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690691  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690696  5581 caffe.cpp:501] detection_eval = 7.73589
-I0511 11:50:55.690699  5581 caffe.cpp:501] detection_eval = 9.29637
-I0511 11:50:55.690702  5581 caffe.cpp:501] detection_eval = 0.0382833
-I0511 11:50:55.690706  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690711  5581 caffe.cpp:501] detection_eval = 0.923387
-I0511 11:50:55.690714  5581 caffe.cpp:501] detection_eval = 7.7379
-I0511 11:50:55.690727  5581 caffe.cpp:501] detection_eval = 9.34879
-I0511 11:50:55.690732  5581 caffe.cpp:501] detection_eval = 0.0420885
-I0511 11:50:55.690737  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.690742  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.690745  5581 caffe.cpp:501] detection_eval = 7.73992
-I0511 11:50:55.690749  5581 caffe.cpp:501] detection_eval = 9.4254
-I0511 11:50:55.690753  5581 caffe.cpp:501] detection_eval = 0.0426532
-I0511 11:50:55.690763  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690768  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.690773  5581 caffe.cpp:501] detection_eval = 7.74194
-I0511 11:50:55.690776  5581 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:50:55.690780  5581 caffe.cpp:501] detection_eval = 0.0398424
-I0511 11:50:55.690784  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690788  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.690793  5581 caffe.cpp:501] detection_eval = 7.74194
-I0511 11:50:55.690796  5581 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:50:55.690800  5581 caffe.cpp:501] detection_eval = 0.0413584
-I0511 11:50:55.690804  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.690809  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.690812  5581 caffe.cpp:501] detection_eval = 7.74597
-I0511 11:50:55.690816  5581 caffe.cpp:501] detection_eval = 9.5746
-I0511 11:50:55.690820  5581 caffe.cpp:501] detection_eval = 0.0429807
-I0511 11:50:55.690824  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690829  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690832  5581 caffe.cpp:501] detection_eval = 7.75605
-I0511 11:50:55.690836  5581 caffe.cpp:501] detection_eval = 9.48589
-I0511 11:50:55.690840  5581 caffe.cpp:501] detection_eval = 0.0447192
-I0511 11:50:55.690845  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690848  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690853  5581 caffe.cpp:501] detection_eval = 7.72177
-I0511 11:50:55.690857  5581 caffe.cpp:501] detection_eval = 9.44355
-I0511 11:50:55.690861  5581 caffe.cpp:501] detection_eval = 0.0487921
-I0511 11:50:55.690865  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.690870  5581 caffe.cpp:501] detection_eval = 0.90121
-I0511 11:50:55.690873  5581 caffe.cpp:501] detection_eval = 7.72177
-I0511 11:50:55.690877  5581 caffe.cpp:501] detection_eval = 9.49194
-I0511 11:50:55.690881  5581 caffe.cpp:501] detection_eval = 0.0415697
-I0511 11:50:55.690886  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690888  5581 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:50:55.690892  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690896  5581 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:50:55.690901  5581 caffe.cpp:501] detection_eval = 0.0432465
-I0511 11:50:55.690904  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690908  5581 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:50:55.690912  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690917  5581 caffe.cpp:501] detection_eval = 9.57863
-I0511 11:50:55.690920  5581 caffe.cpp:501] detection_eval = 0.0443304
-I0511 11:50:55.690924  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.690928  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.690932  5581 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:50:55.690937  5581 caffe.cpp:501] detection_eval = 9.59677
-I0511 11:50:55.690940  5581 caffe.cpp:501] detection_eval = 0.0420757
-I0511 11:50:55.690945  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690949  5581 caffe.cpp:501] detection_eval = 0.91129
-I0511 11:50:55.690953  5581 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:50:55.690958  5581 caffe.cpp:501] detection_eval = 9.6754
-I0511 11:50:55.690961  5581 caffe.cpp:501] detection_eval = 0.0387125
-I0511 11:50:55.690965  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.690969  5581 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:50:55.690973  5581 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:50:55.690984  5581 caffe.cpp:501] detection_eval = 9.77016
-I0511 11:50:55.690989  5581 caffe.cpp:501] detection_eval = 0.0390132
-I0511 11:50:55.690992  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690996  5581 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:50:55.691000  5581 caffe.cpp:501] detection_eval = 7.73387
-I0511 11:50:55.691004  5581 caffe.cpp:501] detection_eval = 9.72782
-I0511 11:50:55.691007  5581 caffe.cpp:501] detection_eval = 0.040033
-I0511 11:50:55.691012  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.691016  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.691020  5581 caffe.cpp:501] detection_eval = 7.73387
-I0511 11:50:55.691023  5581 caffe.cpp:501] detection_eval = 9.85282
-I0511 11:50:55.691027  5581 caffe.cpp:501] detection_eval = 0.0460028
-I0511 11:50:55.691031  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.691035  5581 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:50:55.691040  5581 caffe.cpp:501] detection_eval = 7.70363
-I0511 11:50:55.691043  5581 caffe.cpp:501] detection_eval = 9.79234
-I0511 11:50:55.691047  5581 caffe.cpp:501] detection_eval = 0.0412338
-I0511 11:50:55.691051  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.691056  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.691059  5581 caffe.cpp:501] detection_eval = 7.70968
-I0511 11:50:55.691063  5581 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:50:55.691067  5581 caffe.cpp:501] detection_eval = 0.0459587
-I0511 11:50:55.691071  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.691076  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.691079  5581 caffe.cpp:501] detection_eval = 7.69556
-I0511 11:50:55.691083  5581 caffe.cpp:501] detection_eval = 9.79435
-I0511 11:50:55.691087  5581 caffe.cpp:501] detection_eval = 0.0512184
-I0511 11:50:55.691092  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.691097  5581 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:50:55.691100  5581 caffe.cpp:501] detection_eval = 7.66129
-I0511 11:50:55.691104  5581 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:50:55.691108  5581 caffe.cpp:501] detection_eval = 0.0434903
-I0511 11:50:55.691112  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.691117  5581 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:50:55.691121  5581 caffe.cpp:501] detection_eval = 7.66532
-I0511 11:50:55.691125  5581 caffe.cpp:501] detection_eval = 9.77621
-I0511 11:50:55.691128  5581 caffe.cpp:501] detection_eval = 0.0410269
-I0511 11:50:55.691133  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.691136  5581 caffe.cpp:501] detection_eval = 0.891129
-I0511 11:50:55.691140  5581 caffe.cpp:501] detection_eval = 7.64919
-I0511 11:50:55.691144  5581 caffe.cpp:501] detection_eval = 9.75403
-I0511 11:50:55.691148  5581 caffe.cpp:501] detection_eval = 0.0438427
-I0511 11:50:55.691154  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.691164  5581 caffe.cpp:501] detection_eval = 0.895161
-I0511 11:50:55.691167  5581 caffe.cpp:501] detection_eval = 7.65524
-I0511 11:50:55.691171  5581 caffe.cpp:501] detection_eval = 9.7379
-I0511 11:50:55.691175  5581 caffe.cpp:501] detection_eval = 0.0444285
-I0511 11:50:55.691179  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.691184  5581 caffe.cpp:501] detection_eval = 0.90121
-I0511 11:50:55.691187  5581 caffe.cpp:501] detection_eval = 7.64315
-I0511 11:50:55.691191  5581 caffe.cpp:501] detection_eval = 9.67742
-I0511 11:50:55.691195  5581 caffe.cpp:501] detection_eval = 0.0408442
-I0511 11:50:55.691200  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.691205  5581 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:50:55.691208  5581 caffe.cpp:501] detection_eval = 7.64516
-I0511 11:50:55.691212  5581 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:50:55.691216  5581 caffe.cpp:501] detection_eval = 0.0416625
-I0511 11:50:55.691220  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.691224  5581 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:50:55.691234  5581 caffe.cpp:501] detection_eval = 7.64516
-I0511 11:50:55.691239  5581 caffe.cpp:501] detection_eval = 9.77419
-I0511 11:50:55.691243  5581 caffe.cpp:501] detection_eval = 0.0445151
-I0511 11:50:55.691247  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.691251  5581 caffe.cpp:501] detection_eval = 0.893145
-I0511 11:50:55.691256  5581 caffe.cpp:501] detection_eval = 7.64516
-I0511 11:50:55.691259  5581 caffe.cpp:501] detection_eval = 9.83065
-I0511 11:50:55.691263  5581 caffe.cpp:501] detection_eval = 0.0417487
-I0511 11:50:55.691268  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.691272  5581 caffe.cpp:501] detection_eval = 0.903226
-I0511 11:50:55.691277  5581 caffe.cpp:501] detection_eval = 7.65121
-I0511 11:50:55.691280  5581 caffe.cpp:501] detection_eval = 9.78226
-I0511 11:50:55.691284  5581 caffe.cpp:501] detection_eval = 0.040829
-I0511 11:50:55.691288  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.691293  5581 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:50:55.691296  5581 caffe.cpp:501] detection_eval = 7.65524
-I0511 11:50:55.691300  5581 caffe.cpp:501] detection_eval = 9.77419
-I0511 11:50:55.691304  5581 caffe.cpp:501] detection_eval = 0.0387782
-I0511 11:50:55.691308  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.691313  5581 caffe.cpp:501] detection_eval = 0.899194
-I0511 11:50:55.691316  5581 caffe.cpp:501] detection_eval = 7.64718
-I0511 11:50:55.691320  5581 caffe.cpp:501] detection_eval = 9.60685
-I0511 11:50:55.691324  5581 caffe.cpp:501] detection_eval = 0.0383928
-I0511 11:50:55.691329  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.691332  5581 caffe.cpp:501] detection_eval = 0.90121
-I0511 11:50:55.691336  5581 caffe.cpp:501] detection_eval = 7.64718
-I0511 11:50:55.691340  5581 caffe.cpp:501] detection_eval = 9.71169
-I0511 11:50:55.691344  5581 caffe.cpp:501] detection_eval = 0.0471161
-I0511 11:50:55.692649  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.692672  5581 caffe.cpp:501] detection_eval = 0.895161
-I0511 11:50:55.692678  5581 caffe.cpp:501] detection_eval = 7.59677
-I0511 11:50:55.692682  5581 caffe.cpp:501] detection_eval = 9.59274
-I0511 11:50:55.692687  5581 caffe.cpp:501] detection_eval = 0.0425218
-I0511 11:50:55.692690  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692694  5581 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:50:55.692698  5581 caffe.cpp:501] detection_eval = 7.60081
-I0511 11:50:55.692703  5581 caffe.cpp:501] detection_eval = 9.56452
-I0511 11:50:55.692706  5581 caffe.cpp:501] detection_eval = 0.0429596
-I0511 11:50:55.692711  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692715  5581 caffe.cpp:501] detection_eval = 0.893145
-I0511 11:50:55.692719  5581 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:50:55.692723  5581 caffe.cpp:501] detection_eval = 9.58065
-I0511 11:50:55.692728  5581 caffe.cpp:501] detection_eval = 0.0402131
-I0511 11:50:55.692731  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.692735  5581 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:50:55.692739  5581 caffe.cpp:501] detection_eval = 7.58871
-I0511 11:50:55.692744  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.692747  5581 caffe.cpp:501] detection_eval = 0.0388201
-I0511 11:50:55.692751  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692755  5581 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:50:55.692759  5581 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:50:55.692764  5581 caffe.cpp:501] detection_eval = 9.46371
-I0511 11:50:55.692767  5581 caffe.cpp:501] detection_eval = 0.0393812
-I0511 11:50:55.692771  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692775  5581 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:50:55.692780  5581 caffe.cpp:501] detection_eval = 7.56452
-I0511 11:50:55.692783  5581 caffe.cpp:501] detection_eval = 9.4375
-I0511 11:50:55.692788  5581 caffe.cpp:501] detection_eval = 0.0398975
-I0511 11:50:55.692792  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692796  5581 caffe.cpp:501] detection_eval = 0.887097
-I0511 11:50:55.692811  5581 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:50:55.692816  5581 caffe.cpp:501] detection_eval = 9.34274
-I0511 11:50:55.692821  5581 caffe.cpp:501] detection_eval = 0.0423303
-I0511 11:50:55.692826  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.692829  5581 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:50:55.692833  5581 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:50:55.692836  5581 caffe.cpp:501] detection_eval = 9.40927
-I0511 11:50:55.692840  5581 caffe.cpp:501] detection_eval = 0.0391865
-I0511 11:50:55.692844  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.692848  5581 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:50:55.692852  5581 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:50:55.692857  5581 caffe.cpp:501] detection_eval = 9.45766
-I0511 11:50:55.692860  5581 caffe.cpp:501] detection_eval = 0.0380152
-I0511 11:50:55.692864  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.692868  5581 caffe.cpp:501] detection_eval = 0.877016
-I0511 11:50:55.692873  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.692876  5581 caffe.cpp:501] detection_eval = 9.3004
-I0511 11:50:55.692880  5581 caffe.cpp:501] detection_eval = 0.0360418
-I0511 11:50:55.692884  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.692888  5581 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:50:55.692893  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.692896  5581 caffe.cpp:501] detection_eval = 9.39113
-I0511 11:50:55.692900  5581 caffe.cpp:501] detection_eval = 0.0389658
-I0511 11:50:55.692904  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692909  5581 caffe.cpp:501] detection_eval = 0.875
-I0511 11:50:55.692912  5581 caffe.cpp:501] detection_eval = 7.49194
-I0511 11:50:55.692916  5581 caffe.cpp:501] detection_eval = 9.375
-I0511 11:50:55.692920  5581 caffe.cpp:501] detection_eval = 0.0349493
-I0511 11:50:55.692924  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.692929  5581 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:50:55.692932  5581 caffe.cpp:501] detection_eval = 7.49395
-I0511 11:50:55.692936  5581 caffe.cpp:501] detection_eval = 9.40726
-I0511 11:50:55.692940  5581 caffe.cpp:501] detection_eval = 0.037342
-I0511 11:50:55.692945  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.692948  5581 caffe.cpp:501] detection_eval = 0.879032
-I0511 11:50:55.692952  5581 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:50:55.692956  5581 caffe.cpp:501] detection_eval = 9.4254
-I0511 11:50:55.692960  5581 caffe.cpp:501] detection_eval = 0.0354119
-I0511 11:50:55.692965  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.692970  5581 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:50:55.692973  5581 caffe.cpp:501] detection_eval = 7.5
-I0511 11:50:55.692977  5581 caffe.cpp:501] detection_eval = 9.4496
-I0511 11:50:55.692981  5581 caffe.cpp:501] detection_eval = 0.0395983
-I0511 11:50:55.692984  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.692988  5581 caffe.cpp:501] detection_eval = 0.875
-I0511 11:50:55.692992  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.692996  5581 caffe.cpp:501] detection_eval = 9.46169
-I0511 11:50:55.693001  5581 caffe.cpp:501] detection_eval = 0.0373619
-I0511 11:50:55.693003  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693007  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693011  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.693015  5581 caffe.cpp:501] detection_eval = 9.50806
-I0511 11:50:55.693019  5581 caffe.cpp:501] detection_eval = 0.0331615
-I0511 11:50:55.693023  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.693027  5581 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:50:55.693032  5581 caffe.cpp:501] detection_eval = 7.46774
-I0511 11:50:55.693035  5581 caffe.cpp:501] detection_eval = 9.49597
-I0511 11:50:55.693039  5581 caffe.cpp:501] detection_eval = 0.0373564
-I0511 11:50:55.693042  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693053  5581 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:50:55.693058  5581 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:50:55.693063  5581 caffe.cpp:501] detection_eval = 9.54435
-I0511 11:50:55.693066  5581 caffe.cpp:501] detection_eval = 0.0372191
-I0511 11:50:55.693070  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693079  5581 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:50:55.693084  5581 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:50:55.693087  5581 caffe.cpp:501] detection_eval = 9.55242
-I0511 11:50:55.693091  5581 caffe.cpp:501] detection_eval = 0.0365413
-I0511 11:50:55.693095  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693099  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693104  5581 caffe.cpp:501] detection_eval = 7.43952
-I0511 11:50:55.693106  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.693110  5581 caffe.cpp:501] detection_eval = 0.0387857
-I0511 11:50:55.693114  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693119  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693122  5581 caffe.cpp:501] detection_eval = 7.4254
-I0511 11:50:55.693125  5581 caffe.cpp:501] detection_eval = 9.5504
-I0511 11:50:55.693130  5581 caffe.cpp:501] detection_eval = 0.0408134
-I0511 11:50:55.693133  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693137  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693141  5581 caffe.cpp:501] detection_eval = 7.42742
-I0511 11:50:55.693145  5581 caffe.cpp:501] detection_eval = 9.55645
-I0511 11:50:55.693150  5581 caffe.cpp:501] detection_eval = 0.0359556
-I0511 11:50:55.693153  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693157  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693161  5581 caffe.cpp:501] detection_eval = 7.41129
-I0511 11:50:55.693166  5581 caffe.cpp:501] detection_eval = 9.60081
-I0511 11:50:55.693168  5581 caffe.cpp:501] detection_eval = 0.0401762
-I0511 11:50:55.693172  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693176  5581 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:50:55.693181  5581 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:50:55.693184  5581 caffe.cpp:501] detection_eval = 9.52218
-I0511 11:50:55.693188  5581 caffe.cpp:501] detection_eval = 0.036138
-I0511 11:50:55.693192  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693195  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693199  5581 caffe.cpp:501] detection_eval = 7.40121
-I0511 11:50:55.693203  5581 caffe.cpp:501] detection_eval = 9.62298
-I0511 11:50:55.693207  5581 caffe.cpp:501] detection_eval = 0.035102
-I0511 11:50:55.693212  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693215  5581 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:50:55.693219  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.693223  5581 caffe.cpp:501] detection_eval = 9.5625
-I0511 11:50:55.693226  5581 caffe.cpp:501] detection_eval = 0.0320705
-I0511 11:50:55.693230  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.693234  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693238  5581 caffe.cpp:501] detection_eval = 7.33871
-I0511 11:50:55.693243  5581 caffe.cpp:501] detection_eval = 9.41532
-I0511 11:50:55.693246  5581 caffe.cpp:501] detection_eval = 0.0364101
-I0511 11:50:55.693250  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693254  5581 caffe.cpp:501] detection_eval = 0.860887
-I0511 11:50:55.693259  5581 caffe.cpp:501] detection_eval = 7.33871
-I0511 11:50:55.693261  5581 caffe.cpp:501] detection_eval = 9.4496
-I0511 11:50:55.693265  5581 caffe.cpp:501] detection_eval = 0.0353211
-I0511 11:50:55.693270  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693274  5581 caffe.cpp:501] detection_eval = 0.858871
-I0511 11:50:55.693277  5581 caffe.cpp:501] detection_eval = 7.34274
-I0511 11:50:55.693281  5581 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:50:55.693285  5581 caffe.cpp:501] detection_eval = 0.0360995
-I0511 11:50:55.693296  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693301  5581 caffe.cpp:501] detection_eval = 0.856855
-I0511 11:50:55.693305  5581 caffe.cpp:501] detection_eval = 7.33065
-I0511 11:50:55.693310  5581 caffe.cpp:501] detection_eval = 9.35685
-I0511 11:50:55.693313  5581 caffe.cpp:501] detection_eval = 0.0390568
-I0511 11:50:55.693317  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693321  5581 caffe.cpp:501] detection_eval = 0.858871
-I0511 11:50:55.693325  5581 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:50:55.693328  5581 caffe.cpp:501] detection_eval = 9.38911
-I0511 11:50:55.693332  5581 caffe.cpp:501] detection_eval = 0.0385728
-I0511 11:50:55.693336  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693341  5581 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:50:55.693344  5581 caffe.cpp:501] detection_eval = 7.27621
-I0511 11:50:55.693348  5581 caffe.cpp:501] detection_eval = 9.38105
-I0511 11:50:55.693352  5581 caffe.cpp:501] detection_eval = 0.0362222
-I0511 11:50:55.693356  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693359  5581 caffe.cpp:501] detection_eval = 0.84879
-I0511 11:50:55.693363  5581 caffe.cpp:501] detection_eval = 7.27823
-I0511 11:50:55.693367  5581 caffe.cpp:501] detection_eval = 9.45766
-I0511 11:50:55.693372  5581 caffe.cpp:501] detection_eval = 0.0385586
-I0511 11:50:55.693375  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693379  5581 caffe.cpp:501] detection_eval = 0.84879
-I0511 11:50:55.693383  5581 caffe.cpp:501] detection_eval = 7.28024
-I0511 11:50:55.693387  5581 caffe.cpp:501] detection_eval = 9.4879
-I0511 11:50:55.693392  5581 caffe.cpp:501] detection_eval = 0.0389247
-I0511 11:50:55.693395  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.693399  5581 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:50:55.693403  5581 caffe.cpp:501] detection_eval = 7.28427
-I0511 11:50:55.693408  5581 caffe.cpp:501] detection_eval = 9.52016
-I0511 11:50:55.693411  5581 caffe.cpp:501] detection_eval = 0.0399768
-I0511 11:50:55.693415  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693419  5581 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:50:55.693423  5581 caffe.cpp:501] detection_eval = 7.29032
-I0511 11:50:55.693428  5581 caffe.cpp:501] detection_eval = 9.50403
-I0511 11:50:55.693430  5581 caffe.cpp:501] detection_eval = 0.0372568
-I0511 11:50:55.693434  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693437  5581 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:50:55.693441  5581 caffe.cpp:501] detection_eval = 7.29032
-I0511 11:50:55.693445  5581 caffe.cpp:501] detection_eval = 9.58266
-I0511 11:50:55.693449  5581 caffe.cpp:501] detection_eval = 0.0362175
-I0511 11:50:55.693454  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693457  5581 caffe.cpp:501] detection_eval = 0.84879
-I0511 11:50:55.693461  5581 caffe.cpp:501] detection_eval = 7.29032
-I0511 11:50:55.693464  5581 caffe.cpp:501] detection_eval = 9.65726
-I0511 11:50:55.693469  5581 caffe.cpp:501] detection_eval = 0.0396827
-I0511 11:50:55.693472  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693482  5581 caffe.cpp:501] detection_eval = 0.844758
-I0511 11:50:55.693486  5581 caffe.cpp:501] detection_eval = 7.29234
-I0511 11:50:55.693490  5581 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:50:55.693495  5581 caffe.cpp:501] detection_eval = 0.0361591
-I0511 11:50:55.693498  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693502  5581 caffe.cpp:501] detection_eval = 0.850806
-I0511 11:50:55.693506  5581 caffe.cpp:501] detection_eval = 7.29234
-I0511 11:50:55.693511  5581 caffe.cpp:501] detection_eval = 9.75403
-I0511 11:50:55.693514  5581 caffe.cpp:501] detection_eval = 0.0331379
-I0511 11:50:55.693518  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.693522  5581 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:50:55.693526  5581 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:50:55.693531  5581 caffe.cpp:501] detection_eval = 9.77621
-I0511 11:50:55.693534  5581 caffe.cpp:501] detection_eval = 0.033433
-I0511 11:50:55.693547  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693552  5581 caffe.cpp:501] detection_eval = 0.850806
-I0511 11:50:55.693555  5581 caffe.cpp:501] detection_eval = 7.27621
-I0511 11:50:55.693559  5581 caffe.cpp:501] detection_eval = 9.79234
-I0511 11:50:55.693563  5581 caffe.cpp:501] detection_eval = 0.037148
-I0511 11:50:55.693567  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693572  5581 caffe.cpp:501] detection_eval = 0.84879
-I0511 11:50:55.693575  5581 caffe.cpp:501] detection_eval = 7.2621
-I0511 11:50:55.693579  5581 caffe.cpp:501] detection_eval = 9.74798
-I0511 11:50:55.693583  5581 caffe.cpp:501] detection_eval = 0.0373937
-I0511 11:50:55.693588  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693591  5581 caffe.cpp:501] detection_eval = 0.840726
-I0511 11:50:55.693595  5581 caffe.cpp:501] detection_eval = 7.2621
-I0511 11:50:55.693599  5581 caffe.cpp:501] detection_eval = 9.82056
-I0511 11:50:55.693603  5581 caffe.cpp:501] detection_eval = 0.0338502
-I0511 11:50:55.693608  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693612  5581 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:50:55.693616  5581 caffe.cpp:501] detection_eval = 7.27218
-I0511 11:50:55.693619  5581 caffe.cpp:501] detection_eval = 9.70766
-I0511 11:50:55.693624  5581 caffe.cpp:501] detection_eval = 0.0336465
-I0511 11:50:55.693627  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693631  5581 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:50:55.693635  5581 caffe.cpp:501] detection_eval = 7.27419
-I0511 11:50:55.693639  5581 caffe.cpp:501] detection_eval = 9.73387
-I0511 11:50:55.693644  5581 caffe.cpp:501] detection_eval = 0.032233
-I0511 11:50:55.693647  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.693652  5581 caffe.cpp:501] detection_eval = 0.850806
-I0511 11:50:55.693656  5581 caffe.cpp:501] detection_eval = 7.25605
-I0511 11:50:55.693660  5581 caffe.cpp:501] detection_eval = 9.79839
-I0511 11:50:55.693665  5581 caffe.cpp:501] detection_eval = 0.0418286
-I0511 11:50:55.693668  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.693672  5581 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:50:55.693676  5581 caffe.cpp:501] detection_eval = 7.25806
-I0511 11:50:55.693681  5581 caffe.cpp:501] detection_eval = 9.84476
-I0511 11:50:55.693684  5581 caffe.cpp:501] detection_eval = 0.0355745
-I0511 11:50:55.693688  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693692  5581 caffe.cpp:501] detection_eval = 0.842742
-I0511 11:50:55.693696  5581 caffe.cpp:501] detection_eval = 7.26008
-I0511 11:50:55.693701  5581 caffe.cpp:501] detection_eval = 9.86895
-I0511 11:50:55.693704  5581 caffe.cpp:501] detection_eval = 0.0401162
-I0511 11:50:55.693708  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.693712  5581 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:50:55.693716  5581 caffe.cpp:501] detection_eval = 7.20565
-I0511 11:50:55.693719  5581 caffe.cpp:501] detection_eval = 9.81452
-I0511 11:50:55.693723  5581 caffe.cpp:501] detection_eval = 0.0381054
-I0511 11:50:55.693727  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693732  5581 caffe.cpp:501] detection_eval = 0.836694
-I0511 11:50:55.693735  5581 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:50:55.693739  5581 caffe.cpp:501] detection_eval = 9.78024
-I0511 11:50:55.693742  5581 caffe.cpp:501] detection_eval = 0.0359296
-I0511 11:50:55.693747  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693750  5581 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:50:55.693754  5581 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:50:55.693758  5581 caffe.cpp:501] detection_eval = 9.85081
-I0511 11:50:55.693761  5581 caffe.cpp:501] detection_eval = 0.0400798
-I0511 11:50:55.693765  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693769  5581 caffe.cpp:501] detection_eval = 0.832661
-I0511 11:50:55.693773  5581 caffe.cpp:501] detection_eval = 7.21169
-I0511 11:50:55.693778  5581 caffe.cpp:501] detection_eval = 9.84073
-I0511 11:50:55.693786  5581 caffe.cpp:501] detection_eval = 0.0361626
-I0511 11:50:55.693791  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693795  5581 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:50:55.693799  5581 caffe.cpp:501] detection_eval = 7.21573
-I0511 11:50:55.693804  5581 caffe.cpp:501] detection_eval = 9.8629
-I0511 11:50:55.693807  5581 caffe.cpp:501] detection_eval = 0.0403234
-I0511 11:50:55.693810  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693814  5581 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:50:55.693819  5581 caffe.cpp:501] detection_eval = 7.1996
-I0511 11:50:55.693822  5581 caffe.cpp:501] detection_eval = 9.84476
-I0511 11:50:55.693826  5581 caffe.cpp:501] detection_eval = 0.0365513
-I0511 11:50:55.693830  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.693835  5581 caffe.cpp:501] detection_eval = 0.826613
-I0511 11:50:55.693838  5581 caffe.cpp:501] detection_eval = 7.18145
-I0511 11:50:55.693842  5581 caffe.cpp:501] detection_eval = 9.88306
-I0511 11:50:55.693845  5581 caffe.cpp:501] detection_eval = 0.0335514
-I0511 11:50:55.693850  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693853  5581 caffe.cpp:501] detection_eval = 0.830645
-I0511 11:50:55.693856  5581 caffe.cpp:501] detection_eval = 7.18347
-I0511 11:50:55.693861  5581 caffe.cpp:501] detection_eval = 9.91129
-I0511 11:50:55.693864  5581 caffe.cpp:501] detection_eval = 0.036504
-I0511 11:50:55.693873  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693877  5581 caffe.cpp:501] detection_eval = 0.828629
-I0511 11:50:55.693881  5581 caffe.cpp:501] detection_eval = 7.18347
-I0511 11:50:55.693884  5581 caffe.cpp:501] detection_eval = 9.98589
-I0511 11:50:55.693888  5581 caffe.cpp:501] detection_eval = 0.040345
-I0511 11:50:55.693892  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.693897  5581 caffe.cpp:501] detection_eval = 0.828629
-I0511 11:50:55.693902  5581 caffe.cpp:501] detection_eval = 7.14919
-I0511 11:50:55.693904  5581 caffe.cpp:501] detection_eval = 9.94153
-I0511 11:50:55.693908  5581 caffe.cpp:501] detection_eval = 0.0330725
-I0511 11:50:55.693912  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693917  5581 caffe.cpp:501] detection_eval = 0.830645
-I0511 11:50:55.693922  5581 caffe.cpp:501] detection_eval = 7.13508
-I0511 11:50:55.693925  5581 caffe.cpp:501] detection_eval = 9.88306
-I0511 11:50:55.693929  5581 caffe.cpp:501] detection_eval = 0.0348621
-I0511 11:50:55.693933  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693938  5581 caffe.cpp:501] detection_eval = 0.822581
-I0511 11:50:55.693941  5581 caffe.cpp:501] detection_eval = 7.11694
-I0511 11:50:55.693945  5581 caffe.cpp:501] detection_eval = 9.88911
-I0511 11:50:55.693949  5581 caffe.cpp:501] detection_eval = 0.0353318
-I0511 11:50:55.693953  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.693956  5581 caffe.cpp:501] detection_eval = 0.820565
-I0511 11:50:55.693960  5581 caffe.cpp:501] detection_eval = 7.10081
-I0511 11:50:55.693964  5581 caffe.cpp:501] detection_eval = 9.90927
-I0511 11:50:55.693967  5581 caffe.cpp:501] detection_eval = 0.0390245
-I0511 11:50:55.693971  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.693975  5581 caffe.cpp:501] detection_eval = 0.814516
-I0511 11:50:55.693979  5581 caffe.cpp:501] detection_eval = 7.08468
-I0511 11:50:55.693982  5581 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:50:55.693986  5581 caffe.cpp:501] detection_eval = 0.0376094
-I0511 11:50:55.693990  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693994  5581 caffe.cpp:501] detection_eval = 0.818548
-I0511 11:50:55.693997  5581 caffe.cpp:501] detection_eval = 7.08871
-I0511 11:50:55.694001  5581 caffe.cpp:501] detection_eval = 9.87097
-I0511 11:50:55.694005  5581 caffe.cpp:501] detection_eval = 0.03494
-I0511 11:50:55.694010  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.694013  5581 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:50:55.694017  5581 caffe.cpp:501] detection_eval = 7.07258
-I0511 11:50:55.694021  5581 caffe.cpp:501] detection_eval = 9.85282
-I0511 11:50:55.694031  5581 caffe.cpp:501] detection_eval = 0.032036
-I0511 11:50:55.694036  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694041  5581 caffe.cpp:501] detection_eval = 0.820565
-I0511 11:50:55.694044  5581 caffe.cpp:501] detection_eval = 7.07258
-I0511 11:50:55.694048  5581 caffe.cpp:501] detection_eval = 9.91532
-I0511 11:50:55.694053  5581 caffe.cpp:501] detection_eval = 0.0344601
-I0511 11:50:55.694057  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.694061  5581 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:50:55.694066  5581 caffe.cpp:501] detection_eval = 7.07258
-I0511 11:50:55.694070  5581 caffe.cpp:501] detection_eval = 9.99194
-I0511 11:50:55.694074  5581 caffe.cpp:501] detection_eval = 0.0352947
-I0511 11:50:55.694078  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.694082  5581 caffe.cpp:501] detection_eval = 0.810484
-I0511 11:50:55.694087  5581 caffe.cpp:501] detection_eval = 7.04234
-I0511 11:50:55.694090  5581 caffe.cpp:501] detection_eval = 9.87702
-I0511 11:50:55.694094  5581 caffe.cpp:501] detection_eval = 0.0319296
-I0511 11:50:55.694098  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694103  5581 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:50:55.694106  5581 caffe.cpp:501] detection_eval = 7.04435
-I0511 11:50:55.694110  5581 caffe.cpp:501] detection_eval = 9.92944
-I0511 11:50:55.694115  5581 caffe.cpp:501] detection_eval = 0.0294298
-I0511 11:50:55.694118  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.694123  5581 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:50:55.694128  5581 caffe.cpp:501] detection_eval = 7.03024
-I0511 11:50:55.694131  5581 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:50:55.694747  5581 caffe.cpp:501] detection_eval = 0.032493
-I0511 11:50:55.694761  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.694766  5581 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:50:55.694772  5581 caffe.cpp:501] detection_eval = 7.03226
-I0511 11:50:55.694775  5581 caffe.cpp:501] detection_eval = 9.90121
-I0511 11:50:55.694779  5581 caffe.cpp:501] detection_eval = 0.0373495
-I0511 11:50:55.694783  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.694787  5581 caffe.cpp:501] detection_eval = 0.806452
-I0511 11:50:55.694792  5581 caffe.cpp:501] detection_eval = 7.03427
-I0511 11:50:55.694797  5581 caffe.cpp:501] detection_eval = 9.91532
-I0511 11:50:55.694800  5581 caffe.cpp:501] detection_eval = 0.0287897
-I0511 11:50:55.694804  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.694808  5581 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:50:55.694813  5581 caffe.cpp:501] detection_eval = 7.01613
-I0511 11:50:55.694816  5581 caffe.cpp:501] detection_eval = 9.95968
-I0511 11:50:55.694820  5581 caffe.cpp:501] detection_eval = 0.0300179
-I0511 11:50:55.694825  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.694829  5581 caffe.cpp:501] detection_eval = 0.814516
-I0511 11:50:55.694833  5581 caffe.cpp:501] detection_eval = 7
-I0511 11:50:55.694836  5581 caffe.cpp:501] detection_eval = 9.99194
-I0511 11:50:55.694840  5581 caffe.cpp:501] detection_eval = 0.0333731
-I0511 11:50:55.694844  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694847  5581 caffe.cpp:501] detection_eval = 0.808468
-I0511 11:50:55.694850  5581 caffe.cpp:501] detection_eval = 6.98589
-I0511 11:50:55.694854  5581 caffe.cpp:501] detection_eval = 9.97379
-I0511 11:50:55.694857  5581 caffe.cpp:501] detection_eval = 0.0307876
-I0511 11:50:55.694861  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.694865  5581 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:50:55.694869  5581 caffe.cpp:501] detection_eval = 6.96976
-I0511 11:50:55.694874  5581 caffe.cpp:501] detection_eval = 9.95161
-I0511 11:50:55.694877  5581 caffe.cpp:501] detection_eval = 0.0308016
-I0511 11:50:55.694881  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.694885  5581 caffe.cpp:501] detection_eval = 0.810484
-I0511 11:50:55.694888  5581 caffe.cpp:501] detection_eval = 6.9375
-I0511 11:50:55.694900  5581 caffe.cpp:501] detection_eval = 9.86694
-I0511 11:50:55.694905  5581 caffe.cpp:501] detection_eval = 0.0327063
-I0511 11:50:55.694908  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694912  5581 caffe.cpp:501] detection_eval = 0.802419
-I0511 11:50:55.694916  5581 caffe.cpp:501] detection_eval = 6.93952
-I0511 11:50:55.694919  5581 caffe.cpp:501] detection_eval = 9.92339
-I0511 11:50:55.694923  5581 caffe.cpp:501] detection_eval = 0.0311476
-I0511 11:50:55.694926  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.694931  5581 caffe.cpp:501] detection_eval = 0.806452
-I0511 11:50:55.694933  5581 caffe.cpp:501] detection_eval = 6.92944
-I0511 11:50:55.694937  5581 caffe.cpp:501] detection_eval = 9.83468
-I0511 11:50:55.694941  5581 caffe.cpp:501] detection_eval = 0.0329777
-I0511 11:50:55.694945  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694949  5581 caffe.cpp:501] detection_eval = 0.802419
-I0511 11:50:55.694953  5581 caffe.cpp:501] detection_eval = 6.93145
-I0511 11:50:55.694957  5581 caffe.cpp:501] detection_eval = 9.86895
-I0511 11:50:55.694960  5581 caffe.cpp:501] detection_eval = 0.0373738
-I0511 11:50:55.694964  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.694968  5581 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:50:55.694972  5581 caffe.cpp:501] detection_eval = 6.93548
-I0511 11:50:55.694977  5581 caffe.cpp:501] detection_eval = 9.87097
-I0511 11:50:55.694980  5581 caffe.cpp:501] detection_eval = 0.0336773
-I0511 11:50:55.694984  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.694988  5581 caffe.cpp:501] detection_eval = 0.796371
-I0511 11:50:55.694993  5581 caffe.cpp:501] detection_eval = 6.88508
-I0511 11:50:55.694996  5581 caffe.cpp:501] detection_eval = 9.73992
-I0511 11:50:55.695000  5581 caffe.cpp:501] detection_eval = 0.0320276
-I0511 11:50:55.695004  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.695008  5581 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:50:55.695013  5581 caffe.cpp:501] detection_eval = 6.87097
-I0511 11:50:55.695016  5581 caffe.cpp:501] detection_eval = 9.70766
-I0511 11:50:55.695020  5581 caffe.cpp:501] detection_eval = 0.0358409
-I0511 11:50:55.695024  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695029  5581 caffe.cpp:501] detection_eval = 0.788306
-I0511 11:50:55.695032  5581 caffe.cpp:501] detection_eval = 6.85484
-I0511 11:50:55.695036  5581 caffe.cpp:501] detection_eval = 9.71169
-I0511 11:50:55.695040  5581 caffe.cpp:501] detection_eval = 0.0296722
-I0511 11:50:55.695044  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.695049  5581 caffe.cpp:501] detection_eval = 0.794355
-I0511 11:50:55.695052  5581 caffe.cpp:501] detection_eval = 6.85685
-I0511 11:50:55.695056  5581 caffe.cpp:501] detection_eval = 9.73387
-I0511 11:50:55.695060  5581 caffe.cpp:501] detection_eval = 0.0357246
-I0511 11:50:55.695065  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.695070  5581 caffe.cpp:501] detection_eval = 0.78629
-I0511 11:50:55.695073  5581 caffe.cpp:501] detection_eval = 6.85685
-I0511 11:50:55.695077  5581 caffe.cpp:501] detection_eval = 9.8125
-I0511 11:50:55.695081  5581 caffe.cpp:501] detection_eval = 0.0306283
-I0511 11:50:55.695086  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695089  5581 caffe.cpp:501] detection_eval = 0.790323
-I0511 11:50:55.695093  5581 caffe.cpp:501] detection_eval = 6.85685
-I0511 11:50:55.695097  5581 caffe.cpp:501] detection_eval = 9.88306
-I0511 11:50:55.695101  5581 caffe.cpp:501] detection_eval = 0.0358557
-I0511 11:50:55.695106  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.695109  5581 caffe.cpp:501] detection_eval = 0.782258
-I0511 11:50:55.695113  5581 caffe.cpp:501] detection_eval = 6.82258
-I0511 11:50:55.695117  5581 caffe.cpp:501] detection_eval = 9.80847
-I0511 11:50:55.695122  5581 caffe.cpp:501] detection_eval = 0.0287403
-I0511 11:50:55.695125  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695129  5581 caffe.cpp:501] detection_eval = 0.790323
-I0511 11:50:55.695139  5581 caffe.cpp:501] detection_eval = 6.82661
-I0511 11:50:55.695144  5581 caffe.cpp:501] detection_eval = 9.84073
-I0511 11:50:55.695149  5581 caffe.cpp:501] detection_eval = 0.0328806
-I0511 11:50:55.695153  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695158  5581 caffe.cpp:501] detection_eval = 0.78629
-I0511 11:50:55.695166  5581 caffe.cpp:501] detection_eval = 6.81653
-I0511 11:50:55.695171  5581 caffe.cpp:501] detection_eval = 9.77621
-I0511 11:50:55.695176  5581 caffe.cpp:501] detection_eval = 0.0351629
-I0511 11:50:55.695180  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695184  5581 caffe.cpp:501] detection_eval = 0.780242
-I0511 11:50:55.695188  5581 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:50:55.695192  5581 caffe.cpp:501] detection_eval = 9.81653
-I0511 11:50:55.695196  5581 caffe.cpp:501] detection_eval = 0.0323754
-I0511 11:50:55.695200  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695204  5581 caffe.cpp:501] detection_eval = 0.782258
-I0511 11:50:55.695209  5581 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:50:55.695214  5581 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:50:55.695217  5581 caffe.cpp:501] detection_eval = 0.0343071
-I0511 11:50:55.695221  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.695225  5581 caffe.cpp:501] detection_eval = 0.77621
-I0511 11:50:55.695230  5581 caffe.cpp:501] detection_eval = 6.75
-I0511 11:50:55.695235  5581 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:50:55.695238  5581 caffe.cpp:501] detection_eval = 0.0384378
-I0511 11:50:55.695242  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.695245  5581 caffe.cpp:501] detection_eval = 0.768145
-I0511 11:50:55.695250  5581 caffe.cpp:501] detection_eval = 6.7379
-I0511 11:50:55.695255  5581 caffe.cpp:501] detection_eval = 9.67339
-I0511 11:50:55.695258  5581 caffe.cpp:501] detection_eval = 0.0361436
-I0511 11:50:55.695262  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695266  5581 caffe.cpp:501] detection_eval = 0.770161
-I0511 11:50:55.695271  5581 caffe.cpp:501] detection_eval = 6.73992
-I0511 11:50:55.695276  5581 caffe.cpp:501] detection_eval = 9.71573
-I0511 11:50:55.695279  5581 caffe.cpp:501] detection_eval = 0.0330777
-I0511 11:50:55.695283  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695287  5581 caffe.cpp:501] detection_eval = 0.768145
-I0511 11:50:55.695291  5581 caffe.cpp:501] detection_eval = 6.70363
-I0511 11:50:55.695296  5581 caffe.cpp:501] detection_eval = 9.71371
-I0511 11:50:55.695298  5581 caffe.cpp:501] detection_eval = 0.0299119
-I0511 11:50:55.695302  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695307  5581 caffe.cpp:501] detection_eval = 0.770161
-I0511 11:50:55.695310  5581 caffe.cpp:501] detection_eval = 6.70565
-I0511 11:50:55.695314  5581 caffe.cpp:501] detection_eval = 9.73992
-I0511 11:50:55.695317  5581 caffe.cpp:501] detection_eval = 0.0322463
-I0511 11:50:55.695322  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.695325  5581 caffe.cpp:501] detection_eval = 0.762097
-I0511 11:50:55.695329  5581 caffe.cpp:501] detection_eval = 6.67339
-I0511 11:50:55.695333  5581 caffe.cpp:501] detection_eval = 9.64516
-I0511 11:50:55.695336  5581 caffe.cpp:501] detection_eval = 0.0345244
-I0511 11:50:55.695340  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.695344  5581 caffe.cpp:501] detection_eval = 0.764113
-I0511 11:50:55.695348  5581 caffe.cpp:501] detection_eval = 6.67742
-I0511 11:50:55.695353  5581 caffe.cpp:501] detection_eval = 9.64919
-I0511 11:50:55.695355  5581 caffe.cpp:501] detection_eval = 0.0360615
-I0511 11:50:55.695359  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.695363  5581 caffe.cpp:501] detection_eval = 0.752016
-I0511 11:50:55.695367  5581 caffe.cpp:501] detection_eval = 6.66129
-I0511 11:50:55.695371  5581 caffe.cpp:501] detection_eval = 9.60282
-I0511 11:50:55.695374  5581 caffe.cpp:501] detection_eval = 0.0283827
-I0511 11:50:55.695379  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695382  5581 caffe.cpp:501] detection_eval = 0.764113
-I0511 11:50:55.695392  5581 caffe.cpp:501] detection_eval = 6.64718
-I0511 11:50:55.695396  5581 caffe.cpp:501] detection_eval = 9.58266
-I0511 11:50:55.695400  5581 caffe.cpp:501] detection_eval = 0.0298543
-I0511 11:50:55.695405  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695407  5581 caffe.cpp:501] detection_eval = 0.764113
-I0511 11:50:55.695411  5581 caffe.cpp:501] detection_eval = 6.62903
-I0511 11:50:55.695415  5581 caffe.cpp:501] detection_eval = 9.65323
-I0511 11:50:55.695420  5581 caffe.cpp:501] detection_eval = 0.0314333
-I0511 11:50:55.695423  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.695426  5581 caffe.cpp:501] detection_eval = 0.758065
-I0511 11:50:55.695430  5581 caffe.cpp:501] detection_eval = 6.61492
-I0511 11:50:55.695435  5581 caffe.cpp:501] detection_eval = 9.63306
-I0511 11:50:55.695438  5581 caffe.cpp:501] detection_eval = 0.0416447
-I0511 11:50:55.695442  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.695446  5581 caffe.cpp:501] detection_eval = 0.745968
-I0511 11:50:55.695451  5581 caffe.cpp:501] detection_eval = 6.61492
-I0511 11:50:55.695453  5581 caffe.cpp:501] detection_eval = 9.6754
-I0511 11:50:55.695457  5581 caffe.cpp:501] detection_eval = 0.0339225
-I0511 11:50:55.695461  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695466  5581 caffe.cpp:501] detection_eval = 0.760081
-I0511 11:50:55.695469  5581 caffe.cpp:501] detection_eval = 6.59677
-I0511 11:50:55.695472  5581 caffe.cpp:501] detection_eval = 9.6875
-I0511 11:50:55.695477  5581 caffe.cpp:501] detection_eval = 0.0324571
-I0511 11:50:55.695480  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.695484  5581 caffe.cpp:501] detection_eval = 0.75
-I0511 11:50:55.695488  5581 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:50:55.695492  5581 caffe.cpp:501] detection_eval = 9.65121
-I0511 11:50:55.695497  5581 caffe.cpp:501] detection_eval = 0.0349557
-I0511 11:50:55.695500  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695503  5581 caffe.cpp:501] detection_eval = 0.745968
-I0511 11:50:55.695508  5581 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:50:55.695511  5581 caffe.cpp:501] detection_eval = 9.69556
-I0511 11:50:55.695515  5581 caffe.cpp:501] detection_eval = 0.0303059
-I0511 11:50:55.695519  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.695523  5581 caffe.cpp:501] detection_eval = 0.747984
-I0511 11:50:55.695526  5581 caffe.cpp:501] detection_eval = 6.53226
-I0511 11:50:55.695530  5581 caffe.cpp:501] detection_eval = 9.60484
-I0511 11:50:55.695534  5581 caffe.cpp:501] detection_eval = 0.0280135
-I0511 11:50:55.695538  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695542  5581 caffe.cpp:501] detection_eval = 0.75
-I0511 11:50:55.695545  5581 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:50:55.695549  5581 caffe.cpp:501] detection_eval = 9.56048
-I0511 11:50:55.695554  5581 caffe.cpp:501] detection_eval = 0.02689
-I0511 11:50:55.695556  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.695560  5581 caffe.cpp:501] detection_eval = 0.752016
-I0511 11:50:55.695564  5581 caffe.cpp:501] detection_eval = 6.50202
-I0511 11:50:55.695567  5581 caffe.cpp:501] detection_eval = 9.54234
-I0511 11:50:55.695571  5581 caffe.cpp:501] detection_eval = 0.0274713
-I0511 11:50:55.695580  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695583  5581 caffe.cpp:501] detection_eval = 0.747984
-I0511 11:50:55.695587  5581 caffe.cpp:501] detection_eval = 6.48387
-I0511 11:50:55.695591  5581 caffe.cpp:501] detection_eval = 9.56048
-I0511 11:50:55.695595  5581 caffe.cpp:501] detection_eval = 0.0282462
-I0511 11:50:55.695598  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695602  5581 caffe.cpp:501] detection_eval = 0.739919
-I0511 11:50:55.695606  5581 caffe.cpp:501] detection_eval = 6.44758
-I0511 11:50:55.695611  5581 caffe.cpp:501] detection_eval = 9.5504
-I0511 11:50:55.695614  5581 caffe.cpp:501] detection_eval = 0.0280578
-I0511 11:50:55.695617  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.695626  5581 caffe.cpp:501] detection_eval = 0.739919
-I0511 11:50:55.695631  5581 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:50:55.695634  5581 caffe.cpp:501] detection_eval = 9.59677
-I0511 11:50:55.695637  5581 caffe.cpp:501] detection_eval = 0.0256961
-I0511 11:50:55.695641  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.695646  5581 caffe.cpp:501] detection_eval = 0.743952
-I0511 11:50:55.695649  5581 caffe.cpp:501] detection_eval = 6.43548
-I0511 11:50:55.695653  5581 caffe.cpp:501] detection_eval = 9.53427
-I0511 11:50:55.695657  5581 caffe.cpp:501] detection_eval = 0.0273331
-I0511 11:50:55.695660  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695664  5581 caffe.cpp:501] detection_eval = 0.735887
-I0511 11:50:55.695668  5581 caffe.cpp:501] detection_eval = 6.42339
-I0511 11:50:55.695672  5581 caffe.cpp:501] detection_eval = 9.42742
-I0511 11:50:55.695675  5581 caffe.cpp:501] detection_eval = 0.0274096
-I0511 11:50:55.695679  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695683  5581 caffe.cpp:501] detection_eval = 0.735887
-I0511 11:50:55.695686  5581 caffe.cpp:501] detection_eval = 6.40726
-I0511 11:50:55.695690  5581 caffe.cpp:501] detection_eval = 9.45161
-I0511 11:50:55.695694  5581 caffe.cpp:501] detection_eval = 0.03626
-I0511 11:50:55.695698  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.695703  5581 caffe.cpp:501] detection_eval = 0.721774
-I0511 11:50:55.695706  5581 caffe.cpp:501] detection_eval = 6.40927
-I0511 11:50:55.695710  5581 caffe.cpp:501] detection_eval = 9.47984
-I0511 11:50:55.695714  5581 caffe.cpp:501] detection_eval = 0.0327975
-I0511 11:50:55.703299  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703320  5581 caffe.cpp:501] detection_eval = 0.727823
-I0511 11:50:55.703325  5581 caffe.cpp:501] detection_eval = 6.37298
-I0511 11:50:55.703328  5581 caffe.cpp:501] detection_eval = 9.47782
-I0511 11:50:55.703332  5581 caffe.cpp:501] detection_eval = 0.0288063
-I0511 11:50:55.703336  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703341  5581 caffe.cpp:501] detection_eval = 0.729839
-I0511 11:50:55.703343  5581 caffe.cpp:501] detection_eval = 6.33871
-I0511 11:50:55.703347  5581 caffe.cpp:501] detection_eval = 9.46371
-I0511 11:50:55.703351  5581 caffe.cpp:501] detection_eval = 0.0283002
-I0511 11:50:55.703356  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703358  5581 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:50:55.703362  5581 caffe.cpp:501] detection_eval = 6.30645
-I0511 11:50:55.703366  5581 caffe.cpp:501] detection_eval = 9.40524
-I0511 11:50:55.703371  5581 caffe.cpp:501] detection_eval = 0.0271487
-I0511 11:50:55.703374  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.703377  5581 caffe.cpp:501] detection_eval = 0.725806
-I0511 11:50:55.703382  5581 caffe.cpp:501] detection_eval = 6.28831
-I0511 11:50:55.703385  5581 caffe.cpp:501] detection_eval = 9.45363
-I0511 11:50:55.703389  5581 caffe.cpp:501] detection_eval = 0.0316955
-I0511 11:50:55.703392  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703397  5581 caffe.cpp:501] detection_eval = 0.715726
-I0511 11:50:55.703400  5581 caffe.cpp:501] detection_eval = 6.29032
-I0511 11:50:55.703404  5581 caffe.cpp:501] detection_eval = 9.50202
-I0511 11:50:55.703408  5581 caffe.cpp:501] detection_eval = 0.0298387
-I0511 11:50:55.703411  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703415  5581 caffe.cpp:501] detection_eval = 0.719758
-I0511 11:50:55.703418  5581 caffe.cpp:501] detection_eval = 6.27218
-I0511 11:50:55.703423  5581 caffe.cpp:501] detection_eval = 9.5625
-I0511 11:50:55.703426  5581 caffe.cpp:501] detection_eval = 0.0321499
-I0511 11:50:55.703430  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703433  5581 caffe.cpp:501] detection_eval = 0.711694
-I0511 11:50:55.703438  5581 caffe.cpp:501] detection_eval = 6.25605
-I0511 11:50:55.703441  5581 caffe.cpp:501] detection_eval = 9.59677
-I0511 11:50:55.703444  5581 caffe.cpp:501] detection_eval = 0.0277891
-I0511 11:50:55.703447  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.703461  5581 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:50:55.703465  5581 caffe.cpp:501] detection_eval = 6.21976
-I0511 11:50:55.703469  5581 caffe.cpp:501] detection_eval = 9.60887
-I0511 11:50:55.703472  5581 caffe.cpp:501] detection_eval = 0.0291475
-I0511 11:50:55.703475  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703480  5581 caffe.cpp:501] detection_eval = 0.709677
-I0511 11:50:55.703482  5581 caffe.cpp:501] detection_eval = 6.20363
-I0511 11:50:55.703486  5581 caffe.cpp:501] detection_eval = 9.71371
-I0511 11:50:55.703490  5581 caffe.cpp:501] detection_eval = 0.0273094
-I0511 11:50:55.703492  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703496  5581 caffe.cpp:501] detection_eval = 0.703629
-I0511 11:50:55.703500  5581 caffe.cpp:501] detection_eval = 6.44153
-I0511 11:50:55.703503  5581 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:50:55.703506  5581 caffe.cpp:501] detection_eval = 0.0651437
-I0511 11:50:55.703510  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.703513  5581 caffe.cpp:501] detection_eval = 0.663306
-I0511 11:50:55.703516  5581 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:50:55.703521  5581 caffe.cpp:501] detection_eval = 6.24798
-I0511 11:50:55.703523  5581 caffe.cpp:501] detection_eval = 0.0436009
-I0511 11:50:55.703526  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.703531  5581 caffe.cpp:501] detection_eval = 0.693548
-I0511 11:50:55.703533  5581 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:50:55.703537  5581 caffe.cpp:501] detection_eval = 6.35282
-I0511 11:50:55.703541  5581 caffe.cpp:501] detection_eval = 0.0431912
-I0511 11:50:55.703544  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.703547  5581 caffe.cpp:501] detection_eval = 0.693548
-I0511 11:50:55.703552  5581 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:50:55.703555  5581 caffe.cpp:501] detection_eval = 6.44556
-I0511 11:50:55.703558  5581 caffe.cpp:501] detection_eval = 0.0368396
-I0511 11:50:55.703562  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703567  5581 caffe.cpp:501] detection_eval = 0.699597
-I0511 11:50:55.703569  5581 caffe.cpp:501] detection_eval = 6.3871
-I0511 11:50:55.703573  5581 caffe.cpp:501] detection_eval = 6.45161
-I0511 11:50:55.703577  5581 caffe.cpp:501] detection_eval = 0.0359233
-I0511 11:50:55.703580  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703584  5581 caffe.cpp:501] detection_eval = 0.695565
-I0511 11:50:55.703588  5581 caffe.cpp:501] detection_eval = 6.35081
-I0511 11:50:55.703593  5581 caffe.cpp:501] detection_eval = 6.4375
-I0511 11:50:55.703595  5581 caffe.cpp:501] detection_eval = 0.0357209
-I0511 11:50:55.703599  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703603  5581 caffe.cpp:501] detection_eval = 0.695565
-I0511 11:50:55.703606  5581 caffe.cpp:501] detection_eval = 6.33266
-I0511 11:50:55.703610  5581 caffe.cpp:501] detection_eval = 6.44758
-I0511 11:50:55.703614  5581 caffe.cpp:501] detection_eval = 0.0291685
-I0511 11:50:55.703619  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703621  5581 caffe.cpp:501] detection_eval = 0.693548
-I0511 11:50:55.703625  5581 caffe.cpp:501] detection_eval = 6.31452
-I0511 11:50:55.703629  5581 caffe.cpp:501] detection_eval = 6.47581
-I0511 11:50:55.703632  5581 caffe.cpp:501] detection_eval = 0.0314611
-I0511 11:50:55.703636  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703640  5581 caffe.cpp:501] detection_eval = 0.691532
-I0511 11:50:55.703644  5581 caffe.cpp:501] detection_eval = 6.31452
-I0511 11:50:55.703647  5581 caffe.cpp:501] detection_eval = 6.52419
-I0511 11:50:55.703651  5581 caffe.cpp:501] detection_eval = 0.0320833
-I0511 11:50:55.703655  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703658  5581 caffe.cpp:501] detection_eval = 0.6875
-I0511 11:50:55.703662  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.703666  5581 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:50:55.703670  5581 caffe.cpp:501] detection_eval = 0.0324025
-I0511 11:50:55.703677  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.703682  5581 caffe.cpp:501] detection_eval = 0.689516
-I0511 11:50:55.703685  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.703689  5581 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:50:55.703693  5581 caffe.cpp:501] detection_eval = 0.0294135
-I0511 11:50:55.703697  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703701  5581 caffe.cpp:501] detection_eval = 0.695565
-I0511 11:50:55.703704  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.703708  5581 caffe.cpp:501] detection_eval = 6.6754
-I0511 11:50:55.703712  5581 caffe.cpp:501] detection_eval = 0.0316228
-I0511 11:50:55.703716  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.703719  5581 caffe.cpp:501] detection_eval = 0.689516
-I0511 11:50:55.703723  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.703727  5581 caffe.cpp:501] detection_eval = 6.72984
-I0511 11:50:55.703730  5581 caffe.cpp:501] detection_eval = 0.0291904
-I0511 11:50:55.703734  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703738  5581 caffe.cpp:501] detection_eval = 0.695565
-I0511 11:50:55.703742  5581 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:50:55.703745  5581 caffe.cpp:501] detection_eval = 6.70565
-I0511 11:50:55.703749  5581 caffe.cpp:501] detection_eval = 0.0282254
-I0511 11:50:55.703753  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703758  5581 caffe.cpp:501] detection_eval = 0.689516
-I0511 11:50:55.703760  5581 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:50:55.703764  5581 caffe.cpp:501] detection_eval = 6.75403
-I0511 11:50:55.703768  5581 caffe.cpp:501] detection_eval = 0.0292542
-I0511 11:50:55.703771  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703775  5581 caffe.cpp:501] detection_eval = 0.6875
-I0511 11:50:55.703779  5581 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:50:55.703783  5581 caffe.cpp:501] detection_eval = 6.69556
-I0511 11:50:55.703788  5581 caffe.cpp:501] detection_eval = 0.0290907
-I0511 11:50:55.703790  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703794  5581 caffe.cpp:501] detection_eval = 0.685484
-I0511 11:50:55.703799  5581 caffe.cpp:501] detection_eval = 6.1875
-I0511 11:50:55.703802  5581 caffe.cpp:501] detection_eval = 6.69758
-I0511 11:50:55.703805  5581 caffe.cpp:501] detection_eval = 0.0313242
-I0511 11:50:55.703809  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703814  5581 caffe.cpp:501] detection_eval = 0.675403
-I0511 11:50:55.703816  5581 caffe.cpp:501] detection_eval = 6.16935
-I0511 11:50:55.703820  5581 caffe.cpp:501] detection_eval = 6.71169
-I0511 11:50:55.703824  5581 caffe.cpp:501] detection_eval = 0.031514
-I0511 11:50:55.703829  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703831  5581 caffe.cpp:501] detection_eval = 0.673387
-I0511 11:50:55.703835  5581 caffe.cpp:501] detection_eval = 6.09677
-I0511 11:50:55.703840  5581 caffe.cpp:501] detection_eval = 6.62702
-I0511 11:50:55.703842  5581 caffe.cpp:501] detection_eval = 0.0292035
-I0511 11:50:55.703846  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703850  5581 caffe.cpp:501] detection_eval = 0.671371
-I0511 11:50:55.703855  5581 caffe.cpp:501] detection_eval = 6.07863
-I0511 11:50:55.703857  5581 caffe.cpp:501] detection_eval = 6.64113
-I0511 11:50:55.703861  5581 caffe.cpp:501] detection_eval = 0.0294854
-I0511 11:50:55.703866  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703868  5581 caffe.cpp:501] detection_eval = 0.669355
-I0511 11:50:55.703872  5581 caffe.cpp:501] detection_eval = 6.06048
-I0511 11:50:55.703876  5581 caffe.cpp:501] detection_eval = 6.62702
-I0511 11:50:55.703879  5581 caffe.cpp:501] detection_eval = 0.0281852
-I0511 11:50:55.703883  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703887  5581 caffe.cpp:501] detection_eval = 0.66129
-I0511 11:50:55.703891  5581 caffe.cpp:501] detection_eval = 6.06048
-I0511 11:50:55.703894  5581 caffe.cpp:501] detection_eval = 6.68548
-I0511 11:50:55.703902  5581 caffe.cpp:501] detection_eval = 0.0296146
-I0511 11:50:55.703907  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703910  5581 caffe.cpp:501] detection_eval = 0.669355
-I0511 11:50:55.703914  5581 caffe.cpp:501] detection_eval = 6.04234
-I0511 11:50:55.703917  5581 caffe.cpp:501] detection_eval = 6.70363
-I0511 11:50:55.703922  5581 caffe.cpp:501] detection_eval = 0.0323881
-I0511 11:50:55.703925  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.703928  5581 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:50:55.703933  5581 caffe.cpp:501] detection_eval = 5.9879
-I0511 11:50:55.703936  5581 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:50:55.703940  5581 caffe.cpp:501] detection_eval = 0.026478
-I0511 11:50:55.703943  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703948  5581 caffe.cpp:501] detection_eval = 0.66129
-I0511 11:50:55.703951  5581 caffe.cpp:501] detection_eval = 5.95161
-I0511 11:50:55.703954  5581 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:50:55.703958  5581 caffe.cpp:501] detection_eval = 0.0298143
-I0511 11:50:55.703963  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.703966  5581 caffe.cpp:501] detection_eval = 0.653226
-I0511 11:50:55.703969  5581 caffe.cpp:501] detection_eval = 5.87903
-I0511 11:50:55.703974  5581 caffe.cpp:501] detection_eval = 6.50806
-I0511 11:50:55.703977  5581 caffe.cpp:501] detection_eval = 0.0292611
-I0511 11:50:55.703980  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703984  5581 caffe.cpp:501] detection_eval = 0.641129
-I0511 11:50:55.703987  5581 caffe.cpp:501] detection_eval = 5.84274
-I0511 11:50:55.703990  5581 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:50:55.703994  5581 caffe.cpp:501] detection_eval = 0.0265516
-I0511 11:50:55.703999  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.704002  5581 caffe.cpp:501] detection_eval = 0.641129
-I0511 11:50:55.704007  5581 caffe.cpp:501] detection_eval = 5.80645
-I0511 11:50:55.704011  5581 caffe.cpp:501] detection_eval = 6.49597
-I0511 11:50:55.704015  5581 caffe.cpp:501] detection_eval = 0.0337191
-I0511 11:50:55.704020  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.704023  5581 caffe.cpp:501] detection_eval = 0.631048
-I0511 11:50:55.704026  5581 caffe.cpp:501] detection_eval = 5.77016
-I0511 11:50:55.704030  5581 caffe.cpp:501] detection_eval = 6.46573
-I0511 11:50:55.704035  5581 caffe.cpp:501] detection_eval = 0.0312134
-I0511 11:50:55.704037  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704041  5581 caffe.cpp:501] detection_eval = 0.637097
-I0511 11:50:55.704046  5581 caffe.cpp:501] detection_eval = 5.77016
-I0511 11:50:55.704048  5581 caffe.cpp:501] detection_eval = 6.51008
-I0511 11:50:55.704052  5581 caffe.cpp:501] detection_eval = 0.0271473
-I0511 11:50:55.704056  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.704061  5581 caffe.cpp:501] detection_eval = 0.629032
-I0511 11:50:55.704064  5581 caffe.cpp:501] detection_eval = 5.73387
-I0511 11:50:55.704067  5581 caffe.cpp:501] detection_eval = 6.48185
-I0511 11:50:55.704071  5581 caffe.cpp:501] detection_eval = 0.0296419
-I0511 11:50:55.704074  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.704078  5581 caffe.cpp:501] detection_eval = 0.627016
-I0511 11:50:55.704082  5581 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:50:55.704087  5581 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:50:55.704089  5581 caffe.cpp:501] detection_eval = 0.0287038
-I0511 11:50:55.704093  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.704097  5581 caffe.cpp:501] detection_eval = 0.618952
-I0511 11:50:55.704102  5581 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:50:55.704104  5581 caffe.cpp:501] detection_eval = 6.5121
-I0511 11:50:55.704108  5581 caffe.cpp:501] detection_eval = 0.0241407
-I0511 11:50:55.704113  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.704115  5581 caffe.cpp:501] detection_eval = 0.625
-I0511 11:50:55.704119  5581 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:50:55.704123  5581 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:50:55.704133  5581 caffe.cpp:501] detection_eval = 0.0278125
-I0511 11:50:55.704136  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704140  5581 caffe.cpp:501] detection_eval = 0.629032
-I0511 11:50:55.704144  5581 caffe.cpp:501] detection_eval = 5.69758
-I0511 11:50:55.704147  5581 caffe.cpp:501] detection_eval = 6.56048
-I0511 11:50:55.704151  5581 caffe.cpp:501] detection_eval = 0.0239643
-I0511 11:50:55.704155  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.704159  5581 caffe.cpp:501] detection_eval = 0.631048
-I0511 11:50:55.704162  5581 caffe.cpp:501] detection_eval = 5.64315
-I0511 11:50:55.704166  5581 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:50:55.704170  5581 caffe.cpp:501] detection_eval = 0.0249106
-I0511 11:50:55.704174  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704177  5581 caffe.cpp:501] detection_eval = 0.620968
-I0511 11:50:55.704180  5581 caffe.cpp:501] detection_eval = 5.58871
-I0511 11:50:55.704185  5581 caffe.cpp:501] detection_eval = 6.43548
-I0511 11:50:55.704187  5581 caffe.cpp:501] detection_eval = 0.0239349
-I0511 11:50:55.704191  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704195  5581 caffe.cpp:501] detection_eval = 0.616935
-I0511 11:50:55.704198  5581 caffe.cpp:501] detection_eval = 5.58871
-I0511 11:50:55.704201  5581 caffe.cpp:501] detection_eval = 6.47782
-I0511 11:50:55.704205  5581 caffe.cpp:501] detection_eval = 0.0220331
-I0511 11:50:55.704208  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.704212  5581 caffe.cpp:501] detection_eval = 0.620968
-I0511 11:50:55.704216  5581 caffe.cpp:501] detection_eval = 5.58871
-I0511 11:50:55.704219  5581 caffe.cpp:501] detection_eval = 6.50605
-I0511 11:50:55.704222  5581 caffe.cpp:501] detection_eval = 0.0235767
-I0511 11:50:55.704226  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.704229  5581 caffe.cpp:501] detection_eval = 0.614919
-I0511 11:50:55.704232  5581 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:50:55.704236  5581 caffe.cpp:501] detection_eval = 6.44758
-I0511 11:50:55.704239  5581 caffe.cpp:501] detection_eval = 0.0242647
-I0511 11:50:55.704246  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.704249  5581 caffe.cpp:501] detection_eval = 0.606855
-I0511 11:50:55.704252  5581 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:50:55.704257  5581 caffe.cpp:501] detection_eval = 6.50202
-I0511 11:50:55.704259  5581 caffe.cpp:501] detection_eval = 0.0235616
-I0511 11:50:55.704263  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.704267  5581 caffe.cpp:501] detection_eval = 0.610887
-I0511 11:50:55.704270  5581 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:50:55.704274  5581 caffe.cpp:501] detection_eval = 6.5121
-I0511 11:50:55.704277  5581 caffe.cpp:501] detection_eval = 0.0258441
-I0511 11:50:55.704282  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.704285  5581 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:50:55.704289  5581 caffe.cpp:501] detection_eval = 5.51613
-I0511 11:50:55.704293  5581 caffe.cpp:501] detection_eval = 6.48387
-I0511 11:50:55.704296  5581 caffe.cpp:501] detection_eval = 0.0236597
-I0511 11:50:55.704300  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.704304  5581 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:50:55.704308  5581 caffe.cpp:501] detection_eval = 5.49798
-I0511 11:50:55.704311  5581 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:50:55.704315  5581 caffe.cpp:501] detection_eval = 0.0250569
-I0511 11:50:55.704319  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.704324  5581 caffe.cpp:501] detection_eval = 0.604839
-I0511 11:50:55.704327  5581 caffe.cpp:501] detection_eval = 5.46169
-I0511 11:50:55.704330  5581 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:50:55.704334  5581 caffe.cpp:501] detection_eval = 0.0238263
-I0511 11:50:55.704339  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704342  5581 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:50:55.704346  5581 caffe.cpp:501] detection_eval = 5.44355
-I0511 11:50:55.704355  5581 caffe.cpp:501] detection_eval = 6.49194
-I0511 11:50:55.704358  5581 caffe.cpp:501] detection_eval = 0.0250854
-I0511 11:50:55.704362  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.704366  5581 caffe.cpp:501] detection_eval = 0.594758
-I0511 11:50:55.704370  5581 caffe.cpp:501] detection_eval = 5.44355
-I0511 11:50:55.704375  5581 caffe.cpp:501] detection_eval = 6.52419
-I0511 11:50:55.704378  5581 caffe.cpp:501] detection_eval = 0.0222069
-I0511 11:50:55.704381  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.704385  5581 caffe.cpp:501] detection_eval = 0.600806
-I0511 11:50:55.704390  5581 caffe.cpp:501] detection_eval = 5.40726
-I0511 11:50:55.704393  5581 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:50:55.704396  5581 caffe.cpp:501] detection_eval = 0.0222845
-I0511 11:50:55.704401  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.704404  5581 caffe.cpp:501] detection_eval = 0.59879
-I0511 11:50:55.704408  5581 caffe.cpp:501] detection_eval = 5.29839
-I0511 11:50:55.704411  5581 caffe.cpp:501] detection_eval = 6.34879
-I0511 11:50:55.704416  5581 caffe.cpp:501] detection_eval = 0.0229918
-I0511 11:50:55.704419  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.704423  5581 caffe.cpp:501] detection_eval = 0.578629
-I0511 11:50:55.705934  5581 caffe.cpp:546] class AP 1: 0.649931
-I0511 11:50:55.706599  5581 caffe.cpp:546] class AP 2: 0.730188
-I0511 11:50:55.720845  5581 caffe.cpp:546] class AP 3: 0.553319
-I0511 11:50:55.725518  5581 caffe.cpp:546] class AP 4: 0.506074
-I0511 11:50:55.752445  5581 caffe.cpp:546] class AP 5: 0.339543
-I0511 11:50:55.752918  5581 caffe.cpp:546] class AP 6: 0.730379
-I0511 11:50:55.764034  5581 caffe.cpp:546] class AP 7: 0.701396
-I0511 11:50:55.764760  5581 caffe.cpp:546] class AP 8: 0.815084
-I0511 11:50:55.789405  5581 caffe.cpp:546] class AP 9: 0.431345
-I0511 11:50:55.790325  5581 caffe.cpp:546] class AP 10: 0.624216
-I0511 11:50:55.791142  5581 caffe.cpp:546] class AP 11: 0.593459
-I0511 11:50:55.792280  5581 caffe.cpp:546] class AP 12: 0.721829
-I0511 11:50:55.792790  5581 caffe.cpp:546] class AP 13: 0.790938
-I0511 11:50:55.793241  5581 caffe.cpp:546] class AP 14: 0.743532
-I0511 11:50:55.880975  5581 caffe.cpp:546] class AP 15: 0.724583
-I0511 11:50:55.887090  5581 caffe.cpp:546] class AP 16: 0.363203
-I0511 11:50:55.889358  5581 caffe.cpp:546] class AP 17: 0.598904
-I0511 11:50:55.889951  5581 caffe.cpp:546] class AP 18: 0.609708
-I0511 11:50:55.890596  5581 caffe.cpp:546] class AP 19: 0.754557
-I0511 11:50:55.891871  5581 caffe.cpp:546] class AP 20: 0.610099
-I0511 11:50:55.891880  5581 caffe.cpp:552] Test net output mAP #0: detection_eval = 0.629614

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/run.sh b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/run.sh
deleted file mode 100755 (executable)
index 9768a60..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/run.sh
+++ /dev/null
@@ -1,5 +0,0 @@
-/user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin test_detection \
---model="training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize/test.prototxt" \
---iterations="496" \
---weights="training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel" \
---gpu "0" 2>&1 | tee training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize/run.log

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/solver.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/solver.prototxt
deleted file mode 100755 (executable)
index 91b3ad0..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/solver.prototxt
+++ /dev/null
@@ -1,33 +0,0 @@
-train_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize/train.prototxt"
-test_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize/test.prototxt"
-test_iter: 496
-test_interval: 2000
-base_lr: 0.01
-display: 100
-max_iter: 120000
-lr_policy: "multistep"
-gamma: 0.1
-power: 1.0
-momentum: 0.9
-weight_decay: 1e-05
-snapshot: 2000
-snapshot_prefix: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize/voc0712_mobiledetnet-0.5"
-solver_mode: GPU
-device_id: 0
-random_seed: 33
-debug_info: false
-snapshot_after_train: true
-regularization_type: "L1"
-test_initialization: true
-average_loss: 10
-stepvalue: 60000
-stepvalue: 90000
-stepvalue: 300000
-iter_size: 2
-type: "SGD"
-display_sparsity: 1000
-sparse_mode: SPARSE_UPDATE
-eval_type: "detection"
-ap_version: "11point"
-show_per_class_result: true
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/test.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/test.prototxt
deleted file mode 100755 (executable)
index 1d4190c..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/test.prototxt
+++ /dev/null
@@ -1,2420 +0,0 @@
-quantize: true
-name: "mobiledetnet-0.5_test"
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 10
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
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-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
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-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
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-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
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-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
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-}
-layer {
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-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
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-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
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-    dilation: 1
-  }
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-layer {
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-  bottom: "ctx_output1"
-  top: "ctx_output1"
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
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-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
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-    decay_mult: 1
-  }
-  param {
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-  }
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-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
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-  }
-  param {
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-    decay_mult: 0
-  }
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-    }
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-    }
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-layer {
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-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
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-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
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-    }
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-layer {
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-  type: "BatchNorm"
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-  top: "ctx_output4/1x1"
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-    decay_mult: 0
-  }
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-    }
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-    }
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-layer {
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-  top: "ctx_output4"
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  top: "ctx_output4"
-}
-layer {
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-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
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-    }
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-    }
-    dilation: 1
-  }
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-layer {
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-  top: "ctx_output5/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    group: 512
-    stride: 1
-    weight_filler {
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-    }
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  top: "ctx_output5"
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  top: "ctx_output5"
-}
-layer {
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-  type: "Convolution"
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-  top: "ctx_output1/relu_mbox_loc"
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    group: 1
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
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-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
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-  }
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-layer {
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-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    group: 1
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-    }
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
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-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
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-  type: "Flatten"
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-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
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-    max_size: 88.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
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-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
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-  type: "Flatten"
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-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
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-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
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-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
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-  type: "Flatten"
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-  top: "ctx_output2/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
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-  type: "PriorBox"
-  bottom: "ctx_output2"
-  bottom: "data"
-  top: "ctx_output2/relu_mbox_priorbox"
-  prior_box_param {
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-    max_size: 157.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
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-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_loc"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
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-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
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-  top: "ctx_output3/relu_mbox_loc_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
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-  type: "Flatten"
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-  top: "ctx_output3/relu_mbox_loc_flat"
-  flatten_param {
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-  }
-}
-layer {
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-  top: "ctx_output3/relu_mbox_conf"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
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-  top: "ctx_output3/relu_mbox_conf_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
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-  type: "Flatten"
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-  top: "ctx_output3/relu_mbox_conf_flat"
-  flatten_param {
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-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output3"
-  bottom: "data"
-  top: "ctx_output3/relu_mbox_priorbox"
-  prior_box_param {
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-    max_size: 226.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_loc"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
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-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_loc"
-  top: "ctx_output4/relu_mbox_loc_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
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-layer {
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-  type: "Flatten"
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-  top: "ctx_output4/relu_mbox_loc_flat"
-  flatten_param {
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-  }
-}
-layer {
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-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
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-    bias_term: true
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-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
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-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
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-  type: "Flatten"
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-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
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-  }
-}
-layer {
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-  type: "PriorBox"
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-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
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-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
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-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
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-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
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-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
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-  }
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-layer {
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-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
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-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_reshape"
-  type: "Reshape"
-  bottom: "mbox_conf"
-  top: "mbox_conf_reshape"
-  reshape_param {
-    shape {
-      dim: 0
-      dim: -1
-      dim: 21
-    }
-  }
-}
-layer {
-  name: "mbox_conf_softmax"
-  type: "Softmax"
-  bottom: "mbox_conf_reshape"
-  top: "mbox_conf_softmax"
-  softmax_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_conf_flatten"
-  type: "Flatten"
-  bottom: "mbox_conf_softmax"
-  top: "mbox_conf_flatten"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "detection_out"
-  type: "DetectionOutput"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf_flatten"
-  bottom: "mbox_priorbox"
-  top: "detection_out"
-  include {
-    phase: TEST
-  }
-  detection_output_param {
-    num_classes: 21
-    share_location: true
-    background_label_id: 0
-    nms_param {
-      nms_threshold: 0.45
-      top_k: 400
-    }
-    save_output_param {
-      output_directory: ""
-      output_name_prefix: "comp4_det_test_"
-      output_format: "VOC"
-      label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-      name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-      num_test_image: 4952
-    }
-    code_type: CENTER_SIZE
-    keep_top_k: 200
-    confidence_threshold: 0.01
-  }
-}
-layer {
-  name: "detection_eval"
-  type: "DetectionEvaluate"
-  bottom: "detection_out"
-  bottom: "label"
-  top: "detection_eval"
-  include {
-    phase: TEST
-  }
-  detection_evaluate_param {
-    num_classes: 21
-    background_label_id: 0
-    overlap_threshold: 0.5
-    evaluate_difficult_gt: false
-    name_size_file: "../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/train.prototxt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/train.prototxt
deleted file mode 100755 (executable)
index 63b33c1..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/train.prototxt
+++ /dev/null
@@ -1,2482 +0,0 @@
-name: "mobiledetnet-0.5"
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TRAIN
-  }
-  transform_param {
-    mirror: true
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-      interp_mode: AREA
-      interp_mode: NEAREST
-      interp_mode: CUBIC
-      interp_mode: LANCZOS4
-    }
-    emit_constraint {
-      emit_type: CENTER
-    }
-    crop_h: 256
-    crop_w: 512
-    distort_param {
-      brightness_prob: 0.5
-      brightness_delta: 32
-      contrast_prob: 0.5
-      contrast_lower: 0.5
-      contrast_upper: 1.5
-      hue_prob: 0.5
-      hue_delta: 18
-      saturation_prob: 0.5
-      saturation_lower: 0.5
-      saturation_upper: 1.5
-      random_order_prob: 0.0
-    }
-    expand_param {
-      prob: 0.5
-      max_expand_ratio: 4.0
-    }
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb"
-    batch_size: 16
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-      max_sample: 1
-      max_trials: 1
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.1
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.3
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.5
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.7
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.9
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1.0
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2.0
-      }
-      sample_constraint {
-        max_jaccard_overlap: 1.0
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
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-}
-layer {
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-  top: "conv2_1/sep"
-}
-layer {
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-  top: "conv2_1/sep"
-  scale_param {
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-  }
-}
-layer {
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-  top: "conv2_1/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
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-}
-layer {
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-  type: "BatchNorm"
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-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
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-}
-layer {
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-  type: "BatchNorm"
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-  top: "conv2_2/sep"
-}
-layer {
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-  type: "Scale"
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-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
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-  top: "conv2_2/sep"
-}
-layer {
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-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
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-layer {
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-  top: "conv3_1/dw"
-}
-layer {
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-  type: "Scale"
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-  scale_param {
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-  }
-}
-layer {
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-  top: "conv3_1/dw"
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-layer {
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-  param {
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-    decay_mult: 1
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-    group: 1
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-    weight_filler {
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-}
-layer {
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-layer {
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-  param {
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-layer {
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-layer {
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-layer {
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-  }
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-    stride: 2
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-layer {
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-}
-layer {
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-}
-layer {
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-  param {
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-layer {
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-  top: "conv4_2/sep"
-  scale_param {
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-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_1/sep/scale"
-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
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-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
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-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
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-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
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-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
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-    dilation: 1
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-      value: 0
-    }
-    dilation: 1
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-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
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-    dilation: 1
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-layer {
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-  bottom: "ctx_output2"
-  top: "ctx_output2"
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
-  name: "ctx_output3/1x1"
-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
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-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-    bias_filler {
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-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/relu"
-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19.0
-    max_size: 88.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output2"
-  bottom: "data"
-  top: "ctx_output2/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 88.0
-    max_size: 157.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_loc"
-  top: "ctx_output3/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_loc_perm"
-  top: "ctx_output3/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output3"
-  top: "ctx_output3/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output3/relu_mbox_conf"
-  top: "ctx_output3/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output3/relu_mbox_conf_perm"
-  top: "ctx_output3/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output3/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output3"
-  bottom: "data"
-  top: "ctx_output3/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 157.0
-    max_size: 226.0
-    aspect_ratio: 2
-    aspect_ratio: 3
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_loc"
-  top: "ctx_output4/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_loc_perm"
-  top: "ctx_output4/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output4"
-  top: "ctx_output4/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output4/relu_mbox_conf"
-  top: "ctx_output4/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output4/relu_mbox_conf_perm"
-  top: "ctx_output4/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output4/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output4"
-  bottom: "data"
-  top: "ctx_output4/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 226.0
-    max_size: 295.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_loc"
-  top: "ctx_output5/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_loc_perm"
-  top: "ctx_output5/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output5"
-  top: "ctx_output5/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output5/relu_mbox_conf"
-  top: "ctx_output5/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output5/relu_mbox_conf_perm"
-  top: "ctx_output5/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output5/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output5"
-  bottom: "data"
-  top: "ctx_output5/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 295.0
-    max_size: 364.0
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "mbox_loc"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_loc_flat"
-  bottom: "ctx_output2/relu_mbox_loc_flat"
-  bottom: "ctx_output3/relu_mbox_loc_flat"
-  bottom: "ctx_output4/relu_mbox_loc_flat"
-  bottom: "ctx_output5/relu_mbox_loc_flat"
-  top: "mbox_loc"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_conf"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_conf_flat"
-  bottom: "ctx_output2/relu_mbox_conf_flat"
-  bottom: "ctx_output3/relu_mbox_conf_flat"
-  bottom: "ctx_output4/relu_mbox_conf_flat"
-  bottom: "ctx_output5/relu_mbox_conf_flat"
-  top: "mbox_conf"
-  concat_param {
-    axis: 1
-  }
-}
-layer {
-  name: "mbox_priorbox"
-  type: "Concat"
-  bottom: "ctx_output1/relu_mbox_priorbox"
-  bottom: "ctx_output2/relu_mbox_priorbox"
-  bottom: "ctx_output3/relu_mbox_priorbox"
-  bottom: "ctx_output4/relu_mbox_priorbox"
-  bottom: "ctx_output5/relu_mbox_priorbox"
-  top: "mbox_priorbox"
-  concat_param {
-    axis: 2
-  }
-}
-layer {
-  name: "mbox_loss"
-  type: "MultiBoxLoss"
-  bottom: "mbox_loc"
-  bottom: "mbox_conf"
-  bottom: "mbox_priorbox"
-  bottom: "label"
-  top: "mbox_loss"
-  include {
-    phase: TRAIN
-  }
-  propagate_down: true
-  propagate_down: true
-  propagate_down: false
-  propagate_down: false
-  loss_param {
-    normalization: VALID
-  }
-  multibox_loss_param {
-    loc_loss_type: SMOOTH_L1
-    conf_loss_type: SOFTMAX
-    loc_weight: 1.0
-    num_classes: 21
-    share_location: true
-    match_type: PER_PREDICTION
-    overlap_threshold: 0.5
-    use_prior_for_matching: true
-    background_label_id: 0
-    use_difficult_gt: true
-    neg_pos_ratio: 3.0
-    neg_overlap: 0.5
-    code_type: CENTER_SIZE
-    ignore_cross_boundary_bbox: false
-    mining_type: MAX_NEGATIVE
-    ignore_difficult_gt: false
-  }
-}
-

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/train_image_object_detection.sh b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/train_image_object_detection.sh
deleted file mode 100755 (executable)
index c08e0b4..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/test_quantize/train_image_object_detection.sh
+++ /dev/null
@@ -1,360 +0,0 @@
-#!/bin/bash
-
-#-------------------------------------------------------
-DATE_TIME=`date +'%Y%m%d_%H-%M'`
-#-------------------------------------------------------
-
-#------------------------------------------------
-gpus="0" #"0,1" #"0,1,2"   #IMPORTANT: change this to "0" if you have only one GPU and adjust batch_size (below) accordingly
-
-#-------------------------------------------------------
-model_name=ssdJacintoNetV2       #ssdJacintoNetV2  #mobiledetnet-0.5     
-dataset=voc0712                  #voc0712,ti-custom-cfg1,ti-custom-cfg2
-#------------------------------------------------
-
-#Download the pretrained weights
-weights_dst="../trained/image_classification/imagenet_jacintonet11v2/initial/imagenet_jacintonet11v2_iter_320000.caffemodel"
-
-#------------------------------------------------
-#ssd-size:'512x512', '300x300','256x256'
-ssd_size='512x512'
-
-#0:[1,2,1/2] for each reg head, 1:like orig SSD
-aspect_ratios_type=1
-
-#max donwsampling factor: 16,32
-ds_fac=32
-
-#down sampling type: 'DFLT', 'PSP'
-ds_type='PSP'
-
-#regression head at downsamling 8 layer: 0,1 
-reg_head_at_ds8=1
-
-#use concat layers for regression heads
-concat_reg_head=0
-
-#kernel size for mbox_loc, mbox_conf conv
-ker_mbox_loc_conf=3
-
-#if unintialized value: Average of W,H will be used as min dim
-min_dim=-1
-
-#1:model tuned for small objects, 0:model tuned for moderate size object like PASCAL VOC
-small_objs=0
-
-#"step", "multistep", "poly"
-lr_policy="multistep"
-
-#needed for coco training for gray scale images
-force_color=0
-stepvalue3=300000 
-
-#num op ch for mbox layers = num_intermediate/2
-num_intermediate=512
-rhead_name_non_linear=0
-
-#1: difficult GT will be used for eval, 0: difficult GT will not be used for evaluation
-evaluate_difficult_gt=0
-
-#:Experimntal option. Does not have  any effect now.
-ignore_difficult_gt=0
-
-#set to True for VOC0712
-use_difficult_gt=1
-
-#"poly","multistep"
-lr_policy="multistep"
-
-#set it to 4.0 for poly
-power=1.0
-
-#0.0005 (orignal SSD), 0.0001
-weight_decay_L2=0.0001
-
-#0:linear,1:log,2:like original SSD (min/max ratio will be recomputed)
-log_space_steps=2
-min_ratio=10
-max_ratio=90
-
-#1:FC layer like originalk SSD, 0: no FC layer
-fully_conv_at_end=0
-
-#1: connect 3 head in base n/w. Experimental. set it to 0
-base_nw_3_head=0
-
-#1:first head num of op channel same as other layers, 0: first hd double the number of op channel
-first_hd_same_op_ch=1
-
-#To chop of last few heads. It will make max/min size computed based on original number of heads
-chop_num_heads=0
-
-#known issue - use_image_list=0 && shuffle=1 => hang.
-use_image_list=0 
-
-#Note shuffle is used only in training
-shuffle=0        
-
-#sparsity will be induced gradually starting from this value
-sparsity_start_factor=0.5
-#-------------------------------------------------------
-if [ $dataset = "voc0712" ]
-then
-
-  train_data="../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/VOC0712/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
- 
-  num_test_image=4952
-  num_classes=21
-
-  min_dim=512
-  
-  resize_width=512
-  resize_height=512
-  crop_width=512
-  crop_height=512
-  batch_size=16    #32    #16
-
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=120000    #120000  #64000   #32000
-  stepvalue1=60000   #60000   #32000   #16000
-  stepvalue2=90000   #90000   #48000   #24000
-  base_lr=1e-2       #1e-2    #1e-4    #1e-3
-  
-  #use batch norm ofr mbox layer1:enable,0:disable
-  use_batchnorm_mbox=1
-
-  sparsity_start_factor=0.25 
-
-elif [ $dataset = "ti-custom-cfg1" ]
-then
-  #In V2 removed V153,154(part of TI Demo) and V002(anno has been corrected so no need to use VGG generated)     
- 
-  train_data="../../caffe-jacinto/examples/ti-custom-cfg1/ti-custom-cfg1_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/ti-custom-cfg1/ti-custom-cfg1_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/ti-custom-cfg1/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/ti-custom-cfg1/labelmap.prototxt"
- 
-  num_test_image=3609
-  num_classes=4
-
-  min_dim=368
- 
-  resize_width=720
-  resize_height=368
-  crop_width=720
-  crop_height=368
-  use_difficult_gt=0
-  small_objs=1
-  ker_mbox_loc_conf=1
-  batch_size=16      #32    #16
-
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=120000    #120000  #64000   #32000
-  stepvalue1=30000   #60000   #32000   #16000
-  stepvalue2=45000   #90000   #48000   #24000
-  base_lr=1e-3       #1e-2    #1e-4    #1e-3
-  lr_policy="poly"
-  #set it to 4.0 for poly
-  power=4.0
-
-  #0.0005 (orignal SSD), 0.0001
-  weight_decay_L2=0.0005
-  use_batchnorm_mbox=0
-elif [ $dataset = "ti-custom-cfg2" ]
-then
-  train_data="../../caffe-jacinto/examples/ti-custom-cfg2/ti-custom-cfg2_trainval_lmdb"
-  test_data="../../caffe-jacinto/examples/ti-custom-cfg2/ti-custom-cfg2_test_lmdb"
-
-  name_size_file="../../caffe-jacinto/data/ti-custom-cfg2/test_name_size.txt"
-  label_map_file="../../caffe-jacinto/data/ti-custom-cfg2/labelmap.prototxt"
-
-  num_test_image=294
-  num_classes=3 
-
-  min_dim=256
-  ssd_size='512x512'
- 
-  resize_width=512
-  resize_height=256
-  crop_width=512
-  crop_height=256
-  small_objs=0
-  ker_mbox_loc_conf=1
-  batch_size=16      #32    #16
-
-  #ignore lables are marked as diff in TI dataset 
-  use_difficult_gt=1
-  
-  #solver params
-  type="SGD"         #"SGD"   #Adam    #"Adam"
-  max_iter=50000     #120000  #64000   #32000
-  stepvalue1=30000   #60000   #32000   #16000
-  stepvalue2=40000   #90000   #48000   #24000
-  base_lr=1e-2       #1e-2    #1e-4    #1e-3
-  #set it to 4.0 for poly
-  power=1.0
-
-  #0.0005 (orignal SSD), 0.0001
-  weight_decay_L2=0.0001
-  use_batchnorm_mbox=1
-else
-  echo "Invalid dataset name"
-  exit
-fi
-
-model_name_to_print=$model_name 
-if [ $model_name = 'ssdJacintoNetV2' ]
-then
-  model_name_to_print="JDetNet" 
-fi  
-
-folder_name=training/"$dataset"/"$model_name_to_print"/"$DATE_TIME"_"ds_PSP_dsFac_32_hdDS8_1";mkdir training/"$dataset";mkdir training/"$dataset"/"$model_name_to_print";mkdir $folder_name
-
-#------------------------------------------------
-LOG=$folder_name/train-log_"$DATE_TIME".txt
-exec &> >(tee -a "$LOG")
-echo Logging output to "$LOG"
-
-#-------------------------------------------------------
-#Initial training
-stage="initial"
-weights=$weights_dst
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],'weight_decay':$weight_decay_L2}"
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,\
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,\
-'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type',\
-'rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,\
-'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#l1 regularized training before sparsification
-stage="l1reg"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_"$max_iter".caffemodel
-
-max_iter=60000
-stepvalue1=30000
-stepvalue2=45000
-base_lr=1e-3       #1e-2    #1e-4    #1e-3
-l1reg_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$l1reg_solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#incremental sparsification and finetuning
-stage="sparse"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-#Using more than one GPU for this step gives strange results. Imbalanced accuracy between the GPUs.
-gpus="0" #"0,1,2"
-batch_size=8
-lr_policy="poly"
-#set it to 4.0 for poly
-power=4.0
-base_lr=1e-3       #1e-2    #1e-4    #1e-3
-sparse_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':2000,\
-'sparsity_target':0.70,'sparsity_start_iter':0,'sparsity_start_factor':$sparsity_start_factor,\
-'sparsity_step_iter':2000,'sparsity_step_factor':0.05,'sparsity_itr_increment_bfr_applying':1,'sparsity_threshold_maxratio':0.2,\
-'sparsity_threshold_value_max':0.2}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox, 'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$sparse_solver_param
-config_name_prev=$config_name
-
-#-------------------------------------------------------
-#test
-stage="test"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-test_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':1000}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'test_batch_size':10,'caffe_cmd':'test_detection','display_sparsity':1,\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$test_solver_param
-#config_name_prev=$config_name
-
-#-------------------------------------------------------
-#test_quantize
-stage="test_quantize"
-weights=$config_name_prev/"$dataset"_"$model_name"_iter_$max_iter.caffemodel
-
-test_solver_param="{'type':'$type','base_lr':$base_lr,'max_iter':$max_iter,'lr_policy':'$lr_policy','power':$power,'stepvalue':[$stepvalue1,$stepvalue2,$stepvalue3],\
-'regularization_type':'L1','weight_decay':1e-5,\
-'sparse_mode':1,'display_sparsity':1000}"
-
-config_name="$folder_name"/$stage; echo $config_name; mkdir $config_name
-config_param="{'config_name':'$config_name','model_name':'$model_name','dataset':'$dataset','gpus':'$gpus',\
-'train_data':'$train_data','test_data':'$test_data','name_size_file':'$name_size_file','label_map_file':'$label_map_file',\
-'num_test_image':$num_test_image,'num_classes':$num_classes,'min_ratio':$min_ratio,'max_ratio':$max_ratio,
-'log_space_steps':$log_space_steps,'use_difficult_gt':$use_difficult_gt,'ignore_difficult_gt':$ignore_difficult_gt,'evaluate_difficult_gt':$evaluate_difficult_gt,\
-'pretrain_model':'$weights','use_image_list':$use_image_list,'shuffle':$shuffle,'num_output':8,\
-'resize_width':$resize_width,'resize_height':$resize_height,'crop_width':$crop_width,'crop_height':$crop_height,'batch_size':$batch_size,\
-'test_batch_size':10,'caffe_cmd':'test_detection',\
-'aspect_ratios_type':$aspect_ratios_type,'ssd_size':'$ssd_size','small_objs':$small_objs,'min_dim':$min_dim,'concat_reg_head':$concat_reg_head,
-'fully_conv_at_end':$fully_conv_at_end,'first_hd_same_op_ch':$first_hd_same_op_ch,'ker_mbox_loc_conf':$ker_mbox_loc_conf,\
-'base_nw_3_head':$base_nw_3_head,'reg_head_at_ds8':$reg_head_at_ds8,'ds_fac':$ds_fac,'ds_type':'$ds_type','rhead_name_non_linear':$rhead_name_non_linear,\
-'force_color':$force_color,'num_intermediate':$num_intermediate,'use_batchnorm_mbox':$use_batchnorm_mbox,'chop_num_heads':$chop_num_heads}" 
-
-python ./models/image_object_detection.py --config_param="$config_param" --solver_param=$test_solver_param
-
-echo "quantize: true" > $config_name/deploy_new.prototxt
-cat $config_name/deploy.prototxt >> $config_name/deploy_new.prototxt
-mv --force $config_name/deploy_new.prototxt $config_name/deploy.prototxt
-
-echo "quantize: true" > $config_name/test_new.prototxt
-cat $config_name/test.prototxt >> $config_name/test_new.prototxt
-mv --force $config_name/test_new.prototxt $config_name/test.prototxt
-
-#-------------------------------------------------------
-#run
-list_dirs=`command ls -d1 "$folder_name"/*/ | command cut -f5 -d/`
-for f in $list_dirs; do "$folder_name"/$f/run.sh; done

diff --git a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/train-log_20180510_14-48.txt b/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/train-log_20180510_14-48.txt
deleted file mode 100755 (executable)
index b80a8d5..0000000
--- a/trained/object_detection/voc0712/mobiledetnet-0.5/ssd512x256_ds_PSP_dsFac_32_hdDS8_0/train-log_20180510_14-48.txt
+++ /dev/null
@@ -1,40663 +0,0 @@
-Logging output to training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/train-log_20180510_14-48.txt
-training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial
-{'type':'SGD','base_lr':1e-2,'max_iter':120000,'lr_policy':'multistep','power':1.0,'stepvalue':[60000,90000,300000],'weight_decay':1e-4}
-{'config_name':'training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial','model_name':'mobiledetnet-0.5','dataset':'voc0712','gpus':'0','train_data':'../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb','test_data':'../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb','name_size_file':'../../caffe-jacinto/data/VOC0712/test_name_size.txt','label_map_file':'../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt','num_test_image':4952,'num_classes':21,'min_ratio':5,'max_ratio':95,
-'log_space_steps':0,'use_difficult_gt':1,'ignore_difficult_gt':0,'evaluate_difficult_gt':0,'pretrain_model':'../trained/image_classification/imagenet_mobilenet-0.5/initial/imagenet_mobilenet-0.5_iter_320000.caffemodel','use_image_list':0,'shuffle':0,'num_output':8,'resize_width':512,'resize_height':256,'crop_width':512,'crop_height':256,'batch_size':16,'aspect_ratios_type':1,'ssd_size':'512x256','small_objs':0,'min_dim':-1,'concat_reg_head':0,'fully_conv_at_end':0,'first_hd_same_op_ch':1,'ker_mbox_loc_conf':1,'base_nw_3_head':0,'reg_head_at_ds8':1,'ds_fac':32,'ds_type':'PSP','rhead_name_non_linear':0,'force_color':0,'num_intermediate':512,'use_batchnorm_mbox':1,'chop_num_heads':0}
-caffe_root = :  /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-config_param.ds_fac : 32
-config_param.stride_list : [2, 2, 2, 2, 2]
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv1  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 0, 'decay_mult': 0}]}
-conv_name: conv1 3x3 16 - group=1
-conv_name: conv2_1/dw 3x3 16 - group=16
-conv_name: conv2_1/sep 1x1 32 - group=1
-conv_name: conv2_2/dw 3x3 32 - group=32
-conv_name: conv2_2/sep 1x1 64 - group=1
-conv_name: conv3_1/dw 3x3 64 - group=64
-conv_name: conv3_1/sep 1x1 64 - group=1
-conv_name: conv3_2/dw 3x3 64 - group=64
-conv_name: conv3_2/sep 1x1 128 - group=1
-conv_name: conv4_1/dw 3x3 128 - group=128
-conv_name: conv4_1/sep 1x1 128 - group=1
-conv_name: conv4_2/dw 3x3 128 - group=128
-conv_name: conv4_2/sep 1x1 256 - group=1
-conv_name: conv5_1/dw 3x3 256 - group=256
-conv_name: conv5_1/sep 1x1 256 - group=1
-conv_name: conv5_2/dw 3x3 256 - group=256
-conv_name: conv5_2/sep 1x1 256 - group=1
-conv_name: conv5_3/dw 3x3 256 - group=256
-conv_name: conv5_3/sep 1x1 256 - group=1
-conv_name: conv5_4/dw 3x3 256 - group=256
-conv_name: conv5_4/sep 1x1 256 - group=1
-conv_name: conv5_5/dw 3x3 256 - group=256
-conv_name: conv5_5/sep 1x1 256 - group=1
-conv_name: conv5_6/dw 3x3 256 - group=256
-conv_name: conv5_6/sep 1x1 512 - group=1
-conv_name: conv6/dw 3x3 512 - group=512
-conv_name: conv6/sep 1x1 512 - group=1
-min_dim = 384
-minsizes = [19.0, 88.0, 157.0, 226.0, 295.0]
-maxsizes = [88.0, 157.0, 226.0, 295.0, 364.0]
-ARs: [[2], [2, 3], [2, 3], [2], [2]]
-training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/train.prototxt
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv1  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 0, 'decay_mult': 0}]}
-conv_name: conv1 3x3 16 - group=1
-conv_name: conv2_1/dw 3x3 16 - group=16
-conv_name: conv2_1/sep 1x1 32 - group=1
-conv_name: conv2_2/dw 3x3 32 - group=32
-conv_name: conv2_2/sep 1x1 64 - group=1
-conv_name: conv3_1/dw 3x3 64 - group=64
-conv_name: conv3_1/sep 1x1 64 - group=1
-conv_name: conv3_2/dw 3x3 64 - group=64
-conv_name: conv3_2/sep 1x1 128 - group=1
-conv_name: conv4_1/dw 3x3 128 - group=128
-conv_name: conv4_1/sep 1x1 128 - group=1
-conv_name: conv4_2/dw 3x3 128 - group=128
-conv_name: conv4_2/sep 1x1 256 - group=1
-conv_name: conv5_1/dw 3x3 256 - group=256
-conv_name: conv5_1/sep 1x1 256 - group=1
-conv_name: conv5_2/dw 3x3 256 - group=256
-conv_name: conv5_2/sep 1x1 256 - group=1
-conv_name: conv5_3/dw 3x3 256 - group=256
-conv_name: conv5_3/sep 1x1 256 - group=1
-conv_name: conv5_4/dw 3x3 256 - group=256
-conv_name: conv5_4/sep 1x1 256 - group=1
-conv_name: conv5_5/dw 3x3 256 - group=256
-conv_name: conv5_5/sep 1x1 256 - group=1
-conv_name: conv5_6/dw 3x3 256 - group=256
-conv_name: conv5_6/sep 1x1 512 - group=1
-conv_name: conv6/dw 3x3 512 - group=512
-conv_name: conv6/sep 1x1 512 - group=1
-training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test
-{'type':'SGD','base_lr':1e-2,'max_iter':120000,'lr_policy':'multistep','power':1.0,'stepvalue':[60000,90000,300000],'regularization_type':'L1','weight_decay':1e-5,'sparse_mode':1,'display_sparsity':1000}
-{'config_name':'training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test','model_name':'mobiledetnet-0.5','dataset':'voc0712','gpus':'0','train_data':'../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb','test_data':'../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb','name_size_file':'../../caffe-jacinto/data/VOC0712/test_name_size.txt','label_map_file':'../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt','num_test_image':4952,'num_classes':21,'min_ratio':5,'max_ratio':95,
-'log_space_steps':0,'use_difficult_gt':1,'ignore_difficult_gt':0,'evaluate_difficult_gt':0,'pretrain_model':'training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel','use_image_list':0,'shuffle':0,'num_output':8,'resize_width':512,'resize_height':256,'crop_width':512,'crop_height':256,'batch_size':16,'test_batch_size':10,'caffe_cmd':'test_detection','display_sparsity':1,'aspect_ratios_type':1,'ssd_size':'512x256','small_objs':0,'min_dim':-1,'concat_reg_head':0,
-'fully_conv_at_end':0,'first_hd_same_op_ch':1,'ker_mbox_loc_conf':1,'base_nw_3_head':0,'reg_head_at_ds8':1,'ds_fac':32,'ds_type':'PSP','rhead_name_non_linear':0,'force_color':0,'num_intermediate':512,'use_batchnorm_mbox':1,'chop_num_heads':0}
-caffe_root = :  /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-config_param.ds_fac : 32
-config_param.stride_list : [2, 2, 2, 2, 2]
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv1  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 0, 'decay_mult': 0}]}
-conv_name: conv1 3x3 16 - group=1
-conv_name: conv2_1/dw 3x3 16 - group=16
-conv_name: conv2_1/sep 1x1 32 - group=1
-conv_name: conv2_2/dw 3x3 32 - group=32
-conv_name: conv2_2/sep 1x1 64 - group=1
-conv_name: conv3_1/dw 3x3 64 - group=64
-conv_name: conv3_1/sep 1x1 64 - group=1
-conv_name: conv3_2/dw 3x3 64 - group=64
-conv_name: conv3_2/sep 1x1 128 - group=1
-conv_name: conv4_1/dw 3x3 128 - group=128
-conv_name: conv4_1/sep 1x1 128 - group=1
-conv_name: conv4_2/dw 3x3 128 - group=128
-conv_name: conv4_2/sep 1x1 256 - group=1
-conv_name: conv5_1/dw 3x3 256 - group=256
-conv_name: conv5_1/sep 1x1 256 - group=1
-conv_name: conv5_2/dw 3x3 256 - group=256
-conv_name: conv5_2/sep 1x1 256 - group=1
-conv_name: conv5_3/dw 3x3 256 - group=256
-conv_name: conv5_3/sep 1x1 256 - group=1
-conv_name: conv5_4/dw 3x3 256 - group=256
-conv_name: conv5_4/sep 1x1 256 - group=1
-conv_name: conv5_5/dw 3x3 256 - group=256
-conv_name: conv5_5/sep 1x1 256 - group=1
-conv_name: conv5_6/dw 3x3 256 - group=256
-conv_name: conv5_6/sep 1x1 512 - group=1
-conv_name: conv6/dw 3x3 512 - group=512
-conv_name: conv6/sep 1x1 512 - group=1
-min_dim = 384
-minsizes = [19.0, 88.0, 157.0, 226.0, 295.0]
-maxsizes = [88.0, 157.0, 226.0, 295.0, 364.0]
-ARs: [[2], [2, 3], [2, 3], [2], [2]]
-training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test/train.prototxt
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv1  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 0, 'decay_mult': 0}]}
-conv_name: conv1 3x3 16 - group=1
-conv_name: conv2_1/dw 3x3 16 - group=16
-conv_name: conv2_1/sep 1x1 32 - group=1
-conv_name: conv2_2/dw 3x3 32 - group=32
-conv_name: conv2_2/sep 1x1 64 - group=1
-conv_name: conv3_1/dw 3x3 64 - group=64
-conv_name: conv3_1/sep 1x1 64 - group=1
-conv_name: conv3_2/dw 3x3 64 - group=64
-conv_name: conv3_2/sep 1x1 128 - group=1
-conv_name: conv4_1/dw 3x3 128 - group=128
-conv_name: conv4_1/sep 1x1 128 - group=1
-conv_name: conv4_2/dw 3x3 128 - group=128
-conv_name: conv4_2/sep 1x1 256 - group=1
-conv_name: conv5_1/dw 3x3 256 - group=256
-conv_name: conv5_1/sep 1x1 256 - group=1
-conv_name: conv5_2/dw 3x3 256 - group=256
-conv_name: conv5_2/sep 1x1 256 - group=1
-conv_name: conv5_3/dw 3x3 256 - group=256
-conv_name: conv5_3/sep 1x1 256 - group=1
-conv_name: conv5_4/dw 3x3 256 - group=256
-conv_name: conv5_4/sep 1x1 256 - group=1
-conv_name: conv5_5/dw 3x3 256 - group=256
-conv_name: conv5_5/sep 1x1 256 - group=1
-conv_name: conv5_6/dw 3x3 256 - group=256
-conv_name: conv5_6/sep 1x1 512 - group=1
-conv_name: conv6/dw 3x3 512 - group=512
-conv_name: conv6/sep 1x1 512 - group=1
-training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize
-{'type':'SGD','base_lr':1e-2,'max_iter':120000,'lr_policy':'multistep','power':1.0,'stepvalue':[60000,90000,300000],'regularization_type':'L1','weight_decay':1e-5,'sparse_mode':1,'display_sparsity':1000}
-{'config_name':'training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize','model_name':'mobiledetnet-0.5','dataset':'voc0712','gpus':'0','train_data':'../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb','test_data':'../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb','name_size_file':'../../caffe-jacinto/data/VOC0712/test_name_size.txt','label_map_file':'../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt','num_test_image':4952,'num_classes':21,'min_ratio':5,'max_ratio':95,
-'log_space_steps':0,'use_difficult_gt':1,'ignore_difficult_gt':0,'evaluate_difficult_gt':0,'pretrain_model':'training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel','use_image_list':0,'shuffle':0,'num_output':8,'resize_width':512,'resize_height':256,'crop_width':512,'crop_height':256,'batch_size':16,'test_batch_size':10,'caffe_cmd':'test_detection','aspect_ratios_type':1,'ssd_size':'512x256','small_objs':0,'min_dim':-1,'concat_reg_head':0,
-'fully_conv_at_end':0,'first_hd_same_op_ch':1,'ker_mbox_loc_conf':1,'base_nw_3_head':0,'reg_head_at_ds8':1,'ds_fac':32,'ds_type':'PSP','rhead_name_non_linear':0,'force_color':0,'num_intermediate':512,'use_batchnorm_mbox':1,'chop_num_heads':0}
-caffe_root = :  /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-config_param.ds_fac : 32
-config_param.stride_list : [2, 2, 2, 2, 2]
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv1  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 0, 'decay_mult': 0}]}
-conv_name: conv1 3x3 16 - group=1
-conv_name: conv2_1/dw 3x3 16 - group=16
-conv_name: conv2_1/sep 1x1 32 - group=1
-conv_name: conv2_2/dw 3x3 32 - group=32
-conv_name: conv2_2/sep 1x1 64 - group=1
-conv_name: conv3_1/dw 3x3 64 - group=64
-conv_name: conv3_1/sep 1x1 64 - group=1
-conv_name: conv3_2/dw 3x3 64 - group=64
-conv_name: conv3_2/sep 1x1 128 - group=1
-conv_name: conv4_1/dw 3x3 128 - group=128
-conv_name: conv4_1/sep 1x1 128 - group=1
-conv_name: conv4_2/dw 3x3 128 - group=128
-conv_name: conv4_2/sep 1x1 256 - group=1
-conv_name: conv5_1/dw 3x3 256 - group=256
-conv_name: conv5_1/sep 1x1 256 - group=1
-conv_name: conv5_2/dw 3x3 256 - group=256
-conv_name: conv5_2/sep 1x1 256 - group=1
-conv_name: conv5_3/dw 3x3 256 - group=256
-conv_name: conv5_3/sep 1x1 256 - group=1
-conv_name: conv5_4/dw 3x3 256 - group=256
-conv_name: conv5_4/sep 1x1 256 - group=1
-conv_name: conv5_5/dw 3x3 256 - group=256
-conv_name: conv5_5/sep 1x1 256 - group=1
-conv_name: conv5_6/dw 3x3 256 - group=256
-conv_name: conv5_6/sep 1x1 512 - group=1
-conv_name: conv6/dw 3x3 512 - group=512
-conv_name: conv6/sep 1x1 512 - group=1
-min_dim = 384
-minsizes = [19.0, 88.0, 157.0, 226.0, 295.0]
-maxsizes = [88.0, 157.0, 226.0, 295.0, 364.0]
-ARs: [[2], [2, 3], [2, 3], [2], [2]]
-training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize/train.prototxt
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 1, 'decay_mult': 1}]}
-param_conv1  {'weight_filler': {'type': 'msra'}, 'bias_term': False, 'param': [{'lr_mult': 0, 'decay_mult': 0}]}
-conv_name: conv1 3x3 16 - group=1
-conv_name: conv2_1/dw 3x3 16 - group=16
-conv_name: conv2_1/sep 1x1 32 - group=1
-conv_name: conv2_2/dw 3x3 32 - group=32
-conv_name: conv2_2/sep 1x1 64 - group=1
-conv_name: conv3_1/dw 3x3 64 - group=64
-conv_name: conv3_1/sep 1x1 64 - group=1
-conv_name: conv3_2/dw 3x3 64 - group=64
-conv_name: conv3_2/sep 1x1 128 - group=1
-conv_name: conv4_1/dw 3x3 128 - group=128
-conv_name: conv4_1/sep 1x1 128 - group=1
-conv_name: conv4_2/dw 3x3 128 - group=128
-conv_name: conv4_2/sep 1x1 256 - group=1
-conv_name: conv5_1/dw 3x3 256 - group=256
-conv_name: conv5_1/sep 1x1 256 - group=1
-conv_name: conv5_2/dw 3x3 256 - group=256
-conv_name: conv5_2/sep 1x1 256 - group=1
-conv_name: conv5_3/dw 3x3 256 - group=256
-conv_name: conv5_3/sep 1x1 256 - group=1
-conv_name: conv5_4/dw 3x3 256 - group=256
-conv_name: conv5_4/sep 1x1 256 - group=1
-conv_name: conv5_5/dw 3x3 256 - group=256
-conv_name: conv5_5/sep 1x1 256 - group=1
-conv_name: conv5_6/dw 3x3 256 - group=256
-conv_name: conv5_6/sep 1x1 512 - group=1
-conv_name: conv6/dw 3x3 512 - group=512
-conv_name: conv6/sep 1x1 512 - group=1
-I0510 14:48:29.573801  5307 caffe.cpp:902] This is NVCaffe 0.17.0 started at Thu May 10 14:48:29 2018
-I0510 14:48:29.573921  5307 caffe.cpp:904] CuDNN version: 7003
-I0510 14:48:29.573925  5307 caffe.cpp:905] CuBLAS version: 9000
-I0510 14:48:29.573927  5307 caffe.cpp:906] CUDA version: 9000
-I0510 14:48:29.573930  5307 caffe.cpp:907] CUDA driver version: 9000
-I0510 14:48:29.573932  5307 caffe.cpp:908] Arguments: 
-[0]: /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-[1]: train
-[2]: --solver=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/solver.prototxt
-[3]: --weights=../trained/image_classification/imagenet_mobilenet-0.5/initial/imagenet_mobilenet-0.5_iter_320000.caffemodel
-[4]: --gpu
-[5]: 0
-I0510 14:48:29.596494  5307 gpu_memory.cpp:105] GPUMemory::Manager initialized
-I0510 14:48:29.597261  5307 gpu_memory.cpp:107] Total memory: 11713708032, Free: 11223957504, dev_info[0]: total=11713708032 free=11223957504
-I0510 14:48:29.597268  5307 caffe.cpp:226] Using GPUs 0
-I0510 14:48:29.597745  5307 caffe.cpp:230] GPU 0: GeForce GTX 1080 Ti
-I0510 14:48:29.597784  5307 solver.cpp:41] Solver data type: FLOAT
-I0510 14:48:29.605398  5307 solver.cpp:44] Initializing solver from parameters: 
-train_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/train.prototxt"
-test_net: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/test.prototxt"
-test_iter: 619
-test_interval: 2000
-base_lr: 0.01
-display: 100
-max_iter: 120000
-lr_policy: "multistep"
-gamma: 0.1
-power: 1
-momentum: 0.9
-weight_decay: 0.0001
-snapshot: 2000
-snapshot_prefix: "training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5"
-solver_mode: GPU
-device_id: 0
-random_seed: 33
-debug_info: false
-train_state {
-  level: 0
-  stage: ""
-}
-snapshot_after_train: true
-test_initialization: true
-average_loss: 10
-stepvalue: 60000
-stepvalue: 90000
-stepvalue: 300000
-iter_size: 2
-type: "SGD"
-eval_type: "detection"
-ap_version: "11point"
-show_per_class_result: true
-I0510 14:48:29.605489  5307 solver.cpp:76] Creating training net from train_net file: training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/train.prototxt
-I0510 14:48:29.607403  5307 net.cpp:80] Initializing net from parameters: 
-name: "mobiledetnet-0.5"
-state {
-  phase: TRAIN
-  level: 0
-  stage: ""
-}
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TRAIN
-  }
-  transform_param {
-    mirror: true
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-      interp_mode: AREA
-      interp_mode: NEAREST
-      interp_mode: CUBIC
-      interp_mode: LANCZOS4
-    }
-    emit_constraint {
-      emit_type: CENTER
-    }
-    crop_h: 256
-    crop_w: 512
-    distort_param {
-      brightness_prob: 0.5
-      brightness_delta: 32
-      contrast_prob: 0.5
-      contrast_lower: 0.5
-      contrast_upper: 1.5
-      hue_prob: 0.5
-      hue_delta: 18
-      saturation_prob: 0.5
-      saturation_lower: 0.5
-      saturation_upper: 1.5
-      random_order_prob: 0
-    }
-    expand_param {
-      prob: 0.5
-      max_expand_ratio: 4
-    }
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb"
-    batch_size: 16
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-      max_sample: 1
-      max_trials: 1
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.1
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.3
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
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-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.5
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.7
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
-        min_scale: 0.3
-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
-        min_jaccard_overlap: 0.9
-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    batch_sampler {
-      sampler {
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-        max_scale: 1
-        min_aspect_ratio: 0.5
-        max_aspect_ratio: 2
-      }
-      sample_constraint {
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-      }
-      max_sample: 1
-      max_trials: 50
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
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-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
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-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
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-layer {
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-  top: "conv2_1/dw"
-}
-layer {
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-  scale_param {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-  top: "conv3_1/dw"
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-  top: "conv3_2/dw"
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-  convolution_param {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-layer {
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-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
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-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 0
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-    weight_filler {
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-    }
-    bias_filler {
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-    dilation: 1
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  top: "ctx_output1/1x1"
-}
-layer {
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-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    kernel_size: 3
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-    weight_filler {
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-    }
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-layer {
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-  bottom: "ctx_output1"
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-}
-layer {
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-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
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-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
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-  param {
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-    decay_mult: 0
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-  convolution_param {
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-layer {
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-  top: "ctx_output2/1x1"
-  batch_norm_param {
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-}
-layer {
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-  top: "ctx_output2/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
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-    decay_mult: 0.01
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-  param {
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-    decay_mult: 0
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-  convolution_param {
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-layer {
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-layer {
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-  top: "ctx_output2"
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-layer {
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-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
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-  param {
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-    decay_mult: 0
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-  convolution_param {
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-layer {
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-  top: "ctx_output3/1x1"
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-}
-layer {
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-  top: "ctx_output3/1x1"
-}
-layer {
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-  top: "ctx_output3"
-  param {
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-  }
-  param {
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-    decay_mult: 0
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-  convolution_param {
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-layer {
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-  top: "ctx_output3"
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-layer {
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-  top: "ctx_output3"
-}
-layer {
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-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
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-    decay_mult: 1
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-  param {
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-layer {
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-  top: "ctx_output4/1x1"
-  batch_norm_param {
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-  }
-}
-layer {
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-  top: "ctx_output4/1x1"
-}
-layer {
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-  top: "ctx_output4"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-  convolution_param {
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-layer {
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-  top: "ctx_output4"
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-layer {
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-  top: "ctx_output5/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-layer {
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-  top: "ctx_output5/1x1"
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-  }
-}
-layer {
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-  top: "ctx_output5/1x1"
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-layer {
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-  top: "ctx_output5"
-  param {
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-  }
-  param {
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-    decay_mult: 0
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-  top: "ctx_output5"
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-  }
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-layer {
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-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
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-  convolution_param {
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-    }
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-      value: 0
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-    dilation: 1
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-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-I0510 14:48:29.607969  5307 net.cpp:110] Using FLOAT as default forward math type
-I0510 14:48:29.607976  5307 net.cpp:116] Using FLOAT as default backward math type
-I0510 14:48:29.607981  5307 layer_factory.hpp:172] Creating layer 'data' of type 'AnnotatedData'
-I0510 14:48:29.607986  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:29.608055  5307 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0510 14:48:29.608973  5322 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0510 14:48:29.609016  5307 net.cpp:200] Created Layer data (0)
-I0510 14:48:29.609035  5307 net.cpp:542] data -> data
-I0510 14:48:29.609045  5307 net.cpp:542] data -> label
-I0510 14:48:29.609061  5307 data_reader.cpp:58] Data Reader threads: 4, out queues: 16, depth: 16
-I0510 14:48:29.609109  5307 internal_thread.cpp:19] Starting 4 internal thread(s) on device 0
-I0510 14:48:29.609990  5323 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb
-I0510 14:48:29.610841  5324 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb
-I0510 14:48:29.612040  5307 annotated_data_layer.cpp:105] output data size: 16,3,256,512
-I0510 14:48:29.612288  5307 annotated_data_layer.cpp:150] [0] Output data size: 16, 3, 256, 512
-I0510 14:48:29.612665  5325 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb
-I0510 14:48:29.613466  5326 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_trainval_lmdb
-I0510 14:48:29.613507  5307 internal_thread.cpp:19] Starting 4 internal thread(s) on device 0
-I0510 14:48:29.614493  5328 data_layer.cpp:105] [0] Parser threads: 4
-I0510 14:48:29.614506  5328 data_layer.cpp:107] [0] Transformer threads: 4
-I0510 14:48:29.615298  5307 net.cpp:260] Setting up data
-I0510 14:48:29.624570  5307 net.cpp:267] TRAIN Top shape for layer 0 'data' 16 3 256 512 (6291456)
-I0510 14:48:29.624604  5307 net.cpp:267] TRAIN Top shape for layer 0 'data' 1 1 2 8 (16)
-I0510 14:48:29.624614  5307 layer_factory.hpp:172] Creating layer 'data_data_0_split' of type 'Split'
-I0510 14:48:29.624619  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:29.624629  5307 net.cpp:200] Created Layer data_data_0_split (1)
-I0510 14:48:29.624634  5307 net.cpp:572] data_data_0_split <- data
-I0510 14:48:29.624646  5307 net.cpp:542] data_data_0_split -> data_data_0_split_0
-I0510 14:48:29.624662  5307 net.cpp:542] data_data_0_split -> data_data_0_split_1
-I0510 14:48:29.624671  5307 net.cpp:542] data_data_0_split -> data_data_0_split_2
-I0510 14:48:29.624678  5307 net.cpp:542] data_data_0_split -> data_data_0_split_3
-I0510 14:48:29.624685  5307 net.cpp:542] data_data_0_split -> data_data_0_split_4
-I0510 14:48:29.624688  5307 net.cpp:542] data_data_0_split -> data_data_0_split_5
-I0510 14:48:29.624884  5307 net.cpp:260] Setting up data_data_0_split
-I0510 14:48:29.624892  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624897  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624902  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624907  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624910  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624915  5307 net.cpp:267] TRAIN Top shape for layer 1 'data_data_0_split' 16 3 256 512 (6291456)
-I0510 14:48:29.624933  5307 layer_factory.hpp:172] Creating layer 'data/bias' of type 'Bias'
-I0510 14:48:29.624944  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:29.624961  5307 net.cpp:200] Created Layer data/bias (2)
-I0510 14:48:29.624971  5307 net.cpp:572] data/bias <- data_data_0_split_0
-I0510 14:48:29.624981  5307 net.cpp:542] data/bias -> data/bias
-I0510 14:48:29.637835  5307 net.cpp:260] Setting up data/bias
-I0510 14:48:29.637859  5307 net.cpp:267] TRAIN Top shape for layer 2 'data/bias' 16 3 256 512 (6291456)
-I0510 14:48:29.637876  5307 layer_factory.hpp:172] Creating layer 'conv1' of type 'Convolution'
-I0510 14:48:29.637883  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:29.637907  5307 net.cpp:200] Created Layer conv1 (3)
-I0510 14:48:29.637912  5307 net.cpp:572] conv1 <- data/bias
-I0510 14:48:29.637917  5307 net.cpp:542] conv1 -> conv1
-I0510 14:48:30.098809  5307 net.cpp:260] Setting up conv1
-I0510 14:48:30.098845  5307 net.cpp:267] TRAIN Top shape for layer 3 'conv1' 16 16 128 256 (8388608)
-I0510 14:48:30.098858  5307 layer_factory.hpp:172] Creating layer 'conv1/bn' of type 'BatchNorm'
-I0510 14:48:30.098865  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.098881  5307 net.cpp:200] Created Layer conv1/bn (4)
-I0510 14:48:30.098886  5307 net.cpp:572] conv1/bn <- conv1
-I0510 14:48:30.098891  5307 net.cpp:527] conv1/bn -> conv1 (in-place)
-I0510 14:48:30.099910  5307 net.cpp:260] Setting up conv1/bn
-I0510 14:48:30.099922  5307 net.cpp:267] TRAIN Top shape for layer 4 'conv1/bn' 16 16 128 256 (8388608)
-I0510 14:48:30.099934  5307 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Scale'
-I0510 14:48:30.099942  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.099951  5307 net.cpp:200] Created Layer conv1/scale (5)
-I0510 14:48:30.099956  5307 net.cpp:572] conv1/scale <- conv1
-I0510 14:48:30.099961  5307 net.cpp:527] conv1/scale -> conv1 (in-place)
-I0510 14:48:30.100003  5307 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Bias'
-I0510 14:48:30.100008  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.100152  5307 net.cpp:260] Setting up conv1/scale
-I0510 14:48:30.100162  5307 net.cpp:267] TRAIN Top shape for layer 5 'conv1/scale' 16 16 128 256 (8388608)
-I0510 14:48:30.100169  5307 layer_factory.hpp:172] Creating layer 'relu1' of type 'ReLU'
-I0510 14:48:30.100173  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.100180  5307 net.cpp:200] Created Layer relu1 (6)
-I0510 14:48:30.100184  5307 net.cpp:572] relu1 <- conv1
-I0510 14:48:30.100188  5307 net.cpp:527] relu1 -> conv1 (in-place)
-I0510 14:48:30.100204  5307 net.cpp:260] Setting up relu1
-I0510 14:48:30.100209  5307 net.cpp:267] TRAIN Top shape for layer 6 'relu1' 16 16 128 256 (8388608)
-I0510 14:48:30.100214  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw' of type 'Convolution'
-I0510 14:48:30.100217  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.100227  5307 net.cpp:200] Created Layer conv2_1/dw (7)
-I0510 14:48:30.100232  5307 net.cpp:572] conv2_1/dw <- conv1
-I0510 14:48:30.100236  5307 net.cpp:542] conv2_1/dw -> conv2_1/dw
-I0510 14:48:30.101371  5307 net.cpp:260] Setting up conv2_1/dw
-I0510 14:48:30.101382  5307 net.cpp:267] TRAIN Top shape for layer 7 'conv2_1/dw' 16 16 128 256 (8388608)
-I0510 14:48:30.101388  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.101394  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.101402  5307 net.cpp:200] Created Layer conv2_1/dw/bn (8)
-I0510 14:48:30.101408  5307 net.cpp:572] conv2_1/dw/bn <- conv2_1/dw
-I0510 14:48:30.101411  5307 net.cpp:527] conv2_1/dw/bn -> conv2_1/dw (in-place)
-I0510 14:48:30.101748  5307 net.cpp:260] Setting up conv2_1/dw/bn
-I0510 14:48:30.101757  5307 net.cpp:267] TRAIN Top shape for layer 8 'conv2_1/dw/bn' 16 16 128 256 (8388608)
-I0510 14:48:30.101766  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Scale'
-I0510 14:48:30.101773  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.101778  5307 net.cpp:200] Created Layer conv2_1/dw/scale (9)
-I0510 14:48:30.101783  5307 net.cpp:572] conv2_1/dw/scale <- conv2_1/dw
-I0510 14:48:30.101788  5307 net.cpp:527] conv2_1/dw/scale -> conv2_1/dw (in-place)
-I0510 14:48:30.101821  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Bias'
-I0510 14:48:30.101827  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.101965  5307 net.cpp:260] Setting up conv2_1/dw/scale
-I0510 14:48:30.101975  5307 net.cpp:267] TRAIN Top shape for layer 9 'conv2_1/dw/scale' 16 16 128 256 (8388608)
-I0510 14:48:30.101981  5307 layer_factory.hpp:172] Creating layer 'relu2_1/dw' of type 'ReLU'
-I0510 14:48:30.101995  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102000  5307 net.cpp:200] Created Layer relu2_1/dw (10)
-I0510 14:48:30.102005  5307 net.cpp:572] relu2_1/dw <- conv2_1/dw
-I0510 14:48:30.102008  5307 net.cpp:527] relu2_1/dw -> conv2_1/dw (in-place)
-I0510 14:48:30.102013  5307 net.cpp:260] Setting up relu2_1/dw
-I0510 14:48:30.102018  5307 net.cpp:267] TRAIN Top shape for layer 10 'relu2_1/dw' 16 16 128 256 (8388608)
-I0510 14:48:30.102022  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep' of type 'Convolution'
-I0510 14:48:30.102026  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102035  5307 net.cpp:200] Created Layer conv2_1/sep (11)
-I0510 14:48:30.102038  5307 net.cpp:572] conv2_1/sep <- conv2_1/dw
-I0510 14:48:30.102042  5307 net.cpp:542] conv2_1/sep -> conv2_1/sep
-I0510 14:48:30.102200  5307 net.cpp:260] Setting up conv2_1/sep
-I0510 14:48:30.102208  5307 net.cpp:267] TRAIN Top shape for layer 11 'conv2_1/sep' 16 32 128 256 (16777216)
-I0510 14:48:30.102216  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.102219  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102226  5307 net.cpp:200] Created Layer conv2_1/sep/bn (12)
-I0510 14:48:30.102229  5307 net.cpp:572] conv2_1/sep/bn <- conv2_1/sep
-I0510 14:48:30.102234  5307 net.cpp:527] conv2_1/sep/bn -> conv2_1/sep (in-place)
-I0510 14:48:30.102529  5307 net.cpp:260] Setting up conv2_1/sep/bn
-I0510 14:48:30.102545  5307 net.cpp:267] TRAIN Top shape for layer 12 'conv2_1/sep/bn' 16 32 128 256 (16777216)
-I0510 14:48:30.102557  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Scale'
-I0510 14:48:30.102566  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102576  5307 net.cpp:200] Created Layer conv2_1/sep/scale (13)
-I0510 14:48:30.102583  5307 net.cpp:572] conv2_1/sep/scale <- conv2_1/sep
-I0510 14:48:30.102591  5307 net.cpp:527] conv2_1/sep/scale -> conv2_1/sep (in-place)
-I0510 14:48:30.102627  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Bias'
-I0510 14:48:30.102636  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102756  5307 net.cpp:260] Setting up conv2_1/sep/scale
-I0510 14:48:30.102767  5307 net.cpp:267] TRAIN Top shape for layer 13 'conv2_1/sep/scale' 16 32 128 256 (16777216)
-I0510 14:48:30.102778  5307 layer_factory.hpp:172] Creating layer 'relu2_1/sep' of type 'ReLU'
-I0510 14:48:30.102787  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102794  5307 net.cpp:200] Created Layer relu2_1/sep (14)
-I0510 14:48:30.102802  5307 net.cpp:572] relu2_1/sep <- conv2_1/sep
-I0510 14:48:30.102810  5307 net.cpp:527] relu2_1/sep -> conv2_1/sep (in-place)
-I0510 14:48:30.102820  5307 net.cpp:260] Setting up relu2_1/sep
-I0510 14:48:30.102829  5307 net.cpp:267] TRAIN Top shape for layer 14 'relu2_1/sep' 16 32 128 256 (16777216)
-I0510 14:48:30.102838  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw' of type 'Convolution'
-I0510 14:48:30.102845  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.102857  5307 net.cpp:200] Created Layer conv2_2/dw (15)
-I0510 14:48:30.102865  5307 net.cpp:572] conv2_2/dw <- conv2_1/sep
-I0510 14:48:30.102874  5307 net.cpp:542] conv2_2/dw -> conv2_2/dw
-I0510 14:48:30.103037  5307 net.cpp:260] Setting up conv2_2/dw
-I0510 14:48:30.103050  5307 net.cpp:267] TRAIN Top shape for layer 15 'conv2_2/dw' 16 32 64 128 (4194304)
-I0510 14:48:30.103060  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.103068  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.103081  5307 net.cpp:200] Created Layer conv2_2/dw/bn (16)
-I0510 14:48:30.103094  5307 net.cpp:572] conv2_2/dw/bn <- conv2_2/dw
-I0510 14:48:30.103102  5307 net.cpp:527] conv2_2/dw/bn -> conv2_2/dw (in-place)
-I0510 14:48:30.104127  5307 net.cpp:260] Setting up conv2_2/dw/bn
-I0510 14:48:30.104146  5307 net.cpp:267] TRAIN Top shape for layer 16 'conv2_2/dw/bn' 16 32 64 128 (4194304)
-I0510 14:48:30.104158  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Scale'
-I0510 14:48:30.104167  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.104180  5307 net.cpp:200] Created Layer conv2_2/dw/scale (17)
-I0510 14:48:30.104188  5307 net.cpp:572] conv2_2/dw/scale <- conv2_2/dw
-I0510 14:48:30.104197  5307 net.cpp:527] conv2_2/dw/scale -> conv2_2/dw (in-place)
-I0510 14:48:30.104234  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Bias'
-I0510 14:48:30.104244  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.104336  5307 net.cpp:260] Setting up conv2_2/dw/scale
-I0510 14:48:30.104347  5307 net.cpp:267] TRAIN Top shape for layer 17 'conv2_2/dw/scale' 16 32 64 128 (4194304)
-I0510 14:48:30.104357  5307 layer_factory.hpp:172] Creating layer 'relu2_2/dw' of type 'ReLU'
-I0510 14:48:30.104365  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.104374  5307 net.cpp:200] Created Layer relu2_2/dw (18)
-I0510 14:48:30.104382  5307 net.cpp:572] relu2_2/dw <- conv2_2/dw
-I0510 14:48:30.104390  5307 net.cpp:527] relu2_2/dw -> conv2_2/dw (in-place)
-I0510 14:48:30.104400  5307 net.cpp:260] Setting up relu2_2/dw
-I0510 14:48:30.104409  5307 net.cpp:267] TRAIN Top shape for layer 18 'relu2_2/dw' 16 32 64 128 (4194304)
-I0510 14:48:30.104418  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep' of type 'Convolution'
-I0510 14:48:30.104425  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.104436  5307 net.cpp:200] Created Layer conv2_2/sep (19)
-I0510 14:48:30.104445  5307 net.cpp:572] conv2_2/sep <- conv2_2/dw
-I0510 14:48:30.104454  5307 net.cpp:542] conv2_2/sep -> conv2_2/sep
-I0510 14:48:30.105271  5307 net.cpp:260] Setting up conv2_2/sep
-I0510 14:48:30.105281  5307 net.cpp:267] TRAIN Top shape for layer 19 'conv2_2/sep' 16 64 64 128 (8388608)
-I0510 14:48:30.105289  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.105294  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105303  5307 net.cpp:200] Created Layer conv2_2/sep/bn (20)
-I0510 14:48:30.105306  5307 net.cpp:572] conv2_2/sep/bn <- conv2_2/sep
-I0510 14:48:30.105311  5307 net.cpp:527] conv2_2/sep/bn -> conv2_2/sep (in-place)
-I0510 14:48:30.105557  5307 net.cpp:260] Setting up conv2_2/sep/bn
-I0510 14:48:30.105564  5307 net.cpp:267] TRAIN Top shape for layer 20 'conv2_2/sep/bn' 16 64 64 128 (8388608)
-I0510 14:48:30.105572  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Scale'
-I0510 14:48:30.105576  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105582  5307 net.cpp:200] Created Layer conv2_2/sep/scale (21)
-I0510 14:48:30.105587  5307 net.cpp:572] conv2_2/sep/scale <- conv2_2/sep
-I0510 14:48:30.105590  5307 net.cpp:527] conv2_2/sep/scale -> conv2_2/sep (in-place)
-I0510 14:48:30.105618  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Bias'
-I0510 14:48:30.105623  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105701  5307 net.cpp:260] Setting up conv2_2/sep/scale
-I0510 14:48:30.105707  5307 net.cpp:267] TRAIN Top shape for layer 21 'conv2_2/sep/scale' 16 64 64 128 (8388608)
-I0510 14:48:30.105715  5307 layer_factory.hpp:172] Creating layer 'relu2_2/sep' of type 'ReLU'
-I0510 14:48:30.105718  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105731  5307 net.cpp:200] Created Layer relu2_2/sep (22)
-I0510 14:48:30.105736  5307 net.cpp:572] relu2_2/sep <- conv2_2/sep
-I0510 14:48:30.105741  5307 net.cpp:527] relu2_2/sep -> conv2_2/sep (in-place)
-I0510 14:48:30.105746  5307 net.cpp:260] Setting up relu2_2/sep
-I0510 14:48:30.105751  5307 net.cpp:267] TRAIN Top shape for layer 22 'relu2_2/sep' 16 64 64 128 (8388608)
-I0510 14:48:30.105756  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw' of type 'Convolution'
-I0510 14:48:30.105760  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.105770  5307 net.cpp:200] Created Layer conv3_1/dw (23)
-I0510 14:48:30.105774  5307 net.cpp:572] conv3_1/dw <- conv2_2/sep
-I0510 14:48:30.105778  5307 net.cpp:542] conv3_1/dw -> conv3_1/dw
-I0510 14:48:30.106595  5307 net.cpp:260] Setting up conv3_1/dw
-I0510 14:48:30.106611  5307 net.cpp:267] TRAIN Top shape for layer 23 'conv3_1/dw' 16 64 64 128 (8388608)
-I0510 14:48:30.106621  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.106629  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.106639  5307 net.cpp:200] Created Layer conv3_1/dw/bn (24)
-I0510 14:48:30.106647  5307 net.cpp:572] conv3_1/dw/bn <- conv3_1/dw
-I0510 14:48:30.106657  5307 net.cpp:527] conv3_1/dw/bn -> conv3_1/dw (in-place)
-I0510 14:48:30.106976  5307 net.cpp:260] Setting up conv3_1/dw/bn
-I0510 14:48:30.106989  5307 net.cpp:267] TRAIN Top shape for layer 24 'conv3_1/dw/bn' 16 64 64 128 (8388608)
-I0510 14:48:30.107003  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Scale'
-I0510 14:48:30.107012  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107023  5307 net.cpp:200] Created Layer conv3_1/dw/scale (25)
-I0510 14:48:30.107030  5307 net.cpp:572] conv3_1/dw/scale <- conv3_1/dw
-I0510 14:48:30.107039  5307 net.cpp:527] conv3_1/dw/scale -> conv3_1/dw (in-place)
-I0510 14:48:30.107076  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Bias'
-I0510 14:48:30.107087  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107194  5307 net.cpp:260] Setting up conv3_1/dw/scale
-I0510 14:48:30.107206  5307 net.cpp:267] TRAIN Top shape for layer 25 'conv3_1/dw/scale' 16 64 64 128 (8388608)
-I0510 14:48:30.107218  5307 layer_factory.hpp:172] Creating layer 'relu3_1/dw' of type 'ReLU'
-I0510 14:48:30.107226  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107235  5307 net.cpp:200] Created Layer relu3_1/dw (26)
-I0510 14:48:30.107244  5307 net.cpp:572] relu3_1/dw <- conv3_1/dw
-I0510 14:48:30.107251  5307 net.cpp:527] relu3_1/dw -> conv3_1/dw (in-place)
-I0510 14:48:30.107260  5307 net.cpp:260] Setting up relu3_1/dw
-I0510 14:48:30.107270  5307 net.cpp:267] TRAIN Top shape for layer 26 'relu3_1/dw' 16 64 64 128 (8388608)
-I0510 14:48:30.107278  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep' of type 'Convolution'
-I0510 14:48:30.107286  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107298  5307 net.cpp:200] Created Layer conv3_1/sep (27)
-I0510 14:48:30.107306  5307 net.cpp:572] conv3_1/sep <- conv3_1/dw
-I0510 14:48:30.107314  5307 net.cpp:542] conv3_1/sep -> conv3_1/sep
-I0510 14:48:30.107592  5307 net.cpp:260] Setting up conv3_1/sep
-I0510 14:48:30.107605  5307 net.cpp:267] TRAIN Top shape for layer 27 'conv3_1/sep' 16 64 64 128 (8388608)
-I0510 14:48:30.107615  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.107623  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107633  5307 net.cpp:200] Created Layer conv3_1/sep/bn (28)
-I0510 14:48:30.107637  5307 net.cpp:572] conv3_1/sep/bn <- conv3_1/sep
-I0510 14:48:30.107642  5307 net.cpp:527] conv3_1/sep/bn -> conv3_1/sep (in-place)
-I0510 14:48:30.107893  5307 net.cpp:260] Setting up conv3_1/sep/bn
-I0510 14:48:30.107900  5307 net.cpp:267] TRAIN Top shape for layer 28 'conv3_1/sep/bn' 16 64 64 128 (8388608)
-I0510 14:48:30.107908  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Scale'
-I0510 14:48:30.107913  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.107919  5307 net.cpp:200] Created Layer conv3_1/sep/scale (29)
-I0510 14:48:30.107923  5307 net.cpp:572] conv3_1/sep/scale <- conv3_1/sep
-I0510 14:48:30.107928  5307 net.cpp:527] conv3_1/sep/scale -> conv3_1/sep (in-place)
-I0510 14:48:30.107954  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Bias'
-I0510 14:48:30.107959  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108036  5307 net.cpp:260] Setting up conv3_1/sep/scale
-I0510 14:48:30.108042  5307 net.cpp:267] TRAIN Top shape for layer 29 'conv3_1/sep/scale' 16 64 64 128 (8388608)
-I0510 14:48:30.108048  5307 layer_factory.hpp:172] Creating layer 'relu3_1/sep' of type 'ReLU'
-I0510 14:48:30.108052  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108057  5307 net.cpp:200] Created Layer relu3_1/sep (30)
-I0510 14:48:30.108062  5307 net.cpp:572] relu3_1/sep <- conv3_1/sep
-I0510 14:48:30.108065  5307 net.cpp:527] relu3_1/sep -> conv3_1/sep (in-place)
-I0510 14:48:30.108072  5307 net.cpp:260] Setting up relu3_1/sep
-I0510 14:48:30.108078  5307 net.cpp:267] TRAIN Top shape for layer 30 'relu3_1/sep' 16 64 64 128 (8388608)
-I0510 14:48:30.108081  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw' of type 'Convolution'
-I0510 14:48:30.108086  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108093  5307 net.cpp:200] Created Layer conv3_2/dw (31)
-I0510 14:48:30.108098  5307 net.cpp:572] conv3_2/dw <- conv3_1/sep
-I0510 14:48:30.108103  5307 net.cpp:542] conv3_2/dw -> conv3_2/dw
-I0510 14:48:30.108237  5307 net.cpp:260] Setting up conv3_2/dw
-I0510 14:48:30.108245  5307 net.cpp:267] TRAIN Top shape for layer 31 'conv3_2/dw' 16 64 32 64 (2097152)
-I0510 14:48:30.108252  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.108255  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108263  5307 net.cpp:200] Created Layer conv3_2/dw/bn (32)
-I0510 14:48:30.108266  5307 net.cpp:572] conv3_2/dw/bn <- conv3_2/dw
-I0510 14:48:30.108271  5307 net.cpp:527] conv3_2/dw/bn -> conv3_2/dw (in-place)
-I0510 14:48:30.108546  5307 net.cpp:260] Setting up conv3_2/dw/bn
-I0510 14:48:30.108561  5307 net.cpp:267] TRAIN Top shape for layer 32 'conv3_2/dw/bn' 16 64 32 64 (2097152)
-I0510 14:48:30.108573  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Scale'
-I0510 14:48:30.108582  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108592  5307 net.cpp:200] Created Layer conv3_2/dw/scale (33)
-I0510 14:48:30.108598  5307 net.cpp:572] conv3_2/dw/scale <- conv3_2/dw
-I0510 14:48:30.108606  5307 net.cpp:527] conv3_2/dw/scale -> conv3_2/dw (in-place)
-I0510 14:48:30.108641  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Bias'
-I0510 14:48:30.108650  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108736  5307 net.cpp:260] Setting up conv3_2/dw/scale
-I0510 14:48:30.108747  5307 net.cpp:267] TRAIN Top shape for layer 33 'conv3_2/dw/scale' 16 64 32 64 (2097152)
-I0510 14:48:30.108757  5307 layer_factory.hpp:172] Creating layer 'relu3_2/dw' of type 'ReLU'
-I0510 14:48:30.108765  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108773  5307 net.cpp:200] Created Layer relu3_2/dw (34)
-I0510 14:48:30.108781  5307 net.cpp:572] relu3_2/dw <- conv3_2/dw
-I0510 14:48:30.108793  5307 net.cpp:527] relu3_2/dw -> conv3_2/dw (in-place)
-I0510 14:48:30.108806  5307 net.cpp:260] Setting up relu3_2/dw
-I0510 14:48:30.108815  5307 net.cpp:267] TRAIN Top shape for layer 34 'relu3_2/dw' 16 64 32 64 (2097152)
-I0510 14:48:30.108824  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep' of type 'Convolution'
-I0510 14:48:30.108830  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.108842  5307 net.cpp:200] Created Layer conv3_2/sep (35)
-I0510 14:48:30.108850  5307 net.cpp:572] conv3_2/sep <- conv3_2/dw
-I0510 14:48:30.108857  5307 net.cpp:542] conv3_2/sep -> conv3_2/sep
-I0510 14:48:30.109174  5307 net.cpp:260] Setting up conv3_2/sep
-I0510 14:48:30.109182  5307 net.cpp:267] TRAIN Top shape for layer 35 'conv3_2/sep' 16 128 32 64 (4194304)
-I0510 14:48:30.109189  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.109192  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109200  5307 net.cpp:200] Created Layer conv3_2/sep/bn (36)
-I0510 14:48:30.109203  5307 net.cpp:572] conv3_2/sep/bn <- conv3_2/sep
-I0510 14:48:30.109207  5307 net.cpp:527] conv3_2/sep/bn -> conv3_2/sep (in-place)
-I0510 14:48:30.109417  5307 net.cpp:260] Setting up conv3_2/sep/bn
-I0510 14:48:30.109424  5307 net.cpp:267] TRAIN Top shape for layer 36 'conv3_2/sep/bn' 16 128 32 64 (4194304)
-I0510 14:48:30.109431  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Scale'
-I0510 14:48:30.109436  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109441  5307 net.cpp:200] Created Layer conv3_2/sep/scale (37)
-I0510 14:48:30.109446  5307 net.cpp:572] conv3_2/sep/scale <- conv3_2/sep
-I0510 14:48:30.109449  5307 net.cpp:527] conv3_2/sep/scale -> conv3_2/sep (in-place)
-I0510 14:48:30.109475  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Bias'
-I0510 14:48:30.109480  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109545  5307 net.cpp:260] Setting up conv3_2/sep/scale
-I0510 14:48:30.109552  5307 net.cpp:267] TRAIN Top shape for layer 37 'conv3_2/sep/scale' 16 128 32 64 (4194304)
-I0510 14:48:30.109558  5307 layer_factory.hpp:172] Creating layer 'relu3_2/sep' of type 'ReLU'
-I0510 14:48:30.109563  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109568  5307 net.cpp:200] Created Layer relu3_2/sep (38)
-I0510 14:48:30.109572  5307 net.cpp:572] relu3_2/sep <- conv3_2/sep
-I0510 14:48:30.109576  5307 net.cpp:527] relu3_2/sep -> conv3_2/sep (in-place)
-I0510 14:48:30.109582  5307 net.cpp:260] Setting up relu3_2/sep
-I0510 14:48:30.109586  5307 net.cpp:267] TRAIN Top shape for layer 38 'relu3_2/sep' 16 128 32 64 (4194304)
-I0510 14:48:30.109591  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw' of type 'Convolution'
-I0510 14:48:30.109596  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109604  5307 net.cpp:200] Created Layer conv4_1/dw (39)
-I0510 14:48:30.109607  5307 net.cpp:572] conv4_1/dw <- conv3_2/sep
-I0510 14:48:30.109612  5307 net.cpp:542] conv4_1/dw -> conv4_1/dw
-I0510 14:48:30.109755  5307 net.cpp:260] Setting up conv4_1/dw
-I0510 14:48:30.109761  5307 net.cpp:267] TRAIN Top shape for layer 39 'conv4_1/dw' 16 128 32 64 (4194304)
-I0510 14:48:30.109767  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.109771  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.109777  5307 net.cpp:200] Created Layer conv4_1/dw/bn (40)
-I0510 14:48:30.109781  5307 net.cpp:572] conv4_1/dw/bn <- conv4_1/dw
-I0510 14:48:30.109786  5307 net.cpp:527] conv4_1/dw/bn -> conv4_1/dw (in-place)
-I0510 14:48:30.110059  5307 net.cpp:260] Setting up conv4_1/dw/bn
-I0510 14:48:30.110075  5307 net.cpp:267] TRAIN Top shape for layer 40 'conv4_1/dw/bn' 16 128 32 64 (4194304)
-I0510 14:48:30.110090  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Scale'
-I0510 14:48:30.110102  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.110112  5307 net.cpp:200] Created Layer conv4_1/dw/scale (41)
-I0510 14:48:30.110121  5307 net.cpp:572] conv4_1/dw/scale <- conv4_1/dw
-I0510 14:48:30.110129  5307 net.cpp:527] conv4_1/dw/scale -> conv4_1/dw (in-place)
-I0510 14:48:30.110170  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Bias'
-I0510 14:48:30.110905  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.111003  5307 net.cpp:260] Setting up conv4_1/dw/scale
-I0510 14:48:30.111017  5307 net.cpp:267] TRAIN Top shape for layer 41 'conv4_1/dw/scale' 16 128 32 64 (4194304)
-I0510 14:48:30.111029  5307 layer_factory.hpp:172] Creating layer 'relu4_1/dw' of type 'ReLU'
-I0510 14:48:30.111037  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.111047  5307 net.cpp:200] Created Layer relu4_1/dw (42)
-I0510 14:48:30.111055  5307 net.cpp:572] relu4_1/dw <- conv4_1/dw
-I0510 14:48:30.111064  5307 net.cpp:527] relu4_1/dw -> conv4_1/dw (in-place)
-I0510 14:48:30.111074  5307 net.cpp:260] Setting up relu4_1/dw
-I0510 14:48:30.111084  5307 net.cpp:267] TRAIN Top shape for layer 42 'relu4_1/dw' 16 128 32 64 (4194304)
-I0510 14:48:30.111093  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep' of type 'Convolution'
-I0510 14:48:30.111100  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.111114  5307 net.cpp:200] Created Layer conv4_1/sep (43)
-I0510 14:48:30.111122  5307 net.cpp:572] conv4_1/sep <- conv4_1/dw
-I0510 14:48:30.111131  5307 net.cpp:542] conv4_1/sep -> conv4_1/sep
-I0510 14:48:30.111766  5307 net.cpp:260] Setting up conv4_1/sep
-I0510 14:48:30.111775  5307 net.cpp:267] TRAIN Top shape for layer 43 'conv4_1/sep' 16 128 32 64 (4194304)
-I0510 14:48:30.111783  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.111786  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.111793  5307 net.cpp:200] Created Layer conv4_1/sep/bn (44)
-I0510 14:48:30.111798  5307 net.cpp:572] conv4_1/sep/bn <- conv4_1/sep
-I0510 14:48:30.111802  5307 net.cpp:527] conv4_1/sep/bn -> conv4_1/sep (in-place)
-I0510 14:48:30.112027  5307 net.cpp:260] Setting up conv4_1/sep/bn
-I0510 14:48:30.112035  5307 net.cpp:267] TRAIN Top shape for layer 44 'conv4_1/sep/bn' 16 128 32 64 (4194304)
-I0510 14:48:30.112045  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Scale'
-I0510 14:48:30.112049  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112056  5307 net.cpp:200] Created Layer conv4_1/sep/scale (45)
-I0510 14:48:30.112059  5307 net.cpp:572] conv4_1/sep/scale <- conv4_1/sep
-I0510 14:48:30.112063  5307 net.cpp:527] conv4_1/sep/scale -> conv4_1/sep (in-place)
-I0510 14:48:30.112092  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Bias'
-I0510 14:48:30.112097  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112161  5307 net.cpp:260] Setting up conv4_1/sep/scale
-I0510 14:48:30.112167  5307 net.cpp:267] TRAIN Top shape for layer 45 'conv4_1/sep/scale' 16 128 32 64 (4194304)
-I0510 14:48:30.112174  5307 layer_factory.hpp:172] Creating layer 'relu4_1/sep' of type 'ReLU'
-I0510 14:48:30.112179  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112184  5307 net.cpp:200] Created Layer relu4_1/sep (46)
-I0510 14:48:30.112187  5307 net.cpp:572] relu4_1/sep <- conv4_1/sep
-I0510 14:48:30.112191  5307 net.cpp:527] relu4_1/sep -> conv4_1/sep (in-place)
-I0510 14:48:30.112197  5307 net.cpp:260] Setting up relu4_1/sep
-I0510 14:48:30.112202  5307 net.cpp:267] TRAIN Top shape for layer 46 'relu4_1/sep' 16 128 32 64 (4194304)
-I0510 14:48:30.112215  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw' of type 'Convolution'
-I0510 14:48:30.112220  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112228  5307 net.cpp:200] Created Layer conv4_2/dw (47)
-I0510 14:48:30.112232  5307 net.cpp:572] conv4_2/dw <- conv4_1/sep
-I0510 14:48:30.112237  5307 net.cpp:542] conv4_2/dw -> conv4_2/dw
-I0510 14:48:30.112385  5307 net.cpp:260] Setting up conv4_2/dw
-I0510 14:48:30.112392  5307 net.cpp:267] TRAIN Top shape for layer 47 'conv4_2/dw' 16 128 16 32 (1048576)
-I0510 14:48:30.112399  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.112403  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112409  5307 net.cpp:200] Created Layer conv4_2/dw/bn (48)
-I0510 14:48:30.112413  5307 net.cpp:572] conv4_2/dw/bn <- conv4_2/dw
-I0510 14:48:30.112418  5307 net.cpp:527] conv4_2/dw/bn -> conv4_2/dw (in-place)
-I0510 14:48:30.112669  5307 net.cpp:260] Setting up conv4_2/dw/bn
-I0510 14:48:30.112685  5307 net.cpp:267] TRAIN Top shape for layer 48 'conv4_2/dw/bn' 16 128 16 32 (1048576)
-I0510 14:48:30.112696  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Scale'
-I0510 14:48:30.112705  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112715  5307 net.cpp:200] Created Layer conv4_2/dw/scale (49)
-I0510 14:48:30.112722  5307 net.cpp:572] conv4_2/dw/scale <- conv4_2/dw
-I0510 14:48:30.112730  5307 net.cpp:527] conv4_2/dw/scale -> conv4_2/dw (in-place)
-I0510 14:48:30.112766  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Bias'
-I0510 14:48:30.112776  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112857  5307 net.cpp:260] Setting up conv4_2/dw/scale
-I0510 14:48:30.112869  5307 net.cpp:267] TRAIN Top shape for layer 49 'conv4_2/dw/scale' 16 128 16 32 (1048576)
-I0510 14:48:30.112879  5307 layer_factory.hpp:172] Creating layer 'relu4_2/dw' of type 'ReLU'
-I0510 14:48:30.112887  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112896  5307 net.cpp:200] Created Layer relu4_2/dw (50)
-I0510 14:48:30.112905  5307 net.cpp:572] relu4_2/dw <- conv4_2/dw
-I0510 14:48:30.112912  5307 net.cpp:527] relu4_2/dw -> conv4_2/dw (in-place)
-I0510 14:48:30.112923  5307 net.cpp:260] Setting up relu4_2/dw
-I0510 14:48:30.112928  5307 net.cpp:267] TRAIN Top shape for layer 50 'relu4_2/dw' 16 128 16 32 (1048576)
-I0510 14:48:30.112934  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep' of type 'Convolution'
-I0510 14:48:30.112938  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.112948  5307 net.cpp:200] Created Layer conv4_2/sep (51)
-I0510 14:48:30.112952  5307 net.cpp:572] conv4_2/sep <- conv4_2/dw
-I0510 14:48:30.112957  5307 net.cpp:542] conv4_2/sep -> conv4_2/sep
-I0510 14:48:30.113800  5307 net.cpp:260] Setting up conv4_2/sep
-I0510 14:48:30.113813  5307 net.cpp:267] TRAIN Top shape for layer 51 'conv4_2/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.113823  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.113831  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.113842  5307 net.cpp:200] Created Layer conv4_2/sep/bn (52)
-I0510 14:48:30.113849  5307 net.cpp:572] conv4_2/sep/bn <- conv4_2/sep
-I0510 14:48:30.113857  5307 net.cpp:527] conv4_2/sep/bn -> conv4_2/sep (in-place)
-I0510 14:48:30.114123  5307 net.cpp:260] Setting up conv4_2/sep/bn
-I0510 14:48:30.114135  5307 net.cpp:267] TRAIN Top shape for layer 52 'conv4_2/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.114147  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Scale'
-I0510 14:48:30.114156  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114173  5307 net.cpp:200] Created Layer conv4_2/sep/scale (53)
-I0510 14:48:30.114181  5307 net.cpp:572] conv4_2/sep/scale <- conv4_2/sep
-I0510 14:48:30.114189  5307 net.cpp:527] conv4_2/sep/scale -> conv4_2/sep (in-place)
-I0510 14:48:30.114230  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Bias'
-I0510 14:48:30.114235  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114305  5307 net.cpp:260] Setting up conv4_2/sep/scale
-I0510 14:48:30.114310  5307 net.cpp:267] TRAIN Top shape for layer 53 'conv4_2/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.114317  5307 layer_factory.hpp:172] Creating layer 'relu4_2/sep' of type 'ReLU'
-I0510 14:48:30.114321  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114326  5307 net.cpp:200] Created Layer relu4_2/sep (54)
-I0510 14:48:30.114331  5307 net.cpp:572] relu4_2/sep <- conv4_2/sep
-I0510 14:48:30.114336  5307 net.cpp:527] relu4_2/sep -> conv4_2/sep (in-place)
-I0510 14:48:30.114341  5307 net.cpp:260] Setting up relu4_2/sep
-I0510 14:48:30.114346  5307 net.cpp:267] TRAIN Top shape for layer 54 'relu4_2/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.114349  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw' of type 'Convolution'
-I0510 14:48:30.114354  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114362  5307 net.cpp:200] Created Layer conv5_1/dw (55)
-I0510 14:48:30.114365  5307 net.cpp:572] conv5_1/dw <- conv4_2/sep
-I0510 14:48:30.114370  5307 net.cpp:542] conv5_1/dw -> conv5_1/dw
-I0510 14:48:30.114540  5307 net.cpp:260] Setting up conv5_1/dw
-I0510 14:48:30.114547  5307 net.cpp:267] TRAIN Top shape for layer 55 'conv5_1/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.114553  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.114557  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114563  5307 net.cpp:200] Created Layer conv5_1/dw/bn (56)
-I0510 14:48:30.114567  5307 net.cpp:572] conv5_1/dw/bn <- conv5_1/dw
-I0510 14:48:30.114573  5307 net.cpp:527] conv5_1/dw/bn -> conv5_1/dw (in-place)
-I0510 14:48:30.114795  5307 net.cpp:260] Setting up conv5_1/dw/bn
-I0510 14:48:30.114802  5307 net.cpp:267] TRAIN Top shape for layer 56 'conv5_1/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.114810  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Scale'
-I0510 14:48:30.114820  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114830  5307 net.cpp:200] Created Layer conv5_1/dw/scale (57)
-I0510 14:48:30.114838  5307 net.cpp:572] conv5_1/dw/scale <- conv5_1/dw
-I0510 14:48:30.114845  5307 net.cpp:527] conv5_1/dw/scale -> conv5_1/dw (in-place)
-I0510 14:48:30.114882  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Bias'
-I0510 14:48:30.114892  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.114976  5307 net.cpp:260] Setting up conv5_1/dw/scale
-I0510 14:48:30.114989  5307 net.cpp:267] TRAIN Top shape for layer 57 'conv5_1/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.114998  5307 layer_factory.hpp:172] Creating layer 'relu5_1/dw' of type 'ReLU'
-I0510 14:48:30.115006  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.115015  5307 net.cpp:200] Created Layer relu5_1/dw (58)
-I0510 14:48:30.115022  5307 net.cpp:572] relu5_1/dw <- conv5_1/dw
-I0510 14:48:30.115031  5307 net.cpp:527] relu5_1/dw -> conv5_1/dw (in-place)
-I0510 14:48:30.115041  5307 net.cpp:260] Setting up relu5_1/dw
-I0510 14:48:30.115049  5307 net.cpp:267] TRAIN Top shape for layer 58 'relu5_1/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.115057  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep' of type 'Convolution'
-I0510 14:48:30.115067  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.115084  5307 net.cpp:200] Created Layer conv5_1/sep (59)
-I0510 14:48:30.115093  5307 net.cpp:572] conv5_1/sep <- conv5_1/dw
-I0510 14:48:30.115101  5307 net.cpp:542] conv5_1/sep -> conv5_1/sep
-I0510 14:48:30.117199  5307 net.cpp:260] Setting up conv5_1/sep
-I0510 14:48:30.117218  5307 net.cpp:267] TRAIN Top shape for layer 59 'conv5_1/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.117230  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.117240  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117251  5307 net.cpp:200] Created Layer conv5_1/sep/bn (60)
-I0510 14:48:30.117260  5307 net.cpp:572] conv5_1/sep/bn <- conv5_1/sep
-I0510 14:48:30.117270  5307 net.cpp:527] conv5_1/sep/bn -> conv5_1/sep (in-place)
-I0510 14:48:30.117601  5307 net.cpp:260] Setting up conv5_1/sep/bn
-I0510 14:48:30.117615  5307 net.cpp:267] TRAIN Top shape for layer 60 'conv5_1/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.117628  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Scale'
-I0510 14:48:30.117640  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117650  5307 net.cpp:200] Created Layer conv5_1/sep/scale (61)
-I0510 14:48:30.117660  5307 net.cpp:572] conv5_1/sep/scale <- conv5_1/sep
-I0510 14:48:30.117669  5307 net.cpp:527] conv5_1/sep/scale -> conv5_1/sep (in-place)
-I0510 14:48:30.117710  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Bias'
-I0510 14:48:30.117722  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117818  5307 net.cpp:260] Setting up conv5_1/sep/scale
-I0510 14:48:30.117835  5307 net.cpp:267] TRAIN Top shape for layer 61 'conv5_1/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.117847  5307 layer_factory.hpp:172] Creating layer 'relu5_1/sep' of type 'ReLU'
-I0510 14:48:30.117853  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117861  5307 net.cpp:200] Created Layer relu5_1/sep (62)
-I0510 14:48:30.117866  5307 net.cpp:572] relu5_1/sep <- conv5_1/sep
-I0510 14:48:30.117871  5307 net.cpp:527] relu5_1/sep -> conv5_1/sep (in-place)
-I0510 14:48:30.117877  5307 net.cpp:260] Setting up relu5_1/sep
-I0510 14:48:30.117883  5307 net.cpp:267] TRAIN Top shape for layer 62 'relu5_1/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.117887  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw' of type 'Convolution'
-I0510 14:48:30.117892  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.117900  5307 net.cpp:200] Created Layer conv5_2/dw (63)
-I0510 14:48:30.117903  5307 net.cpp:572] conv5_2/dw <- conv5_1/sep
-I0510 14:48:30.117908  5307 net.cpp:542] conv5_2/dw -> conv5_2/dw
-I0510 14:48:30.118083  5307 net.cpp:260] Setting up conv5_2/dw
-I0510 14:48:30.118090  5307 net.cpp:267] TRAIN Top shape for layer 63 'conv5_2/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.118096  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.118100  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118109  5307 net.cpp:200] Created Layer conv5_2/dw/bn (64)
-I0510 14:48:30.118113  5307 net.cpp:572] conv5_2/dw/bn <- conv5_2/dw
-I0510 14:48:30.118119  5307 net.cpp:527] conv5_2/dw/bn -> conv5_2/dw (in-place)
-I0510 14:48:30.118343  5307 net.cpp:260] Setting up conv5_2/dw/bn
-I0510 14:48:30.118350  5307 net.cpp:267] TRAIN Top shape for layer 64 'conv5_2/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.118357  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Scale'
-I0510 14:48:30.118361  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118367  5307 net.cpp:200] Created Layer conv5_2/dw/scale (65)
-I0510 14:48:30.118371  5307 net.cpp:572] conv5_2/dw/scale <- conv5_2/dw
-I0510 14:48:30.118376  5307 net.cpp:527] conv5_2/dw/scale -> conv5_2/dw (in-place)
-I0510 14:48:30.118410  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Bias'
-I0510 14:48:30.118415  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118484  5307 net.cpp:260] Setting up conv5_2/dw/scale
-I0510 14:48:30.118489  5307 net.cpp:267] TRAIN Top shape for layer 65 'conv5_2/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.118496  5307 layer_factory.hpp:172] Creating layer 'relu5_2/dw' of type 'ReLU'
-I0510 14:48:30.118500  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118505  5307 net.cpp:200] Created Layer relu5_2/dw (66)
-I0510 14:48:30.118510  5307 net.cpp:572] relu5_2/dw <- conv5_2/dw
-I0510 14:48:30.118515  5307 net.cpp:527] relu5_2/dw -> conv5_2/dw (in-place)
-I0510 14:48:30.118520  5307 net.cpp:260] Setting up relu5_2/dw
-I0510 14:48:30.118525  5307 net.cpp:267] TRAIN Top shape for layer 66 'relu5_2/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.118528  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep' of type 'Convolution'
-I0510 14:48:30.118533  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.118542  5307 net.cpp:200] Created Layer conv5_2/sep (67)
-I0510 14:48:30.118546  5307 net.cpp:572] conv5_2/sep <- conv5_2/dw
-I0510 14:48:30.118551  5307 net.cpp:542] conv5_2/sep -> conv5_2/sep
-I0510 14:48:30.120138  5307 net.cpp:260] Setting up conv5_2/sep
-I0510 14:48:30.120154  5307 net.cpp:267] TRAIN Top shape for layer 67 'conv5_2/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.120165  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.120174  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120184  5307 net.cpp:200] Created Layer conv5_2/sep/bn (68)
-I0510 14:48:30.120193  5307 net.cpp:572] conv5_2/sep/bn <- conv5_2/sep
-I0510 14:48:30.120203  5307 net.cpp:527] conv5_2/sep/bn -> conv5_2/sep (in-place)
-I0510 14:48:30.120518  5307 net.cpp:260] Setting up conv5_2/sep/bn
-I0510 14:48:30.120535  5307 net.cpp:267] TRAIN Top shape for layer 68 'conv5_2/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.120548  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Scale'
-I0510 14:48:30.120555  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120565  5307 net.cpp:200] Created Layer conv5_2/sep/scale (69)
-I0510 14:48:30.120573  5307 net.cpp:572] conv5_2/sep/scale <- conv5_2/sep
-I0510 14:48:30.120581  5307 net.cpp:527] conv5_2/sep/scale -> conv5_2/sep (in-place)
-I0510 14:48:30.120617  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Bias'
-I0510 14:48:30.120626  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120719  5307 net.cpp:260] Setting up conv5_2/sep/scale
-I0510 14:48:30.120730  5307 net.cpp:267] TRAIN Top shape for layer 69 'conv5_2/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.120740  5307 layer_factory.hpp:172] Creating layer 'relu5_2/sep' of type 'ReLU'
-I0510 14:48:30.120748  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120757  5307 net.cpp:200] Created Layer relu5_2/sep (70)
-I0510 14:48:30.120764  5307 net.cpp:572] relu5_2/sep <- conv5_2/sep
-I0510 14:48:30.120772  5307 net.cpp:527] relu5_2/sep -> conv5_2/sep (in-place)
-I0510 14:48:30.120782  5307 net.cpp:260] Setting up relu5_2/sep
-I0510 14:48:30.120791  5307 net.cpp:267] TRAIN Top shape for layer 70 'relu5_2/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.120800  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw' of type 'Convolution'
-I0510 14:48:30.120807  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.120818  5307 net.cpp:200] Created Layer conv5_3/dw (71)
-I0510 14:48:30.120829  5307 net.cpp:572] conv5_3/dw <- conv5_2/sep
-I0510 14:48:30.120838  5307 net.cpp:542] conv5_3/dw -> conv5_3/dw
-I0510 14:48:30.121068  5307 net.cpp:260] Setting up conv5_3/dw
-I0510 14:48:30.121081  5307 net.cpp:267] TRAIN Top shape for layer 71 'conv5_3/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.121091  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.121099  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121109  5307 net.cpp:200] Created Layer conv5_3/dw/bn (72)
-I0510 14:48:30.121116  5307 net.cpp:572] conv5_3/dw/bn <- conv5_3/dw
-I0510 14:48:30.121125  5307 net.cpp:527] conv5_3/dw/bn -> conv5_3/dw (in-place)
-I0510 14:48:30.121392  5307 net.cpp:260] Setting up conv5_3/dw/bn
-I0510 14:48:30.121398  5307 net.cpp:267] TRAIN Top shape for layer 72 'conv5_3/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.121407  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Scale'
-I0510 14:48:30.121410  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121417  5307 net.cpp:200] Created Layer conv5_3/dw/scale (73)
-I0510 14:48:30.121420  5307 net.cpp:572] conv5_3/dw/scale <- conv5_3/dw
-I0510 14:48:30.121425  5307 net.cpp:527] conv5_3/dw/scale -> conv5_3/dw (in-place)
-I0510 14:48:30.121454  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Bias'
-I0510 14:48:30.121459  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121527  5307 net.cpp:260] Setting up conv5_3/dw/scale
-I0510 14:48:30.121533  5307 net.cpp:267] TRAIN Top shape for layer 73 'conv5_3/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.121541  5307 layer_factory.hpp:172] Creating layer 'relu5_3/dw' of type 'ReLU'
-I0510 14:48:30.121544  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121549  5307 net.cpp:200] Created Layer relu5_3/dw (74)
-I0510 14:48:30.121553  5307 net.cpp:572] relu5_3/dw <- conv5_3/dw
-I0510 14:48:30.121558  5307 net.cpp:527] relu5_3/dw -> conv5_3/dw (in-place)
-I0510 14:48:30.121565  5307 net.cpp:260] Setting up relu5_3/dw
-I0510 14:48:30.121570  5307 net.cpp:267] TRAIN Top shape for layer 74 'relu5_3/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.121574  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep' of type 'Convolution'
-I0510 14:48:30.121578  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.121587  5307 net.cpp:200] Created Layer conv5_3/sep (75)
-I0510 14:48:30.121589  5307 net.cpp:572] conv5_3/sep <- conv5_3/dw
-I0510 14:48:30.121594  5307 net.cpp:542] conv5_3/sep -> conv5_3/sep
-I0510 14:48:30.123428  5307 net.cpp:260] Setting up conv5_3/sep
-I0510 14:48:30.123436  5307 net.cpp:267] TRAIN Top shape for layer 75 'conv5_3/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.123442  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.123446  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123452  5307 net.cpp:200] Created Layer conv5_3/sep/bn (76)
-I0510 14:48:30.123456  5307 net.cpp:572] conv5_3/sep/bn <- conv5_3/sep
-I0510 14:48:30.123461  5307 net.cpp:527] conv5_3/sep/bn -> conv5_3/sep (in-place)
-I0510 14:48:30.123687  5307 net.cpp:260] Setting up conv5_3/sep/bn
-I0510 14:48:30.123692  5307 net.cpp:267] TRAIN Top shape for layer 76 'conv5_3/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.123700  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Scale'
-I0510 14:48:30.123703  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123711  5307 net.cpp:200] Created Layer conv5_3/sep/scale (77)
-I0510 14:48:30.123715  5307 net.cpp:572] conv5_3/sep/scale <- conv5_3/sep
-I0510 14:48:30.123720  5307 net.cpp:527] conv5_3/sep/scale -> conv5_3/sep (in-place)
-I0510 14:48:30.123749  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Bias'
-I0510 14:48:30.123754  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123829  5307 net.cpp:260] Setting up conv5_3/sep/scale
-I0510 14:48:30.123836  5307 net.cpp:267] TRAIN Top shape for layer 77 'conv5_3/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.123842  5307 layer_factory.hpp:172] Creating layer 'relu5_3/sep' of type 'ReLU'
-I0510 14:48:30.123847  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123852  5307 net.cpp:200] Created Layer relu5_3/sep (78)
-I0510 14:48:30.123855  5307 net.cpp:572] relu5_3/sep <- conv5_3/sep
-I0510 14:48:30.123859  5307 net.cpp:527] relu5_3/sep -> conv5_3/sep (in-place)
-I0510 14:48:30.123865  5307 net.cpp:260] Setting up relu5_3/sep
-I0510 14:48:30.123870  5307 net.cpp:267] TRAIN Top shape for layer 78 'relu5_3/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.123874  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw' of type 'Convolution'
-I0510 14:48:30.123878  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.123886  5307 net.cpp:200] Created Layer conv5_4/dw (79)
-I0510 14:48:30.123890  5307 net.cpp:572] conv5_4/dw <- conv5_3/sep
-I0510 14:48:30.123894  5307 net.cpp:542] conv5_4/dw -> conv5_4/dw
-I0510 14:48:30.124126  5307 net.cpp:260] Setting up conv5_4/dw
-I0510 14:48:30.124142  5307 net.cpp:267] TRAIN Top shape for layer 79 'conv5_4/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.124152  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.124161  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124172  5307 net.cpp:200] Created Layer conv5_4/dw/bn (80)
-I0510 14:48:30.124181  5307 net.cpp:572] conv5_4/dw/bn <- conv5_4/dw
-I0510 14:48:30.124189  5307 net.cpp:527] conv5_4/dw/bn -> conv5_4/dw (in-place)
-I0510 14:48:30.124495  5307 net.cpp:260] Setting up conv5_4/dw/bn
-I0510 14:48:30.124506  5307 net.cpp:267] TRAIN Top shape for layer 80 'conv5_4/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.124517  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Scale'
-I0510 14:48:30.124533  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124545  5307 net.cpp:200] Created Layer conv5_4/dw/scale (81)
-I0510 14:48:30.124554  5307 net.cpp:572] conv5_4/dw/scale <- conv5_4/dw
-I0510 14:48:30.124563  5307 net.cpp:527] conv5_4/dw/scale -> conv5_4/dw (in-place)
-I0510 14:48:30.124601  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Bias'
-I0510 14:48:30.124611  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124696  5307 net.cpp:260] Setting up conv5_4/dw/scale
-I0510 14:48:30.124706  5307 net.cpp:267] TRAIN Top shape for layer 81 'conv5_4/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.124716  5307 layer_factory.hpp:172] Creating layer 'relu5_4/dw' of type 'ReLU'
-I0510 14:48:30.124724  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124732  5307 net.cpp:200] Created Layer relu5_4/dw (82)
-I0510 14:48:30.124740  5307 net.cpp:572] relu5_4/dw <- conv5_4/dw
-I0510 14:48:30.124748  5307 net.cpp:527] relu5_4/dw -> conv5_4/dw (in-place)
-I0510 14:48:30.124758  5307 net.cpp:260] Setting up relu5_4/dw
-I0510 14:48:30.124766  5307 net.cpp:267] TRAIN Top shape for layer 82 'relu5_4/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.124774  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep' of type 'Convolution'
-I0510 14:48:30.124783  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.124794  5307 net.cpp:200] Created Layer conv5_4/sep (83)
-I0510 14:48:30.124802  5307 net.cpp:572] conv5_4/sep <- conv5_4/dw
-I0510 14:48:30.124810  5307 net.cpp:542] conv5_4/sep -> conv5_4/sep
-I0510 14:48:30.128613  5307 net.cpp:260] Setting up conv5_4/sep
-I0510 14:48:30.128695  5307 net.cpp:267] TRAIN Top shape for layer 83 'conv5_4/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.128736  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.128757  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.128780  5307 net.cpp:200] Created Layer conv5_4/sep/bn (84)
-I0510 14:48:30.128794  5307 net.cpp:572] conv5_4/sep/bn <- conv5_4/sep
-I0510 14:48:30.128809  5307 net.cpp:527] conv5_4/sep/bn -> conv5_4/sep (in-place)
-I0510 14:48:30.129273  5307 net.cpp:260] Setting up conv5_4/sep/bn
-I0510 14:48:30.129310  5307 net.cpp:267] TRAIN Top shape for layer 84 'conv5_4/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.129335  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Scale'
-I0510 14:48:30.129354  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.129376  5307 net.cpp:200] Created Layer conv5_4/sep/scale (85)
-I0510 14:48:30.129393  5307 net.cpp:572] conv5_4/sep/scale <- conv5_4/sep
-I0510 14:48:30.129410  5307 net.cpp:527] conv5_4/sep/scale -> conv5_4/sep (in-place)
-I0510 14:48:30.129469  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Bias'
-I0510 14:48:30.129492  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.129631  5307 net.cpp:260] Setting up conv5_4/sep/scale
-I0510 14:48:30.129653  5307 net.cpp:267] TRAIN Top shape for layer 85 'conv5_4/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.129673  5307 layer_factory.hpp:172] Creating layer 'relu5_4/sep' of type 'ReLU'
-I0510 14:48:30.129693  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.129714  5307 net.cpp:200] Created Layer relu5_4/sep (86)
-I0510 14:48:30.129737  5307 net.cpp:572] relu5_4/sep <- conv5_4/sep
-I0510 14:48:30.129758  5307 net.cpp:527] relu5_4/sep -> conv5_4/sep (in-place)
-I0510 14:48:30.129781  5307 net.cpp:260] Setting up relu5_4/sep
-I0510 14:48:30.129801  5307 net.cpp:267] TRAIN Top shape for layer 86 'relu5_4/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.129820  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw' of type 'Convolution'
-I0510 14:48:30.129839  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.129868  5307 net.cpp:200] Created Layer conv5_5/dw (87)
-I0510 14:48:30.129887  5307 net.cpp:572] conv5_5/dw <- conv5_4/sep
-I0510 14:48:30.129905  5307 net.cpp:542] conv5_5/dw -> conv5_5/dw
-I0510 14:48:30.130306  5307 net.cpp:260] Setting up conv5_5/dw
-I0510 14:48:30.130342  5307 net.cpp:267] TRAIN Top shape for layer 87 'conv5_5/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.130373  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.130393  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.130414  5307 net.cpp:200] Created Layer conv5_5/dw/bn (88)
-I0510 14:48:30.130434  5307 net.cpp:572] conv5_5/dw/bn <- conv5_5/dw
-I0510 14:48:30.130450  5307 net.cpp:527] conv5_5/dw/bn -> conv5_5/dw (in-place)
-I0510 14:48:30.130820  5307 net.cpp:260] Setting up conv5_5/dw/bn
-I0510 14:48:30.130844  5307 net.cpp:267] TRAIN Top shape for layer 88 'conv5_5/dw/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.130873  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Scale'
-I0510 14:48:30.130889  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.130909  5307 net.cpp:200] Created Layer conv5_5/dw/scale (89)
-I0510 14:48:30.130926  5307 net.cpp:572] conv5_5/dw/scale <- conv5_5/dw
-I0510 14:48:30.130942  5307 net.cpp:527] conv5_5/dw/scale -> conv5_5/dw (in-place)
-I0510 14:48:30.130995  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Bias'
-I0510 14:48:30.131014  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.131129  5307 net.cpp:260] Setting up conv5_5/dw/scale
-I0510 14:48:30.131156  5307 net.cpp:267] TRAIN Top shape for layer 89 'conv5_5/dw/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.131183  5307 layer_factory.hpp:172] Creating layer 'relu5_5/dw' of type 'ReLU'
-I0510 14:48:30.131199  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.131216  5307 net.cpp:200] Created Layer relu5_5/dw (90)
-I0510 14:48:30.131229  5307 net.cpp:572] relu5_5/dw <- conv5_5/dw
-I0510 14:48:30.131244  5307 net.cpp:527] relu5_5/dw -> conv5_5/dw (in-place)
-I0510 14:48:30.131261  5307 net.cpp:260] Setting up relu5_5/dw
-I0510 14:48:30.131278  5307 net.cpp:267] TRAIN Top shape for layer 90 'relu5_5/dw' 16 256 16 32 (2097152)
-I0510 14:48:30.131291  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep' of type 'Convolution'
-I0510 14:48:30.131305  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.131325  5307 net.cpp:200] Created Layer conv5_5/sep (91)
-I0510 14:48:30.131340  5307 net.cpp:572] conv5_5/sep <- conv5_5/dw
-I0510 14:48:30.131356  5307 net.cpp:542] conv5_5/sep -> conv5_5/sep
-I0510 14:48:30.133545  5307 net.cpp:260] Setting up conv5_5/sep
-I0510 14:48:30.133577  5307 net.cpp:267] TRAIN Top shape for layer 91 'conv5_5/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.133596  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.133611  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.133628  5307 net.cpp:200] Created Layer conv5_5/sep/bn (92)
-I0510 14:48:30.133644  5307 net.cpp:572] conv5_5/sep/bn <- conv5_5/sep
-I0510 14:48:30.133661  5307 net.cpp:527] conv5_5/sep/bn -> conv5_5/sep (in-place)
-I0510 14:48:30.134043  5307 net.cpp:260] Setting up conv5_5/sep/bn
-I0510 14:48:30.134069  5307 net.cpp:267] TRAIN Top shape for layer 92 'conv5_5/sep/bn' 16 256 16 32 (2097152)
-I0510 14:48:30.134088  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Scale'
-I0510 14:48:30.134104  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134121  5307 net.cpp:200] Created Layer conv5_5/sep/scale (93)
-I0510 14:48:30.134137  5307 net.cpp:572] conv5_5/sep/scale <- conv5_5/sep
-I0510 14:48:30.134155  5307 net.cpp:527] conv5_5/sep/scale -> conv5_5/sep (in-place)
-I0510 14:48:30.134205  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Bias'
-I0510 14:48:30.134222  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134336  5307 net.cpp:260] Setting up conv5_5/sep/scale
-I0510 14:48:30.134356  5307 net.cpp:267] TRAIN Top shape for layer 93 'conv5_5/sep/scale' 16 256 16 32 (2097152)
-I0510 14:48:30.134379  5307 layer_factory.hpp:172] Creating layer 'relu5_5/sep' of type 'ReLU'
-I0510 14:48:30.134397  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134414  5307 net.cpp:200] Created Layer relu5_5/sep (94)
-I0510 14:48:30.134429  5307 net.cpp:572] relu5_5/sep <- conv5_5/sep
-I0510 14:48:30.134443  5307 net.cpp:527] relu5_5/sep -> conv5_5/sep (in-place)
-I0510 14:48:30.134460  5307 net.cpp:260] Setting up relu5_5/sep
-I0510 14:48:30.134475  5307 net.cpp:267] TRAIN Top shape for layer 94 'relu5_5/sep' 16 256 16 32 (2097152)
-I0510 14:48:30.134490  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep_relu5_5/sep_0_split' of type 'Split'
-I0510 14:48:30.134505  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134519  5307 net.cpp:200] Created Layer conv5_5/sep_relu5_5/sep_0_split (95)
-I0510 14:48:30.134533  5307 net.cpp:572] conv5_5/sep_relu5_5/sep_0_split <- conv5_5/sep
-I0510 14:48:30.134548  5307 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_0
-I0510 14:48:30.134565  5307 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_1
-I0510 14:48:30.134613  5307 net.cpp:260] Setting up conv5_5/sep_relu5_5/sep_0_split
-I0510 14:48:30.134639  5307 net.cpp:267] TRAIN Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 16 256 16 32 (2097152)
-I0510 14:48:30.134663  5307 net.cpp:267] TRAIN Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 16 256 16 32 (2097152)
-I0510 14:48:30.134680  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw' of type 'Convolution'
-I0510 14:48:30.134696  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.134718  5307 net.cpp:200] Created Layer conv5_6/dw (96)
-I0510 14:48:30.134734  5307 net.cpp:572] conv5_6/dw <- conv5_5/sep_relu5_5/sep_0_split_0
-I0510 14:48:30.134749  5307 net.cpp:542] conv5_6/dw -> conv5_6/dw
-I0510 14:48:30.135025  5307 net.cpp:260] Setting up conv5_6/dw
-I0510 14:48:30.135047  5307 net.cpp:267] TRAIN Top shape for layer 96 'conv5_6/dw' 16 256 8 16 (524288)
-I0510 14:48:30.135064  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.135078  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135095  5307 net.cpp:200] Created Layer conv5_6/dw/bn (97)
-I0510 14:48:30.135114  5307 net.cpp:572] conv5_6/dw/bn <- conv5_6/dw
-I0510 14:48:30.135130  5307 net.cpp:527] conv5_6/dw/bn -> conv5_6/dw (in-place)
-I0510 14:48:30.135478  5307 net.cpp:260] Setting up conv5_6/dw/bn
-I0510 14:48:30.135500  5307 net.cpp:267] TRAIN Top shape for layer 97 'conv5_6/dw/bn' 16 256 8 16 (524288)
-I0510 14:48:30.135519  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Scale'
-I0510 14:48:30.135534  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135550  5307 net.cpp:200] Created Layer conv5_6/dw/scale (98)
-I0510 14:48:30.135568  5307 net.cpp:572] conv5_6/dw/scale <- conv5_6/dw
-I0510 14:48:30.135586  5307 net.cpp:527] conv5_6/dw/scale -> conv5_6/dw (in-place)
-I0510 14:48:30.135637  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Bias'
-I0510 14:48:30.135654  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135759  5307 net.cpp:260] Setting up conv5_6/dw/scale
-I0510 14:48:30.135778  5307 net.cpp:267] TRAIN Top shape for layer 98 'conv5_6/dw/scale' 16 256 8 16 (524288)
-I0510 14:48:30.135797  5307 layer_factory.hpp:172] Creating layer 'relu5_6/dw' of type 'ReLU'
-I0510 14:48:30.135814  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135830  5307 net.cpp:200] Created Layer relu5_6/dw (99)
-I0510 14:48:30.135845  5307 net.cpp:572] relu5_6/dw <- conv5_6/dw
-I0510 14:48:30.135860  5307 net.cpp:527] relu5_6/dw -> conv5_6/dw (in-place)
-I0510 14:48:30.135876  5307 net.cpp:260] Setting up relu5_6/dw
-I0510 14:48:30.135891  5307 net.cpp:267] TRAIN Top shape for layer 99 'relu5_6/dw' 16 256 8 16 (524288)
-I0510 14:48:30.135906  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep' of type 'Convolution'
-I0510 14:48:30.135921  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.135939  5307 net.cpp:200] Created Layer conv5_6/sep (100)
-I0510 14:48:30.135953  5307 net.cpp:572] conv5_6/sep <- conv5_6/dw
-I0510 14:48:30.135967  5307 net.cpp:542] conv5_6/sep -> conv5_6/sep
-I0510 14:48:30.140096  5307 net.cpp:260] Setting up conv5_6/sep
-I0510 14:48:30.140142  5307 net.cpp:267] TRAIN Top shape for layer 100 'conv5_6/sep' 16 512 8 16 (1048576)
-I0510 14:48:30.140163  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.140183  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.140204  5307 net.cpp:200] Created Layer conv5_6/sep/bn (101)
-I0510 14:48:30.140221  5307 net.cpp:572] conv5_6/sep/bn <- conv5_6/sep
-I0510 14:48:30.140239  5307 net.cpp:527] conv5_6/sep/bn -> conv5_6/sep (in-place)
-I0510 14:48:30.140622  5307 net.cpp:260] Setting up conv5_6/sep/bn
-I0510 14:48:30.140650  5307 net.cpp:267] TRAIN Top shape for layer 101 'conv5_6/sep/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.140676  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Scale'
-I0510 14:48:30.140700  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.140722  5307 net.cpp:200] Created Layer conv5_6/sep/scale (102)
-I0510 14:48:30.140741  5307 net.cpp:572] conv5_6/sep/scale <- conv5_6/sep
-I0510 14:48:30.140758  5307 net.cpp:527] conv5_6/sep/scale -> conv5_6/sep (in-place)
-I0510 14:48:30.140813  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Bias'
-I0510 14:48:30.140830  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.140949  5307 net.cpp:260] Setting up conv5_6/sep/scale
-I0510 14:48:30.140969  5307 net.cpp:267] TRAIN Top shape for layer 102 'conv5_6/sep/scale' 16 512 8 16 (1048576)
-I0510 14:48:30.140987  5307 layer_factory.hpp:172] Creating layer 'relu5_6/sep' of type 'ReLU'
-I0510 14:48:30.141003  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.141021  5307 net.cpp:200] Created Layer relu5_6/sep (103)
-I0510 14:48:30.141036  5307 net.cpp:572] relu5_6/sep <- conv5_6/sep
-I0510 14:48:30.141052  5307 net.cpp:527] relu5_6/sep -> conv5_6/sep (in-place)
-I0510 14:48:30.141070  5307 net.cpp:260] Setting up relu5_6/sep
-I0510 14:48:30.141088  5307 net.cpp:267] TRAIN Top shape for layer 103 'relu5_6/sep' 16 512 8 16 (1048576)
-I0510 14:48:30.141103  5307 layer_factory.hpp:172] Creating layer 'conv6/dw' of type 'Convolution'
-I0510 14:48:30.141118  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.141139  5307 net.cpp:200] Created Layer conv6/dw (104)
-I0510 14:48:30.141163  5307 net.cpp:572] conv6/dw <- conv5_6/sep
-I0510 14:48:30.141181  5307 net.cpp:542] conv6/dw -> conv6/dw
-I0510 14:48:30.141530  5307 net.cpp:260] Setting up conv6/dw
-I0510 14:48:30.141553  5307 net.cpp:267] TRAIN Top shape for layer 104 'conv6/dw' 16 512 8 16 (1048576)
-I0510 14:48:30.141571  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.141587  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.141602  5307 net.cpp:200] Created Layer conv6/dw/bn (105)
-I0510 14:48:30.141618  5307 net.cpp:572] conv6/dw/bn <- conv6/dw
-I0510 14:48:30.141631  5307 net.cpp:527] conv6/dw/bn -> conv6/dw (in-place)
-I0510 14:48:30.141988  5307 net.cpp:260] Setting up conv6/dw/bn
-I0510 14:48:30.142010  5307 net.cpp:267] TRAIN Top shape for layer 105 'conv6/dw/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.142029  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Scale'
-I0510 14:48:30.142045  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.142060  5307 net.cpp:200] Created Layer conv6/dw/scale (106)
-I0510 14:48:30.142076  5307 net.cpp:572] conv6/dw/scale <- conv6/dw
-I0510 14:48:30.142089  5307 net.cpp:527] conv6/dw/scale -> conv6/dw (in-place)
-I0510 14:48:30.142138  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Bias'
-I0510 14:48:30.142154  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.142272  5307 net.cpp:260] Setting up conv6/dw/scale
-I0510 14:48:30.142292  5307 net.cpp:267] TRAIN Top shape for layer 106 'conv6/dw/scale' 16 512 8 16 (1048576)
-I0510 14:48:30.142313  5307 layer_factory.hpp:172] Creating layer 'relu6/dw' of type 'ReLU'
-I0510 14:48:30.142328  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.142344  5307 net.cpp:200] Created Layer relu6/dw (107)
-I0510 14:48:30.142359  5307 net.cpp:572] relu6/dw <- conv6/dw
-I0510 14:48:30.142375  5307 net.cpp:527] relu6/dw -> conv6/dw (in-place)
-I0510 14:48:30.142392  5307 net.cpp:260] Setting up relu6/dw
-I0510 14:48:30.142410  5307 net.cpp:267] TRAIN Top shape for layer 107 'relu6/dw' 16 512 8 16 (1048576)
-I0510 14:48:30.142429  5307 layer_factory.hpp:172] Creating layer 'conv6/sep' of type 'Convolution'
-I0510 14:48:30.142452  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.142474  5307 net.cpp:200] Created Layer conv6/sep (108)
-I0510 14:48:30.142490  5307 net.cpp:572] conv6/sep <- conv6/dw
-I0510 14:48:30.142504  5307 net.cpp:542] conv6/sep -> conv6/sep
-I0510 14:48:30.148224  5307 net.cpp:260] Setting up conv6/sep
-I0510 14:48:30.148257  5307 net.cpp:267] TRAIN Top shape for layer 108 'conv6/sep' 16 512 8 16 (1048576)
-I0510 14:48:30.148267  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.148273  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148284  5307 net.cpp:200] Created Layer conv6/sep/bn (109)
-I0510 14:48:30.148300  5307 net.cpp:572] conv6/sep/bn <- conv6/sep
-I0510 14:48:30.148313  5307 net.cpp:527] conv6/sep/bn -> conv6/sep (in-place)
-I0510 14:48:30.148607  5307 net.cpp:260] Setting up conv6/sep/bn
-I0510 14:48:30.148614  5307 net.cpp:267] TRAIN Top shape for layer 109 'conv6/sep/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.148622  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Scale'
-I0510 14:48:30.148633  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148646  5307 net.cpp:200] Created Layer conv6/sep/scale (110)
-I0510 14:48:30.148651  5307 net.cpp:572] conv6/sep/scale <- conv6/sep
-I0510 14:48:30.148655  5307 net.cpp:527] conv6/sep/scale -> conv6/sep (in-place)
-I0510 14:48:30.148696  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Bias'
-I0510 14:48:30.148701  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148789  5307 net.cpp:260] Setting up conv6/sep/scale
-I0510 14:48:30.148797  5307 net.cpp:267] TRAIN Top shape for layer 110 'conv6/sep/scale' 16 512 8 16 (1048576)
-I0510 14:48:30.148802  5307 layer_factory.hpp:172] Creating layer 'relu6/sep' of type 'ReLU'
-I0510 14:48:30.148813  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148820  5307 net.cpp:200] Created Layer relu6/sep (111)
-I0510 14:48:30.148829  5307 net.cpp:572] relu6/sep <- conv6/sep
-I0510 14:48:30.148834  5307 net.cpp:527] relu6/sep -> conv6/sep (in-place)
-I0510 14:48:30.148846  5307 net.cpp:260] Setting up relu6/sep
-I0510 14:48:30.148852  5307 net.cpp:267] TRAIN Top shape for layer 111 'relu6/sep' 16 512 8 16 (1048576)
-I0510 14:48:30.148861  5307 layer_factory.hpp:172] Creating layer 'conv6/sep_relu6/sep_0_split' of type 'Split'
-I0510 14:48:30.148867  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.148877  5307 net.cpp:200] Created Layer conv6/sep_relu6/sep_0_split (112)
-I0510 14:48:30.148890  5307 net.cpp:572] conv6/sep_relu6/sep_0_split <- conv6/sep
-I0510 14:48:30.148902  5307 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_0
-I0510 14:48:30.148916  5307 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_1
-I0510 14:48:30.148953  5307 net.cpp:260] Setting up conv6/sep_relu6/sep_0_split
-I0510 14:48:30.148969  5307 net.cpp:267] TRAIN Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.148983  5307 net.cpp:267] TRAIN Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.148994  5307 layer_factory.hpp:172] Creating layer 'pool6' of type 'Pooling'
-I0510 14:48:30.149006  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149024  5307 net.cpp:200] Created Layer pool6 (113)
-I0510 14:48:30.149036  5307 net.cpp:572] pool6 <- conv6/sep_relu6/sep_0_split_0
-I0510 14:48:30.149049  5307 net.cpp:542] pool6 -> pool6
-I0510 14:48:30.149118  5307 net.cpp:260] Setting up pool6
-I0510 14:48:30.149134  5307 net.cpp:267] TRAIN Top shape for layer 113 'pool6' 16 512 5 9 (368640)
-I0510 14:48:30.149150  5307 layer_factory.hpp:172] Creating layer 'pool6_pool6_0_split' of type 'Split'
-I0510 14:48:30.149171  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149184  5307 net.cpp:200] Created Layer pool6_pool6_0_split (114)
-I0510 14:48:30.149196  5307 net.cpp:572] pool6_pool6_0_split <- pool6
-I0510 14:48:30.149209  5307 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_0
-I0510 14:48:30.149220  5307 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_1
-I0510 14:48:30.149258  5307 net.cpp:260] Setting up pool6_pool6_0_split
-I0510 14:48:30.149273  5307 net.cpp:267] TRAIN Top shape for layer 114 'pool6_pool6_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.149286  5307 net.cpp:267] TRAIN Top shape for layer 114 'pool6_pool6_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.149297  5307 layer_factory.hpp:172] Creating layer 'pool7' of type 'Pooling'
-I0510 14:48:30.149302  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149309  5307 net.cpp:200] Created Layer pool7 (115)
-I0510 14:48:30.149318  5307 net.cpp:572] pool7 <- pool6_pool6_0_split_0
-I0510 14:48:30.149324  5307 net.cpp:542] pool7 -> pool7
-I0510 14:48:30.149363  5307 net.cpp:260] Setting up pool7
-I0510 14:48:30.149369  5307 net.cpp:267] TRAIN Top shape for layer 115 'pool7' 16 512 3 5 (122880)
-I0510 14:48:30.149379  5307 layer_factory.hpp:172] Creating layer 'pool7_pool7_0_split' of type 'Split'
-I0510 14:48:30.149384  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149394  5307 net.cpp:200] Created Layer pool7_pool7_0_split (116)
-I0510 14:48:30.149399  5307 net.cpp:572] pool7_pool7_0_split <- pool7
-I0510 14:48:30.149408  5307 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_0
-I0510 14:48:30.149418  5307 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_1
-I0510 14:48:30.149449  5307 net.cpp:260] Setting up pool7_pool7_0_split
-I0510 14:48:30.149456  5307 net.cpp:267] TRAIN Top shape for layer 116 'pool7_pool7_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.149466  5307 net.cpp:267] TRAIN Top shape for layer 116 'pool7_pool7_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.149471  5307 layer_factory.hpp:172] Creating layer 'pool8' of type 'Pooling'
-I0510 14:48:30.149479  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149487  5307 net.cpp:200] Created Layer pool8 (117)
-I0510 14:48:30.149495  5307 net.cpp:572] pool8 <- pool7_pool7_0_split_0
-I0510 14:48:30.149500  5307 net.cpp:542] pool8 -> pool8
-I0510 14:48:30.149540  5307 net.cpp:260] Setting up pool8
-I0510 14:48:30.149546  5307 net.cpp:267] TRAIN Top shape for layer 117 'pool8' 16 512 3 5 (122880)
-I0510 14:48:30.149556  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1' of type 'Convolution'
-I0510 14:48:30.149562  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.149576  5307 net.cpp:200] Created Layer ctx_output1/1x1 (118)
-I0510 14:48:30.149581  5307 net.cpp:572] ctx_output1/1x1 <- conv5_5/sep_relu5_5/sep_0_split_1
-I0510 14:48:30.149591  5307 net.cpp:542] ctx_output1/1x1 -> ctx_output1/1x1
-I0510 14:48:30.153045  5307 net.cpp:260] Setting up ctx_output1/1x1
-I0510 14:48:30.153059  5307 net.cpp:267] TRAIN Top shape for layer 118 'ctx_output1/1x1' 16 512 16 32 (4194304)
-I0510 14:48:30.153066  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.153079  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.153091  5307 net.cpp:200] Created Layer ctx_output1/1x1/bn (119)
-I0510 14:48:30.153097  5307 net.cpp:572] ctx_output1/1x1/bn <- ctx_output1/1x1
-I0510 14:48:30.153102  5307 net.cpp:527] ctx_output1/1x1/bn -> ctx_output1/1x1 (in-place)
-I0510 14:48:30.153360  5307 net.cpp:260] Setting up ctx_output1/1x1/bn
-I0510 14:48:30.153368  5307 net.cpp:267] TRAIN Top shape for layer 119 'ctx_output1/1x1/bn' 16 512 16 32 (4194304)
-I0510 14:48:30.153378  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/relu' of type 'ReLU'
-I0510 14:48:30.153395  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.153403  5307 net.cpp:200] Created Layer ctx_output1/1x1/relu (120)
-I0510 14:48:30.153412  5307 net.cpp:572] ctx_output1/1x1/relu <- ctx_output1/1x1
-I0510 14:48:30.153419  5307 net.cpp:527] ctx_output1/1x1/relu -> ctx_output1/1x1 (in-place)
-I0510 14:48:30.153429  5307 net.cpp:260] Setting up ctx_output1/1x1/relu
-I0510 14:48:30.153435  5307 net.cpp:267] TRAIN Top shape for layer 120 'ctx_output1/1x1/relu' 16 512 16 32 (4194304)
-I0510 14:48:30.153445  5307 layer_factory.hpp:172] Creating layer 'ctx_output1' of type 'Convolution'
-I0510 14:48:30.153450  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.153465  5307 net.cpp:200] Created Layer ctx_output1 (121)
-I0510 14:48:30.153470  5307 net.cpp:572] ctx_output1 <- ctx_output1/1x1
-I0510 14:48:30.153475  5307 net.cpp:542] ctx_output1 -> ctx_output1
-I0510 14:48:30.153739  5307 net.cpp:260] Setting up ctx_output1
-I0510 14:48:30.153748  5307 net.cpp:267] TRAIN Top shape for layer 121 'ctx_output1' 16 512 16 32 (4194304)
-I0510 14:48:30.153754  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/bn' of type 'BatchNorm'
-I0510 14:48:30.153764  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.153772  5307 net.cpp:200] Created Layer ctx_output1/bn (122)
-I0510 14:48:30.153781  5307 net.cpp:572] ctx_output1/bn <- ctx_output1
-I0510 14:48:30.153787  5307 net.cpp:527] ctx_output1/bn -> ctx_output1 (in-place)
-I0510 14:48:30.154044  5307 net.cpp:260] Setting up ctx_output1/bn
-I0510 14:48:30.154052  5307 net.cpp:267] TRAIN Top shape for layer 122 'ctx_output1/bn' 16 512 16 32 (4194304)
-I0510 14:48:30.154067  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu' of type 'ReLU'
-I0510 14:48:30.154073  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.154079  5307 net.cpp:200] Created Layer ctx_output1/relu (123)
-I0510 14:48:30.154088  5307 net.cpp:572] ctx_output1/relu <- ctx_output1
-I0510 14:48:30.154095  5307 net.cpp:527] ctx_output1/relu -> ctx_output1 (in-place)
-I0510 14:48:30.154106  5307 net.cpp:260] Setting up ctx_output1/relu
-I0510 14:48:30.154111  5307 net.cpp:267] TRAIN Top shape for layer 123 'ctx_output1/relu' 16 512 16 32 (4194304)
-I0510 14:48:30.154120  5307 layer_factory.hpp:172] Creating layer 'ctx_output1_ctx_output1/relu_0_split' of type 'Split'
-I0510 14:48:30.154126  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.154136  5307 net.cpp:200] Created Layer ctx_output1_ctx_output1/relu_0_split (124)
-I0510 14:48:30.154141  5307 net.cpp:572] ctx_output1_ctx_output1/relu_0_split <- ctx_output1
-I0510 14:48:30.154150  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_0
-I0510 14:48:30.154157  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_1
-I0510 14:48:30.154167  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_2
-I0510 14:48:30.154211  5307 net.cpp:260] Setting up ctx_output1_ctx_output1/relu_0_split
-I0510 14:48:30.154217  5307 net.cpp:267] TRAIN Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 16 512 16 32 (4194304)
-I0510 14:48:30.154227  5307 net.cpp:267] TRAIN Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 16 512 16 32 (4194304)
-I0510 14:48:30.154233  5307 net.cpp:267] TRAIN Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 16 512 16 32 (4194304)
-I0510 14:48:30.154242  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1' of type 'Convolution'
-I0510 14:48:30.154247  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.154265  5307 net.cpp:200] Created Layer ctx_output2/1x1 (125)
-I0510 14:48:30.154275  5307 net.cpp:572] ctx_output2/1x1 <- conv6/sep_relu6/sep_0_split_1
-I0510 14:48:30.154285  5307 net.cpp:542] ctx_output2/1x1 -> ctx_output2/1x1
-I0510 14:48:30.162034  5307 net.cpp:260] Setting up ctx_output2/1x1
-I0510 14:48:30.162204  5307 net.cpp:267] TRAIN Top shape for layer 125 'ctx_output2/1x1' 16 512 8 16 (1048576)
-I0510 14:48:30.162295  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.162374  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.162456  5307 net.cpp:200] Created Layer ctx_output2/1x1/bn (126)
-I0510 14:48:30.162525  5307 net.cpp:572] ctx_output2/1x1/bn <- ctx_output2/1x1
-I0510 14:48:30.162591  5307 net.cpp:527] ctx_output2/1x1/bn -> ctx_output2/1x1 (in-place)
-I0510 14:48:30.163060  5307 net.cpp:260] Setting up ctx_output2/1x1/bn
-I0510 14:48:30.163136  5307 net.cpp:267] TRAIN Top shape for layer 126 'ctx_output2/1x1/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.163213  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/relu' of type 'ReLU'
-I0510 14:48:30.163283  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.163358  5307 net.cpp:200] Created Layer ctx_output2/1x1/relu (127)
-I0510 14:48:30.163419  5307 net.cpp:572] ctx_output2/1x1/relu <- ctx_output2/1x1
-I0510 14:48:30.163480  5307 net.cpp:527] ctx_output2/1x1/relu -> ctx_output2/1x1 (in-place)
-I0510 14:48:30.163552  5307 net.cpp:260] Setting up ctx_output2/1x1/relu
-I0510 14:48:30.163614  5307 net.cpp:267] TRAIN Top shape for layer 127 'ctx_output2/1x1/relu' 16 512 8 16 (1048576)
-I0510 14:48:30.163682  5307 layer_factory.hpp:172] Creating layer 'ctx_output2' of type 'Convolution'
-I0510 14:48:30.163758  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.163839  5307 net.cpp:200] Created Layer ctx_output2 (128)
-I0510 14:48:30.163899  5307 net.cpp:572] ctx_output2 <- ctx_output2/1x1
-I0510 14:48:30.163960  5307 net.cpp:542] ctx_output2 -> ctx_output2
-I0510 14:48:30.164412  5307 net.cpp:260] Setting up ctx_output2
-I0510 14:48:30.164489  5307 net.cpp:267] TRAIN Top shape for layer 128 'ctx_output2' 16 512 8 16 (1048576)
-I0510 14:48:30.164567  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/bn' of type 'BatchNorm'
-I0510 14:48:30.164635  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.164711  5307 net.cpp:200] Created Layer ctx_output2/bn (129)
-I0510 14:48:30.164772  5307 net.cpp:572] ctx_output2/bn <- ctx_output2
-I0510 14:48:30.164831  5307 net.cpp:527] ctx_output2/bn -> ctx_output2 (in-place)
-I0510 14:48:30.165230  5307 net.cpp:260] Setting up ctx_output2/bn
-I0510 14:48:30.165298  5307 net.cpp:267] TRAIN Top shape for layer 129 'ctx_output2/bn' 16 512 8 16 (1048576)
-I0510 14:48:30.165375  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu' of type 'ReLU'
-I0510 14:48:30.165443  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.165515  5307 net.cpp:200] Created Layer ctx_output2/relu (130)
-I0510 14:48:30.165576  5307 net.cpp:572] ctx_output2/relu <- ctx_output2
-I0510 14:48:30.165642  5307 net.cpp:527] ctx_output2/relu -> ctx_output2 (in-place)
-I0510 14:48:30.165704  5307 net.cpp:260] Setting up ctx_output2/relu
-I0510 14:48:30.165763  5307 net.cpp:267] TRAIN Top shape for layer 130 'ctx_output2/relu' 16 512 8 16 (1048576)
-I0510 14:48:30.165832  5307 layer_factory.hpp:172] Creating layer 'ctx_output2_ctx_output2/relu_0_split' of type 'Split'
-I0510 14:48:30.165905  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.165974  5307 net.cpp:200] Created Layer ctx_output2_ctx_output2/relu_0_split (131)
-I0510 14:48:30.166040  5307 net.cpp:572] ctx_output2_ctx_output2/relu_0_split <- ctx_output2
-I0510 14:48:30.166112  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_0
-I0510 14:48:30.166188  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_1
-I0510 14:48:30.166267  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_2
-I0510 14:48:30.166391  5307 net.cpp:260] Setting up ctx_output2_ctx_output2/relu_0_split
-I0510 14:48:30.166460  5307 net.cpp:267] TRAIN Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.166540  5307 net.cpp:267] TRAIN Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.166615  5307 net.cpp:267] TRAIN Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 16 512 8 16 (1048576)
-I0510 14:48:30.166692  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1' of type 'Convolution'
-I0510 14:48:30.166769  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.166844  5307 net.cpp:200] Created Layer ctx_output3/1x1 (132)
-I0510 14:48:30.166905  5307 net.cpp:572] ctx_output3/1x1 <- pool6_pool6_0_split_1
-I0510 14:48:30.166970  5307 net.cpp:542] ctx_output3/1x1 -> ctx_output3/1x1
-I0510 14:48:30.175863  5307 net.cpp:260] Setting up ctx_output3/1x1
-I0510 14:48:30.175884  5307 net.cpp:267] TRAIN Top shape for layer 132 'ctx_output3/1x1' 16 512 5 9 (368640)
-I0510 14:48:30.175894  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.175899  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.175916  5307 net.cpp:200] Created Layer ctx_output3/1x1/bn (133)
-I0510 14:48:30.176038  5307 net.cpp:572] ctx_output3/1x1/bn <- ctx_output3/1x1
-I0510 14:48:30.176079  5307 net.cpp:527] ctx_output3/1x1/bn -> ctx_output3/1x1 (in-place)
-I0510 14:48:30.176417  5307 net.cpp:260] Setting up ctx_output3/1x1/bn
-I0510 14:48:30.176426  5307 net.cpp:267] TRAIN Top shape for layer 133 'ctx_output3/1x1/bn' 16 512 5 9 (368640)
-I0510 14:48:30.176435  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/relu' of type 'ReLU'
-I0510 14:48:30.176491  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.176533  5307 net.cpp:200] Created Layer ctx_output3/1x1/relu (134)
-I0510 14:48:30.176587  5307 net.cpp:572] ctx_output3/1x1/relu <- ctx_output3/1x1
-I0510 14:48:30.176594  5307 net.cpp:527] ctx_output3/1x1/relu -> ctx_output3/1x1 (in-place)
-I0510 14:48:30.176601  5307 net.cpp:260] Setting up ctx_output3/1x1/relu
-I0510 14:48:30.176676  5307 net.cpp:267] TRAIN Top shape for layer 134 'ctx_output3/1x1/relu' 16 512 5 9 (368640)
-I0510 14:48:30.176682  5307 layer_factory.hpp:172] Creating layer 'ctx_output3' of type 'Convolution'
-I0510 14:48:30.176738  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.176784  5307 net.cpp:200] Created Layer ctx_output3 (135)
-I0510 14:48:30.176790  5307 net.cpp:572] ctx_output3 <- ctx_output3/1x1
-I0510 14:48:30.176795  5307 net.cpp:542] ctx_output3 -> ctx_output3
-I0510 14:48:30.177225  5307 net.cpp:260] Setting up ctx_output3
-I0510 14:48:30.177243  5307 net.cpp:267] TRAIN Top shape for layer 135 'ctx_output3' 16 512 5 9 (368640)
-I0510 14:48:30.177256  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/bn' of type 'BatchNorm'
-I0510 14:48:30.177265  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.177276  5307 net.cpp:200] Created Layer ctx_output3/bn (136)
-I0510 14:48:30.177286  5307 net.cpp:572] ctx_output3/bn <- ctx_output3
-I0510 14:48:30.177296  5307 net.cpp:527] ctx_output3/bn -> ctx_output3 (in-place)
-I0510 14:48:30.177644  5307 net.cpp:260] Setting up ctx_output3/bn
-I0510 14:48:30.177659  5307 net.cpp:267] TRAIN Top shape for layer 136 'ctx_output3/bn' 16 512 5 9 (368640)
-I0510 14:48:30.177676  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu' of type 'ReLU'
-I0510 14:48:30.177685  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.177903  5307 net.cpp:200] Created Layer ctx_output3/relu (137)
-I0510 14:48:30.177911  5307 net.cpp:572] ctx_output3/relu <- ctx_output3
-I0510 14:48:30.177914  5307 net.cpp:527] ctx_output3/relu -> ctx_output3 (in-place)
-I0510 14:48:30.177976  5307 net.cpp:260] Setting up ctx_output3/relu
-I0510 14:48:30.177984  5307 net.cpp:267] TRAIN Top shape for layer 137 'ctx_output3/relu' 16 512 5 9 (368640)
-I0510 14:48:30.178035  5307 layer_factory.hpp:172] Creating layer 'ctx_output3_ctx_output3/relu_0_split' of type 'Split'
-I0510 14:48:30.178041  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.178047  5307 net.cpp:200] Created Layer ctx_output3_ctx_output3/relu_0_split (138)
-I0510 14:48:30.178133  5307 net.cpp:572] ctx_output3_ctx_output3/relu_0_split <- ctx_output3
-I0510 14:48:30.178143  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_0
-I0510 14:48:30.178200  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_1
-I0510 14:48:30.178207  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_2
-I0510 14:48:30.178302  5307 net.cpp:260] Setting up ctx_output3_ctx_output3/relu_0_split
-I0510 14:48:30.178309  5307 net.cpp:267] TRAIN Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.178367  5307 net.cpp:267] TRAIN Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.178375  5307 net.cpp:267] TRAIN Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 16 512 5 9 (368640)
-I0510 14:48:30.178445  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1' of type 'Convolution'
-I0510 14:48:30.178452  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.178521  5307 net.cpp:200] Created Layer ctx_output4/1x1 (139)
-I0510 14:48:30.178527  5307 net.cpp:572] ctx_output4/1x1 <- pool7_pool7_0_split_1
-I0510 14:48:30.178581  5307 net.cpp:542] ctx_output4/1x1 -> ctx_output4/1x1
-I0510 14:48:30.183876  5307 net.cpp:260] Setting up ctx_output4/1x1
-I0510 14:48:30.183899  5307 net.cpp:267] TRAIN Top shape for layer 139 'ctx_output4/1x1' 16 512 3 5 (122880)
-I0510 14:48:30.183907  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.183912  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.184043  5307 net.cpp:200] Created Layer ctx_output4/1x1/bn (140)
-I0510 14:48:30.184052  5307 net.cpp:572] ctx_output4/1x1/bn <- ctx_output4/1x1
-I0510 14:48:30.184064  5307 net.cpp:527] ctx_output4/1x1/bn -> ctx_output4/1x1 (in-place)
-I0510 14:48:30.184386  5307 net.cpp:260] Setting up ctx_output4/1x1/bn
-I0510 14:48:30.184393  5307 net.cpp:267] TRAIN Top shape for layer 140 'ctx_output4/1x1/bn' 16 512 3 5 (122880)
-I0510 14:48:30.184403  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/relu' of type 'ReLU'
-I0510 14:48:30.184415  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.184427  5307 net.cpp:200] Created Layer ctx_output4/1x1/relu (141)
-I0510 14:48:30.184437  5307 net.cpp:572] ctx_output4/1x1/relu <- ctx_output4/1x1
-I0510 14:48:30.184448  5307 net.cpp:527] ctx_output4/1x1/relu -> ctx_output4/1x1 (in-place)
-I0510 14:48:30.184461  5307 net.cpp:260] Setting up ctx_output4/1x1/relu
-I0510 14:48:30.184473  5307 net.cpp:267] TRAIN Top shape for layer 141 'ctx_output4/1x1/relu' 16 512 3 5 (122880)
-I0510 14:48:30.184482  5307 layer_factory.hpp:172] Creating layer 'ctx_output4' of type 'Convolution'
-I0510 14:48:30.184491  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.184509  5307 net.cpp:200] Created Layer ctx_output4 (142)
-I0510 14:48:30.184520  5307 net.cpp:572] ctx_output4 <- ctx_output4/1x1
-I0510 14:48:30.184541  5307 net.cpp:542] ctx_output4 -> ctx_output4
-I0510 14:48:30.184945  5307 net.cpp:260] Setting up ctx_output4
-I0510 14:48:30.184970  5307 net.cpp:267] TRAIN Top shape for layer 142 'ctx_output4' 16 512 3 5 (122880)
-I0510 14:48:30.184983  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/bn' of type 'BatchNorm'
-I0510 14:48:30.184994  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.185008  5307 net.cpp:200] Created Layer ctx_output4/bn (143)
-I0510 14:48:30.185017  5307 net.cpp:572] ctx_output4/bn <- ctx_output4
-I0510 14:48:30.185027  5307 net.cpp:527] ctx_output4/bn -> ctx_output4 (in-place)
-I0510 14:48:30.185374  5307 net.cpp:260] Setting up ctx_output4/bn
-I0510 14:48:30.185382  5307 net.cpp:267] TRAIN Top shape for layer 143 'ctx_output4/bn' 16 512 3 5 (122880)
-I0510 14:48:30.185391  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu' of type 'ReLU'
-I0510 14:48:30.185402  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.185415  5307 net.cpp:200] Created Layer ctx_output4/relu (144)
-I0510 14:48:30.185425  5307 net.cpp:572] ctx_output4/relu <- ctx_output4
-I0510 14:48:30.185436  5307 net.cpp:527] ctx_output4/relu -> ctx_output4 (in-place)
-I0510 14:48:30.185448  5307 net.cpp:260] Setting up ctx_output4/relu
-I0510 14:48:30.185459  5307 net.cpp:267] TRAIN Top shape for layer 144 'ctx_output4/relu' 16 512 3 5 (122880)
-I0510 14:48:30.185469  5307 layer_factory.hpp:172] Creating layer 'ctx_output4_ctx_output4/relu_0_split' of type 'Split'
-I0510 14:48:30.185479  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.185492  5307 net.cpp:200] Created Layer ctx_output4_ctx_output4/relu_0_split (145)
-I0510 14:48:30.185501  5307 net.cpp:572] ctx_output4_ctx_output4/relu_0_split <- ctx_output4
-I0510 14:48:30.185513  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_0
-I0510 14:48:30.185525  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_1
-I0510 14:48:30.185537  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_2
-I0510 14:48:30.185593  5307 net.cpp:260] Setting up ctx_output4_ctx_output4/relu_0_split
-I0510 14:48:30.185607  5307 net.cpp:267] TRAIN Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.185619  5307 net.cpp:267] TRAIN Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.185631  5307 net.cpp:267] TRAIN Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.185640  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1' of type 'Convolution'
-I0510 14:48:30.185650  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.185667  5307 net.cpp:200] Created Layer ctx_output5/1x1 (146)
-I0510 14:48:30.185678  5307 net.cpp:572] ctx_output5/1x1 <- pool8
-I0510 14:48:30.185688  5307 net.cpp:542] ctx_output5/1x1 -> ctx_output5/1x1
-I0510 14:48:30.194860  5307 net.cpp:260] Setting up ctx_output5/1x1
-I0510 14:48:30.194931  5307 net.cpp:267] TRAIN Top shape for layer 146 'ctx_output5/1x1' 16 512 3 5 (122880)
-I0510 14:48:30.194957  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.194974  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.194999  5307 net.cpp:200] Created Layer ctx_output5/1x1/bn (147)
-I0510 14:48:30.195019  5307 net.cpp:572] ctx_output5/1x1/bn <- ctx_output5/1x1
-I0510 14:48:30.195035  5307 net.cpp:527] ctx_output5/1x1/bn -> ctx_output5/1x1 (in-place)
-I0510 14:48:30.195438  5307 net.cpp:260] Setting up ctx_output5/1x1/bn
-I0510 14:48:30.195466  5307 net.cpp:267] TRAIN Top shape for layer 147 'ctx_output5/1x1/bn' 16 512 3 5 (122880)
-I0510 14:48:30.195488  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/relu' of type 'ReLU'
-I0510 14:48:30.195513  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.195540  5307 net.cpp:200] Created Layer ctx_output5/1x1/relu (148)
-I0510 14:48:30.195557  5307 net.cpp:572] ctx_output5/1x1/relu <- ctx_output5/1x1
-I0510 14:48:30.195574  5307 net.cpp:527] ctx_output5/1x1/relu -> ctx_output5/1x1 (in-place)
-I0510 14:48:30.195593  5307 net.cpp:260] Setting up ctx_output5/1x1/relu
-I0510 14:48:30.195610  5307 net.cpp:267] TRAIN Top shape for layer 148 'ctx_output5/1x1/relu' 16 512 3 5 (122880)
-I0510 14:48:30.195626  5307 layer_factory.hpp:172] Creating layer 'ctx_output5' of type 'Convolution'
-I0510 14:48:30.195641  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.195664  5307 net.cpp:200] Created Layer ctx_output5 (149)
-I0510 14:48:30.195683  5307 net.cpp:572] ctx_output5 <- ctx_output5/1x1
-I0510 14:48:30.195698  5307 net.cpp:542] ctx_output5 -> ctx_output5
-I0510 14:48:30.196110  5307 net.cpp:260] Setting up ctx_output5
-I0510 14:48:30.196135  5307 net.cpp:267] TRAIN Top shape for layer 149 'ctx_output5' 16 512 3 5 (122880)
-I0510 14:48:30.196156  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/bn' of type 'BatchNorm'
-I0510 14:48:30.196174  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.196193  5307 net.cpp:200] Created Layer ctx_output5/bn (150)
-I0510 14:48:30.196210  5307 net.cpp:572] ctx_output5/bn <- ctx_output5
-I0510 14:48:30.196226  5307 net.cpp:527] ctx_output5/bn -> ctx_output5 (in-place)
-I0510 14:48:30.196609  5307 net.cpp:260] Setting up ctx_output5/bn
-I0510 14:48:30.196635  5307 net.cpp:267] TRAIN Top shape for layer 150 'ctx_output5/bn' 16 512 3 5 (122880)
-I0510 14:48:30.196662  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu' of type 'ReLU'
-I0510 14:48:30.196681  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.196698  5307 net.cpp:200] Created Layer ctx_output5/relu (151)
-I0510 14:48:30.196717  5307 net.cpp:572] ctx_output5/relu <- ctx_output5
-I0510 14:48:30.196732  5307 net.cpp:527] ctx_output5/relu -> ctx_output5 (in-place)
-I0510 14:48:30.196750  5307 net.cpp:260] Setting up ctx_output5/relu
-I0510 14:48:30.196768  5307 net.cpp:267] TRAIN Top shape for layer 151 'ctx_output5/relu' 16 512 3 5 (122880)
-I0510 14:48:30.196784  5307 layer_factory.hpp:172] Creating layer 'ctx_output5_ctx_output5/relu_0_split' of type 'Split'
-I0510 14:48:30.196800  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.196818  5307 net.cpp:200] Created Layer ctx_output5_ctx_output5/relu_0_split (152)
-I0510 14:48:30.196833  5307 net.cpp:572] ctx_output5_ctx_output5/relu_0_split <- ctx_output5
-I0510 14:48:30.196849  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_0
-I0510 14:48:30.196867  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_1
-I0510 14:48:30.196887  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_2
-I0510 14:48:30.196943  5307 net.cpp:260] Setting up ctx_output5_ctx_output5/relu_0_split
-I0510 14:48:30.196961  5307 net.cpp:267] TRAIN Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.196979  5307 net.cpp:267] TRAIN Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.196995  5307 net.cpp:267] TRAIN Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 16 512 3 5 (122880)
-I0510 14:48:30.197012  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.197028  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.197051  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc (153)
-I0510 14:48:30.197068  5307 net.cpp:572] ctx_output1/relu_mbox_loc <- ctx_output1_ctx_output1/relu_0_split_0
-I0510 14:48:30.197089  5307 net.cpp:542] ctx_output1/relu_mbox_loc -> ctx_output1/relu_mbox_loc
-I0510 14:48:30.197599  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc
-I0510 14:48:30.197623  5307 net.cpp:267] TRAIN Top shape for layer 153 'ctx_output1/relu_mbox_loc' 16 16 16 32 (131072)
-I0510 14:48:30.197641  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.197657  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.197681  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_perm (154)
-I0510 14:48:30.197700  5307 net.cpp:572] ctx_output1/relu_mbox_loc_perm <- ctx_output1/relu_mbox_loc
-I0510 14:48:30.197717  5307 net.cpp:542] ctx_output1/relu_mbox_loc_perm -> ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.197830  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.197850  5307 net.cpp:267] TRAIN Top shape for layer 154 'ctx_output1/relu_mbox_loc_perm' 16 16 32 16 (131072)
-I0510 14:48:30.197866  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.197883  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.197902  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_flat (155)
-I0510 14:48:30.197918  5307 net.cpp:572] ctx_output1/relu_mbox_loc_flat <- ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.197934  5307 net.cpp:542] ctx_output1/relu_mbox_loc_flat -> ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.198081  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.198103  5307 net.cpp:267] TRAIN Top shape for layer 155 'ctx_output1/relu_mbox_loc_flat' 16 8192 (131072)
-I0510 14:48:30.198122  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.198138  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.198158  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf (156)
-I0510 14:48:30.198174  5307 net.cpp:572] ctx_output1/relu_mbox_conf <- ctx_output1_ctx_output1/relu_0_split_1
-I0510 14:48:30.198191  5307 net.cpp:542] ctx_output1/relu_mbox_conf -> ctx_output1/relu_mbox_conf
-I0510 14:48:30.199424  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf
-I0510 14:48:30.199432  5307 net.cpp:267] TRAIN Top shape for layer 156 'ctx_output1/relu_mbox_conf' 16 84 16 32 (688128)
-I0510 14:48:30.199439  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.199455  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.199476  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_perm (157)
-I0510 14:48:30.199491  5307 net.cpp:572] ctx_output1/relu_mbox_conf_perm <- ctx_output1/relu_mbox_conf
-I0510 14:48:30.199507  5307 net.cpp:542] ctx_output1/relu_mbox_conf_perm -> ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.199615  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.199636  5307 net.cpp:267] TRAIN Top shape for layer 157 'ctx_output1/relu_mbox_conf_perm' 16 16 32 84 (688128)
-I0510 14:48:30.199651  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.199667  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.199683  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_flat (158)
-I0510 14:48:30.199700  5307 net.cpp:572] ctx_output1/relu_mbox_conf_flat <- ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.199718  5307 net.cpp:542] ctx_output1/relu_mbox_conf_flat -> ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.202023  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.202046  5307 net.cpp:267] TRAIN Top shape for layer 158 'ctx_output1/relu_mbox_conf_flat' 16 43008 (688128)
-I0510 14:48:30.202054  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.202088  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.202116  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_priorbox (159)
-I0510 14:48:30.202134  5307 net.cpp:572] ctx_output1/relu_mbox_priorbox <- ctx_output1_ctx_output1/relu_0_split_2
-I0510 14:48:30.202153  5307 net.cpp:572] ctx_output1/relu_mbox_priorbox <- data_data_0_split_1
-I0510 14:48:30.202172  5307 net.cpp:542] ctx_output1/relu_mbox_priorbox -> ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.202232  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.202253  5307 net.cpp:267] TRAIN Top shape for layer 159 'ctx_output1/relu_mbox_priorbox' 1 2 8192 (16384)
-I0510 14:48:30.202270  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.202286  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.202309  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc (160)
-I0510 14:48:30.202325  5307 net.cpp:572] ctx_output2/relu_mbox_loc <- ctx_output2_ctx_output2/relu_0_split_0
-I0510 14:48:30.202342  5307 net.cpp:542] ctx_output2/relu_mbox_loc -> ctx_output2/relu_mbox_loc
-I0510 14:48:30.202988  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc
-I0510 14:48:30.203012  5307 net.cpp:267] TRAIN Top shape for layer 160 'ctx_output2/relu_mbox_loc' 16 24 8 16 (49152)
-I0510 14:48:30.203033  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.203050  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.203073  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_perm (161)
-I0510 14:48:30.203092  5307 net.cpp:572] ctx_output2/relu_mbox_loc_perm <- ctx_output2/relu_mbox_loc
-I0510 14:48:30.203110  5307 net.cpp:542] ctx_output2/relu_mbox_loc_perm -> ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.203215  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.203235  5307 net.cpp:267] TRAIN Top shape for layer 161 'ctx_output2/relu_mbox_loc_perm' 16 8 16 24 (49152)
-I0510 14:48:30.203253  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.203269  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.203286  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_flat (162)
-I0510 14:48:30.203301  5307 net.cpp:572] ctx_output2/relu_mbox_loc_flat <- ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.203318  5307 net.cpp:542] ctx_output2/relu_mbox_loc_flat -> ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.203414  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.203434  5307 net.cpp:267] TRAIN Top shape for layer 162 'ctx_output2/relu_mbox_loc_flat' 16 3072 (49152)
-I0510 14:48:30.203452  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.203469  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.203488  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf (163)
-I0510 14:48:30.203505  5307 net.cpp:572] ctx_output2/relu_mbox_conf <- ctx_output2_ctx_output2/relu_0_split_1
-I0510 14:48:30.203522  5307 net.cpp:542] ctx_output2/relu_mbox_conf -> ctx_output2/relu_mbox_conf
-I0510 14:48:30.205476  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf
-I0510 14:48:30.205487  5307 net.cpp:267] TRAIN Top shape for layer 163 'ctx_output2/relu_mbox_conf' 16 126 8 16 (258048)
-I0510 14:48:30.205520  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.205536  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.205556  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_perm (164)
-I0510 14:48:30.205574  5307 net.cpp:572] ctx_output2/relu_mbox_conf_perm <- ctx_output2/relu_mbox_conf
-I0510 14:48:30.205595  5307 net.cpp:542] ctx_output2/relu_mbox_conf_perm -> ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.205690  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.205698  5307 net.cpp:267] TRAIN Top shape for layer 164 'ctx_output2/relu_mbox_conf_perm' 16 8 16 126 (258048)
-I0510 14:48:30.205719  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.205734  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.205750  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_flat (165)
-I0510 14:48:30.205765  5307 net.cpp:572] ctx_output2/relu_mbox_conf_flat <- ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.205780  5307 net.cpp:542] ctx_output2/relu_mbox_conf_flat -> ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.206703  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.206729  5307 net.cpp:267] TRAIN Top shape for layer 165 'ctx_output2/relu_mbox_conf_flat' 16 16128 (258048)
-I0510 14:48:30.206745  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.206761  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.206779  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_priorbox (166)
-I0510 14:48:30.206794  5307 net.cpp:572] ctx_output2/relu_mbox_priorbox <- ctx_output2_ctx_output2/relu_0_split_2
-I0510 14:48:30.206810  5307 net.cpp:572] ctx_output2/relu_mbox_priorbox <- data_data_0_split_2
-I0510 14:48:30.206826  5307 net.cpp:542] ctx_output2/relu_mbox_priorbox -> ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.206867  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.206888  5307 net.cpp:267] TRAIN Top shape for layer 166 'ctx_output2/relu_mbox_priorbox' 1 2 3072 (6144)
-I0510 14:48:30.206904  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.206919  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.206944  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc (167)
-I0510 14:48:30.206959  5307 net.cpp:572] ctx_output3/relu_mbox_loc <- ctx_output3_ctx_output3/relu_0_split_0
-I0510 14:48:30.206975  5307 net.cpp:542] ctx_output3/relu_mbox_loc -> ctx_output3/relu_mbox_loc
-I0510 14:48:30.207593  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc
-I0510 14:48:30.207613  5307 net.cpp:267] TRAIN Top shape for layer 167 'ctx_output3/relu_mbox_loc' 16 24 5 9 (17280)
-I0510 14:48:30.207634  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.207653  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.207671  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_perm (168)
-I0510 14:48:30.207690  5307 net.cpp:572] ctx_output3/relu_mbox_loc_perm <- ctx_output3/relu_mbox_loc
-I0510 14:48:30.207707  5307 net.cpp:542] ctx_output3/relu_mbox_loc_perm -> ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.207818  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.207839  5307 net.cpp:267] TRAIN Top shape for layer 168 'ctx_output3/relu_mbox_loc_perm' 16 5 9 24 (17280)
-I0510 14:48:30.207854  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.207870  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.207886  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_flat (169)
-I0510 14:48:30.207901  5307 net.cpp:572] ctx_output3/relu_mbox_loc_flat <- ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.207916  5307 net.cpp:542] ctx_output3/relu_mbox_loc_flat -> ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.207991  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.208011  5307 net.cpp:267] TRAIN Top shape for layer 169 'ctx_output3/relu_mbox_loc_flat' 16 1080 (17280)
-I0510 14:48:30.208036  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.208052  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.208072  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf (170)
-I0510 14:48:30.208088  5307 net.cpp:572] ctx_output3/relu_mbox_conf <- ctx_output3_ctx_output3/relu_0_split_1
-I0510 14:48:30.208104  5307 net.cpp:542] ctx_output3/relu_mbox_conf -> ctx_output3/relu_mbox_conf
-I0510 14:48:30.209836  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf
-I0510 14:48:30.209846  5307 net.cpp:267] TRAIN Top shape for layer 170 'ctx_output3/relu_mbox_conf' 16 126 5 9 (90720)
-I0510 14:48:30.209878  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.209895  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.209915  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_perm (171)
-I0510 14:48:30.209931  5307 net.cpp:572] ctx_output3/relu_mbox_conf_perm <- ctx_output3/relu_mbox_conf
-I0510 14:48:30.209949  5307 net.cpp:542] ctx_output3/relu_mbox_conf_perm -> ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.210062  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.210083  5307 net.cpp:267] TRAIN Top shape for layer 171 'ctx_output3/relu_mbox_conf_perm' 16 5 9 126 (90720)
-I0510 14:48:30.210099  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.210116  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.210136  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_flat (172)
-I0510 14:48:30.210152  5307 net.cpp:572] ctx_output3/relu_mbox_conf_flat <- ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.210170  5307 net.cpp:542] ctx_output3/relu_mbox_conf_flat -> ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.210278  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.210299  5307 net.cpp:267] TRAIN Top shape for layer 172 'ctx_output3/relu_mbox_conf_flat' 16 5670 (90720)
-I0510 14:48:30.210316  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.210331  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.210348  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_priorbox (173)
-I0510 14:48:30.210366  5307 net.cpp:572] ctx_output3/relu_mbox_priorbox <- ctx_output3_ctx_output3/relu_0_split_2
-I0510 14:48:30.210383  5307 net.cpp:572] ctx_output3/relu_mbox_priorbox <- data_data_0_split_3
-I0510 14:48:30.210399  5307 net.cpp:542] ctx_output3/relu_mbox_priorbox -> ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.210436  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.210455  5307 net.cpp:267] TRAIN Top shape for layer 173 'ctx_output3/relu_mbox_priorbox' 1 2 1080 (2160)
-I0510 14:48:30.210472  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.210489  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.210510  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc (174)
-I0510 14:48:30.210525  5307 net.cpp:572] ctx_output4/relu_mbox_loc <- ctx_output4_ctx_output4/relu_0_split_0
-I0510 14:48:30.210542  5307 net.cpp:542] ctx_output4/relu_mbox_loc -> ctx_output4/relu_mbox_loc
-I0510 14:48:30.210978  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc
-I0510 14:48:30.210986  5307 net.cpp:267] TRAIN Top shape for layer 174 'ctx_output4/relu_mbox_loc' 16 16 3 5 (3840)
-I0510 14:48:30.211015  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.211032  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.211056  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_perm (175)
-I0510 14:48:30.211083  5307 net.cpp:572] ctx_output4/relu_mbox_loc_perm <- ctx_output4/relu_mbox_loc
-I0510 14:48:30.211099  5307 net.cpp:542] ctx_output4/relu_mbox_loc_perm -> ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.211210  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.211230  5307 net.cpp:267] TRAIN Top shape for layer 175 'ctx_output4/relu_mbox_loc_perm' 16 3 5 16 (3840)
-I0510 14:48:30.211247  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.211263  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.211282  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_flat (176)
-I0510 14:48:30.211297  5307 net.cpp:572] ctx_output4/relu_mbox_loc_flat <- ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.211313  5307 net.cpp:542] ctx_output4/relu_mbox_loc_flat -> ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.211381  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.211403  5307 net.cpp:267] TRAIN Top shape for layer 176 'ctx_output4/relu_mbox_loc_flat' 16 240 (3840)
-I0510 14:48:30.211419  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.211434  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.211457  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf (177)
-I0510 14:48:30.211473  5307 net.cpp:572] ctx_output4/relu_mbox_conf <- ctx_output4_ctx_output4/relu_0_split_1
-I0510 14:48:30.211493  5307 net.cpp:542] ctx_output4/relu_mbox_conf -> ctx_output4/relu_mbox_conf
-I0510 14:48:30.212776  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf
-I0510 14:48:30.212785  5307 net.cpp:267] TRAIN Top shape for layer 177 'ctx_output4/relu_mbox_conf' 16 84 3 5 (20160)
-I0510 14:48:30.212822  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.212841  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.212859  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_perm (178)
-I0510 14:48:30.212877  5307 net.cpp:572] ctx_output4/relu_mbox_conf_perm <- ctx_output4/relu_mbox_conf
-I0510 14:48:30.212894  5307 net.cpp:542] ctx_output4/relu_mbox_conf_perm -> ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.213009  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.213030  5307 net.cpp:267] TRAIN Top shape for layer 178 'ctx_output4/relu_mbox_conf_perm' 16 3 5 84 (20160)
-I0510 14:48:30.213047  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.213063  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.213080  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_flat (179)
-I0510 14:48:30.213096  5307 net.cpp:572] ctx_output4/relu_mbox_conf_flat <- ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.213112  5307 net.cpp:542] ctx_output4/relu_mbox_conf_flat -> ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.213191  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.213210  5307 net.cpp:267] TRAIN Top shape for layer 179 'ctx_output4/relu_mbox_conf_flat' 16 1260 (20160)
-I0510 14:48:30.213227  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.213241  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.213259  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_priorbox (180)
-I0510 14:48:30.213276  5307 net.cpp:572] ctx_output4/relu_mbox_priorbox <- ctx_output4_ctx_output4/relu_0_split_2
-I0510 14:48:30.213292  5307 net.cpp:572] ctx_output4/relu_mbox_priorbox <- data_data_0_split_4
-I0510 14:48:30.213310  5307 net.cpp:542] ctx_output4/relu_mbox_priorbox -> ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.213349  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.213374  5307 net.cpp:267] TRAIN Top shape for layer 180 'ctx_output4/relu_mbox_priorbox' 1 2 240 (480)
-I0510 14:48:30.213392  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.213407  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.213428  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc (181)
-I0510 14:48:30.213444  5307 net.cpp:572] ctx_output5/relu_mbox_loc <- ctx_output5_ctx_output5/relu_0_split_0
-I0510 14:48:30.213460  5307 net.cpp:542] ctx_output5/relu_mbox_loc -> ctx_output5/relu_mbox_loc
-I0510 14:48:30.213901  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc
-I0510 14:48:30.213910  5307 net.cpp:267] TRAIN Top shape for layer 181 'ctx_output5/relu_mbox_loc' 16 16 3 5 (3840)
-I0510 14:48:30.213917  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.213928  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.213940  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_perm (182)
-I0510 14:48:30.213950  5307 net.cpp:572] ctx_output5/relu_mbox_loc_perm <- ctx_output5/relu_mbox_loc
-I0510 14:48:30.213961  5307 net.cpp:542] ctx_output5/relu_mbox_loc_perm -> ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.214069  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.214084  5307 net.cpp:267] TRAIN Top shape for layer 182 'ctx_output5/relu_mbox_loc_perm' 16 3 5 16 (3840)
-I0510 14:48:30.214095  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.214105  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.214118  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_flat (183)
-I0510 14:48:30.214126  5307 net.cpp:572] ctx_output5/relu_mbox_loc_flat <- ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.214136  5307 net.cpp:542] ctx_output5/relu_mbox_loc_flat -> ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.214196  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.214210  5307 net.cpp:267] TRAIN Top shape for layer 183 'ctx_output5/relu_mbox_loc_flat' 16 240 (3840)
-I0510 14:48:30.214221  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.214232  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.214246  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf (184)
-I0510 14:48:30.214256  5307 net.cpp:572] ctx_output5/relu_mbox_conf <- ctx_output5_ctx_output5/relu_0_split_1
-I0510 14:48:30.214267  5307 net.cpp:542] ctx_output5/relu_mbox_conf -> ctx_output5/relu_mbox_conf
-I0510 14:48:30.215553  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf
-I0510 14:48:30.215562  5307 net.cpp:267] TRAIN Top shape for layer 184 'ctx_output5/relu_mbox_conf' 16 84 3 5 (20160)
-I0510 14:48:30.215569  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.215580  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.215595  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_perm (185)
-I0510 14:48:30.215605  5307 net.cpp:572] ctx_output5/relu_mbox_conf_perm <- ctx_output5/relu_mbox_conf
-I0510 14:48:30.215615  5307 net.cpp:542] ctx_output5/relu_mbox_conf_perm -> ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.215721  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.215736  5307 net.cpp:267] TRAIN Top shape for layer 185 'ctx_output5/relu_mbox_conf_perm' 16 3 5 84 (20160)
-I0510 14:48:30.215747  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.215757  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.215773  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_flat (186)
-I0510 14:48:30.215790  5307 net.cpp:572] ctx_output5/relu_mbox_conf_flat <- ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.215801  5307 net.cpp:542] ctx_output5/relu_mbox_conf_flat -> ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.215883  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.215898  5307 net.cpp:267] TRAIN Top shape for layer 186 'ctx_output5/relu_mbox_conf_flat' 16 1260 (20160)
-I0510 14:48:30.215907  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.215919  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.215931  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_priorbox (187)
-I0510 14:48:30.215942  5307 net.cpp:572] ctx_output5/relu_mbox_priorbox <- ctx_output5_ctx_output5/relu_0_split_2
-I0510 14:48:30.215953  5307 net.cpp:572] ctx_output5/relu_mbox_priorbox <- data_data_0_split_5
-I0510 14:48:30.215963  5307 net.cpp:542] ctx_output5/relu_mbox_priorbox -> ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.215996  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.216009  5307 net.cpp:267] TRAIN Top shape for layer 187 'ctx_output5/relu_mbox_priorbox' 1 2 240 (480)
-I0510 14:48:30.216018  5307 layer_factory.hpp:172] Creating layer 'mbox_loc' of type 'Concat'
-I0510 14:48:30.216028  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216044  5307 net.cpp:200] Created Layer mbox_loc (188)
-I0510 14:48:30.216055  5307 net.cpp:572] mbox_loc <- ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.216065  5307 net.cpp:572] mbox_loc <- ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.216076  5307 net.cpp:572] mbox_loc <- ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.216087  5307 net.cpp:572] mbox_loc <- ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.216099  5307 net.cpp:572] mbox_loc <- ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.216110  5307 net.cpp:542] mbox_loc -> mbox_loc
-I0510 14:48:30.216143  5307 net.cpp:260] Setting up mbox_loc
-I0510 14:48:30.216156  5307 net.cpp:267] TRAIN Top shape for layer 188 'mbox_loc' 16 12824 (205184)
-I0510 14:48:30.216167  5307 layer_factory.hpp:172] Creating layer 'mbox_conf' of type 'Concat'
-I0510 14:48:30.216177  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216187  5307 net.cpp:200] Created Layer mbox_conf (189)
-I0510 14:48:30.216197  5307 net.cpp:572] mbox_conf <- ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.216207  5307 net.cpp:572] mbox_conf <- ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.216219  5307 net.cpp:572] mbox_conf <- ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.216231  5307 net.cpp:572] mbox_conf <- ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.216241  5307 net.cpp:572] mbox_conf <- ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.216253  5307 net.cpp:542] mbox_conf -> mbox_conf
-I0510 14:48:30.216284  5307 net.cpp:260] Setting up mbox_conf
-I0510 14:48:30.216296  5307 net.cpp:267] TRAIN Top shape for layer 189 'mbox_conf' 16 67326 (1077216)
-I0510 14:48:30.216306  5307 layer_factory.hpp:172] Creating layer 'mbox_priorbox' of type 'Concat'
-I0510 14:48:30.216317  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216329  5307 net.cpp:200] Created Layer mbox_priorbox (190)
-I0510 14:48:30.216339  5307 net.cpp:572] mbox_priorbox <- ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.216351  5307 net.cpp:572] mbox_priorbox <- ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.216361  5307 net.cpp:572] mbox_priorbox <- ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.216372  5307 net.cpp:572] mbox_priorbox <- ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.216383  5307 net.cpp:572] mbox_priorbox <- ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.216393  5307 net.cpp:542] mbox_priorbox -> mbox_priorbox
-I0510 14:48:30.216425  5307 net.cpp:260] Setting up mbox_priorbox
-I0510 14:48:30.216442  5307 net.cpp:267] TRAIN Top shape for layer 190 'mbox_priorbox' 1 2 12824 (25648)
-I0510 14:48:30.216459  5307 layer_factory.hpp:172] Creating layer 'mbox_loss' of type 'MultiBoxLoss'
-I0510 14:48:30.216470  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216485  5307 net.cpp:200] Created Layer mbox_loss (191)
-I0510 14:48:30.216495  5307 net.cpp:572] mbox_loss <- mbox_loc
-I0510 14:48:30.216506  5307 net.cpp:572] mbox_loss <- mbox_conf
-I0510 14:48:30.216517  5307 net.cpp:572] mbox_loss <- mbox_priorbox
-I0510 14:48:30.216532  5307 net.cpp:572] mbox_loss <- label
-I0510 14:48:30.216547  5307 net.cpp:542] mbox_loss -> mbox_loss
-I0510 14:48:30.216626  5307 layer_factory.hpp:172] Creating layer 'mbox_loss_smooth_L1_loc' of type 'SmoothL1Loss'
-I0510 14:48:30.216639  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216751  5307 layer_factory.hpp:172] Creating layer 'mbox_loss_softmax_conf' of type 'SoftmaxWithLoss'
-I0510 14:48:30.216764  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.216893  5307 net.cpp:260] Setting up mbox_loss
-I0510 14:48:30.216907  5307 net.cpp:267] TRAIN Top shape for layer 191 'mbox_loss' (1)
-I0510 14:48:30.216917  5307 net.cpp:271]     with loss weight 1
-I0510 14:48:30.216939  5307 net.cpp:336] mbox_loss needs backward computation.
-I0510 14:48:30.216951  5307 net.cpp:338] mbox_priorbox does not need backward computation.
-I0510 14:48:30.216964  5307 net.cpp:336] mbox_conf needs backward computation.
-I0510 14:48:30.216974  5307 net.cpp:336] mbox_loc needs backward computation.
-I0510 14:48:30.216984  5307 net.cpp:338] ctx_output5/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.216995  5307 net.cpp:336] ctx_output5/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217005  5307 net.cpp:336] ctx_output5/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217015  5307 net.cpp:336] ctx_output5/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217025  5307 net.cpp:336] ctx_output5/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217036  5307 net.cpp:336] ctx_output5/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217046  5307 net.cpp:336] ctx_output5/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217056  5307 net.cpp:338] ctx_output4/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.217067  5307 net.cpp:336] ctx_output4/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217077  5307 net.cpp:336] ctx_output4/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217087  5307 net.cpp:336] ctx_output4/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217098  5307 net.cpp:336] ctx_output4/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217108  5307 net.cpp:336] ctx_output4/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217118  5307 net.cpp:336] ctx_output4/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217128  5307 net.cpp:338] ctx_output3/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.217139  5307 net.cpp:336] ctx_output3/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217149  5307 net.cpp:336] ctx_output3/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217159  5307 net.cpp:336] ctx_output3/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217169  5307 net.cpp:336] ctx_output3/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217177  5307 net.cpp:336] ctx_output3/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217185  5307 net.cpp:336] ctx_output3/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217195  5307 net.cpp:338] ctx_output2/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.217206  5307 net.cpp:336] ctx_output2/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217214  5307 net.cpp:336] ctx_output2/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217227  5307 net.cpp:336] ctx_output2/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217242  5307 net.cpp:336] ctx_output2/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217250  5307 net.cpp:336] ctx_output2/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217259  5307 net.cpp:336] ctx_output2/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217268  5307 net.cpp:338] ctx_output1/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.217278  5307 net.cpp:336] ctx_output1/relu_mbox_conf_flat needs backward computation.
-I0510 14:48:30.217288  5307 net.cpp:336] ctx_output1/relu_mbox_conf_perm needs backward computation.
-I0510 14:48:30.217296  5307 net.cpp:336] ctx_output1/relu_mbox_conf needs backward computation.
-I0510 14:48:30.217305  5307 net.cpp:336] ctx_output1/relu_mbox_loc_flat needs backward computation.
-I0510 14:48:30.217314  5307 net.cpp:336] ctx_output1/relu_mbox_loc_perm needs backward computation.
-I0510 14:48:30.217322  5307 net.cpp:336] ctx_output1/relu_mbox_loc needs backward computation.
-I0510 14:48:30.217331  5307 net.cpp:336] ctx_output5_ctx_output5/relu_0_split needs backward computation.
-I0510 14:48:30.217340  5307 net.cpp:336] ctx_output5/relu needs backward computation.
-I0510 14:48:30.217350  5307 net.cpp:336] ctx_output5/bn needs backward computation.
-I0510 14:48:30.217358  5307 net.cpp:336] ctx_output5 needs backward computation.
-I0510 14:48:30.217367  5307 net.cpp:336] ctx_output5/1x1/relu needs backward computation.
-I0510 14:48:30.217376  5307 net.cpp:336] ctx_output5/1x1/bn needs backward computation.
-I0510 14:48:30.217386  5307 net.cpp:336] ctx_output5/1x1 needs backward computation.
-I0510 14:48:30.217394  5307 net.cpp:336] ctx_output4_ctx_output4/relu_0_split needs backward computation.
-I0510 14:48:30.217403  5307 net.cpp:336] ctx_output4/relu needs backward computation.
-I0510 14:48:30.217412  5307 net.cpp:336] ctx_output4/bn needs backward computation.
-I0510 14:48:30.217422  5307 net.cpp:336] ctx_output4 needs backward computation.
-I0510 14:48:30.217429  5307 net.cpp:336] ctx_output4/1x1/relu needs backward computation.
-I0510 14:48:30.217438  5307 net.cpp:336] ctx_output4/1x1/bn needs backward computation.
-I0510 14:48:30.217447  5307 net.cpp:336] ctx_output4/1x1 needs backward computation.
-I0510 14:48:30.217455  5307 net.cpp:336] ctx_output3_ctx_output3/relu_0_split needs backward computation.
-I0510 14:48:30.217463  5307 net.cpp:336] ctx_output3/relu needs backward computation.
-I0510 14:48:30.217473  5307 net.cpp:336] ctx_output3/bn needs backward computation.
-I0510 14:48:30.217480  5307 net.cpp:336] ctx_output3 needs backward computation.
-I0510 14:48:30.217489  5307 net.cpp:336] ctx_output3/1x1/relu needs backward computation.
-I0510 14:48:30.217496  5307 net.cpp:336] ctx_output3/1x1/bn needs backward computation.
-I0510 14:48:30.217505  5307 net.cpp:336] ctx_output3/1x1 needs backward computation.
-I0510 14:48:30.217514  5307 net.cpp:336] ctx_output2_ctx_output2/relu_0_split needs backward computation.
-I0510 14:48:30.217522  5307 net.cpp:336] ctx_output2/relu needs backward computation.
-I0510 14:48:30.217530  5307 net.cpp:336] ctx_output2/bn needs backward computation.
-I0510 14:48:30.217538  5307 net.cpp:336] ctx_output2 needs backward computation.
-I0510 14:48:30.217546  5307 net.cpp:336] ctx_output2/1x1/relu needs backward computation.
-I0510 14:48:30.217555  5307 net.cpp:336] ctx_output2/1x1/bn needs backward computation.
-I0510 14:48:30.217563  5307 net.cpp:336] ctx_output2/1x1 needs backward computation.
-I0510 14:48:30.217571  5307 net.cpp:336] ctx_output1_ctx_output1/relu_0_split needs backward computation.
-I0510 14:48:30.217581  5307 net.cpp:336] ctx_output1/relu needs backward computation.
-I0510 14:48:30.217588  5307 net.cpp:336] ctx_output1/bn needs backward computation.
-I0510 14:48:30.217597  5307 net.cpp:336] ctx_output1 needs backward computation.
-I0510 14:48:30.217605  5307 net.cpp:336] ctx_output1/1x1/relu needs backward computation.
-I0510 14:48:30.217617  5307 net.cpp:336] ctx_output1/1x1/bn needs backward computation.
-I0510 14:48:30.217628  5307 net.cpp:336] ctx_output1/1x1 needs backward computation.
-I0510 14:48:30.217638  5307 net.cpp:336] pool8 needs backward computation.
-I0510 14:48:30.217646  5307 net.cpp:336] pool7_pool7_0_split needs backward computation.
-I0510 14:48:30.217654  5307 net.cpp:336] pool7 needs backward computation.
-I0510 14:48:30.217664  5307 net.cpp:336] pool6_pool6_0_split needs backward computation.
-I0510 14:48:30.217671  5307 net.cpp:336] pool6 needs backward computation.
-I0510 14:48:30.217679  5307 net.cpp:336] conv6/sep_relu6/sep_0_split needs backward computation.
-I0510 14:48:30.217689  5307 net.cpp:336] relu6/sep needs backward computation.
-I0510 14:48:30.217697  5307 net.cpp:336] conv6/sep/scale needs backward computation.
-I0510 14:48:30.217705  5307 net.cpp:336] conv6/sep/bn needs backward computation.
-I0510 14:48:30.217713  5307 net.cpp:336] conv6/sep needs backward computation.
-I0510 14:48:30.217721  5307 net.cpp:336] relu6/dw needs backward computation.
-I0510 14:48:30.217730  5307 net.cpp:336] conv6/dw/scale needs backward computation.
-I0510 14:48:30.217738  5307 net.cpp:336] conv6/dw/bn needs backward computation.
-I0510 14:48:30.217747  5307 net.cpp:336] conv6/dw needs backward computation.
-I0510 14:48:30.217756  5307 net.cpp:336] relu5_6/sep needs backward computation.
-I0510 14:48:30.217766  5307 net.cpp:336] conv5_6/sep/scale needs backward computation.
-I0510 14:48:30.217774  5307 net.cpp:336] conv5_6/sep/bn needs backward computation.
-I0510 14:48:30.217782  5307 net.cpp:336] conv5_6/sep needs backward computation.
-I0510 14:48:30.217792  5307 net.cpp:336] relu5_6/dw needs backward computation.
-I0510 14:48:30.217800  5307 net.cpp:336] conv5_6/dw/scale needs backward computation.
-I0510 14:48:30.217808  5307 net.cpp:336] conv5_6/dw/bn needs backward computation.
-I0510 14:48:30.217816  5307 net.cpp:336] conv5_6/dw needs backward computation.
-I0510 14:48:30.217825  5307 net.cpp:336] conv5_5/sep_relu5_5/sep_0_split needs backward computation.
-I0510 14:48:30.217834  5307 net.cpp:336] relu5_5/sep needs backward computation.
-I0510 14:48:30.217842  5307 net.cpp:336] conv5_5/sep/scale needs backward computation.
-I0510 14:48:30.217850  5307 net.cpp:336] conv5_5/sep/bn needs backward computation.
-I0510 14:48:30.217859  5307 net.cpp:336] conv5_5/sep needs backward computation.
-I0510 14:48:30.217866  5307 net.cpp:336] relu5_5/dw needs backward computation.
-I0510 14:48:30.217875  5307 net.cpp:336] conv5_5/dw/scale needs backward computation.
-I0510 14:48:30.217883  5307 net.cpp:336] conv5_5/dw/bn needs backward computation.
-I0510 14:48:30.217891  5307 net.cpp:336] conv5_5/dw needs backward computation.
-I0510 14:48:30.217900  5307 net.cpp:336] relu5_4/sep needs backward computation.
-I0510 14:48:30.217908  5307 net.cpp:336] conv5_4/sep/scale needs backward computation.
-I0510 14:48:30.217916  5307 net.cpp:336] conv5_4/sep/bn needs backward computation.
-I0510 14:48:30.217924  5307 net.cpp:336] conv5_4/sep needs backward computation.
-I0510 14:48:30.217932  5307 net.cpp:336] relu5_4/dw needs backward computation.
-I0510 14:48:30.217941  5307 net.cpp:336] conv5_4/dw/scale needs backward computation.
-I0510 14:48:30.217949  5307 net.cpp:336] conv5_4/dw/bn needs backward computation.
-I0510 14:48:30.217959  5307 net.cpp:336] conv5_4/dw needs backward computation.
-I0510 14:48:30.217969  5307 net.cpp:336] relu5_3/sep needs backward computation.
-I0510 14:48:30.217978  5307 net.cpp:336] conv5_3/sep/scale needs backward computation.
-I0510 14:48:30.217988  5307 net.cpp:336] conv5_3/sep/bn needs backward computation.
-I0510 14:48:30.217998  5307 net.cpp:336] conv5_3/sep needs backward computation.
-I0510 14:48:30.218006  5307 net.cpp:336] relu5_3/dw needs backward computation.
-I0510 14:48:30.218016  5307 net.cpp:336] conv5_3/dw/scale needs backward computation.
-I0510 14:48:30.218026  5307 net.cpp:336] conv5_3/dw/bn needs backward computation.
-I0510 14:48:30.218035  5307 net.cpp:336] conv5_3/dw needs backward computation.
-I0510 14:48:30.218045  5307 net.cpp:336] relu5_2/sep needs backward computation.
-I0510 14:48:30.218058  5307 net.cpp:336] conv5_2/sep/scale needs backward computation.
-I0510 14:48:30.218072  5307 net.cpp:336] conv5_2/sep/bn needs backward computation.
-I0510 14:48:30.218082  5307 net.cpp:336] conv5_2/sep needs backward computation.
-I0510 14:48:30.218091  5307 net.cpp:336] relu5_2/dw needs backward computation.
-I0510 14:48:30.218101  5307 net.cpp:336] conv5_2/dw/scale needs backward computation.
-I0510 14:48:30.218111  5307 net.cpp:336] conv5_2/dw/bn needs backward computation.
-I0510 14:48:30.218120  5307 net.cpp:336] conv5_2/dw needs backward computation.
-I0510 14:48:30.218130  5307 net.cpp:336] relu5_1/sep needs backward computation.
-I0510 14:48:30.218140  5307 net.cpp:336] conv5_1/sep/scale needs backward computation.
-I0510 14:48:30.218150  5307 net.cpp:336] conv5_1/sep/bn needs backward computation.
-I0510 14:48:30.218160  5307 net.cpp:336] conv5_1/sep needs backward computation.
-I0510 14:48:30.218169  5307 net.cpp:336] relu5_1/dw needs backward computation.
-I0510 14:48:30.218179  5307 net.cpp:336] conv5_1/dw/scale needs backward computation.
-I0510 14:48:30.218189  5307 net.cpp:336] conv5_1/dw/bn needs backward computation.
-I0510 14:48:30.218199  5307 net.cpp:336] conv5_1/dw needs backward computation.
-I0510 14:48:30.218209  5307 net.cpp:336] relu4_2/sep needs backward computation.
-I0510 14:48:30.218219  5307 net.cpp:336] conv4_2/sep/scale needs backward computation.
-I0510 14:48:30.218227  5307 net.cpp:336] conv4_2/sep/bn needs backward computation.
-I0510 14:48:30.218237  5307 net.cpp:336] conv4_2/sep needs backward computation.
-I0510 14:48:30.218247  5307 net.cpp:336] relu4_2/dw needs backward computation.
-I0510 14:48:30.218256  5307 net.cpp:336] conv4_2/dw/scale needs backward computation.
-I0510 14:48:30.218266  5307 net.cpp:336] conv4_2/dw/bn needs backward computation.
-I0510 14:48:30.218276  5307 net.cpp:336] conv4_2/dw needs backward computation.
-I0510 14:48:30.218286  5307 net.cpp:336] relu4_1/sep needs backward computation.
-I0510 14:48:30.218295  5307 net.cpp:336] conv4_1/sep/scale needs backward computation.
-I0510 14:48:30.218305  5307 net.cpp:336] conv4_1/sep/bn needs backward computation.
-I0510 14:48:30.218314  5307 net.cpp:336] conv4_1/sep needs backward computation.
-I0510 14:48:30.218324  5307 net.cpp:336] relu4_1/dw needs backward computation.
-I0510 14:48:30.218334  5307 net.cpp:336] conv4_1/dw/scale needs backward computation.
-I0510 14:48:30.218343  5307 net.cpp:336] conv4_1/dw/bn needs backward computation.
-I0510 14:48:30.218353  5307 net.cpp:336] conv4_1/dw needs backward computation.
-I0510 14:48:30.218364  5307 net.cpp:336] relu3_2/sep needs backward computation.
-I0510 14:48:30.218372  5307 net.cpp:336] conv3_2/sep/scale needs backward computation.
-I0510 14:48:30.218382  5307 net.cpp:336] conv3_2/sep/bn needs backward computation.
-I0510 14:48:30.218392  5307 net.cpp:336] conv3_2/sep needs backward computation.
-I0510 14:48:30.218402  5307 net.cpp:336] relu3_2/dw needs backward computation.
-I0510 14:48:30.218411  5307 net.cpp:336] conv3_2/dw/scale needs backward computation.
-I0510 14:48:30.218421  5307 net.cpp:336] conv3_2/dw/bn needs backward computation.
-I0510 14:48:30.218430  5307 net.cpp:336] conv3_2/dw needs backward computation.
-I0510 14:48:30.218441  5307 net.cpp:336] relu3_1/sep needs backward computation.
-I0510 14:48:30.218451  5307 net.cpp:336] conv3_1/sep/scale needs backward computation.
-I0510 14:48:30.218459  5307 net.cpp:336] conv3_1/sep/bn needs backward computation.
-I0510 14:48:30.218469  5307 net.cpp:336] conv3_1/sep needs backward computation.
-I0510 14:48:30.218479  5307 net.cpp:336] relu3_1/dw needs backward computation.
-I0510 14:48:30.218488  5307 net.cpp:336] conv3_1/dw/scale needs backward computation.
-I0510 14:48:30.218497  5307 net.cpp:336] conv3_1/dw/bn needs backward computation.
-I0510 14:48:30.218508  5307 net.cpp:336] conv3_1/dw needs backward computation.
-I0510 14:48:30.218518  5307 net.cpp:336] relu2_2/sep needs backward computation.
-I0510 14:48:30.218528  5307 net.cpp:336] conv2_2/sep/scale needs backward computation.
-I0510 14:48:30.218539  5307 net.cpp:336] conv2_2/sep/bn needs backward computation.
-I0510 14:48:30.218554  5307 net.cpp:336] conv2_2/sep needs backward computation.
-I0510 14:48:30.218562  5307 net.cpp:336] relu2_2/dw needs backward computation.
-I0510 14:48:30.218571  5307 net.cpp:336] conv2_2/dw/scale needs backward computation.
-I0510 14:48:30.218580  5307 net.cpp:336] conv2_2/dw/bn needs backward computation.
-I0510 14:48:30.218586  5307 net.cpp:336] conv2_2/dw needs backward computation.
-I0510 14:48:30.218595  5307 net.cpp:336] relu2_1/sep needs backward computation.
-I0510 14:48:30.218602  5307 net.cpp:336] conv2_1/sep/scale needs backward computation.
-I0510 14:48:30.218611  5307 net.cpp:336] conv2_1/sep/bn needs backward computation.
-I0510 14:48:30.218618  5307 net.cpp:336] conv2_1/sep needs backward computation.
-I0510 14:48:30.218626  5307 net.cpp:336] relu2_1/dw needs backward computation.
-I0510 14:48:30.218634  5307 net.cpp:336] conv2_1/dw/scale needs backward computation.
-I0510 14:48:30.218642  5307 net.cpp:336] conv2_1/dw/bn needs backward computation.
-I0510 14:48:30.218650  5307 net.cpp:336] conv2_1/dw needs backward computation.
-I0510 14:48:30.218658  5307 net.cpp:336] relu1 needs backward computation.
-I0510 14:48:30.218667  5307 net.cpp:336] conv1/scale needs backward computation.
-I0510 14:48:30.218673  5307 net.cpp:336] conv1/bn needs backward computation.
-I0510 14:48:30.218681  5307 net.cpp:336] conv1 needs backward computation.
-I0510 14:48:30.218691  5307 net.cpp:338] data/bias does not need backward computation.
-I0510 14:48:30.218700  5307 net.cpp:338] data_data_0_split does not need backward computation.
-I0510 14:48:30.218709  5307 net.cpp:338] data does not need backward computation.
-I0510 14:48:30.218717  5307 net.cpp:380] This network produces output mbox_loss
-I0510 14:48:30.218881  5307 net.cpp:403] Top memory (TRAIN) required for data: 2150578120 diff: 2150578120
-I0510 14:48:30.218894  5307 net.cpp:406] Bottom memory (TRAIN) required for data: 2150578112 diff: 2150578112
-I0510 14:48:30.218901  5307 net.cpp:409] Shared (in-place) memory (TRAIN) by data: 1358299136 diff: 1358299136
-I0510 14:48:30.218910  5307 net.cpp:412] Parameters memory (TRAIN) required for data: 9462808 diff: 9462808
-I0510 14:48:30.218919  5307 net.cpp:415] Parameters shared memory (TRAIN) by data: 0 diff: 0
-I0510 14:48:30.218926  5307 net.cpp:421] Network initialization done.
-I0510 14:48:30.221627  5307 solver.cpp:175] Creating test net (#0) specified by test_net file: training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/test.prototxt
-I0510 14:48:30.222658  5307 net.cpp:80] Initializing net from parameters: 
-name: "mobiledetnet-0.5_test"
-state {
-  phase: TEST
-}
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 8
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_1/sep/scale"
-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/dw/scale"
-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/dw"
-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/sep"
-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "conv6/sep/scale"
-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu6/sep"
-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool8"
-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-}
-layer {
-  name: "ctx_output1"
-  type: "Convolution"
-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output1/relu"
-  type: "ReLU"
-  bottom: "ctx_output1"
-  top: "ctx_output1"
-}
-layer {
-  name: "ctx_output2/1x1"
-  type: "Convolution"
-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
-  name: "ctx_output2"
-  type: "Convolution"
-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output2/relu"
-  type: "ReLU"
-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
-  name: "ctx_output3/1x1"
-  type: "Convolution"
-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
-  name: "ctx_output3"
-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/relu"
-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19
-    max_size: 88
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx_output2/rel
-I0510 14:48:30.223242  5307 net.cpp:110] Using FLOAT as default forward math type
-I0510 14:48:30.223258  5307 net.cpp:116] Using FLOAT as default backward math type
-I0510 14:48:30.223271  5307 layer_factory.hpp:172] Creating layer 'data' of type 'AnnotatedData'
-I0510 14:48:30.223291  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.223315  5307 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0510 14:48:30.224280  5307 net.cpp:200] Created Layer data (0)
-I0510 14:48:30.224289  5307 net.cpp:542] data -> data
-I0510 14:48:30.224298  5307 net.cpp:542] data -> label
-I0510 14:48:30.224310  5307 data_reader.cpp:58] Data Reader threads: 1, out queues: 1, depth: 8
-I0510 14:48:30.224318  5307 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0510 14:48:30.225162  5353 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb
-I0510 14:48:30.226320  5307 annotated_data_layer.cpp:105] output data size: 8,3,256,512
-I0510 14:48:30.226392  5307 annotated_data_layer.cpp:150] (0) Output data size: 8, 3, 256, 512
-I0510 14:48:30.226428  5307 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0510 14:48:30.226449  5307 net.cpp:260] Setting up data
-I0510 14:48:30.226456  5307 net.cpp:267] TEST Top shape for layer 0 'data' 8 3 256 512 (3145728)
-I0510 14:48:30.227767  5354 data_layer.cpp:105] (0) Parser threads: 1
-I0510 14:48:30.227777  5354 data_layer.cpp:107] (0) Transformer threads: 1
-I0510 14:48:30.227795  5307 net.cpp:267] TEST Top shape for layer 0 'data' 1 1 2 8 (16)
-I0510 14:48:30.227813  5307 layer_factory.hpp:172] Creating layer 'data_data_0_split' of type 'Split'
-I0510 14:48:30.227828  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.227845  5307 net.cpp:200] Created Layer data_data_0_split (1)
-I0510 14:48:30.227859  5307 net.cpp:572] data_data_0_split <- data
-I0510 14:48:30.227874  5307 net.cpp:542] data_data_0_split -> data_data_0_split_0
-I0510 14:48:30.227890  5307 net.cpp:542] data_data_0_split -> data_data_0_split_1
-I0510 14:48:30.227902  5307 net.cpp:542] data_data_0_split -> data_data_0_split_2
-I0510 14:48:30.227917  5307 net.cpp:542] data_data_0_split -> data_data_0_split_3
-I0510 14:48:30.227931  5307 net.cpp:542] data_data_0_split -> data_data_0_split_4
-I0510 14:48:30.227943  5307 net.cpp:542] data_data_0_split -> data_data_0_split_5
-I0510 14:48:30.228044  5307 net.cpp:260] Setting up data_data_0_split
-I0510 14:48:30.228060  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228075  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228087  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228101  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228114  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228127  5307 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 8 3 256 512 (3145728)
-I0510 14:48:30.228140  5307 layer_factory.hpp:172] Creating layer 'data/bias' of type 'Bias'
-I0510 14:48:30.228154  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.228170  5307 net.cpp:200] Created Layer data/bias (2)
-I0510 14:48:30.228183  5307 net.cpp:572] data/bias <- data_data_0_split_0
-I0510 14:48:30.228196  5307 net.cpp:542] data/bias -> data/bias
-I0510 14:48:30.228427  5307 net.cpp:260] Setting up data/bias
-I0510 14:48:30.228446  5307 net.cpp:267] TEST Top shape for layer 2 'data/bias' 8 3 256 512 (3145728)
-I0510 14:48:30.228464  5307 layer_factory.hpp:172] Creating layer 'conv1' of type 'Convolution'
-I0510 14:48:30.228478  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.228498  5307 net.cpp:200] Created Layer conv1 (3)
-I0510 14:48:30.228513  5307 net.cpp:572] conv1 <- data/bias
-I0510 14:48:30.228540  5307 net.cpp:542] conv1 -> conv1
-I0510 14:48:30.228772  5307 net.cpp:260] Setting up conv1
-I0510 14:48:30.228781  5307 net.cpp:267] TEST Top shape for layer 3 'conv1' 8 16 128 256 (4194304)
-I0510 14:48:30.228788  5307 layer_factory.hpp:172] Creating layer 'conv1/bn' of type 'BatchNorm'
-I0510 14:48:30.228801  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.228811  5307 net.cpp:200] Created Layer conv1/bn (4)
-I0510 14:48:30.228814  5307 net.cpp:572] conv1/bn <- conv1
-I0510 14:48:30.228818  5307 net.cpp:527] conv1/bn -> conv1 (in-place)
-I0510 14:48:30.242122  5307 net.cpp:260] Setting up conv1/bn
-I0510 14:48:30.242146  5307 net.cpp:267] TEST Top shape for layer 4 'conv1/bn' 8 16 128 256 (4194304)
-I0510 14:48:30.242161  5307 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Scale'
-I0510 14:48:30.242178  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242193  5307 net.cpp:200] Created Layer conv1/scale (5)
-I0510 14:48:30.242205  5307 net.cpp:572] conv1/scale <- conv1
-I0510 14:48:30.242216  5307 net.cpp:527] conv1/scale -> conv1 (in-place)
-I0510 14:48:30.242266  5307 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Bias'
-I0510 14:48:30.242278  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242435  5307 net.cpp:260] Setting up conv1/scale
-I0510 14:48:30.242456  5307 net.cpp:267] TEST Top shape for layer 5 'conv1/scale' 8 16 128 256 (4194304)
-I0510 14:48:30.242472  5307 layer_factory.hpp:172] Creating layer 'relu1' of type 'ReLU'
-I0510 14:48:30.242486  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242501  5307 net.cpp:200] Created Layer relu1 (6)
-I0510 14:48:30.242513  5307 net.cpp:572] relu1 <- conv1
-I0510 14:48:30.242527  5307 net.cpp:527] relu1 -> conv1 (in-place)
-I0510 14:48:30.242547  5307 net.cpp:260] Setting up relu1
-I0510 14:48:30.242563  5307 net.cpp:267] TEST Top shape for layer 6 'relu1' 8 16 128 256 (4194304)
-I0510 14:48:30.242575  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw' of type 'Convolution'
-I0510 14:48:30.242588  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242612  5307 net.cpp:200] Created Layer conv2_1/dw (7)
-I0510 14:48:30.242625  5307 net.cpp:572] conv2_1/dw <- conv1
-I0510 14:48:30.242638  5307 net.cpp:542] conv2_1/dw -> conv2_1/dw
-I0510 14:48:30.242871  5307 net.cpp:260] Setting up conv2_1/dw
-I0510 14:48:30.242893  5307 net.cpp:267] TEST Top shape for layer 7 'conv2_1/dw' 8 16 128 256 (4194304)
-I0510 14:48:30.242910  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.242925  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.242943  5307 net.cpp:200] Created Layer conv2_1/dw/bn (8)
-I0510 14:48:30.242957  5307 net.cpp:572] conv2_1/dw/bn <- conv2_1/dw
-I0510 14:48:30.242971  5307 net.cpp:527] conv2_1/dw/bn -> conv2_1/dw (in-place)
-I0510 14:48:30.243391  5307 net.cpp:260] Setting up conv2_1/dw/bn
-I0510 14:48:30.243412  5307 net.cpp:267] TEST Top shape for layer 8 'conv2_1/dw/bn' 8 16 128 256 (4194304)
-I0510 14:48:30.243432  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Scale'
-I0510 14:48:30.243445  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.243461  5307 net.cpp:200] Created Layer conv2_1/dw/scale (9)
-I0510 14:48:30.243475  5307 net.cpp:572] conv2_1/dw/scale <- conv2_1/dw
-I0510 14:48:30.243489  5307 net.cpp:527] conv2_1/dw/scale -> conv2_1/dw (in-place)
-I0510 14:48:30.243537  5307 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Bias'
-I0510 14:48:30.243553  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.243713  5307 net.cpp:260] Setting up conv2_1/dw/scale
-I0510 14:48:30.243731  5307 net.cpp:267] TEST Top shape for layer 9 'conv2_1/dw/scale' 8 16 128 256 (4194304)
-I0510 14:48:30.243748  5307 layer_factory.hpp:172] Creating layer 'relu2_1/dw' of type 'ReLU'
-I0510 14:48:30.243767  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.243791  5307 net.cpp:200] Created Layer relu2_1/dw (10)
-I0510 14:48:30.243805  5307 net.cpp:572] relu2_1/dw <- conv2_1/dw
-I0510 14:48:30.243819  5307 net.cpp:527] relu2_1/dw -> conv2_1/dw (in-place)
-I0510 14:48:30.243835  5307 net.cpp:260] Setting up relu2_1/dw
-I0510 14:48:30.243849  5307 net.cpp:267] TEST Top shape for layer 10 'relu2_1/dw' 8 16 128 256 (4194304)
-I0510 14:48:30.243863  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep' of type 'Convolution'
-I0510 14:48:30.243876  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.243896  5307 net.cpp:200] Created Layer conv2_1/sep (11)
-I0510 14:48:30.243911  5307 net.cpp:572] conv2_1/sep <- conv2_1/dw
-I0510 14:48:30.243927  5307 net.cpp:542] conv2_1/sep -> conv2_1/sep
-I0510 14:48:30.244163  5307 net.cpp:260] Setting up conv2_1/sep
-I0510 14:48:30.244171  5307 net.cpp:267] TEST Top shape for layer 11 'conv2_1/sep' 8 32 128 256 (8388608)
-I0510 14:48:30.244179  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.244184  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244190  5307 net.cpp:200] Created Layer conv2_1/sep/bn (12)
-I0510 14:48:30.244194  5307 net.cpp:572] conv2_1/sep/bn <- conv2_1/sep
-I0510 14:48:30.244199  5307 net.cpp:527] conv2_1/sep/bn -> conv2_1/sep (in-place)
-I0510 14:48:30.244614  5307 net.cpp:260] Setting up conv2_1/sep/bn
-I0510 14:48:30.244623  5307 net.cpp:267] TEST Top shape for layer 12 'conv2_1/sep/bn' 8 32 128 256 (8388608)
-I0510 14:48:30.244632  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Scale'
-I0510 14:48:30.244637  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244642  5307 net.cpp:200] Created Layer conv2_1/sep/scale (13)
-I0510 14:48:30.244647  5307 net.cpp:572] conv2_1/sep/scale <- conv2_1/sep
-I0510 14:48:30.244650  5307 net.cpp:527] conv2_1/sep/scale -> conv2_1/sep (in-place)
-I0510 14:48:30.244686  5307 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Bias'
-I0510 14:48:30.244701  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244850  5307 net.cpp:260] Setting up conv2_1/sep/scale
-I0510 14:48:30.244863  5307 net.cpp:267] TEST Top shape for layer 13 'conv2_1/sep/scale' 8 32 128 256 (8388608)
-I0510 14:48:30.244875  5307 layer_factory.hpp:172] Creating layer 'relu2_1/sep' of type 'ReLU'
-I0510 14:48:30.244884  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244894  5307 net.cpp:200] Created Layer relu2_1/sep (14)
-I0510 14:48:30.244902  5307 net.cpp:572] relu2_1/sep <- conv2_1/sep
-I0510 14:48:30.244911  5307 net.cpp:527] relu2_1/sep -> conv2_1/sep (in-place)
-I0510 14:48:30.244922  5307 net.cpp:260] Setting up relu2_1/sep
-I0510 14:48:30.244932  5307 net.cpp:267] TEST Top shape for layer 14 'relu2_1/sep' 8 32 128 256 (8388608)
-I0510 14:48:30.244941  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw' of type 'Convolution'
-I0510 14:48:30.244951  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.244962  5307 net.cpp:200] Created Layer conv2_2/dw (15)
-I0510 14:48:30.244971  5307 net.cpp:572] conv2_2/dw <- conv2_1/sep
-I0510 14:48:30.244979  5307 net.cpp:542] conv2_2/dw -> conv2_2/dw
-I0510 14:48:30.245188  5307 net.cpp:260] Setting up conv2_2/dw
-I0510 14:48:30.245209  5307 net.cpp:267] TEST Top shape for layer 15 'conv2_2/dw' 8 32 64 128 (2097152)
-I0510 14:48:30.245224  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.245237  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.245254  5307 net.cpp:200] Created Layer conv2_2/dw/bn (16)
-I0510 14:48:30.245270  5307 net.cpp:572] conv2_2/dw/bn <- conv2_2/dw
-I0510 14:48:30.245283  5307 net.cpp:527] conv2_2/dw/bn -> conv2_2/dw (in-place)
-I0510 14:48:30.245674  5307 net.cpp:260] Setting up conv2_2/dw/bn
-I0510 14:48:30.245693  5307 net.cpp:267] TEST Top shape for layer 16 'conv2_2/dw/bn' 8 32 64 128 (2097152)
-I0510 14:48:30.245710  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Scale'
-I0510 14:48:30.245724  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.245738  5307 net.cpp:200] Created Layer conv2_2/dw/scale (17)
-I0510 14:48:30.245751  5307 net.cpp:572] conv2_2/dw/scale <- conv2_2/dw
-I0510 14:48:30.245764  5307 net.cpp:527] conv2_2/dw/scale -> conv2_2/dw (in-place)
-I0510 14:48:30.245811  5307 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Bias'
-I0510 14:48:30.245826  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.245949  5307 net.cpp:260] Setting up conv2_2/dw/scale
-I0510 14:48:30.245966  5307 net.cpp:267] TEST Top shape for layer 17 'conv2_2/dw/scale' 8 32 64 128 (2097152)
-I0510 14:48:30.245982  5307 layer_factory.hpp:172] Creating layer 'relu2_2/dw' of type 'ReLU'
-I0510 14:48:30.245995  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.246008  5307 net.cpp:200] Created Layer relu2_2/dw (18)
-I0510 14:48:30.246021  5307 net.cpp:572] relu2_2/dw <- conv2_2/dw
-I0510 14:48:30.246035  5307 net.cpp:527] relu2_2/dw -> conv2_2/dw (in-place)
-I0510 14:48:30.246049  5307 net.cpp:260] Setting up relu2_2/dw
-I0510 14:48:30.246063  5307 net.cpp:267] TEST Top shape for layer 18 'relu2_2/dw' 8 32 64 128 (2097152)
-I0510 14:48:30.246076  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep' of type 'Convolution'
-I0510 14:48:30.246093  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.246112  5307 net.cpp:200] Created Layer conv2_2/sep (19)
-I0510 14:48:30.246125  5307 net.cpp:572] conv2_2/sep <- conv2_2/dw
-I0510 14:48:30.246139  5307 net.cpp:542] conv2_2/sep -> conv2_2/sep
-I0510 14:48:30.246407  5307 net.cpp:260] Setting up conv2_2/sep
-I0510 14:48:30.246417  5307 net.cpp:267] TEST Top shape for layer 19 'conv2_2/sep' 8 64 64 128 (4194304)
-I0510 14:48:30.246421  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.246425  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.246431  5307 net.cpp:200] Created Layer conv2_2/sep/bn (20)
-I0510 14:48:30.246435  5307 net.cpp:572] conv2_2/sep/bn <- conv2_2/sep
-I0510 14:48:30.246439  5307 net.cpp:527] conv2_2/sep/bn -> conv2_2/sep (in-place)
-I0510 14:48:30.246834  5307 net.cpp:260] Setting up conv2_2/sep/bn
-I0510 14:48:30.246841  5307 net.cpp:267] TEST Top shape for layer 20 'conv2_2/sep/bn' 8 64 64 128 (4194304)
-I0510 14:48:30.246850  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Scale'
-I0510 14:48:30.246853  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.246860  5307 net.cpp:200] Created Layer conv2_2/sep/scale (21)
-I0510 14:48:30.246862  5307 net.cpp:572] conv2_2/sep/scale <- conv2_2/sep
-I0510 14:48:30.246866  5307 net.cpp:527] conv2_2/sep/scale -> conv2_2/sep (in-place)
-I0510 14:48:30.246904  5307 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Bias'
-I0510 14:48:30.246909  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247018  5307 net.cpp:260] Setting up conv2_2/sep/scale
-I0510 14:48:30.247025  5307 net.cpp:267] TEST Top shape for layer 21 'conv2_2/sep/scale' 8 64 64 128 (4194304)
-I0510 14:48:30.247032  5307 layer_factory.hpp:172] Creating layer 'relu2_2/sep' of type 'ReLU'
-I0510 14:48:30.247036  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247041  5307 net.cpp:200] Created Layer relu2_2/sep (22)
-I0510 14:48:30.247045  5307 net.cpp:572] relu2_2/sep <- conv2_2/sep
-I0510 14:48:30.247058  5307 net.cpp:527] relu2_2/sep -> conv2_2/sep (in-place)
-I0510 14:48:30.247064  5307 net.cpp:260] Setting up relu2_2/sep
-I0510 14:48:30.247068  5307 net.cpp:267] TEST Top shape for layer 22 'relu2_2/sep' 8 64 64 128 (4194304)
-I0510 14:48:30.247072  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw' of type 'Convolution'
-I0510 14:48:30.247076  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247084  5307 net.cpp:200] Created Layer conv3_1/dw (23)
-I0510 14:48:30.247088  5307 net.cpp:572] conv3_1/dw <- conv2_2/sep
-I0510 14:48:30.247092  5307 net.cpp:542] conv3_1/dw -> conv3_1/dw
-I0510 14:48:30.247303  5307 net.cpp:260] Setting up conv3_1/dw
-I0510 14:48:30.247310  5307 net.cpp:267] TEST Top shape for layer 23 'conv3_1/dw' 8 64 64 128 (4194304)
-I0510 14:48:30.247316  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.247321  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247328  5307 net.cpp:200] Created Layer conv3_1/dw/bn (24)
-I0510 14:48:30.247333  5307 net.cpp:572] conv3_1/dw/bn <- conv3_1/dw
-I0510 14:48:30.247337  5307 net.cpp:527] conv3_1/dw/bn -> conv3_1/dw (in-place)
-I0510 14:48:30.247715  5307 net.cpp:260] Setting up conv3_1/dw/bn
-I0510 14:48:30.247725  5307 net.cpp:267] TEST Top shape for layer 24 'conv3_1/dw/bn' 8 64 64 128 (4194304)
-I0510 14:48:30.247738  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Scale'
-I0510 14:48:30.247743  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247751  5307 net.cpp:200] Created Layer conv3_1/dw/scale (25)
-I0510 14:48:30.247756  5307 net.cpp:572] conv3_1/dw/scale <- conv3_1/dw
-I0510 14:48:30.247761  5307 net.cpp:527] conv3_1/dw/scale -> conv3_1/dw (in-place)
-I0510 14:48:30.247802  5307 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Bias'
-I0510 14:48:30.247807  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247918  5307 net.cpp:260] Setting up conv3_1/dw/scale
-I0510 14:48:30.247925  5307 net.cpp:267] TEST Top shape for layer 25 'conv3_1/dw/scale' 8 64 64 128 (4194304)
-I0510 14:48:30.247941  5307 layer_factory.hpp:172] Creating layer 'relu3_1/dw' of type 'ReLU'
-I0510 14:48:30.247951  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.247962  5307 net.cpp:200] Created Layer relu3_1/dw (26)
-I0510 14:48:30.247972  5307 net.cpp:572] relu3_1/dw <- conv3_1/dw
-I0510 14:48:30.247982  5307 net.cpp:527] relu3_1/dw -> conv3_1/dw (in-place)
-I0510 14:48:30.247993  5307 net.cpp:260] Setting up relu3_1/dw
-I0510 14:48:30.248004  5307 net.cpp:267] TEST Top shape for layer 26 'relu3_1/dw' 8 64 64 128 (4194304)
-I0510 14:48:30.248014  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep' of type 'Convolution'
-I0510 14:48:30.248024  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.248037  5307 net.cpp:200] Created Layer conv3_1/sep (27)
-I0510 14:48:30.248047  5307 net.cpp:572] conv3_1/sep <- conv3_1/dw
-I0510 14:48:30.248057  5307 net.cpp:542] conv3_1/sep -> conv3_1/sep
-I0510 14:48:30.248392  5307 net.cpp:260] Setting up conv3_1/sep
-I0510 14:48:30.248400  5307 net.cpp:267] TEST Top shape for layer 27 'conv3_1/sep' 8 64 64 128 (4194304)
-I0510 14:48:30.248407  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.248411  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.248417  5307 net.cpp:200] Created Layer conv3_1/sep/bn (28)
-I0510 14:48:30.248421  5307 net.cpp:572] conv3_1/sep/bn <- conv3_1/sep
-I0510 14:48:30.248426  5307 net.cpp:527] conv3_1/sep/bn -> conv3_1/sep (in-place)
-I0510 14:48:30.248793  5307 net.cpp:260] Setting up conv3_1/sep/bn
-I0510 14:48:30.248801  5307 net.cpp:267] TEST Top shape for layer 28 'conv3_1/sep/bn' 8 64 64 128 (4194304)
-I0510 14:48:30.248826  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Scale'
-I0510 14:48:30.248831  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.248837  5307 net.cpp:200] Created Layer conv3_1/sep/scale (29)
-I0510 14:48:30.248842  5307 net.cpp:572] conv3_1/sep/scale <- conv3_1/sep
-I0510 14:48:30.248845  5307 net.cpp:527] conv3_1/sep/scale -> conv3_1/sep (in-place)
-I0510 14:48:30.248880  5307 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Bias'
-I0510 14:48:30.248893  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249006  5307 net.cpp:260] Setting up conv3_1/sep/scale
-I0510 14:48:30.249013  5307 net.cpp:267] TEST Top shape for layer 29 'conv3_1/sep/scale' 8 64 64 128 (4194304)
-I0510 14:48:30.249020  5307 layer_factory.hpp:172] Creating layer 'relu3_1/sep' of type 'ReLU'
-I0510 14:48:30.249025  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249030  5307 net.cpp:200] Created Layer relu3_1/sep (30)
-I0510 14:48:30.249034  5307 net.cpp:572] relu3_1/sep <- conv3_1/sep
-I0510 14:48:30.249039  5307 net.cpp:527] relu3_1/sep -> conv3_1/sep (in-place)
-I0510 14:48:30.249044  5307 net.cpp:260] Setting up relu3_1/sep
-I0510 14:48:30.249049  5307 net.cpp:267] TEST Top shape for layer 30 'relu3_1/sep' 8 64 64 128 (4194304)
-I0510 14:48:30.249053  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw' of type 'Convolution'
-I0510 14:48:30.249058  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249065  5307 net.cpp:200] Created Layer conv3_2/dw (31)
-I0510 14:48:30.249069  5307 net.cpp:572] conv3_2/dw <- conv3_1/sep
-I0510 14:48:30.249074  5307 net.cpp:542] conv3_2/dw -> conv3_2/dw
-I0510 14:48:30.249277  5307 net.cpp:260] Setting up conv3_2/dw
-I0510 14:48:30.249285  5307 net.cpp:267] TEST Top shape for layer 31 'conv3_2/dw' 8 64 32 64 (1048576)
-I0510 14:48:30.249291  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.249296  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249305  5307 net.cpp:200] Created Layer conv3_2/dw/bn (32)
-I0510 14:48:30.249310  5307 net.cpp:572] conv3_2/dw/bn <- conv3_2/dw
-I0510 14:48:30.249315  5307 net.cpp:527] conv3_2/dw/bn -> conv3_2/dw (in-place)
-I0510 14:48:30.249661  5307 net.cpp:260] Setting up conv3_2/dw/bn
-I0510 14:48:30.249670  5307 net.cpp:267] TEST Top shape for layer 32 'conv3_2/dw/bn' 8 64 32 64 (1048576)
-I0510 14:48:30.249685  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Scale'
-I0510 14:48:30.249694  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249706  5307 net.cpp:200] Created Layer conv3_2/dw/scale (33)
-I0510 14:48:30.249714  5307 net.cpp:572] conv3_2/dw/scale <- conv3_2/dw
-I0510 14:48:30.249723  5307 net.cpp:527] conv3_2/dw/scale -> conv3_2/dw (in-place)
-I0510 14:48:30.249765  5307 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Bias'
-I0510 14:48:30.249776  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249883  5307 net.cpp:260] Setting up conv3_2/dw/scale
-I0510 14:48:30.249891  5307 net.cpp:267] TEST Top shape for layer 33 'conv3_2/dw/scale' 8 64 32 64 (1048576)
-I0510 14:48:30.249898  5307 layer_factory.hpp:172] Creating layer 'relu3_2/dw' of type 'ReLU'
-I0510 14:48:30.249903  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249908  5307 net.cpp:200] Created Layer relu3_2/dw (34)
-I0510 14:48:30.249913  5307 net.cpp:572] relu3_2/dw <- conv3_2/dw
-I0510 14:48:30.249917  5307 net.cpp:527] relu3_2/dw -> conv3_2/dw (in-place)
-I0510 14:48:30.249923  5307 net.cpp:260] Setting up relu3_2/dw
-I0510 14:48:30.249938  5307 net.cpp:267] TEST Top shape for layer 34 'relu3_2/dw' 8 64 32 64 (1048576)
-I0510 14:48:30.249953  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep' of type 'Convolution'
-I0510 14:48:30.249963  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.249975  5307 net.cpp:200] Created Layer conv3_2/sep (35)
-I0510 14:48:30.249984  5307 net.cpp:572] conv3_2/sep <- conv3_2/dw
-I0510 14:48:30.249992  5307 net.cpp:542] conv3_2/sep -> conv3_2/sep
-I0510 14:48:30.250567  5307 net.cpp:260] Setting up conv3_2/sep
-I0510 14:48:30.250586  5307 net.cpp:267] TEST Top shape for layer 35 'conv3_2/sep' 8 128 32 64 (2097152)
-I0510 14:48:30.250597  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.250604  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.250614  5307 net.cpp:200] Created Layer conv3_2/sep/bn (36)
-I0510 14:48:30.250622  5307 net.cpp:572] conv3_2/sep/bn <- conv3_2/sep
-I0510 14:48:30.250630  5307 net.cpp:527] conv3_2/sep/bn -> conv3_2/sep (in-place)
-I0510 14:48:30.251098  5307 net.cpp:260] Setting up conv3_2/sep/bn
-I0510 14:48:30.251116  5307 net.cpp:267] TEST Top shape for layer 36 'conv3_2/sep/bn' 8 128 32 64 (2097152)
-I0510 14:48:30.251128  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Scale'
-I0510 14:48:30.251137  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251147  5307 net.cpp:200] Created Layer conv3_2/sep/scale (37)
-I0510 14:48:30.251157  5307 net.cpp:572] conv3_2/sep/scale <- conv3_2/sep
-I0510 14:48:30.251164  5307 net.cpp:527] conv3_2/sep/scale -> conv3_2/sep (in-place)
-I0510 14:48:30.251205  5307 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Bias'
-I0510 14:48:30.251215  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251317  5307 net.cpp:260] Setting up conv3_2/sep/scale
-I0510 14:48:30.251330  5307 net.cpp:267] TEST Top shape for layer 37 'conv3_2/sep/scale' 8 128 32 64 (2097152)
-I0510 14:48:30.251341  5307 layer_factory.hpp:172] Creating layer 'relu3_2/sep' of type 'ReLU'
-I0510 14:48:30.251350  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251360  5307 net.cpp:200] Created Layer relu3_2/sep (38)
-I0510 14:48:30.251369  5307 net.cpp:572] relu3_2/sep <- conv3_2/sep
-I0510 14:48:30.251379  5307 net.cpp:527] relu3_2/sep -> conv3_2/sep (in-place)
-I0510 14:48:30.251389  5307 net.cpp:260] Setting up relu3_2/sep
-I0510 14:48:30.251399  5307 net.cpp:267] TEST Top shape for layer 38 'relu3_2/sep' 8 128 32 64 (2097152)
-I0510 14:48:30.251407  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw' of type 'Convolution'
-I0510 14:48:30.251416  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251430  5307 net.cpp:200] Created Layer conv4_1/dw (39)
-I0510 14:48:30.251438  5307 net.cpp:572] conv4_1/dw <- conv3_2/sep
-I0510 14:48:30.251447  5307 net.cpp:542] conv4_1/dw -> conv4_1/dw
-I0510 14:48:30.251679  5307 net.cpp:260] Setting up conv4_1/dw
-I0510 14:48:30.251698  5307 net.cpp:267] TEST Top shape for layer 39 'conv4_1/dw' 8 128 32 64 (2097152)
-I0510 14:48:30.251710  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.251720  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.251732  5307 net.cpp:200] Created Layer conv4_1/dw/bn (40)
-I0510 14:48:30.251742  5307 net.cpp:572] conv4_1/dw/bn <- conv4_1/dw
-I0510 14:48:30.251752  5307 net.cpp:527] conv4_1/dw/bn -> conv4_1/dw (in-place)
-I0510 14:48:30.252107  5307 net.cpp:260] Setting up conv4_1/dw/bn
-I0510 14:48:30.252125  5307 net.cpp:267] TEST Top shape for layer 40 'conv4_1/dw/bn' 8 128 32 64 (2097152)
-I0510 14:48:30.252138  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Scale'
-I0510 14:48:30.252153  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.252174  5307 net.cpp:200] Created Layer conv4_1/dw/scale (41)
-I0510 14:48:30.252184  5307 net.cpp:572] conv4_1/dw/scale <- conv4_1/dw
-I0510 14:48:30.252193  5307 net.cpp:527] conv4_1/dw/scale -> conv4_1/dw (in-place)
-I0510 14:48:30.252236  5307 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Bias'
-I0510 14:48:30.252249  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.252357  5307 net.cpp:260] Setting up conv4_1/dw/scale
-I0510 14:48:30.252372  5307 net.cpp:267] TEST Top shape for layer 41 'conv4_1/dw/scale' 8 128 32 64 (2097152)
-I0510 14:48:30.252387  5307 layer_factory.hpp:172] Creating layer 'relu4_1/dw' of type 'ReLU'
-I0510 14:48:30.252398  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.252408  5307 net.cpp:200] Created Layer relu4_1/dw (42)
-I0510 14:48:30.252418  5307 net.cpp:572] relu4_1/dw <- conv4_1/dw
-I0510 14:48:30.252429  5307 net.cpp:527] relu4_1/dw -> conv4_1/dw (in-place)
-I0510 14:48:30.252442  5307 net.cpp:260] Setting up relu4_1/dw
-I0510 14:48:30.252454  5307 net.cpp:267] TEST Top shape for layer 42 'relu4_1/dw' 8 128 32 64 (2097152)
-I0510 14:48:30.252465  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep' of type 'Convolution'
-I0510 14:48:30.252475  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.252490  5307 net.cpp:200] Created Layer conv4_1/sep (43)
-I0510 14:48:30.252501  5307 net.cpp:572] conv4_1/sep <- conv4_1/dw
-I0510 14:48:30.252511  5307 net.cpp:542] conv4_1/sep -> conv4_1/sep
-I0510 14:48:30.253233  5307 net.cpp:260] Setting up conv4_1/sep
-I0510 14:48:30.253252  5307 net.cpp:267] TEST Top shape for layer 43 'conv4_1/sep' 8 128 32 64 (2097152)
-I0510 14:48:30.253264  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.253273  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253284  5307 net.cpp:200] Created Layer conv4_1/sep/bn (44)
-I0510 14:48:30.253293  5307 net.cpp:572] conv4_1/sep/bn <- conv4_1/sep
-I0510 14:48:30.253302  5307 net.cpp:527] conv4_1/sep/bn -> conv4_1/sep (in-place)
-I0510 14:48:30.253645  5307 net.cpp:260] Setting up conv4_1/sep/bn
-I0510 14:48:30.253659  5307 net.cpp:267] TEST Top shape for layer 44 'conv4_1/sep/bn' 8 128 32 64 (2097152)
-I0510 14:48:30.253674  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Scale'
-I0510 14:48:30.253684  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253695  5307 net.cpp:200] Created Layer conv4_1/sep/scale (45)
-I0510 14:48:30.253705  5307 net.cpp:572] conv4_1/sep/scale <- conv4_1/sep
-I0510 14:48:30.253713  5307 net.cpp:527] conv4_1/sep/scale -> conv4_1/sep (in-place)
-I0510 14:48:30.253756  5307 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Bias'
-I0510 14:48:30.253767  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253870  5307 net.cpp:260] Setting up conv4_1/sep/scale
-I0510 14:48:30.253882  5307 net.cpp:267] TEST Top shape for layer 45 'conv4_1/sep/scale' 8 128 32 64 (2097152)
-I0510 14:48:30.253895  5307 layer_factory.hpp:172] Creating layer 'relu4_1/sep' of type 'ReLU'
-I0510 14:48:30.253902  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253912  5307 net.cpp:200] Created Layer relu4_1/sep (46)
-I0510 14:48:30.253921  5307 net.cpp:572] relu4_1/sep <- conv4_1/sep
-I0510 14:48:30.253929  5307 net.cpp:527] relu4_1/sep -> conv4_1/sep (in-place)
-I0510 14:48:30.253939  5307 net.cpp:260] Setting up relu4_1/sep
-I0510 14:48:30.253949  5307 net.cpp:267] TEST Top shape for layer 46 'relu4_1/sep' 8 128 32 64 (2097152)
-I0510 14:48:30.253957  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw' of type 'Convolution'
-I0510 14:48:30.253969  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.253988  5307 net.cpp:200] Created Layer conv4_2/dw (47)
-I0510 14:48:30.253998  5307 net.cpp:572] conv4_2/dw <- conv4_1/sep
-I0510 14:48:30.254006  5307 net.cpp:542] conv4_2/dw -> conv4_2/dw
-I0510 14:48:30.254235  5307 net.cpp:260] Setting up conv4_2/dw
-I0510 14:48:30.254248  5307 net.cpp:267] TEST Top shape for layer 47 'conv4_2/dw' 8 128 16 32 (524288)
-I0510 14:48:30.254259  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.254268  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254278  5307 net.cpp:200] Created Layer conv4_2/dw/bn (48)
-I0510 14:48:30.254287  5307 net.cpp:572] conv4_2/dw/bn <- conv4_2/dw
-I0510 14:48:30.254297  5307 net.cpp:527] conv4_2/dw/bn -> conv4_2/dw (in-place)
-I0510 14:48:30.254638  5307 net.cpp:260] Setting up conv4_2/dw/bn
-I0510 14:48:30.254652  5307 net.cpp:267] TEST Top shape for layer 48 'conv4_2/dw/bn' 8 128 16 32 (524288)
-I0510 14:48:30.254663  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Scale'
-I0510 14:48:30.254673  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254683  5307 net.cpp:200] Created Layer conv4_2/dw/scale (49)
-I0510 14:48:30.254691  5307 net.cpp:572] conv4_2/dw/scale <- conv4_2/dw
-I0510 14:48:30.254699  5307 net.cpp:527] conv4_2/dw/scale -> conv4_2/dw (in-place)
-I0510 14:48:30.254740  5307 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Bias'
-I0510 14:48:30.254750  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254853  5307 net.cpp:260] Setting up conv4_2/dw/scale
-I0510 14:48:30.254865  5307 net.cpp:267] TEST Top shape for layer 49 'conv4_2/dw/scale' 8 128 16 32 (524288)
-I0510 14:48:30.254876  5307 layer_factory.hpp:172] Creating layer 'relu4_2/dw' of type 'ReLU'
-I0510 14:48:30.254885  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254895  5307 net.cpp:200] Created Layer relu4_2/dw (50)
-I0510 14:48:30.254906  5307 net.cpp:572] relu4_2/dw <- conv4_2/dw
-I0510 14:48:30.254916  5307 net.cpp:527] relu4_2/dw -> conv4_2/dw (in-place)
-I0510 14:48:30.254928  5307 net.cpp:260] Setting up relu4_2/dw
-I0510 14:48:30.254940  5307 net.cpp:267] TEST Top shape for layer 50 'relu4_2/dw' 8 128 16 32 (524288)
-I0510 14:48:30.254951  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep' of type 'Convolution'
-I0510 14:48:30.254961  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.254974  5307 net.cpp:200] Created Layer conv4_2/sep (51)
-I0510 14:48:30.254982  5307 net.cpp:572] conv4_2/sep <- conv4_2/dw
-I0510 14:48:30.254992  5307 net.cpp:542] conv4_2/sep -> conv4_2/sep
-I0510 14:48:30.256186  5307 net.cpp:260] Setting up conv4_2/sep
-I0510 14:48:30.256203  5307 net.cpp:267] TEST Top shape for layer 51 'conv4_2/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.256216  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.256224  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256237  5307 net.cpp:200] Created Layer conv4_2/sep/bn (52)
-I0510 14:48:30.256247  5307 net.cpp:572] conv4_2/sep/bn <- conv4_2/sep
-I0510 14:48:30.256256  5307 net.cpp:527] conv4_2/sep/bn -> conv4_2/sep (in-place)
-I0510 14:48:30.256623  5307 net.cpp:260] Setting up conv4_2/sep/bn
-I0510 14:48:30.256640  5307 net.cpp:267] TEST Top shape for layer 52 'conv4_2/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.256654  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Scale'
-I0510 14:48:30.256664  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256675  5307 net.cpp:200] Created Layer conv4_2/sep/scale (53)
-I0510 14:48:30.256683  5307 net.cpp:572] conv4_2/sep/scale <- conv4_2/sep
-I0510 14:48:30.256696  5307 net.cpp:527] conv4_2/sep/scale -> conv4_2/sep (in-place)
-I0510 14:48:30.256747  5307 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Bias'
-I0510 14:48:30.256757  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256861  5307 net.cpp:260] Setting up conv4_2/sep/scale
-I0510 14:48:30.256873  5307 net.cpp:267] TEST Top shape for layer 53 'conv4_2/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.256886  5307 layer_factory.hpp:172] Creating layer 'relu4_2/sep' of type 'ReLU'
-I0510 14:48:30.256893  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256903  5307 net.cpp:200] Created Layer relu4_2/sep (54)
-I0510 14:48:30.256912  5307 net.cpp:572] relu4_2/sep <- conv4_2/sep
-I0510 14:48:30.256920  5307 net.cpp:527] relu4_2/sep -> conv4_2/sep (in-place)
-I0510 14:48:30.256932  5307 net.cpp:260] Setting up relu4_2/sep
-I0510 14:48:30.256940  5307 net.cpp:267] TEST Top shape for layer 54 'relu4_2/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.256949  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw' of type 'Convolution'
-I0510 14:48:30.256958  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.256971  5307 net.cpp:200] Created Layer conv5_1/dw (55)
-I0510 14:48:30.256980  5307 net.cpp:572] conv5_1/dw <- conv4_2/sep
-I0510 14:48:30.256989  5307 net.cpp:542] conv5_1/dw -> conv5_1/dw
-I0510 14:48:30.257251  5307 net.cpp:260] Setting up conv5_1/dw
-I0510 14:48:30.257264  5307 net.cpp:267] TEST Top shape for layer 55 'conv5_1/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.257275  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.257284  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257295  5307 net.cpp:200] Created Layer conv5_1/dw/bn (56)
-I0510 14:48:30.257304  5307 net.cpp:572] conv5_1/dw/bn <- conv5_1/dw
-I0510 14:48:30.257313  5307 net.cpp:527] conv5_1/dw/bn -> conv5_1/dw (in-place)
-I0510 14:48:30.257652  5307 net.cpp:260] Setting up conv5_1/dw/bn
-I0510 14:48:30.257665  5307 net.cpp:267] TEST Top shape for layer 56 'conv5_1/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.257678  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Scale'
-I0510 14:48:30.257686  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257697  5307 net.cpp:200] Created Layer conv5_1/dw/scale (57)
-I0510 14:48:30.257706  5307 net.cpp:572] conv5_1/dw/scale <- conv5_1/dw
-I0510 14:48:30.257714  5307 net.cpp:527] conv5_1/dw/scale -> conv5_1/dw (in-place)
-I0510 14:48:30.257757  5307 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Bias'
-I0510 14:48:30.257767  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257871  5307 net.cpp:260] Setting up conv5_1/dw/scale
-I0510 14:48:30.257884  5307 net.cpp:267] TEST Top shape for layer 57 'conv5_1/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.257895  5307 layer_factory.hpp:172] Creating layer 'relu5_1/dw' of type 'ReLU'
-I0510 14:48:30.257903  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257912  5307 net.cpp:200] Created Layer relu5_1/dw (58)
-I0510 14:48:30.257921  5307 net.cpp:572] relu5_1/dw <- conv5_1/dw
-I0510 14:48:30.257930  5307 net.cpp:527] relu5_1/dw -> conv5_1/dw (in-place)
-I0510 14:48:30.257941  5307 net.cpp:260] Setting up relu5_1/dw
-I0510 14:48:30.257951  5307 net.cpp:267] TEST Top shape for layer 58 'relu5_1/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.257958  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep' of type 'Convolution'
-I0510 14:48:30.257967  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.257982  5307 net.cpp:200] Created Layer conv5_1/sep (59)
-I0510 14:48:30.257990  5307 net.cpp:572] conv5_1/sep <- conv5_1/dw
-I0510 14:48:30.258002  5307 net.cpp:542] conv5_1/sep -> conv5_1/sep
-I0510 14:48:30.260092  5307 net.cpp:260] Setting up conv5_1/sep
-I0510 14:48:30.260109  5307 net.cpp:267] TEST Top shape for layer 59 'conv5_1/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.260119  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.260128  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260138  5307 net.cpp:200] Created Layer conv5_1/sep/bn (60)
-I0510 14:48:30.260145  5307 net.cpp:572] conv5_1/sep/bn <- conv5_1/sep
-I0510 14:48:30.260154  5307 net.cpp:527] conv5_1/sep/bn -> conv5_1/sep (in-place)
-I0510 14:48:30.260478  5307 net.cpp:260] Setting up conv5_1/sep/bn
-I0510 14:48:30.260491  5307 net.cpp:267] TEST Top shape for layer 60 'conv5_1/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.260504  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Scale'
-I0510 14:48:30.260514  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260529  5307 net.cpp:200] Created Layer conv5_1/sep/scale (61)
-I0510 14:48:30.260540  5307 net.cpp:572] conv5_1/sep/scale <- conv5_1/sep
-I0510 14:48:30.260550  5307 net.cpp:527] conv5_1/sep/scale -> conv5_1/sep (in-place)
-I0510 14:48:30.260593  5307 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Bias'
-I0510 14:48:30.260604  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260711  5307 net.cpp:260] Setting up conv5_1/sep/scale
-I0510 14:48:30.260723  5307 net.cpp:267] TEST Top shape for layer 61 'conv5_1/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.260735  5307 layer_factory.hpp:172] Creating layer 'relu5_1/sep' of type 'ReLU'
-I0510 14:48:30.260743  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260752  5307 net.cpp:200] Created Layer relu5_1/sep (62)
-I0510 14:48:30.260761  5307 net.cpp:572] relu5_1/sep <- conv5_1/sep
-I0510 14:48:30.260771  5307 net.cpp:527] relu5_1/sep -> conv5_1/sep (in-place)
-I0510 14:48:30.260782  5307 net.cpp:260] Setting up relu5_1/sep
-I0510 14:48:30.260792  5307 net.cpp:267] TEST Top shape for layer 62 'relu5_1/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.260800  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw' of type 'Convolution'
-I0510 14:48:30.260809  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.260821  5307 net.cpp:200] Created Layer conv5_2/dw (63)
-I0510 14:48:30.260830  5307 net.cpp:572] conv5_2/dw <- conv5_1/sep
-I0510 14:48:30.260838  5307 net.cpp:542] conv5_2/dw -> conv5_2/dw
-I0510 14:48:30.261092  5307 net.cpp:260] Setting up conv5_2/dw
-I0510 14:48:30.261106  5307 net.cpp:267] TEST Top shape for layer 63 'conv5_2/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.261116  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.261124  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261135  5307 net.cpp:200] Created Layer conv5_2/dw/bn (64)
-I0510 14:48:30.261144  5307 net.cpp:572] conv5_2/dw/bn <- conv5_2/dw
-I0510 14:48:30.261152  5307 net.cpp:527] conv5_2/dw/bn -> conv5_2/dw (in-place)
-I0510 14:48:30.261476  5307 net.cpp:260] Setting up conv5_2/dw/bn
-I0510 14:48:30.261487  5307 net.cpp:267] TEST Top shape for layer 64 'conv5_2/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.261499  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Scale'
-I0510 14:48:30.261507  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261519  5307 net.cpp:200] Created Layer conv5_2/dw/scale (65)
-I0510 14:48:30.261528  5307 net.cpp:572] conv5_2/dw/scale <- conv5_2/dw
-I0510 14:48:30.261535  5307 net.cpp:527] conv5_2/dw/scale -> conv5_2/dw (in-place)
-I0510 14:48:30.261574  5307 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Bias'
-I0510 14:48:30.261586  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261684  5307 net.cpp:260] Setting up conv5_2/dw/scale
-I0510 14:48:30.261696  5307 net.cpp:267] TEST Top shape for layer 65 'conv5_2/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.261708  5307 layer_factory.hpp:172] Creating layer 'relu5_2/dw' of type 'ReLU'
-I0510 14:48:30.261715  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261723  5307 net.cpp:200] Created Layer relu5_2/dw (66)
-I0510 14:48:30.261732  5307 net.cpp:572] relu5_2/dw <- conv5_2/dw
-I0510 14:48:30.261740  5307 net.cpp:527] relu5_2/dw -> conv5_2/dw (in-place)
-I0510 14:48:30.261749  5307 net.cpp:260] Setting up relu5_2/dw
-I0510 14:48:30.261759  5307 net.cpp:267] TEST Top shape for layer 66 'relu5_2/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.261766  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep' of type 'Convolution'
-I0510 14:48:30.261775  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.261786  5307 net.cpp:200] Created Layer conv5_2/sep (67)
-I0510 14:48:30.261795  5307 net.cpp:572] conv5_2/sep <- conv5_2/dw
-I0510 14:48:30.261802  5307 net.cpp:542] conv5_2/sep -> conv5_2/sep
-I0510 14:48:30.263923  5307 net.cpp:260] Setting up conv5_2/sep
-I0510 14:48:30.263937  5307 net.cpp:267] TEST Top shape for layer 67 'conv5_2/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.263947  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.263955  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.263967  5307 net.cpp:200] Created Layer conv5_2/sep/bn (68)
-I0510 14:48:30.263975  5307 net.cpp:572] conv5_2/sep/bn <- conv5_2/sep
-I0510 14:48:30.263983  5307 net.cpp:527] conv5_2/sep/bn -> conv5_2/sep (in-place)
-I0510 14:48:30.264274  5307 net.cpp:260] Setting up conv5_2/sep/bn
-I0510 14:48:30.264288  5307 net.cpp:267] TEST Top shape for layer 68 'conv5_2/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.264300  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Scale'
-I0510 14:48:30.264310  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264320  5307 net.cpp:200] Created Layer conv5_2/sep/scale (69)
-I0510 14:48:30.264329  5307 net.cpp:572] conv5_2/sep/scale <- conv5_2/sep
-I0510 14:48:30.264338  5307 net.cpp:527] conv5_2/sep/scale -> conv5_2/sep (in-place)
-I0510 14:48:30.264381  5307 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Bias'
-I0510 14:48:30.264392  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264497  5307 net.cpp:260] Setting up conv5_2/sep/scale
-I0510 14:48:30.264510  5307 net.cpp:267] TEST Top shape for layer 69 'conv5_2/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.264521  5307 layer_factory.hpp:172] Creating layer 'relu5_2/sep' of type 'ReLU'
-I0510 14:48:30.264536  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264545  5307 net.cpp:200] Created Layer relu5_2/sep (70)
-I0510 14:48:30.264554  5307 net.cpp:572] relu5_2/sep <- conv5_2/sep
-I0510 14:48:30.264564  5307 net.cpp:527] relu5_2/sep -> conv5_2/sep (in-place)
-I0510 14:48:30.264575  5307 net.cpp:260] Setting up relu5_2/sep
-I0510 14:48:30.264585  5307 net.cpp:267] TEST Top shape for layer 70 'relu5_2/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.264592  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw' of type 'Convolution'
-I0510 14:48:30.264601  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264616  5307 net.cpp:200] Created Layer conv5_3/dw (71)
-I0510 14:48:30.264626  5307 net.cpp:572] conv5_3/dw <- conv5_2/sep
-I0510 14:48:30.264633  5307 net.cpp:542] conv5_3/dw -> conv5_3/dw
-I0510 14:48:30.264899  5307 net.cpp:260] Setting up conv5_3/dw
-I0510 14:48:30.264914  5307 net.cpp:267] TEST Top shape for layer 71 'conv5_3/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.264930  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.264946  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.264956  5307 net.cpp:200] Created Layer conv5_3/dw/bn (72)
-I0510 14:48:30.264966  5307 net.cpp:572] conv5_3/dw/bn <- conv5_3/dw
-I0510 14:48:30.264974  5307 net.cpp:527] conv5_3/dw/bn -> conv5_3/dw (in-place)
-I0510 14:48:30.265358  5307 net.cpp:260] Setting up conv5_3/dw/bn
-I0510 14:48:30.265375  5307 net.cpp:267] TEST Top shape for layer 72 'conv5_3/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.265388  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Scale'
-I0510 14:48:30.265398  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.265409  5307 net.cpp:200] Created Layer conv5_3/dw/scale (73)
-I0510 14:48:30.265419  5307 net.cpp:572] conv5_3/dw/scale <- conv5_3/dw
-I0510 14:48:30.265429  5307 net.cpp:527] conv5_3/dw/scale -> conv5_3/dw (in-place)
-I0510 14:48:30.265482  5307 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Bias'
-I0510 14:48:30.265493  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.265604  5307 net.cpp:260] Setting up conv5_3/dw/scale
-I0510 14:48:30.265615  5307 net.cpp:267] TEST Top shape for layer 73 'conv5_3/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.265626  5307 layer_factory.hpp:172] Creating layer 'relu5_3/dw' of type 'ReLU'
-I0510 14:48:30.265635  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.265643  5307 net.cpp:200] Created Layer relu5_3/dw (74)
-I0510 14:48:30.265651  5307 net.cpp:572] relu5_3/dw <- conv5_3/dw
-I0510 14:48:30.265658  5307 net.cpp:527] relu5_3/dw -> conv5_3/dw (in-place)
-I0510 14:48:30.265668  5307 net.cpp:260] Setting up relu5_3/dw
-I0510 14:48:30.265676  5307 net.cpp:267] TEST Top shape for layer 74 'relu5_3/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.265684  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep' of type 'Convolution'
-I0510 14:48:30.265692  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.265704  5307 net.cpp:200] Created Layer conv5_3/sep (75)
-I0510 14:48:30.265712  5307 net.cpp:572] conv5_3/sep <- conv5_3/dw
-I0510 14:48:30.265720  5307 net.cpp:542] conv5_3/sep -> conv5_3/sep
-I0510 14:48:30.277580  5307 net.cpp:260] Setting up conv5_3/sep
-I0510 14:48:30.277678  5307 net.cpp:267] TEST Top shape for layer 75 'conv5_3/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.277724  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.277750  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.277782  5307 net.cpp:200] Created Layer conv5_3/sep/bn (76)
-I0510 14:48:30.277806  5307 net.cpp:572] conv5_3/sep/bn <- conv5_3/sep
-I0510 14:48:30.277829  5307 net.cpp:527] conv5_3/sep/bn -> conv5_3/sep (in-place)
-I0510 14:48:30.278512  5307 net.cpp:260] Setting up conv5_3/sep/bn
-I0510 14:48:30.278524  5307 net.cpp:267] TEST Top shape for layer 76 'conv5_3/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.278535  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Scale'
-I0510 14:48:30.278543  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.278571  5307 net.cpp:200] Created Layer conv5_3/sep/scale (77)
-I0510 14:48:30.278589  5307 net.cpp:572] conv5_3/sep/scale <- conv5_3/sep
-I0510 14:48:30.278605  5307 net.cpp:527] conv5_3/sep/scale -> conv5_3/sep (in-place)
-I0510 14:48:30.278686  5307 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Bias'
-I0510 14:48:30.278695  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.279238  5307 net.cpp:260] Setting up conv5_3/sep/scale
-I0510 14:48:30.279259  5307 net.cpp:267] TEST Top shape for layer 77 'conv5_3/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.279630  5307 layer_factory.hpp:172] Creating layer 'relu5_3/sep' of type 'ReLU'
-I0510 14:48:30.279650  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.279662  5307 net.cpp:200] Created Layer relu5_3/sep (78)
-I0510 14:48:30.279671  5307 net.cpp:572] relu5_3/sep <- conv5_3/sep
-I0510 14:48:30.279681  5307 net.cpp:527] relu5_3/sep -> conv5_3/sep (in-place)
-I0510 14:48:30.279696  5307 net.cpp:260] Setting up relu5_3/sep
-I0510 14:48:30.279707  5307 net.cpp:267] TEST Top shape for layer 78 'relu5_3/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.279716  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw' of type 'Convolution'
-I0510 14:48:30.279726  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.279747  5307 net.cpp:200] Created Layer conv5_4/dw (79)
-I0510 14:48:30.279757  5307 net.cpp:572] conv5_4/dw <- conv5_3/sep
-I0510 14:48:30.279765  5307 net.cpp:542] conv5_4/dw -> conv5_4/dw
-I0510 14:48:30.280048  5307 net.cpp:260] Setting up conv5_4/dw
-I0510 14:48:30.280062  5307 net.cpp:267] TEST Top shape for layer 79 'conv5_4/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.280073  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.280082  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.280093  5307 net.cpp:200] Created Layer conv5_4/dw/bn (80)
-I0510 14:48:30.280102  5307 net.cpp:572] conv5_4/dw/bn <- conv5_4/dw
-I0510 14:48:30.280112  5307 net.cpp:527] conv5_4/dw/bn -> conv5_4/dw (in-place)
-I0510 14:48:30.281548  5307 net.cpp:260] Setting up conv5_4/dw/bn
-I0510 14:48:30.281565  5307 net.cpp:267] TEST Top shape for layer 80 'conv5_4/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.281579  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Scale'
-I0510 14:48:30.281587  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.281599  5307 net.cpp:200] Created Layer conv5_4/dw/scale (81)
-I0510 14:48:30.281606  5307 net.cpp:572] conv5_4/dw/scale <- conv5_4/dw
-I0510 14:48:30.281615  5307 net.cpp:527] conv5_4/dw/scale -> conv5_4/dw (in-place)
-I0510 14:48:30.281661  5307 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Bias'
-I0510 14:48:30.281672  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.281785  5307 net.cpp:260] Setting up conv5_4/dw/scale
-I0510 14:48:30.281801  5307 net.cpp:267] TEST Top shape for layer 81 'conv5_4/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.281816  5307 layer_factory.hpp:172] Creating layer 'relu5_4/dw' of type 'ReLU'
-I0510 14:48:30.281826  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.281837  5307 net.cpp:200] Created Layer relu5_4/dw (82)
-I0510 14:48:30.281848  5307 net.cpp:572] relu5_4/dw <- conv5_4/dw
-I0510 14:48:30.281859  5307 net.cpp:527] relu5_4/dw -> conv5_4/dw (in-place)
-I0510 14:48:30.281872  5307 net.cpp:260] Setting up relu5_4/dw
-I0510 14:48:30.282164  5307 net.cpp:267] TEST Top shape for layer 82 'relu5_4/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.282176  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep' of type 'Convolution'
-I0510 14:48:30.282184  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.282199  5307 net.cpp:200] Created Layer conv5_4/sep (83)
-I0510 14:48:30.282209  5307 net.cpp:572] conv5_4/sep <- conv5_4/dw
-I0510 14:48:30.282219  5307 net.cpp:542] conv5_4/sep -> conv5_4/sep
-I0510 14:48:30.288540  5307 net.cpp:260] Setting up conv5_4/sep
-I0510 14:48:30.288624  5307 net.cpp:267] TEST Top shape for layer 83 'conv5_4/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.288655  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.288674  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.288705  5307 net.cpp:200] Created Layer conv5_4/sep/bn (84)
-I0510 14:48:30.288733  5307 net.cpp:572] conv5_4/sep/bn <- conv5_4/sep
-I0510 14:48:30.288749  5307 net.cpp:527] conv5_4/sep/bn -> conv5_4/sep (in-place)
-I0510 14:48:30.289172  5307 net.cpp:260] Setting up conv5_4/sep/bn
-I0510 14:48:30.289194  5307 net.cpp:267] TEST Top shape for layer 84 'conv5_4/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.289214  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Scale'
-I0510 14:48:30.289229  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.289247  5307 net.cpp:200] Created Layer conv5_4/sep/scale (85)
-I0510 14:48:30.289263  5307 net.cpp:572] conv5_4/sep/scale <- conv5_4/sep
-I0510 14:48:30.289278  5307 net.cpp:527] conv5_4/sep/scale -> conv5_4/sep (in-place)
-I0510 14:48:30.289335  5307 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Bias'
-I0510 14:48:30.289351  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.289476  5307 net.cpp:260] Setting up conv5_4/sep/scale
-I0510 14:48:30.289496  5307 net.cpp:267] TEST Top shape for layer 85 'conv5_4/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.289515  5307 layer_factory.hpp:172] Creating layer 'relu5_4/sep' of type 'ReLU'
-I0510 14:48:30.289530  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.289546  5307 net.cpp:200] Created Layer relu5_4/sep (86)
-I0510 14:48:30.289561  5307 net.cpp:572] relu5_4/sep <- conv5_4/sep
-I0510 14:48:30.289575  5307 net.cpp:527] relu5_4/sep -> conv5_4/sep (in-place)
-I0510 14:48:30.289592  5307 net.cpp:260] Setting up relu5_4/sep
-I0510 14:48:30.289608  5307 net.cpp:267] TEST Top shape for layer 86 'relu5_4/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.289626  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw' of type 'Convolution'
-I0510 14:48:30.289643  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.289662  5307 net.cpp:200] Created Layer conv5_5/dw (87)
-I0510 14:48:30.289677  5307 net.cpp:572] conv5_5/dw <- conv5_4/sep
-I0510 14:48:30.289691  5307 net.cpp:542] conv5_5/dw -> conv5_5/dw
-I0510 14:48:30.289973  5307 net.cpp:260] Setting up conv5_5/dw
-I0510 14:48:30.289995  5307 net.cpp:267] TEST Top shape for layer 87 'conv5_5/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.290016  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.290036  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.290056  5307 net.cpp:200] Created Layer conv5_5/dw/bn (88)
-I0510 14:48:30.290076  5307 net.cpp:572] conv5_5/dw/bn <- conv5_5/dw
-I0510 14:48:30.290094  5307 net.cpp:527] conv5_5/dw/bn -> conv5_5/dw (in-place)
-I0510 14:48:30.290571  5307 net.cpp:260] Setting up conv5_5/dw/bn
-I0510 14:48:30.290596  5307 net.cpp:267] TEST Top shape for layer 88 'conv5_5/dw/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.290626  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Scale'
-I0510 14:48:30.290642  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.290661  5307 net.cpp:200] Created Layer conv5_5/dw/scale (89)
-I0510 14:48:30.290678  5307 net.cpp:572] conv5_5/dw/scale <- conv5_5/dw
-I0510 14:48:30.290693  5307 net.cpp:527] conv5_5/dw/scale -> conv5_5/dw (in-place)
-I0510 14:48:30.290745  5307 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Bias'
-I0510 14:48:30.290763  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.290879  5307 net.cpp:260] Setting up conv5_5/dw/scale
-I0510 14:48:30.290900  5307 net.cpp:267] TEST Top shape for layer 89 'conv5_5/dw/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.290920  5307 layer_factory.hpp:172] Creating layer 'relu5_5/dw' of type 'ReLU'
-I0510 14:48:30.290935  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.290956  5307 net.cpp:200] Created Layer relu5_5/dw (90)
-I0510 14:48:30.290980  5307 net.cpp:572] relu5_5/dw <- conv5_5/dw
-I0510 14:48:30.290997  5307 net.cpp:527] relu5_5/dw -> conv5_5/dw (in-place)
-I0510 14:48:30.291014  5307 net.cpp:260] Setting up relu5_5/dw
-I0510 14:48:30.291031  5307 net.cpp:267] TEST Top shape for layer 90 'relu5_5/dw' 8 256 16 32 (1048576)
-I0510 14:48:30.291046  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep' of type 'Convolution'
-I0510 14:48:30.291062  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.291085  5307 net.cpp:200] Created Layer conv5_5/sep (91)
-I0510 14:48:30.291100  5307 net.cpp:572] conv5_5/sep <- conv5_5/dw
-I0510 14:48:30.291116  5307 net.cpp:542] conv5_5/sep -> conv5_5/sep
-I0510 14:48:30.295755  5307 net.cpp:260] Setting up conv5_5/sep
-I0510 14:48:30.295776  5307 net.cpp:267] TEST Top shape for layer 91 'conv5_5/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.295784  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.295789  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.295799  5307 net.cpp:200] Created Layer conv5_5/sep/bn (92)
-I0510 14:48:30.295804  5307 net.cpp:572] conv5_5/sep/bn <- conv5_5/sep
-I0510 14:48:30.295809  5307 net.cpp:527] conv5_5/sep/bn -> conv5_5/sep (in-place)
-I0510 14:48:30.296200  5307 net.cpp:260] Setting up conv5_5/sep/bn
-I0510 14:48:30.296209  5307 net.cpp:267] TEST Top shape for layer 92 'conv5_5/sep/bn' 8 256 16 32 (1048576)
-I0510 14:48:30.296223  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Scale'
-I0510 14:48:30.296231  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296252  5307 net.cpp:200] Created Layer conv5_5/sep/scale (93)
-I0510 14:48:30.296265  5307 net.cpp:572] conv5_5/sep/scale <- conv5_5/sep
-I0510 14:48:30.296277  5307 net.cpp:527] conv5_5/sep/scale -> conv5_5/sep (in-place)
-I0510 14:48:30.296329  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Bias'
-I0510 14:48:30.296336  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296476  5307 net.cpp:260] Setting up conv5_5/sep/scale
-I0510 14:48:30.296484  5307 net.cpp:267] TEST Top shape for layer 93 'conv5_5/sep/scale' 8 256 16 32 (1048576)
-I0510 14:48:30.296499  5307 layer_factory.hpp:172] Creating layer 'relu5_5/sep' of type 'ReLU'
-I0510 14:48:30.296509  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296520  5307 net.cpp:200] Created Layer relu5_5/sep (94)
-I0510 14:48:30.296541  5307 net.cpp:572] relu5_5/sep <- conv5_5/sep
-I0510 14:48:30.296551  5307 net.cpp:527] relu5_5/sep -> conv5_5/sep (in-place)
-I0510 14:48:30.296564  5307 net.cpp:260] Setting up relu5_5/sep
-I0510 14:48:30.296576  5307 net.cpp:267] TEST Top shape for layer 94 'relu5_5/sep' 8 256 16 32 (1048576)
-I0510 14:48:30.296584  5307 layer_factory.hpp:172] Creating layer 'conv5_5/sep_relu5_5/sep_0_split' of type 'Split'
-I0510 14:48:30.296594  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296604  5307 net.cpp:200] Created Layer conv5_5/sep_relu5_5/sep_0_split (95)
-I0510 14:48:30.296614  5307 net.cpp:572] conv5_5/sep_relu5_5/sep_0_split <- conv5_5/sep
-I0510 14:48:30.296623  5307 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_0
-I0510 14:48:30.296635  5307 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_1
-I0510 14:48:30.296679  5307 net.cpp:260] Setting up conv5_5/sep_relu5_5/sep_0_split
-I0510 14:48:30.296685  5307 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 8 256 16 32 (1048576)
-I0510 14:48:30.296691  5307 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 8 256 16 32 (1048576)
-I0510 14:48:30.296696  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw' of type 'Convolution'
-I0510 14:48:30.296710  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.296722  5307 net.cpp:200] Created Layer conv5_6/dw (96)
-I0510 14:48:30.296726  5307 net.cpp:572] conv5_6/dw <- conv5_5/sep_relu5_5/sep_0_split_0
-I0510 14:48:30.296731  5307 net.cpp:542] conv5_6/dw -> conv5_6/dw
-I0510 14:48:30.297003  5307 net.cpp:260] Setting up conv5_6/dw
-I0510 14:48:30.297011  5307 net.cpp:267] TEST Top shape for layer 96 'conv5_6/dw' 8 256 8 16 (262144)
-I0510 14:48:30.297017  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.297030  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297049  5307 net.cpp:200] Created Layer conv5_6/dw/bn (97)
-I0510 14:48:30.297062  5307 net.cpp:572] conv5_6/dw/bn <- conv5_6/dw
-I0510 14:48:30.297076  5307 net.cpp:527] conv5_6/dw/bn -> conv5_6/dw (in-place)
-I0510 14:48:30.297441  5307 net.cpp:260] Setting up conv5_6/dw/bn
-I0510 14:48:30.297461  5307 net.cpp:267] TEST Top shape for layer 97 'conv5_6/dw/bn' 8 256 8 16 (262144)
-I0510 14:48:30.297479  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Scale'
-I0510 14:48:30.297493  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297510  5307 net.cpp:200] Created Layer conv5_6/dw/scale (98)
-I0510 14:48:30.297524  5307 net.cpp:572] conv5_6/dw/scale <- conv5_6/dw
-I0510 14:48:30.297538  5307 net.cpp:527] conv5_6/dw/scale -> conv5_6/dw (in-place)
-I0510 14:48:30.297588  5307 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Bias'
-I0510 14:48:30.297605  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297725  5307 net.cpp:260] Setting up conv5_6/dw/scale
-I0510 14:48:30.297744  5307 net.cpp:267] TEST Top shape for layer 98 'conv5_6/dw/scale' 8 256 8 16 (262144)
-I0510 14:48:30.297760  5307 layer_factory.hpp:172] Creating layer 'relu5_6/dw' of type 'ReLU'
-I0510 14:48:30.297775  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297789  5307 net.cpp:200] Created Layer relu5_6/dw (99)
-I0510 14:48:30.297802  5307 net.cpp:572] relu5_6/dw <- conv5_6/dw
-I0510 14:48:30.297816  5307 net.cpp:527] relu5_6/dw -> conv5_6/dw (in-place)
-I0510 14:48:30.297832  5307 net.cpp:260] Setting up relu5_6/dw
-I0510 14:48:30.297839  5307 net.cpp:267] TEST Top shape for layer 99 'relu5_6/dw' 8 256 8 16 (262144)
-I0510 14:48:30.297843  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep' of type 'Convolution'
-I0510 14:48:30.297848  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.297857  5307 net.cpp:200] Created Layer conv5_6/sep (100)
-I0510 14:48:30.297860  5307 net.cpp:572] conv5_6/sep <- conv5_6/dw
-I0510 14:48:30.297864  5307 net.cpp:542] conv5_6/sep -> conv5_6/sep
-I0510 14:48:30.301995  5307 net.cpp:260] Setting up conv5_6/sep
-I0510 14:48:30.302006  5307 net.cpp:267] TEST Top shape for layer 100 'conv5_6/sep' 8 512 8 16 (524288)
-I0510 14:48:30.302012  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.302016  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302022  5307 net.cpp:200] Created Layer conv5_6/sep/bn (101)
-I0510 14:48:30.302027  5307 net.cpp:572] conv5_6/sep/bn <- conv5_6/sep
-I0510 14:48:30.302031  5307 net.cpp:527] conv5_6/sep/bn -> conv5_6/sep (in-place)
-I0510 14:48:30.302390  5307 net.cpp:260] Setting up conv5_6/sep/bn
-I0510 14:48:30.302413  5307 net.cpp:267] TEST Top shape for layer 101 'conv5_6/sep/bn' 8 512 8 16 (524288)
-I0510 14:48:30.302433  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Scale'
-I0510 14:48:30.302446  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302469  5307 net.cpp:200] Created Layer conv5_6/sep/scale (102)
-I0510 14:48:30.302484  5307 net.cpp:572] conv5_6/sep/scale <- conv5_6/sep
-I0510 14:48:30.302505  5307 net.cpp:527] conv5_6/sep/scale -> conv5_6/sep (in-place)
-I0510 14:48:30.302554  5307 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Bias'
-I0510 14:48:30.302570  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302696  5307 net.cpp:260] Setting up conv5_6/sep/scale
-I0510 14:48:30.302714  5307 net.cpp:267] TEST Top shape for layer 102 'conv5_6/sep/scale' 8 512 8 16 (524288)
-I0510 14:48:30.302731  5307 layer_factory.hpp:172] Creating layer 'relu5_6/sep' of type 'ReLU'
-I0510 14:48:30.302743  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302758  5307 net.cpp:200] Created Layer relu5_6/sep (103)
-I0510 14:48:30.302772  5307 net.cpp:572] relu5_6/sep <- conv5_6/sep
-I0510 14:48:30.302784  5307 net.cpp:527] relu5_6/sep -> conv5_6/sep (in-place)
-I0510 14:48:30.302799  5307 net.cpp:260] Setting up relu5_6/sep
-I0510 14:48:30.302814  5307 net.cpp:267] TEST Top shape for layer 103 'relu5_6/sep' 8 512 8 16 (524288)
-I0510 14:48:30.302826  5307 layer_factory.hpp:172] Creating layer 'conv6/dw' of type 'Convolution'
-I0510 14:48:30.302839  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.302856  5307 net.cpp:200] Created Layer conv6/dw (104)
-I0510 14:48:30.302870  5307 net.cpp:572] conv6/dw <- conv5_6/sep
-I0510 14:48:30.302882  5307 net.cpp:542] conv6/dw -> conv6/dw
-I0510 14:48:30.303230  5307 net.cpp:260] Setting up conv6/dw
-I0510 14:48:30.303238  5307 net.cpp:267] TEST Top shape for layer 104 'conv6/dw' 8 512 8 16 (524288)
-I0510 14:48:30.303262  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/bn' of type 'BatchNorm'
-I0510 14:48:30.303278  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.303295  5307 net.cpp:200] Created Layer conv6/dw/bn (105)
-I0510 14:48:30.303308  5307 net.cpp:572] conv6/dw/bn <- conv6/dw
-I0510 14:48:30.303320  5307 net.cpp:527] conv6/dw/bn -> conv6/dw (in-place)
-I0510 14:48:30.303689  5307 net.cpp:260] Setting up conv6/dw/bn
-I0510 14:48:30.303696  5307 net.cpp:267] TEST Top shape for layer 105 'conv6/dw/bn' 8 512 8 16 (524288)
-I0510 14:48:30.303721  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Scale'
-I0510 14:48:30.303735  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.303750  5307 net.cpp:200] Created Layer conv6/dw/scale (106)
-I0510 14:48:30.303763  5307 net.cpp:572] conv6/dw/scale <- conv6/dw
-I0510 14:48:30.303776  5307 net.cpp:527] conv6/dw/scale -> conv6/dw (in-place)
-I0510 14:48:30.303827  5307 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Bias'
-I0510 14:48:30.303833  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.303958  5307 net.cpp:260] Setting up conv6/dw/scale
-I0510 14:48:30.303972  5307 net.cpp:267] TEST Top shape for layer 106 'conv6/dw/scale' 8 512 8 16 (524288)
-I0510 14:48:30.303988  5307 layer_factory.hpp:172] Creating layer 'relu6/dw' of type 'ReLU'
-I0510 14:48:30.304003  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.304016  5307 net.cpp:200] Created Layer relu6/dw (107)
-I0510 14:48:30.304029  5307 net.cpp:572] relu6/dw <- conv6/dw
-I0510 14:48:30.304041  5307 net.cpp:527] relu6/dw -> conv6/dw (in-place)
-I0510 14:48:30.304055  5307 net.cpp:260] Setting up relu6/dw
-I0510 14:48:30.304069  5307 net.cpp:267] TEST Top shape for layer 107 'relu6/dw' 8 512 8 16 (524288)
-I0510 14:48:30.304082  5307 layer_factory.hpp:172] Creating layer 'conv6/sep' of type 'Convolution'
-I0510 14:48:30.304095  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.304113  5307 net.cpp:200] Created Layer conv6/sep (108)
-I0510 14:48:30.304129  5307 net.cpp:572] conv6/sep <- conv6/dw
-I0510 14:48:30.304143  5307 net.cpp:542] conv6/sep -> conv6/sep
-I0510 14:48:30.314024  5307 net.cpp:260] Setting up conv6/sep
-I0510 14:48:30.314102  5307 net.cpp:267] TEST Top shape for layer 108 'conv6/sep' 8 512 8 16 (524288)
-I0510 14:48:30.314126  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/bn' of type 'BatchNorm'
-I0510 14:48:30.314141  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.314159  5307 net.cpp:200] Created Layer conv6/sep/bn (109)
-I0510 14:48:30.314174  5307 net.cpp:572] conv6/sep/bn <- conv6/sep
-I0510 14:48:30.314188  5307 net.cpp:527] conv6/sep/bn -> conv6/sep (in-place)
-I0510 14:48:30.314595  5307 net.cpp:260] Setting up conv6/sep/bn
-I0510 14:48:30.314612  5307 net.cpp:267] TEST Top shape for layer 109 'conv6/sep/bn' 8 512 8 16 (524288)
-I0510 14:48:30.314628  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Scale'
-I0510 14:48:30.314641  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.314657  5307 net.cpp:200] Created Layer conv6/sep/scale (110)
-I0510 14:48:30.314668  5307 net.cpp:572] conv6/sep/scale <- conv6/sep
-I0510 14:48:30.314680  5307 net.cpp:527] conv6/sep/scale -> conv6/sep (in-place)
-I0510 14:48:30.314728  5307 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Bias'
-I0510 14:48:30.314743  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.314865  5307 net.cpp:260] Setting up conv6/sep/scale
-I0510 14:48:30.314882  5307 net.cpp:267] TEST Top shape for layer 110 'conv6/sep/scale' 8 512 8 16 (524288)
-I0510 14:48:30.314896  5307 layer_factory.hpp:172] Creating layer 'relu6/sep' of type 'ReLU'
-I0510 14:48:30.314914  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.314929  5307 net.cpp:200] Created Layer relu6/sep (111)
-I0510 14:48:30.314939  5307 net.cpp:572] relu6/sep <- conv6/sep
-I0510 14:48:30.314950  5307 net.cpp:527] relu6/sep -> conv6/sep (in-place)
-I0510 14:48:30.314965  5307 net.cpp:260] Setting up relu6/sep
-I0510 14:48:30.314977  5307 net.cpp:267] TEST Top shape for layer 111 'relu6/sep' 8 512 8 16 (524288)
-I0510 14:48:30.314988  5307 layer_factory.hpp:172] Creating layer 'conv6/sep_relu6/sep_0_split' of type 'Split'
-I0510 14:48:30.315001  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315013  5307 net.cpp:200] Created Layer conv6/sep_relu6/sep_0_split (112)
-I0510 14:48:30.315024  5307 net.cpp:572] conv6/sep_relu6/sep_0_split <- conv6/sep
-I0510 14:48:30.315035  5307 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_0
-I0510 14:48:30.315048  5307 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_1
-I0510 14:48:30.315089  5307 net.cpp:260] Setting up conv6/sep_relu6/sep_0_split
-I0510 14:48:30.315105  5307 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.315117  5307 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.315129  5307 layer_factory.hpp:172] Creating layer 'pool6' of type 'Pooling'
-I0510 14:48:30.315140  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315155  5307 net.cpp:200] Created Layer pool6 (113)
-I0510 14:48:30.315165  5307 net.cpp:572] pool6 <- conv6/sep_relu6/sep_0_split_0
-I0510 14:48:30.315177  5307 net.cpp:542] pool6 -> pool6
-I0510 14:48:30.315233  5307 net.cpp:260] Setting up pool6
-I0510 14:48:30.315248  5307 net.cpp:267] TEST Top shape for layer 113 'pool6' 8 512 5 9 (184320)
-I0510 14:48:30.315259  5307 layer_factory.hpp:172] Creating layer 'pool6_pool6_0_split' of type 'Split'
-I0510 14:48:30.315271  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315284  5307 net.cpp:200] Created Layer pool6_pool6_0_split (114)
-I0510 14:48:30.315300  5307 net.cpp:572] pool6_pool6_0_split <- pool6
-I0510 14:48:30.315312  5307 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_0
-I0510 14:48:30.315332  5307 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_1
-I0510 14:48:30.315374  5307 net.cpp:260] Setting up pool6_pool6_0_split
-I0510 14:48:30.315388  5307 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.315400  5307 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.315412  5307 layer_factory.hpp:172] Creating layer 'pool7' of type 'Pooling'
-I0510 14:48:30.315423  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315435  5307 net.cpp:200] Created Layer pool7 (115)
-I0510 14:48:30.315448  5307 net.cpp:572] pool7 <- pool6_pool6_0_split_0
-I0510 14:48:30.315459  5307 net.cpp:542] pool7 -> pool7
-I0510 14:48:30.315513  5307 net.cpp:260] Setting up pool7
-I0510 14:48:30.315528  5307 net.cpp:267] TEST Top shape for layer 115 'pool7' 8 512 3 5 (61440)
-I0510 14:48:30.315539  5307 layer_factory.hpp:172] Creating layer 'pool7_pool7_0_split' of type 'Split'
-I0510 14:48:30.315551  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315563  5307 net.cpp:200] Created Layer pool7_pool7_0_split (116)
-I0510 14:48:30.315574  5307 net.cpp:572] pool7_pool7_0_split <- pool7
-I0510 14:48:30.315585  5307 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_0
-I0510 14:48:30.315598  5307 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_1
-I0510 14:48:30.315639  5307 net.cpp:260] Setting up pool7_pool7_0_split
-I0510 14:48:30.315654  5307 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.315670  5307 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.315681  5307 layer_factory.hpp:172] Creating layer 'pool8' of type 'Pooling'
-I0510 14:48:30.315692  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315706  5307 net.cpp:200] Created Layer pool8 (117)
-I0510 14:48:30.315717  5307 net.cpp:572] pool8 <- pool7_pool7_0_split_0
-I0510 14:48:30.315729  5307 net.cpp:542] pool8 -> pool8
-I0510 14:48:30.315781  5307 net.cpp:260] Setting up pool8
-I0510 14:48:30.315796  5307 net.cpp:267] TEST Top shape for layer 117 'pool8' 8 512 3 5 (61440)
-I0510 14:48:30.315809  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1' of type 'Convolution'
-I0510 14:48:30.315819  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.315837  5307 net.cpp:200] Created Layer ctx_output1/1x1 (118)
-I0510 14:48:30.315850  5307 net.cpp:572] ctx_output1/1x1 <- conv5_5/sep_relu5_5/sep_0_split_1
-I0510 14:48:30.315862  5307 net.cpp:542] ctx_output1/1x1 -> ctx_output1/1x1
-I0510 14:48:30.319830  5307 net.cpp:260] Setting up ctx_output1/1x1
-I0510 14:48:30.319865  5307 net.cpp:267] TEST Top shape for layer 118 'ctx_output1/1x1' 8 512 16 32 (2097152)
-I0510 14:48:30.319883  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.319895  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.319916  5307 net.cpp:200] Created Layer ctx_output1/1x1/bn (119)
-I0510 14:48:30.319929  5307 net.cpp:572] ctx_output1/1x1/bn <- ctx_output1/1x1
-I0510 14:48:30.319944  5307 net.cpp:527] ctx_output1/1x1/bn -> ctx_output1/1x1 (in-place)
-I0510 14:48:30.320313  5307 net.cpp:260] Setting up ctx_output1/1x1/bn
-I0510 14:48:30.320389  5307 net.cpp:267] TEST Top shape for layer 119 'ctx_output1/1x1/bn' 8 512 16 32 (2097152)
-I0510 14:48:30.320462  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/relu' of type 'ReLU'
-I0510 14:48:30.320534  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.320606  5307 net.cpp:200] Created Layer ctx_output1/1x1/relu (120)
-I0510 14:48:30.320670  5307 net.cpp:572] ctx_output1/1x1/relu <- ctx_output1/1x1
-I0510 14:48:30.320737  5307 net.cpp:527] ctx_output1/1x1/relu -> ctx_output1/1x1 (in-place)
-I0510 14:48:30.320801  5307 net.cpp:260] Setting up ctx_output1/1x1/relu
-I0510 14:48:30.320860  5307 net.cpp:267] TEST Top shape for layer 120 'ctx_output1/1x1/relu' 8 512 16 32 (2097152)
-I0510 14:48:30.320928  5307 layer_factory.hpp:172] Creating layer 'ctx_output1' of type 'Convolution'
-I0510 14:48:30.320991  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.321064  5307 net.cpp:200] Created Layer ctx_output1 (121)
-I0510 14:48:30.321121  5307 net.cpp:572] ctx_output1 <- ctx_output1/1x1
-I0510 14:48:30.321177  5307 net.cpp:542] ctx_output1 -> ctx_output1
-I0510 14:48:30.321615  5307 net.cpp:260] Setting up ctx_output1
-I0510 14:48:30.321679  5307 net.cpp:267] TEST Top shape for layer 121 'ctx_output1' 8 512 16 32 (2097152)
-I0510 14:48:30.321748  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/bn' of type 'BatchNorm'
-I0510 14:48:30.321811  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.321873  5307 net.cpp:200] Created Layer ctx_output1/bn (122)
-I0510 14:48:30.321925  5307 net.cpp:572] ctx_output1/bn <- ctx_output1
-I0510 14:48:30.321975  5307 net.cpp:527] ctx_output1/bn -> ctx_output1 (in-place)
-I0510 14:48:30.322360  5307 net.cpp:260] Setting up ctx_output1/bn
-I0510 14:48:30.322424  5307 net.cpp:267] TEST Top shape for layer 122 'ctx_output1/bn' 8 512 16 32 (2097152)
-I0510 14:48:30.322499  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu' of type 'ReLU'
-I0510 14:48:30.322566  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.322643  5307 net.cpp:200] Created Layer ctx_output1/relu (123)
-I0510 14:48:30.322703  5307 net.cpp:572] ctx_output1/relu <- ctx_output1
-I0510 14:48:30.322757  5307 net.cpp:527] ctx_output1/relu -> ctx_output1 (in-place)
-I0510 14:48:30.322819  5307 net.cpp:260] Setting up ctx_output1/relu
-I0510 14:48:30.322877  5307 net.cpp:267] TEST Top shape for layer 123 'ctx_output1/relu' 8 512 16 32 (2097152)
-I0510 14:48:30.322943  5307 layer_factory.hpp:172] Creating layer 'ctx_output1_ctx_output1/relu_0_split' of type 'Split'
-I0510 14:48:30.323010  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.323079  5307 net.cpp:200] Created Layer ctx_output1_ctx_output1/relu_0_split (124)
-I0510 14:48:30.323150  5307 net.cpp:572] ctx_output1_ctx_output1/relu_0_split <- ctx_output1
-I0510 14:48:30.323212  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_0
-I0510 14:48:30.323287  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_1
-I0510 14:48:30.323357  5307 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_2
-I0510 14:48:30.323474  5307 net.cpp:260] Setting up ctx_output1_ctx_output1/relu_0_split
-I0510 14:48:30.323539  5307 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 8 512 16 32 (2097152)
-I0510 14:48:30.323612  5307 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 8 512 16 32 (2097152)
-I0510 14:48:30.323689  5307 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 8 512 16 32 (2097152)
-I0510 14:48:30.323763  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1' of type 'Convolution'
-I0510 14:48:30.323829  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.323902  5307 net.cpp:200] Created Layer ctx_output2/1x1 (125)
-I0510 14:48:30.323961  5307 net.cpp:572] ctx_output2/1x1 <- conv6/sep_relu6/sep_0_split_1
-I0510 14:48:30.324023  5307 net.cpp:542] ctx_output2/1x1 -> ctx_output2/1x1
-I0510 14:48:30.333039  5307 net.cpp:260] Setting up ctx_output2/1x1
-I0510 14:48:30.333173  5307 net.cpp:267] TEST Top shape for layer 125 'ctx_output2/1x1' 8 512 8 16 (524288)
-I0510 14:48:30.333248  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.333317  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.333382  5307 net.cpp:200] Created Layer ctx_output2/1x1/bn (126)
-I0510 14:48:30.333403  5307 net.cpp:572] ctx_output2/1x1/bn <- ctx_output2/1x1
-I0510 14:48:30.333421  5307 net.cpp:527] ctx_output2/1x1/bn -> ctx_output2/1x1 (in-place)
-I0510 14:48:30.333811  5307 net.cpp:260] Setting up ctx_output2/1x1/bn
-I0510 14:48:30.333820  5307 net.cpp:267] TEST Top shape for layer 126 'ctx_output2/1x1/bn' 8 512 8 16 (524288)
-I0510 14:48:30.333829  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/relu' of type 'ReLU'
-I0510 14:48:30.333834  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.333840  5307 net.cpp:200] Created Layer ctx_output2/1x1/relu (127)
-I0510 14:48:30.333844  5307 net.cpp:572] ctx_output2/1x1/relu <- ctx_output2/1x1
-I0510 14:48:30.333875  5307 net.cpp:527] ctx_output2/1x1/relu -> ctx_output2/1x1 (in-place)
-I0510 14:48:30.333899  5307 net.cpp:260] Setting up ctx_output2/1x1/relu
-I0510 14:48:30.333911  5307 net.cpp:267] TEST Top shape for layer 127 'ctx_output2/1x1/relu' 8 512 8 16 (524288)
-I0510 14:48:30.333925  5307 layer_factory.hpp:172] Creating layer 'ctx_output2' of type 'Convolution'
-I0510 14:48:30.333938  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.333961  5307 net.cpp:200] Created Layer ctx_output2 (128)
-I0510 14:48:30.333966  5307 net.cpp:572] ctx_output2 <- ctx_output2/1x1
-I0510 14:48:30.333986  5307 net.cpp:542] ctx_output2 -> ctx_output2
-I0510 14:48:30.334405  5307 net.cpp:260] Setting up ctx_output2
-I0510 14:48:30.334429  5307 net.cpp:267] TEST Top shape for layer 128 'ctx_output2' 8 512 8 16 (524288)
-I0510 14:48:30.334444  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/bn' of type 'BatchNorm'
-I0510 14:48:30.334450  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.334468  5307 net.cpp:200] Created Layer ctx_output2/bn (129)
-I0510 14:48:30.334473  5307 net.cpp:572] ctx_output2/bn <- ctx_output2
-I0510 14:48:30.334491  5307 net.cpp:527] ctx_output2/bn -> ctx_output2 (in-place)
-I0510 14:48:30.334856  5307 net.cpp:260] Setting up ctx_output2/bn
-I0510 14:48:30.334874  5307 net.cpp:267] TEST Top shape for layer 129 'ctx_output2/bn' 8 512 8 16 (524288)
-I0510 14:48:30.334892  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu' of type 'ReLU'
-I0510 14:48:30.334905  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.334919  5307 net.cpp:200] Created Layer ctx_output2/relu (130)
-I0510 14:48:30.334933  5307 net.cpp:572] ctx_output2/relu <- ctx_output2
-I0510 14:48:30.334944  5307 net.cpp:527] ctx_output2/relu -> ctx_output2 (in-place)
-I0510 14:48:30.334959  5307 net.cpp:260] Setting up ctx_output2/relu
-I0510 14:48:30.334972  5307 net.cpp:267] TEST Top shape for layer 130 'ctx_output2/relu' 8 512 8 16 (524288)
-I0510 14:48:30.334985  5307 layer_factory.hpp:172] Creating layer 'ctx_output2_ctx_output2/relu_0_split' of type 'Split'
-I0510 14:48:30.334997  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.335011  5307 net.cpp:200] Created Layer ctx_output2_ctx_output2/relu_0_split (131)
-I0510 14:48:30.335023  5307 net.cpp:572] ctx_output2_ctx_output2/relu_0_split <- ctx_output2
-I0510 14:48:30.335036  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_0
-I0510 14:48:30.335050  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_1
-I0510 14:48:30.335064  5307 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_2
-I0510 14:48:30.335119  5307 net.cpp:260] Setting up ctx_output2_ctx_output2/relu_0_split
-I0510 14:48:30.335137  5307 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.335158  5307 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.335171  5307 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 8 512 8 16 (524288)
-I0510 14:48:30.335183  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1' of type 'Convolution'
-I0510 14:48:30.335196  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.335212  5307 net.cpp:200] Created Layer ctx_output3/1x1 (132)
-I0510 14:48:30.335225  5307 net.cpp:572] ctx_output3/1x1 <- pool6_pool6_0_split_1
-I0510 14:48:30.335238  5307 net.cpp:542] ctx_output3/1x1 -> ctx_output3/1x1
-I0510 14:48:30.343972  5307 net.cpp:260] Setting up ctx_output3/1x1
-I0510 14:48:30.344038  5307 net.cpp:267] TEST Top shape for layer 132 'ctx_output3/1x1' 8 512 5 9 (184320)
-I0510 14:48:30.344063  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.344081  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.344110  5307 net.cpp:200] Created Layer ctx_output3/1x1/bn (133)
-I0510 14:48:30.344127  5307 net.cpp:572] ctx_output3/1x1/bn <- ctx_output3/1x1
-I0510 14:48:30.344146  5307 net.cpp:527] ctx_output3/1x1/bn -> ctx_output3/1x1 (in-place)
-I0510 14:48:30.344579  5307 net.cpp:260] Setting up ctx_output3/1x1/bn
-I0510 14:48:30.344604  5307 net.cpp:267] TEST Top shape for layer 133 'ctx_output3/1x1/bn' 8 512 5 9 (184320)
-I0510 14:48:30.344625  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/relu' of type 'ReLU'
-I0510 14:48:30.344641  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.344671  5307 net.cpp:200] Created Layer ctx_output3/1x1/relu (134)
-I0510 14:48:30.344687  5307 net.cpp:572] ctx_output3/1x1/relu <- ctx_output3/1x1
-I0510 14:48:30.344702  5307 net.cpp:527] ctx_output3/1x1/relu -> ctx_output3/1x1 (in-place)
-I0510 14:48:30.344722  5307 net.cpp:260] Setting up ctx_output3/1x1/relu
-I0510 14:48:30.344739  5307 net.cpp:267] TEST Top shape for layer 134 'ctx_output3/1x1/relu' 8 512 5 9 (184320)
-I0510 14:48:30.344755  5307 layer_factory.hpp:172] Creating layer 'ctx_output3' of type 'Convolution'
-I0510 14:48:30.344771  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.344795  5307 net.cpp:200] Created Layer ctx_output3 (135)
-I0510 14:48:30.344811  5307 net.cpp:572] ctx_output3 <- ctx_output3/1x1
-I0510 14:48:30.344826  5307 net.cpp:542] ctx_output3 -> ctx_output3
-I0510 14:48:30.345271  5307 net.cpp:260] Setting up ctx_output3
-I0510 14:48:30.345295  5307 net.cpp:267] TEST Top shape for layer 135 'ctx_output3' 8 512 5 9 (184320)
-I0510 14:48:30.345315  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/bn' of type 'BatchNorm'
-I0510 14:48:30.345333  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.345353  5307 net.cpp:200] Created Layer ctx_output3/bn (136)
-I0510 14:48:30.345371  5307 net.cpp:572] ctx_output3/bn <- ctx_output3
-I0510 14:48:30.345386  5307 net.cpp:527] ctx_output3/bn -> ctx_output3 (in-place)
-I0510 14:48:30.345791  5307 net.cpp:260] Setting up ctx_output3/bn
-I0510 14:48:30.345813  5307 net.cpp:267] TEST Top shape for layer 136 'ctx_output3/bn' 8 512 5 9 (184320)
-I0510 14:48:30.345834  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu' of type 'ReLU'
-I0510 14:48:30.345852  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.345870  5307 net.cpp:200] Created Layer ctx_output3/relu (137)
-I0510 14:48:30.345885  5307 net.cpp:572] ctx_output3/relu <- ctx_output3
-I0510 14:48:30.345902  5307 net.cpp:527] ctx_output3/relu -> ctx_output3 (in-place)
-I0510 14:48:30.345921  5307 net.cpp:260] Setting up ctx_output3/relu
-I0510 14:48:30.345937  5307 net.cpp:267] TEST Top shape for layer 137 'ctx_output3/relu' 8 512 5 9 (184320)
-I0510 14:48:30.345960  5307 layer_factory.hpp:172] Creating layer 'ctx_output3_ctx_output3/relu_0_split' of type 'Split'
-I0510 14:48:30.345985  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.346002  5307 net.cpp:200] Created Layer ctx_output3_ctx_output3/relu_0_split (138)
-I0510 14:48:30.346017  5307 net.cpp:572] ctx_output3_ctx_output3/relu_0_split <- ctx_output3
-I0510 14:48:30.346036  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_0
-I0510 14:48:30.346053  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_1
-I0510 14:48:30.346071  5307 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_2
-I0510 14:48:30.346129  5307 net.cpp:260] Setting up ctx_output3_ctx_output3/relu_0_split
-I0510 14:48:30.346148  5307 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.346166  5307 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.346181  5307 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 8 512 5 9 (184320)
-I0510 14:48:30.346196  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1' of type 'Convolution'
-I0510 14:48:30.346211  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.346231  5307 net.cpp:200] Created Layer ctx_output4/1x1 (139)
-I0510 14:48:30.346248  5307 net.cpp:572] ctx_output4/1x1 <- pool7_pool7_0_split_1
-I0510 14:48:30.346264  5307 net.cpp:542] ctx_output4/1x1 -> ctx_output4/1x1
-I0510 14:48:30.355239  5307 net.cpp:260] Setting up ctx_output4/1x1
-I0510 14:48:30.355317  5307 net.cpp:267] TEST Top shape for layer 139 'ctx_output4/1x1' 8 512 3 5 (61440)
-I0510 14:48:30.355342  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.355360  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.355389  5307 net.cpp:200] Created Layer ctx_output4/1x1/bn (140)
-I0510 14:48:30.355408  5307 net.cpp:572] ctx_output4/1x1/bn <- ctx_output4/1x1
-I0510 14:48:30.355425  5307 net.cpp:527] ctx_output4/1x1/bn -> ctx_output4/1x1 (in-place)
-I0510 14:48:30.355901  5307 net.cpp:260] Setting up ctx_output4/1x1/bn
-I0510 14:48:30.355921  5307 net.cpp:267] TEST Top shape for layer 140 'ctx_output4/1x1/bn' 8 512 3 5 (61440)
-I0510 14:48:30.355939  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/relu' of type 'ReLU'
-I0510 14:48:30.355952  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.355965  5307 net.cpp:200] Created Layer ctx_output4/1x1/relu (141)
-I0510 14:48:30.355976  5307 net.cpp:572] ctx_output4/1x1/relu <- ctx_output4/1x1
-I0510 14:48:30.355988  5307 net.cpp:527] ctx_output4/1x1/relu -> ctx_output4/1x1 (in-place)
-I0510 14:48:30.356003  5307 net.cpp:260] Setting up ctx_output4/1x1/relu
-I0510 14:48:30.356014  5307 net.cpp:267] TEST Top shape for layer 141 'ctx_output4/1x1/relu' 8 512 3 5 (61440)
-I0510 14:48:30.356026  5307 layer_factory.hpp:172] Creating layer 'ctx_output4' of type 'Convolution'
-I0510 14:48:30.356039  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.356055  5307 net.cpp:200] Created Layer ctx_output4 (142)
-I0510 14:48:30.356066  5307 net.cpp:572] ctx_output4 <- ctx_output4/1x1
-I0510 14:48:30.356077  5307 net.cpp:542] ctx_output4 -> ctx_output4
-I0510 14:48:30.356488  5307 net.cpp:260] Setting up ctx_output4
-I0510 14:48:30.356510  5307 net.cpp:267] TEST Top shape for layer 142 'ctx_output4' 8 512 3 5 (61440)
-I0510 14:48:30.356542  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/bn' of type 'BatchNorm'
-I0510 14:48:30.356559  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.356581  5307 net.cpp:200] Created Layer ctx_output4/bn (143)
-I0510 14:48:30.356603  5307 net.cpp:572] ctx_output4/bn <- ctx_output4
-I0510 14:48:30.356616  5307 net.cpp:527] ctx_output4/bn -> ctx_output4 (in-place)
-I0510 14:48:30.356990  5307 net.cpp:260] Setting up ctx_output4/bn
-I0510 14:48:30.357010  5307 net.cpp:267] TEST Top shape for layer 143 'ctx_output4/bn' 8 512 3 5 (61440)
-I0510 14:48:30.357029  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu' of type 'ReLU'
-I0510 14:48:30.357046  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.357069  5307 net.cpp:200] Created Layer ctx_output4/relu (144)
-I0510 14:48:30.357084  5307 net.cpp:572] ctx_output4/relu <- ctx_output4
-I0510 14:48:30.357100  5307 net.cpp:527] ctx_output4/relu -> ctx_output4 (in-place)
-I0510 14:48:30.357116  5307 net.cpp:260] Setting up ctx_output4/relu
-I0510 14:48:30.357132  5307 net.cpp:267] TEST Top shape for layer 144 'ctx_output4/relu' 8 512 3 5 (61440)
-I0510 14:48:30.357147  5307 layer_factory.hpp:172] Creating layer 'ctx_output4_ctx_output4/relu_0_split' of type 'Split'
-I0510 14:48:30.357162  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.357178  5307 net.cpp:200] Created Layer ctx_output4_ctx_output4/relu_0_split (145)
-I0510 14:48:30.357193  5307 net.cpp:572] ctx_output4_ctx_output4/relu_0_split <- ctx_output4
-I0510 14:48:30.357208  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_0
-I0510 14:48:30.357230  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_1
-I0510 14:48:30.357247  5307 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_2
-I0510 14:48:30.357311  5307 net.cpp:260] Setting up ctx_output4_ctx_output4/relu_0_split
-I0510 14:48:30.357331  5307 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.357347  5307 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.357362  5307 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.357376  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1' of type 'Convolution'
-I0510 14:48:30.357389  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.357409  5307 net.cpp:200] Created Layer ctx_output5/1x1 (146)
-I0510 14:48:30.357424  5307 net.cpp:572] ctx_output5/1x1 <- pool8
-I0510 14:48:30.357439  5307 net.cpp:542] ctx_output5/1x1 -> ctx_output5/1x1
-I0510 14:48:30.365607  5307 net.cpp:260] Setting up ctx_output5/1x1
-I0510 14:48:30.365667  5307 net.cpp:267] TEST Top shape for layer 146 'ctx_output5/1x1' 8 512 3 5 (61440)
-I0510 14:48:30.365686  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/bn' of type 'BatchNorm'
-I0510 14:48:30.365700  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.365716  5307 net.cpp:200] Created Layer ctx_output5/1x1/bn (147)
-I0510 14:48:30.365731  5307 net.cpp:572] ctx_output5/1x1/bn <- ctx_output5/1x1
-I0510 14:48:30.365743  5307 net.cpp:527] ctx_output5/1x1/bn -> ctx_output5/1x1 (in-place)
-I0510 14:48:30.366083  5307 net.cpp:260] Setting up ctx_output5/1x1/bn
-I0510 14:48:30.366092  5307 net.cpp:267] TEST Top shape for layer 147 'ctx_output5/1x1/bn' 8 512 3 5 (61440)
-I0510 14:48:30.366101  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/relu' of type 'ReLU'
-I0510 14:48:30.366104  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.366109  5307 net.cpp:200] Created Layer ctx_output5/1x1/relu (148)
-I0510 14:48:30.366113  5307 net.cpp:572] ctx_output5/1x1/relu <- ctx_output5/1x1
-I0510 14:48:30.366117  5307 net.cpp:527] ctx_output5/1x1/relu -> ctx_output5/1x1 (in-place)
-I0510 14:48:30.366137  5307 net.cpp:260] Setting up ctx_output5/1x1/relu
-I0510 14:48:30.366158  5307 net.cpp:267] TEST Top shape for layer 148 'ctx_output5/1x1/relu' 8 512 3 5 (61440)
-I0510 14:48:30.366180  5307 layer_factory.hpp:172] Creating layer 'ctx_output5' of type 'Convolution'
-I0510 14:48:30.366194  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.366211  5307 net.cpp:200] Created Layer ctx_output5 (149)
-I0510 14:48:30.366223  5307 net.cpp:572] ctx_output5 <- ctx_output5/1x1
-I0510 14:48:30.366236  5307 net.cpp:542] ctx_output5 -> ctx_output5
-I0510 14:48:30.366629  5307 net.cpp:260] Setting up ctx_output5
-I0510 14:48:30.366637  5307 net.cpp:267] TEST Top shape for layer 149 'ctx_output5' 8 512 3 5 (61440)
-I0510 14:48:30.366662  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/bn' of type 'BatchNorm'
-I0510 14:48:30.366677  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.366693  5307 net.cpp:200] Created Layer ctx_output5/bn (150)
-I0510 14:48:30.366706  5307 net.cpp:572] ctx_output5/bn <- ctx_output5
-I0510 14:48:30.366720  5307 net.cpp:527] ctx_output5/bn -> ctx_output5 (in-place)
-I0510 14:48:30.367090  5307 net.cpp:260] Setting up ctx_output5/bn
-I0510 14:48:30.367097  5307 net.cpp:267] TEST Top shape for layer 150 'ctx_output5/bn' 8 512 3 5 (61440)
-I0510 14:48:30.367121  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu' of type 'ReLU'
-I0510 14:48:30.367133  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.367146  5307 net.cpp:200] Created Layer ctx_output5/relu (151)
-I0510 14:48:30.367158  5307 net.cpp:572] ctx_output5/relu <- ctx_output5
-I0510 14:48:30.367171  5307 net.cpp:527] ctx_output5/relu -> ctx_output5 (in-place)
-I0510 14:48:30.367187  5307 net.cpp:260] Setting up ctx_output5/relu
-I0510 14:48:30.367200  5307 net.cpp:267] TEST Top shape for layer 151 'ctx_output5/relu' 8 512 3 5 (61440)
-I0510 14:48:30.367213  5307 layer_factory.hpp:172] Creating layer 'ctx_output5_ctx_output5/relu_0_split' of type 'Split'
-I0510 14:48:30.367224  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.367238  5307 net.cpp:200] Created Layer ctx_output5_ctx_output5/relu_0_split (152)
-I0510 14:48:30.367249  5307 net.cpp:572] ctx_output5_ctx_output5/relu_0_split <- ctx_output5
-I0510 14:48:30.367261  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_0
-I0510 14:48:30.367274  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_1
-I0510 14:48:30.367288  5307 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_2
-I0510 14:48:30.367344  5307 net.cpp:260] Setting up ctx_output5_ctx_output5/relu_0_split
-I0510 14:48:30.367359  5307 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.367372  5307 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.367385  5307 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 8 512 3 5 (61440)
-I0510 14:48:30.367398  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.367411  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.367432  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc (153)
-I0510 14:48:30.367446  5307 net.cpp:572] ctx_output1/relu_mbox_loc <- ctx_output1_ctx_output1/relu_0_split_0
-I0510 14:48:30.367461  5307 net.cpp:542] ctx_output1/relu_mbox_loc -> ctx_output1/relu_mbox_loc
-I0510 14:48:30.367933  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc
-I0510 14:48:30.367951  5307 net.cpp:267] TEST Top shape for layer 153 'ctx_output1/relu_mbox_loc' 8 16 16 32 (65536)
-I0510 14:48:30.367966  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.367979  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.368005  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_perm (154)
-I0510 14:48:30.368018  5307 net.cpp:572] ctx_output1/relu_mbox_loc_perm <- ctx_output1/relu_mbox_loc
-I0510 14:48:30.368031  5307 net.cpp:542] ctx_output1/relu_mbox_loc_perm -> ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.368134  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.368149  5307 net.cpp:267] TEST Top shape for layer 154 'ctx_output1/relu_mbox_loc_perm' 8 16 32 16 (65536)
-I0510 14:48:30.368162  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.368175  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.368188  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_flat (155)
-I0510 14:48:30.368201  5307 net.cpp:572] ctx_output1/relu_mbox_loc_flat <- ctx_output1/relu_mbox_loc_perm
-I0510 14:48:30.368214  5307 net.cpp:542] ctx_output1/relu_mbox_loc_flat -> ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.368324  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.368340  5307 net.cpp:267] TEST Top shape for layer 155 'ctx_output1/relu_mbox_loc_flat' 8 8192 (65536)
-I0510 14:48:30.368352  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.368366  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.368384  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf (156)
-I0510 14:48:30.368396  5307 net.cpp:572] ctx_output1/relu_mbox_conf <- ctx_output1_ctx_output1/relu_0_split_1
-I0510 14:48:30.368410  5307 net.cpp:542] ctx_output1/relu_mbox_conf -> ctx_output1/relu_mbox_conf
-I0510 14:48:30.369997  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf
-I0510 14:48:30.370007  5307 net.cpp:267] TEST Top shape for layer 156 'ctx_output1/relu_mbox_conf' 8 84 16 32 (344064)
-I0510 14:48:30.370031  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.370044  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.370059  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_perm (157)
-I0510 14:48:30.370071  5307 net.cpp:572] ctx_output1/relu_mbox_conf_perm <- ctx_output1/relu_mbox_conf
-I0510 14:48:30.370085  5307 net.cpp:542] ctx_output1/relu_mbox_conf_perm -> ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.370190  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.370206  5307 net.cpp:267] TEST Top shape for layer 157 'ctx_output1/relu_mbox_conf_perm' 8 16 32 84 (344064)
-I0510 14:48:30.370219  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.370232  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.370245  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_flat (158)
-I0510 14:48:30.370257  5307 net.cpp:572] ctx_output1/relu_mbox_conf_flat <- ctx_output1/relu_mbox_conf_perm
-I0510 14:48:30.370270  5307 net.cpp:542] ctx_output1/relu_mbox_conf_flat -> ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.379266  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.379313  5307 net.cpp:267] TEST Top shape for layer 158 'ctx_output1/relu_mbox_conf_flat' 8 43008 (344064)
-I0510 14:48:30.379328  5307 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.379344  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.379364  5307 net.cpp:200] Created Layer ctx_output1/relu_mbox_priorbox (159)
-I0510 14:48:30.379375  5307 net.cpp:572] ctx_output1/relu_mbox_priorbox <- ctx_output1_ctx_output1/relu_0_split_2
-I0510 14:48:30.379390  5307 net.cpp:572] ctx_output1/relu_mbox_priorbox <- data_data_0_split_1
-I0510 14:48:30.379401  5307 net.cpp:542] ctx_output1/relu_mbox_priorbox -> ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.379524  5307 net.cpp:260] Setting up ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.379534  5307 net.cpp:267] TEST Top shape for layer 159 'ctx_output1/relu_mbox_priorbox' 1 2 8192 (16384)
-I0510 14:48:30.379539  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.379546  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.379560  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc (160)
-I0510 14:48:30.379565  5307 net.cpp:572] ctx_output2/relu_mbox_loc <- ctx_output2_ctx_output2/relu_0_split_0
-I0510 14:48:30.379570  5307 net.cpp:542] ctx_output2/relu_mbox_loc -> ctx_output2/relu_mbox_loc
-I0510 14:48:30.380260  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc
-I0510 14:48:30.380270  5307 net.cpp:267] TEST Top shape for layer 160 'ctx_output2/relu_mbox_loc' 8 24 8 16 (24576)
-I0510 14:48:30.380276  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.380281  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.380288  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_perm (161)
-I0510 14:48:30.380293  5307 net.cpp:572] ctx_output2/relu_mbox_loc_perm <- ctx_output2/relu_mbox_loc
-I0510 14:48:30.380297  5307 net.cpp:542] ctx_output2/relu_mbox_loc_perm -> ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.380390  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.380398  5307 net.cpp:267] TEST Top shape for layer 161 'ctx_output2/relu_mbox_loc_perm' 8 8 16 24 (24576)
-I0510 14:48:30.380403  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.380406  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.380411  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_flat (162)
-I0510 14:48:30.380415  5307 net.cpp:572] ctx_output2/relu_mbox_loc_flat <- ctx_output2/relu_mbox_loc_perm
-I0510 14:48:30.380420  5307 net.cpp:542] ctx_output2/relu_mbox_loc_flat -> ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.380486  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.380492  5307 net.cpp:267] TEST Top shape for layer 162 'ctx_output2/relu_mbox_loc_flat' 8 3072 (24576)
-I0510 14:48:30.380497  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.380501  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.380509  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf (163)
-I0510 14:48:30.380513  5307 net.cpp:572] ctx_output2/relu_mbox_conf <- ctx_output2_ctx_output2/relu_0_split_1
-I0510 14:48:30.380518  5307 net.cpp:542] ctx_output2/relu_mbox_conf -> ctx_output2/relu_mbox_conf
-I0510 14:48:30.382915  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf
-I0510 14:48:30.382927  5307 net.cpp:267] TEST Top shape for layer 163 'ctx_output2/relu_mbox_conf' 8 126 8 16 (129024)
-I0510 14:48:30.382935  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.382939  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.382946  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_perm (164)
-I0510 14:48:30.382951  5307 net.cpp:572] ctx_output2/relu_mbox_conf_perm <- ctx_output2/relu_mbox_conf
-I0510 14:48:30.382954  5307 net.cpp:542] ctx_output2/relu_mbox_conf_perm -> ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.383042  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.383049  5307 net.cpp:267] TEST Top shape for layer 164 'ctx_output2/relu_mbox_conf_perm' 8 8 16 126 (129024)
-I0510 14:48:30.383052  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.383057  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.383070  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_flat (165)
-I0510 14:48:30.383074  5307 net.cpp:572] ctx_output2/relu_mbox_conf_flat <- ctx_output2/relu_mbox_conf_perm
-I0510 14:48:30.383080  5307 net.cpp:542] ctx_output2/relu_mbox_conf_flat -> ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.383201  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.383208  5307 net.cpp:267] TEST Top shape for layer 165 'ctx_output2/relu_mbox_conf_flat' 8 16128 (129024)
-I0510 14:48:30.383213  5307 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.383216  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.383221  5307 net.cpp:200] Created Layer ctx_output2/relu_mbox_priorbox (166)
-I0510 14:48:30.383224  5307 net.cpp:572] ctx_output2/relu_mbox_priorbox <- ctx_output2_ctx_output2/relu_0_split_2
-I0510 14:48:30.383229  5307 net.cpp:572] ctx_output2/relu_mbox_priorbox <- data_data_0_split_2
-I0510 14:48:30.383234  5307 net.cpp:542] ctx_output2/relu_mbox_priorbox -> ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.383253  5307 net.cpp:260] Setting up ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.383260  5307 net.cpp:267] TEST Top shape for layer 166 'ctx_output2/relu_mbox_priorbox' 1 2 3072 (6144)
-I0510 14:48:30.383263  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.383266  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.383277  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc (167)
-I0510 14:48:30.383281  5307 net.cpp:572] ctx_output3/relu_mbox_loc <- ctx_output3_ctx_output3/relu_0_split_0
-I0510 14:48:30.383285  5307 net.cpp:542] ctx_output3/relu_mbox_loc -> ctx_output3/relu_mbox_loc
-I0510 14:48:30.383890  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc
-I0510 14:48:30.383898  5307 net.cpp:267] TEST Top shape for layer 167 'ctx_output3/relu_mbox_loc' 8 24 5 9 (8640)
-I0510 14:48:30.383905  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.383908  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.383913  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_perm (168)
-I0510 14:48:30.383918  5307 net.cpp:572] ctx_output3/relu_mbox_loc_perm <- ctx_output3/relu_mbox_loc
-I0510 14:48:30.383921  5307 net.cpp:542] ctx_output3/relu_mbox_loc_perm -> ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.384006  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.384011  5307 net.cpp:267] TEST Top shape for layer 168 'ctx_output3/relu_mbox_loc_perm' 8 5 9 24 (8640)
-I0510 14:48:30.384016  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.384018  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.384022  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_flat (169)
-I0510 14:48:30.384027  5307 net.cpp:572] ctx_output3/relu_mbox_loc_flat <- ctx_output3/relu_mbox_loc_perm
-I0510 14:48:30.384032  5307 net.cpp:542] ctx_output3/relu_mbox_loc_flat -> ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.384083  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.384089  5307 net.cpp:267] TEST Top shape for layer 169 'ctx_output3/relu_mbox_loc_flat' 8 1080 (8640)
-I0510 14:48:30.384093  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.384096  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.384102  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf (170)
-I0510 14:48:30.384106  5307 net.cpp:572] ctx_output3/relu_mbox_conf <- ctx_output3_ctx_output3/relu_0_split_1
-I0510 14:48:30.384110  5307 net.cpp:542] ctx_output3/relu_mbox_conf -> ctx_output3/relu_mbox_conf
-I0510 14:48:30.386309  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf
-I0510 14:48:30.386322  5307 net.cpp:267] TEST Top shape for layer 170 'ctx_output3/relu_mbox_conf' 8 126 5 9 (45360)
-I0510 14:48:30.386328  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.386333  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.386339  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_perm (171)
-I0510 14:48:30.386343  5307 net.cpp:572] ctx_output3/relu_mbox_conf_perm <- ctx_output3/relu_mbox_conf
-I0510 14:48:30.386348  5307 net.cpp:542] ctx_output3/relu_mbox_conf_perm -> ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.386449  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.386456  5307 net.cpp:267] TEST Top shape for layer 171 'ctx_output3/relu_mbox_conf_perm' 8 5 9 126 (45360)
-I0510 14:48:30.386461  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.386464  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.386468  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_flat (172)
-I0510 14:48:30.386472  5307 net.cpp:572] ctx_output3/relu_mbox_conf_flat <- ctx_output3/relu_mbox_conf_perm
-I0510 14:48:30.386476  5307 net.cpp:542] ctx_output3/relu_mbox_conf_flat -> ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.387451  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.387465  5307 net.cpp:267] TEST Top shape for layer 172 'ctx_output3/relu_mbox_conf_flat' 8 5670 (45360)
-I0510 14:48:30.387470  5307 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.387476  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.387483  5307 net.cpp:200] Created Layer ctx_output3/relu_mbox_priorbox (173)
-I0510 14:48:30.387488  5307 net.cpp:572] ctx_output3/relu_mbox_priorbox <- ctx_output3_ctx_output3/relu_0_split_2
-I0510 14:48:30.387495  5307 net.cpp:572] ctx_output3/relu_mbox_priorbox <- data_data_0_split_3
-I0510 14:48:30.387501  5307 net.cpp:542] ctx_output3/relu_mbox_priorbox -> ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.387526  5307 net.cpp:260] Setting up ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.387534  5307 net.cpp:267] TEST Top shape for layer 173 'ctx_output3/relu_mbox_priorbox' 1 2 1080 (2160)
-I0510 14:48:30.387538  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.387543  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.387553  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc (174)
-I0510 14:48:30.387557  5307 net.cpp:572] ctx_output4/relu_mbox_loc <- ctx_output4_ctx_output4/relu_0_split_0
-I0510 14:48:30.387562  5307 net.cpp:542] ctx_output4/relu_mbox_loc -> ctx_output4/relu_mbox_loc
-I0510 14:48:30.388070  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc
-I0510 14:48:30.388082  5307 net.cpp:267] TEST Top shape for layer 174 'ctx_output4/relu_mbox_loc' 8 16 3 5 (1920)
-I0510 14:48:30.388089  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.388094  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.388101  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_perm (175)
-I0510 14:48:30.388108  5307 net.cpp:572] ctx_output4/relu_mbox_loc_perm <- ctx_output4/relu_mbox_loc
-I0510 14:48:30.388113  5307 net.cpp:542] ctx_output4/relu_mbox_loc_perm -> ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.388193  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.388201  5307 net.cpp:267] TEST Top shape for layer 175 'ctx_output4/relu_mbox_loc_perm' 8 3 5 16 (1920)
-I0510 14:48:30.388206  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.388226  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.388233  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_flat (176)
-I0510 14:48:30.388237  5307 net.cpp:572] ctx_output4/relu_mbox_loc_flat <- ctx_output4/relu_mbox_loc_perm
-I0510 14:48:30.388242  5307 net.cpp:542] ctx_output4/relu_mbox_loc_flat -> ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.388301  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.388309  5307 net.cpp:267] TEST Top shape for layer 176 'ctx_output4/relu_mbox_loc_flat' 8 240 (1920)
-I0510 14:48:30.388314  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.388319  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.388327  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf (177)
-I0510 14:48:30.388331  5307 net.cpp:572] ctx_output4/relu_mbox_conf <- ctx_output4_ctx_output4/relu_0_split_1
-I0510 14:48:30.388336  5307 net.cpp:542] ctx_output4/relu_mbox_conf -> ctx_output4/relu_mbox_conf
-I0510 14:48:30.389809  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf
-I0510 14:48:30.389820  5307 net.cpp:267] TEST Top shape for layer 177 'ctx_output4/relu_mbox_conf' 8 84 3 5 (10080)
-I0510 14:48:30.389827  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.389832  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.389837  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_perm (178)
-I0510 14:48:30.389842  5307 net.cpp:572] ctx_output4/relu_mbox_conf_perm <- ctx_output4/relu_mbox_conf
-I0510 14:48:30.389847  5307 net.cpp:542] ctx_output4/relu_mbox_conf_perm -> ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.389919  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.389926  5307 net.cpp:267] TEST Top shape for layer 178 'ctx_output4/relu_mbox_conf_perm' 8 3 5 84 (10080)
-I0510 14:48:30.389930  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.389935  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.389940  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_flat (179)
-I0510 14:48:30.389943  5307 net.cpp:572] ctx_output4/relu_mbox_conf_flat <- ctx_output4/relu_mbox_conf_perm
-I0510 14:48:30.389959  5307 net.cpp:542] ctx_output4/relu_mbox_conf_flat -> ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.391364  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.391393  5307 net.cpp:267] TEST Top shape for layer 179 'ctx_output4/relu_mbox_conf_flat' 8 1260 (10080)
-I0510 14:48:30.391407  5307 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.391420  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.391439  5307 net.cpp:200] Created Layer ctx_output4/relu_mbox_priorbox (180)
-I0510 14:48:30.391455  5307 net.cpp:572] ctx_output4/relu_mbox_priorbox <- ctx_output4_ctx_output4/relu_0_split_2
-I0510 14:48:30.391474  5307 net.cpp:572] ctx_output4/relu_mbox_priorbox <- data_data_0_split_4
-I0510 14:48:30.391490  5307 net.cpp:542] ctx_output4/relu_mbox_priorbox -> ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.391535  5307 net.cpp:260] Setting up ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.391548  5307 net.cpp:267] TEST Top shape for layer 180 'ctx_output4/relu_mbox_priorbox' 1 2 240 (480)
-I0510 14:48:30.391559  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc' of type 'Convolution'
-I0510 14:48:30.391571  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.391589  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc (181)
-I0510 14:48:30.391605  5307 net.cpp:572] ctx_output5/relu_mbox_loc <- ctx_output5_ctx_output5/relu_0_split_0
-I0510 14:48:30.391626  5307 net.cpp:542] ctx_output5/relu_mbox_loc -> ctx_output5/relu_mbox_loc
-I0510 14:48:30.393018  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc
-I0510 14:48:30.393043  5307 net.cpp:267] TEST Top shape for layer 181 'ctx_output5/relu_mbox_loc' 8 16 3 5 (1920)
-I0510 14:48:30.393057  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_perm' of type 'Permute'
-I0510 14:48:30.393067  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.393081  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_perm (182)
-I0510 14:48:30.393092  5307 net.cpp:572] ctx_output5/relu_mbox_loc_perm <- ctx_output5/relu_mbox_loc
-I0510 14:48:30.393103  5307 net.cpp:542] ctx_output5/relu_mbox_loc_perm -> ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.393191  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.393204  5307 net.cpp:267] TEST Top shape for layer 182 'ctx_output5/relu_mbox_loc_perm' 8 3 5 16 (1920)
-I0510 14:48:30.393214  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_flat' of type 'Flatten'
-I0510 14:48:30.393224  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.393236  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_flat (183)
-I0510 14:48:30.393246  5307 net.cpp:572] ctx_output5/relu_mbox_loc_flat <- ctx_output5/relu_mbox_loc_perm
-I0510 14:48:30.393257  5307 net.cpp:542] ctx_output5/relu_mbox_loc_flat -> ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.393319  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.393332  5307 net.cpp:267] TEST Top shape for layer 183 'ctx_output5/relu_mbox_loc_flat' 8 240 (1920)
-I0510 14:48:30.393343  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf' of type 'Convolution'
-I0510 14:48:30.393352  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.393366  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf (184)
-I0510 14:48:30.393378  5307 net.cpp:572] ctx_output5/relu_mbox_conf <- ctx_output5_ctx_output5/relu_0_split_1
-I0510 14:48:30.393398  5307 net.cpp:542] ctx_output5/relu_mbox_conf -> ctx_output5/relu_mbox_conf
-I0510 14:48:30.395787  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf
-I0510 14:48:30.395815  5307 net.cpp:267] TEST Top shape for layer 184 'ctx_output5/relu_mbox_conf' 8 84 3 5 (10080)
-I0510 14:48:30.395833  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_perm' of type 'Permute'
-I0510 14:48:30.395848  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.395864  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_perm (185)
-I0510 14:48:30.395879  5307 net.cpp:572] ctx_output5/relu_mbox_conf_perm <- ctx_output5/relu_mbox_conf
-I0510 14:48:30.395893  5307 net.cpp:542] ctx_output5/relu_mbox_conf_perm -> ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.395985  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.396003  5307 net.cpp:267] TEST Top shape for layer 185 'ctx_output5/relu_mbox_conf_perm' 8 3 5 84 (10080)
-I0510 14:48:30.396016  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_flat' of type 'Flatten'
-I0510 14:48:30.396030  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396046  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_flat (186)
-I0510 14:48:30.396060  5307 net.cpp:572] ctx_output5/relu_mbox_conf_flat <- ctx_output5/relu_mbox_conf_perm
-I0510 14:48:30.396075  5307 net.cpp:542] ctx_output5/relu_mbox_conf_flat -> ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.396143  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.396162  5307 net.cpp:267] TEST Top shape for layer 186 'ctx_output5/relu_mbox_conf_flat' 8 1260 (10080)
-I0510 14:48:30.396179  5307 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_priorbox' of type 'PriorBox'
-I0510 14:48:30.396200  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396216  5307 net.cpp:200] Created Layer ctx_output5/relu_mbox_priorbox (187)
-I0510 14:48:30.396230  5307 net.cpp:572] ctx_output5/relu_mbox_priorbox <- ctx_output5_ctx_output5/relu_0_split_2
-I0510 14:48:30.396245  5307 net.cpp:572] ctx_output5/relu_mbox_priorbox <- data_data_0_split_5
-I0510 14:48:30.396260  5307 net.cpp:542] ctx_output5/relu_mbox_priorbox -> ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.396292  5307 net.cpp:260] Setting up ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.396317  5307 net.cpp:267] TEST Top shape for layer 187 'ctx_output5/relu_mbox_priorbox' 1 2 240 (480)
-I0510 14:48:30.396332  5307 layer_factory.hpp:172] Creating layer 'mbox_loc' of type 'Concat'
-I0510 14:48:30.396344  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396360  5307 net.cpp:200] Created Layer mbox_loc (188)
-I0510 14:48:30.396374  5307 net.cpp:572] mbox_loc <- ctx_output1/relu_mbox_loc_flat
-I0510 14:48:30.396389  5307 net.cpp:572] mbox_loc <- ctx_output2/relu_mbox_loc_flat
-I0510 14:48:30.396404  5307 net.cpp:572] mbox_loc <- ctx_output3/relu_mbox_loc_flat
-I0510 14:48:30.396417  5307 net.cpp:572] mbox_loc <- ctx_output4/relu_mbox_loc_flat
-I0510 14:48:30.396438  5307 net.cpp:572] mbox_loc <- ctx_output5/relu_mbox_loc_flat
-I0510 14:48:30.396452  5307 net.cpp:542] mbox_loc -> mbox_loc
-I0510 14:48:30.396486  5307 net.cpp:260] Setting up mbox_loc
-I0510 14:48:30.396502  5307 net.cpp:267] TEST Top shape for layer 188 'mbox_loc' 8 12824 (102592)
-I0510 14:48:30.396515  5307 layer_factory.hpp:172] Creating layer 'mbox_conf' of type 'Concat'
-I0510 14:48:30.396543  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396560  5307 net.cpp:200] Created Layer mbox_conf (189)
-I0510 14:48:30.396574  5307 net.cpp:572] mbox_conf <- ctx_output1/relu_mbox_conf_flat
-I0510 14:48:30.396589  5307 net.cpp:572] mbox_conf <- ctx_output2/relu_mbox_conf_flat
-I0510 14:48:30.396603  5307 net.cpp:572] mbox_conf <- ctx_output3/relu_mbox_conf_flat
-I0510 14:48:30.396617  5307 net.cpp:572] mbox_conf <- ctx_output4/relu_mbox_conf_flat
-I0510 14:48:30.396631  5307 net.cpp:572] mbox_conf <- ctx_output5/relu_mbox_conf_flat
-I0510 14:48:30.396648  5307 net.cpp:542] mbox_conf -> mbox_conf
-I0510 14:48:30.396682  5307 net.cpp:260] Setting up mbox_conf
-I0510 14:48:30.396697  5307 net.cpp:267] TEST Top shape for layer 189 'mbox_conf' 8 67326 (538608)
-I0510 14:48:30.396711  5307 layer_factory.hpp:172] Creating layer 'mbox_priorbox' of type 'Concat'
-I0510 14:48:30.396724  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396739  5307 net.cpp:200] Created Layer mbox_priorbox (190)
-I0510 14:48:30.396751  5307 net.cpp:572] mbox_priorbox <- ctx_output1/relu_mbox_priorbox
-I0510 14:48:30.396765  5307 net.cpp:572] mbox_priorbox <- ctx_output2/relu_mbox_priorbox
-I0510 14:48:30.396780  5307 net.cpp:572] mbox_priorbox <- ctx_output3/relu_mbox_priorbox
-I0510 14:48:30.396793  5307 net.cpp:572] mbox_priorbox <- ctx_output4/relu_mbox_priorbox
-I0510 14:48:30.396806  5307 net.cpp:572] mbox_priorbox <- ctx_output5/relu_mbox_priorbox
-I0510 14:48:30.396821  5307 net.cpp:542] mbox_priorbox -> mbox_priorbox
-I0510 14:48:30.396848  5307 net.cpp:260] Setting up mbox_priorbox
-I0510 14:48:30.396864  5307 net.cpp:267] TEST Top shape for layer 190 'mbox_priorbox' 1 2 12824 (25648)
-I0510 14:48:30.396878  5307 layer_factory.hpp:172] Creating layer 'mbox_conf_reshape' of type 'Reshape'
-I0510 14:48:30.396891  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.396908  5307 net.cpp:200] Created Layer mbox_conf_reshape (191)
-I0510 14:48:30.396921  5307 net.cpp:572] mbox_conf_reshape <- mbox_conf
-I0510 14:48:30.396935  5307 net.cpp:542] mbox_conf_reshape -> mbox_conf_reshape
-I0510 14:48:30.396970  5307 net.cpp:260] Setting up mbox_conf_reshape
-I0510 14:48:30.396992  5307 net.cpp:267] TEST Top shape for layer 191 'mbox_conf_reshape' 8 3206 21 (538608)
-I0510 14:48:30.397006  5307 layer_factory.hpp:172] Creating layer 'mbox_conf_softmax' of type 'Softmax'
-I0510 14:48:30.397020  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.397042  5307 net.cpp:200] Created Layer mbox_conf_softmax (192)
-I0510 14:48:30.397056  5307 net.cpp:572] mbox_conf_softmax <- mbox_conf_reshape
-I0510 14:48:30.397070  5307 net.cpp:542] mbox_conf_softmax -> mbox_conf_softmax
-I0510 14:48:30.397140  5307 net.cpp:260] Setting up mbox_conf_softmax
-I0510 14:48:30.397156  5307 net.cpp:267] TEST Top shape for layer 192 'mbox_conf_softmax' 8 3206 21 (538608)
-I0510 14:48:30.397169  5307 layer_factory.hpp:172] Creating layer 'mbox_conf_flatten' of type 'Flatten'
-I0510 14:48:30.397182  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.397215  5307 net.cpp:200] Created Layer mbox_conf_flatten (193)
-I0510 14:48:30.397230  5307 net.cpp:572] mbox_conf_flatten <- mbox_conf_softmax
-I0510 14:48:30.397243  5307 net.cpp:542] mbox_conf_flatten -> mbox_conf_flatten
-I0510 14:48:30.399592  5307 net.cpp:260] Setting up mbox_conf_flatten
-I0510 14:48:30.399636  5307 net.cpp:267] TEST Top shape for layer 193 'mbox_conf_flatten' 8 67326 (538608)
-I0510 14:48:30.399652  5307 layer_factory.hpp:172] Creating layer 'detection_out' of type 'DetectionOutput'
-I0510 14:48:30.399667  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.399698  5307 net.cpp:200] Created Layer detection_out (194)
-I0510 14:48:30.399714  5307 net.cpp:572] detection_out <- mbox_loc
-I0510 14:48:30.399745  5307 net.cpp:572] detection_out <- mbox_conf_flatten
-I0510 14:48:30.399768  5307 net.cpp:572] detection_out <- mbox_priorbox
-I0510 14:48:30.399790  5307 net.cpp:542] detection_out -> detection_out
-I0510 14:48:30.401743  5307 net.cpp:260] Setting up detection_out
-I0510 14:48:30.401783  5307 net.cpp:267] TEST Top shape for layer 194 'detection_out' 1 1 1 7 (7)
-I0510 14:48:30.401799  5307 layer_factory.hpp:172] Creating layer 'detection_eval' of type 'DetectionEvaluate'
-I0510 14:48:30.401813  5307 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0510 14:48:30.401832  5307 net.cpp:200] Created Layer detection_eval (195)
-I0510 14:48:30.401847  5307 net.cpp:572] detection_eval <- detection_out
-I0510 14:48:30.401861  5307 net.cpp:572] detection_eval <- label
-I0510 14:48:30.401875  5307 net.cpp:542] detection_eval -> detection_eval
-I0510 14:48:30.403245  5307 net.cpp:260] Setting up detection_eval
-I0510 14:48:30.403267  5307 net.cpp:267] TEST Top shape for layer 195 'detection_eval' 1 1 21 5 (105)
-I0510 14:48:30.403282  5307 net.cpp:338] detection_eval does not need backward computation.
-I0510 14:48:30.403296  5307 net.cpp:338] detection_out does not need backward computation.
-I0510 14:48:30.403309  5307 net.cpp:338] mbox_conf_flatten does not need backward computation.
-I0510 14:48:30.403322  5307 net.cpp:338] mbox_conf_softmax does not need backward computation.
-I0510 14:48:30.403334  5307 net.cpp:338] mbox_conf_reshape does not need backward computation.
-I0510 14:48:30.403347  5307 net.cpp:338] mbox_priorbox does not need backward computation.
-I0510 14:48:30.403362  5307 net.cpp:338] mbox_conf does not need backward computation.
-I0510 14:48:30.403375  5307 net.cpp:338] mbox_loc does not need backward computation.
-I0510 14:48:30.403389  5307 net.cpp:338] ctx_output5/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403403  5307 net.cpp:338] ctx_output5/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403415  5307 net.cpp:338] ctx_output5/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403429  5307 net.cpp:338] ctx_output5/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403450  5307 net.cpp:338] ctx_output5/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403471  5307 net.cpp:338] ctx_output5/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403484  5307 net.cpp:338] ctx_output5/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403497  5307 net.cpp:338] ctx_output4/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403511  5307 net.cpp:338] ctx_output4/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403522  5307 net.cpp:338] ctx_output4/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403537  5307 net.cpp:338] ctx_output4/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403549  5307 net.cpp:338] ctx_output4/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403563  5307 net.cpp:338] ctx_output4/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403575  5307 net.cpp:338] ctx_output4/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403589  5307 net.cpp:338] ctx_output3/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403602  5307 net.cpp:338] ctx_output3/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403615  5307 net.cpp:338] ctx_output3/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403628  5307 net.cpp:338] ctx_output3/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403641  5307 net.cpp:338] ctx_output3/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403654  5307 net.cpp:338] ctx_output3/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403666  5307 net.cpp:338] ctx_output3/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403682  5307 net.cpp:338] ctx_output2/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403695  5307 net.cpp:338] ctx_output2/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403708  5307 net.cpp:338] ctx_output2/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403722  5307 net.cpp:338] ctx_output2/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403733  5307 net.cpp:338] ctx_output2/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403746  5307 net.cpp:338] ctx_output2/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403759  5307 net.cpp:338] ctx_output2/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403770  5307 net.cpp:338] ctx_output1/relu_mbox_priorbox does not need backward computation.
-I0510 14:48:30.403787  5307 net.cpp:338] ctx_output1/relu_mbox_conf_flat does not need backward computation.
-I0510 14:48:30.403803  5307 net.cpp:338] ctx_output1/relu_mbox_conf_perm does not need backward computation.
-I0510 14:48:30.403818  5307 net.cpp:338] ctx_output1/relu_mbox_conf does not need backward computation.
-I0510 14:48:30.403834  5307 net.cpp:338] ctx_output1/relu_mbox_loc_flat does not need backward computation.
-I0510 14:48:30.403849  5307 net.cpp:338] ctx_output1/relu_mbox_loc_perm does not need backward computation.
-I0510 14:48:30.403864  5307 net.cpp:338] ctx_output1/relu_mbox_loc does not need backward computation.
-I0510 14:48:30.403879  5307 net.cpp:338] ctx_output5_ctx_output5/relu_0_split does not need backward computation.
-I0510 14:48:30.403895  5307 net.cpp:338] ctx_output5/relu does not need backward computation.
-I0510 14:48:30.403910  5307 net.cpp:338] ctx_output5/bn does not need backward computation.
-I0510 14:48:30.403926  5307 net.cpp:338] ctx_output5 does not need backward computation.
-I0510 14:48:30.403944  5307 net.cpp:338] ctx_output5/1x1/relu does not need backward computation.
-I0510 14:48:30.403959  5307 net.cpp:338] ctx_output5/1x1/bn does not need backward computation.
-I0510 14:48:30.403973  5307 net.cpp:338] ctx_output5/1x1 does not need backward computation.
-I0510 14:48:30.403988  5307 net.cpp:338] ctx_output4_ctx_output4/relu_0_split does not need backward computation.
-I0510 14:48:30.404006  5307 net.cpp:338] ctx_output4/relu does not need backward computation.
-I0510 14:48:30.404026  5307 net.cpp:338] ctx_output4/bn does not need backward computation.
-I0510 14:48:30.404042  5307 net.cpp:338] ctx_output4 does not need backward computation.
-I0510 14:48:30.404057  5307 net.cpp:338] ctx_output4/1x1/relu does not need backward computation.
-I0510 14:48:30.404072  5307 net.cpp:338] ctx_output4/1x1/bn does not need backward computation.
-I0510 14:48:30.404086  5307 net.cpp:338] ctx_output4/1x1 does not need backward computation.
-I0510 14:48:30.404101  5307 net.cpp:338] ctx_output3_ctx_output3/relu_0_split does not need backward computation.
-I0510 14:48:30.404116  5307 net.cpp:338] ctx_output3/relu does not need backward computation.
-I0510 14:48:30.404131  5307 net.cpp:338] ctx_output3/bn does not need backward computation.
-I0510 14:48:30.404146  5307 net.cpp:338] ctx_output3 does not need backward computation.
-I0510 14:48:30.404161  5307 net.cpp:338] ctx_output3/1x1/relu does not need backward computation.
-I0510 14:48:30.404176  5307 net.cpp:338] ctx_output3/1x1/bn does not need backward computation.
-I0510 14:48:30.404191  5307 net.cpp:338] ctx_output3/1x1 does not need backward computation.
-I0510 14:48:30.404206  5307 net.cpp:338] ctx_output2_ctx_output2/relu_0_split does not need backward computation.
-I0510 14:48:30.404222  5307 net.cpp:338] ctx_output2/relu does not need backward computation.
-I0510 14:48:30.404237  5307 net.cpp:338] ctx_output2/bn does not need backward computation.
-I0510 14:48:30.404251  5307 net.cpp:338] ctx_output2 does not need backward computation.
-I0510 14:48:30.404266  5307 net.cpp:338] ctx_output2/1x1/relu does not need backward computation.
-I0510 14:48:30.404283  5307 net.cpp:338] ctx_output2/1x1/bn does not need backward computation.
-I0510 14:48:30.404299  5307 net.cpp:338] ctx_output2/1x1 does not need backward computation.
-I0510 14:48:30.404315  5307 net.cpp:338] ctx_output1_ctx_output1/relu_0_split does not need backward computation.
-I0510 14:48:30.404330  5307 net.cpp:338] ctx_output1/relu does not need backward computation.
-I0510 14:48:30.404345  5307 net.cpp:338] ctx_output1/bn does not need backward computation.
-I0510 14:48:30.404359  5307 net.cpp:338] ctx_output1 does not need backward computation.
-I0510 14:48:30.404374  5307 net.cpp:338] ctx_output1/1x1/relu does not need backward computation.
-I0510 14:48:30.404389  5307 net.cpp:338] ctx_output1/1x1/bn does not need backward computation.
-I0510 14:48:30.404404  5307 net.cpp:338] ctx_output1/1x1 does not need backward computation.
-I0510 14:48:30.404419  5307 net.cpp:338] pool8 does not need backward computation.
-I0510 14:48:30.404434  5307 net.cpp:338] pool7_pool7_0_split does not need backward computation.
-I0510 14:48:30.404449  5307 net.cpp:338] pool7 does not need backward computation.
-I0510 14:48:30.404464  5307 net.cpp:338] pool6_pool6_0_split does not need backward computation.
-I0510 14:48:30.404479  5307 net.cpp:338] pool6 does not need backward computation.
-I0510 14:48:30.404495  5307 net.cpp:338] conv6/sep_relu6/sep_0_split does not need backward computation.
-I0510 14:48:30.404510  5307 net.cpp:338] relu6/sep does not need backward computation.
-I0510 14:48:30.404530  5307 net.cpp:338] conv6/sep/scale does not need backward computation.
-I0510 14:48:30.404546  5307 net.cpp:338] conv6/sep/bn does not need backward computation.
-I0510 14:48:30.404561  5307 net.cpp:338] conv6/sep does not need backward computation.
-I0510 14:48:30.404577  5307 net.cpp:338] relu6/dw does not need backward computation.
-I0510 14:48:30.404592  5307 net.cpp:338] conv6/dw/scale does not need backward computation.
-I0510 14:48:30.404606  5307 net.cpp:338] conv6/dw/bn does not need backward computation.
-I0510 14:48:30.404621  5307 net.cpp:338] conv6/dw does not need backward computation.
-I0510 14:48:30.404636  5307 net.cpp:338] relu5_6/sep does not need backward computation.
-I0510 14:48:30.404650  5307 net.cpp:338] conv5_6/sep/scale does not need backward computation.
-I0510 14:48:30.404665  5307 net.cpp:338] conv5_6/sep/bn does not need backward computation.
-I0510 14:48:30.404683  5307 net.cpp:338] conv5_6/sep does not need backward computation.
-I0510 14:48:30.404705  5307 net.cpp:338] relu5_6/dw does not need backward computation.
-I0510 14:48:30.404719  5307 net.cpp:338] conv5_6/dw/scale does not need backward computation.
-I0510 14:48:30.404733  5307 net.cpp:338] conv5_6/dw/bn does not need backward computation.
-I0510 14:48:30.404748  5307 net.cpp:338] conv5_6/dw does not need backward computation.
-I0510 14:48:30.404763  5307 net.cpp:338] conv5_5/sep_relu5_5/sep_0_split does not need backward computation.
-I0510 14:48:30.404779  5307 net.cpp:338] relu5_5/sep does not need backward computation.
-I0510 14:48:30.404793  5307 net.cpp:338] conv5_5/sep/scale does not need backward computation.
-I0510 14:48:30.404808  5307 net.cpp:338] conv5_5/sep/bn does not need backward computation.
-I0510 14:48:30.404824  5307 net.cpp:338] conv5_5/sep does not need backward computation.
-I0510 14:48:30.404842  5307 net.cpp:338] relu5_5/dw does not need backward computation.
-I0510 14:48:30.404860  5307 net.cpp:338] conv5_5/dw/scale does not need backward computation.
-I0510 14:48:30.404875  5307 net.cpp:338] conv5_5/dw/bn does not need backward computation.
-I0510 14:48:30.404891  5307 net.cpp:338] conv5_5/dw does not need backward computation.
-I0510 14:48:30.404906  5307 net.cpp:338] relu5_4/sep does not need backward computation.
-I0510 14:48:30.404920  5307 net.cpp:338] conv5_4/sep/scale does not need backward computation.
-I0510 14:48:30.404935  5307 net.cpp:338] conv5_4/sep/bn does not need backward computation.
-I0510 14:48:30.404949  5307 net.cpp:338] conv5_4/sep does not need backward computation.
-I0510 14:48:30.404964  5307 net.cpp:338] relu5_4/dw does not need backward computation.
-I0510 14:48:30.404978  5307 net.cpp:338] conv5_4/dw/scale does not need backward computation.
-I0510 14:48:30.404996  5307 net.cpp:338] conv5_4/dw/bn does not need backward computation.
-I0510 14:48:30.405012  5307 net.cpp:338] conv5_4/dw does not need backward computation.
-I0510 14:48:30.405027  5307 net.cpp:338] relu5_3/sep does not need backward computation.
-I0510 14:48:30.405042  5307 net.cpp:338] conv5_3/sep/scale does not need backward computation.
-I0510 14:48:30.405057  5307 net.cpp:338] conv5_3/sep/bn does not need backward computation.
-I0510 14:48:30.405076  5307 net.cpp:338] conv5_3/sep does not need backward computation.
-I0510 14:48:30.405092  5307 net.cpp:338] relu5_3/dw does not need backward computation.
-I0510 14:48:30.405107  5307 net.cpp:338] conv5_3/dw/scale does not need backward computation.
-I0510 14:48:30.405122  5307 net.cpp:338] conv5_3/dw/bn does not need backward computation.
-I0510 14:48:30.405136  5307 net.cpp:338] conv5_3/dw does not need backward computation.
-I0510 14:48:30.405153  5307 net.cpp:338] relu5_2/sep does not need backward computation.
-I0510 14:48:30.405167  5307 net.cpp:338] conv5_2/sep/scale does not need backward computation.
-I0510 14:48:30.405182  5307 net.cpp:338] conv5_2/sep/bn does not need backward computation.
-I0510 14:48:30.405198  5307 net.cpp:338] conv5_2/sep does not need backward computation.
-I0510 14:48:30.405213  5307 net.cpp:338] relu5_2/dw does not need backward computation.
-I0510 14:48:30.405228  5307 net.cpp:338] conv5_2/dw/scale does not need backward computation.
-I0510 14:48:30.405243  5307 net.cpp:338] conv5_2/dw/bn does not need backward computation.
-I0510 14:48:30.405258  5307 net.cpp:338] conv5_2/dw does not need backward computation.
-I0510 14:48:30.405273  5307 net.cpp:338] relu5_1/sep does not need backward computation.
-I0510 14:48:30.405287  5307 net.cpp:338] conv5_1/sep/scale does not need backward computation.
-I0510 14:48:30.405303  5307 net.cpp:338] conv5_1/sep/bn does not need backward computation.
-I0510 14:48:30.405318  5307 net.cpp:338] conv5_1/sep does not need backward computation.
-I0510 14:48:30.405333  5307 net.cpp:338] relu5_1/dw does not need backward computation.
-I0510 14:48:30.405346  5307 net.cpp:338] conv5_1/dw/scale does not need backward computation.
-I0510 14:48:30.405361  5307 net.cpp:338] conv5_1/dw/bn does not need backward computation.
-I0510 14:48:30.405386  5307 net.cpp:338] conv5_1/dw does not need backward computation.
-I0510 14:48:30.405408  5307 net.cpp:338] relu4_2/sep does not need backward computation.
-I0510 14:48:30.405423  5307 net.cpp:338] conv4_2/sep/scale does not need backward computation.
-I0510 14:48:30.405438  5307 net.cpp:338] conv4_2/sep/bn does not need backward computation.
-I0510 14:48:30.405453  5307 net.cpp:338] conv4_2/sep does not need backward computation.
-I0510 14:48:30.405468  5307 net.cpp:338] relu4_2/dw does not need backward computation.
-I0510 14:48:30.405483  5307 net.cpp:338] conv4_2/dw/scale does not need backward computation.
-I0510 14:48:30.405498  5307 net.cpp:338] conv4_2/dw/bn does not need backward computation.
-I0510 14:48:30.405513  5307 net.cpp:338] conv4_2/dw does not need backward computation.
-I0510 14:48:30.405527  5307 net.cpp:338] relu4_1/sep does not need backward computation.
-I0510 14:48:30.405542  5307 net.cpp:338] conv4_1/sep/scale does not need backward computation.
-I0510 14:48:30.405557  5307 net.cpp:338] conv4_1/sep/bn does not need backward computation.
-I0510 14:48:30.405571  5307 net.cpp:338] conv4_1/sep does not need backward computation.
-I0510 14:48:30.405586  5307 net.cpp:338] relu4_1/dw does not need backward computation.
-I0510 14:48:30.405601  5307 net.cpp:338] conv4_1/dw/scale does not need backward computation.
-I0510 14:48:30.405614  5307 net.cpp:338] conv4_1/dw/bn does not need backward computation.
-I0510 14:48:30.405630  5307 net.cpp:338] conv4_1/dw does not need backward computation.
-I0510 14:48:30.405644  5307 net.cpp:338] relu3_2/sep does not need backward computation.
-I0510 14:48:30.405659  5307 net.cpp:338] conv3_2/sep/scale does not need backward computation.
-I0510 14:48:30.405673  5307 net.cpp:338] conv3_2/sep/bn does not need backward computation.
-I0510 14:48:30.405691  5307 net.cpp:338] conv3_2/sep does not need backward computation.
-I0510 14:48:30.405706  5307 net.cpp:338] relu3_2/dw does not need backward computation.
-I0510 14:48:30.405722  5307 net.cpp:338] conv3_2/dw/scale does not need backward computation.
-I0510 14:48:30.405736  5307 net.cpp:338] conv3_2/dw/bn does not need backward computation.
-I0510 14:48:30.405751  5307 net.cpp:338] conv3_2/dw does not need backward computation.
-I0510 14:48:30.405766  5307 net.cpp:338] relu3_1/sep does not need backward computation.
-I0510 14:48:30.405781  5307 net.cpp:338] conv3_1/sep/scale does not need backward computation.
-I0510 14:48:30.405797  5307 net.cpp:338] conv3_1/sep/bn does not need backward computation.
-I0510 14:48:30.405812  5307 net.cpp:338] conv3_1/sep does not need backward computation.
-I0510 14:48:30.405827  5307 net.cpp:338] relu3_1/dw does not need backward computation.
-I0510 14:48:30.405841  5307 net.cpp:338] conv3_1/dw/scale does not need backward computation.
-I0510 14:48:30.405856  5307 net.cpp:338] conv3_1/dw/bn does not need backward computation.
-I0510 14:48:30.405870  5307 net.cpp:338] conv3_1/dw does not need backward computation.
-I0510 14:48:30.405886  5307 net.cpp:338] relu2_2/sep does not need backward computation.
-I0510 14:48:30.405901  5307 net.cpp:338] conv2_2/sep/scale does not need backward computation.
-I0510 14:48:30.405916  5307 net.cpp:338] conv2_2/sep/bn does not need backward computation.
-I0510 14:48:30.405930  5307 net.cpp:338] conv2_2/sep does not need backward computation.
-I0510 14:48:30.405944  5307 net.cpp:338] relu2_2/dw does not need backward computation.
-I0510 14:48:30.405959  5307 net.cpp:338] conv2_2/dw/scale does not need backward computation.
-I0510 14:48:30.405974  5307 net.cpp:338] conv2_2/dw/bn does not need backward computation.
-I0510 14:48:30.405989  5307 net.cpp:338] conv2_2/dw does not need backward computation.
-I0510 14:48:30.406004  5307 net.cpp:338] relu2_1/sep does not need backward computation.
-I0510 14:48:30.406018  5307 net.cpp:338] conv2_1/sep/scale does not need backward computation.
-I0510 14:48:30.406033  5307 net.cpp:338] conv2_1/sep/bn does not need backward computation.
-I0510 14:48:30.406046  5307 net.cpp:338] conv2_1/sep does not need backward computation.
-I0510 14:48:30.406064  5307 net.cpp:338] relu2_1/dw does not need backward computation.
-I0510 14:48:30.406086  5307 net.cpp:338] conv2_1/dw/scale does not need backward computation.
-I0510 14:48:30.406100  5307 net.cpp:338] conv2_1/dw/bn does not need backward computation.
-I0510 14:48:30.406116  5307 net.cpp:338] conv2_1/dw does not need backward computation.
-I0510 14:48:30.406131  5307 net.cpp:338] relu1 does not need backward computation.
-I0510 14:48:30.406146  5307 net.cpp:338] conv1/scale does not need backward computation.
-I0510 14:48:30.406160  5307 net.cpp:338] conv1/bn does not need backward computation.
-I0510 14:48:30.406175  5307 net.cpp:338] conv1 does not need backward computation.
-I0510 14:48:30.406190  5307 net.cpp:338] data/bias does not need backward computation.
-I0510 14:48:30.406205  5307 net.cpp:338] data_data_0_split does not need backward computation.
-I0510 14:48:30.406220  5307 net.cpp:338] data does not need backward computation.
-I0510 14:48:30.406234  5307 net.cpp:380] This network produces output detection_eval
-I0510 14:48:30.406448  5307 net.cpp:403] Top memory (TEST) required for data: 1081855432 diff: 1081855432
-I0510 14:48:30.406466  5307 net.cpp:406] Bottom memory (TEST) required for data: 1081855008 diff: 1081855008
-I0510 14:48:30.406481  5307 net.cpp:409] Shared (in-place) memory (TEST) by data: 679149568 diff: 679149568
-I0510 14:48:30.406496  5307 net.cpp:412] Parameters memory (TEST) required for data: 9462808 diff: 9462808
-I0510 14:48:30.406510  5307 net.cpp:415] Parameters shared memory (TEST) by data: 0 diff: 0
-I0510 14:48:30.406525  5307 net.cpp:421] Network initialization done.
-I0510 14:48:30.406883  5307 solver.cpp:55] Solver scaffolding done.
-I0510 14:48:30.413641  5307 caffe.cpp:158] Finetuning from ../trained/image_classification/imagenet_mobilenet-0.5/initial/imagenet_mobilenet-0.5_iter_320000.caffemodel
-I0510 14:48:30.415630  5307 net.cpp:1144] Copying source layer data Type:Data #blobs=0
-I0510 14:48:30.415675  5307 net.cpp:1144] Copying source layer data/bias Type:Bias #blobs=1
-I0510 14:48:30.415719  5307 net.cpp:1144] Copying source layer conv1 Type:Convolution #blobs=1
-I0510 14:48:30.415745  5307 net.cpp:1144] Copying source layer conv1/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.415774  5307 net.cpp:1144] Copying source layer conv1/scale Type:Scale #blobs=2
-I0510 14:48:30.415802  5307 net.cpp:1144] Copying source layer relu1 Type:ReLU #blobs=0
-I0510 14:48:30.415817  5307 net.cpp:1144] Copying source layer conv2_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.415838  5307 net.cpp:1144] Copying source layer conv2_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.415866  5307 net.cpp:1144] Copying source layer conv2_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.415891  5307 net.cpp:1144] Copying source layer relu2_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.415906  5307 net.cpp:1144] Copying source layer conv2_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.415927  5307 net.cpp:1144] Copying source layer conv2_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.415959  5307 net.cpp:1144] Copying source layer conv2_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.415987  5307 net.cpp:1144] Copying source layer relu2_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.416002  5307 net.cpp:1144] Copying source layer conv2_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.416023  5307 net.cpp:1144] Copying source layer conv2_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416052  5307 net.cpp:1144] Copying source layer conv2_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416079  5307 net.cpp:1144] Copying source layer relu2_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.416095  5307 net.cpp:1144] Copying source layer conv2_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.416118  5307 net.cpp:1144] Copying source layer conv2_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416151  5307 net.cpp:1144] Copying source layer conv2_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416177  5307 net.cpp:1144] Copying source layer relu2_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.416193  5307 net.cpp:1144] Copying source layer conv3_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.416219  5307 net.cpp:1144] Copying source layer conv3_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416255  5307 net.cpp:1144] Copying source layer conv3_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416281  5307 net.cpp:1144] Copying source layer relu3_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.416297  5307 net.cpp:1144] Copying source layer conv3_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.416319  5307 net.cpp:1144] Copying source layer conv3_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416348  5307 net.cpp:1144] Copying source layer conv3_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416374  5307 net.cpp:1144] Copying source layer relu3_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.416389  5307 net.cpp:1144] Copying source layer conv3_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.416410  5307 net.cpp:1144] Copying source layer conv3_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416440  5307 net.cpp:1144] Copying source layer conv3_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416465  5307 net.cpp:1144] Copying source layer relu3_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.416479  5307 net.cpp:1144] Copying source layer conv3_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.416503  5307 net.cpp:1144] Copying source layer conv3_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416546  5307 net.cpp:1144] Copying source layer conv3_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416574  5307 net.cpp:1144] Copying source layer relu3_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.416589  5307 net.cpp:1144] Copying source layer conv4_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.416610  5307 net.cpp:1144] Copying source layer conv4_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416638  5307 net.cpp:1144] Copying source layer conv4_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416666  5307 net.cpp:1144] Copying source layer relu4_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.416682  5307 net.cpp:1144] Copying source layer conv4_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.416709  5307 net.cpp:1144] Copying source layer conv4_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416739  5307 net.cpp:1144] Copying source layer conv4_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416764  5307 net.cpp:1144] Copying source layer relu4_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.416779  5307 net.cpp:1144] Copying source layer conv4_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.416802  5307 net.cpp:1144] Copying source layer conv4_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416828  5307 net.cpp:1144] Copying source layer conv4_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.416851  5307 net.cpp:1144] Copying source layer relu4_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.416863  5307 net.cpp:1144] Copying source layer conv4_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.416894  5307 net.cpp:1144] Copying source layer conv4_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.416921  5307 net.cpp:1144] Copying source layer conv4_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.416944  5307 net.cpp:1144] Copying source layer relu4_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.416956  5307 net.cpp:1144] Copying source layer conv5_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.416975  5307 net.cpp:1144] Copying source layer conv5_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417001  5307 net.cpp:1144] Copying source layer conv5_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417021  5307 net.cpp:1144] Copying source layer relu5_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.417034  5307 net.cpp:1144] Copying source layer conv5_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.417079  5307 net.cpp:1144] Copying source layer conv5_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417106  5307 net.cpp:1144] Copying source layer conv5_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417129  5307 net.cpp:1144] Copying source layer relu5_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.417141  5307 net.cpp:1144] Copying source layer conv5_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.417158  5307 net.cpp:1144] Copying source layer conv5_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417186  5307 net.cpp:1144] Copying source layer conv5_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417217  5307 net.cpp:1144] Copying source layer relu5_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.417229  5307 net.cpp:1144] Copying source layer conv5_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.417277  5307 net.cpp:1144] Copying source layer conv5_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417304  5307 net.cpp:1144] Copying source layer conv5_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417327  5307 net.cpp:1144] Copying source layer relu5_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.417340  5307 net.cpp:1144] Copying source layer conv5_3/dw Type:Convolution #blobs=1
-I0510 14:48:30.417358  5307 net.cpp:1144] Copying source layer conv5_3/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417383  5307 net.cpp:1144] Copying source layer conv5_3/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417405  5307 net.cpp:1144] Copying source layer relu5_3/dw Type:ReLU #blobs=0
-I0510 14:48:30.417418  5307 net.cpp:1144] Copying source layer conv5_3/sep Type:Convolution #blobs=1
-I0510 14:48:30.417486  5307 net.cpp:1144] Copying source layer conv5_3/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417515  5307 net.cpp:1144] Copying source layer conv5_3/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417536  5307 net.cpp:1144] Copying source layer relu5_3/sep Type:ReLU #blobs=0
-I0510 14:48:30.417549  5307 net.cpp:1144] Copying source layer conv5_4/dw Type:Convolution #blobs=1
-I0510 14:48:30.417567  5307 net.cpp:1144] Copying source layer conv5_4/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417593  5307 net.cpp:1144] Copying source layer conv5_4/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417614  5307 net.cpp:1144] Copying source layer relu5_4/dw Type:ReLU #blobs=0
-I0510 14:48:30.417626  5307 net.cpp:1144] Copying source layer conv5_4/sep Type:Convolution #blobs=1
-I0510 14:48:30.417673  5307 net.cpp:1144] Copying source layer conv5_4/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417699  5307 net.cpp:1144] Copying source layer conv5_4/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417721  5307 net.cpp:1144] Copying source layer relu5_4/sep Type:ReLU #blobs=0
-I0510 14:48:30.417733  5307 net.cpp:1144] Copying source layer conv5_5/dw Type:Convolution #blobs=1
-I0510 14:48:30.417752  5307 net.cpp:1144] Copying source layer conv5_5/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417776  5307 net.cpp:1144] Copying source layer conv5_5/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417798  5307 net.cpp:1144] Copying source layer relu5_5/dw Type:ReLU #blobs=0
-I0510 14:48:30.417810  5307 net.cpp:1144] Copying source layer conv5_5/sep Type:Convolution #blobs=1
-I0510 14:48:30.417853  5307 net.cpp:1144] Copying source layer conv5_5/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417879  5307 net.cpp:1144] Copying source layer conv5_5/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.417902  5307 net.cpp:1144] Copying source layer relu5_5/sep Type:ReLU #blobs=0
-I0510 14:48:30.417915  5307 net.cpp:1144] Copying source layer conv5_6/dw Type:Convolution #blobs=1
-I0510 14:48:30.417933  5307 net.cpp:1144] Copying source layer conv5_6/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.417958  5307 net.cpp:1144] Copying source layer conv5_6/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.417980  5307 net.cpp:1144] Copying source layer relu5_6/dw Type:ReLU #blobs=0
-I0510 14:48:30.417992  5307 net.cpp:1144] Copying source layer conv5_6/sep Type:Convolution #blobs=1
-I0510 14:48:30.418058  5307 net.cpp:1144] Copying source layer conv5_6/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.418087  5307 net.cpp:1144] Copying source layer conv5_6/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.418109  5307 net.cpp:1144] Copying source layer relu5_6/sep Type:ReLU #blobs=0
-I0510 14:48:30.418121  5307 net.cpp:1144] Copying source layer conv6/dw Type:Convolution #blobs=1
-I0510 14:48:30.418140  5307 net.cpp:1144] Copying source layer conv6/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.418165  5307 net.cpp:1144] Copying source layer conv6/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.418189  5307 net.cpp:1144] Copying source layer relu6/dw Type:ReLU #blobs=0
-I0510 14:48:30.418203  5307 net.cpp:1144] Copying source layer conv6/sep Type:Convolution #blobs=1
-I0510 14:48:30.418311  5307 net.cpp:1144] Copying source layer conv6/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.418339  5307 net.cpp:1144] Copying source layer conv6/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.418361  5307 net.cpp:1144] Copying source layer relu6/sep Type:ReLU #blobs=0
-I0510 14:48:30.418375  5307 net.cpp:1144] Copying source layer pool6 Type:Pooling #blobs=0
-I0510 14:48:30.418385  5307 net.cpp:1136] Ignoring source layer fc7
-I0510 14:48:30.418396  5307 net.cpp:1136] Ignoring source layer loss
-I0510 14:48:30.420141  5307 net.cpp:1144] Copying source layer data Type:Data #blobs=0
-I0510 14:48:30.420172  5307 net.cpp:1144] Copying source layer data/bias Type:Bias #blobs=1
-I0510 14:48:30.420200  5307 net.cpp:1144] Copying source layer conv1 Type:Convolution #blobs=1
-I0510 14:48:30.420218  5307 net.cpp:1144] Copying source layer conv1/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420244  5307 net.cpp:1144] Copying source layer conv1/scale Type:Scale #blobs=2
-I0510 14:48:30.420265  5307 net.cpp:1144] Copying source layer relu1 Type:ReLU #blobs=0
-I0510 14:48:30.420277  5307 net.cpp:1144] Copying source layer conv2_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.420295  5307 net.cpp:1144] Copying source layer conv2_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420320  5307 net.cpp:1144] Copying source layer conv2_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420341  5307 net.cpp:1144] Copying source layer relu2_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.420352  5307 net.cpp:1144] Copying source layer conv2_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.420369  5307 net.cpp:1144] Copying source layer conv2_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420398  5307 net.cpp:1144] Copying source layer conv2_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.420421  5307 net.cpp:1144] Copying source layer relu2_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.420433  5307 net.cpp:1144] Copying source layer conv2_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.420450  5307 net.cpp:1144] Copying source layer conv2_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420476  5307 net.cpp:1144] Copying source layer conv2_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420500  5307 net.cpp:1144] Copying source layer relu2_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.420512  5307 net.cpp:1144] Copying source layer conv2_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.420537  5307 net.cpp:1144] Copying source layer conv2_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420565  5307 net.cpp:1144] Copying source layer conv2_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.420586  5307 net.cpp:1144] Copying source layer relu2_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.420598  5307 net.cpp:1144] Copying source layer conv3_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.420616  5307 net.cpp:1144] Copying source layer conv3_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420640  5307 net.cpp:1144] Copying source layer conv3_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420662  5307 net.cpp:1144] Copying source layer relu3_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.420675  5307 net.cpp:1144] Copying source layer conv3_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.420693  5307 net.cpp:1144] Copying source layer conv3_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420718  5307 net.cpp:1144] Copying source layer conv3_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.420740  5307 net.cpp:1144] Copying source layer relu3_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.420753  5307 net.cpp:1144] Copying source layer conv3_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.420769  5307 net.cpp:1144] Copying source layer conv3_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420794  5307 net.cpp:1144] Copying source layer conv3_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420815  5307 net.cpp:1144] Copying source layer relu3_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.420827  5307 net.cpp:1144] Copying source layer conv3_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.420851  5307 net.cpp:1144] Copying source layer conv3_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420883  5307 net.cpp:1144] Copying source layer conv3_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.420905  5307 net.cpp:1144] Copying source layer relu3_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.420918  5307 net.cpp:1144] Copying source layer conv4_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.420936  5307 net.cpp:1144] Copying source layer conv4_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.420960  5307 net.cpp:1144] Copying source layer conv4_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.420982  5307 net.cpp:1144] Copying source layer relu4_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.420994  5307 net.cpp:1144] Copying source layer conv4_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.421017  5307 net.cpp:1144] Copying source layer conv4_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421042  5307 net.cpp:1144] Copying source layer conv4_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421064  5307 net.cpp:1144] Copying source layer relu4_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.421077  5307 net.cpp:1144] Copying source layer conv4_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.421095  5307 net.cpp:1144] Copying source layer conv4_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421119  5307 net.cpp:1144] Copying source layer conv4_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421141  5307 net.cpp:1144] Copying source layer relu4_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.421154  5307 net.cpp:1144] Copying source layer conv4_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.421190  5307 net.cpp:1144] Copying source layer conv4_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421217  5307 net.cpp:1144] Copying source layer conv4_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421241  5307 net.cpp:1144] Copying source layer relu4_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.421254  5307 net.cpp:1144] Copying source layer conv5_1/dw Type:Convolution #blobs=1
-I0510 14:48:30.421272  5307 net.cpp:1144] Copying source layer conv5_1/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421298  5307 net.cpp:1144] Copying source layer conv5_1/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421319  5307 net.cpp:1144] Copying source layer relu5_1/dw Type:ReLU #blobs=0
-I0510 14:48:30.421331  5307 net.cpp:1144] Copying source layer conv5_1/sep Type:Convolution #blobs=1
-I0510 14:48:30.421375  5307 net.cpp:1144] Copying source layer conv5_1/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421401  5307 net.cpp:1144] Copying source layer conv5_1/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421423  5307 net.cpp:1144] Copying source layer relu5_1/sep Type:ReLU #blobs=0
-I0510 14:48:30.421435  5307 net.cpp:1144] Copying source layer conv5_2/dw Type:Convolution #blobs=1
-I0510 14:48:30.421452  5307 net.cpp:1144] Copying source layer conv5_2/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421476  5307 net.cpp:1144] Copying source layer conv5_2/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421499  5307 net.cpp:1144] Copying source layer relu5_2/dw Type:ReLU #blobs=0
-I0510 14:48:30.421510  5307 net.cpp:1144] Copying source layer conv5_2/sep Type:Convolution #blobs=1
-I0510 14:48:30.421555  5307 net.cpp:1144] Copying source layer conv5_2/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421581  5307 net.cpp:1144] Copying source layer conv5_2/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421603  5307 net.cpp:1144] Copying source layer relu5_2/sep Type:ReLU #blobs=0
-I0510 14:48:30.421615  5307 net.cpp:1144] Copying source layer conv5_3/dw Type:Convolution #blobs=1
-I0510 14:48:30.421633  5307 net.cpp:1144] Copying source layer conv5_3/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421658  5307 net.cpp:1144] Copying source layer conv5_3/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421681  5307 net.cpp:1144] Copying source layer relu5_3/dw Type:ReLU #blobs=0
-I0510 14:48:30.421694  5307 net.cpp:1144] Copying source layer conv5_3/sep Type:Convolution #blobs=1
-I0510 14:48:30.421737  5307 net.cpp:1144] Copying source layer conv5_3/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421762  5307 net.cpp:1144] Copying source layer conv5_3/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421788  5307 net.cpp:1144] Copying source layer relu5_3/sep Type:ReLU #blobs=0
-I0510 14:48:30.421805  5307 net.cpp:1144] Copying source layer conv5_4/dw Type:Convolution #blobs=1
-I0510 14:48:30.421824  5307 net.cpp:1144] Copying source layer conv5_4/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421849  5307 net.cpp:1144] Copying source layer conv5_4/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.421871  5307 net.cpp:1144] Copying source layer relu5_4/dw Type:ReLU #blobs=0
-I0510 14:48:30.421883  5307 net.cpp:1144] Copying source layer conv5_4/sep Type:Convolution #blobs=1
-I0510 14:48:30.421927  5307 net.cpp:1144] Copying source layer conv5_4/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.421955  5307 net.cpp:1144] Copying source layer conv5_4/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.421979  5307 net.cpp:1144] Copying source layer relu5_4/sep Type:ReLU #blobs=0
-I0510 14:48:30.421993  5307 net.cpp:1144] Copying source layer conv5_5/dw Type:Convolution #blobs=1
-I0510 14:48:30.422011  5307 net.cpp:1144] Copying source layer conv5_5/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422036  5307 net.cpp:1144] Copying source layer conv5_5/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.422060  5307 net.cpp:1144] Copying source layer relu5_5/dw Type:ReLU #blobs=0
-I0510 14:48:30.422073  5307 net.cpp:1144] Copying source layer conv5_5/sep Type:Convolution #blobs=1
-I0510 14:48:30.422117  5307 net.cpp:1144] Copying source layer conv5_5/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422147  5307 net.cpp:1144] Copying source layer conv5_5/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.422169  5307 net.cpp:1144] Copying source layer relu5_5/sep Type:ReLU #blobs=0
-I0510 14:48:30.422183  5307 net.cpp:1144] Copying source layer conv5_6/dw Type:Convolution #blobs=1
-I0510 14:48:30.422205  5307 net.cpp:1144] Copying source layer conv5_6/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422232  5307 net.cpp:1144] Copying source layer conv5_6/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.422255  5307 net.cpp:1144] Copying source layer relu5_6/dw Type:ReLU #blobs=0
-I0510 14:48:30.422268  5307 net.cpp:1144] Copying source layer conv5_6/sep Type:Convolution #blobs=1
-I0510 14:48:30.422336  5307 net.cpp:1144] Copying source layer conv5_6/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422365  5307 net.cpp:1144] Copying source layer conv5_6/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.422389  5307 net.cpp:1144] Copying source layer relu5_6/sep Type:ReLU #blobs=0
-I0510 14:48:30.422402  5307 net.cpp:1144] Copying source layer conv6/dw Type:Convolution #blobs=1
-I0510 14:48:30.422422  5307 net.cpp:1144] Copying source layer conv6/dw/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422449  5307 net.cpp:1144] Copying source layer conv6/dw/scale Type:Scale #blobs=2
-I0510 14:48:30.422472  5307 net.cpp:1144] Copying source layer relu6/dw Type:ReLU #blobs=0
-I0510 14:48:30.422485  5307 net.cpp:1144] Copying source layer conv6/sep Type:Convolution #blobs=1
-I0510 14:48:30.422605  5307 net.cpp:1144] Copying source layer conv6/sep/bn Type:BatchNorm #blobs=3
-I0510 14:48:30.422636  5307 net.cpp:1144] Copying source layer conv6/sep/scale Type:Scale #blobs=2
-I0510 14:48:30.422662  5307 net.cpp:1144] Copying source layer relu6/sep Type:ReLU #blobs=0
-I0510 14:48:30.422675  5307 net.cpp:1144] Copying source layer pool6 Type:Pooling #blobs=0
-I0510 14:48:30.422689  5307 net.cpp:1136] Ignoring source layer fc7
-I0510 14:48:30.422701  5307 net.cpp:1136] Ignoring source layer loss
-I0510 14:48:30.422816  5307 caffe.cpp:260] Starting Optimization
-I0510 14:48:30.422832  5307 solver.cpp:453] Solving mobiledetnet-0.5
-I0510 14:48:30.422842  5307 solver.cpp:454] Learning Rate Policy: multistep
-I0510 14:48:30.422900  5307 net.cpp:1443] [0] Reserving 9381120 bytes of shared learnable space for type FLOAT
-I0510 14:48:30.428328  5307 solver.cpp:269] Initial Test started...
-I0510 14:48:30.428369  5307 solver.cpp:635] Iteration 0, Testing net (#0)
-I0510 14:48:30.429464  5355 common.cpp:528] NVML initialized, thread 5355
-I0510 14:48:30.433272  5307 net.cpp:1071] Ignoring source layer mbox_loss
-I0510 14:48:30.508715  5355 common.cpp:550] NVML succeeded to set CPU affinity on device 0, thread 5355
-I0510 14:49:00.809654  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 14:49:00.990506  5307 solver.cpp:747] class AP 1: 4.20608e-06
-I0510 14:49:00.998561  5307 solver.cpp:747] class AP 2: 2.36312e-05
-I0510 14:49:01.033555  5307 solver.cpp:747] class AP 3: 3.95601e-05
-I0510 14:49:01.033614  5307 solver.cpp:747] class AP 4: 0
-W0510 14:49:01.033622  5307 solver.cpp:731] Missing true_pos for label: 5
-W0510 14:49:01.033705  5307 solver.cpp:731] Missing true_pos for label: 6
-W0510 14:49:01.033710  5307 solver.cpp:731] Missing true_pos for label: 7
-W0510 14:49:01.033713  5307 solver.cpp:731] Missing true_pos for label: 8
-W0510 14:49:01.033716  5307 solver.cpp:731] Missing true_pos for label: 9
-W0510 14:49:01.033718  5307 solver.cpp:731] Missing true_pos for label: 10
-W0510 14:49:01.033721  5307 solver.cpp:731] Missing true_pos for label: 11
-W0510 14:49:01.033723  5307 solver.cpp:731] Missing true_pos for label: 12
-W0510 14:49:01.033726  5307 solver.cpp:731] Missing true_pos for label: 13
-W0510 14:49:01.033728  5307 solver.cpp:731] Missing true_pos for label: 14
-W0510 14:49:01.033731  5307 solver.cpp:731] Missing true_pos for label: 15
-W0510 14:49:01.033735  5307 solver.cpp:731] Missing true_pos for label: 16
-W0510 14:49:01.033736  5307 solver.cpp:731] Missing true_pos for label: 17
-W0510 14:49:01.033740  5307 solver.cpp:731] Missing true_pos for label: 18
-W0510 14:49:01.033741  5307 solver.cpp:731] Missing true_pos for label: 19
-W0510 14:49:01.033744  5307 solver.cpp:731] Missing true_pos for label: 20
-I0510 14:49:01.033747  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 3.36987e-06
-I0510 14:49:01.033784  5307 solver.cpp:274] Initial Test completed in 30.6046s
-I0510 14:49:01.729894  5307 solver.cpp:358] Iteration 0 (0.696069 s), loss = 30.2997
-I0510 14:49:01.729921  5307 solver.cpp:376]     Train net output #0: mbox_loss = 28.8664 (* 1 = 28.8664 loss)
-I0510 14:49:01.729928  5307 sgd_solver.cpp:172] Iteration 0, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:49:01.750205  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv1' with space 3.29M 3/1 1 1 3     (avail 1.28G, req 3.29M)        t: 0 0 0.92
-I0510 14:49:01.872751  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv2_1/dw' with space 3.29M 16/16. 0 1 3     (avail 1.28G, req 3.29M)        t: 0 2.47 8.62
-I0510 14:49:01.937407  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv2_1/sep' with space 3.29M 16/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.33 1.49
-I0510 14:49:02.031493  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv2_2/dw' with space 3.29M 32/32. 0 0 3     (avail 1.28G, req 3.29M)        t: 0 3.58 4.43
-I0510 14:49:02.084003  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv2_2/sep' with space 3.29M 32/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.31 0.83
-I0510 14:49:02.237854  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv3_1/dw' with space 3.29M 64/64. 0 1 3     (avail 1.28G, req 3.29M)        t: 0 2.74 8.84
-I0510 14:49:02.313946  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv3_1/sep' with space 3.29M 64/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.29 0.87
-I0510 14:49:02.403553  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv3_2/dw' with space 3.29M 64/64. 0 0 0     (avail 1.28G, req 3.29M)        t: 0 1.87 2.19
-I0510 14:49:02.433367  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv3_2/sep' with space 3.29M 64/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.13 0.22
-I0510 14:49:02.500931  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv4_1/dw' with space 3.29M 128/128. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.43 4.07
-I0510 14:49:02.541015  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv4_1/sep' with space 3.29M 128/1 1 1 3     (avail 1.28G, req 3.29M)        t: 0 0.17 0.24
-I0510 14:49:02.578392  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv4_2/dw' with space 3.29M 128/128. 0 1 3   (avail 1.28G, req 3.29M)        t: 0 1.86 1.51
-I0510 14:49:02.594458  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv4_2/sep' with space 3.29M 128/1 1 1 3     (avail 1.28G, req 3.29M)        t: 0 0.1 0.13
-I0510 14:49:02.656378  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_1/dw' with space 3.29M 256/256. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.8 2.88
-I0510 14:49:02.687712  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_1/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.15 0.22
-I0510 14:49:02.751070  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_2/dw' with space 3.29M 256/256. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.9 2.91
-I0510 14:49:02.783671  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_2/sep' with space 3.29M 256/1 1 1 3     (avail 1.28G, req 3.29M)        t: 0 0.22 0.29
-I0510 14:49:02.885000  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_3/dw' with space 3.29M 256/256. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.84 2.91
-I0510 14:49:02.918089  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_3/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.21 0.21
-I0510 14:49:03.025629  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_4/dw' with space 3.29M 256/256. 0 1 0   (avail 1.28G, req 3.29M)        t: 0 1.82 2.9
-I0510 14:49:03.055307  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_4/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.18 0.24
-I0510 14:49:03.127607  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_5/dw' with space 3.29M 256/256. 0 1 3   (avail 1.28G, req 3.29M)        t: 0 2.09 3.49
-I0510 14:49:03.155717  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_5/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.15 0.21
-I0510 14:49:03.205742  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_6/dw' with space 3.29M 256/256. 0 0 3   (avail 1.28G, req 3.29M)        t: 0 4.67 2.27
-I0510 14:49:03.221109  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv5_6/sep' with space 3.29M 256/1 1 1 1     (avail 1.28G, req 3.29M)        t: 0 0.11 0.11
-I0510 14:49:03.308890  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv6/dw' with space 3.29M 512/512. 0 1 0     (avail 1.28G, req 3.29M)        t: 0 3.54 4.82
-I0510 14:49:03.339993  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'conv6/sep' with space 3.29M 512/1 1 1 1       (avail 1.28G, req 3.29M)        t: 0 0.17 0.18
-I0510 14:49:03.385284  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output1/1x1' with space 3.29M 256/1 1 1 1         (avail 1.28G, req 3.29M)        t: 0 0.29 0.31
-I0510 14:49:03.546432  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output1' with space 3.29M 512/512. 0 1 0  (avail 1.28G, req 3.29M)        t: 0 3.56 5.95
-I0510 14:49:03.576686  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output2/1x1' with space 3.29M 512/1 1 1 1         (avail 1.28G, req 3.29M)        t: 0 0.17 0.17
-I0510 14:49:03.656278  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output2' with space 3.29M 512/512. 0 1 3  (avail 1.28G, req 3.29M)        t: 0 3.55 4.45
-I0510 14:49:03.679927  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output3/1x1' with space 3.29M 512/1 1 1 1         (avail 1.28G, req 3.29M)        t: 0 0.09 0.11
-I0510 14:49:03.779830  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output3' with space 3.29M 512/512. 0 1 3  (avail 1.28G, req 3.29M)        t: 0 3.66 4.51
-I0510 14:49:03.805711  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output4/1x1' with space 3.29M 512/1 1 0 1         (avail 1.28G, req 3.29M)        t: 0 0.07 0.06
-I0510 14:49:03.892918  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output4' with space 3.29M 512/512. 0 1 0  (avail 1.28G, req 3.29M)        t: 0 3.58 4.73
-I0510 14:49:03.916041  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output5/1x1' with space 3.29M 512/1 1 0 1         (avail 1.28G, req 3.29M)        t: 0 0.07 0.06
-I0510 14:49:04.017879  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output5' with space 3.29M 512/512. 0 1 0  (avail 1.28G, req 3.29M)        t: 0 3.56 4.66
-I0510 14:49:04.029551  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output1/relu_mbox_loc' with space 3.29M 512/1 1 1 3       (avail 1.28G, req 3.29M)        t: 0 0.08 0.14
-I0510 14:49:04.056619  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output1/relu_mbox_conf' with space 3.29M 512/1 1 1 0      (avail 1.28G, req 3.29M)        t: 0 0.14 0.25
-I0510 14:49:04.066035  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output2/relu_mbox_loc' with space 3.29M 512/1 1 1 0       (avail 1.28G, req 3.29M)        t: 0 0.04 0.05
-I0510 14:49:04.076759  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output2/relu_mbox_conf' with space 3.29M 512/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.07 0.08
-I0510 14:49:04.083274  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output3/relu_mbox_loc' with space 3.29M 512/1 1 1 0       (avail 1.28G, req 3.29M)        t: 0 0.03 0.03
-I0510 14:49:04.094904  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output3/relu_mbox_conf' with space 3.29M 512/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.04 0.05
-I0510 14:49:04.101155  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output4/relu_mbox_loc' with space 3.29M 512/1 1 0 0       (avail 1.28G, req 3.29M)        t: 0 0.03 0.02
-I0510 14:49:04.115995  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output4/relu_mbox_conf' with space 3.29M 512/1 1 0 3      (avail 1.28G, req 3.29M)        t: 0 0.04 0.04
-I0510 14:49:04.123507  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output5/relu_mbox_loc' with space 3.29M 512/1 0 0 0       (avail 1.28G, req 3.29M)        t: 0 0.04 0.03
-I0510 14:49:04.138696  5307 cudnn_conv_layer.cpp:848] [0] Conv Algos (F,BD,BF): 'ctx_output5/relu_mbox_conf' with space 3.29M 512/1 1 1 3      (avail 1.28G, req 3.29M)        t: 0 0.05 0.06
-I0510 14:49:04.617333  5307 solver.cpp:358] Iteration 1 (2.88736 s), loss = 27.6163
-I0510 14:49:04.617358  5307 solver.cpp:376]     Train net output #0: mbox_loss = 25.7089 (* 1 = 25.7089 loss)
-I0510 14:49:05.138526  5307 solver.cpp:358] Iteration 2 (0.521175 s), loss = 26.3567
-I0510 14:49:05.138555  5307 solver.cpp:376]     Train net output #0: mbox_loss = 24.5248 (* 1 = 24.5248 loss)
-I0510 14:49:53.104404  5307 solver.cpp:352] Iteration 100 (2.04317 iter/s, 47.9647s/98 iter), loss = 7.17953
-I0510 14:49:53.104457  5307 solver.cpp:376]     Train net output #0: mbox_loss = 7.1951 (* 1 = 7.1951 loss)
-I0510 14:49:53.104465  5307 sgd_solver.cpp:172] Iteration 100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:50:44.360132  5307 solver.cpp:352] Iteration 200 (1.95105 iter/s, 51.2546s/100 iter), loss = 6.72388
-I0510 14:50:44.360198  5307 solver.cpp:376]     Train net output #0: mbox_loss = 6.90003 (* 1 = 6.90003 loss)
-I0510 14:50:44.360209  5307 sgd_solver.cpp:172] Iteration 200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:51:45.371630  5307 solver.cpp:352] Iteration 300 (1.63907 iter/s, 61.0102s/100 iter), loss = 6.42418
-I0510 14:51:45.371706  5307 solver.cpp:376]     Train net output #0: mbox_loss = 6.27518 (* 1 = 6.27518 loss)
-I0510 14:51:45.371714  5307 sgd_solver.cpp:172] Iteration 300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:52:45.343096  5307 solver.cpp:352] Iteration 400 (1.66749 iter/s, 59.9703s/100 iter), loss = 6.34919
-I0510 14:52:45.343987  5307 solver.cpp:376]     Train net output #0: mbox_loss = 7.68054 (* 1 = 7.68054 loss)
-I0510 14:52:45.344005  5307 sgd_solver.cpp:172] Iteration 400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:53:45.887753  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 14:53:46.284636  5307 solver.cpp:352] Iteration 500 (1.64095 iter/s, 60.9404s/100 iter), 1/231.9ep, loss = 6.23284
-I0510 14:53:46.284762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 6.66315 (* 1 = 6.66315 loss)
-I0510 14:53:46.284775  5307 sgd_solver.cpp:172] Iteration 500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:54:46.641153  5307 solver.cpp:352] Iteration 600 (1.65685 iter/s, 60.3554s/100 iter), 1.2/232ep, loss = 6.05849
-I0510 14:54:46.641240  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.92231 (* 1 = 5.92231 loss)
-I0510 14:54:46.641304  5307 sgd_solver.cpp:172] Iteration 600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:55:47.433953  5307 solver.cpp:352] Iteration 700 (1.64496 iter/s, 60.7917s/100 iter), 1.4/232ep, loss = 6.17512
-I0510 14:55:47.434027  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.76096 (* 1 = 5.76096 loss)
-I0510 14:55:47.434036  5307 sgd_solver.cpp:172] Iteration 700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:56:47.787348  5307 solver.cpp:352] Iteration 800 (1.65694 iter/s, 60.3523s/100 iter), 1.5/232ep, loss = 5.85499
-I0510 14:56:47.787832  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.32266 (* 1 = 5.32266 loss)
-I0510 14:56:47.787853  5307 sgd_solver.cpp:172] Iteration 800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:57:48.278928  5307 solver.cpp:352] Iteration 900 (1.65315 iter/s, 60.4905s/100 iter), 1.7/232ep, loss = 5.92378
-I0510 14:57:48.278992  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.94175 (* 1 = 4.94175 loss)
-I0510 14:57:48.279001  5307 sgd_solver.cpp:172] Iteration 900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:58:48.328603  5307 solver.cpp:352] Iteration 1000 (1.66532 iter/s, 60.0486s/100 iter), 1.9/232ep, loss = 5.526
-I0510 14:58:48.328774  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.45025 (* 1 = 5.45025 loss)
-I0510 14:58:48.328784  5307 sgd_solver.cpp:172] Iteration 1000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 14:58:58.570034  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 14:59:48.448968  5307 solver.cpp:352] Iteration 1100 (1.66336 iter/s, 60.1193s/100 iter), 2.1/232ep, loss = 5.69474
-I0510 14:59:48.449040  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.50119 (* 1 = 5.50119 loss)
-I0510 14:59:48.449049  5307 sgd_solver.cpp:172] Iteration 1100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:00:48.629653  5307 solver.cpp:352] Iteration 1200 (1.66169 iter/s, 60.1796s/100 iter), 2.3/232ep, loss = 5.57004
-I0510 15:00:48.629717  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.65429 (* 1 = 5.65429 loss)
-I0510 15:00:48.629725  5307 sgd_solver.cpp:172] Iteration 1200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:01:49.735715  5307 solver.cpp:352] Iteration 1300 (1.63653 iter/s, 61.1049s/100 iter), 2.5/232ep, loss = 5.30555
-I0510 15:01:49.735811  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.14266 (* 1 = 5.14266 loss)
-I0510 15:01:49.735837  5307 sgd_solver.cpp:172] Iteration 1300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:02:49.690517  5307 solver.cpp:352] Iteration 1400 (1.66795 iter/s, 59.9537s/100 iter), 2.7/232ep, loss = 5.25238
-I0510 15:02:49.690871  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.66859 (* 1 = 4.66859 loss)
-I0510 15:02:49.690878  5307 sgd_solver.cpp:172] Iteration 1400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:03:50.002152  5307 solver.cpp:352] Iteration 1500 (1.65809 iter/s, 60.3105s/100 iter), 2.9/232ep, loss = 5.29437
-I0510 15:03:50.002264  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.88893 (* 1 = 4.88893 loss)
-I0510 15:03:50.002279  5307 sgd_solver.cpp:172] Iteration 1500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:04:09.962220  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:04:51.827756  5307 solver.cpp:352] Iteration 1600 (1.61748 iter/s, 61.8245s/100 iter), 3.1/232ep, loss = 5.31895
-I0510 15:04:51.827807  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.96819 (* 1 = 4.96819 loss)
-I0510 15:04:51.827816  5307 sgd_solver.cpp:172] Iteration 1600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:05:53.059509  5307 solver.cpp:352] Iteration 1700 (1.63317 iter/s, 61.2306s/100 iter), 3.3/232ep, loss = 5.27998
-I0510 15:05:53.059577  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.47371 (* 1 = 4.47371 loss)
-I0510 15:05:53.059587  5307 sgd_solver.cpp:172] Iteration 1700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:06:53.011014  5307 solver.cpp:352] Iteration 1800 (1.66805 iter/s, 59.9504s/100 iter), 3.5/232ep, loss = 5.39397
-I0510 15:06:53.011147  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.32477 (* 1 = 5.32477 loss)
-I0510 15:06:53.011168  5307 sgd_solver.cpp:172] Iteration 1800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:07:52.740694  5307 solver.cpp:352] Iteration 1900 (1.67424 iter/s, 59.7286s/100 iter), 3.7/232ep, loss = 5.28387
-I0510 15:07:52.741019  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.91122 (* 1 = 4.91122 loss)
-I0510 15:07:52.741029  5307 sgd_solver.cpp:172] Iteration 1900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:08:52.557755  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_2000.caffemodel
-I0510 15:08:52.587344  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_2000.solverstate
-I0510 15:08:52.593171  5307 solver.cpp:635] Iteration 2000, Testing net (#0)
-I0510 15:09:36.971422  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:09:37.205752  5307 solver.cpp:747] class AP 1: 0.241176
-I0510 15:09:37.205962  5307 solver.cpp:747] class AP 2: 0.276057
-I0510 15:09:37.207545  5307 solver.cpp:747] class AP 3: 0.14808
-I0510 15:09:37.208468  5307 solver.cpp:747] class AP 4: 0.104791
-I0510 15:09:37.210508  5307 solver.cpp:747] class AP 5: 0.00422833
-I0510 15:09:37.210934  5307 solver.cpp:747] class AP 6: 0.308869
-I0510 15:09:37.216711  5307 solver.cpp:747] class AP 7: 0.388322
-I0510 15:09:37.217422  5307 solver.cpp:747] class AP 8: 0.392466
-I0510 15:09:37.275566  5307 solver.cpp:747] class AP 9: 0.135234
-I0510 15:09:37.276011  5307 solver.cpp:747] class AP 10: 0.146175
-I0510 15:09:37.276978  5307 solver.cpp:747] class AP 11: 0.059112
-I0510 15:09:37.277819  5307 solver.cpp:747] class AP 12: 0.288268
-I0510 15:09:37.278260  5307 solver.cpp:747] class AP 13: 0.337969
-I0510 15:09:37.278450  5307 solver.cpp:747] class AP 14: 0.24926
-I0510 15:09:37.347717  5307 solver.cpp:747] class AP 15: 0.433317
-I0510 15:09:37.347993  5307 solver.cpp:747] class AP 16: 0.0127273
-I0510 15:09:37.348687  5307 solver.cpp:747] class AP 17: 0.19425
-I0510 15:09:37.349203  5307 solver.cpp:747] class AP 18: 0.166066
-I0510 15:09:37.349592  5307 solver.cpp:747] class AP 19: 0.265589
-I0510 15:09:37.351342  5307 solver.cpp:747] class AP 20: 0.112928
-I0510 15:09:37.351349  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.213244
-I0510 15:09:37.351563  5307 solver.cpp:283] Tests completed in 104.609s
-I0510 15:09:37.907531  5307 solver.cpp:352] Iteration 2000 (0.955941 iter/s, 104.609s/100 iter), 3.9/232ep, loss = 5.1678
-I0510 15:09:37.907558  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.39318 (* 1 = 5.39318 loss)
-I0510 15:09:37.907567  5307 sgd_solver.cpp:172] Iteration 2000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:10:08.820240  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:10:37.929075  5307 solver.cpp:352] Iteration 2100 (1.6661 iter/s, 60.0204s/100 iter), 4.1/232ep, loss = 5.23718
-I0510 15:10:37.929100  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.6325 (* 1 = 4.6325 loss)
-I0510 15:10:37.929107  5307 sgd_solver.cpp:172] Iteration 2100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:11:38.703663  5307 solver.cpp:352] Iteration 2200 (1.64545 iter/s, 60.7735s/100 iter), 4.3/232ep, loss = 5.204
-I0510 15:11:38.703722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.60013 (* 1 = 5.60013 loss)
-I0510 15:11:38.703730  5307 sgd_solver.cpp:172] Iteration 2200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:12:38.392817  5307 solver.cpp:352] Iteration 2300 (1.67538 iter/s, 59.6881s/100 iter), 4.4/232ep, loss = 5.23689
-I0510 15:12:38.392879  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.4605 (* 1 = 5.4605 loss)
-I0510 15:12:38.392889  5307 sgd_solver.cpp:172] Iteration 2300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:13:39.239018  5307 solver.cpp:352] Iteration 2400 (1.64352 iter/s, 60.8451s/100 iter), 4.6/232ep, loss = 4.8862
-I0510 15:13:39.239135  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.68924 (* 1 = 4.68924 loss)
-I0510 15:13:39.239411  5307 sgd_solver.cpp:172] Iteration 2400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:14:40.495874  5307 solver.cpp:352] Iteration 2500 (1.6325 iter/s, 61.2558s/100 iter), 4.8/232ep, loss = 4.9742
-I0510 15:14:40.495930  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.79053 (* 1 = 5.79053 loss)
-I0510 15:14:40.495941  5307 sgd_solver.cpp:172] Iteration 2500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:15:22.295766  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:15:41.688493  5307 solver.cpp:352] Iteration 2600 (1.63421 iter/s, 61.1915s/100 iter), 5/232ep, loss = 5.10483
-I0510 15:15:41.688520  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.85971 (* 1 = 4.85971 loss)
-I0510 15:15:41.688539  5307 sgd_solver.cpp:172] Iteration 2600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:16:42.982174  5307 solver.cpp:352] Iteration 2700 (1.63152 iter/s, 61.2926s/100 iter), 5.2/232ep, loss = 5.12771
-I0510 15:16:42.982233  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.38579 (* 1 = 4.38579 loss)
-I0510 15:16:42.982241  5307 sgd_solver.cpp:172] Iteration 2700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:17:43.821645  5307 solver.cpp:352] Iteration 2800 (1.6437 iter/s, 60.8384s/100 iter), 5.4/232ep, loss = 4.86479
-I0510 15:17:43.821764  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.85436 (* 1 = 4.85436 loss)
-I0510 15:17:43.821818  5307 sgd_solver.cpp:172] Iteration 2800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:18:44.342092  5307 solver.cpp:352] Iteration 2900 (1.65236 iter/s, 60.5194s/100 iter), 5.6/232ep, loss = 4.99139
-I0510 15:18:44.342231  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.15122 (* 1 = 5.15122 loss)
-I0510 15:18:44.342245  5307 sgd_solver.cpp:172] Iteration 2900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:19:46.351919  5307 solver.cpp:352] Iteration 3000 (1.61268 iter/s, 62.0087s/100 iter), 5.8/232ep, loss = 4.95241
-I0510 15:19:46.352030  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.45109 (* 1 = 4.45109 loss)
-I0510 15:19:46.352042  5307 sgd_solver.cpp:172] Iteration 3000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:20:38.992974  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:20:48.269686  5307 solver.cpp:352] Iteration 3100 (1.61507 iter/s, 61.9167s/100 iter), 6/232ep, loss = 5.13158
-I0510 15:20:48.269755  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.02616 (* 1 = 5.02616 loss)
-I0510 15:20:48.269775  5307 sgd_solver.cpp:172] Iteration 3100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:21:50.193011  5307 solver.cpp:352] Iteration 3200 (1.61493 iter/s, 61.9222s/100 iter), 6.2/232ep, loss = 4.95878
-I0510 15:21:50.193161  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.99084 (* 1 = 4.99084 loss)
-I0510 15:21:50.193187  5307 sgd_solver.cpp:172] Iteration 3200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:22:52.971943  5307 solver.cpp:352] Iteration 3300 (1.59292 iter/s, 62.7777s/100 iter), 6.4/232ep, loss = 4.71981
-I0510 15:22:52.972044  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.98499 (* 1 = 4.98499 loss)
-I0510 15:22:52.972054  5307 sgd_solver.cpp:172] Iteration 3300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:23:54.334111  5307 solver.cpp:352] Iteration 3400 (1.6297 iter/s, 61.3611s/100 iter), 6.6/232ep, loss = 4.78574
-I0510 15:23:54.334228  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49641 (* 1 = 4.49641 loss)
-I0510 15:23:54.334244  5307 sgd_solver.cpp:172] Iteration 3400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:24:55.895929  5307 solver.cpp:352] Iteration 3500 (1.62441 iter/s, 61.5607s/100 iter), 6.8/232ep, loss = 4.77709
-I0510 15:24:55.897032  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.93638 (* 1 = 4.93638 loss)
-I0510 15:24:55.897043  5307 sgd_solver.cpp:172] Iteration 3500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:25:56.356941  5307 solver.cpp:352] Iteration 3600 (1.65399 iter/s, 60.4599s/100 iter), 7/232ep, loss = 4.90801
-I0510 15:25:56.358294  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.33671 (* 1 = 4.33671 loss)
-I0510 15:25:56.358317  5307 sgd_solver.cpp:172] Iteration 3600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:25:58.086321  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:26:57.752619  5307 solver.cpp:352] Iteration 3700 (1.62881 iter/s, 61.3946s/100 iter), 7.2/232ep, loss = 4.89432
-I0510 15:26:57.752725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.51655 (* 1 = 4.51655 loss)
-I0510 15:26:57.752748  5307 sgd_solver.cpp:172] Iteration 3700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:27:59.361323  5307 solver.cpp:352] Iteration 3800 (1.62318 iter/s, 61.6076s/100 iter), 7.3/232ep, loss = 4.72437
-I0510 15:27:59.364637  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02982 (* 1 = 4.02982 loss)
-I0510 15:27:59.364663  5307 sgd_solver.cpp:172] Iteration 3800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:29:00.746966  5307 solver.cpp:352] Iteration 3900 (1.62908 iter/s, 61.3845s/100 iter), 7.5/232ep, loss = 4.54618
-I0510 15:29:00.752626  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.57019 (* 1 = 4.57019 loss)
-I0510 15:29:00.752717  5307 sgd_solver.cpp:172] Iteration 3900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:30:01.201730  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_4000.caffemodel
-I0510 15:30:01.218586  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_4000.solverstate
-I0510 15:30:01.223902  5307 solver.cpp:635] Iteration 4000, Testing net (#0)
-I0510 15:30:45.120575  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:30:45.351639  5307 solver.cpp:747] class AP 1: 0.206601
-I0510 15:30:45.352443  5307 solver.cpp:747] class AP 2: 0.367045
-I0510 15:30:45.355480  5307 solver.cpp:747] class AP 3: 0.230397
-I0510 15:30:45.356767  5307 solver.cpp:747] class AP 4: 0.135427
-I0510 15:30:45.374042  5307 solver.cpp:747] class AP 5: 0.0700225
-I0510 15:30:45.374305  5307 solver.cpp:747] class AP 6: 0.389016
-I0510 15:30:45.376086  5307 solver.cpp:747] class AP 7: 0.423877
-I0510 15:30:45.376555  5307 solver.cpp:747] class AP 8: 0.466201
-I0510 15:30:45.418108  5307 solver.cpp:747] class AP 9: 0.152882
-I0510 15:30:45.418695  5307 solver.cpp:747] class AP 10: 0.224414
-I0510 15:30:45.420948  5307 solver.cpp:747] class AP 11: 0.260761
-I0510 15:30:45.421463  5307 solver.cpp:747] class AP 12: 0.367263
-I0510 15:30:45.421973  5307 solver.cpp:747] class AP 13: 0.403105
-I0510 15:30:45.422230  5307 solver.cpp:747] class AP 14: 0.355312
-I0510 15:30:45.484895  5307 solver.cpp:747] class AP 15: 0.501333
-I0510 15:30:45.488716  5307 solver.cpp:747] class AP 16: 0.0390343
-I0510 15:30:45.490855  5307 solver.cpp:747] class AP 17: 0.256806
-I0510 15:30:45.492317  5307 solver.cpp:747] class AP 18: 0.220857
-I0510 15:30:45.492729  5307 solver.cpp:747] class AP 19: 0.323311
-I0510 15:30:45.493448  5307 solver.cpp:747] class AP 20: 0.171304
-I0510 15:30:45.493455  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.278248
-I0510 15:30:45.493628  5307 solver.cpp:283] Tests completed in 104.745s
-I0510 15:30:46.064640  5307 solver.cpp:352] Iteration 4000 (0.954702 iter/s, 104.745s/100 iter), 7.7/232ep, loss = 4.75776
-I0510 15:30:46.064726  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.69811 (* 1 = 4.69811 loss)
-I0510 15:30:46.064749  5307 sgd_solver.cpp:172] Iteration 4000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:31:46.889731  5307 solver.cpp:352] Iteration 4100 (1.64409 iter/s, 60.824s/100 iter), 7.9/232ep, loss = 4.62315
-I0510 15:31:46.889819  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65004 (* 1 = 3.65004 loss)
-I0510 15:31:46.889827  5307 sgd_solver.cpp:172] Iteration 4100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:31:58.322438  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:32:47.780087  5307 solver.cpp:352] Iteration 4200 (1.64233 iter/s, 60.8892s/100 iter), 8.1/232ep, loss = 4.93722
-I0510 15:32:47.780309  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.30114 (* 1 = 4.30114 loss)
-I0510 15:32:47.780371  5307 sgd_solver.cpp:172] Iteration 4200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:33:48.548478  5307 solver.cpp:352] Iteration 4300 (1.64562 iter/s, 60.7673s/100 iter), 8.3/232ep, loss = 4.73264
-I0510 15:33:48.548557  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.864 (* 1 = 4.864 loss)
-I0510 15:33:48.548565  5307 sgd_solver.cpp:172] Iteration 4300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:34:49.456447  5307 solver.cpp:352] Iteration 4400 (1.64185 iter/s, 60.9069s/100 iter), 8.5/232ep, loss = 4.58244
-I0510 15:34:49.456498  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41459 (* 1 = 4.41459 loss)
-I0510 15:34:49.456506  5307 sgd_solver.cpp:172] Iteration 4400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:35:49.381788  5307 solver.cpp:352] Iteration 4500 (1.66877 iter/s, 59.9243s/100 iter), 8.7/232ep, loss = 4.66685
-I0510 15:35:49.381906  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.01909 (* 1 = 4.01909 loss)
-I0510 15:35:49.381916  5307 sgd_solver.cpp:172] Iteration 4500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:36:50.129918  5307 solver.cpp:352] Iteration 4600 (1.64617 iter/s, 60.747s/100 iter), 8.9/232ep, loss = 4.64371
-I0510 15:36:50.131379  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.87533 (* 1 = 4.87533 loss)
-I0510 15:36:50.131404  5307 sgd_solver.cpp:172] Iteration 4600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:37:12.411576  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:37:49.867966  5307 solver.cpp:352] Iteration 4700 (1.674 iter/s, 59.737s/100 iter), 9.1/232ep, loss = 4.62321
-I0510 15:37:49.868119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 6.32694 (* 1 = 6.32694 loss)
-I0510 15:37:49.868136  5307 sgd_solver.cpp:172] Iteration 4700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:38:50.386214  5307 solver.cpp:352] Iteration 4800 (1.65242 iter/s, 60.5172s/100 iter), 9.3/232ep, loss = 4.515
-I0510 15:38:50.386273  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.09599 (* 1 = 4.09599 loss)
-I0510 15:38:50.386282  5307 sgd_solver.cpp:172] Iteration 4800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:39:51.384122  5307 solver.cpp:352] Iteration 4900 (1.63943 iter/s, 60.9968s/100 iter), 9.5/232ep, loss = 4.58634
-I0510 15:39:51.384201  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49087 (* 1 = 4.49087 loss)
-I0510 15:39:51.384210  5307 sgd_solver.cpp:172] Iteration 4900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:40:51.456099  5307 solver.cpp:352] Iteration 5000 (1.6647 iter/s, 60.0709s/100 iter), 9.7/232ep, loss = 4.79531
-I0510 15:40:51.461995  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.5938 (* 1 = 4.5938 loss)
-I0510 15:40:51.462021  5307 sgd_solver.cpp:172] Iteration 5000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:41:52.329574  5307 solver.cpp:352] Iteration 5100 (1.64278 iter/s, 60.8724s/100 iter), 9.9/232ep, loss = 4.69331
-I0510 15:41:52.329661  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.59687 (* 1 = 4.59687 loss)
-I0510 15:41:52.329679  5307 sgd_solver.cpp:172] Iteration 5100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:42:25.642316  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:42:52.869071  5307 solver.cpp:352] Iteration 5200 (1.65184 iter/s, 60.5384s/100 iter), 10.1/232ep, loss = 4.61058
-I0510 15:42:52.869096  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73034 (* 1 = 3.73034 loss)
-I0510 15:42:52.869102  5307 sgd_solver.cpp:172] Iteration 5200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:43:53.011672  5307 solver.cpp:352] Iteration 5300 (1.66274 iter/s, 60.1415s/100 iter), 10.2/232ep, loss = 4.53749
-I0510 15:43:53.016227  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06435 (* 1 = 4.06435 loss)
-I0510 15:43:53.016248  5307 sgd_solver.cpp:172] Iteration 5300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:44:52.968842  5307 solver.cpp:352] Iteration 5400 (1.66789 iter/s, 59.9561s/100 iter), 10.4/232ep, loss = 4.64367
-I0510 15:44:52.969082  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.59465 (* 1 = 4.59465 loss)
-I0510 15:44:52.969095  5307 sgd_solver.cpp:172] Iteration 5400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:45:53.614475  5307 solver.cpp:352] Iteration 5500 (1.64895 iter/s, 60.6446s/100 iter), 10.6/232ep, loss = 4.76142
-I0510 15:45:53.614565  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.71894 (* 1 = 4.71894 loss)
-I0510 15:45:53.614584  5307 sgd_solver.cpp:172] Iteration 5500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:46:54.232838  5307 solver.cpp:352] Iteration 5600 (1.6497 iter/s, 60.6173s/100 iter), 10.8/232ep, loss = 4.59661
-I0510 15:46:54.232895  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.42444 (* 1 = 3.42444 loss)
-I0510 15:46:54.232906  5307 sgd_solver.cpp:172] Iteration 5600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:47:37.166826  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:47:54.647212  5307 solver.cpp:352] Iteration 5700 (1.65527 iter/s, 60.4133s/100 iter), 11/232ep, loss = 4.50432
-I0510 15:47:54.647388  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91722 (* 1 = 3.91722 loss)
-I0510 15:47:54.647413  5307 sgd_solver.cpp:172] Iteration 5700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:48:54.521733  5307 solver.cpp:352] Iteration 5800 (1.67019 iter/s, 59.8734s/100 iter), 11.2/232ep, loss = 4.55135
-I0510 15:48:54.521875  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.27885 (* 1 = 5.27885 loss)
-I0510 15:48:54.521898  5307 sgd_solver.cpp:172] Iteration 5800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:49:54.036702  5307 solver.cpp:352] Iteration 5900 (1.68028 iter/s, 59.5139s/100 iter), 11.4/232ep, loss = 4.54151
-I0510 15:49:54.036756  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00221 (* 1 = 4.00221 loss)
-I0510 15:49:54.036764  5307 sgd_solver.cpp:172] Iteration 5900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:50:53.529439  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_6000.caffemodel
-I0510 15:50:53.545519  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_6000.solverstate
-I0510 15:50:53.550115  5307 solver.cpp:635] Iteration 6000, Testing net (#0)
-I0510 15:51:35.765430  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:51:36.005661  5307 solver.cpp:747] class AP 1: 0.343603
-I0510 15:51:36.005951  5307 solver.cpp:747] class AP 2: 0.339176
-I0510 15:51:36.008163  5307 solver.cpp:747] class AP 3: 0.200234
-I0510 15:51:36.009189  5307 solver.cpp:747] class AP 4: 0.132322
-I0510 15:51:36.045416  5307 solver.cpp:747] class AP 5: 0.143882
-I0510 15:51:36.045706  5307 solver.cpp:747] class AP 6: 0.421355
-I0510 15:51:36.047044  5307 solver.cpp:747] class AP 7: 0.482913
-I0510 15:51:36.047725  5307 solver.cpp:747] class AP 8: 0.503616
-I0510 15:51:36.076642  5307 solver.cpp:747] class AP 9: 0.170713
-I0510 15:51:36.076894  5307 solver.cpp:747] class AP 10: 0.266493
-I0510 15:51:36.078565  5307 solver.cpp:747] class AP 11: 0.231238
-I0510 15:51:36.080288  5307 solver.cpp:747] class AP 12: 0.375903
-I0510 15:51:36.080466  5307 solver.cpp:747] class AP 13: 0.504411
-I0510 15:51:36.080862  5307 solver.cpp:747] class AP 14: 0.371008
-I0510 15:51:36.137048  5307 solver.cpp:747] class AP 15: 0.498699
-I0510 15:51:36.140677  5307 solver.cpp:747] class AP 16: 0.0532492
-I0510 15:51:36.142189  5307 solver.cpp:747] class AP 17: 0.250349
-I0510 15:51:36.143249  5307 solver.cpp:747] class AP 18: 0.233757
-I0510 15:51:36.143421  5307 solver.cpp:747] class AP 19: 0.337436
-I0510 15:51:36.144233  5307 solver.cpp:747] class AP 20: 0.298036
-I0510 15:51:36.144239  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.30792
-I0510 15:51:36.144384  5307 solver.cpp:283] Tests completed in 102.106s
-I0510 15:51:36.718585  5307 solver.cpp:352] Iteration 6000 (0.979376 iter/s, 102.106s/100 iter), 11.6/232ep, loss = 4.49617
-I0510 15:51:36.718739  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89786 (* 1 = 3.89786 loss)
-I0510 15:51:36.718768  5307 sgd_solver.cpp:172] Iteration 6000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:52:36.928555  5307 solver.cpp:352] Iteration 6100 (1.66089 iter/s, 60.2088s/100 iter), 11.8/232ep, loss = 4.57125
-I0510 15:52:36.928704  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78149 (* 1 = 3.78149 loss)
-I0510 15:52:36.928714  5307 sgd_solver.cpp:172] Iteration 6100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:53:30.810858  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:53:37.308396  5307 solver.cpp:352] Iteration 6200 (1.65621 iter/s, 60.3787s/100 iter), 12/232ep, loss = 4.49143
-I0510 15:53:37.308425  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49279 (* 1 = 4.49279 loss)
-I0510 15:53:37.308434  5307 sgd_solver.cpp:172] Iteration 6200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:54:37.473292  5307 solver.cpp:352] Iteration 6300 (1.66213 iter/s, 60.1638s/100 iter), 12.2/232ep, loss = 4.48289
-I0510 15:54:37.473388  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.74283 (* 1 = 4.74283 loss)
-I0510 15:54:37.473410  5307 sgd_solver.cpp:172] Iteration 6300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:55:37.702651  5307 solver.cpp:352] Iteration 6400 (1.66035 iter/s, 60.2283s/100 iter), 12.4/232ep, loss = 4.56006
-I0510 15:55:37.702899  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.82329 (* 1 = 4.82329 loss)
-I0510 15:55:37.702926  5307 sgd_solver.cpp:172] Iteration 6400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:56:37.662981  5307 solver.cpp:352] Iteration 6500 (1.6678 iter/s, 59.9593s/100 iter), 12.6/232ep, loss = 4.48101
-I0510 15:56:37.663030  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.19505 (* 1 = 4.19505 loss)
-I0510 15:56:37.663039  5307 sgd_solver.cpp:172] Iteration 6500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:57:36.854810  5307 solver.cpp:352] Iteration 6600 (1.68945 iter/s, 59.1908s/100 iter), 12.8/232ep, loss = 4.38066
-I0510 15:57:36.855403  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.18159 (* 1 = 4.18159 loss)
-I0510 15:57:36.855425  5307 sgd_solver.cpp:172] Iteration 6600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:58:44.572839  5307 solver.cpp:352] Iteration 6700 (1.47674 iter/s, 67.7168s/100 iter), 13/232ep, loss = 4.418
-I0510 15:58:44.572919  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.71588 (* 1 = 4.71588 loss)
-I0510 15:58:44.572929  5307 sgd_solver.cpp:172] Iteration 6700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 15:58:48.144181  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 15:59:47.231030  5307 solver.cpp:352] Iteration 6800 (1.59599 iter/s, 62.6571s/100 iter), 13.1/232ep, loss = 4.3694
-I0510 15:59:47.231144  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.31186 (* 1 = 4.31186 loss)
-I0510 15:59:47.231168  5307 sgd_solver.cpp:172] Iteration 6800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:00:47.528723  5307 solver.cpp:352] Iteration 6900 (1.65847 iter/s, 60.2966s/100 iter), 13.3/232ep, loss = 4.40375
-I0510 16:00:47.529601  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.53692 (* 1 = 5.53692 loss)
-I0510 16:00:47.529611  5307 sgd_solver.cpp:172] Iteration 6900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:01:47.887481  5307 solver.cpp:352] Iteration 7000 (1.65679 iter/s, 60.3577s/100 iter), 13.5/232ep, loss = 4.29458
-I0510 16:01:47.887647  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.5077 (* 1 = 4.5077 loss)
-I0510 16:01:47.887661  5307 sgd_solver.cpp:172] Iteration 7000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:02:48.194983  5307 solver.cpp:352] Iteration 7100 (1.6582 iter/s, 60.3065s/100 iter), 13.7/232ep, loss = 4.34698
-I0510 16:02:48.195036  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.99513 (* 1 = 3.99513 loss)
-I0510 16:02:48.195044  5307 sgd_solver.cpp:172] Iteration 7100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:03:47.820672  5307 solver.cpp:352] Iteration 7200 (1.67716 iter/s, 59.6247s/100 iter), 13.9/232ep, loss = 4.21892
-I0510 16:03:47.820744  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91532 (* 1 = 3.91532 loss)
-I0510 16:03:47.820753  5307 sgd_solver.cpp:172] Iteration 7200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:04:01.660982  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:04:48.659145  5307 solver.cpp:352] Iteration 7300 (1.64373 iter/s, 60.8374s/100 iter), 14.1/232ep, loss = 4.43065
-I0510 16:04:48.659251  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.29698 (* 1 = 4.29698 loss)
-I0510 16:04:48.659278  5307 sgd_solver.cpp:172] Iteration 7300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:05:48.998246  5307 solver.cpp:352] Iteration 7400 (1.65733 iter/s, 60.338s/100 iter), 14.3/232ep, loss = 4.41088
-I0510 16:05:48.998353  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.48164 (* 1 = 3.48164 loss)
-I0510 16:05:48.998364  5307 sgd_solver.cpp:172] Iteration 7400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:06:49.963078  5307 solver.cpp:352] Iteration 7500 (1.64032 iter/s, 60.9638s/100 iter), 14.5/232ep, loss = 4.42881
-I0510 16:06:49.963234  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.26356 (* 1 = 4.26356 loss)
-I0510 16:06:49.963246  5307 sgd_solver.cpp:172] Iteration 7500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:07:51.170918  5307 solver.cpp:352] Iteration 7600 (1.63381 iter/s, 61.2068s/100 iter), 14.7/232ep, loss = 4.38766
-I0510 16:07:51.171381  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.86193 (* 1 = 4.86193 loss)
-I0510 16:07:51.171404  5307 sgd_solver.cpp:172] Iteration 7600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:08:52.659510  5307 solver.cpp:352] Iteration 7700 (1.62635 iter/s, 61.4875s/100 iter), 14.9/232ep, loss = 4.28137
-I0510 16:08:52.659694  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95457 (* 1 = 3.95457 loss)
-I0510 16:08:52.659721  5307 sgd_solver.cpp:172] Iteration 7700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:09:17.163449  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:09:53.273126  5307 solver.cpp:352] Iteration 7800 (1.64982 iter/s, 60.6125s/100 iter), 15.1/232ep, loss = 4.28748
-I0510 16:09:53.273193  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.74378 (* 1 = 4.74378 loss)
-I0510 16:09:53.273202  5307 sgd_solver.cpp:172] Iteration 7800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:10:53.718170  5307 solver.cpp:352] Iteration 7900 (1.65443 iter/s, 60.444s/100 iter), 15.3/232ep, loss = 4.48724
-I0510 16:10:53.718232  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.72057 (* 1 = 4.72057 loss)
-I0510 16:10:53.718240  5307 sgd_solver.cpp:172] Iteration 7900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:11:53.707036  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_8000.caffemodel
-I0510 16:11:53.729109  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_8000.solverstate
-I0510 16:11:53.735050  5307 solver.cpp:635] Iteration 8000, Testing net (#0)
-I0510 16:12:35.622887  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:12:35.819828  5307 solver.cpp:747] class AP 1: 0.187161
-I0510 16:12:35.819895  5307 solver.cpp:747] class AP 2: 0.132867
-I0510 16:12:35.820551  5307 solver.cpp:747] class AP 3: 0.093213
-I0510 16:12:35.822451  5307 solver.cpp:747] class AP 4: 0.134172
-I0510 16:12:35.833393  5307 solver.cpp:747] class AP 5: 0.116078
-I0510 16:12:35.833920  5307 solver.cpp:747] class AP 6: 0.18732
-I0510 16:12:35.843909  5307 solver.cpp:747] class AP 7: 0.326991
-I0510 16:12:35.844079  5307 solver.cpp:747] class AP 8: 0.380603
-I0510 16:12:35.871490  5307 solver.cpp:747] class AP 9: 0.0880095
-I0510 16:12:35.871589  5307 solver.cpp:747] class AP 10: 0.23624
-I0510 16:12:35.871991  5307 solver.cpp:747] class AP 11: 0.147733
-I0510 16:12:35.872153  5307 solver.cpp:747] class AP 12: 0.253221
-I0510 16:12:35.872205  5307 solver.cpp:747] class AP 13: 0.174242
-I0510 16:12:35.872351  5307 solver.cpp:747] class AP 14: 0.146544
-I0510 16:12:36.012958  5307 solver.cpp:747] class AP 15: 0.278914
-I0510 16:12:36.013765  5307 solver.cpp:747] class AP 16: 0.0510046
-I0510 16:12:36.014111  5307 solver.cpp:747] class AP 17: 0.115495
-I0510 16:12:36.015322  5307 solver.cpp:747] class AP 18: 0.170786
-I0510 16:12:36.015656  5307 solver.cpp:747] class AP 19: 0.274256
-I0510 16:12:36.022532  5307 solver.cpp:747] class AP 20: 0.157187
-I0510 16:12:36.022603  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.182602
-I0510 16:12:36.023149  5307 solver.cpp:283] Tests completed in 102.303s
-I0510 16:12:36.587702  5307 solver.cpp:352] Iteration 8000 (0.977487 iter/s, 102.303s/100 iter), 15.5/232ep, loss = 4.39346
-I0510 16:12:36.587725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.59318 (* 1 = 5.59318 loss)
-I0510 16:12:36.587734  5307 sgd_solver.cpp:172] Iteration 8000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:13:36.125911  5307 solver.cpp:352] Iteration 8100 (1.67963 iter/s, 59.5371s/100 iter), 15.7/232ep, loss = 4.40548
-I0510 16:13:36.126049  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.30731 (* 1 = 4.30731 loss)
-I0510 16:13:36.126067  5307 sgd_solver.cpp:172] Iteration 8100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:14:37.028736  5307 solver.cpp:352] Iteration 8200 (1.64199 iter/s, 60.9017s/100 iter), 15.9/232ep, loss = 4.36387
-I0510 16:14:37.028792  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.04558 (* 1 = 4.04558 loss)
-I0510 16:14:37.028800  5307 sgd_solver.cpp:172] Iteration 8200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:15:11.105940  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:15:37.020285  5307 solver.cpp:352] Iteration 8300 (1.66693 iter/s, 59.9904s/100 iter), 16/232ep, loss = 4.31154
-I0510 16:15:37.020372  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.1889 (* 1 = 5.1889 loss)
-I0510 16:15:37.020390  5307 sgd_solver.cpp:172] Iteration 8300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:16:37.154593  5307 solver.cpp:352] Iteration 8400 (1.66297 iter/s, 60.1332s/100 iter), 16.2/232ep, loss = 4.4104
-I0510 16:16:37.154779  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.68552 (* 1 = 4.68552 loss)
-I0510 16:16:37.154812  5307 sgd_solver.cpp:172] Iteration 8400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:17:38.530937  5307 solver.cpp:352] Iteration 8500 (1.62932 iter/s, 61.3753s/100 iter), 16.4/232ep, loss = 4.27246
-I0510 16:17:38.531033  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4225 (* 1 = 3.4225 loss)
-I0510 16:17:38.531054  5307 sgd_solver.cpp:172] Iteration 8500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:18:39.009922  5307 solver.cpp:352] Iteration 8600 (1.6535 iter/s, 60.4779s/100 iter), 16.6/232ep, loss = 4.39125
-I0510 16:18:39.010030  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.33212 (* 1 = 4.33212 loss)
-I0510 16:18:39.010053  5307 sgd_solver.cpp:172] Iteration 8600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:19:40.334738  5307 solver.cpp:352] Iteration 8700 (1.63069 iter/s, 61.3237s/100 iter), 16.8/232ep, loss = 4.33689
-I0510 16:19:40.335502  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.9013 (* 1 = 4.9013 loss)
-I0510 16:19:40.335515  5307 sgd_solver.cpp:172] Iteration 8700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:20:26.046443  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:20:41.286645  5307 solver.cpp:352] Iteration 8800 (1.64067 iter/s, 60.9509s/100 iter), 17/232ep, loss = 4.26008
-I0510 16:20:41.286676  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.38479 (* 1 = 5.38479 loss)
-I0510 16:20:41.286685  5307 sgd_solver.cpp:172] Iteration 8800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:21:41.783578  5307 solver.cpp:352] Iteration 8900 (1.65301 iter/s, 60.4959s/100 iter), 17.2/232ep, loss = 4.10042
-I0510 16:21:41.783674  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54616 (* 1 = 3.54616 loss)
-I0510 16:21:41.783684  5307 sgd_solver.cpp:172] Iteration 8900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:22:43.384639  5307 solver.cpp:352] Iteration 9000 (1.62338 iter/s, 61.6s/100 iter), 17.4/232ep, loss = 4.29836
-I0510 16:22:43.384814  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.46384 (* 1 = 4.46384 loss)
-I0510 16:22:43.384824  5307 sgd_solver.cpp:172] Iteration 9000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:23:44.433280  5307 solver.cpp:352] Iteration 9100 (1.63807 iter/s, 61.0476s/100 iter), 17.6/232ep, loss = 4.13168
-I0510 16:23:44.433372  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.40502 (* 1 = 4.40502 loss)
-I0510 16:23:44.433382  5307 sgd_solver.cpp:172] Iteration 9100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:24:46.060052  5307 solver.cpp:352] Iteration 9200 (1.6227 iter/s, 61.6257s/100 iter), 17.8/232ep, loss = 4.21399
-I0510 16:24:46.060153  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.21245 (* 1 = 4.21245 loss)
-I0510 16:24:46.060163  5307 sgd_solver.cpp:172] Iteration 9200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:25:42.008615  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:25:47.175756  5307 solver.cpp:352] Iteration 9300 (1.63627 iter/s, 61.1146s/100 iter), 18/232ep, loss = 4.42703
-I0510 16:25:47.175787  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93399 (* 1 = 3.93399 loss)
-I0510 16:25:47.175796  5307 sgd_solver.cpp:172] Iteration 9300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:26:48.714920  5307 solver.cpp:352] Iteration 9400 (1.62501 iter/s, 61.5381s/100 iter), 18.2/232ep, loss = 4.3202
-I0510 16:26:48.715634  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.67566 (* 1 = 4.67566 loss)
-I0510 16:26:48.715649  5307 sgd_solver.cpp:172] Iteration 9400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:27:49.669996  5307 solver.cpp:352] Iteration 9500 (1.64058 iter/s, 60.954s/100 iter), 18.4/232ep, loss = 4.3158
-I0510 16:27:49.670137  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.50218 (* 1 = 4.50218 loss)
-I0510 16:27:49.670156  5307 sgd_solver.cpp:172] Iteration 9500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:28:50.534543  5307 solver.cpp:352] Iteration 9600 (1.64302 iter/s, 60.8635s/100 iter), 18.6/232ep, loss = 4.31481
-I0510 16:28:50.534724  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.78233 (* 1 = 4.78233 loss)
-I0510 16:28:50.534744  5307 sgd_solver.cpp:172] Iteration 9600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:29:52.043104  5307 solver.cpp:352] Iteration 9700 (1.62582 iter/s, 61.5075s/100 iter), 18.8/232ep, loss = 4.26232
-I0510 16:29:52.044564  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.77904 (* 1 = 3.77904 loss)
-I0510 16:29:52.044596  5307 sgd_solver.cpp:172] Iteration 9700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:30:52.859931  5307 solver.cpp:352] Iteration 9800 (1.64431 iter/s, 60.8158s/100 iter), 18.9/232ep, loss = 4.17125
-I0510 16:30:52.860009  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84245 (* 1 = 3.84245 loss)
-I0510 16:30:52.860018  5307 sgd_solver.cpp:172] Iteration 9800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:30:58.494596  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:31:53.523766  5307 solver.cpp:352] Iteration 9900 (1.64846 iter/s, 60.6627s/100 iter), 19.1/232ep, loss = 4.19495
-I0510 16:31:53.523844  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.45795 (* 1 = 4.45795 loss)
-I0510 16:31:53.523854  5307 sgd_solver.cpp:172] Iteration 9900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:32:53.689491  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_10000.caffemodel
-I0510 16:32:53.705381  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_10000.solverstate
-I0510 16:32:53.710855  5307 solver.cpp:635] Iteration 10000, Testing net (#0)
-I0510 16:33:35.652021  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:33:35.887356  5307 solver.cpp:747] class AP 1: 0.378373
-I0510 16:33:35.887681  5307 solver.cpp:747] class AP 2: 0.446617
-I0510 16:33:35.890889  5307 solver.cpp:747] class AP 3: 0.323297
-I0510 16:33:35.893777  5307 solver.cpp:747] class AP 4: 0.22195
-I0510 16:33:35.909973  5307 solver.cpp:747] class AP 5: 0.127367
-I0510 16:33:35.910291  5307 solver.cpp:747] class AP 6: 0.42865
-I0510 16:33:35.913208  5307 solver.cpp:747] class AP 7: 0.439762
-I0510 16:33:35.913678  5307 solver.cpp:747] class AP 8: 0.564868
-I0510 16:33:35.935222  5307 solver.cpp:747] class AP 9: 0.217799
-I0510 16:33:35.935350  5307 solver.cpp:747] class AP 10: 0.278676
-I0510 16:33:35.936563  5307 solver.cpp:747] class AP 11: 0.347657
-I0510 16:33:35.937006  5307 solver.cpp:747] class AP 12: 0.462001
-I0510 16:33:35.937166  5307 solver.cpp:747] class AP 13: 0.457945
-I0510 16:33:35.937306  5307 solver.cpp:747] class AP 14: 0.48744
-I0510 16:33:36.011561  5307 solver.cpp:747] class AP 15: 0.539054
-I0510 16:33:36.020725  5307 solver.cpp:747] class AP 16: 0.150607
-I0510 16:33:36.021001  5307 solver.cpp:747] class AP 17: 0.341589
-I0510 16:33:36.021291  5307 solver.cpp:747] class AP 18: 0.307463
-I0510 16:33:36.021807  5307 solver.cpp:747] class AP 19: 0.426576
-I0510 16:33:36.023761  5307 solver.cpp:747] class AP 20: 0.277367
-I0510 16:33:36.023767  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.361253
-I0510 16:33:36.023957  5307 solver.cpp:283] Tests completed in 102.498s
-I0510 16:33:36.602188  5307 solver.cpp:352] Iteration 10000 (0.975625 iter/s, 102.498s/100 iter), 19.3/232ep, loss = 4.38477
-I0510 16:33:36.602257  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.72253 (* 1 = 4.72253 loss)
-I0510 16:33:36.602274  5307 sgd_solver.cpp:172] Iteration 10000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:34:38.145097  5307 solver.cpp:352] Iteration 10100 (1.62491 iter/s, 61.5418s/100 iter), 19.5/232ep, loss = 4.14872
-I0510 16:34:38.145155  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.9657 (* 1 = 3.9657 loss)
-I0510 16:34:38.145354  5307 sgd_solver.cpp:172] Iteration 10100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:35:39.481259  5307 solver.cpp:352] Iteration 10200 (1.63039 iter/s, 61.335s/100 iter), 19.7/232ep, loss = 4.3917
-I0510 16:35:39.481500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11003 (* 1 = 4.11003 loss)
-I0510 16:35:39.481559  5307 sgd_solver.cpp:172] Iteration 10200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:36:40.322700  5307 solver.cpp:352] Iteration 10300 (1.64365 iter/s, 60.8404s/100 iter), 19.9/232ep, loss = 4.11278
-I0510 16:36:40.322809  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95169 (* 1 = 3.95169 loss)
-I0510 16:36:40.322818  5307 sgd_solver.cpp:172] Iteration 10300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:36:56.879952  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:37:41.590212  5307 solver.cpp:352] Iteration 10400 (1.63222 iter/s, 61.2664s/100 iter), 20.1/232ep, loss = 4.2348
-I0510 16:37:41.590725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0292 (* 1 = 4.0292 loss)
-I0510 16:37:41.590734  5307 sgd_solver.cpp:172] Iteration 10400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:38:42.635974  5307 solver.cpp:352] Iteration 10500 (1.63814 iter/s, 61.0447s/100 iter), 20.3/232ep, loss = 4.43859
-I0510 16:38:42.636080  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.53269 (* 1 = 4.53269 loss)
-I0510 16:38:42.636142  5307 sgd_solver.cpp:172] Iteration 10500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:39:43.396457  5307 solver.cpp:352] Iteration 10600 (1.64584 iter/s, 60.7594s/100 iter), 20.5/232ep, loss = 4.08796
-I0510 16:39:43.396561  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.48421 (* 1 = 4.48421 loss)
-I0510 16:39:43.396579  5307 sgd_solver.cpp:172] Iteration 10600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:40:44.580492  5307 solver.cpp:352] Iteration 10700 (1.63444 iter/s, 61.183s/100 iter), 20.7/232ep, loss = 4.25233
-I0510 16:40:44.582834  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41945 (* 1 = 3.41945 loss)
-I0510 16:40:44.582845  5307 sgd_solver.cpp:172] Iteration 10700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:41:46.095185  5307 solver.cpp:352] Iteration 10800 (1.62566 iter/s, 61.5136s/100 iter), 20.9/232ep, loss = 4.1095
-I0510 16:41:46.095281  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.14543 (* 1 = 5.14543 loss)
-I0510 16:41:46.095299  5307 sgd_solver.cpp:172] Iteration 10800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:42:12.404253  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:42:47.050778  5307 solver.cpp:352] Iteration 10900 (1.64057 iter/s, 60.9545s/100 iter), 21.1/232ep, loss = 4.19932
-I0510 16:42:47.050837  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.53899 (* 1 = 4.53899 loss)
-I0510 16:42:47.050843  5307 sgd_solver.cpp:172] Iteration 10900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:43:48.170625  5307 solver.cpp:352] Iteration 11000 (1.63616 iter/s, 61.1188s/100 iter), 21.3/232ep, loss = 4.08915
-I0510 16:43:48.170718  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.08948 (* 1 = 4.08948 loss)
-I0510 16:43:48.170742  5307 sgd_solver.cpp:172] Iteration 11000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:44:48.368515  5307 solver.cpp:352] Iteration 11100 (1.66122 iter/s, 60.1968s/100 iter), 21.5/232ep, loss = 3.97626
-I0510 16:44:48.368626  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.17662 (* 1 = 4.17662 loss)
-I0510 16:44:48.368635  5307 sgd_solver.cpp:172] Iteration 11100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:45:48.322374  5307 solver.cpp:352] Iteration 11200 (1.66798 iter/s, 59.9528s/100 iter), 21.7/232ep, loss = 4.23018
-I0510 16:45:48.322760  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64182 (* 1 = 3.64182 loss)
-I0510 16:45:48.322772  5307 sgd_solver.cpp:172] Iteration 11200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:46:48.441637  5307 solver.cpp:352] Iteration 11300 (1.66339 iter/s, 60.1182s/100 iter), 21.8/232ep, loss = 4.2839
-I0510 16:46:48.441692  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20155 (* 1 = 3.20155 loss)
-I0510 16:46:48.441699  5307 sgd_solver.cpp:172] Iteration 11300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:47:25.483207  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:47:49.252192  5307 solver.cpp:352] Iteration 11400 (1.64448 iter/s, 60.8095s/100 iter), 22/232ep, loss = 4.16623
-I0510 16:47:49.252215  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13885 (* 1 = 3.13885 loss)
-I0510 16:47:49.252223  5307 sgd_solver.cpp:172] Iteration 11400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:48:50.116747  5307 solver.cpp:352] Iteration 11500 (1.64302 iter/s, 60.8635s/100 iter), 22.2/232ep, loss = 4.14411
-I0510 16:48:50.116850  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.16257 (* 1 = 4.16257 loss)
-I0510 16:48:50.116873  5307 sgd_solver.cpp:172] Iteration 11500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:49:51.222333  5307 solver.cpp:352] Iteration 11600 (1.63654 iter/s, 61.1045s/100 iter), 22.4/232ep, loss = 4.14758
-I0510 16:49:51.222458  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.1045 (* 1 = 4.1045 loss)
-I0510 16:49:51.222470  5307 sgd_solver.cpp:172] Iteration 11600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:50:52.188690  5307 solver.cpp:352] Iteration 11700 (1.64028 iter/s, 60.9653s/100 iter), 22.6/232ep, loss = 4.45619
-I0510 16:50:52.188776  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.1889 (* 1 = 5.1889 loss)
-I0510 16:50:52.188787  5307 sgd_solver.cpp:172] Iteration 11700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:51:53.544272  5307 solver.cpp:352] Iteration 11800 (1.62987 iter/s, 61.3545s/100 iter), 22.8/232ep, loss = 4.10034
-I0510 16:51:53.544347  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.12696 (* 1 = 4.12696 loss)
-I0510 16:51:53.544355  5307 sgd_solver.cpp:172] Iteration 11800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:52:40.321614  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:52:54.253976  5307 solver.cpp:352] Iteration 11900 (1.64721 iter/s, 60.7086s/100 iter), 23/232ep, loss = 4.27672
-I0510 16:52:54.254007  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.39659 (* 1 = 4.39659 loss)
-I0510 16:52:54.254089  5307 sgd_solver.cpp:172] Iteration 11900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:53:53.266656  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_12000.caffemodel
-I0510 16:53:53.284037  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_12000.solverstate
-I0510 16:53:53.289765  5307 solver.cpp:635] Iteration 12000, Testing net (#0)
-I0510 16:54:34.372668  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:54:34.597332  5307 solver.cpp:747] class AP 1: 0.377338
-I0510 16:54:34.598632  5307 solver.cpp:747] class AP 2: 0.473243
-I0510 16:54:34.606649  5307 solver.cpp:747] class AP 3: 0.28361
-I0510 16:54:34.609349  5307 solver.cpp:747] class AP 4: 0.236268
-I0510 16:54:34.614091  5307 solver.cpp:747] class AP 5: 0.154874
-I0510 16:54:34.614581  5307 solver.cpp:747] class AP 6: 0.430217
-I0510 16:54:34.625377  5307 solver.cpp:747] class AP 7: 0.498381
-I0510 16:54:34.625912  5307 solver.cpp:747] class AP 8: 0.514091
-I0510 16:54:34.643224  5307 solver.cpp:747] class AP 9: 0.185966
-I0510 16:54:34.643985  5307 solver.cpp:747] class AP 10: 0.279618
-I0510 16:54:34.644327  5307 solver.cpp:747] class AP 11: 0.260463
-I0510 16:54:34.645735  5307 solver.cpp:747] class AP 12: 0.434783
-I0510 16:54:34.646425  5307 solver.cpp:747] class AP 13: 0.544954
-I0510 16:54:34.646972  5307 solver.cpp:747] class AP 14: 0.511976
-I0510 16:54:34.737347  5307 solver.cpp:747] class AP 15: 0.500064
-I0510 16:54:34.738363  5307 solver.cpp:747] class AP 16: 0.167407
-I0510 16:54:34.741420  5307 solver.cpp:747] class AP 17: 0.288721
-I0510 16:54:34.741683  5307 solver.cpp:747] class AP 18: 0.227028
-I0510 16:54:34.742285  5307 solver.cpp:747] class AP 19: 0.392775
-I0510 16:54:34.742945  5307 solver.cpp:747] class AP 20: 0.278508
-I0510 16:54:34.742951  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.352014
-I0510 16:54:34.743127  5307 solver.cpp:283] Tests completed in 100.487s
-I0510 16:54:35.285920  5307 solver.cpp:352] Iteration 12000 (0.99515 iter/s, 100.487s/100 iter), 23.2/232ep, loss = 4.13124
-I0510 16:54:35.285944  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.88816 (* 1 = 3.88816 loss)
-I0510 16:54:35.285953  5307 sgd_solver.cpp:172] Iteration 12000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:55:34.848623  5307 solver.cpp:352] Iteration 12100 (1.67893 iter/s, 59.5616s/100 iter), 23.4/232ep, loss = 3.97695
-I0510 16:55:34.848683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20505 (* 1 = 3.20505 loss)
-I0510 16:55:34.848691  5307 sgd_solver.cpp:172] Iteration 12100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:56:35.011502  5307 solver.cpp:352] Iteration 12200 (1.66219 iter/s, 60.1617s/100 iter), 23.6/232ep, loss = 4.0189
-I0510 16:56:35.012388  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4049 (* 1 = 3.4049 loss)
-I0510 16:56:35.012408  5307 sgd_solver.cpp:172] Iteration 12200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:57:35.002763  5307 solver.cpp:352] Iteration 12300 (1.66694 iter/s, 59.9902s/100 iter), 23.8/232ep, loss = 4.05656
-I0510 16:57:35.003190  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.29515 (* 1 = 4.29515 loss)
-I0510 16:57:35.003201  5307 sgd_solver.cpp:172] Iteration 12300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:58:32.893283  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 16:58:35.812647  5307 solver.cpp:352] Iteration 12400 (1.6445 iter/s, 60.8088s/100 iter), 24/232ep, loss = 4.24311
-I0510 16:58:35.812897  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02051 (* 1 = 4.02051 loss)
-I0510 16:58:35.812952  5307 sgd_solver.cpp:172] Iteration 12400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 16:59:37.592346  5307 solver.cpp:352] Iteration 12500 (1.61868 iter/s, 61.7786s/100 iter), 24.2/232ep, loss = 4.08884
-I0510 16:59:37.596276  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82929 (* 1 = 3.82929 loss)
-I0510 16:59:37.596339  5307 sgd_solver.cpp:172] Iteration 12500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:00:38.686198  5307 solver.cpp:352] Iteration 12600 (1.63686 iter/s, 61.0928s/100 iter), 24.4/232ep, loss = 4.14987
-I0510 17:00:38.686290  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.31445 (* 1 = 4.31445 loss)
-I0510 17:00:38.686305  5307 sgd_solver.cpp:172] Iteration 12600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:01:38.478579  5307 solver.cpp:352] Iteration 12700 (1.67248 iter/s, 59.7913s/100 iter), 24.6/232ep, loss = 3.97729
-I0510 17:01:38.479331  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.01469 (* 1 = 4.01469 loss)
-I0510 17:01:38.479349  5307 sgd_solver.cpp:172] Iteration 12700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:02:39.137495  5307 solver.cpp:352] Iteration 12800 (1.64859 iter/s, 60.6578s/100 iter), 24.7/232ep, loss = 4.10032
-I0510 17:02:39.137583  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.73172 (* 1 = 4.73172 loss)
-I0510 17:02:39.137591  5307 sgd_solver.cpp:172] Iteration 12800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:03:39.246263  5307 solver.cpp:352] Iteration 12900 (1.66368 iter/s, 60.1077s/100 iter), 24.9/232ep, loss = 4.03988
-I0510 17:03:39.246330  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.31536 (* 1 = 4.31536 loss)
-I0510 17:03:39.246340  5307 sgd_solver.cpp:172] Iteration 12900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:03:47.180572  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:04:40.025022  5307 solver.cpp:352] Iteration 13000 (1.64534 iter/s, 60.7777s/100 iter), 25.1/232ep, loss = 4.02856
-I0510 17:04:40.025166  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68971 (* 1 = 3.68971 loss)
-I0510 17:04:40.025225  5307 sgd_solver.cpp:172] Iteration 13000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:05:40.191223  5307 solver.cpp:352] Iteration 13100 (1.66209 iter/s, 60.1651s/100 iter), 25.3/232ep, loss = 4.16508
-I0510 17:05:40.191306  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49254 (* 1 = 4.49254 loss)
-I0510 17:05:40.191313  5307 sgd_solver.cpp:172] Iteration 13100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:06:48.350085  5307 solver.cpp:352] Iteration 13200 (1.46719 iter/s, 68.1577s/100 iter), 25.5/232ep, loss = 4.01508
-I0510 17:06:48.354142  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.76144 (* 1 = 4.76144 loss)
-I0510 17:06:48.354167  5307 sgd_solver.cpp:172] Iteration 13200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:07:53.096518  5307 solver.cpp:352] Iteration 13300 (1.54451 iter/s, 64.7453s/100 iter), 25.7/232ep, loss = 4.15617
-I0510 17:07:53.096621  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.55177 (* 1 = 4.55177 loss)
-I0510 17:07:53.096631  5307 sgd_solver.cpp:172] Iteration 13300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:08:52.704501  5307 solver.cpp:352] Iteration 13400 (1.67766 iter/s, 59.6069s/100 iter), 25.9/232ep, loss = 4.03562
-I0510 17:08:52.704582  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56205 (* 1 = 3.56205 loss)
-I0510 17:08:52.704591  5307 sgd_solver.cpp:172] Iteration 13400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:09:10.333612  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:09:53.295830  5307 solver.cpp:352] Iteration 13500 (1.65043 iter/s, 60.5903s/100 iter), 26.1/232ep, loss = 4.18251
-I0510 17:09:53.295914  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89812 (* 1 = 3.89812 loss)
-I0510 17:09:53.295923  5307 sgd_solver.cpp:172] Iteration 13500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:10:53.762625  5307 solver.cpp:352] Iteration 13600 (1.65383 iter/s, 60.4657s/100 iter), 26.3/232ep, loss = 4.3044
-I0510 17:10:53.762749  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.40704 (* 1 = 4.40704 loss)
-I0510 17:10:53.762779  5307 sgd_solver.cpp:172] Iteration 13600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:11:53.526618  5307 solver.cpp:352] Iteration 13700 (1.67328 iter/s, 59.763s/100 iter), 26.5/232ep, loss = 4.05516
-I0510 17:11:53.526890  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.48273 (* 1 = 4.48273 loss)
-I0510 17:11:53.526914  5307 sgd_solver.cpp:172] Iteration 13700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:12:54.021212  5307 solver.cpp:352] Iteration 13800 (1.65307 iter/s, 60.4935s/100 iter), 26.7/232ep, loss = 4.13883
-I0510 17:12:54.023648  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82784 (* 1 = 3.82784 loss)
-I0510 17:12:54.023679  5307 sgd_solver.cpp:172] Iteration 13800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:13:53.147681  5307 solver.cpp:352] Iteration 13900 (1.69132 iter/s, 59.1254s/100 iter), 26.9/232ep, loss = 3.92843
-I0510 17:13:53.147752  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.15256 (* 1 = 5.15256 loss)
-I0510 17:13:53.147760  5307 sgd_solver.cpp:172] Iteration 13900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:14:21.294966  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:14:53.081138  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_14000.caffemodel
-I0510 17:14:53.106668  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_14000.solverstate
-I0510 17:14:53.115489  5307 solver.cpp:635] Iteration 14000, Testing net (#0)
-I0510 17:15:36.413102  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:15:36.644253  5307 solver.cpp:747] class AP 1: 0.26767
-I0510 17:15:36.644846  5307 solver.cpp:747] class AP 2: 0.521108
-I0510 17:15:36.645982  5307 solver.cpp:747] class AP 3: 0.190442
-I0510 17:15:36.649343  5307 solver.cpp:747] class AP 4: 0.209313
-I0510 17:15:36.675809  5307 solver.cpp:747] class AP 5: 0.196156
-I0510 17:15:36.676244  5307 solver.cpp:747] class AP 6: 0.524823
-I0510 17:15:36.684424  5307 solver.cpp:747] class AP 7: 0.544608
-I0510 17:15:36.684862  5307 solver.cpp:747] class AP 8: 0.460104
-I0510 17:15:36.702005  5307 solver.cpp:747] class AP 9: 0.141894
-I0510 17:15:36.702060  5307 solver.cpp:747] class AP 10: 0.171285
-I0510 17:15:36.704457  5307 solver.cpp:747] class AP 11: 0.324904
-I0510 17:15:36.704716  5307 solver.cpp:747] class AP 12: 0.356893
-I0510 17:15:36.704767  5307 solver.cpp:747] class AP 13: 0.244357
-I0510 17:15:36.705610  5307 solver.cpp:747] class AP 14: 0.572795
-I0510 17:15:36.763828  5307 solver.cpp:747] class AP 15: 0.551995
-I0510 17:15:36.782464  5307 solver.cpp:747] class AP 16: 0.160565
-I0510 17:15:36.782575  5307 solver.cpp:747] class AP 17: 0.262686
-I0510 17:15:36.783303  5307 solver.cpp:747] class AP 18: 0.248361
-I0510 17:15:36.783385  5307 solver.cpp:747] class AP 19: 0.502314
-I0510 17:15:36.785104  5307 solver.cpp:747] class AP 20: 0.379687
-I0510 17:15:36.785117  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.341598
-I0510 17:15:36.785410  5307 solver.cpp:283] Tests completed in 103.636s
-I0510 17:15:37.416332  5307 solver.cpp:352] Iteration 14000 (0.964917 iter/s, 103.636s/100 iter), 27.1/232ep, loss = 4.10391
-I0510 17:15:37.416354  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.94686 (* 1 = 3.94686 loss)
-I0510 17:15:37.416363  5307 sgd_solver.cpp:172] Iteration 14000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:16:38.509384  5307 solver.cpp:352] Iteration 14100 (1.63688 iter/s, 61.0919s/100 iter), 27.3/232ep, loss = 4.0748
-I0510 17:16:38.509459  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.024 (* 1 = 4.024 loss)
-I0510 17:16:38.509469  5307 sgd_solver.cpp:172] Iteration 14100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:17:39.031899  5307 solver.cpp:352] Iteration 14200 (1.65231 iter/s, 60.5214s/100 iter), 27.5/232ep, loss = 4.04891
-I0510 17:17:39.031961  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.72282 (* 1 = 4.72282 loss)
-I0510 17:17:39.031971  5307 sgd_solver.cpp:172] Iteration 14200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:18:39.693130  5307 solver.cpp:352] Iteration 14300 (1.64853 iter/s, 60.6601s/100 iter), 27.6/232ep, loss = 4.06177
-I0510 17:18:39.693199  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.31345 (* 1 = 4.31345 loss)
-I0510 17:18:39.693244  5307 sgd_solver.cpp:172] Iteration 14300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:19:40.746486  5307 solver.cpp:352] Iteration 14400 (1.63794 iter/s, 61.0523s/100 iter), 27.8/232ep, loss = 4.2231
-I0510 17:19:40.746574  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.62917 (* 1 = 4.62917 loss)
-I0510 17:19:40.746584  5307 sgd_solver.cpp:172] Iteration 14400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:20:20.180049  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:20:41.706598  5307 solver.cpp:352] Iteration 14500 (1.64045 iter/s, 60.959s/100 iter), 28/232ep, loss = 3.993
-I0510 17:20:41.706683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.50615 (* 1 = 4.50615 loss)
-I0510 17:20:41.706708  5307 sgd_solver.cpp:172] Iteration 14500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:21:42.623369  5307 solver.cpp:352] Iteration 14600 (1.64161 iter/s, 60.9157s/100 iter), 28.2/232ep, loss = 4.06883
-I0510 17:21:42.623472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08766 (* 1 = 3.08766 loss)
-I0510 17:21:42.623486  5307 sgd_solver.cpp:172] Iteration 14600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:22:43.666040  5307 solver.cpp:352] Iteration 14700 (1.63823 iter/s, 61.0416s/100 iter), 28.4/232ep, loss = 3.97623
-I0510 17:22:43.666119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33782 (* 1 = 3.33782 loss)
-I0510 17:22:43.666136  5307 sgd_solver.cpp:172] Iteration 14700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:23:44.337112  5307 solver.cpp:352] Iteration 14800 (1.64826 iter/s, 60.67s/100 iter), 28.6/232ep, loss = 4.22662
-I0510 17:23:44.337558  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.92494 (* 1 = 3.92494 loss)
-I0510 17:23:44.337577  5307 sgd_solver.cpp:172] Iteration 14800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:24:44.634955  5307 solver.cpp:352] Iteration 14900 (1.65846 iter/s, 60.2968s/100 iter), 28.8/232ep, loss = 4.08335
-I0510 17:24:44.635013  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.69729 (* 1 = 4.69729 loss)
-I0510 17:24:44.635020  5307 sgd_solver.cpp:172] Iteration 14900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:25:33.500568  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:25:44.786931  5307 solver.cpp:352] Iteration 15000 (1.66249 iter/s, 60.1509s/100 iter), 29/232ep, loss = 4.09779
-I0510 17:25:44.786994  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80358 (* 1 = 3.80358 loss)
-I0510 17:25:44.787019  5307 sgd_solver.cpp:172] Iteration 15000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:26:45.754842  5307 solver.cpp:352] Iteration 15100 (1.64024 iter/s, 60.9668s/100 iter), 29.2/232ep, loss = 3.83954
-I0510 17:26:45.759059  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.36041 (* 1 = 4.36041 loss)
-I0510 17:26:45.759080  5307 sgd_solver.cpp:172] Iteration 15100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:27:46.087405  5307 solver.cpp:352] Iteration 15200 (1.65751 iter/s, 60.3315s/100 iter), 29.4/232ep, loss = 3.79234
-I0510 17:27:46.087489  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89815 (* 1 = 3.89815 loss)
-I0510 17:27:46.087505  5307 sgd_solver.cpp:172] Iteration 15200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:28:47.248160  5307 solver.cpp:352] Iteration 15300 (1.63506 iter/s, 61.1597s/100 iter), 29.6/232ep, loss = 4.25529
-I0510 17:28:47.248291  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.52093 (* 1 = 4.52093 loss)
-I0510 17:28:47.248311  5307 sgd_solver.cpp:172] Iteration 15300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:29:47.624392  5307 solver.cpp:352] Iteration 15400 (1.65631 iter/s, 60.3752s/100 iter), 29.8/232ep, loss = 3.90185
-I0510 17:29:47.624768  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.14909 (* 1 = 4.14909 loss)
-I0510 17:29:47.624789  5307 sgd_solver.cpp:172] Iteration 15400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:30:47.525804  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:30:48.213439  5307 solver.cpp:352] Iteration 15500 (1.65049 iter/s, 60.588s/100 iter), 30/232ep, loss = 4.31352
-I0510 17:30:48.213562  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.92865 (* 1 = 4.92865 loss)
-I0510 17:30:48.213585  5307 sgd_solver.cpp:172] Iteration 15500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:31:49.500659  5307 solver.cpp:352] Iteration 15600 (1.63169 iter/s, 61.2862s/100 iter), 30.2/232ep, loss = 4.06144
-I0510 17:31:49.500794  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.67102 (* 1 = 4.67102 loss)
-I0510 17:31:49.500823  5307 sgd_solver.cpp:172] Iteration 15600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:32:49.536686  5307 solver.cpp:352] Iteration 15700 (1.6657 iter/s, 60.035s/100 iter), 30.4/232ep, loss = 4.13441
-I0510 17:32:49.537791  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47626 (* 1 = 3.47626 loss)
-I0510 17:32:49.537806  5307 sgd_solver.cpp:172] Iteration 15700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:33:50.337203  5307 solver.cpp:352] Iteration 15800 (1.64475 iter/s, 60.7995s/100 iter), 30.5/232ep, loss = 3.98306
-I0510 17:33:50.337349  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89969 (* 1 = 3.89969 loss)
-I0510 17:33:50.337357  5307 sgd_solver.cpp:172] Iteration 15800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:34:50.994805  5307 solver.cpp:352] Iteration 15900 (1.64863 iter/s, 60.6565s/100 iter), 30.7/232ep, loss = 3.94058
-I0510 17:34:50.995951  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15672 (* 1 = 4.15672 loss)
-I0510 17:34:50.995962  5307 sgd_solver.cpp:172] Iteration 15900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:35:51.081809  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_16000.caffemodel
-I0510 17:35:51.098748  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_16000.solverstate
-I0510 17:35:51.104290  5307 solver.cpp:635] Iteration 16000, Testing net (#0)
-I0510 17:36:33.383131  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:36:33.610116  5307 solver.cpp:747] class AP 1: 0.486965
-I0510 17:36:33.610594  5307 solver.cpp:747] class AP 2: 0.526476
-I0510 17:36:33.614055  5307 solver.cpp:747] class AP 3: 0.364743
-I0510 17:36:33.615774  5307 solver.cpp:747] class AP 4: 0.298434
-I0510 17:36:33.624733  5307 solver.cpp:747] class AP 5: 0.151348
-I0510 17:36:33.625550  5307 solver.cpp:747] class AP 6: 0.594422
-I0510 17:36:33.635076  5307 solver.cpp:747] class AP 7: 0.564054
-I0510 17:36:33.635455  5307 solver.cpp:747] class AP 8: 0.653435
-I0510 17:36:33.657244  5307 solver.cpp:747] class AP 9: 0.246602
-I0510 17:36:33.657665  5307 solver.cpp:747] class AP 10: 0.407204
-I0510 17:36:33.658128  5307 solver.cpp:747] class AP 11: 0.326416
-I0510 17:36:33.659003  5307 solver.cpp:747] class AP 12: 0.557808
-I0510 17:36:33.659384  5307 solver.cpp:747] class AP 13: 0.654049
-I0510 17:36:33.659610  5307 solver.cpp:747] class AP 14: 0.561787
-I0510 17:36:33.743221  5307 solver.cpp:747] class AP 15: 0.609836
-I0510 17:36:33.745687  5307 solver.cpp:747] class AP 16: 0.204773
-I0510 17:36:33.746655  5307 solver.cpp:747] class AP 17: 0.436756
-I0510 17:36:33.747130  5307 solver.cpp:747] class AP 18: 0.468889
-I0510 17:36:33.747989  5307 solver.cpp:747] class AP 19: 0.595545
-I0510 17:36:33.749708  5307 solver.cpp:747] class AP 20: 0.467597
-I0510 17:36:33.749716  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.458857
-I0510 17:36:33.749986  5307 solver.cpp:283] Tests completed in 102.753s
-I0510 17:36:34.340684  5307 solver.cpp:352] Iteration 16000 (0.973204 iter/s, 102.753s/100 iter), 30.9/232ep, loss = 3.82997
-I0510 17:36:34.340775  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73402 (* 1 = 2.73402 loss)
-I0510 17:36:34.340798  5307 sgd_solver.cpp:172] Iteration 16000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:36:43.517487  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:37:35.048465  5307 solver.cpp:352] Iteration 16100 (1.64727 iter/s, 60.7067s/100 iter), 31.1/232ep, loss = 4.22994
-I0510 17:37:35.048614  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.20404 (* 1 = 5.20404 loss)
-I0510 17:37:35.048635  5307 sgd_solver.cpp:172] Iteration 16100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:38:35.793680  5307 solver.cpp:352] Iteration 16200 (1.64625 iter/s, 60.7441s/100 iter), 31.3/232ep, loss = 3.97765
-I0510 17:38:35.793766  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.58101 (* 1 = 4.58101 loss)
-I0510 17:38:35.793776  5307 sgd_solver.cpp:172] Iteration 16200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:39:35.721940  5307 solver.cpp:352] Iteration 16300 (1.66869 iter/s, 59.9272s/100 iter), 31.5/232ep, loss = 3.78574
-I0510 17:39:35.722015  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.64567 (* 1 = 4.64567 loss)
-I0510 17:39:35.722024  5307 sgd_solver.cpp:172] Iteration 16300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:40:35.965342  5307 solver.cpp:352] Iteration 16400 (1.65996 iter/s, 60.2423s/100 iter), 31.7/232ep, loss = 3.97578
-I0510 17:40:35.965407  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22316 (* 1 = 3.22316 loss)
-I0510 17:40:35.965415  5307 sgd_solver.cpp:172] Iteration 16400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:41:37.109102  5307 solver.cpp:352] Iteration 16500 (1.63552 iter/s, 61.1426s/100 iter), 31.9/232ep, loss = 3.84236
-I0510 17:41:37.112644  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.35575 (* 1 = 4.35575 loss)
-I0510 17:41:37.112681  5307 sgd_solver.cpp:172] Iteration 16500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:41:57.559957  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:42:38.290222  5307 solver.cpp:352] Iteration 16600 (1.63452 iter/s, 61.18s/100 iter), 32.1/232ep, loss = 3.9832
-I0510 17:42:38.290297  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06678 (* 1 = 4.06678 loss)
-I0510 17:42:38.290305  5307 sgd_solver.cpp:172] Iteration 16600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:43:39.620643  5307 solver.cpp:352] Iteration 16700 (1.63054 iter/s, 61.3293s/100 iter), 32.3/232ep, loss = 3.93954
-I0510 17:43:39.620726  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65763 (* 1 = 3.65763 loss)
-I0510 17:43:39.620740  5307 sgd_solver.cpp:172] Iteration 16700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:44:40.493341  5307 solver.cpp:352] Iteration 16800 (1.6428 iter/s, 60.8716s/100 iter), 32.5/232ep, loss = 4.09846
-I0510 17:44:40.493398  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68261 (* 1 = 3.68261 loss)
-I0510 17:44:40.493405  5307 sgd_solver.cpp:172] Iteration 16800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:45:41.239418  5307 solver.cpp:352] Iteration 16900 (1.64623 iter/s, 60.745s/100 iter), 32.7/232ep, loss = 3.76668
-I0510 17:45:41.239538  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.29666 (* 1 = 3.29666 loss)
-I0510 17:45:41.239555  5307 sgd_solver.cpp:172] Iteration 16900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:46:42.703081  5307 solver.cpp:352] Iteration 17000 (1.62701 iter/s, 61.4626s/100 iter), 32.9/232ep, loss = 3.9525
-I0510 17:46:42.703943  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58665 (* 1 = 3.58665 loss)
-I0510 17:46:42.703951  5307 sgd_solver.cpp:172] Iteration 17000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:47:13.536533  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:47:43.672152  5307 solver.cpp:352] Iteration 17100 (1.64021 iter/s, 60.968s/100 iter), 33.1/232ep, loss = 4.24186
-I0510 17:47:43.672236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.35574 (* 1 = 4.35574 loss)
-I0510 17:47:43.672252  5307 sgd_solver.cpp:172] Iteration 17100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:48:44.434834  5307 solver.cpp:352] Iteration 17200 (1.64578 iter/s, 60.7616s/100 iter), 33.3/232ep, loss = 4.11966
-I0510 17:48:44.434926  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3499 (* 1 = 3.3499 loss)
-I0510 17:48:44.434934  5307 sgd_solver.cpp:172] Iteration 17200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:49:45.975968  5307 solver.cpp:352] Iteration 17300 (1.62496 iter/s, 61.54s/100 iter), 33.4/232ep, loss = 3.93047
-I0510 17:49:45.976122  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.90535 (* 1 = 3.90535 loss)
-I0510 17:49:45.976135  5307 sgd_solver.cpp:172] Iteration 17300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:50:46.313288  5307 solver.cpp:352] Iteration 17400 (1.65738 iter/s, 60.3363s/100 iter), 33.6/232ep, loss = 3.95524
-I0510 17:50:46.315484  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67539 (* 1 = 3.67539 loss)
-I0510 17:50:46.315497  5307 sgd_solver.cpp:172] Iteration 17400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:51:47.110417  5307 solver.cpp:352] Iteration 17500 (1.64484 iter/s, 60.7961s/100 iter), 33.8/232ep, loss = 4.11225
-I0510 17:51:47.110472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.59651 (* 1 = 4.59651 loss)
-I0510 17:51:47.110479  5307 sgd_solver.cpp:172] Iteration 17500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:52:27.470515  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:52:47.254881  5307 solver.cpp:352] Iteration 17600 (1.66269 iter/s, 60.1434s/100 iter), 34/232ep, loss = 4.07409
-I0510 17:52:47.254906  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87837 (* 1 = 3.87837 loss)
-I0510 17:52:47.254914  5307 sgd_solver.cpp:172] Iteration 17600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:53:47.585824  5307 solver.cpp:352] Iteration 17700 (1.65755 iter/s, 60.3299s/100 iter), 34.2/232ep, loss = 4.09266
-I0510 17:53:47.585917  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.20773 (* 1 = 4.20773 loss)
-I0510 17:53:47.585937  5307 sgd_solver.cpp:172] Iteration 17700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:54:49.169430  5307 solver.cpp:352] Iteration 17800 (1.62384 iter/s, 61.5825s/100 iter), 34.4/232ep, loss = 4.06271
-I0510 17:54:49.169489  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.08636 (* 1 = 4.08636 loss)
-I0510 17:54:49.169497  5307 sgd_solver.cpp:172] Iteration 17800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:55:51.290794  5307 solver.cpp:352] Iteration 17900 (1.60978 iter/s, 62.1203s/100 iter), 34.6/232ep, loss = 3.95755
-I0510 17:55:51.290895  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02087 (* 1 = 4.02087 loss)
-I0510 17:55:51.290905  5307 sgd_solver.cpp:172] Iteration 17900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:56:51.971354  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_18000.caffemodel
-I0510 17:56:51.990205  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_18000.solverstate
-I0510 17:56:51.995992  5307 solver.cpp:635] Iteration 18000, Testing net (#0)
-I0510 17:57:33.766407  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:57:33.960752  5307 solver.cpp:747] class AP 1: 0.406091
-I0510 17:57:33.961108  5307 solver.cpp:747] class AP 2: 0.464497
-I0510 17:57:33.964440  5307 solver.cpp:747] class AP 3: 0.2912
-I0510 17:57:33.965749  5307 solver.cpp:747] class AP 4: 0.207739
-I0510 17:57:33.996084  5307 solver.cpp:747] class AP 5: 0.167533
-I0510 17:57:33.996301  5307 solver.cpp:747] class AP 6: 0.579484
-I0510 17:57:34.003047  5307 solver.cpp:747] class AP 7: 0.549524
-I0510 17:57:34.003806  5307 solver.cpp:747] class AP 8: 0.616621
-I0510 17:57:34.028941  5307 solver.cpp:747] class AP 9: 0.269421
-I0510 17:57:34.029110  5307 solver.cpp:747] class AP 10: 0.293091
-I0510 17:57:34.030127  5307 solver.cpp:747] class AP 11: 0.404158
-I0510 17:57:34.030670  5307 solver.cpp:747] class AP 12: 0.489255
-I0510 17:57:34.030750  5307 solver.cpp:747] class AP 13: 0.475573
-I0510 17:57:34.031006  5307 solver.cpp:747] class AP 14: 0.444097
-I0510 17:57:34.081130  5307 solver.cpp:747] class AP 15: 0.539198
-I0510 17:57:34.096513  5307 solver.cpp:747] class AP 16: 0.149469
-I0510 17:57:34.096949  5307 solver.cpp:747] class AP 17: 0.370188
-I0510 17:57:34.097833  5307 solver.cpp:747] class AP 18: 0.353684
-I0510 17:57:34.098188  5307 solver.cpp:747] class AP 19: 0.501156
-I0510 17:57:34.101331  5307 solver.cpp:747] class AP 20: 0.364472
-I0510 17:57:34.101347  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.396823
-I0510 17:57:34.101477  5307 solver.cpp:283] Tests completed in 102.809s
-I0510 17:57:34.706904  5307 solver.cpp:352] Iteration 18000 (0.972679 iter/s, 102.809s/100 iter), 34.8/232ep, loss = 4.1169
-I0510 17:57:34.706931  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.28014 (* 1 = 4.28014 loss)
-I0510 17:57:34.706939  5307 sgd_solver.cpp:172] Iteration 18000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:58:26.168864  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 17:58:34.832660  5307 solver.cpp:352] Iteration 18100 (1.66321 iter/s, 60.1246s/100 iter), 35/232ep, loss = 4.08924
-I0510 17:58:34.832814  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.48788 (* 1 = 4.48788 loss)
-I0510 17:58:34.832832  5307 sgd_solver.cpp:172] Iteration 18100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 17:59:35.985110  5307 solver.cpp:352] Iteration 18200 (1.63529 iter/s, 61.1514s/100 iter), 35.2/232ep, loss = 3.75936
-I0510 17:59:35.985201  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16756 (* 1 = 3.16756 loss)
-I0510 17:59:35.985221  5307 sgd_solver.cpp:172] Iteration 18200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:00:36.783682  5307 solver.cpp:352] Iteration 18300 (1.64481 iter/s, 60.7975s/100 iter), 35.4/232ep, loss = 3.86903
-I0510 18:00:36.783763  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.3618 (* 1 = 4.3618 loss)
-I0510 18:00:36.783771  5307 sgd_solver.cpp:172] Iteration 18300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:01:38.399515  5307 solver.cpp:352] Iteration 18400 (1.62299 iter/s, 61.6147s/100 iter), 35.6/232ep, loss = 4.0389
-I0510 18:01:38.399615  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.60873 (* 1 = 3.60873 loss)
-I0510 18:01:38.399624  5307 sgd_solver.cpp:172] Iteration 18400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:02:40.127353  5307 solver.cpp:352] Iteration 18500 (1.62004 iter/s, 61.7267s/100 iter), 35.8/232ep, loss = 3.90535
-I0510 18:02:40.127506  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57586 (* 1 = 3.57586 loss)
-I0510 18:02:40.127534  5307 sgd_solver.cpp:172] Iteration 18500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:03:39.942431  5307 solver.cpp:352] Iteration 18600 (1.67185 iter/s, 59.814s/100 iter), 36/232ep, loss = 3.91408
-I0510 18:03:39.942529  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.13427 (* 1 = 5.13427 loss)
-I0510 18:03:39.942539  5307 sgd_solver.cpp:172] Iteration 18600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:03:40.720665  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:04:39.985424  5307 solver.cpp:352] Iteration 18700 (1.6655 iter/s, 60.0419s/100 iter), 36.2/232ep, loss = 3.97106
-I0510 18:04:39.985500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63197 (* 1 = 3.63197 loss)
-I0510 18:04:39.985510  5307 sgd_solver.cpp:172] Iteration 18700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:05:40.361156  5307 solver.cpp:352] Iteration 18800 (1.65632 iter/s, 60.3746s/100 iter), 36.3/232ep, loss = 3.98146
-I0510 18:05:40.364639  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.842 (* 1 = 4.842 loss)
-I0510 18:05:40.364675  5307 sgd_solver.cpp:172] Iteration 18800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:06:40.600116  5307 solver.cpp:352] Iteration 18900 (1.66008 iter/s, 60.2379s/100 iter), 36.5/232ep, loss = 3.86298
-I0510 18:06:40.600175  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85125 (* 1 = 3.85125 loss)
-I0510 18:06:40.600183  5307 sgd_solver.cpp:172] Iteration 18900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:07:41.151947  5307 solver.cpp:352] Iteration 19000 (1.65151 iter/s, 60.5508s/100 iter), 36.7/232ep, loss = 4.04988
-I0510 18:07:41.152015  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93703 (* 1 = 3.93703 loss)
-I0510 18:07:41.152024  5307 sgd_solver.cpp:172] Iteration 19000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:08:41.814600  5307 solver.cpp:352] Iteration 19100 (1.64849 iter/s, 60.6616s/100 iter), 36.9/232ep, loss = 3.8313
-I0510 18:08:41.815102  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.45588 (* 1 = 4.45588 loss)
-I0510 18:08:41.815121  5307 sgd_solver.cpp:172] Iteration 19100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:08:53.398103  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:09:41.547041  5307 solver.cpp:352] Iteration 19200 (1.67416 iter/s, 59.7314s/100 iter), 37.1/232ep, loss = 3.9092
-I0510 18:09:41.547230  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30575 (* 1 = 3.30575 loss)
-I0510 18:09:41.547346  5307 sgd_solver.cpp:172] Iteration 19200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:10:41.878931  5307 solver.cpp:352] Iteration 19300 (1.65753 iter/s, 60.3308s/100 iter), 37.3/232ep, loss = 4.02067
-I0510 18:10:41.879042  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05662 (* 1 = 4.05662 loss)
-I0510 18:10:41.879062  5307 sgd_solver.cpp:172] Iteration 19300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:11:41.982174  5307 solver.cpp:352] Iteration 19400 (1.66383 iter/s, 60.1022s/100 iter), 37.5/232ep, loss = 3.94155
-I0510 18:11:41.982257  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.74712 (* 1 = 4.74712 loss)
-I0510 18:11:41.982267  5307 sgd_solver.cpp:172] Iteration 19400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:12:42.256016  5307 solver.cpp:352] Iteration 19500 (1.65912 iter/s, 60.2727s/100 iter), 37.7/232ep, loss = 3.96735
-I0510 18:12:42.256213  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91876 (* 1 = 3.91876 loss)
-I0510 18:12:42.256234  5307 sgd_solver.cpp:172] Iteration 19500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:13:42.999758  5307 solver.cpp:352] Iteration 19600 (1.64629 iter/s, 60.7427s/100 iter), 37.9/232ep, loss = 4.12041
-I0510 18:13:42.999848  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56942 (* 1 = 3.56942 loss)
-I0510 18:13:42.999858  5307 sgd_solver.cpp:172] Iteration 19600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:14:06.984825  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:14:50.224472  5307 solver.cpp:352] Iteration 19700 (1.48757 iter/s, 67.2235s/100 iter), 38.1/232ep, loss = 4.04457
-I0510 18:14:50.224571  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.32989 (* 1 = 4.32989 loss)
-I0510 18:14:50.224588  5307 sgd_solver.cpp:172] Iteration 19700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:15:55.267130  5307 solver.cpp:352] Iteration 19800 (1.53748 iter/s, 65.0415s/100 iter), 38.3/232ep, loss = 3.97563
-I0510 18:15:55.267290  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43165 (* 1 = 3.43165 loss)
-I0510 18:15:55.267304  5307 sgd_solver.cpp:172] Iteration 19800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:16:56.501657  5307 solver.cpp:352] Iteration 19900 (1.63309 iter/s, 61.2334s/100 iter), 38.5/232ep, loss = 3.9215
-I0510 18:16:56.501725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38991 (* 1 = 3.38991 loss)
-I0510 18:16:56.501735  5307 sgd_solver.cpp:172] Iteration 19900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:17:55.653561  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_20000.caffemodel
-I0510 18:17:55.693248  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_20000.solverstate
-I0510 18:17:55.697934  5307 solver.cpp:635] Iteration 20000, Testing net (#0)
-I0510 18:18:37.112228  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:18:37.306205  5307 solver.cpp:747] class AP 1: 0.34128
-I0510 18:18:37.306692  5307 solver.cpp:747] class AP 2: 0.466179
-I0510 18:18:37.316076  5307 solver.cpp:747] class AP 3: 0.338858
-I0510 18:18:37.320827  5307 solver.cpp:747] class AP 4: 0.227758
-I0510 18:18:37.331344  5307 solver.cpp:747] class AP 5: 0.208365
-I0510 18:18:37.332031  5307 solver.cpp:747] class AP 6: 0.544774
-I0510 18:18:37.339907  5307 solver.cpp:747] class AP 7: 0.530615
-I0510 18:18:37.341220  5307 solver.cpp:747] class AP 8: 0.540702
-I0510 18:18:37.378499  5307 solver.cpp:747] class AP 9: 0.206761
-I0510 18:18:37.379087  5307 solver.cpp:747] class AP 10: 0.379273
-I0510 18:18:37.379915  5307 solver.cpp:747] class AP 11: 0.333792
-I0510 18:18:37.380676  5307 solver.cpp:747] class AP 12: 0.447937
-I0510 18:18:37.381017  5307 solver.cpp:747] class AP 13: 0.587963
-I0510 18:18:37.381248  5307 solver.cpp:747] class AP 14: 0.473695
-I0510 18:18:37.442178  5307 solver.cpp:747] class AP 15: 0.517321
-I0510 18:18:37.448504  5307 solver.cpp:747] class AP 16: 0.189493
-I0510 18:18:37.452178  5307 solver.cpp:747] class AP 17: 0.361723
-I0510 18:18:37.452957  5307 solver.cpp:747] class AP 18: 0.335269
-I0510 18:18:37.454664  5307 solver.cpp:747] class AP 19: 0.548444
-I0510 18:18:37.459687  5307 solver.cpp:747] class AP 20: 0.405736
-I0510 18:18:37.459728  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.399297
-I0510 18:18:37.460028  5307 solver.cpp:283] Tests completed in 100.957s
-I0510 18:18:38.128073  5307 solver.cpp:352] Iteration 20000 (0.990525 iter/s, 100.957s/100 iter), 38.7/232ep, loss = 3.92276
-I0510 18:18:38.128098  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68845 (* 1 = 3.68845 loss)
-I0510 18:18:38.128104  5307 sgd_solver.cpp:172] Iteration 20000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:19:38.890480  5307 solver.cpp:352] Iteration 20100 (1.64578 iter/s, 60.7613s/100 iter), 38.9/232ep, loss = 3.81434
-I0510 18:19:38.890576  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05766 (* 1 = 4.05766 loss)
-I0510 18:19:38.890584  5307 sgd_solver.cpp:172] Iteration 20100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:20:10.870867  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:20:39.101873  5307 solver.cpp:352] Iteration 20200 (1.66085 iter/s, 60.2103s/100 iter), 39.1/232ep, loss = 3.93665
-I0510 18:20:39.101954  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.36537 (* 1 = 4.36537 loss)
-I0510 18:20:39.101975  5307 sgd_solver.cpp:172] Iteration 20200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:21:39.325006  5307 solver.cpp:352] Iteration 20300 (1.66052 iter/s, 60.2221s/100 iter), 39.2/232ep, loss = 3.84677
-I0510 18:21:39.325109  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61705 (* 1 = 3.61705 loss)
-I0510 18:21:39.325120  5307 sgd_solver.cpp:172] Iteration 20300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:22:39.772847  5307 solver.cpp:352] Iteration 20400 (1.65435 iter/s, 60.4467s/100 iter), 39.4/232ep, loss = 3.83104
-I0510 18:22:39.773057  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03349 (* 1 = 4.03349 loss)
-I0510 18:22:39.773083  5307 sgd_solver.cpp:172] Iteration 20400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:23:39.822788  5307 solver.cpp:352] Iteration 20500 (1.66531 iter/s, 60.0489s/100 iter), 39.6/232ep, loss = 3.87636
-I0510 18:23:39.822922  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.35261 (* 1 = 4.35261 loss)
-I0510 18:23:39.822937  5307 sgd_solver.cpp:172] Iteration 20500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:24:39.488035  5307 solver.cpp:352] Iteration 20600 (1.67605 iter/s, 59.6642s/100 iter), 39.8/232ep, loss = 3.97765
-I0510 18:24:39.488114  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.28101 (* 1 = 4.28101 loss)
-I0510 18:24:39.488124  5307 sgd_solver.cpp:172] Iteration 20600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:25:22.277652  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:25:39.628329  5307 solver.cpp:352] Iteration 20700 (1.66281 iter/s, 60.1392s/100 iter), 40/232ep, loss = 3.92331
-I0510 18:25:39.628352  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61269 (* 1 = 3.61269 loss)
-I0510 18:25:39.628358  5307 sgd_solver.cpp:172] Iteration 20700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:26:39.289927  5307 solver.cpp:352] Iteration 20800 (1.67615 iter/s, 59.6605s/100 iter), 40.2/232ep, loss = 3.75517
-I0510 18:26:39.289999  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53533 (* 1 = 3.53533 loss)
-I0510 18:26:39.290007  5307 sgd_solver.cpp:172] Iteration 20800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:27:40.264546  5307 solver.cpp:352] Iteration 20900 (1.64006 iter/s, 60.9735s/100 iter), 40.4/232ep, loss = 4.09701
-I0510 18:27:40.265084  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93349 (* 1 = 3.93349 loss)
-I0510 18:27:40.265094  5307 sgd_solver.cpp:172] Iteration 20900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:28:41.227520  5307 solver.cpp:352] Iteration 21000 (1.64037 iter/s, 60.9619s/100 iter), 40.6/232ep, loss = 3.9031
-I0510 18:28:41.229018  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82276 (* 1 = 3.82276 loss)
-I0510 18:28:41.229033  5307 sgd_solver.cpp:172] Iteration 21000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:29:41.710839  5307 solver.cpp:352] Iteration 21100 (1.65338 iter/s, 60.4822s/100 iter), 40.8/232ep, loss = 4.0459
-I0510 18:29:41.710918  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.45003 (* 1 = 5.45003 loss)
-I0510 18:29:41.710929  5307 sgd_solver.cpp:172] Iteration 21100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:30:34.003978  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:30:41.507900  5307 solver.cpp:352] Iteration 21200 (1.67235 iter/s, 59.796s/100 iter), 41/232ep, loss = 4.03447
-I0510 18:30:41.507969  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.2517 (* 1 = 4.2517 loss)
-I0510 18:30:41.507989  5307 sgd_solver.cpp:172] Iteration 21200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:31:41.589257  5307 solver.cpp:352] Iteration 21300 (1.66444 iter/s, 60.0803s/100 iter), 41.2/232ep, loss = 4.00796
-I0510 18:31:41.589359  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.64948 (* 1 = 4.64948 loss)
-I0510 18:31:41.589378  5307 sgd_solver.cpp:172] Iteration 21300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:32:41.931206  5307 solver.cpp:352] Iteration 21400 (1.65725 iter/s, 60.3409s/100 iter), 41.4/232ep, loss = 3.80331
-I0510 18:32:41.931308  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65604 (* 1 = 3.65604 loss)
-I0510 18:32:41.931512  5307 sgd_solver.cpp:172] Iteration 21400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:33:42.036473  5307 solver.cpp:352] Iteration 21500 (1.66378 iter/s, 60.1042s/100 iter), 41.6/232ep, loss = 4.00471
-I0510 18:33:42.036576  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.9934 (* 1 = 5.9934 loss)
-I0510 18:33:42.036587  5307 sgd_solver.cpp:172] Iteration 21500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:34:41.460405  5307 solver.cpp:352] Iteration 21600 (1.68285 iter/s, 59.4229s/100 iter), 41.8/232ep, loss = 3.79898
-I0510 18:34:41.460487  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.68195 (* 1 = 4.68195 loss)
-I0510 18:34:41.460497  5307 sgd_solver.cpp:172] Iteration 21600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:35:41.398211  5307 solver.cpp:352] Iteration 21700 (1.66843 iter/s, 59.9368s/100 iter), 42/232ep, loss = 3.8566
-I0510 18:35:41.398293  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.24144 (* 1 = 4.24144 loss)
-I0510 18:35:41.398301  5307 sgd_solver.cpp:172] Iteration 21700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:35:44.294472  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:36:41.684083  5307 solver.cpp:352] Iteration 21800 (1.65879 iter/s, 60.2848s/100 iter), 42.1/232ep, loss = 3.88238
-I0510 18:36:41.684232  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80177 (* 1 = 3.80177 loss)
-I0510 18:36:41.684255  5307 sgd_solver.cpp:172] Iteration 21800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:37:42.083560  5307 solver.cpp:352] Iteration 21900 (1.65567 iter/s, 60.3984s/100 iter), 42.3/232ep, loss = 3.93615
-I0510 18:37:42.083660  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.17012 (* 1 = 3.17012 loss)
-I0510 18:37:42.083669  5307 sgd_solver.cpp:172] Iteration 21900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:38:42.316890  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_22000.caffemodel
-I0510 18:38:42.336257  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_22000.solverstate
-I0510 18:38:42.343206  5307 solver.cpp:635] Iteration 22000, Testing net (#0)
-I0510 18:39:23.263263  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:39:23.482539  5307 solver.cpp:747] class AP 1: 0.530255
-I0510 18:39:23.483283  5307 solver.cpp:747] class AP 2: 0.599847
-I0510 18:39:23.490195  5307 solver.cpp:747] class AP 3: 0.416361
-I0510 18:39:23.492012  5307 solver.cpp:747] class AP 4: 0.327485
-I0510 18:39:23.506052  5307 solver.cpp:747] class AP 5: 0.238198
-I0510 18:39:23.506343  5307 solver.cpp:747] class AP 6: 0.611445
-I0510 18:39:23.512264  5307 solver.cpp:747] class AP 7: 0.597716
-I0510 18:39:23.513100  5307 solver.cpp:747] class AP 8: 0.673315
-I0510 18:39:23.529266  5307 solver.cpp:747] class AP 9: 0.239872
-I0510 18:39:23.530041  5307 solver.cpp:747] class AP 10: 0.456606
-I0510 18:39:23.530591  5307 solver.cpp:747] class AP 11: 0.429406
-I0510 18:39:23.532676  5307 solver.cpp:747] class AP 12: 0.59359
-I0510 18:39:23.533262  5307 solver.cpp:747] class AP 13: 0.692092
-I0510 18:39:23.533761  5307 solver.cpp:747] class AP 14: 0.583687
-I0510 18:39:23.602900  5307 solver.cpp:747] class AP 15: 0.641689
-I0510 18:39:23.609939  5307 solver.cpp:747] class AP 16: 0.227152
-I0510 18:39:23.611941  5307 solver.cpp:747] class AP 17: 0.475418
-I0510 18:39:23.613131  5307 solver.cpp:747] class AP 18: 0.426319
-I0510 18:39:23.614387  5307 solver.cpp:747] class AP 19: 0.632528
-I0510 18:39:23.615263  5307 solver.cpp:747] class AP 20: 0.441181
-I0510 18:39:23.615268  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.491708
-I0510 18:39:23.615408  5307 solver.cpp:283] Tests completed in 101.53s
-I0510 18:39:24.182399  5307 solver.cpp:352] Iteration 22000 (0.98493 iter/s, 101.53s/100 iter), 42.5/232ep, loss = 3.75261
-I0510 18:39:24.182422  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.98661 (* 1 = 3.98661 loss)
-I0510 18:39:24.182430  5307 sgd_solver.cpp:172] Iteration 22000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:40:24.254237  5307 solver.cpp:352] Iteration 22100 (1.6647 iter/s, 60.0707s/100 iter), 42.7/232ep, loss = 3.94477
-I0510 18:40:24.255007  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.10083 (* 1 = 4.10083 loss)
-I0510 18:40:24.255017  5307 sgd_solver.cpp:172] Iteration 22100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:41:25.275432  5307 solver.cpp:352] Iteration 22200 (1.63881 iter/s, 61.0201s/100 iter), 42.9/232ep, loss = 3.93176
-I0510 18:41:25.275652  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.34443 (* 1 = 4.34443 loss)
-I0510 18:41:25.275666  5307 sgd_solver.cpp:172] Iteration 22200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:41:39.151403  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:42:25.048168  5307 solver.cpp:352] Iteration 22300 (1.67303 iter/s, 59.7717s/100 iter), 43.1/232ep, loss = 3.80451
-I0510 18:42:25.048316  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.18245 (* 1 = 3.18245 loss)
-I0510 18:42:25.048336  5307 sgd_solver.cpp:172] Iteration 22300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:43:24.551668  5307 solver.cpp:352] Iteration 22400 (1.6806 iter/s, 59.5024s/100 iter), 43.3/232ep, loss = 3.88076
-I0510 18:43:24.551745  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.97335 (* 1 = 2.97335 loss)
-I0510 18:43:24.551754  5307 sgd_solver.cpp:172] Iteration 22400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:44:24.905186  5307 solver.cpp:352] Iteration 22500 (1.65693 iter/s, 60.3524s/100 iter), 43.5/232ep, loss = 3.91015
-I0510 18:44:24.905256  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46989 (* 1 = 3.46989 loss)
-I0510 18:44:24.905262  5307 sgd_solver.cpp:172] Iteration 22500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:45:25.671592  5307 solver.cpp:352] Iteration 22600 (1.64568 iter/s, 60.7653s/100 iter), 43.7/232ep, loss = 3.83031
-I0510 18:45:25.671681  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.12052 (* 1 = 3.12052 loss)
-I0510 18:45:25.671700  5307 sgd_solver.cpp:172] Iteration 22600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:46:25.727347  5307 solver.cpp:352] Iteration 22700 (1.66515 iter/s, 60.0547s/100 iter), 43.9/232ep, loss = 3.77082
-I0510 18:46:25.727466  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15335 (* 1 = 4.15335 loss)
-I0510 18:46:25.727480  5307 sgd_solver.cpp:172] Iteration 22700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:46:49.056587  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:47:25.671694  5307 solver.cpp:352] Iteration 22800 (1.66824 iter/s, 59.9433s/100 iter), 44.1/232ep, loss = 3.75317
-I0510 18:47:25.675361  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.52456 (* 1 = 3.52456 loss)
-I0510 18:47:25.675397  5307 sgd_solver.cpp:172] Iteration 22800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:48:26.058811  5307 solver.cpp:352] Iteration 22900 (1.65601 iter/s, 60.386s/100 iter), 44.3/232ep, loss = 3.91824
-I0510 18:48:26.058909  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.12324 (* 1 = 3.12324 loss)
-I0510 18:48:26.058931  5307 sgd_solver.cpp:172] Iteration 22900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:49:25.958818  5307 solver.cpp:352] Iteration 23000 (1.66948 iter/s, 59.8989s/100 iter), 44.5/232ep, loss = 3.88529
-I0510 18:49:25.958876  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82834 (* 1 = 3.82834 loss)
-I0510 18:49:25.958884  5307 sgd_solver.cpp:172] Iteration 23000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:50:26.141391  5307 solver.cpp:352] Iteration 23100 (1.66164 iter/s, 60.1815s/100 iter), 44.7/232ep, loss = 3.84205
-I0510 18:50:26.141486  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80804 (* 1 = 3.80804 loss)
-I0510 18:50:26.141495  5307 sgd_solver.cpp:172] Iteration 23100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:51:26.120424  5307 solver.cpp:352] Iteration 23200 (1.66728 iter/s, 59.978s/100 iter), 44.9/232ep, loss = 3.85392
-I0510 18:51:26.120483  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56861 (* 1 = 3.56861 loss)
-I0510 18:51:26.120492  5307 sgd_solver.cpp:172] Iteration 23200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:52:00.375195  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:52:25.731971  5307 solver.cpp:352] Iteration 23300 (1.67756 iter/s, 59.6105s/100 iter), 45/232ep, loss = 3.81557
-I0510 18:52:25.732010  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.45628 (* 1 = 3.45628 loss)
-I0510 18:52:25.732020  5307 sgd_solver.cpp:172] Iteration 23300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:53:26.464812  5307 solver.cpp:352] Iteration 23400 (1.64658 iter/s, 60.7318s/100 iter), 45.2/232ep, loss = 3.80069
-I0510 18:53:26.464896  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2912 (* 1 = 3.2912 loss)
-I0510 18:53:26.464906  5307 sgd_solver.cpp:172] Iteration 23400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:54:27.701195  5307 solver.cpp:352] Iteration 23500 (1.63304 iter/s, 61.2353s/100 iter), 45.4/232ep, loss = 3.89957
-I0510 18:54:27.701269  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27479 (* 1 = 3.27479 loss)
-I0510 18:54:27.701277  5307 sgd_solver.cpp:172] Iteration 23500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:55:29.363590  5307 solver.cpp:352] Iteration 23600 (1.62176 iter/s, 61.6613s/100 iter), 45.6/232ep, loss = 4.05547
-I0510 18:55:29.363911  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.68351 (* 1 = 4.68351 loss)
-I0510 18:55:29.363940  5307 sgd_solver.cpp:172] Iteration 23600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:56:31.339885  5307 solver.cpp:352] Iteration 23700 (1.61355 iter/s, 61.9752s/100 iter), 45.8/232ep, loss = 3.94768
-I0510 18:56:31.339956  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78877 (* 1 = 3.78877 loss)
-I0510 18:56:31.339964  5307 sgd_solver.cpp:172] Iteration 23700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:57:16.840919  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 18:57:32.433218  5307 solver.cpp:352] Iteration 23800 (1.63687 iter/s, 61.0923s/100 iter), 46/232ep, loss = 3.87
-I0510 18:57:32.433284  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.22068 (* 1 = 4.22068 loss)
-I0510 18:57:32.433292  5307 sgd_solver.cpp:172] Iteration 23800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:58:33.108304  5307 solver.cpp:352] Iteration 23900 (1.64815 iter/s, 60.674s/100 iter), 46.2/232ep, loss = 3.5852
-I0510 18:58:33.108393  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06789 (* 1 = 4.06789 loss)
-I0510 18:58:33.108404  5307 sgd_solver.cpp:172] Iteration 23900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 18:59:33.702417  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_24000.caffemodel
-I0510 18:59:33.715880  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_24000.solverstate
-I0510 18:59:33.719976  5307 solver.cpp:635] Iteration 24000, Testing net (#0)
-I0510 19:00:15.762233  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:00:15.999637  5307 solver.cpp:747] class AP 1: 0.484444
-I0510 19:00:15.999975  5307 solver.cpp:747] class AP 2: 0.482623
-I0510 19:00:16.003038  5307 solver.cpp:747] class AP 3: 0.351549
-I0510 19:00:16.006753  5307 solver.cpp:747] class AP 4: 0.350077
-I0510 19:00:16.033462  5307 solver.cpp:747] class AP 5: 0.213984
-I0510 19:00:16.034142  5307 solver.cpp:747] class AP 6: 0.605831
-I0510 19:00:16.040594  5307 solver.cpp:747] class AP 7: 0.574534
-I0510 19:00:16.041268  5307 solver.cpp:747] class AP 8: 0.637335
-I0510 19:00:16.059988  5307 solver.cpp:747] class AP 9: 0.269435
-I0510 19:00:16.060272  5307 solver.cpp:747] class AP 10: 0.375766
-I0510 19:00:16.061775  5307 solver.cpp:747] class AP 11: 0.40548
-I0510 19:00:16.062548  5307 solver.cpp:747] class AP 12: 0.519061
-I0510 19:00:16.062849  5307 solver.cpp:747] class AP 13: 0.527503
-I0510 19:00:16.063004  5307 solver.cpp:747] class AP 14: 0.472097
-I0510 19:00:16.124413  5307 solver.cpp:747] class AP 15: 0.617836
-I0510 19:00:16.132398  5307 solver.cpp:747] class AP 16: 0.211552
-I0510 19:00:16.133635  5307 solver.cpp:747] class AP 17: 0.336798
-I0510 19:00:16.134557  5307 solver.cpp:747] class AP 18: 0.421108
-I0510 19:00:16.135125  5307 solver.cpp:747] class AP 19: 0.594174
-I0510 19:00:16.136035  5307 solver.cpp:747] class AP 20: 0.435553
-I0510 19:00:16.136041  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.444337
-I0510 19:00:16.136257  5307 solver.cpp:283] Tests completed in 103.026s
-I0510 19:00:16.756871  5307 solver.cpp:352] Iteration 24000 (0.970627 iter/s, 103.026s/100 iter), 46.4/232ep, loss = 3.9067
-I0510 19:00:16.756903  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44319 (* 1 = 3.44319 loss)
-I0510 19:00:16.756912  5307 sgd_solver.cpp:172] Iteration 24000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:01:17.363162  5307 solver.cpp:352] Iteration 24100 (1.65002 iter/s, 60.6052s/100 iter), 46.6/232ep, loss = 3.77663
-I0510 19:01:17.363291  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.04249 (* 1 = 4.04249 loss)
-I0510 19:01:17.363312  5307 sgd_solver.cpp:172] Iteration 24100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:02:18.204226  5307 solver.cpp:352] Iteration 24200 (1.64366 iter/s, 60.84s/100 iter), 46.8/232ep, loss = 3.9649
-I0510 19:02:18.204455  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57627 (* 1 = 3.57627 loss)
-I0510 19:02:18.204466  5307 sgd_solver.cpp:172] Iteration 24200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:03:14.237166  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:03:19.448635  5307 solver.cpp:352] Iteration 24300 (1.63283 iter/s, 61.2433s/100 iter), 47/232ep, loss = 3.96085
-I0510 19:03:19.448683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11814 (* 1 = 3.11814 loss)
-I0510 19:03:19.448693  5307 sgd_solver.cpp:172] Iteration 24300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:04:19.763339  5307 solver.cpp:352] Iteration 24400 (1.658 iter/s, 60.3136s/100 iter), 47.2/232ep, loss = 3.78938
-I0510 19:04:19.763430  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58582 (* 1 = 3.58582 loss)
-I0510 19:04:19.763447  5307 sgd_solver.cpp:172] Iteration 24400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:05:20.826309  5307 solver.cpp:352] Iteration 24500 (1.63768 iter/s, 61.0619s/100 iter), 47.4/232ep, loss = 3.86039
-I0510 19:05:20.826555  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19428 (* 1 = 3.19428 loss)
-I0510 19:05:20.826565  5307 sgd_solver.cpp:172] Iteration 24500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:06:21.950335  5307 solver.cpp:352] Iteration 24600 (1.63605 iter/s, 61.1229s/100 iter), 47.6/232ep, loss = 3.78745
-I0510 19:06:21.950456  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.91877 (* 1 = 4.91877 loss)
-I0510 19:06:21.950484  5307 sgd_solver.cpp:172] Iteration 24600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:07:24.160080  5307 solver.cpp:352] Iteration 24700 (1.60749 iter/s, 62.2086s/100 iter), 47.8/232ep, loss = 3.66962
-I0510 19:07:24.160152  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87449 (* 1 = 3.87449 loss)
-I0510 19:07:24.160161  5307 sgd_solver.cpp:172] Iteration 24700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:08:25.133620  5307 solver.cpp:352] Iteration 24800 (1.64009 iter/s, 60.9724s/100 iter), 47.9/232ep, loss = 3.65032
-I0510 19:08:25.133761  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.49542 (* 1 = 3.49542 loss)
-I0510 19:08:25.133775  5307 sgd_solver.cpp:172] Iteration 24800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:08:30.483697  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:09:26.062394  5307 solver.cpp:352] Iteration 24900 (1.64129 iter/s, 60.9277s/100 iter), 48.1/232ep, loss = 3.83275
-I0510 19:09:26.062619  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.22737 (* 1 = 5.22737 loss)
-I0510 19:09:26.062644  5307 sgd_solver.cpp:172] Iteration 24900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:10:27.073468  5307 solver.cpp:352] Iteration 25000 (1.63908 iter/s, 61.01s/100 iter), 48.3/232ep, loss = 4.03657
-I0510 19:10:27.073570  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51471 (* 1 = 3.51471 loss)
-I0510 19:10:27.073578  5307 sgd_solver.cpp:172] Iteration 25000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:11:28.260156  5307 solver.cpp:352] Iteration 25100 (1.63437 iter/s, 61.1856s/100 iter), 48.5/232ep, loss = 3.5904
-I0510 19:11:28.260237  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.638 (* 1 = 3.638 loss)
-I0510 19:11:28.260244  5307 sgd_solver.cpp:172] Iteration 25100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:12:29.748556  5307 solver.cpp:352] Iteration 25200 (1.62635 iter/s, 61.4873s/100 iter), 48.7/232ep, loss = 3.85716
-I0510 19:12:29.748668  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36624 (* 1 = 3.36624 loss)
-I0510 19:12:29.748684  5307 sgd_solver.cpp:172] Iteration 25200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:13:30.301437  5307 solver.cpp:352] Iteration 25300 (1.65148 iter/s, 60.5518s/100 iter), 48.9/232ep, loss = 3.68767
-I0510 19:13:30.301498  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43387 (* 1 = 3.43387 loss)
-I0510 19:13:30.301506  5307 sgd_solver.cpp:172] Iteration 25300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:13:45.276093  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:14:29.971930  5307 solver.cpp:352] Iteration 25400 (1.6759 iter/s, 59.6694s/100 iter), 49.1/232ep, loss = 3.84171
-I0510 19:14:29.972039  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.54642 (* 1 = 4.54642 loss)
-I0510 19:14:29.972059  5307 sgd_solver.cpp:172] Iteration 25400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:15:30.884881  5307 solver.cpp:352] Iteration 25500 (1.64172 iter/s, 60.9119s/100 iter), 49.3/232ep, loss = 4.00768
-I0510 19:15:30.884943  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93366 (* 1 = 3.93366 loss)
-I0510 19:15:30.884948  5307 sgd_solver.cpp:172] Iteration 25500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:16:30.960016  5307 solver.cpp:352] Iteration 25600 (1.66461 iter/s, 60.0741s/100 iter), 49.5/232ep, loss = 3.89147
-I0510 19:16:30.960086  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27457 (* 1 = 3.27457 loss)
-I0510 19:16:30.960094  5307 sgd_solver.cpp:172] Iteration 25600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:17:31.220655  5307 solver.cpp:352] Iteration 25700 (1.65949 iter/s, 60.2596s/100 iter), 49.7/232ep, loss = 3.77153
-I0510 19:17:31.222297  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89295 (* 1 = 3.89295 loss)
-I0510 19:17:31.222306  5307 sgd_solver.cpp:172] Iteration 25700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:18:31.005316  5307 solver.cpp:352] Iteration 25800 (1.6727 iter/s, 59.7836s/100 iter), 49.9/232ep, loss = 3.86166
-I0510 19:18:31.005399  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.19522 (* 1 = 4.19522 loss)
-I0510 19:18:31.005409  5307 sgd_solver.cpp:172] Iteration 25800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:18:57.666621  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:19:31.365808  5307 solver.cpp:352] Iteration 25900 (1.65674 iter/s, 60.3594s/100 iter), 50.1/232ep, loss = 3.97279
-I0510 19:19:31.365890  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03542 (* 1 = 4.03542 loss)
-I0510 19:19:31.365897  5307 sgd_solver.cpp:172] Iteration 25900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:20:31.104477  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_26000.caffemodel
-I0510 19:20:31.123970  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_26000.solverstate
-I0510 19:20:31.131429  5307 solver.cpp:635] Iteration 26000, Testing net (#0)
-I0510 19:21:12.665139  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:21:12.910117  5307 solver.cpp:747] class AP 1: 0.527658
-I0510 19:21:12.910953  5307 solver.cpp:747] class AP 2: 0.58519
-I0510 19:21:12.918699  5307 solver.cpp:747] class AP 3: 0.408892
-I0510 19:21:12.925354  5307 solver.cpp:747] class AP 4: 0.323238
-I0510 19:21:12.933722  5307 solver.cpp:747] class AP 5: 0.196721
-I0510 19:21:12.934037  5307 solver.cpp:747] class AP 6: 0.601376
-I0510 19:21:12.953480  5307 solver.cpp:747] class AP 7: 0.617601
-I0510 19:21:12.954058  5307 solver.cpp:747] class AP 8: 0.655444
-I0510 19:21:12.971992  5307 solver.cpp:747] class AP 9: 0.291683
-I0510 19:21:12.972307  5307 solver.cpp:747] class AP 10: 0.440488
-I0510 19:21:12.972625  5307 solver.cpp:747] class AP 11: 0.432128
-I0510 19:21:12.973682  5307 solver.cpp:747] class AP 12: 0.558183
-I0510 19:21:12.973996  5307 solver.cpp:747] class AP 13: 0.66504
-I0510 19:21:12.974239  5307 solver.cpp:747] class AP 14: 0.63709
-I0510 19:21:13.041898  5307 solver.cpp:747] class AP 15: 0.59983
-I0510 19:21:13.044495  5307 solver.cpp:747] class AP 16: 0.20258
-I0510 19:21:13.047165  5307 solver.cpp:747] class AP 17: 0.391476
-I0510 19:21:13.048035  5307 solver.cpp:747] class AP 18: 0.391003
-I0510 19:21:13.048532  5307 solver.cpp:747] class AP 19: 0.637381
-I0510 19:21:13.049194  5307 solver.cpp:747] class AP 20: 0.471418
-I0510 19:21:13.049202  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.481721
-I0510 19:21:13.049327  5307 solver.cpp:283] Tests completed in 101.682s
-I0510 19:21:13.606369  5307 solver.cpp:352] Iteration 26000 (0.983461 iter/s, 101.682s/100 iter), 50.3/232ep, loss = 3.93858
-I0510 19:21:13.606431  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02108 (* 1 = 4.02108 loss)
-I0510 19:21:13.606443  5307 sgd_solver.cpp:172] Iteration 26000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:22:16.320257  5307 solver.cpp:352] Iteration 26100 (1.59457 iter/s, 62.7127s/100 iter), 50.5/232ep, loss = 3.82841
-I0510 19:22:16.320799  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68787 (* 1 = 3.68787 loss)
-I0510 19:22:16.320818  5307 sgd_solver.cpp:172] Iteration 26100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:23:24.497467  5307 solver.cpp:352] Iteration 26200 (1.46679 iter/s, 68.176s/100 iter), 50.7/232ep, loss = 3.76185
-I0510 19:23:24.497622  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67768 (* 1 = 3.67768 loss)
-I0510 19:23:24.497642  5307 sgd_solver.cpp:172] Iteration 26200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:24:25.847491  5307 solver.cpp:352] Iteration 26300 (1.63002 iter/s, 61.3489s/100 iter), 50.8/232ep, loss = 3.94741
-I0510 19:24:25.847573  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.27126 (* 1 = 4.27126 loss)
-I0510 19:24:25.847581  5307 sgd_solver.cpp:172] Iteration 26300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:25:02.195729  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:25:25.784054  5307 solver.cpp:352] Iteration 26400 (1.66846 iter/s, 59.9355s/100 iter), 51/232ep, loss = 3.76409
-I0510 19:25:25.784085  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.58813 (* 1 = 4.58813 loss)
-I0510 19:25:25.784093  5307 sgd_solver.cpp:172] Iteration 26400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:26:26.028339  5307 solver.cpp:352] Iteration 26500 (1.65994 iter/s, 60.2432s/100 iter), 51.2/232ep, loss = 3.84718
-I0510 19:26:26.028415  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.04022 (* 1 = 4.04022 loss)
-I0510 19:26:26.028424  5307 sgd_solver.cpp:172] Iteration 26500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:27:27.105324  5307 solver.cpp:352] Iteration 26600 (1.63731 iter/s, 61.0759s/100 iter), 51.4/232ep, loss = 3.73108
-I0510 19:27:27.105420  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22452 (* 1 = 3.22452 loss)
-I0510 19:27:27.105428  5307 sgd_solver.cpp:172] Iteration 26600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:28:27.265174  5307 solver.cpp:352] Iteration 26700 (1.66227 iter/s, 60.1588s/100 iter), 51.6/232ep, loss = 3.73865
-I0510 19:28:27.265241  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65277 (* 1 = 3.65277 loss)
-I0510 19:28:27.265247  5307 sgd_solver.cpp:172] Iteration 26700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:29:27.365866  5307 solver.cpp:352] Iteration 26800 (1.6639 iter/s, 60.0996s/100 iter), 51.8/232ep, loss = 3.82671
-I0510 19:29:27.365945  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.49587 (* 1 = 4.49587 loss)
-I0510 19:29:27.365955  5307 sgd_solver.cpp:172] Iteration 26800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:30:13.481175  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:30:27.466990  5307 solver.cpp:352] Iteration 26900 (1.66389 iter/s, 60.1s/100 iter), 52/232ep, loss = 3.72676
-I0510 19:30:27.467074  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.70798 (* 1 = 3.70798 loss)
-I0510 19:30:27.467095  5307 sgd_solver.cpp:172] Iteration 26900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:31:27.867920  5307 solver.cpp:352] Iteration 27000 (1.65563 iter/s, 60.3998s/100 iter), 52.2/232ep, loss = 3.60723
-I0510 19:31:27.868335  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30788 (* 1 = 3.30788 loss)
-I0510 19:31:27.868350  5307 sgd_solver.cpp:172] Iteration 27000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:32:27.997393  5307 solver.cpp:352] Iteration 27100 (1.66311 iter/s, 60.1284s/100 iter), 52.4/232ep, loss = 3.60799
-I0510 19:32:27.998000  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05221 (* 1 = 3.05221 loss)
-I0510 19:32:27.998009  5307 sgd_solver.cpp:172] Iteration 27100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:33:28.887500  5307 solver.cpp:352] Iteration 27200 (1.64233 iter/s, 60.889s/100 iter), 52.6/232ep, loss = 3.85192
-I0510 19:33:28.887666  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.21449 (* 1 = 4.21449 loss)
-I0510 19:33:28.887676  5307 sgd_solver.cpp:172] Iteration 27200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:34:29.287021  5307 solver.cpp:352] Iteration 27300 (1.65567 iter/s, 60.3984s/100 iter), 52.8/232ep, loss = 3.80451
-I0510 19:34:29.290815  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61041 (* 1 = 3.61041 loss)
-I0510 19:34:29.290830  5307 sgd_solver.cpp:172] Iteration 27300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:35:27.106932  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:35:30.255291  5307 solver.cpp:352] Iteration 27400 (1.64023 iter/s, 60.9672s/100 iter), 53/232ep, loss = 3.9971
-I0510 19:35:30.255317  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47735 (* 1 = 3.47735 loss)
-I0510 19:35:30.255324  5307 sgd_solver.cpp:172] Iteration 27400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:36:30.755306  5307 solver.cpp:352] Iteration 27500 (1.65292 iter/s, 60.4989s/100 iter), 53.2/232ep, loss = 3.76978
-I0510 19:36:30.755390  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83909 (* 1 = 3.83909 loss)
-I0510 19:36:30.755400  5307 sgd_solver.cpp:172] Iteration 27500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:37:31.814741  5307 solver.cpp:352] Iteration 27600 (1.63778 iter/s, 61.0584s/100 iter), 53.4/232ep, loss = 3.97396
-I0510 19:37:31.814800  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91227 (* 1 = 3.91227 loss)
-I0510 19:37:31.814810  5307 sgd_solver.cpp:172] Iteration 27600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:38:32.215876  5307 solver.cpp:352] Iteration 27700 (1.65563 iter/s, 60.4001s/100 iter), 53.6/232ep, loss = 3.80746
-I0510 19:38:32.215960  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0961 (* 1 = 4.0961 loss)
-I0510 19:38:32.215975  5307 sgd_solver.cpp:172] Iteration 27700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:39:32.541234  5307 solver.cpp:352] Iteration 27800 (1.65771 iter/s, 60.3243s/100 iter), 53.7/232ep, loss = 3.68896
-I0510 19:39:32.541684  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.45826 (* 1 = 3.45826 loss)
-I0510 19:39:32.541694  5307 sgd_solver.cpp:172] Iteration 27800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:40:32.999799  5307 solver.cpp:352] Iteration 27900 (1.65406 iter/s, 60.4575s/100 iter), 53.9/232ep, loss = 3.7588
-I0510 19:40:33.000018  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.83248 (* 1 = 4.83248 loss)
-I0510 19:40:33.000042  5307 sgd_solver.cpp:172] Iteration 27900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:40:39.858031  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:41:32.854823  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_28000.caffemodel
-I0510 19:41:32.869741  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_28000.solverstate
-I0510 19:41:32.875227  5307 solver.cpp:635] Iteration 28000, Testing net (#0)
-I0510 19:42:13.878679  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:42:14.101833  5307 solver.cpp:747] class AP 1: 0.447821
-I0510 19:42:14.102130  5307 solver.cpp:747] class AP 2: 0.514945
-I0510 19:42:14.110472  5307 solver.cpp:747] class AP 3: 0.332307
-I0510 19:42:14.113862  5307 solver.cpp:747] class AP 4: 0.276696
-I0510 19:42:14.147543  5307 solver.cpp:747] class AP 5: 0.218325
-I0510 19:42:14.147663  5307 solver.cpp:747] class AP 6: 0.566076
-I0510 19:42:14.150702  5307 solver.cpp:747] class AP 7: 0.520006
-I0510 19:42:14.151751  5307 solver.cpp:747] class AP 8: 0.57054
-I0510 19:42:14.180486  5307 solver.cpp:747] class AP 9: 0.224394
-I0510 19:42:14.181216  5307 solver.cpp:747] class AP 10: 0.335236
-I0510 19:42:14.183318  5307 solver.cpp:747] class AP 11: 0.356538
-I0510 19:42:14.184463  5307 solver.cpp:747] class AP 12: 0.474195
-I0510 19:42:14.184739  5307 solver.cpp:747] class AP 13: 0.507128
-I0510 19:42:14.184957  5307 solver.cpp:747] class AP 14: 0.516949
-I0510 19:42:14.219790  5307 solver.cpp:747] class AP 15: 0.595535
-I0510 19:42:14.231107  5307 solver.cpp:747] class AP 16: 0.219246
-I0510 19:42:14.232429  5307 solver.cpp:747] class AP 17: 0.385486
-I0510 19:42:14.233534  5307 solver.cpp:747] class AP 18: 0.332484
-I0510 19:42:14.233866  5307 solver.cpp:747] class AP 19: 0.542427
-I0510 19:42:14.234956  5307 solver.cpp:747] class AP 20: 0.421216
-I0510 19:42:14.234963  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.417878
-I0510 19:42:14.235227  5307 solver.cpp:283] Tests completed in 101.234s
-I0510 19:42:14.854811  5307 solver.cpp:352] Iteration 28000 (0.987813 iter/s, 101.234s/100 iter), 54.1/232ep, loss = 3.52533
-I0510 19:42:14.854843  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06378 (* 1 = 4.06378 loss)
-I0510 19:42:14.854853  5307 sgd_solver.cpp:172] Iteration 28000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:43:15.252923  5307 solver.cpp:352] Iteration 28100 (1.65571 iter/s, 60.397s/100 iter), 54.3/232ep, loss = 3.81855
-I0510 19:43:15.253015  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67796 (* 1 = 3.67796 loss)
-I0510 19:43:15.253027  5307 sgd_solver.cpp:172] Iteration 28100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:44:15.360148  5307 solver.cpp:352] Iteration 28200 (1.66372 iter/s, 60.1062s/100 iter), 54.5/232ep, loss = 3.75696
-I0510 19:44:15.360235  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11185 (* 1 = 4.11185 loss)
-I0510 19:44:15.360249  5307 sgd_solver.cpp:172] Iteration 28200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:45:16.344228  5307 solver.cpp:352] Iteration 28300 (1.6398 iter/s, 60.983s/100 iter), 54.7/232ep, loss = 3.74448
-I0510 19:45:16.344310  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.81193 (* 1 = 3.81193 loss)
-I0510 19:45:16.344317  5307 sgd_solver.cpp:172] Iteration 28300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:46:16.309695  5307 solver.cpp:352] Iteration 28400 (1.66766 iter/s, 59.9644s/100 iter), 54.9/232ep, loss = 3.7683
-I0510 19:46:16.309792  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.79755 (* 1 = 3.79755 loss)
-I0510 19:46:16.309808  5307 sgd_solver.cpp:172] Iteration 28400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:46:33.785228  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:47:16.645256  5307 solver.cpp:352] Iteration 28500 (1.65743 iter/s, 60.3345s/100 iter), 55.1/232ep, loss = 3.87838
-I0510 19:47:16.645334  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.06779 (* 1 = 3.06779 loss)
-I0510 19:47:16.645344  5307 sgd_solver.cpp:172] Iteration 28500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:48:16.931111  5307 solver.cpp:352] Iteration 28600 (1.65879 iter/s, 60.2848s/100 iter), 55.3/232ep, loss = 3.7845
-I0510 19:48:16.931172  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.90429 (* 1 = 3.90429 loss)
-I0510 19:48:16.931180  5307 sgd_solver.cpp:172] Iteration 28600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:49:17.907735  5307 solver.cpp:352] Iteration 28700 (1.64 iter/s, 60.9755s/100 iter), 55.5/232ep, loss = 3.6071
-I0510 19:49:17.907867  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59682 (* 1 = 3.59682 loss)
-I0510 19:49:17.907881  5307 sgd_solver.cpp:172] Iteration 28700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:50:18.755187  5307 solver.cpp:352] Iteration 28800 (1.64348 iter/s, 60.8463s/100 iter), 55.7/232ep, loss = 3.75675
-I0510 19:50:18.755365  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5903 (* 1 = 3.5903 loss)
-I0510 19:50:18.755391  5307 sgd_solver.cpp:172] Iteration 28800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:51:19.042055  5307 solver.cpp:352] Iteration 28900 (1.65877 iter/s, 60.2858s/100 iter), 55.9/232ep, loss = 3.71257
-I0510 19:51:19.042114  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.48781 (* 1 = 4.48781 loss)
-I0510 19:51:19.042121  5307 sgd_solver.cpp:172] Iteration 28900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:51:47.191911  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:52:19.624878  5307 solver.cpp:352] Iteration 29000 (1.65066 iter/s, 60.5817s/100 iter), 56.1/232ep, loss = 3.67674
-I0510 19:52:19.625249  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87256 (* 1 = 3.87256 loss)
-I0510 19:52:19.625259  5307 sgd_solver.cpp:172] Iteration 29000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:53:20.396816  5307 solver.cpp:352] Iteration 29100 (1.64553 iter/s, 60.7708s/100 iter), 56.3/232ep, loss = 3.99434
-I0510 19:53:20.396867  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.8691 (* 1 = 3.8691 loss)
-I0510 19:53:20.396876  5307 sgd_solver.cpp:172] Iteration 29100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:54:20.580611  5307 solver.cpp:352] Iteration 29200 (1.66161 iter/s, 60.1827s/100 iter), 56.5/232ep, loss = 3.78493
-I0510 19:54:20.580708  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06183 (* 1 = 4.06183 loss)
-I0510 19:54:20.580732  5307 sgd_solver.cpp:172] Iteration 29200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:55:20.472167  5307 solver.cpp:352] Iteration 29300 (1.66971 iter/s, 59.8905s/100 iter), 56.6/232ep, loss = 3.62764
-I0510 19:55:20.472227  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31053 (* 1 = 3.31053 loss)
-I0510 19:55:20.472235  5307 sgd_solver.cpp:172] Iteration 29300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:56:21.429445  5307 solver.cpp:352] Iteration 29400 (1.64052 iter/s, 60.9562s/100 iter), 56.8/232ep, loss = 3.77345
-I0510 19:56:21.429524  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61489 (* 1 = 3.61489 loss)
-I0510 19:56:21.429533  5307 sgd_solver.cpp:172] Iteration 29400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:56:59.462847  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 19:57:22.076934  5307 solver.cpp:352] Iteration 29500 (1.6489 iter/s, 60.6464s/100 iter), 57/232ep, loss = 3.6652
-I0510 19:57:22.076967  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40196 (* 1 = 3.40196 loss)
-I0510 19:57:22.076977  5307 sgd_solver.cpp:172] Iteration 29500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:58:22.610980  5307 solver.cpp:352] Iteration 29600 (1.65199 iter/s, 60.533s/100 iter), 57.2/232ep, loss = 3.70211
-I0510 19:58:22.611089  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43717 (* 1 = 3.43717 loss)
-I0510 19:58:22.611099  5307 sgd_solver.cpp:172] Iteration 29600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 19:59:22.832132  5307 solver.cpp:352] Iteration 29700 (1.66058 iter/s, 60.2201s/100 iter), 57.4/232ep, loss = 3.74542
-I0510 19:59:22.835464  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.23196 (* 1 = 4.23196 loss)
-I0510 19:59:22.835556  5307 sgd_solver.cpp:172] Iteration 29700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:00:23.247373  5307 solver.cpp:352] Iteration 29800 (1.65524 iter/s, 60.4142s/100 iter), 57.6/232ep, loss = 3.74278
-I0510 20:00:23.247465  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83845 (* 1 = 3.83845 loss)
-I0510 20:00:23.247474  5307 sgd_solver.cpp:172] Iteration 29800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:01:24.044986  5307 solver.cpp:352] Iteration 29900 (1.64483 iter/s, 60.7965s/100 iter), 57.8/232ep, loss = 3.6145
-I0510 20:01:24.045045  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74996 (* 1 = 2.74996 loss)
-I0510 20:01:24.045053  5307 sgd_solver.cpp:172] Iteration 29900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:02:12.929261  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:02:23.974081  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_30000.caffemodel
-I0510 20:02:23.993046  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_30000.solverstate
-I0510 20:02:23.999919  5307 solver.cpp:635] Iteration 30000, Testing net (#0)
-I0510 20:03:05.099125  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:03:05.335094  5307 solver.cpp:747] class AP 1: 0.49288
-I0510 20:03:05.335618  5307 solver.cpp:747] class AP 2: 0.572298
-I0510 20:03:05.351456  5307 solver.cpp:747] class AP 3: 0.411125
-I0510 20:03:05.354663  5307 solver.cpp:747] class AP 4: 0.283815
-I0510 20:03:05.369340  5307 solver.cpp:747] class AP 5: 0.159748
-I0510 20:03:05.369539  5307 solver.cpp:747] class AP 6: 0.57257
-I0510 20:03:05.377823  5307 solver.cpp:747] class AP 7: 0.55566
-I0510 20:03:05.378362  5307 solver.cpp:747] class AP 8: 0.604174
-I0510 20:03:05.393599  5307 solver.cpp:747] class AP 9: 0.217753
-I0510 20:03:05.394135  5307 solver.cpp:747] class AP 10: 0.400134
-I0510 20:03:05.394649  5307 solver.cpp:747] class AP 11: 0.429815
-I0510 20:03:05.396200  5307 solver.cpp:747] class AP 12: 0.544543
-I0510 20:03:05.396452  5307 solver.cpp:747] class AP 13: 0.672034
-I0510 20:03:05.396749  5307 solver.cpp:747] class AP 14: 0.587423
-I0510 20:03:05.454797  5307 solver.cpp:747] class AP 15: 0.603451
-I0510 20:03:05.464190  5307 solver.cpp:747] class AP 16: 0.160115
-I0510 20:03:05.465623  5307 solver.cpp:747] class AP 17: 0.407475
-I0510 20:03:05.465979  5307 solver.cpp:747] class AP 18: 0.364085
-I0510 20:03:05.466434  5307 solver.cpp:747] class AP 19: 0.563487
-I0510 20:03:05.467962  5307 solver.cpp:747] class AP 20: 0.370664
-I0510 20:03:05.467970  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.448662
-I0510 20:03:05.468106  5307 solver.cpp:283] Tests completed in 101.421s
-I0510 20:03:06.032670  5307 solver.cpp:352] Iteration 30000 (0.985986 iter/s, 101.421s/100 iter), 58/232ep, loss = 3.82731
-I0510 20:03:06.032719  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5366 (* 1 = 3.5366 loss)
-I0510 20:03:06.032733  5307 sgd_solver.cpp:172] Iteration 30000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:04:06.726922  5307 solver.cpp:352] Iteration 30100 (1.64763 iter/s, 60.6932s/100 iter), 58.2/232ep, loss = 3.74437
-I0510 20:04:06.726979  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78703 (* 1 = 3.78703 loss)
-I0510 20:04:06.726985  5307 sgd_solver.cpp:172] Iteration 30100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:05:07.274248  5307 solver.cpp:352] Iteration 30200 (1.65163 iter/s, 60.5462s/100 iter), 58.4/232ep, loss = 3.47742
-I0510 20:05:07.274332  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05092 (* 1 = 4.05092 loss)
-I0510 20:05:07.274341  5307 sgd_solver.cpp:172] Iteration 30200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:06:08.827862  5307 solver.cpp:352] Iteration 30300 (1.62463 iter/s, 61.5525s/100 iter), 58.6/232ep, loss = 3.77468
-I0510 20:06:08.827973  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50115 (* 1 = 3.50115 loss)
-I0510 20:06:08.827985  5307 sgd_solver.cpp:172] Iteration 30300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:07:10.170852  5307 solver.cpp:352] Iteration 30400 (1.63021 iter/s, 61.3419s/100 iter), 58.8/232ep, loss = 3.64959
-I0510 20:07:10.170904  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96388 (* 1 = 2.96388 loss)
-I0510 20:07:10.170913  5307 sgd_solver.cpp:172] Iteration 30400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:08:10.422246  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:08:12.163167  5307 solver.cpp:352] Iteration 30500 (1.61313 iter/s, 61.9912s/100 iter), 59/232ep, loss = 3.95137
-I0510 20:08:12.163193  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.71779 (* 1 = 4.71779 loss)
-I0510 20:08:12.163203  5307 sgd_solver.cpp:172] Iteration 30500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:09:13.321945  5307 solver.cpp:352] Iteration 30600 (1.63512 iter/s, 61.1576s/100 iter), 59.2/232ep, loss = 3.72914
-I0510 20:09:13.322137  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.10117 (* 1 = 4.10117 loss)
-I0510 20:09:13.322167  5307 sgd_solver.cpp:172] Iteration 30600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:10:14.789160  5307 solver.cpp:352] Iteration 30700 (1.62691 iter/s, 61.4662s/100 iter), 59.4/232ep, loss = 3.80969
-I0510 20:10:14.789242  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.44581 (* 1 = 4.44581 loss)
-I0510 20:10:14.789257  5307 sgd_solver.cpp:172] Iteration 30700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:11:16.550231  5307 solver.cpp:352] Iteration 30800 (1.61917 iter/s, 61.76s/100 iter), 59.5/232ep, loss = 3.63191
-I0510 20:11:16.551460  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.36055 (* 1 = 4.36055 loss)
-I0510 20:11:16.551486  5307 sgd_solver.cpp:172] Iteration 30800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:12:16.602501  5307 solver.cpp:352] Iteration 30900 (1.66524 iter/s, 60.0513s/100 iter), 59.7/232ep, loss = 3.7639
-I0510 20:12:16.602596  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01655 (* 1 = 3.01655 loss)
-I0510 20:12:16.602603  5307 sgd_solver.cpp:172] Iteration 30900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:13:16.543359  5307 solver.cpp:352] Iteration 31000 (1.66834 iter/s, 59.9398s/100 iter), 59.9/232ep, loss = 3.63295
-I0510 20:13:16.543452  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37379 (* 1 = 3.37379 loss)
-I0510 20:13:16.543471  5307 sgd_solver.cpp:172] Iteration 31000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:13:25.537050  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:14:16.204613  5307 solver.cpp:352] Iteration 31100 (1.67616 iter/s, 59.6602s/100 iter), 60.1/232ep, loss = 3.72176
-I0510 20:14:16.204711  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31073 (* 1 = 3.31073 loss)
-I0510 20:14:16.204720  5307 sgd_solver.cpp:172] Iteration 31100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:15:16.277683  5307 solver.cpp:352] Iteration 31200 (1.66467 iter/s, 60.072s/100 iter), 60.3/232ep, loss = 3.58337
-I0510 20:15:16.278057  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95243 (* 1 = 3.95243 loss)
-I0510 20:15:16.278071  5307 sgd_solver.cpp:172] Iteration 31200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:16:17.477808  5307 solver.cpp:352] Iteration 31300 (1.63401 iter/s, 61.1991s/100 iter), 60.5/232ep, loss = 3.7103
-I0510 20:16:17.477916  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.55529 (* 1 = 2.55529 loss)
-I0510 20:16:17.477927  5307 sgd_solver.cpp:172] Iteration 31300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:17:18.232285  5307 solver.cpp:352] Iteration 31400 (1.646 iter/s, 60.7534s/100 iter), 60.7/232ep, loss = 3.75925
-I0510 20:17:18.232393  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.36327 (* 1 = 4.36327 loss)
-I0510 20:17:18.232416  5307 sgd_solver.cpp:172] Iteration 31400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:18:19.069918  5307 solver.cpp:352] Iteration 31500 (1.64375 iter/s, 60.8366s/100 iter), 60.9/232ep, loss = 3.53607
-I0510 20:18:19.069981  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8967 (* 1 = 2.8967 loss)
-I0510 20:18:19.069990  5307 sgd_solver.cpp:172] Iteration 31500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:18:39.256943  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:19:19.638444  5307 solver.cpp:352] Iteration 31600 (1.65105 iter/s, 60.5675s/100 iter), 61.1/232ep, loss = 3.67042
-I0510 20:19:19.638500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.80708 (* 1 = 2.80708 loss)
-I0510 20:19:19.638509  5307 sgd_solver.cpp:172] Iteration 31600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:20:21.356631  5307 solver.cpp:352] Iteration 31700 (1.6203 iter/s, 61.7171s/100 iter), 61.3/232ep, loss = 3.81229
-I0510 20:20:21.357816  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15715 (* 1 = 4.15715 loss)
-I0510 20:20:21.357830  5307 sgd_solver.cpp:172] Iteration 31700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:21:22.677747  5307 solver.cpp:352] Iteration 31800 (1.63079 iter/s, 61.3201s/100 iter), 61.5/232ep, loss = 3.76929
-I0510 20:21:22.677806  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08326 (* 1 = 3.08326 loss)
-I0510 20:21:22.677814  5307 sgd_solver.cpp:172] Iteration 31800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:22:24.012138  5307 solver.cpp:352] Iteration 31900 (1.63043 iter/s, 61.3333s/100 iter), 61.7/232ep, loss = 3.64278
-I0510 20:22:24.012224  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.62073 (* 1 = 3.62073 loss)
-I0510 20:22:24.012233  5307 sgd_solver.cpp:172] Iteration 31900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:23:25.565407  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_32000.caffemodel
-I0510 20:23:25.587774  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_32000.solverstate
-I0510 20:23:25.595491  5307 solver.cpp:635] Iteration 32000, Testing net (#0)
-I0510 20:23:31.821794  5352 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0510 20:24:06.804874  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:24:07.037050  5307 solver.cpp:747] class AP 1: 0.526383
-I0510 20:24:07.037438  5307 solver.cpp:747] class AP 2: 0.635977
-I0510 20:24:07.048976  5307 solver.cpp:747] class AP 3: 0.399524
-I0510 20:24:07.051331  5307 solver.cpp:747] class AP 4: 0.347869
-I0510 20:24:07.067064  5307 solver.cpp:747] class AP 5: 0.256745
-I0510 20:24:07.067379  5307 solver.cpp:747] class AP 6: 0.649957
-I0510 20:24:07.072592  5307 solver.cpp:747] class AP 7: 0.617347
-I0510 20:24:07.073444  5307 solver.cpp:747] class AP 8: 0.690625
-I0510 20:24:07.097751  5307 solver.cpp:747] class AP 9: 0.335321
-I0510 20:24:07.098278  5307 solver.cpp:747] class AP 10: 0.517511
-I0510 20:24:07.099396  5307 solver.cpp:747] class AP 11: 0.472751
-I0510 20:24:07.100687  5307 solver.cpp:747] class AP 12: 0.596647
-I0510 20:24:07.100947  5307 solver.cpp:747] class AP 13: 0.676235
-I0510 20:24:07.101212  5307 solver.cpp:747] class AP 14: 0.649562
-I0510 20:24:07.157392  5307 solver.cpp:747] class AP 15: 0.64047
-I0510 20:24:07.162349  5307 solver.cpp:747] class AP 16: 0.223401
-I0510 20:24:07.165511  5307 solver.cpp:747] class AP 17: 0.496675
-I0510 20:24:07.166776  5307 solver.cpp:747] class AP 18: 0.510274
-I0510 20:24:07.167563  5307 solver.cpp:747] class AP 19: 0.621777
-I0510 20:24:07.168772  5307 solver.cpp:747] class AP 20: 0.474429
-I0510 20:24:07.168787  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.516974
-I0510 20:24:07.169006  5307 solver.cpp:283] Tests completed in 103.155s
-I0510 20:24:07.804672  5307 solver.cpp:352] Iteration 32000 (0.969414 iter/s, 103.155s/100 iter), 61.9/232ep, loss = 3.62977
-I0510 20:24:07.804797  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.35768 (* 1 = 3.35768 loss)
-I0510 20:24:07.804810  5307 sgd_solver.cpp:172] Iteration 32000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:24:38.469461  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:25:10.240434  5307 solver.cpp:352] Iteration 32100 (1.60168 iter/s, 62.4346s/100 iter), 62.1/232ep, loss = 3.66677
-I0510 20:25:10.240602  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87714 (* 1 = 3.87714 loss)
-I0510 20:25:10.240623  5307 sgd_solver.cpp:172] Iteration 32100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:26:11.415913  5307 solver.cpp:352] Iteration 32200 (1.63467 iter/s, 61.1744s/100 iter), 62.3/232ep, loss = 3.86129
-I0510 20:26:11.416028  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.7976 (* 1 = 3.7976 loss)
-I0510 20:26:11.416046  5307 sgd_solver.cpp:172] Iteration 32200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:27:13.032047  5307 solver.cpp:352] Iteration 32300 (1.62298 iter/s, 61.6151s/100 iter), 62.4/232ep, loss = 3.80358
-I0510 20:27:13.032133  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5296 (* 1 = 3.5296 loss)
-I0510 20:27:13.032150  5307 sgd_solver.cpp:172] Iteration 32300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:28:13.966925  5307 solver.cpp:352] Iteration 32400 (1.64113 iter/s, 60.9338s/100 iter), 62.6/232ep, loss = 3.76398
-I0510 20:28:13.967087  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.43466 (* 1 = 4.43466 loss)
-I0510 20:28:13.967106  5307 sgd_solver.cpp:172] Iteration 32400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:29:14.266544  5307 solver.cpp:352] Iteration 32500 (1.65841 iter/s, 60.2986s/100 iter), 62.8/232ep, loss = 3.84687
-I0510 20:29:14.267472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.96284 (* 1 = 3.96284 loss)
-I0510 20:29:14.267482  5307 sgd_solver.cpp:172] Iteration 32500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:29:55.900570  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:30:19.120484  5307 solver.cpp:352] Iteration 32600 (1.54195 iter/s, 64.8528s/100 iter), 63/232ep, loss = 3.61782
-I0510 20:30:19.120555  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3348 (* 1 = 3.3348 loss)
-I0510 20:30:19.120576  5307 sgd_solver.cpp:172] Iteration 32600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:31:27.233445  5307 solver.cpp:352] Iteration 32700 (1.46818 iter/s, 68.1118s/100 iter), 63.2/232ep, loss = 3.76131
-I0510 20:31:27.233536  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.97666 (* 1 = 3.97666 loss)
-I0510 20:31:27.233542  5307 sgd_solver.cpp:172] Iteration 32700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:32:27.301883  5307 solver.cpp:352] Iteration 32800 (1.6648 iter/s, 60.0674s/100 iter), 63.4/232ep, loss = 3.6275
-I0510 20:32:27.302006  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.93594 (* 1 = 2.93594 loss)
-I0510 20:32:27.302021  5307 sgd_solver.cpp:172] Iteration 32800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:33:28.381314  5307 solver.cpp:352] Iteration 32900 (1.63724 iter/s, 61.0784s/100 iter), 63.6/232ep, loss = 3.75429
-I0510 20:33:28.382957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.38282 (* 1 = 4.38282 loss)
-I0510 20:33:28.382968  5307 sgd_solver.cpp:172] Iteration 32900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:34:28.517973  5307 solver.cpp:352] Iteration 33000 (1.66291 iter/s, 60.1356s/100 iter), 63.8/232ep, loss = 3.79048
-I0510 20:34:28.518059  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.23225 (* 1 = 4.23225 loss)
-I0510 20:34:28.518067  5307 sgd_solver.cpp:172] Iteration 33000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:35:18.557407  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:35:28.267971  5307 solver.cpp:352] Iteration 33100 (1.67367 iter/s, 59.749s/100 iter), 64/232ep, loss = 3.6645
-I0510 20:35:28.267993  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03611 (* 1 = 3.03611 loss)
-I0510 20:35:28.267999  5307 sgd_solver.cpp:172] Iteration 33100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:36:29.240681  5307 solver.cpp:352] Iteration 33200 (1.64011 iter/s, 60.9717s/100 iter), 64.2/232ep, loss = 3.70925
-I0510 20:36:29.240780  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69101 (* 1 = 3.69101 loss)
-I0510 20:36:29.240792  5307 sgd_solver.cpp:172] Iteration 33200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:37:29.509500  5307 solver.cpp:352] Iteration 33300 (1.65926 iter/s, 60.2678s/100 iter), 64.4/232ep, loss = 3.64561
-I0510 20:37:29.512552  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32793 (* 1 = 3.32793 loss)
-I0510 20:37:29.512594  5307 sgd_solver.cpp:172] Iteration 33300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:38:30.920509  5307 solver.cpp:352] Iteration 33400 (1.6284 iter/s, 61.41s/100 iter), 64.6/232ep, loss = 3.73497
-I0510 20:38:30.920578  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.27622 (* 1 = 4.27622 loss)
-I0510 20:38:30.920588  5307 sgd_solver.cpp:172] Iteration 33400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:39:32.842433  5307 solver.cpp:352] Iteration 33500 (1.61496 iter/s, 61.9209s/100 iter), 64.8/232ep, loss = 3.82568
-I0510 20:39:32.842490  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.13622 (* 1 = 4.13622 loss)
-I0510 20:39:32.842499  5307 sgd_solver.cpp:172] Iteration 33500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:40:33.841985  5307 solver.cpp:352] Iteration 33600 (1.63938 iter/s, 60.9985s/100 iter), 65/232ep, loss = 3.69743
-I0510 20:40:33.842221  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.75096 (* 1 = 3.75096 loss)
-I0510 20:40:33.842247  5307 sgd_solver.cpp:172] Iteration 33600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:40:34.609417  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:41:35.916772  5307 solver.cpp:352] Iteration 33700 (1.61099 iter/s, 62.0737s/100 iter), 65.2/232ep, loss = 3.8023
-I0510 20:41:35.916874  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.88991 (* 1 = 3.88991 loss)
-I0510 20:41:35.916884  5307 sgd_solver.cpp:172] Iteration 33700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:42:36.419731  5307 solver.cpp:352] Iteration 33800 (1.65284 iter/s, 60.5019s/100 iter), 65.3/232ep, loss = 3.567
-I0510 20:42:36.419812  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4897 (* 1 = 3.4897 loss)
-I0510 20:42:36.419819  5307 sgd_solver.cpp:172] Iteration 33800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:43:36.926913  5307 solver.cpp:352] Iteration 33900 (1.65272 iter/s, 60.5061s/100 iter), 65.5/232ep, loss = 3.61852
-I0510 20:43:36.929528  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40645 (* 1 = 3.40645 loss)
-I0510 20:43:36.929539  5307 sgd_solver.cpp:172] Iteration 33900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:44:37.329893  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_34000.caffemodel
-I0510 20:44:37.345214  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_34000.solverstate
-I0510 20:44:37.350540  5307 solver.cpp:635] Iteration 34000, Testing net (#0)
-I0510 20:45:18.248383  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:45:18.483002  5307 solver.cpp:747] class AP 1: 0.468396
-I0510 20:45:18.484258  5307 solver.cpp:747] class AP 2: 0.505179
-I0510 20:45:18.489697  5307 solver.cpp:747] class AP 3: 0.354221
-I0510 20:45:18.493027  5307 solver.cpp:747] class AP 4: 0.355639
-I0510 20:45:18.514153  5307 solver.cpp:747] class AP 5: 0.19221
-I0510 20:45:18.514439  5307 solver.cpp:747] class AP 6: 0.58785
-I0510 20:45:18.519455  5307 solver.cpp:747] class AP 7: 0.56004
-I0510 20:45:18.519934  5307 solver.cpp:747] class AP 8: 0.604614
-I0510 20:45:18.549664  5307 solver.cpp:747] class AP 9: 0.315277
-I0510 20:45:18.549860  5307 solver.cpp:747] class AP 10: 0.427041
-I0510 20:45:18.550740  5307 solver.cpp:747] class AP 11: 0.436946
-I0510 20:45:18.551120  5307 solver.cpp:747] class AP 12: 0.507325
-I0510 20:45:18.551321  5307 solver.cpp:747] class AP 13: 0.552242
-I0510 20:45:18.551616  5307 solver.cpp:747] class AP 14: 0.531344
-I0510 20:45:18.596168  5307 solver.cpp:747] class AP 15: 0.593803
-I0510 20:45:18.613611  5307 solver.cpp:747] class AP 16: 0.182031
-I0510 20:45:18.614923  5307 solver.cpp:747] class AP 17: 0.416545
-I0510 20:45:18.615754  5307 solver.cpp:747] class AP 18: 0.478007
-I0510 20:45:18.616039  5307 solver.cpp:747] class AP 19: 0.576452
-I0510 20:45:18.617624  5307 solver.cpp:747] class AP 20: 0.367012
-I0510 20:45:18.617635  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.450609
-I0510 20:45:18.617774  5307 solver.cpp:283] Tests completed in 101.689s
-I0510 20:45:19.214574  5307 solver.cpp:352] Iteration 34000 (0.983389 iter/s, 101.689s/100 iter), 65.7/232ep, loss = 3.70767
-I0510 20:45:19.214648  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.55412 (* 1 = 4.55412 loss)
-I0510 20:45:19.214668  5307 sgd_solver.cpp:172] Iteration 34000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:46:19.771157  5307 solver.cpp:352] Iteration 34100 (1.65138 iter/s, 60.5555s/100 iter), 65.9/232ep, loss = 3.48196
-I0510 20:46:19.771966  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2801 (* 1 = 3.2801 loss)
-I0510 20:46:19.771975  5307 sgd_solver.cpp:172] Iteration 34100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:46:31.240007  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:47:20.672050  5307 solver.cpp:352] Iteration 34200 (1.64204 iter/s, 60.8998s/100 iter), 66.1/232ep, loss = 3.76233
-I0510 20:47:20.672143  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.77907 (* 1 = 3.77907 loss)
-I0510 20:47:20.672163  5307 sgd_solver.cpp:172] Iteration 34200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:48:21.350836  5307 solver.cpp:352] Iteration 34300 (1.64805 iter/s, 60.6777s/100 iter), 66.3/232ep, loss = 3.5743
-I0510 20:48:21.350909  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14103 (* 1 = 3.14103 loss)
-I0510 20:48:21.350927  5307 sgd_solver.cpp:172] Iteration 34300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:49:22.619603  5307 solver.cpp:352] Iteration 34400 (1.63218 iter/s, 61.2677s/100 iter), 66.5/232ep, loss = 3.59712
-I0510 20:49:22.620645  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3178 (* 1 = 3.3178 loss)
-I0510 20:49:22.620659  5307 sgd_solver.cpp:172] Iteration 34400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:50:24.179818  5307 solver.cpp:352] Iteration 34500 (1.62445 iter/s, 61.5592s/100 iter), 66.7/232ep, loss = 3.80377
-I0510 20:50:24.180825  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.96294 (* 1 = 3.96294 loss)
-I0510 20:50:24.180835  5307 sgd_solver.cpp:172] Iteration 34500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:51:24.903394  5307 solver.cpp:352] Iteration 34600 (1.64683 iter/s, 60.7225s/100 iter), 66.9/232ep, loss = 3.86259
-I0510 20:51:24.903481  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41186 (* 1 = 4.41186 loss)
-I0510 20:51:24.903538  5307 sgd_solver.cpp:172] Iteration 34600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:51:46.390770  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:52:25.481698  5307 solver.cpp:352] Iteration 34700 (1.65078 iter/s, 60.5773s/100 iter), 67.1/232ep, loss = 3.66415
-I0510 20:52:25.481909  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71425 (* 1 = 3.71425 loss)
-I0510 20:52:25.481936  5307 sgd_solver.cpp:172] Iteration 34700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:53:25.305434  5307 solver.cpp:352] Iteration 34800 (1.67161 iter/s, 59.8227s/100 iter), 67.3/232ep, loss = 3.60402
-I0510 20:53:25.305531  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56683 (* 1 = 3.56683 loss)
-I0510 20:53:25.305541  5307 sgd_solver.cpp:172] Iteration 34800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:54:25.806474  5307 solver.cpp:352] Iteration 34900 (1.65289 iter/s, 60.5s/100 iter), 67.5/232ep, loss = 3.95134
-I0510 20:54:25.806650  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80422 (* 1 = 3.80422 loss)
-I0510 20:54:25.806704  5307 sgd_solver.cpp:172] Iteration 34900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:55:26.613881  5307 solver.cpp:352] Iteration 35000 (1.64456 iter/s, 60.8064s/100 iter), 67.7/232ep, loss = 3.76141
-I0510 20:55:26.613971  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25462 (* 1 = 3.25462 loss)
-I0510 20:55:26.613988  5307 sgd_solver.cpp:172] Iteration 35000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:56:27.344899  5307 solver.cpp:352] Iteration 35100 (1.64663 iter/s, 60.73s/100 iter), 67.9/232ep, loss = 3.5772
-I0510 20:56:27.344980  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69115 (* 1 = 3.69115 loss)
-I0510 20:56:27.344990  5307 sgd_solver.cpp:172] Iteration 35100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:56:59.136808  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 20:57:27.278641  5307 solver.cpp:352] Iteration 35200 (1.66854 iter/s, 59.9327s/100 iter), 68.1/232ep, loss = 3.73241
-I0510 20:57:27.278709  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85551 (* 1 = 3.85551 loss)
-I0510 20:57:27.278722  5307 sgd_solver.cpp:172] Iteration 35200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:58:27.649441  5307 solver.cpp:352] Iteration 35300 (1.65646 iter/s, 60.3698s/100 iter), 68.2/232ep, loss = 3.69123
-I0510 20:58:27.649540  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00623 (* 1 = 4.00623 loss)
-I0510 20:58:27.649559  5307 sgd_solver.cpp:172] Iteration 35300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 20:59:28.589807  5307 solver.cpp:352] Iteration 35400 (1.64098 iter/s, 60.9393s/100 iter), 68.4/232ep, loss = 3.6245
-I0510 20:59:28.589917  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83925 (* 1 = 3.83925 loss)
-I0510 20:59:28.589929  5307 sgd_solver.cpp:172] Iteration 35400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:00:28.993971  5307 solver.cpp:352] Iteration 35500 (1.65554 iter/s, 60.4032s/100 iter), 68.6/232ep, loss = 3.68356
-I0510 21:00:28.994617  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54682 (* 1 = 3.54682 loss)
-I0510 21:00:28.994635  5307 sgd_solver.cpp:172] Iteration 35500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:01:29.870028  5307 solver.cpp:352] Iteration 35600 (1.64271 iter/s, 60.875s/100 iter), 68.8/232ep, loss = 3.76594
-I0510 21:01:29.870085  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28141 (* 1 = 3.28141 loss)
-I0510 21:01:29.870092  5307 sgd_solver.cpp:172] Iteration 35600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:02:11.876209  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:02:29.675426  5307 solver.cpp:352] Iteration 35700 (1.67212 iter/s, 59.8044s/100 iter), 69/232ep, loss = 3.60164
-I0510 21:02:29.675454  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.09273 (* 1 = 4.09273 loss)
-I0510 21:02:29.675460  5307 sgd_solver.cpp:172] Iteration 35700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:03:30.000664  5307 solver.cpp:352] Iteration 35800 (1.65771 iter/s, 60.3242s/100 iter), 69.2/232ep, loss = 3.59873
-I0510 21:03:30.000756  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.98077 (* 1 = 3.98077 loss)
-I0510 21:03:30.000772  5307 sgd_solver.cpp:172] Iteration 35800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:04:30.281559  5307 solver.cpp:352] Iteration 35900 (1.65893 iter/s, 60.2799s/100 iter), 69.4/232ep, loss = 3.67615
-I0510 21:04:30.281621  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51516 (* 1 = 3.51516 loss)
-I0510 21:04:30.281631  5307 sgd_solver.cpp:172] Iteration 35900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:05:30.561995  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_36000.caffemodel
-I0510 21:05:30.577775  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_36000.solverstate
-I0510 21:05:30.582509  5307 solver.cpp:635] Iteration 36000, Testing net (#0)
-I0510 21:06:11.008594  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:06:11.250401  5307 solver.cpp:747] class AP 1: 0.568783
-I0510 21:06:11.251291  5307 solver.cpp:747] class AP 2: 0.65916
-I0510 21:06:11.261994  5307 solver.cpp:747] class AP 3: 0.446317
-I0510 21:06:11.267140  5307 solver.cpp:747] class AP 4: 0.395777
-I0510 21:06:11.279081  5307 solver.cpp:747] class AP 5: 0.260131
-I0510 21:06:11.279667  5307 solver.cpp:747] class AP 6: 0.619327
-I0510 21:06:11.286386  5307 solver.cpp:747] class AP 7: 0.635646
-I0510 21:06:11.287024  5307 solver.cpp:747] class AP 8: 0.685365
-I0510 21:06:11.310312  5307 solver.cpp:747] class AP 9: 0.308565
-I0510 21:06:11.311499  5307 solver.cpp:747] class AP 10: 0.4708
-I0510 21:06:11.312520  5307 solver.cpp:747] class AP 11: 0.476802
-I0510 21:06:11.314118  5307 solver.cpp:747] class AP 12: 0.617592
-I0510 21:06:11.314607  5307 solver.cpp:747] class AP 13: 0.680942
-I0510 21:06:11.315171  5307 solver.cpp:747] class AP 14: 0.635709
-I0510 21:06:11.376093  5307 solver.cpp:747] class AP 15: 0.637665
-I0510 21:06:11.382761  5307 solver.cpp:747] class AP 16: 0.224308
-I0510 21:06:11.392376  5307 solver.cpp:747] class AP 17: 0.440435
-I0510 21:06:11.393535  5307 solver.cpp:747] class AP 18: 0.524649
-I0510 21:06:11.394313  5307 solver.cpp:747] class AP 19: 0.632256
-I0510 21:06:11.395380  5307 solver.cpp:747] class AP 20: 0.475234
-I0510 21:06:11.395386  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.519773
-I0510 21:06:11.395527  5307 solver.cpp:283] Tests completed in 101.112s
-I0510 21:06:11.943778  5307 solver.cpp:352] Iteration 36000 (0.989 iter/s, 101.112s/100 iter), 69.6/232ep, loss = 3.35457
-I0510 21:06:11.943830  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43099 (* 1 = 3.43099 loss)
-I0510 21:06:11.943842  5307 sgd_solver.cpp:172] Iteration 36000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:07:12.810127  5307 solver.cpp:352] Iteration 36100 (1.64297 iter/s, 60.8653s/100 iter), 69.8/232ep, loss = 3.67175
-I0510 21:07:12.810981  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53452 (* 1 = 3.53452 loss)
-I0510 21:07:12.811048  5307 sgd_solver.cpp:172] Iteration 36100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:08:05.406282  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:08:13.164630  5307 solver.cpp:352] Iteration 36200 (1.65691 iter/s, 60.3534s/100 iter), 70/232ep, loss = 3.62086
-I0510 21:08:13.164672  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.69297 (* 1 = 2.69297 loss)
-I0510 21:08:13.164682  5307 sgd_solver.cpp:172] Iteration 36200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:09:13.744716  5307 solver.cpp:352] Iteration 36300 (1.65074 iter/s, 60.579s/100 iter), 70.2/232ep, loss = 3.5315
-I0510 21:09:13.744881  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55787 (* 1 = 3.55787 loss)
-I0510 21:09:13.744909  5307 sgd_solver.cpp:172] Iteration 36300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:10:14.500439  5307 solver.cpp:352] Iteration 36400 (1.64596 iter/s, 60.7547s/100 iter), 70.4/232ep, loss = 3.63935
-I0510 21:10:14.500519  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89221 (* 1 = 3.89221 loss)
-I0510 21:10:14.500545  5307 sgd_solver.cpp:172] Iteration 36400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:11:14.099763  5307 solver.cpp:352] Iteration 36500 (1.6779 iter/s, 59.5983s/100 iter), 70.6/232ep, loss = 3.9966
-I0510 21:11:14.099948  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.81575 (* 1 = 3.81575 loss)
-I0510 21:11:14.099975  5307 sgd_solver.cpp:172] Iteration 36500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:12:14.474020  5307 solver.cpp:352] Iteration 36600 (1.65636 iter/s, 60.3732s/100 iter), 70.8/232ep, loss = 3.64754
-I0510 21:12:14.485167  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13334 (* 1 = 3.13334 loss)
-I0510 21:12:14.485191  5307 sgd_solver.cpp:172] Iteration 36600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:13:14.260732  5307 solver.cpp:352] Iteration 36700 (1.67264 iter/s, 59.7857s/100 iter), 71/232ep, loss = 3.69982
-I0510 21:13:14.260835  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.12445 (* 1 = 4.12445 loss)
-I0510 21:13:14.260859  5307 sgd_solver.cpp:172] Iteration 36700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:13:17.213470  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:14:13.801023  5307 solver.cpp:352] Iteration 36800 (1.67956 iter/s, 59.5393s/100 iter), 71.1/232ep, loss = 3.5667
-I0510 21:14:13.801134  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63345 (* 1 = 3.63345 loss)
-I0510 21:14:13.801147  5307 sgd_solver.cpp:172] Iteration 36800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:15:14.316159  5307 solver.cpp:352] Iteration 36900 (1.65251 iter/s, 60.5141s/100 iter), 71.3/232ep, loss = 3.71623
-I0510 21:15:14.316234  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73786 (* 1 = 2.73786 loss)
-I0510 21:15:14.316244  5307 sgd_solver.cpp:172] Iteration 36900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:16:14.722913  5307 solver.cpp:352] Iteration 37000 (1.65547 iter/s, 60.4057s/100 iter), 71.5/232ep, loss = 3.5448
-I0510 21:16:14.722980  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92331 (* 1 = 2.92331 loss)
-I0510 21:16:14.722988  5307 sgd_solver.cpp:172] Iteration 37000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:17:14.764508  5307 solver.cpp:352] Iteration 37100 (1.66554 iter/s, 60.0406s/100 iter), 71.7/232ep, loss = 3.59719
-I0510 21:17:14.764567  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05983 (* 1 = 4.05983 loss)
-I0510 21:17:14.764573  5307 sgd_solver.cpp:172] Iteration 37100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:18:14.917587  5307 solver.cpp:352] Iteration 37200 (1.66245 iter/s, 60.1521s/100 iter), 71.9/232ep, loss = 3.60382
-I0510 21:18:14.917676  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51662 (* 1 = 3.51662 loss)
-I0510 21:18:14.917697  5307 sgd_solver.cpp:172] Iteration 37200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:18:27.635392  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:19:15.886972  5307 solver.cpp:352] Iteration 37300 (1.6402 iter/s, 60.9683s/100 iter), 72.1/232ep, loss = 3.70657
-I0510 21:19:15.887038  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28576 (* 1 = 3.28576 loss)
-I0510 21:19:15.887046  5307 sgd_solver.cpp:172] Iteration 37300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:20:15.671473  5307 solver.cpp:352] Iteration 37400 (1.6727 iter/s, 59.7835s/100 iter), 72.3/232ep, loss = 3.46799
-I0510 21:20:15.671617  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.14536 (* 1 = 4.14536 loss)
-I0510 21:20:15.671633  5307 sgd_solver.cpp:172] Iteration 37400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:21:17.264648  5307 solver.cpp:352] Iteration 37500 (1.62358 iter/s, 61.5922s/100 iter), 72.5/232ep, loss = 3.59698
-I0510 21:21:17.264725  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37801 (* 1 = 3.37801 loss)
-I0510 21:21:17.264735  5307 sgd_solver.cpp:172] Iteration 37500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:22:18.230902  5307 solver.cpp:352] Iteration 37600 (1.64028 iter/s, 60.9652s/100 iter), 72.7/232ep, loss = 3.59863
-I0510 21:22:18.231084  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41289 (* 1 = 3.41289 loss)
-I0510 21:22:18.231132  5307 sgd_solver.cpp:172] Iteration 37600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:23:19.303782  5307 solver.cpp:352] Iteration 37700 (1.63742 iter/s, 61.0719s/100 iter), 72.9/232ep, loss = 3.61308
-I0510 21:23:19.303894  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26588 (* 1 = 3.26588 loss)
-I0510 21:23:19.303903  5307 sgd_solver.cpp:172] Iteration 37700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:23:43.063323  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:24:19.149380  5307 solver.cpp:352] Iteration 37800 (1.67099 iter/s, 59.8446s/100 iter), 73.1/232ep, loss = 3.59578
-I0510 21:24:19.149605  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.75051 (* 1 = 3.75051 loss)
-I0510 21:24:19.149615  5307 sgd_solver.cpp:172] Iteration 37800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:25:19.356627  5307 solver.cpp:352] Iteration 37900 (1.66096 iter/s, 60.2062s/100 iter), 73.3/232ep, loss = 3.73517
-I0510 21:25:19.356943  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.43998 (* 1 = 4.43998 loss)
-I0510 21:25:19.356952  5307 sgd_solver.cpp:172] Iteration 37900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:26:19.011675  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_38000.caffemodel
-I0510 21:26:19.031734  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_38000.solverstate
-I0510 21:26:19.038130  5307 solver.cpp:635] Iteration 38000, Testing net (#0)
-I0510 21:26:59.776566  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:27:00.004941  5307 solver.cpp:747] class AP 1: 0.5052
-I0510 21:27:00.005132  5307 solver.cpp:747] class AP 2: 0.539033
-I0510 21:27:00.010339  5307 solver.cpp:747] class AP 3: 0.357168
-I0510 21:27:00.012910  5307 solver.cpp:747] class AP 4: 0.333069
-I0510 21:27:00.030097  5307 solver.cpp:747] class AP 5: 0.204389
-I0510 21:27:00.030365  5307 solver.cpp:747] class AP 6: 0.609031
-I0510 21:27:00.039222  5307 solver.cpp:747] class AP 7: 0.591758
-I0510 21:27:00.040027  5307 solver.cpp:747] class AP 8: 0.656491
-I0510 21:27:00.071101  5307 solver.cpp:747] class AP 9: 0.298
-I0510 21:27:00.071439  5307 solver.cpp:747] class AP 10: 0.475356
-I0510 21:27:00.071856  5307 solver.cpp:747] class AP 11: 0.50872
-I0510 21:27:00.072576  5307 solver.cpp:747] class AP 12: 0.538248
-I0510 21:27:00.072798  5307 solver.cpp:747] class AP 13: 0.651622
-I0510 21:27:00.073029  5307 solver.cpp:747] class AP 14: 0.562866
-I0510 21:27:00.128082  5307 solver.cpp:747] class AP 15: 0.606885
-I0510 21:27:00.130252  5307 solver.cpp:747] class AP 16: 0.222947
-I0510 21:27:00.132756  5307 solver.cpp:747] class AP 17: 0.437542
-I0510 21:27:00.134523  5307 solver.cpp:747] class AP 18: 0.413573
-I0510 21:27:00.134902  5307 solver.cpp:747] class AP 19: 0.619407
-I0510 21:27:00.136670  5307 solver.cpp:747] class AP 20: 0.461706
-I0510 21:27:00.136685  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.47965
-I0510 21:27:00.136886  5307 solver.cpp:283] Tests completed in 100.779s
-I0510 21:27:00.678278  5307 solver.cpp:352] Iteration 38000 (0.992274 iter/s, 100.779s/100 iter), 73.5/232ep, loss = 3.82641
-I0510 21:27:00.678313  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13177 (* 1 = 3.13177 loss)
-I0510 21:27:00.678320  5307 sgd_solver.cpp:172] Iteration 38000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:28:00.853718  5307 solver.cpp:352] Iteration 38100 (1.66184 iter/s, 60.1744s/100 iter), 73.7/232ep, loss = 3.62437
-I0510 21:28:00.853843  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30541 (* 1 = 3.30541 loss)
-I0510 21:28:00.853859  5307 sgd_solver.cpp:172] Iteration 38100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:29:01.346016  5307 solver.cpp:352] Iteration 38200 (1.65313 iter/s, 60.4912s/100 iter), 73.9/232ep, loss = 3.60155
-I0510 21:29:01.350435  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.7041 (* 1 = 3.7041 loss)
-I0510 21:29:01.350448  5307 sgd_solver.cpp:172] Iteration 38200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:29:35.598528  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:30:01.741117  5307 solver.cpp:352] Iteration 38300 (1.65579 iter/s, 60.3941s/100 iter), 74/232ep, loss = 3.58561
-I0510 21:30:01.741160  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.48464 (* 1 = 3.48464 loss)
-I0510 21:30:01.741169  5307 sgd_solver.cpp:172] Iteration 38300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:31:02.368338  5307 solver.cpp:352] Iteration 38400 (1.64945 iter/s, 60.6262s/100 iter), 74.2/232ep, loss = 3.65317
-I0510 21:31:02.368399  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03553 (* 1 = 4.03553 loss)
-I0510 21:31:02.368409  5307 sgd_solver.cpp:172] Iteration 38400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:32:03.428159  5307 solver.cpp:352] Iteration 38500 (1.63777 iter/s, 61.0588s/100 iter), 74.4/232ep, loss = 3.61148
-I0510 21:32:03.428247  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.8391 (* 1 = 3.8391 loss)
-I0510 21:32:03.428261  5307 sgd_solver.cpp:172] Iteration 38500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:33:03.708784  5307 solver.cpp:352] Iteration 38600 (1.65894 iter/s, 60.2796s/100 iter), 74.6/232ep, loss = 3.81464
-I0510 21:33:03.709264  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.7558 (* 1 = 3.7558 loss)
-I0510 21:33:03.709309  5307 sgd_solver.cpp:172] Iteration 38600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:34:04.382413  5307 solver.cpp:352] Iteration 38700 (1.64819 iter/s, 60.6726s/100 iter), 74.8/232ep, loss = 3.83513
-I0510 21:34:04.382488  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41642 (* 1 = 3.41642 loss)
-I0510 21:34:04.382498  5307 sgd_solver.cpp:172] Iteration 38700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:34:48.086021  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:35:04.040887  5307 solver.cpp:352] Iteration 38800 (1.67624 iter/s, 59.6575s/100 iter), 75/232ep, loss = 3.62916
-I0510 21:35:04.040923  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41938 (* 1 = 4.41938 loss)
-I0510 21:35:04.040931  5307 sgd_solver.cpp:172] Iteration 38800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:36:04.107892  5307 solver.cpp:352] Iteration 38900 (1.66484 iter/s, 60.066s/100 iter), 75.2/232ep, loss = 3.58486
-I0510 21:36:04.107978  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21385 (* 1 = 3.21385 loss)
-I0510 21:36:04.107995  5307 sgd_solver.cpp:172] Iteration 38900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:37:04.114724  5307 solver.cpp:352] Iteration 39000 (1.6665 iter/s, 60.0058s/100 iter), 75.4/232ep, loss = 3.52668
-I0510 21:37:04.115047  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.35119 (* 1 = 4.35119 loss)
-I0510 21:37:04.115056  5307 sgd_solver.cpp:172] Iteration 39000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:38:06.187549  5307 solver.cpp:352] Iteration 39100 (1.61104 iter/s, 62.0718s/100 iter), 75.6/232ep, loss = 3.52495
-I0510 21:38:06.187664  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.16989 (* 1 = 4.16989 loss)
-I0510 21:38:06.187674  5307 sgd_solver.cpp:172] Iteration 39100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:39:15.436691  5307 solver.cpp:352] Iteration 39200 (1.44409 iter/s, 69.248s/100 iter), 75.8/232ep, loss = 3.67819
-I0510 21:39:15.437286  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09562 (* 1 = 3.09562 loss)
-I0510 21:39:15.437294  5307 sgd_solver.cpp:172] Iteration 39200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:40:11.855397  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:40:17.215807  5307 solver.cpp:352] Iteration 39300 (1.6187 iter/s, 61.7781s/100 iter), 76/232ep, loss = 3.78971
-I0510 21:40:17.215832  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55306 (* 1 = 3.55306 loss)
-I0510 21:40:17.215840  5307 sgd_solver.cpp:172] Iteration 39300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:41:17.962391  5307 solver.cpp:352] Iteration 39400 (1.64621 iter/s, 60.7455s/100 iter), 76.2/232ep, loss = 3.89644
-I0510 21:41:17.962517  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11371 (* 1 = 4.11371 loss)
-I0510 21:41:17.962525  5307 sgd_solver.cpp:172] Iteration 39400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:42:18.468636  5307 solver.cpp:352] Iteration 39500 (1.65275 iter/s, 60.5052s/100 iter), 76.4/232ep, loss = 3.64194
-I0510 21:42:18.468721  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74449 (* 1 = 3.74449 loss)
-I0510 21:42:18.468731  5307 sgd_solver.cpp:172] Iteration 39500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:43:19.419124  5307 solver.cpp:352] Iteration 39600 (1.6407 iter/s, 60.9495s/100 iter), 76.6/232ep, loss = 3.63924
-I0510 21:43:19.419281  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61965 (* 1 = 3.61965 loss)
-I0510 21:43:19.419332  5307 sgd_solver.cpp:172] Iteration 39600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:44:20.567492  5307 solver.cpp:352] Iteration 39700 (1.63539 iter/s, 61.1473s/100 iter), 76.8/232ep, loss = 3.65378
-I0510 21:44:20.568058  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64097 (* 1 = 3.64097 loss)
-I0510 21:44:20.568075  5307 sgd_solver.cpp:172] Iteration 39700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:45:20.776649  5307 solver.cpp:352] Iteration 39800 (1.66091 iter/s, 60.2081s/100 iter), 77/232ep, loss = 3.61238
-I0510 21:45:20.776767  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.49909 (* 1 = 3.49909 loss)
-I0510 21:45:20.776785  5307 sgd_solver.cpp:172] Iteration 39800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:45:24.994469  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:46:20.611048  5307 solver.cpp:352] Iteration 39900 (1.67131 iter/s, 59.8334s/100 iter), 77.1/232ep, loss = 3.56136
-I0510 21:46:20.611136  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26811 (* 1 = 3.26811 loss)
-I0510 21:46:20.611156  5307 sgd_solver.cpp:172] Iteration 39900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:47:20.372117  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_40000.caffemodel
-I0510 21:47:20.389097  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_40000.solverstate
-I0510 21:47:20.394568  5307 solver.cpp:635] Iteration 40000, Testing net (#0)
-I0510 21:48:00.663660  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:48:00.872752  5307 solver.cpp:747] class AP 1: 0.520476
-I0510 21:48:00.873112  5307 solver.cpp:747] class AP 2: 0.577247
-I0510 21:48:00.878597  5307 solver.cpp:747] class AP 3: 0.314433
-I0510 21:48:00.879312  5307 solver.cpp:747] class AP 4: 0.335391
-I0510 21:48:00.899533  5307 solver.cpp:747] class AP 5: 0.227511
-I0510 21:48:00.899749  5307 solver.cpp:747] class AP 6: 0.573794
-I0510 21:48:00.905573  5307 solver.cpp:747] class AP 7: 0.569326
-I0510 21:48:00.907130  5307 solver.cpp:747] class AP 8: 0.655245
-I0510 21:48:00.917480  5307 solver.cpp:747] class AP 9: 0.261153
-I0510 21:48:00.918313  5307 solver.cpp:747] class AP 10: 0.416685
-I0510 21:48:00.918567  5307 solver.cpp:747] class AP 11: 0.489146
-I0510 21:48:00.921221  5307 solver.cpp:747] class AP 12: 0.578182
-I0510 21:48:00.921957  5307 solver.cpp:747] class AP 13: 0.706205
-I0510 21:48:00.922250  5307 solver.cpp:747] class AP 14: 0.591031
-I0510 21:48:01.001513  5307 solver.cpp:747] class AP 15: 0.615364
-I0510 21:48:01.005388  5307 solver.cpp:747] class AP 16: 0.207144
-I0510 21:48:01.006865  5307 solver.cpp:747] class AP 17: 0.43087
-I0510 21:48:01.007848  5307 solver.cpp:747] class AP 18: 0.419016
-I0510 21:48:01.008469  5307 solver.cpp:747] class AP 19: 0.614923
-I0510 21:48:01.009793  5307 solver.cpp:747] class AP 20: 0.450545
-I0510 21:48:01.009802  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.477684
-I0510 21:48:01.010001  5307 solver.cpp:283] Tests completed in 100.397s
-I0510 21:48:01.576629  5307 solver.cpp:352] Iteration 40000 (0.996043 iter/s, 100.397s/100 iter), 77.3/232ep, loss = 3.86338
-I0510 21:48:01.576654  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.65106 (* 1 = 4.65106 loss)
-I0510 21:48:01.576660  5307 sgd_solver.cpp:172] Iteration 40000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:49:01.632191  5307 solver.cpp:352] Iteration 40100 (1.66515 iter/s, 60.0545s/100 iter), 77.5/232ep, loss = 3.58973
-I0510 21:49:01.632961  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.6637 (* 1 = 3.6637 loss)
-I0510 21:49:01.632982  5307 sgd_solver.cpp:172] Iteration 40100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:50:02.186213  5307 solver.cpp:352] Iteration 40200 (1.65145 iter/s, 60.553s/100 iter), 77.7/232ep, loss = 3.734
-I0510 21:50:02.187319  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30205 (* 1 = 3.30205 loss)
-I0510 21:50:02.187347  5307 sgd_solver.cpp:172] Iteration 40200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:51:02.389930  5307 solver.cpp:352] Iteration 40300 (1.66106 iter/s, 60.2027s/100 iter), 77.9/232ep, loss = 3.55042
-I0510 21:51:02.389989  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4546 (* 1 = 3.4546 loss)
-I0510 21:51:02.389998  5307 sgd_solver.cpp:172] Iteration 40300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:51:17.505239  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:52:02.887758  5307 solver.cpp:352] Iteration 40400 (1.65298 iter/s, 60.4968s/100 iter), 78.1/232ep, loss = 3.61956
-I0510 21:52:02.887820  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15467 (* 1 = 4.15467 loss)
-I0510 21:52:02.887827  5307 sgd_solver.cpp:172] Iteration 40400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:53:03.079121  5307 solver.cpp:352] Iteration 40500 (1.6614 iter/s, 60.1904s/100 iter), 78.3/232ep, loss = 3.71012
-I0510 21:53:03.079205  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61716 (* 1 = 3.61716 loss)
-I0510 21:53:03.079222  5307 sgd_solver.cpp:172] Iteration 40500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:54:03.590065  5307 solver.cpp:352] Iteration 40600 (1.65262 iter/s, 60.5099s/100 iter), 78.5/232ep, loss = 3.5501
-I0510 21:54:03.590135  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.84851 (* 1 = 2.84851 loss)
-I0510 21:54:03.590147  5307 sgd_solver.cpp:172] Iteration 40600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:55:04.550119  5307 solver.cpp:352] Iteration 40700 (1.64045 iter/s, 60.959s/100 iter), 78.7/232ep, loss = 3.6139
-I0510 21:55:04.550245  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00362 (* 1 = 4.00362 loss)
-I0510 21:55:04.550262  5307 sgd_solver.cpp:172] Iteration 40700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:56:04.426820  5307 solver.cpp:352] Iteration 40800 (1.67013 iter/s, 59.8757s/100 iter), 78.9/232ep, loss = 3.45172
-I0510 21:56:04.426923  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41889 (* 1 = 3.41889 loss)
-I0510 21:56:04.426934  5307 sgd_solver.cpp:172] Iteration 40800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:56:30.006772  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 21:57:04.665575  5307 solver.cpp:352] Iteration 40900 (1.66009 iter/s, 60.2377s/100 iter), 79.1/232ep, loss = 3.62553
-I0510 21:57:04.665683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69357 (* 1 = 3.69357 loss)
-I0510 21:57:04.665704  5307 sgd_solver.cpp:172] Iteration 40900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:58:04.750860  5307 solver.cpp:352] Iteration 41000 (1.66433 iter/s, 60.0843s/100 iter), 79.3/232ep, loss = 3.74795
-I0510 21:58:04.750957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99367 (* 1 = 2.99367 loss)
-I0510 21:58:04.750977  5307 sgd_solver.cpp:172] Iteration 41000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 21:59:05.323962  5307 solver.cpp:352] Iteration 41100 (1.65093 iter/s, 60.5721s/100 iter), 79.5/232ep, loss = 3.56803
-I0510 21:59:05.324067  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03478 (* 1 = 4.03478 loss)
-I0510 21:59:05.324082  5307 sgd_solver.cpp:172] Iteration 41100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:00:05.307688  5307 solver.cpp:352] Iteration 41200 (1.66715 iter/s, 59.9827s/100 iter), 79.7/232ep, loss = 3.52172
-I0510 22:00:05.312608  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72247 (* 1 = 3.72247 loss)
-I0510 22:00:05.312623  5307 sgd_solver.cpp:172] Iteration 41200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:01:04.931408  5307 solver.cpp:352] Iteration 41300 (1.67721 iter/s, 59.6227s/100 iter), 79.9/232ep, loss = 3.77013
-I0510 22:01:04.931486  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.49615 (* 1 = 3.49615 loss)
-I0510 22:01:04.931495  5307 sgd_solver.cpp:172] Iteration 41300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:01:40.768656  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:02:05.374547  5307 solver.cpp:352] Iteration 41400 (1.65448 iter/s, 60.4421s/100 iter), 80/232ep, loss = 3.62685
-I0510 22:02:05.374572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10421 (* 1 = 3.10421 loss)
-I0510 22:02:05.374579  5307 sgd_solver.cpp:172] Iteration 41400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:03:06.852798  5307 solver.cpp:352] Iteration 41500 (1.62662 iter/s, 61.4772s/100 iter), 80.2/232ep, loss = 3.50893
-I0510 22:03:06.853668  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39475 (* 1 = 3.39475 loss)
-I0510 22:03:06.853682  5307 sgd_solver.cpp:172] Iteration 41500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:04:07.508661  5307 solver.cpp:352] Iteration 41600 (1.64867 iter/s, 60.6548s/100 iter), 80.4/232ep, loss = 3.59382
-I0510 22:04:07.509981  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.30832 (* 1 = 4.30832 loss)
-I0510 22:04:07.509997  5307 sgd_solver.cpp:172] Iteration 41600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:05:07.744612  5307 solver.cpp:352] Iteration 41700 (1.66017 iter/s, 60.235s/100 iter), 80.6/232ep, loss = 3.74398
-I0510 22:05:07.744665  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21229 (* 1 = 3.21229 loss)
-I0510 22:05:07.744671  5307 sgd_solver.cpp:172] Iteration 41700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:06:08.835930  5307 solver.cpp:352] Iteration 41800 (1.63692 iter/s, 61.0903s/100 iter), 80.8/232ep, loss = 3.61463
-I0510 22:06:08.836014  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87827 (* 1 = 3.87827 loss)
-I0510 22:06:08.836027  5307 sgd_solver.cpp:172] Iteration 41800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:06:55.344455  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:07:09.105779  5307 solver.cpp:352] Iteration 41900 (1.65923 iter/s, 60.2688s/100 iter), 81/232ep, loss = 3.66765
-I0510 22:07:09.105804  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.99514 (* 1 = 3.99514 loss)
-I0510 22:07:09.105813  5307 sgd_solver.cpp:172] Iteration 41900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:08:08.894412  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_42000.caffemodel
-I0510 22:08:08.913151  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_42000.solverstate
-I0510 22:08:08.920022  5307 solver.cpp:635] Iteration 42000, Testing net (#0)
-I0510 22:08:49.789216  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:08:50.003633  5307 solver.cpp:747] class AP 1: 0.534171
-I0510 22:08:50.004140  5307 solver.cpp:747] class AP 2: 0.628472
-I0510 22:08:50.010937  5307 solver.cpp:747] class AP 3: 0.418746
-I0510 22:08:50.014612  5307 solver.cpp:747] class AP 4: 0.364946
-I0510 22:08:50.031375  5307 solver.cpp:747] class AP 5: 0.213854
-I0510 22:08:50.031503  5307 solver.cpp:747] class AP 6: 0.627559
-I0510 22:08:50.041143  5307 solver.cpp:747] class AP 7: 0.620652
-I0510 22:08:50.042007  5307 solver.cpp:747] class AP 8: 0.710804
-I0510 22:08:50.061527  5307 solver.cpp:747] class AP 9: 0.330063
-I0510 22:08:50.061870  5307 solver.cpp:747] class AP 10: 0.504193
-I0510 22:08:50.062520  5307 solver.cpp:747] class AP 11: 0.534669
-I0510 22:08:50.063248  5307 solver.cpp:747] class AP 12: 0.633615
-I0510 22:08:50.063508  5307 solver.cpp:747] class AP 13: 0.705069
-I0510 22:08:50.063880  5307 solver.cpp:747] class AP 14: 0.632479
-I0510 22:08:50.124693  5307 solver.cpp:747] class AP 15: 0.632617
-I0510 22:08:50.129084  5307 solver.cpp:747] class AP 16: 0.246861
-I0510 22:08:50.130812  5307 solver.cpp:747] class AP 17: 0.470018
-I0510 22:08:50.131456  5307 solver.cpp:747] class AP 18: 0.51479
-I0510 22:08:50.131898  5307 solver.cpp:747] class AP 19: 0.688099
-I0510 22:08:50.132757  5307 solver.cpp:747] class AP 20: 0.523382
-I0510 22:08:50.132762  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.526753
-I0510 22:08:50.133000  5307 solver.cpp:283] Tests completed in 101.026s
-I0510 22:08:50.669611  5307 solver.cpp:352] Iteration 42000 (0.989849 iter/s, 101.026s/100 iter), 81.2/232ep, loss = 3.56295
-I0510 22:08:50.669718  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.17089 (* 1 = 3.17089 loss)
-I0510 22:08:50.669739  5307 sgd_solver.cpp:172] Iteration 42000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:09:50.111747  5307 solver.cpp:352] Iteration 42100 (1.68234 iter/s, 59.4411s/100 iter), 81.4/232ep, loss = 3.46262
-I0510 22:09:50.111821  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.23969 (* 1 = 4.23969 loss)
-I0510 22:09:50.111830  5307 sgd_solver.cpp:172] Iteration 42100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:10:50.060981  5307 solver.cpp:352] Iteration 42200 (1.66811 iter/s, 59.9482s/100 iter), 81.6/232ep, loss = 3.44918
-I0510 22:10:50.061062  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74013 (* 1 = 2.74013 loss)
-I0510 22:10:50.061074  5307 sgd_solver.cpp:172] Iteration 42200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:11:50.372360  5307 solver.cpp:352] Iteration 42300 (1.65809 iter/s, 60.3104s/100 iter), 81.8/232ep, loss = 3.7762
-I0510 22:11:50.372473  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85189 (* 1 = 3.85189 loss)
-I0510 22:11:50.372489  5307 sgd_solver.cpp:172] Iteration 42300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:12:46.130507  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:12:50.435878  5307 solver.cpp:352] Iteration 42400 (1.66493 iter/s, 60.0625s/100 iter), 82/232ep, loss = 3.733
-I0510 22:12:50.435904  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.80832 (* 1 = 4.80832 loss)
-I0510 22:12:50.435912  5307 sgd_solver.cpp:172] Iteration 42400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:13:51.216261  5307 solver.cpp:352] Iteration 42500 (1.6453 iter/s, 60.7794s/100 iter), 82.2/232ep, loss = 3.67476
-I0510 22:13:51.216312  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61387 (* 1 = 3.61387 loss)
-I0510 22:13:51.216320  5307 sgd_solver.cpp:172] Iteration 42500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:14:51.837419  5307 solver.cpp:352] Iteration 42600 (1.64962 iter/s, 60.6201s/100 iter), 82.4/232ep, loss = 3.84191
-I0510 22:14:51.837563  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19984 (* 1 = 3.19984 loss)
-I0510 22:14:51.837589  5307 sgd_solver.cpp:172] Iteration 42600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:15:52.448808  5307 solver.cpp:352] Iteration 42700 (1.64988 iter/s, 60.6104s/100 iter), 82.6/232ep, loss = 3.55317
-I0510 22:15:52.448926  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00699 (* 1 = 4.00699 loss)
-I0510 22:15:52.448948  5307 sgd_solver.cpp:172] Iteration 42700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:16:53.346068  5307 solver.cpp:352] Iteration 42800 (1.64214 iter/s, 60.8962s/100 iter), 82.8/232ep, loss = 3.53187
-I0510 22:16:53.346138  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.07234 (* 1 = 4.07234 loss)
-I0510 22:16:53.346146  5307 sgd_solver.cpp:172] Iteration 42800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:17:53.733168  5307 solver.cpp:352] Iteration 42900 (1.65601 iter/s, 60.3861s/100 iter), 82.9/232ep, loss = 3.60057
-I0510 22:17:53.733270  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.17121 (* 1 = 4.17121 loss)
-I0510 22:17:53.733295  5307 sgd_solver.cpp:172] Iteration 42900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:18:00.223826  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:18:54.359382  5307 solver.cpp:352] Iteration 43000 (1.64948 iter/s, 60.6252s/100 iter), 83.1/232ep, loss = 3.46198
-I0510 22:18:54.359463  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06771 (* 1 = 4.06771 loss)
-I0510 22:18:54.359474  5307 sgd_solver.cpp:172] Iteration 43000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:19:55.495054  5307 solver.cpp:352] Iteration 43100 (1.63573 iter/s, 61.1346s/100 iter), 83.3/232ep, loss = 3.58179
-I0510 22:19:55.495151  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99761 (* 1 = 2.99761 loss)
-I0510 22:19:55.495167  5307 sgd_solver.cpp:172] Iteration 43100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:20:57.084606  5307 solver.cpp:352] Iteration 43200 (1.62368 iter/s, 61.5885s/100 iter), 83.5/232ep, loss = 3.36912
-I0510 22:20:57.084743  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31 (* 1 = 3.31 loss)
-I0510 22:20:57.084753  5307 sgd_solver.cpp:172] Iteration 43200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:21:57.941856  5307 solver.cpp:352] Iteration 43300 (1.64322 iter/s, 60.8563s/100 iter), 83.7/232ep, loss = 3.66869
-I0510 22:21:57.941979  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.89205 (* 1 = 3.89205 loss)
-I0510 22:21:57.942003  5307 sgd_solver.cpp:172] Iteration 43300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:22:59.763221  5307 solver.cpp:352] Iteration 43400 (1.61759 iter/s, 61.8203s/100 iter), 83.9/232ep, loss = 3.53433
-I0510 22:22:59.763306  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77005 (* 1 = 2.77005 loss)
-I0510 22:22:59.763316  5307 sgd_solver.cpp:172] Iteration 43400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:23:17.433843  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:24:00.845634  5307 solver.cpp:352] Iteration 43500 (1.63716 iter/s, 61.0814s/100 iter), 84.1/232ep, loss = 3.45022
-I0510 22:24:00.845722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95186 (* 1 = 3.95186 loss)
-I0510 22:24:00.845732  5307 sgd_solver.cpp:172] Iteration 43500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:25:00.274463  5307 solver.cpp:352] Iteration 43600 (1.68271 iter/s, 59.4278s/100 iter), 84.3/232ep, loss = 3.60126
-I0510 22:25:00.274605  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.79965 (* 1 = 2.79965 loss)
-I0510 22:25:00.274617  5307 sgd_solver.cpp:172] Iteration 43600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:26:00.962894  5307 solver.cpp:352] Iteration 43700 (1.64779 iter/s, 60.6874s/100 iter), 84.5/232ep, loss = 3.59502
-I0510 22:26:00.964380  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.55997 (* 1 = 2.55997 loss)
-I0510 22:26:00.964414  5307 sgd_solver.cpp:172] Iteration 43700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:27:01.428666  5307 solver.cpp:352] Iteration 43800 (1.65386 iter/s, 60.4647s/100 iter), 84.7/232ep, loss = 3.55229
-I0510 22:27:01.428730  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.97239 (* 1 = 3.97239 loss)
-I0510 22:27:01.428738  5307 sgd_solver.cpp:172] Iteration 43800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:28:02.477066  5307 solver.cpp:352] Iteration 43900 (1.63807 iter/s, 61.0474s/100 iter), 84.9/232ep, loss = 3.45262
-I0510 22:28:02.477171  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.79397 (* 1 = 3.79397 loss)
-I0510 22:28:02.477183  5307 sgd_solver.cpp:172] Iteration 43900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:28:30.984215  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:29:03.972008  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_44000.caffemodel
-I0510 22:29:03.986655  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_44000.solverstate
-I0510 22:29:03.990772  5307 solver.cpp:635] Iteration 44000, Testing net (#0)
-I0510 22:29:44.763483  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:29:45.015172  5307 solver.cpp:747] class AP 1: 0.537234
-I0510 22:29:45.015624  5307 solver.cpp:747] class AP 2: 0.566408
-I0510 22:29:45.019718  5307 solver.cpp:747] class AP 3: 0.411401
-I0510 22:29:45.022940  5307 solver.cpp:747] class AP 4: 0.364857
-I0510 22:29:45.038170  5307 solver.cpp:747] class AP 5: 0.233334
-I0510 22:29:45.038571  5307 solver.cpp:747] class AP 6: 0.629944
-I0510 22:29:45.042909  5307 solver.cpp:747] class AP 7: 0.613214
-I0510 22:29:45.043376  5307 solver.cpp:747] class AP 8: 0.656918
-I0510 22:29:45.063295  5307 solver.cpp:747] class AP 9: 0.338147
-I0510 22:29:45.063719  5307 solver.cpp:747] class AP 10: 0.461028
-I0510 22:29:45.064224  5307 solver.cpp:747] class AP 11: 0.43602
-I0510 22:29:45.064898  5307 solver.cpp:747] class AP 12: 0.606772
-I0510 22:29:45.065259  5307 solver.cpp:747] class AP 13: 0.686549
-I0510 22:29:45.065376  5307 solver.cpp:747] class AP 14: 0.586515
-I0510 22:29:45.134161  5307 solver.cpp:747] class AP 15: 0.635893
-I0510 22:29:45.143028  5307 solver.cpp:747] class AP 16: 0.177475
-I0510 22:29:45.144666  5307 solver.cpp:747] class AP 17: 0.391172
-I0510 22:29:45.145244  5307 solver.cpp:747] class AP 18: 0.434161
-I0510 22:29:45.145675  5307 solver.cpp:747] class AP 19: 0.618719
-I0510 22:29:45.146224  5307 solver.cpp:747] class AP 20: 0.446521
-I0510 22:29:45.146230  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.491614
-I0510 22:29:45.146399  5307 solver.cpp:283] Tests completed in 102.668s
-I0510 22:29:45.713840  5307 solver.cpp:352] Iteration 44000 (0.974017 iter/s, 102.668s/100 iter), 85.1/232ep, loss = 3.40872
-I0510 22:29:45.713865  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.29076 (* 1 = 3.29076 loss)
-I0510 22:29:45.713871  5307 sgd_solver.cpp:172] Iteration 44000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:30:45.584980  5307 solver.cpp:352] Iteration 44100 (1.67028 iter/s, 59.8701s/100 iter), 85.3/232ep, loss = 3.56606
-I0510 22:30:45.586292  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71579 (* 1 = 3.71579 loss)
-I0510 22:30:45.586303  5307 sgd_solver.cpp:172] Iteration 44100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:31:45.395543  5307 solver.cpp:352] Iteration 44200 (1.67197 iter/s, 59.8095s/100 iter), 85.5/232ep, loss = 3.64415
-I0510 22:31:45.395606  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41891 (* 1 = 4.41891 loss)
-I0510 22:31:45.395613  5307 sgd_solver.cpp:172] Iteration 44200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:32:46.211119  5307 solver.cpp:352] Iteration 44300 (1.64434 iter/s, 60.8145s/100 iter), 85.7/232ep, loss = 3.5561
-I0510 22:32:46.211210  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11668 (* 1 = 4.11668 loss)
-I0510 22:32:46.211227  5307 sgd_solver.cpp:172] Iteration 44300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:33:47.296813  5307 solver.cpp:352] Iteration 44400 (1.63707 iter/s, 61.0847s/100 iter), 85.8/232ep, loss = 3.65152
-I0510 22:33:47.296867  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.57339 (* 1 = 4.57339 loss)
-I0510 22:33:47.296875  5307 sgd_solver.cpp:172] Iteration 44400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:34:26.328572  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:34:48.634385  5307 solver.cpp:352] Iteration 44500 (1.63035 iter/s, 61.3365s/100 iter), 86/232ep, loss = 3.51682
-I0510 22:34:48.634536  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.79272 (* 1 = 3.79272 loss)
-I0510 22:34:48.634568  5307 sgd_solver.cpp:172] Iteration 44500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:35:49.449618  5307 solver.cpp:352] Iteration 44600 (1.64435 iter/s, 60.8142s/100 iter), 86.2/232ep, loss = 3.63962
-I0510 22:35:49.451788  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.95575 (* 1 = 3.95575 loss)
-I0510 22:35:49.451802  5307 sgd_solver.cpp:172] Iteration 44600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:36:50.505905  5307 solver.cpp:352] Iteration 44700 (1.63786 iter/s, 61.0553s/100 iter), 86.4/232ep, loss = 3.55994
-I0510 22:36:50.506018  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28054 (* 1 = 3.28054 loss)
-I0510 22:36:50.506028  5307 sgd_solver.cpp:172] Iteration 44700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:37:51.268187  5307 solver.cpp:352] Iteration 44800 (1.64579 iter/s, 60.7613s/100 iter), 86.6/232ep, loss = 3.58286
-I0510 22:37:51.268245  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.91869 (* 1 = 3.91869 loss)
-I0510 22:37:51.268254  5307 sgd_solver.cpp:172] Iteration 44800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:38:52.239480  5307 solver.cpp:352] Iteration 44900 (1.64014 iter/s, 60.9703s/100 iter), 86.8/232ep, loss = 3.62117
-I0510 22:38:52.241292  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73229 (* 1 = 2.73229 loss)
-I0510 22:38:52.241310  5307 sgd_solver.cpp:172] Iteration 44900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:39:40.497205  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:39:53.324957  5307 solver.cpp:352] Iteration 45000 (1.63708 iter/s, 61.0844s/100 iter), 87/232ep, loss = 3.54813
-I0510 22:39:53.325136  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.86743 (* 1 = 2.86743 loss)
-I0510 22:39:53.325163  5307 sgd_solver.cpp:172] Iteration 45000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:40:53.649266  5307 solver.cpp:352] Iteration 45100 (1.65773 iter/s, 60.3233s/100 iter), 87.2/232ep, loss = 3.34768
-I0510 22:40:53.649327  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63302 (* 1 = 3.63302 loss)
-I0510 22:40:53.649335  5307 sgd_solver.cpp:172] Iteration 45100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:41:53.778311  5307 solver.cpp:352] Iteration 45200 (1.66312 iter/s, 60.128s/100 iter), 87.4/232ep, loss = 3.61005
-I0510 22:41:53.778378  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56444 (* 1 = 3.56444 loss)
-I0510 22:41:53.778388  5307 sgd_solver.cpp:172] Iteration 45200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:42:54.838815  5307 solver.cpp:352] Iteration 45300 (1.63775 iter/s, 61.0595s/100 iter), 87.6/232ep, loss = 3.43124
-I0510 22:42:54.838886  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.88264 (* 1 = 3.88264 loss)
-I0510 22:42:54.838896  5307 sgd_solver.cpp:172] Iteration 45300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:43:55.382688  5307 solver.cpp:352] Iteration 45400 (1.65172 iter/s, 60.5428s/100 iter), 87.8/232ep, loss = 3.39923
-I0510 22:43:55.382769  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00722 (* 1 = 3.00722 loss)
-I0510 22:43:55.382781  5307 sgd_solver.cpp:172] Iteration 45400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:44:53.739300  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:44:55.335280  5307 solver.cpp:352] Iteration 45500 (1.66801 iter/s, 59.9516s/100 iter), 88/232ep, loss = 3.77631
-I0510 22:44:55.335304  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65193 (* 1 = 3.65193 loss)
-I0510 22:44:55.335312  5307 sgd_solver.cpp:172] Iteration 45500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:45:57.312166  5307 solver.cpp:352] Iteration 45600 (1.61353 iter/s, 61.9758s/100 iter), 88.2/232ep, loss = 3.60661
-I0510 22:45:57.312297  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44258 (* 1 = 3.44258 loss)
-I0510 22:45:57.312321  5307 sgd_solver.cpp:172] Iteration 45600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:47:06.872303  5307 solver.cpp:352] Iteration 45700 (1.43763 iter/s, 69.559s/100 iter), 88.4/232ep, loss = 3.70569
-I0510 22:47:06.872428  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80139 (* 1 = 3.80139 loss)
-I0510 22:47:06.872499  5307 sgd_solver.cpp:172] Iteration 45700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:48:08.359077  5307 solver.cpp:352] Iteration 45800 (1.62639 iter/s, 61.4857s/100 iter), 88.6/232ep, loss = 3.43112
-I0510 22:48:08.359217  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58173 (* 1 = 3.58173 loss)
-I0510 22:48:08.359228  5307 sgd_solver.cpp:172] Iteration 45800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:49:09.033349  5307 solver.cpp:352] Iteration 45900 (1.64817 iter/s, 60.6732s/100 iter), 88.7/232ep, loss = 3.56771
-I0510 22:49:09.033437  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74137 (* 1 = 3.74137 loss)
-I0510 22:49:09.033447  5307 sgd_solver.cpp:172] Iteration 45900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:50:08.859191  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_46000.caffemodel
-I0510 22:50:08.871475  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_46000.solverstate
-I0510 22:50:08.877465  5307 solver.cpp:635] Iteration 46000, Testing net (#0)
-I0510 22:50:49.766000  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:50:50.001467  5307 solver.cpp:747] class AP 1: 0.505791
-I0510 22:50:50.002292  5307 solver.cpp:747] class AP 2: 0.564018
-I0510 22:50:50.012104  5307 solver.cpp:747] class AP 3: 0.350009
-I0510 22:50:50.013630  5307 solver.cpp:747] class AP 4: 0.233533
-I0510 22:50:50.032207  5307 solver.cpp:747] class AP 5: 0.18993
-I0510 22:50:50.032379  5307 solver.cpp:747] class AP 6: 0.539161
-I0510 22:50:50.035763  5307 solver.cpp:747] class AP 7: 0.567182
-I0510 22:50:50.036207  5307 solver.cpp:747] class AP 8: 0.649454
-I0510 22:50:50.061702  5307 solver.cpp:747] class AP 9: 0.276798
-I0510 22:50:50.061992  5307 solver.cpp:747] class AP 10: 0.46867
-I0510 22:50:50.062243  5307 solver.cpp:747] class AP 11: 0.443067
-I0510 22:50:50.062950  5307 solver.cpp:747] class AP 12: 0.539027
-I0510 22:50:50.063304  5307 solver.cpp:747] class AP 13: 0.625951
-I0510 22:50:50.063649  5307 solver.cpp:747] class AP 14: 0.53717
-I0510 22:50:50.126659  5307 solver.cpp:747] class AP 15: 0.567079
-I0510 22:50:50.130455  5307 solver.cpp:747] class AP 16: 0.213157
-I0510 22:50:50.132161  5307 solver.cpp:747] class AP 17: 0.450719
-I0510 22:50:50.133276  5307 solver.cpp:747] class AP 18: 0.382244
-I0510 22:50:50.133790  5307 solver.cpp:747] class AP 19: 0.491094
-I0510 22:50:50.134387  5307 solver.cpp:747] class AP 20: 0.415519
-I0510 22:50:50.134392  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.450479
-I0510 22:50:50.134629  5307 solver.cpp:283] Tests completed in 101.1s
-I0510 22:50:50.690054  5307 solver.cpp:352] Iteration 46000 (0.989124 iter/s, 101.1s/100 iter), 88.9/232ep, loss = 3.5812
-I0510 22:50:50.690084  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04849 (* 1 = 3.04849 loss)
-I0510 22:50:50.690093  5307 sgd_solver.cpp:172] Iteration 46000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:50:59.990258  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:51:52.370064  5307 solver.cpp:352] Iteration 46100 (1.6213 iter/s, 61.6789s/100 iter), 89.1/232ep, loss = 3.6177
-I0510 22:51:52.375166  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14417 (* 1 = 3.14417 loss)
-I0510 22:51:52.375182  5307 sgd_solver.cpp:172] Iteration 46100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:52:52.779439  5307 solver.cpp:352] Iteration 46200 (1.6554 iter/s, 60.4083s/100 iter), 89.3/232ep, loss = 3.5219
-I0510 22:52:52.780040  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57021 (* 1 = 3.57021 loss)
-I0510 22:52:52.780048  5307 sgd_solver.cpp:172] Iteration 46200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:53:52.598860  5307 solver.cpp:352] Iteration 46300 (1.67173 iter/s, 59.8184s/100 iter), 89.5/232ep, loss = 3.51801
-I0510 22:53:52.598942  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.62599 (* 1 = 4.62599 loss)
-I0510 22:53:52.598951  5307 sgd_solver.cpp:172] Iteration 46300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:54:54.260977  5307 solver.cpp:352] Iteration 46400 (1.62177 iter/s, 61.6611s/100 iter), 89.7/232ep, loss = 3.51888
-I0510 22:54:54.261050  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83006 (* 1 = 3.83006 loss)
-I0510 22:54:54.261060  5307 sgd_solver.cpp:172] Iteration 46400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:55:55.168646  5307 solver.cpp:352] Iteration 46500 (1.64186 iter/s, 60.9066s/100 iter), 89.9/232ep, loss = 3.59075
-I0510 22:55:55.168771  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46868 (* 1 = 3.46868 loss)
-I0510 22:55:55.168786  5307 sgd_solver.cpp:172] Iteration 46500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:56:14.018493  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 22:56:55.430907  5307 solver.cpp:352] Iteration 46600 (1.65944 iter/s, 60.2613s/100 iter), 90.1/232ep, loss = 3.5544
-I0510 22:56:55.430966  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53938 (* 1 = 3.53938 loss)
-I0510 22:56:55.430976  5307 sgd_solver.cpp:172] Iteration 46600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:57:55.534490  5307 solver.cpp:352] Iteration 46700 (1.66382 iter/s, 60.1026s/100 iter), 90.3/232ep, loss = 3.58514
-I0510 22:57:55.534706  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84802 (* 1 = 3.84802 loss)
-I0510 22:57:55.534716  5307 sgd_solver.cpp:172] Iteration 46700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:58:56.183460  5307 solver.cpp:352] Iteration 46800 (1.64886 iter/s, 60.648s/100 iter), 90.5/232ep, loss = 3.73727
-I0510 22:58:56.183609  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74044 (* 1 = 3.74044 loss)
-I0510 22:58:56.183665  5307 sgd_solver.cpp:172] Iteration 46800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 22:59:55.746423  5307 solver.cpp:352] Iteration 46900 (1.67892 iter/s, 59.562s/100 iter), 90.7/232ep, loss = 3.45096
-I0510 22:59:55.747187  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21738 (* 1 = 3.21738 loss)
-I0510 22:59:55.747200  5307 sgd_solver.cpp:172] Iteration 46900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:00:56.605301  5307 solver.cpp:352] Iteration 47000 (1.64317 iter/s, 60.8579s/100 iter), 90.9/232ep, loss = 3.43792
-I0510 23:00:56.605358  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27902 (* 1 = 3.27902 loss)
-I0510 23:00:56.605366  5307 sgd_solver.cpp:172] Iteration 47000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:01:25.881090  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:01:56.549991  5307 solver.cpp:352] Iteration 47100 (1.66823 iter/s, 59.9437s/100 iter), 91.1/232ep, loss = 3.42707
-I0510 23:01:56.550885  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03025 (* 1 = 4.03025 loss)
-I0510 23:01:56.550915  5307 sgd_solver.cpp:172] Iteration 47100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:02:57.036665  5307 solver.cpp:352] Iteration 47200 (1.65328 iter/s, 60.4857s/100 iter), 91.3/232ep, loss = 3.7613
-I0510 23:02:57.036772  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40235 (* 1 = 3.40235 loss)
-I0510 23:02:57.036782  5307 sgd_solver.cpp:172] Iteration 47200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:03:56.531098  5307 solver.cpp:352] Iteration 47300 (1.68086 iter/s, 59.4934s/100 iter), 91.5/232ep, loss = 3.48968
-I0510 23:03:56.531193  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.02474 (* 1 = 3.02474 loss)
-I0510 23:03:56.531200  5307 sgd_solver.cpp:172] Iteration 47300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:04:57.948027  5307 solver.cpp:352] Iteration 47400 (1.62824 iter/s, 61.4159s/100 iter), 91.6/232ep, loss = 3.50518
-I0510 23:04:57.948096  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26962 (* 1 = 3.26962 loss)
-I0510 23:04:57.948105  5307 sgd_solver.cpp:172] Iteration 47400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:05:58.396701  5307 solver.cpp:352] Iteration 47500 (1.65432 iter/s, 60.4476s/100 iter), 91.8/232ep, loss = 3.48586
-I0510 23:05:58.397729  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72773 (* 1 = 3.72773 loss)
-I0510 23:05:58.397742  5307 sgd_solver.cpp:172] Iteration 47500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:06:38.718721  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:06:59.352711  5307 solver.cpp:352] Iteration 47600 (1.64055 iter/s, 60.955s/100 iter), 92/232ep, loss = 3.41207
-I0510 23:06:59.352737  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55819 (* 1 = 3.55819 loss)
-I0510 23:06:59.352746  5307 sgd_solver.cpp:172] Iteration 47600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:08:00.463523  5307 solver.cpp:352] Iteration 47700 (1.6364 iter/s, 61.1098s/100 iter), 92.2/232ep, loss = 3.60284
-I0510 23:08:00.463587  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78579 (* 1 = 3.78579 loss)
-I0510 23:08:00.463596  5307 sgd_solver.cpp:172] Iteration 47700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:09:01.200682  5307 solver.cpp:352] Iteration 47800 (1.64647 iter/s, 60.7361s/100 iter), 92.4/232ep, loss = 3.47811
-I0510 23:09:01.200820  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30471 (* 1 = 3.30471 loss)
-I0510 23:09:01.200846  5307 sgd_solver.cpp:172] Iteration 47800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:10:01.542644  5307 solver.cpp:352] Iteration 47900 (1.65725 iter/s, 60.341s/100 iter), 92.6/232ep, loss = 3.50561
-I0510 23:10:01.542717  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78229 (* 1 = 3.78229 loss)
-I0510 23:10:01.542724  5307 sgd_solver.cpp:172] Iteration 47900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:11:01.568513  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_48000.caffemodel
-I0510 23:11:01.588152  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_48000.solverstate
-I0510 23:11:01.593969  5307 solver.cpp:635] Iteration 48000, Testing net (#0)
-I0510 23:11:42.426506  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:11:42.629566  5307 solver.cpp:747] class AP 1: 0.561305
-I0510 23:11:42.630336  5307 solver.cpp:747] class AP 2: 0.631307
-I0510 23:11:42.641363  5307 solver.cpp:747] class AP 3: 0.430626
-I0510 23:11:42.645922  5307 solver.cpp:747] class AP 4: 0.414595
-I0510 23:11:42.659302  5307 solver.cpp:747] class AP 5: 0.252742
-I0510 23:11:42.659512  5307 solver.cpp:747] class AP 6: 0.633689
-I0510 23:11:42.666606  5307 solver.cpp:747] class AP 7: 0.623457
-I0510 23:11:42.667166  5307 solver.cpp:747] class AP 8: 0.719229
-I0510 23:11:42.683421  5307 solver.cpp:747] class AP 9: 0.326172
-I0510 23:11:42.683758  5307 solver.cpp:747] class AP 10: 0.497288
-I0510 23:11:42.684813  5307 solver.cpp:747] class AP 11: 0.421488
-I0510 23:11:42.685557  5307 solver.cpp:747] class AP 12: 0.630654
-I0510 23:11:42.685842  5307 solver.cpp:747] class AP 13: 0.69289
-I0510 23:11:42.686149  5307 solver.cpp:747] class AP 14: 0.646715
-I0510 23:11:42.750618  5307 solver.cpp:747] class AP 15: 0.665926
-I0510 23:11:42.756969  5307 solver.cpp:747] class AP 16: 0.265218
-I0510 23:11:42.757716  5307 solver.cpp:747] class AP 17: 0.466147
-I0510 23:11:42.758103  5307 solver.cpp:747] class AP 18: 0.448701
-I0510 23:11:42.758491  5307 solver.cpp:747] class AP 19: 0.658598
-I0510 23:11:42.759832  5307 solver.cpp:747] class AP 20: 0.479947
-I0510 23:11:42.759840  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.523335
-I0510 23:11:42.760054  5307 solver.cpp:283] Tests completed in 101.216s
-I0510 23:11:43.307546  5307 solver.cpp:352] Iteration 48000 (0.987989 iter/s, 101.216s/100 iter), 92.8/232ep, loss = 3.52073
-I0510 23:11:43.307855  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.35066 (* 1 = 3.35066 loss)
-I0510 23:11:43.307865  5307 sgd_solver.cpp:172] Iteration 48000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:12:33.688110  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:12:43.568645  5307 solver.cpp:352] Iteration 48100 (1.65947 iter/s, 60.26s/100 iter), 93/232ep, loss = 3.5282
-I0510 23:12:43.568722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.78314 (* 1 = 3.78314 loss)
-I0510 23:12:43.568742  5307 sgd_solver.cpp:172] Iteration 48100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:13:43.754045  5307 solver.cpp:352] Iteration 48200 (1.66156 iter/s, 60.1844s/100 iter), 93.2/232ep, loss = 3.47301
-I0510 23:13:43.754109  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.12876 (* 1 = 4.12876 loss)
-I0510 23:13:43.754146  5307 sgd_solver.cpp:172] Iteration 48200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:14:43.993510  5307 solver.cpp:352] Iteration 48300 (1.66007 iter/s, 60.2384s/100 iter), 93.4/232ep, loss = 3.32308
-I0510 23:14:43.993574  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74263 (* 1 = 2.74263 loss)
-I0510 23:14:43.993583  5307 sgd_solver.cpp:172] Iteration 48300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:15:44.278393  5307 solver.cpp:352] Iteration 48400 (1.65882 iter/s, 60.2839s/100 iter), 93.6/232ep, loss = 3.54178
-I0510 23:15:44.278501  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.06438 (* 1 = 3.06438 loss)
-I0510 23:15:44.278522  5307 sgd_solver.cpp:172] Iteration 48400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:16:45.246727  5307 solver.cpp:352] Iteration 48500 (1.64022 iter/s, 60.9673s/100 iter), 93.8/232ep, loss = 3.41037
-I0510 23:16:45.247236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.66525 (* 1 = 2.66525 loss)
-I0510 23:16:45.247246  5307 sgd_solver.cpp:172] Iteration 48500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:17:46.222647  5307 solver.cpp:352] Iteration 48600 (1.64002 iter/s, 60.9749s/100 iter), 94/232ep, loss = 3.44866
-I0510 23:17:46.222743  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.40669 (* 1 = 4.40669 loss)
-I0510 23:17:46.222754  5307 sgd_solver.cpp:172] Iteration 48600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:17:46.884136  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:18:46.703645  5307 solver.cpp:352] Iteration 48700 (1.65344 iter/s, 60.48s/100 iter), 94.2/232ep, loss = 3.52651
-I0510 23:18:46.703832  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07363 (* 1 = 3.07363 loss)
-I0510 23:18:46.703843  5307 sgd_solver.cpp:172] Iteration 48700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:19:46.584103  5307 solver.cpp:352] Iteration 48800 (1.67002 iter/s, 59.8794s/100 iter), 94.4/232ep, loss = 3.60143
-I0510 23:19:46.584192  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.7301 (* 1 = 5.7301 loss)
-I0510 23:19:46.584203  5307 sgd_solver.cpp:172] Iteration 48800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:20:47.415668  5307 solver.cpp:352] Iteration 48900 (1.64391 iter/s, 60.8305s/100 iter), 94.5/232ep, loss = 3.5456
-I0510 23:20:47.415730  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.52771 (* 1 = 4.52771 loss)
-I0510 23:20:47.415740  5307 sgd_solver.cpp:172] Iteration 48900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:21:48.702627  5307 solver.cpp:352] Iteration 49000 (1.6317 iter/s, 61.2859s/100 iter), 94.7/232ep, loss = 3.63742
-I0510 23:21:48.702687  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15913 (* 1 = 3.15913 loss)
-I0510 23:21:48.702695  5307 sgd_solver.cpp:172] Iteration 49000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:22:49.551187  5307 solver.cpp:352] Iteration 49100 (1.64345 iter/s, 60.8475s/100 iter), 94.9/232ep, loss = 3.31566
-I0510 23:22:49.551270  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04667 (* 1 = 3.04667 loss)
-I0510 23:22:49.551278  5307 sgd_solver.cpp:172] Iteration 49100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:22:59.950218  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:23:49.574358  5307 solver.cpp:352] Iteration 49200 (1.66605 iter/s, 60.0222s/100 iter), 95.1/232ep, loss = 3.35315
-I0510 23:23:49.575289  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41286 (* 1 = 3.41286 loss)
-I0510 23:23:49.575297  5307 sgd_solver.cpp:172] Iteration 49200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:24:50.395352  5307 solver.cpp:352] Iteration 49300 (1.6442 iter/s, 60.82s/100 iter), 95.3/232ep, loss = 3.40763
-I0510 23:24:50.395437  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00214 (* 1 = 3.00214 loss)
-I0510 23:24:50.395447  5307 sgd_solver.cpp:172] Iteration 49300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:25:50.372149  5307 solver.cpp:352] Iteration 49400 (1.66734 iter/s, 59.9758s/100 iter), 95.5/232ep, loss = 3.49907
-I0510 23:25:50.372229  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.41385 (* 1 = 4.41385 loss)
-I0510 23:25:50.372244  5307 sgd_solver.cpp:172] Iteration 49400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:26:50.997179  5307 solver.cpp:352] Iteration 49500 (1.64951 iter/s, 60.624s/100 iter), 95.7/232ep, loss = 3.59319
-I0510 23:26:50.997364  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9471 (* 1 = 2.9471 loss)
-I0510 23:26:50.997385  5307 sgd_solver.cpp:172] Iteration 49500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:27:51.858150  5307 solver.cpp:352] Iteration 49600 (1.64312 iter/s, 60.8599s/100 iter), 95.9/232ep, loss = 3.64598
-I0510 23:27:51.858709  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03478 (* 1 = 3.03478 loss)
-I0510 23:27:51.858719  5307 sgd_solver.cpp:172] Iteration 49600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:28:13.082340  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:28:52.739567  5307 solver.cpp:352] Iteration 49700 (1.64257 iter/s, 60.8804s/100 iter), 96.1/232ep, loss = 3.42936
-I0510 23:28:52.740306  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38264 (* 1 = 3.38264 loss)
-I0510 23:28:52.740326  5307 sgd_solver.cpp:172] Iteration 49700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:29:52.705199  5307 solver.cpp:352] Iteration 49800 (1.66765 iter/s, 59.9646s/100 iter), 96.3/232ep, loss = 3.6499
-I0510 23:29:52.705310  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.27572 (* 1 = 4.27572 loss)
-I0510 23:29:52.705402  5307 sgd_solver.cpp:172] Iteration 49800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:30:53.042645  5307 solver.cpp:352] Iteration 49900 (1.65737 iter/s, 60.3364s/100 iter), 96.5/232ep, loss = 3.74318
-I0510 23:30:53.042707  5307 solver.cpp:376]     Train net output #0: mbox_loss = 5.01434 (* 1 = 5.01434 loss)
-I0510 23:30:53.042718  5307 sgd_solver.cpp:172] Iteration 49900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:31:53.273087  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_50000.caffemodel
-I0510 23:31:53.290220  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_50000.solverstate
-I0510 23:31:53.295753  5307 solver.cpp:635] Iteration 50000, Testing net (#0)
-I0510 23:32:33.427985  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:32:33.640146  5307 solver.cpp:747] class AP 1: 0.498915
-I0510 23:32:33.640626  5307 solver.cpp:747] class AP 2: 0.585154
-I0510 23:32:33.648393  5307 solver.cpp:747] class AP 3: 0.417897
-I0510 23:32:33.664778  5307 solver.cpp:747] class AP 4: 0.337787
-I0510 23:32:33.674645  5307 solver.cpp:747] class AP 5: 0.251842
-I0510 23:32:33.676306  5307 solver.cpp:747] class AP 6: 0.628646
-I0510 23:32:33.684816  5307 solver.cpp:747] class AP 7: 0.572198
-I0510 23:32:33.685539  5307 solver.cpp:747] class AP 8: 0.663112
-I0510 23:32:33.709209  5307 solver.cpp:747] class AP 9: 0.282948
-I0510 23:32:33.710723  5307 solver.cpp:747] class AP 10: 0.427062
-I0510 23:32:33.711442  5307 solver.cpp:747] class AP 11: 0.48655
-I0510 23:32:33.712664  5307 solver.cpp:747] class AP 12: 0.581236
-I0510 23:32:33.713263  5307 solver.cpp:747] class AP 13: 0.654671
-I0510 23:32:33.713531  5307 solver.cpp:747] class AP 14: 0.589124
-I0510 23:32:33.759228  5307 solver.cpp:747] class AP 15: 0.633411
-I0510 23:32:33.766373  5307 solver.cpp:747] class AP 16: 0.243572
-I0510 23:32:33.774631  5307 solver.cpp:747] class AP 17: 0.457656
-I0510 23:32:33.775758  5307 solver.cpp:747] class AP 18: 0.471969
-I0510 23:32:33.776513  5307 solver.cpp:747] class AP 19: 0.627506
-I0510 23:32:33.778980  5307 solver.cpp:747] class AP 20: 0.464373
-I0510 23:32:33.778993  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.493781
-I0510 23:32:33.779156  5307 solver.cpp:283] Tests completed in 100.735s
-I0510 23:32:34.377696  5307 solver.cpp:352] Iteration 50000 (0.992705 iter/s, 100.735s/100 iter), 96.7/232ep, loss = 3.42507
-I0510 23:32:34.377723  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.44672 (* 1 = 4.44672 loss)
-I0510 23:32:34.377730  5307 sgd_solver.cpp:172] Iteration 50000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:33:35.872683  5307 solver.cpp:352] Iteration 50100 (1.62618 iter/s, 61.4939s/100 iter), 96.9/232ep, loss = 3.44612
-I0510 23:33:35.873013  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74043 (* 1 = 3.74043 loss)
-I0510 23:33:35.873035  5307 sgd_solver.cpp:172] Iteration 50100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:34:07.855278  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:34:36.364137  5307 solver.cpp:352] Iteration 50200 (1.65315 iter/s, 60.4904s/100 iter), 97.1/232ep, loss = 3.55674
-I0510 23:34:36.364169  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.44396 (* 1 = 4.44396 loss)
-I0510 23:34:36.364176  5307 sgd_solver.cpp:172] Iteration 50200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:35:35.969579  5307 solver.cpp:352] Iteration 50300 (1.67773 iter/s, 59.6044s/100 iter), 97.3/232ep, loss = 3.51906
-I0510 23:35:35.969683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.32653 (* 1 = 4.32653 loss)
-I0510 23:35:35.969761  5307 sgd_solver.cpp:172] Iteration 50300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:36:36.370111  5307 solver.cpp:352] Iteration 50400 (1.65564 iter/s, 60.3995s/100 iter), 97.4/232ep, loss = 3.47102
-I0510 23:36:36.370185  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71015 (* 1 = 3.71015 loss)
-I0510 23:36:36.370198  5307 sgd_solver.cpp:172] Iteration 50400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:37:37.328444  5307 solver.cpp:352] Iteration 50500 (1.64049 iter/s, 60.9573s/100 iter), 97.6/232ep, loss = 3.49171
-I0510 23:37:37.328510  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7692 (* 1 = 2.7692 loss)
-I0510 23:37:37.328521  5307 sgd_solver.cpp:172] Iteration 50500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:38:37.899471  5307 solver.cpp:352] Iteration 50600 (1.65098 iter/s, 60.57s/100 iter), 97.8/232ep, loss = 3.53187
-I0510 23:38:37.899546  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51964 (* 1 = 3.51964 loss)
-I0510 23:38:37.899555  5307 sgd_solver.cpp:172] Iteration 50600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:39:19.902827  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:39:38.853461  5307 solver.cpp:352] Iteration 50700 (1.64061 iter/s, 60.953s/100 iter), 98/232ep, loss = 3.48521
-I0510 23:39:38.853549  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.83649 (* 1 = 3.83649 loss)
-I0510 23:39:38.853569  5307 sgd_solver.cpp:172] Iteration 50700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:40:39.750469  5307 solver.cpp:352] Iteration 50800 (1.64214 iter/s, 60.896s/100 iter), 98.2/232ep, loss = 3.33293
-I0510 23:40:39.750550  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.94241 (* 1 = 3.94241 loss)
-I0510 23:40:39.750560  5307 sgd_solver.cpp:172] Iteration 50800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:41:40.515030  5307 solver.cpp:352] Iteration 50900 (1.64572 iter/s, 60.7635s/100 iter), 98.4/232ep, loss = 3.48554
-I0510 23:41:40.515100  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14265 (* 1 = 3.14265 loss)
-I0510 23:41:40.515107  5307 sgd_solver.cpp:172] Iteration 50900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:42:41.899195  5307 solver.cpp:352] Iteration 51000 (1.62911 iter/s, 61.3831s/100 iter), 98.6/232ep, loss = 3.37388
-I0510 23:42:41.899366  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59194 (* 1 = 3.59194 loss)
-I0510 23:42:41.899385  5307 sgd_solver.cpp:172] Iteration 51000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:43:43.308969  5307 solver.cpp:352] Iteration 51100 (1.62843 iter/s, 61.4087s/100 iter), 98.8/232ep, loss = 3.53026
-I0510 23:43:43.309039  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1463 (* 1 = 3.1463 loss)
-I0510 23:43:43.309047  5307 sgd_solver.cpp:172] Iteration 51100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:44:37.293272  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:44:45.357547  5307 solver.cpp:352] Iteration 51200 (1.61167 iter/s, 62.0475s/100 iter), 99/232ep, loss = 3.4011
-I0510 23:44:45.357604  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56569 (* 1 = 3.56569 loss)
-I0510 23:44:45.357622  5307 sgd_solver.cpp:172] Iteration 51200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:45:47.347355  5307 solver.cpp:352] Iteration 51300 (1.6132 iter/s, 61.9888s/100 iter), 99.2/232ep, loss = 3.5833
-I0510 23:45:47.347461  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82223 (* 1 = 3.82223 loss)
-I0510 23:45:47.347473  5307 sgd_solver.cpp:172] Iteration 51300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:46:49.121846  5307 solver.cpp:352] Iteration 51400 (1.61882 iter/s, 61.7735s/100 iter), 99.4/232ep, loss = 3.3464
-I0510 23:46:49.122498  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88903 (* 1 = 2.88903 loss)
-I0510 23:46:49.122505  5307 sgd_solver.cpp:172] Iteration 51400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:47:50.326306  5307 solver.cpp:352] Iteration 51500 (1.6339 iter/s, 61.2034s/100 iter), 99.6/232ep, loss = 3.49587
-I0510 23:47:50.326407  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25812 (* 1 = 3.25812 loss)
-I0510 23:47:50.326422  5307 sgd_solver.cpp:172] Iteration 51500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:48:50.905516  5307 solver.cpp:352] Iteration 51600 (1.65076 iter/s, 60.5782s/100 iter), 99.8/232ep, loss = 3.49921
-I0510 23:48:50.905804  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91085 (* 1 = 2.91085 loss)
-I0510 23:48:50.905815  5307 sgd_solver.cpp:172] Iteration 51600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:49:52.094168  5307 solver.cpp:352] Iteration 51700 (1.63432 iter/s, 61.1876s/100 iter), 100/232ep, loss = 3.39004
-I0510 23:49:52.094250  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73419 (* 1 = 2.73419 loss)
-I0510 23:49:52.094262  5307 sgd_solver.cpp:172] Iteration 51700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:49:53.973093  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:50:52.856155  5307 solver.cpp:352] Iteration 51800 (1.64579 iter/s, 60.761s/100 iter), 100.2/232ep, loss = 3.36415
-I0510 23:50:52.856760  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68732 (* 1 = 3.68732 loss)
-I0510 23:50:52.856777  5307 sgd_solver.cpp:172] Iteration 51800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:51:54.498759  5307 solver.cpp:352] Iteration 51900 (1.62228 iter/s, 61.6416s/100 iter), 100.3/232ep, loss = 3.44527
-I0510 23:51:54.498867  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07261 (* 1 = 3.07261 loss)
-I0510 23:51:54.498878  5307 sgd_solver.cpp:172] Iteration 51900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:52:55.465734  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_52000.caffemodel
-I0510 23:52:55.483183  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_52000.solverstate
-I0510 23:52:55.490092  5307 solver.cpp:635] Iteration 52000, Testing net (#0)
-I0510 23:53:35.352563  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:53:35.534699  5307 solver.cpp:747] class AP 1: 0.518978
-I0510 23:53:35.535761  5307 solver.cpp:747] class AP 2: 0.636386
-I0510 23:53:35.548604  5307 solver.cpp:747] class AP 3: 0.366596
-I0510 23:53:35.551271  5307 solver.cpp:747] class AP 4: 0.37599
-I0510 23:53:35.572114  5307 solver.cpp:747] class AP 5: 0.227827
-I0510 23:53:35.572397  5307 solver.cpp:747] class AP 6: 0.615003
-I0510 23:53:35.578673  5307 solver.cpp:747] class AP 7: 0.608683
-I0510 23:53:35.579653  5307 solver.cpp:747] class AP 8: 0.675214
-I0510 23:53:35.606160  5307 solver.cpp:747] class AP 9: 0.318541
-I0510 23:53:35.606945  5307 solver.cpp:747] class AP 10: 0.467367
-I0510 23:53:35.607692  5307 solver.cpp:747] class AP 11: 0.484164
-I0510 23:53:35.608516  5307 solver.cpp:747] class AP 12: 0.578948
-I0510 23:53:35.608963  5307 solver.cpp:747] class AP 13: 0.713434
-I0510 23:53:35.609189  5307 solver.cpp:747] class AP 14: 0.620618
-I0510 23:53:35.680815  5307 solver.cpp:747] class AP 15: 0.642361
-I0510 23:53:35.699427  5307 solver.cpp:747] class AP 16: 0.23837
-I0510 23:53:35.703963  5307 solver.cpp:747] class AP 17: 0.460253
-I0510 23:53:35.705580  5307 solver.cpp:747] class AP 18: 0.542439
-I0510 23:53:35.706110  5307 solver.cpp:747] class AP 19: 0.657206
-I0510 23:53:35.707695  5307 solver.cpp:747] class AP 20: 0.473692
-I0510 23:53:35.707732  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.511103
-I0510 23:53:35.707897  5307 solver.cpp:283] Tests completed in 101.207s
-I0510 23:53:36.340836  5307 solver.cpp:352] Iteration 52000 (0.98807 iter/s, 101.207s/100 iter), 100.5/232ep, loss = 3.33154
-I0510 23:53:36.340910  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54616 (* 1 = 3.54616 loss)
-I0510 23:53:36.340932  5307 sgd_solver.cpp:172] Iteration 52000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:54:44.919634  5307 solver.cpp:352] Iteration 52100 (1.4582 iter/s, 68.5776s/100 iter), 100.7/232ep, loss = 3.29883
-I0510 23:54:44.922762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.15171 (* 1 = 4.15171 loss)
-I0510 23:54:44.922811  5307 sgd_solver.cpp:172] Iteration 52100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:55:47.649695  5307 solver.cpp:352] Iteration 52200 (1.59416 iter/s, 62.729s/100 iter), 100.9/232ep, loss = 3.4715
-I0510 23:55:47.649773  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65583 (* 1 = 3.65583 loss)
-I0510 23:55:47.649786  5307 sgd_solver.cpp:172] Iteration 52200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:56:00.402654  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0510 23:56:47.282253  5307 solver.cpp:352] Iteration 52300 (1.67696 iter/s, 59.6315s/100 iter), 101.1/232ep, loss = 3.6139
-I0510 23:56:47.282346  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04672 (* 1 = 3.04672 loss)
-I0510 23:56:47.282354  5307 sgd_solver.cpp:172] Iteration 52300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:57:48.046723  5307 solver.cpp:352] Iteration 52400 (1.64573 iter/s, 60.7634s/100 iter), 101.3/232ep, loss = 3.62294
-I0510 23:57:48.046809  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25532 (* 1 = 3.25532 loss)
-I0510 23:57:48.046818  5307 sgd_solver.cpp:172] Iteration 52400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:58:48.641021  5307 solver.cpp:352] Iteration 52500 (1.65035 iter/s, 60.5933s/100 iter), 101.5/232ep, loss = 3.43837
-I0510 23:58:48.641079  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36506 (* 1 = 3.36506 loss)
-I0510 23:58:48.641089  5307 sgd_solver.cpp:172] Iteration 52500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0510 23:59:49.140475  5307 solver.cpp:352] Iteration 52600 (1.65294 iter/s, 60.4984s/100 iter), 101.7/232ep, loss = 3.55552
-I0510 23:59:49.140640  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.77614 (* 1 = 3.77614 loss)
-I0510 23:59:49.140661  5307 sgd_solver.cpp:172] Iteration 52600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:00:49.939690  5307 solver.cpp:352] Iteration 52700 (1.64479 iter/s, 60.7982s/100 iter), 101.9/232ep, loss = 3.40258
-I0511 00:00:49.939792  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.58967 (* 1 = 2.58967 loss)
-I0511 00:00:49.939841  5307 sgd_solver.cpp:172] Iteration 52700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:01:13.674773  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:01:51.234668  5307 solver.cpp:352] Iteration 52800 (1.63148 iter/s, 61.2939s/100 iter), 102.1/232ep, loss = 3.52778
-I0511 00:01:51.235667  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.6839 (* 1 = 3.6839 loss)
-I0511 00:01:51.235677  5307 sgd_solver.cpp:172] Iteration 52800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:02:52.080087  5307 solver.cpp:352] Iteration 52900 (1.64354 iter/s, 60.8444s/100 iter), 102.3/232ep, loss = 3.51606
-I0511 00:02:52.080184  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.61498 (* 1 = 2.61498 loss)
-I0511 00:02:52.080193  5307 sgd_solver.cpp:172] Iteration 52900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:03:51.713644  5307 solver.cpp:352] Iteration 53000 (1.67694 iter/s, 59.6325s/100 iter), 102.5/232ep, loss = 3.56518
-I0511 00:03:51.713754  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.98872 (* 1 = 2.98872 loss)
-I0511 00:03:51.713768  5307 sgd_solver.cpp:172] Iteration 53000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:04:51.912704  5307 solver.cpp:352] Iteration 53100 (1.66118 iter/s, 60.198s/100 iter), 102.7/232ep, loss = 3.60422
-I0511 00:04:51.912780  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.43261 (* 1 = 4.43261 loss)
-I0511 00:04:51.912791  5307 sgd_solver.cpp:172] Iteration 53100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:05:52.756698  5307 solver.cpp:352] Iteration 53200 (1.64358 iter/s, 60.843s/100 iter), 102.9/232ep, loss = 3.65099
-I0511 00:05:52.756784  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59315 (* 1 = 3.59315 loss)
-I0511 00:05:52.756800  5307 sgd_solver.cpp:172] Iteration 53200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:06:26.347018  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:06:53.908424  5307 solver.cpp:352] Iteration 53300 (1.6353 iter/s, 61.1507s/100 iter), 103.1/232ep, loss = 3.49781
-I0511 00:06:53.908447  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37101 (* 1 = 3.37101 loss)
-I0511 00:06:53.908455  5307 sgd_solver.cpp:172] Iteration 53300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:07:55.388799  5307 solver.cpp:352] Iteration 53400 (1.62656 iter/s, 61.4793s/100 iter), 103.2/232ep, loss = 3.4449
-I0511 00:07:55.388917  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.35449 (* 1 = 3.35449 loss)
-I0511 00:07:55.388942  5307 sgd_solver.cpp:172] Iteration 53400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:08:55.777259  5307 solver.cpp:352] Iteration 53500 (1.65597 iter/s, 60.3874s/100 iter), 103.4/232ep, loss = 3.47036
-I0511 00:08:55.777381  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.902 (* 1 = 3.902 loss)
-I0511 00:08:55.777406  5307 sgd_solver.cpp:172] Iteration 53500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:09:55.897388  5307 solver.cpp:352] Iteration 53600 (1.66336 iter/s, 60.1191s/100 iter), 103.6/232ep, loss = 3.55858
-I0511 00:09:55.897610  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.62222 (* 1 = 2.62222 loss)
-I0511 00:09:55.897622  5307 sgd_solver.cpp:172] Iteration 53600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:10:55.804698  5307 solver.cpp:352] Iteration 53700 (1.66927 iter/s, 59.9063s/100 iter), 103.8/232ep, loss = 3.53354
-I0511 00:10:55.804759  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07751 (* 1 = 3.07751 loss)
-I0511 00:10:55.804765  5307 sgd_solver.cpp:172] Iteration 53700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:11:39.663512  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:11:56.229519  5307 solver.cpp:352] Iteration 53800 (1.65498 iter/s, 60.4238s/100 iter), 104/232ep, loss = 3.35147
-I0511 00:11:56.229543  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7491 (* 1 = 2.7491 loss)
-I0511 00:11:56.229549  5307 sgd_solver.cpp:172] Iteration 53800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:12:56.770020  5307 solver.cpp:352] Iteration 53900 (1.65181 iter/s, 60.5395s/100 iter), 104.2/232ep, loss = 3.51365
-I0511 00:12:56.770087  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95267 (* 1 = 2.95267 loss)
-I0511 00:12:56.770093  5307 sgd_solver.cpp:172] Iteration 53900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:13:56.372295  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_54000.caffemodel
-I0511 00:13:56.389125  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_54000.solverstate
-I0511 00:13:56.394472  5307 solver.cpp:635] Iteration 54000, Testing net (#0)
-I0511 00:14:37.672940  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:14:37.919394  5307 solver.cpp:747] class AP 1: 0.525506
-I0511 00:14:37.919723  5307 solver.cpp:747] class AP 2: 0.623355
-I0511 00:14:37.921825  5307 solver.cpp:747] class AP 3: 0.432165
-I0511 00:14:37.923365  5307 solver.cpp:747] class AP 4: 0.382349
-I0511 00:14:37.949615  5307 solver.cpp:747] class AP 5: 0.247984
-I0511 00:14:37.949892  5307 solver.cpp:747] class AP 6: 0.653941
-I0511 00:14:37.955955  5307 solver.cpp:747] class AP 7: 0.630902
-I0511 00:14:37.956923  5307 solver.cpp:747] class AP 8: 0.71827
-I0511 00:14:37.979024  5307 solver.cpp:747] class AP 9: 0.326747
-I0511 00:14:37.979353  5307 solver.cpp:747] class AP 10: 0.480525
-I0511 00:14:37.980017  5307 solver.cpp:747] class AP 11: 0.530881
-I0511 00:14:37.980465  5307 solver.cpp:747] class AP 12: 0.623067
-I0511 00:14:37.980967  5307 solver.cpp:747] class AP 13: 0.69642
-I0511 00:14:37.981154  5307 solver.cpp:747] class AP 14: 0.665992
-I0511 00:14:38.042522  5307 solver.cpp:747] class AP 15: 0.670577
-I0511 00:14:38.047544  5307 solver.cpp:747] class AP 16: 0.282663
-I0511 00:14:38.048463  5307 solver.cpp:747] class AP 17: 0.492775
-I0511 00:14:38.049235  5307 solver.cpp:747] class AP 18: 0.524552
-I0511 00:14:38.050112  5307 solver.cpp:747] class AP 19: 0.65139
-I0511 00:14:38.052436  5307 solver.cpp:747] class AP 20: 0.517409
-I0511 00:14:38.052445  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.533873
-I0511 00:14:38.052774  5307 solver.cpp:283] Tests completed in 101.281s
-I0511 00:14:38.590441  5307 solver.cpp:352] Iteration 54000 (0.987352 iter/s, 101.281s/100 iter), 104.4/232ep, loss = 3.6458
-I0511 00:14:38.590467  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.11997 (* 1 = 4.11997 loss)
-I0511 00:14:38.590474  5307 sgd_solver.cpp:172] Iteration 54000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:15:37.921257  5307 solver.cpp:352] Iteration 54100 (1.68549 iter/s, 59.3298s/100 iter), 104.6/232ep, loss = 3.58635
-I0511 00:15:37.921360  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27227 (* 1 = 3.27227 loss)
-I0511 00:15:37.921370  5307 sgd_solver.cpp:172] Iteration 54100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:16:37.701010  5307 solver.cpp:352] Iteration 54200 (1.67284 iter/s, 59.7787s/100 iter), 104.8/232ep, loss = 3.72543
-I0511 00:16:37.702693  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84609 (* 1 = 3.84609 loss)
-I0511 00:16:37.702716  5307 sgd_solver.cpp:172] Iteration 54200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:17:31.908587  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:17:38.575501  5307 solver.cpp:352] Iteration 54300 (1.64275 iter/s, 60.8734s/100 iter), 105/232ep, loss = 3.60018
-I0511 00:17:38.575531  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38112 (* 1 = 3.38112 loss)
-I0511 00:17:38.575538  5307 sgd_solver.cpp:172] Iteration 54300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:18:38.992295  5307 solver.cpp:352] Iteration 54400 (1.6552 iter/s, 60.4158s/100 iter), 105.2/232ep, loss = 3.65693
-I0511 00:18:38.992363  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51708 (* 1 = 2.51708 loss)
-I0511 00:18:38.992372  5307 sgd_solver.cpp:172] Iteration 54400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:19:39.192565  5307 solver.cpp:352] Iteration 54500 (1.66115 iter/s, 60.1992s/100 iter), 105.4/232ep, loss = 3.34804
-I0511 00:19:39.192680  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.07612 (* 1 = 4.07612 loss)
-I0511 00:19:39.192697  5307 sgd_solver.cpp:172] Iteration 54500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:20:39.840927  5307 solver.cpp:352] Iteration 54600 (1.64888 iter/s, 60.6473s/100 iter), 105.6/232ep, loss = 3.49878
-I0511 00:20:39.841084  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.6027 (* 1 = 4.6027 loss)
-I0511 00:20:39.841110  5307 sgd_solver.cpp:172] Iteration 54600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:21:40.356724  5307 solver.cpp:352] Iteration 54700 (1.65249 iter/s, 60.5148s/100 iter), 105.8/232ep, loss = 3.41457
-I0511 00:21:40.356827  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73008 (* 1 = 2.73008 loss)
-I0511 00:21:40.356837  5307 sgd_solver.cpp:172] Iteration 54700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:22:40.322903  5307 solver.cpp:352] Iteration 54800 (1.66763 iter/s, 59.9652s/100 iter), 106/232ep, loss = 3.46247
-I0511 00:22:40.324194  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.50552 (* 1 = 2.50552 loss)
-I0511 00:22:40.324211  5307 sgd_solver.cpp:172] Iteration 54800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:22:44.903548  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:23:40.294348  5307 solver.cpp:352] Iteration 54900 (1.66749 iter/s, 59.9704s/100 iter), 106.1/232ep, loss = 3.46535
-I0511 00:23:40.294414  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37254 (* 1 = 3.37254 loss)
-I0511 00:23:40.294423  5307 sgd_solver.cpp:172] Iteration 54900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:24:40.674048  5307 solver.cpp:352] Iteration 55000 (1.65621 iter/s, 60.3787s/100 iter), 106.3/232ep, loss = 3.60302
-I0511 00:24:40.674123  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72011 (* 1 = 3.72011 loss)
-I0511 00:24:40.674132  5307 sgd_solver.cpp:172] Iteration 55000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:25:42.052397  5307 solver.cpp:352] Iteration 55100 (1.62927 iter/s, 61.3773s/100 iter), 106.5/232ep, loss = 3.48589
-I0511 00:25:42.052486  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.69904 (* 1 = 2.69904 loss)
-I0511 00:25:42.052500  5307 sgd_solver.cpp:172] Iteration 55100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:26:41.886087  5307 solver.cpp:352] Iteration 55200 (1.67133 iter/s, 59.8327s/100 iter), 106.7/232ep, loss = 3.52104
-I0511 00:26:41.886149  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02414 (* 1 = 4.02414 loss)
-I0511 00:26:41.886157  5307 sgd_solver.cpp:172] Iteration 55200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:27:42.614260  5307 solver.cpp:352] Iteration 55300 (1.64671 iter/s, 60.7271s/100 iter), 106.9/232ep, loss = 3.50302
-I0511 00:27:42.614336  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99667 (* 1 = 2.99667 loss)
-I0511 00:27:42.614346  5307 sgd_solver.cpp:172] Iteration 55300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:27:57.643421  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:28:42.579155  5307 solver.cpp:352] Iteration 55400 (1.66767 iter/s, 59.9639s/100 iter), 107.1/232ep, loss = 3.60342
-I0511 00:28:42.579264  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53387 (* 1 = 3.53387 loss)
-I0511 00:28:42.579288  5307 sgd_solver.cpp:172] Iteration 55400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:29:43.274452  5307 solver.cpp:352] Iteration 55500 (1.6476 iter/s, 60.6943s/100 iter), 107.3/232ep, loss = 3.50229
-I0511 00:29:43.274533  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57112 (* 1 = 3.57112 loss)
-I0511 00:29:43.274541  5307 sgd_solver.cpp:172] Iteration 55500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:30:43.800295  5307 solver.cpp:352] Iteration 55600 (1.65222 iter/s, 60.5248s/100 iter), 107.5/232ep, loss = 3.44192
-I0511 00:30:43.804119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46049 (* 1 = 3.46049 loss)
-I0511 00:30:43.804157  5307 sgd_solver.cpp:172] Iteration 55600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:31:44.431244  5307 solver.cpp:352] Iteration 55700 (1.64935 iter/s, 60.6299s/100 iter), 107.7/232ep, loss = 3.45246
-I0511 00:31:44.431331  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.46113 (* 1 = 2.46113 loss)
-I0511 00:31:44.431356  5307 sgd_solver.cpp:172] Iteration 55700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:32:45.694702  5307 solver.cpp:352] Iteration 55800 (1.63232 iter/s, 61.2624s/100 iter), 107.9/232ep, loss = 3.40326
-I0511 00:32:45.694761  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.0129 (* 1 = 3.0129 loss)
-I0511 00:32:45.694770  5307 sgd_solver.cpp:172] Iteration 55800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:33:10.587299  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:33:46.352715  5307 solver.cpp:352] Iteration 55900 (1.64862 iter/s, 60.6569s/100 iter), 108.1/232ep, loss = 3.54755
-I0511 00:33:46.352850  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69712 (* 1 = 3.69712 loss)
-I0511 00:33:46.352869  5307 sgd_solver.cpp:172] Iteration 55900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:34:46.579649  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_56000.caffemodel
-I0511 00:34:46.599112  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_56000.solverstate
-I0511 00:34:46.605146  5307 solver.cpp:635] Iteration 56000, Testing net (#0)
-I0511 00:35:27.777395  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:35:28.025400  5307 solver.cpp:747] class AP 1: 0.535526
-I0511 00:35:28.026069  5307 solver.cpp:747] class AP 2: 0.638728
-I0511 00:35:28.036048  5307 solver.cpp:747] class AP 3: 0.429233
-I0511 00:35:28.038990  5307 solver.cpp:747] class AP 4: 0.333136
-I0511 00:35:28.053520  5307 solver.cpp:747] class AP 5: 0.211951
-I0511 00:35:28.053802  5307 solver.cpp:747] class AP 6: 0.661569
-I0511 00:35:28.064337  5307 solver.cpp:747] class AP 7: 0.616551
-I0511 00:35:28.064812  5307 solver.cpp:747] class AP 8: 0.672303
-I0511 00:35:28.090167  5307 solver.cpp:747] class AP 9: 0.349538
-I0511 00:35:28.090848  5307 solver.cpp:747] class AP 10: 0.511583
-I0511 00:35:28.091517  5307 solver.cpp:747] class AP 11: 0.503518
-I0511 00:35:28.092128  5307 solver.cpp:747] class AP 12: 0.58544
-I0511 00:35:28.092429  5307 solver.cpp:747] class AP 13: 0.694684
-I0511 00:35:28.092682  5307 solver.cpp:747] class AP 14: 0.630494
-I0511 00:35:28.145862  5307 solver.cpp:747] class AP 15: 0.655244
-I0511 00:35:28.150086  5307 solver.cpp:747] class AP 16: 0.245485
-I0511 00:35:28.153009  5307 solver.cpp:747] class AP 17: 0.516143
-I0511 00:35:28.153900  5307 solver.cpp:747] class AP 18: 0.465221
-I0511 00:35:28.154693  5307 solver.cpp:747] class AP 19: 0.633202
-I0511 00:35:28.155895  5307 solver.cpp:747] class AP 20: 0.515829
-I0511 00:35:28.155906  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.520269
-I0511 00:35:28.156122  5307 solver.cpp:283] Tests completed in 101.802s
-I0511 00:35:28.712455  5307 solver.cpp:352] Iteration 56000 (0.982302 iter/s, 101.802s/100 iter), 108.3/232ep, loss = 3.7071
-I0511 00:35:28.712481  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10523 (* 1 = 3.10523 loss)
-I0511 00:35:28.712489  5307 sgd_solver.cpp:172] Iteration 56000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:36:28.768484  5307 solver.cpp:352] Iteration 56100 (1.66514 iter/s, 60.055s/100 iter), 108.5/232ep, loss = 3.5618
-I0511 00:36:28.768560  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67482 (* 1 = 3.67482 loss)
-I0511 00:36:28.768570  5307 sgd_solver.cpp:172] Iteration 56100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:37:29.082165  5307 solver.cpp:352] Iteration 56200 (1.65803 iter/s, 60.3126s/100 iter), 108.7/232ep, loss = 3.36023
-I0511 00:37:29.083581  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33626 (* 1 = 3.33626 loss)
-I0511 00:37:29.083616  5307 sgd_solver.cpp:172] Iteration 56200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:38:30.046433  5307 solver.cpp:352] Iteration 56300 (1.64033 iter/s, 60.9632s/100 iter), 108.9/232ep, loss = 3.67072
-I0511 00:38:30.046625  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69164 (* 1 = 3.69164 loss)
-I0511 00:38:30.046633  5307 sgd_solver.cpp:172] Iteration 56300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:39:05.675428  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:39:29.936378  5307 solver.cpp:352] Iteration 56400 (1.66976 iter/s, 59.8889s/100 iter), 109/232ep, loss = 3.347
-I0511 00:39:29.936400  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32941 (* 1 = 3.32941 loss)
-I0511 00:39:29.936405  5307 sgd_solver.cpp:172] Iteration 56400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:40:30.386986  5307 solver.cpp:352] Iteration 56500 (1.65427 iter/s, 60.4496s/100 iter), 109.2/232ep, loss = 3.47285
-I0511 00:40:30.387064  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59983 (* 1 = 3.59983 loss)
-I0511 00:40:30.387073  5307 sgd_solver.cpp:172] Iteration 56500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:41:30.451970  5307 solver.cpp:352] Iteration 56600 (1.66489 iter/s, 60.064s/100 iter), 109.4/232ep, loss = 3.34361
-I0511 00:41:30.452033  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31377 (* 1 = 3.31377 loss)
-I0511 00:41:30.452042  5307 sgd_solver.cpp:172] Iteration 56600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:42:31.110832  5307 solver.cpp:352] Iteration 56700 (1.64859 iter/s, 60.6578s/100 iter), 109.6/232ep, loss = 3.63717
-I0511 00:42:31.110963  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51525 (* 1 = 3.51525 loss)
-I0511 00:42:31.110978  5307 sgd_solver.cpp:172] Iteration 56700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:43:31.553923  5307 solver.cpp:352] Iteration 56800 (1.65448 iter/s, 60.4421s/100 iter), 109.8/232ep, loss = 3.71151
-I0511 00:43:31.553988  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.05874 (* 1 = 4.05874 loss)
-I0511 00:43:31.553997  5307 sgd_solver.cpp:172] Iteration 56800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:44:18.155795  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:44:32.454998  5307 solver.cpp:352] Iteration 56900 (1.64204 iter/s, 60.9s/100 iter), 110/232ep, loss = 3.56385
-I0511 00:44:32.455027  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38724 (* 1 = 3.38724 loss)
-I0511 00:44:32.455034  5307 sgd_solver.cpp:172] Iteration 56900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:45:32.628466  5307 solver.cpp:352] Iteration 57000 (1.66189 iter/s, 60.1725s/100 iter), 110.2/232ep, loss = 3.36299
-I0511 00:45:32.628590  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87368 (* 1 = 3.87368 loss)
-I0511 00:45:32.628612  5307 sgd_solver.cpp:172] Iteration 57000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:46:33.259104  5307 solver.cpp:352] Iteration 57100 (1.64936 iter/s, 60.6296s/100 iter), 110.4/232ep, loss = 3.57393
-I0511 00:46:33.259186  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.70297 (* 1 = 3.70297 loss)
-I0511 00:46:33.259202  5307 sgd_solver.cpp:172] Iteration 57100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:47:34.351581  5307 solver.cpp:352] Iteration 57200 (1.63689 iter/s, 61.0914s/100 iter), 110.6/232ep, loss = 3.46394
-I0511 00:47:34.351634  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81547 (* 1 = 2.81547 loss)
-I0511 00:47:34.351642  5307 sgd_solver.cpp:172] Iteration 57200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:48:34.817998  5307 solver.cpp:352] Iteration 57300 (1.65384 iter/s, 60.4654s/100 iter), 110.8/232ep, loss = 3.3979
-I0511 00:48:34.818073  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7929 (* 1 = 2.7929 loss)
-I0511 00:48:34.818079  5307 sgd_solver.cpp:172] Iteration 57300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:49:32.352228  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:49:36.503605  5307 solver.cpp:352] Iteration 57400 (1.62115 iter/s, 61.6846s/100 iter), 111/232ep, loss = 3.83276
-I0511 00:49:36.503638  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1509 (* 1 = 3.1509 loss)
-I0511 00:49:36.503646  5307 sgd_solver.cpp:172] Iteration 57400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:50:38.050436  5307 solver.cpp:352] Iteration 57500 (1.62481 iter/s, 61.5458s/100 iter), 111.2/232ep, loss = 3.42789
-I0511 00:50:38.050493  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65941 (* 1 = 3.65941 loss)
-I0511 00:50:38.050503  5307 sgd_solver.cpp:172] Iteration 57500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:51:40.025753  5307 solver.cpp:352] Iteration 57600 (1.61357 iter/s, 61.9743s/100 iter), 111.4/232ep, loss = 3.73921
-I0511 00:51:40.026000  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.20821 (* 1 = 4.20821 loss)
-I0511 00:51:40.026042  5307 sgd_solver.cpp:172] Iteration 57600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:52:41.653494  5307 solver.cpp:352] Iteration 57700 (1.62267 iter/s, 61.6267s/100 iter), 111.6/232ep, loss = 3.42248
-I0511 00:52:41.653587  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36359 (* 1 = 3.36359 loss)
-I0511 00:52:41.653602  5307 sgd_solver.cpp:172] Iteration 57700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:53:42.557371  5307 solver.cpp:352] Iteration 57800 (1.64196 iter/s, 60.9028s/100 iter), 111.8/232ep, loss = 3.44499
-I0511 00:53:42.557584  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.86643 (* 1 = 3.86643 loss)
-I0511 00:53:42.557593  5307 sgd_solver.cpp:172] Iteration 57800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:54:43.308697  5307 solver.cpp:352] Iteration 57900 (1.64608 iter/s, 60.7503s/100 iter), 111.9/232ep, loss = 3.27644
-I0511 00:54:43.308866  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.78733 (* 1 = 2.78733 loss)
-I0511 00:54:43.308876  5307 sgd_solver.cpp:172] Iteration 57900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:54:50.058835  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:55:43.244065  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_58000.caffemodel
-I0511 00:55:43.258394  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_58000.solverstate
-I0511 00:55:43.266721  5307 solver.cpp:635] Iteration 58000, Testing net (#0)
-I0511 00:56:24.250465  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 00:56:24.440966  5307 solver.cpp:747] class AP 1: 0.536921
-I0511 00:56:24.441691  5307 solver.cpp:747] class AP 2: 0.636741
-I0511 00:56:24.448153  5307 solver.cpp:747] class AP 3: 0.475505
-I0511 00:56:24.453078  5307 solver.cpp:747] class AP 4: 0.408649
-I0511 00:56:24.466481  5307 solver.cpp:747] class AP 5: 0.271112
-I0511 00:56:24.466751  5307 solver.cpp:747] class AP 6: 0.634191
-I0511 00:56:24.474997  5307 solver.cpp:747] class AP 7: 0.636721
-I0511 00:56:24.475579  5307 solver.cpp:747] class AP 8: 0.72689
-I0511 00:56:24.498325  5307 solver.cpp:747] class AP 9: 0.362138
-I0511 00:56:24.499078  5307 solver.cpp:747] class AP 10: 0.496736
-I0511 00:56:24.500514  5307 solver.cpp:747] class AP 11: 0.492416
-I0511 00:56:24.501749  5307 solver.cpp:747] class AP 12: 0.646025
-I0511 00:56:24.502315  5307 solver.cpp:747] class AP 13: 0.765683
-I0511 00:56:24.502632  5307 solver.cpp:747] class AP 14: 0.669449
-I0511 00:56:24.566150  5307 solver.cpp:747] class AP 15: 0.672423
-I0511 00:56:24.569351  5307 solver.cpp:747] class AP 16: 0.284018
-I0511 00:56:24.570860  5307 solver.cpp:747] class AP 17: 0.476287
-I0511 00:56:24.571535  5307 solver.cpp:747] class AP 18: 0.55905
-I0511 00:56:24.572093  5307 solver.cpp:747] class AP 19: 0.676947
-I0511 00:56:24.572917  5307 solver.cpp:747] class AP 20: 0.550362
-I0511 00:56:24.572924  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.548913
-I0511 00:56:24.573099  5307 solver.cpp:283] Tests completed in 101.263s
-I0511 00:56:25.165314  5307 solver.cpp:352] Iteration 58000 (0.98753 iter/s, 101.263s/100 iter), 112.1/232ep, loss = 3.30281
-I0511 00:56:25.165344  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47412 (* 1 = 3.47412 loss)
-I0511 00:56:25.165351  5307 sgd_solver.cpp:172] Iteration 58000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:57:25.432214  5307 solver.cpp:352] Iteration 58100 (1.65931 iter/s, 60.2658s/100 iter), 112.3/232ep, loss = 3.57495
-I0511 00:57:25.432303  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09301 (* 1 = 3.09301 loss)
-I0511 00:57:25.432313  5307 sgd_solver.cpp:172] Iteration 58100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:58:25.854038  5307 solver.cpp:352] Iteration 58200 (1.65506 iter/s, 60.4207s/100 iter), 112.5/232ep, loss = 3.37738
-I0511 00:58:25.854207  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47003 (* 1 = 3.47003 loss)
-I0511 00:58:25.854228  5307 sgd_solver.cpp:172] Iteration 58200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 00:59:25.874824  5307 solver.cpp:352] Iteration 58300 (1.66612 iter/s, 60.0198s/100 iter), 112.7/232ep, loss = 3.43581
-I0511 00:59:25.874918  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27225 (* 1 = 3.27225 loss)
-I0511 00:59:25.874928  5307 sgd_solver.cpp:172] Iteration 58300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:00:27.051739  5307 solver.cpp:352] Iteration 58400 (1.63463 iter/s, 61.1759s/100 iter), 112.9/232ep, loss = 3.4495
-I0511 01:00:27.051857  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92781 (* 1 = 2.92781 loss)
-I0511 01:00:27.051867  5307 sgd_solver.cpp:172] Iteration 58400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:00:43.793057  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:01:30.215191  5307 solver.cpp:352] Iteration 58500 (1.58322 iter/s, 63.1624s/100 iter), 113.1/232ep, loss = 3.54849
-I0511 01:01:30.217983  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15411 (* 1 = 3.15411 loss)
-I0511 01:01:30.218010  5307 sgd_solver.cpp:172] Iteration 58500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:02:39.419816  5307 solver.cpp:352] Iteration 58600 (1.44501 iter/s, 69.2034s/100 iter), 113.3/232ep, loss = 3.44474
-I0511 01:02:39.419972  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19437 (* 1 = 3.19437 loss)
-I0511 01:02:39.419981  5307 sgd_solver.cpp:172] Iteration 58600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:03:41.282872  5307 solver.cpp:352] Iteration 58700 (1.6165 iter/s, 61.862s/100 iter), 113.5/232ep, loss = 3.48314
-I0511 01:03:41.282948  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47422 (* 1 = 3.47422 loss)
-I0511 01:03:41.282958  5307 sgd_solver.cpp:172] Iteration 58700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:04:42.387756  5307 solver.cpp:352] Iteration 58800 (1.63656 iter/s, 61.1038s/100 iter), 113.7/232ep, loss = 3.30446
-I0511 01:04:42.387814  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.03247 (* 1 = 4.03247 loss)
-I0511 01:04:42.387821  5307 sgd_solver.cpp:172] Iteration 58800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:05:42.568261  5307 solver.cpp:352] Iteration 58900 (1.6617 iter/s, 60.1795s/100 iter), 113.9/232ep, loss = 3.26982
-I0511 01:05:42.568331  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71852 (* 1 = 2.71852 loss)
-I0511 01:05:42.568341  5307 sgd_solver.cpp:172] Iteration 58900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:06:09.855984  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:06:43.287122  5307 solver.cpp:352] Iteration 59000 (1.64696 iter/s, 60.7178s/100 iter), 114.1/232ep, loss = 3.40579
-I0511 01:06:43.287201  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13 (* 1 = 3.13 loss)
-I0511 01:06:43.287211  5307 sgd_solver.cpp:172] Iteration 59000, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:07:43.903594  5307 solver.cpp:352] Iteration 59100 (1.64974 iter/s, 60.6154s/100 iter), 114.3/232ep, loss = 3.52119
-I0511 01:07:43.903730  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2336 (* 1 = 3.2336 loss)
-I0511 01:07:43.903741  5307 sgd_solver.cpp:172] Iteration 59100, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:08:44.515570  5307 solver.cpp:352] Iteration 59200 (1.64987 iter/s, 60.611s/100 iter), 114.5/232ep, loss = 3.51671
-I0511 01:08:44.515648  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63872 (* 1 = 3.63872 loss)
-I0511 01:08:44.515664  5307 sgd_solver.cpp:172] Iteration 59200, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:09:44.930148  5307 solver.cpp:352] Iteration 59300 (1.65526 iter/s, 60.4136s/100 iter), 114.7/232ep, loss = 3.38098
-I0511 01:09:44.930215  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.86821 (* 1 = 3.86821 loss)
-I0511 01:09:44.930222  5307 sgd_solver.cpp:172] Iteration 59300, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:10:44.699968  5307 solver.cpp:352] Iteration 59400 (1.67311 iter/s, 59.7688s/100 iter), 114.8/232ep, loss = 3.61522
-I0511 01:10:44.700042  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.49936 (* 1 = 3.49936 loss)
-I0511 01:10:44.700050  5307 sgd_solver.cpp:172] Iteration 59400, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:11:22.176784  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:11:44.708138  5307 solver.cpp:352] Iteration 59500 (1.66647 iter/s, 60.0071s/100 iter), 115/232ep, loss = 3.24844
-I0511 01:11:44.708240  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.93217 (* 1 = 2.93217 loss)
-I0511 01:11:44.708266  5307 sgd_solver.cpp:172] Iteration 59500, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:12:45.026967  5307 solver.cpp:352] Iteration 59600 (1.65788 iter/s, 60.3178s/100 iter), 115.2/232ep, loss = 3.47464
-I0511 01:12:45.027045  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0506 (* 1 = 4.0506 loss)
-I0511 01:12:45.027056  5307 sgd_solver.cpp:172] Iteration 59600, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:13:45.293133  5307 solver.cpp:352] Iteration 59700 (1.65933 iter/s, 60.2651s/100 iter), 115.4/232ep, loss = 3.29606
-I0511 01:13:45.293268  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.21834 (* 1 = 2.21834 loss)
-I0511 01:13:45.293280  5307 sgd_solver.cpp:172] Iteration 59700, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:14:45.865222  5307 solver.cpp:352] Iteration 59800 (1.65095 iter/s, 60.5711s/100 iter), 115.6/232ep, loss = 3.48137
-I0511 01:14:45.865280  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19146 (* 1 = 3.19146 loss)
-I0511 01:14:45.865288  5307 sgd_solver.cpp:172] Iteration 59800, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:15:45.711884  5307 solver.cpp:352] Iteration 59900 (1.67097 iter/s, 59.8456s/100 iter), 115.8/232ep, loss = 3.47236
-I0511 01:15:45.711971  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.97808 (* 1 = 2.97808 loss)
-I0511 01:15:45.711985  5307 sgd_solver.cpp:172] Iteration 59900, lr = 0.01, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:16:34.266850  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:16:46.247411  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_60000.caffemodel
-I0511 01:16:46.265805  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_60000.solverstate
-I0511 01:16:46.271970  5307 solver.cpp:635] Iteration 60000, Testing net (#0)
-I0511 01:17:26.765581  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:17:26.971472  5307 solver.cpp:747] class AP 1: 0.574086
-I0511 01:17:26.971858  5307 solver.cpp:747] class AP 2: 0.613003
-I0511 01:17:26.980267  5307 solver.cpp:747] class AP 3: 0.452021
-I0511 01:17:26.987545  5307 solver.cpp:747] class AP 4: 0.332015
-I0511 01:17:27.011425  5307 solver.cpp:747] class AP 5: 0.259983
-I0511 01:17:27.011533  5307 solver.cpp:747] class AP 6: 0.614489
-I0511 01:17:27.020190  5307 solver.cpp:747] class AP 7: 0.613133
-I0511 01:17:27.021162  5307 solver.cpp:747] class AP 8: 0.677218
-I0511 01:17:27.039156  5307 solver.cpp:747] class AP 9: 0.334882
-I0511 01:17:27.039464  5307 solver.cpp:747] class AP 10: 0.527755
-I0511 01:17:27.040042  5307 solver.cpp:747] class AP 11: 0.480282
-I0511 01:17:27.040508  5307 solver.cpp:747] class AP 12: 0.591494
-I0511 01:17:27.040783  5307 solver.cpp:747] class AP 13: 0.700473
-I0511 01:17:27.041205  5307 solver.cpp:747] class AP 14: 0.655316
-I0511 01:17:27.083600  5307 solver.cpp:747] class AP 15: 0.615903
-I0511 01:17:27.092900  5307 solver.cpp:747] class AP 16: 0.274368
-I0511 01:17:27.094329  5307 solver.cpp:747] class AP 17: 0.427949
-I0511 01:17:27.094879  5307 solver.cpp:747] class AP 18: 0.54173
-I0511 01:17:27.095206  5307 solver.cpp:747] class AP 19: 0.654811
-I0511 01:17:27.096396  5307 solver.cpp:747] class AP 20: 0.495851
-I0511 01:17:27.096405  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.521838
-I0511 01:17:27.096727  5307 solver.cpp:283] Tests completed in 101.383s
-I0511 01:17:27.445214  5355 sgd_solver.cpp:50] MultiStep Status: Iteration 60000, step = 1
-I0511 01:17:27.682260  5307 solver.cpp:352] Iteration 60000 (0.986357 iter/s, 101.383s/100 iter), 116/232ep, loss = 3.57575
-I0511 01:17:27.682317  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59007 (* 1 = 3.59007 loss)
-I0511 01:17:27.682333  5307 sgd_solver.cpp:172] Iteration 60000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:18:29.066782  5307 solver.cpp:352] Iteration 60100 (1.6291 iter/s, 61.3834s/100 iter), 116.2/232ep, loss = 3.33893
-I0511 01:18:29.066859  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36745 (* 1 = 3.36745 loss)
-I0511 01:18:29.066942  5307 sgd_solver.cpp:172] Iteration 60100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:19:30.656616  5307 solver.cpp:352] Iteration 60200 (1.62367 iter/s, 61.5887s/100 iter), 116.4/232ep, loss = 3.30766
-I0511 01:19:30.657325  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.66321 (* 1 = 3.66321 loss)
-I0511 01:19:30.657394  5307 sgd_solver.cpp:172] Iteration 60200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:20:32.139109  5307 solver.cpp:352] Iteration 60300 (1.62651 iter/s, 61.4814s/100 iter), 116.6/232ep, loss = 3.53453
-I0511 01:20:32.139199  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.27908 (* 1 = 4.27908 loss)
-I0511 01:20:32.139214  5307 sgd_solver.cpp:172] Iteration 60300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:21:33.893513  5307 solver.cpp:352] Iteration 60400 (1.61935 iter/s, 61.7534s/100 iter), 116.8/232ep, loss = 3.07137
-I0511 01:21:33.893599  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51694 (* 1 = 2.51694 loss)
-I0511 01:21:33.893795  5307 sgd_solver.cpp:172] Iteration 60400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:22:34.057631  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:22:35.990677  5307 solver.cpp:352] Iteration 60500 (1.61041 iter/s, 62.0961s/100 iter), 117/232ep, loss = 3.3171
-I0511 01:22:35.990705  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99441 (* 1 = 2.99441 loss)
-I0511 01:22:35.990715  5307 sgd_solver.cpp:172] Iteration 60500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:23:37.404093  5307 solver.cpp:352] Iteration 60600 (1.62834 iter/s, 61.4123s/100 iter), 117.2/232ep, loss = 3.38382
-I0511 01:23:37.404161  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96618 (* 1 = 2.96618 loss)
-I0511 01:23:37.404171  5307 sgd_solver.cpp:172] Iteration 60600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:24:39.115162  5307 solver.cpp:352] Iteration 60700 (1.62048 iter/s, 61.71s/100 iter), 117.4/232ep, loss = 3.29782
-I0511 01:24:39.115264  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73199 (* 1 = 2.73199 loss)
-I0511 01:24:39.115273  5307 sgd_solver.cpp:172] Iteration 60700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:25:40.255695  5307 solver.cpp:352] Iteration 60800 (1.6356 iter/s, 61.1395s/100 iter), 117.6/232ep, loss = 3.31946
-I0511 01:25:40.255801  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72749 (* 1 = 3.72749 loss)
-I0511 01:25:40.255810  5307 sgd_solver.cpp:172] Iteration 60800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:26:40.877454  5307 solver.cpp:352] Iteration 60900 (1.6496 iter/s, 60.6207s/100 iter), 117.7/232ep, loss = 3.24465
-I0511 01:26:40.877571  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59557 (* 1 = 3.59557 loss)
-I0511 01:26:40.877586  5307 sgd_solver.cpp:172] Iteration 60900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:27:42.193470  5307 solver.cpp:352] Iteration 61000 (1.63092 iter/s, 61.315s/100 iter), 117.9/232ep, loss = 2.96329
-I0511 01:27:42.195245  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5253 (* 1 = 2.5253 loss)
-I0511 01:27:42.195256  5307 sgd_solver.cpp:172] Iteration 61000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:27:50.109959  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:28:42.751310  5307 solver.cpp:352] Iteration 61100 (1.65134 iter/s, 60.5568s/100 iter), 118.1/232ep, loss = 3.174
-I0511 01:28:42.754483  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.70197 (* 1 = 2.70197 loss)
-I0511 01:28:42.754503  5307 sgd_solver.cpp:172] Iteration 61100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:29:44.676252  5307 solver.cpp:352] Iteration 61200 (1.61489 iter/s, 61.9239s/100 iter), 118.3/232ep, loss = 3.40893
-I0511 01:29:44.676367  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61415 (* 1 = 3.61415 loss)
-I0511 01:29:44.676388  5307 sgd_solver.cpp:172] Iteration 61200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:30:44.929544  5307 solver.cpp:352] Iteration 61300 (1.65969 iter/s, 60.2523s/100 iter), 118.5/232ep, loss = 3.03333
-I0511 01:30:44.930357  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07757 (* 1 = 3.07757 loss)
-I0511 01:30:44.930377  5307 sgd_solver.cpp:172] Iteration 61300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:31:45.904727  5307 solver.cpp:352] Iteration 61400 (1.64004 iter/s, 60.9742s/100 iter), 118.7/232ep, loss = 3.19597
-I0511 01:31:45.905048  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73004 (* 1 = 2.73004 loss)
-I0511 01:31:45.905057  5307 sgd_solver.cpp:172] Iteration 61400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:32:46.642874  5307 solver.cpp:352] Iteration 61500 (1.64644 iter/s, 60.7371s/100 iter), 118.9/232ep, loss = 3.19309
-I0511 01:32:46.642956  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14063 (* 1 = 3.14063 loss)
-I0511 01:32:46.642966  5307 sgd_solver.cpp:172] Iteration 61500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:33:05.857440  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:33:47.518443  5307 solver.cpp:352] Iteration 61600 (1.64272 iter/s, 60.8745s/100 iter), 119.1/232ep, loss = 3.33877
-I0511 01:33:47.518563  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71762 (* 1 = 3.71762 loss)
-I0511 01:33:47.518584  5307 sgd_solver.cpp:172] Iteration 61600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:34:47.873309  5307 solver.cpp:352] Iteration 61700 (1.6569 iter/s, 60.3538s/100 iter), 119.3/232ep, loss = 3.27758
-I0511 01:34:47.873818  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90094 (* 1 = 2.90094 loss)
-I0511 01:34:47.873839  5307 sgd_solver.cpp:172] Iteration 61700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:35:48.313613  5307 solver.cpp:352] Iteration 61800 (1.65455 iter/s, 60.4393s/100 iter), 119.5/232ep, loss = 3.40443
-I0511 01:35:48.313936  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3341 (* 1 = 3.3341 loss)
-I0511 01:35:48.313948  5307 sgd_solver.cpp:172] Iteration 61800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:36:49.063982  5307 solver.cpp:352] Iteration 61900 (1.64611 iter/s, 60.7493s/100 iter), 119.7/232ep, loss = 3.16417
-I0511 01:36:49.064105  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.94675 (* 1 = 3.94675 loss)
-I0511 01:36:49.064129  5307 sgd_solver.cpp:172] Iteration 61900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:37:49.609964  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_62000.caffemodel
-I0511 01:37:49.629725  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_62000.solverstate
-I0511 01:37:49.637205  5307 solver.cpp:635] Iteration 62000, Testing net (#0)
-I0511 01:38:30.271909  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:38:30.498445  5307 solver.cpp:747] class AP 1: 0.638976
-I0511 01:38:30.498889  5307 solver.cpp:747] class AP 2: 0.696391
-I0511 01:38:30.506206  5307 solver.cpp:747] class AP 3: 0.530722
-I0511 01:38:30.509886  5307 solver.cpp:747] class AP 4: 0.474306
-I0511 01:38:30.532281  5307 solver.cpp:747] class AP 5: 0.325235
-I0511 01:38:30.532739  5307 solver.cpp:747] class AP 6: 0.705911
-I0511 01:38:30.541038  5307 solver.cpp:747] class AP 7: 0.682504
-I0511 01:38:30.541545  5307 solver.cpp:747] class AP 8: 0.784299
-I0511 01:38:30.562366  5307 solver.cpp:747] class AP 9: 0.406171
-I0511 01:38:30.563141  5307 solver.cpp:747] class AP 10: 0.579289
-I0511 01:38:30.563907  5307 solver.cpp:747] class AP 11: 0.579477
-I0511 01:38:30.564935  5307 solver.cpp:747] class AP 12: 0.707274
-I0511 01:38:30.565356  5307 solver.cpp:747] class AP 13: 0.781847
-I0511 01:38:30.565732  5307 solver.cpp:747] class AP 14: 0.725835
-I0511 01:38:30.624557  5307 solver.cpp:747] class AP 15: 0.717883
-I0511 01:38:30.633199  5307 solver.cpp:747] class AP 16: 0.318442
-I0511 01:38:30.637576  5307 solver.cpp:747] class AP 17: 0.577362
-I0511 01:38:30.638466  5307 solver.cpp:747] class AP 18: 0.617153
-I0511 01:38:30.639308  5307 solver.cpp:747] class AP 19: 0.734592
-I0511 01:38:30.641549  5307 solver.cpp:747] class AP 20: 0.582975
-I0511 01:38:30.641572  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.608332
-I0511 01:38:30.641708  5307 solver.cpp:283] Tests completed in 101.576s
-I0511 01:38:31.202342  5307 solver.cpp:352] Iteration 62000 (0.984484 iter/s, 101.576s/100 iter), 119.9/232ep, loss = 3.18528
-I0511 01:38:31.202376  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26906 (* 1 = 3.26906 loss)
-I0511 01:38:31.202385  5307 sgd_solver.cpp:172] Iteration 62000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:39:00.942828  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:39:32.470726  5307 solver.cpp:352] Iteration 62100 (1.63219 iter/s, 61.2673s/100 iter), 120.1/232ep, loss = 3.32069
-I0511 01:39:32.470837  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25149 (* 1 = 3.25149 loss)
-I0511 01:39:32.470847  5307 sgd_solver.cpp:172] Iteration 62100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:40:32.866340  5307 solver.cpp:352] Iteration 62200 (1.65578 iter/s, 60.3946s/100 iter), 120.3/232ep, loss = 3.24012
-I0511 01:40:32.871697  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33285 (* 1 = 3.33285 loss)
-I0511 01:40:32.871791  5307 sgd_solver.cpp:172] Iteration 62200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:41:33.514859  5307 solver.cpp:352] Iteration 62300 (1.64887 iter/s, 60.6474s/100 iter), 120.5/232ep, loss = 3.14737
-I0511 01:41:33.517706  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.01378 (* 1 = 2.01378 loss)
-I0511 01:41:33.517721  5307 sgd_solver.cpp:172] Iteration 62300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:42:34.198036  5307 solver.cpp:352] Iteration 62400 (1.64793 iter/s, 60.6822s/100 iter), 120.6/232ep, loss = 3.04684
-I0511 01:42:34.198324  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95164 (* 1 = 2.95164 loss)
-I0511 01:42:34.198341  5307 sgd_solver.cpp:172] Iteration 62400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:43:35.042399  5307 solver.cpp:352] Iteration 62500 (1.64357 iter/s, 60.8433s/100 iter), 120.8/232ep, loss = 3.38942
-I0511 01:43:35.042520  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01356 (* 1 = 3.01356 loss)
-I0511 01:43:35.042529  5307 sgd_solver.cpp:172] Iteration 62500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:44:15.422554  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:44:36.124577  5307 solver.cpp:352] Iteration 62600 (1.63717 iter/s, 61.0811s/100 iter), 121/232ep, loss = 3.2401
-I0511 01:44:36.124794  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.23748 (* 1 = 3.23748 loss)
-I0511 01:44:36.124814  5307 sgd_solver.cpp:172] Iteration 62600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:45:36.969264  5307 solver.cpp:352] Iteration 62700 (1.64356 iter/s, 60.8437s/100 iter), 121.2/232ep, loss = 3.49287
-I0511 01:45:36.969357  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.75813 (* 1 = 3.75813 loss)
-I0511 01:45:36.969365  5307 sgd_solver.cpp:172] Iteration 62700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:46:37.442836  5307 solver.cpp:352] Iteration 62800 (1.65364 iter/s, 60.4725s/100 iter), 121.4/232ep, loss = 3.21464
-I0511 01:46:37.442962  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30845 (* 1 = 3.30845 loss)
-I0511 01:46:37.442970  5307 sgd_solver.cpp:172] Iteration 62800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:47:38.004196  5307 solver.cpp:352] Iteration 62900 (1.65125 iter/s, 60.5603s/100 iter), 121.6/232ep, loss = 3.15143
-I0511 01:47:38.004312  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25155 (* 1 = 3.25155 loss)
-I0511 01:47:38.004331  5307 sgd_solver.cpp:172] Iteration 62900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:48:38.915096  5307 solver.cpp:352] Iteration 63000 (1.64177 iter/s, 60.9099s/100 iter), 121.8/232ep, loss = 3.1154
-I0511 01:48:38.915282  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55979 (* 1 = 3.55979 loss)
-I0511 01:48:38.915294  5307 sgd_solver.cpp:172] Iteration 63000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:49:29.128574  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:49:39.204468  5307 solver.cpp:352] Iteration 63100 (1.65869 iter/s, 60.2884s/100 iter), 122/232ep, loss = 3.10442
-I0511 01:49:39.204491  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14016 (* 1 = 3.14016 loss)
-I0511 01:49:39.204499  5307 sgd_solver.cpp:172] Iteration 63100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:50:38.492687  5307 solver.cpp:352] Iteration 63200 (1.68671 iter/s, 59.2872s/100 iter), 122.2/232ep, loss = 3.15629
-I0511 01:50:38.492832  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.25644 (* 1 = 4.25644 loss)
-I0511 01:50:38.492857  5307 sgd_solver.cpp:172] Iteration 63200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:51:39.091516  5307 solver.cpp:352] Iteration 63300 (1.65022 iter/s, 60.5978s/100 iter), 122.4/232ep, loss = 3.01801
-I0511 01:51:39.091578  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67144 (* 1 = 3.67144 loss)
-I0511 01:51:39.091585  5307 sgd_solver.cpp:172] Iteration 63300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:52:39.720751  5307 solver.cpp:352] Iteration 63400 (1.6494 iter/s, 60.6282s/100 iter), 122.6/232ep, loss = 3.26002
-I0511 01:52:39.721735  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84441 (* 1 = 3.84441 loss)
-I0511 01:52:39.721746  5307 sgd_solver.cpp:172] Iteration 63400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:53:39.748903  5307 solver.cpp:352] Iteration 63500 (1.66591 iter/s, 60.0271s/100 iter), 122.8/232ep, loss = 3.11425
-I0511 01:53:39.749964  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13076 (* 1 = 3.13076 loss)
-I0511 01:53:39.749975  5307 sgd_solver.cpp:172] Iteration 63500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:54:39.551507  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:54:40.126468  5307 solver.cpp:352] Iteration 63600 (1.65627 iter/s, 60.3766s/100 iter), 123/232ep, loss = 3.36435
-I0511 01:54:40.126544  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82291 (* 1 = 3.82291 loss)
-I0511 01:54:40.126564  5307 sgd_solver.cpp:172] Iteration 63600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:55:41.248622  5307 solver.cpp:352] Iteration 63700 (1.6361 iter/s, 61.1211s/100 iter), 123.2/232ep, loss = 3.28457
-I0511 01:55:41.250053  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.92716 (* 1 = 3.92716 loss)
-I0511 01:55:41.250136  5307 sgd_solver.cpp:172] Iteration 63700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:56:41.808493  5307 solver.cpp:352] Iteration 63800 (1.65129 iter/s, 60.5588s/100 iter), 123.4/232ep, loss = 3.16873
-I0511 01:56:41.808573  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16457 (* 1 = 3.16457 loss)
-I0511 01:56:41.808583  5307 sgd_solver.cpp:172] Iteration 63800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:57:41.697094  5307 solver.cpp:352] Iteration 63900 (1.6698 iter/s, 59.8876s/100 iter), 123.5/232ep, loss = 3.09208
-I0511 01:57:41.697197  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.56341 (* 1 = 2.56341 loss)
-I0511 01:57:41.697211  5307 sgd_solver.cpp:172] Iteration 63900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 01:58:41.914530  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_64000.caffemodel
-I0511 01:58:41.936115  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_64000.solverstate
-I0511 01:58:41.942518  5307 solver.cpp:635] Iteration 64000, Testing net (#0)
-I0511 01:58:54.503506  5352 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0511 01:59:22.812211  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 01:59:23.034703  5307 solver.cpp:747] class AP 1: 0.633344
-I0511 01:59:23.035193  5307 solver.cpp:747] class AP 2: 0.71913
-I0511 01:59:23.041399  5307 solver.cpp:747] class AP 3: 0.523038
-I0511 01:59:23.044920  5307 solver.cpp:747] class AP 4: 0.487088
-I0511 01:59:23.065953  5307 solver.cpp:747] class AP 5: 0.323399
-I0511 01:59:23.066340  5307 solver.cpp:747] class AP 6: 0.712963
-I0511 01:59:23.073334  5307 solver.cpp:747] class AP 7: 0.678412
-I0511 01:59:23.073962  5307 solver.cpp:747] class AP 8: 0.791006
-I0511 01:59:23.093544  5307 solver.cpp:747] class AP 9: 0.418986
-I0511 01:59:23.094259  5307 solver.cpp:747] class AP 10: 0.613647
-I0511 01:59:23.094915  5307 solver.cpp:747] class AP 11: 0.564244
-I0511 01:59:23.095716  5307 solver.cpp:747] class AP 12: 0.6965
-I0511 01:59:23.096119  5307 solver.cpp:747] class AP 13: 0.777461
-I0511 01:59:23.096477  5307 solver.cpp:747] class AP 14: 0.733747
-I0511 01:59:23.148425  5307 solver.cpp:747] class AP 15: 0.713203
-I0511 01:59:23.154863  5307 solver.cpp:747] class AP 16: 0.343052
-I0511 01:59:23.157761  5307 solver.cpp:747] class AP 17: 0.584989
-I0511 01:59:23.158402  5307 solver.cpp:747] class AP 18: 0.589125
-I0511 01:59:23.158951  5307 solver.cpp:747] class AP 19: 0.73742
-I0511 01:59:23.160584  5307 solver.cpp:747] class AP 20: 0.592467
-I0511 01:59:23.160596  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.611661
-I0511 01:59:23.160784  5307 solver.cpp:283] Tests completed in 101.462s
-I0511 01:59:23.710171  5307 solver.cpp:352] Iteration 64000 (0.985591 iter/s, 101.462s/100 iter), 123.7/232ep, loss = 3.07692
-I0511 01:59:23.710196  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87853 (* 1 = 2.87853 loss)
-I0511 01:59:23.710201  5307 sgd_solver.cpp:172] Iteration 64000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:00:23.587422  5307 solver.cpp:352] Iteration 64100 (1.67011 iter/s, 59.8762s/100 iter), 123.9/232ep, loss = 3.19645
-I0511 02:00:23.587507  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44664 (* 1 = 3.44664 loss)
-I0511 02:00:23.587524  5307 sgd_solver.cpp:172] Iteration 64100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:00:34.106542  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:01:23.968485  5307 solver.cpp:352] Iteration 64200 (1.65618 iter/s, 60.38s/100 iter), 124.1/232ep, loss = 3.05154
-I0511 02:01:23.968683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59048 (* 1 = 3.59048 loss)
-I0511 02:01:23.968695  5307 sgd_solver.cpp:172] Iteration 64200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:02:24.219705  5307 solver.cpp:352] Iteration 64300 (1.65975 iter/s, 60.2502s/100 iter), 124.3/232ep, loss = 3.12734
-I0511 02:02:24.219782  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08787 (* 1 = 3.08787 loss)
-I0511 02:02:24.219791  5307 sgd_solver.cpp:172] Iteration 64300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:03:24.846391  5307 solver.cpp:352] Iteration 64400 (1.64947 iter/s, 60.6257s/100 iter), 124.5/232ep, loss = 3.0666
-I0511 02:03:24.846494  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15372 (* 1 = 3.15372 loss)
-I0511 02:03:24.846513  5307 sgd_solver.cpp:172] Iteration 64400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:04:25.418087  5307 solver.cpp:352] Iteration 64500 (1.65096 iter/s, 60.5707s/100 iter), 124.7/232ep, loss = 3.25712
-I0511 02:04:25.418170  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20735 (* 1 = 3.20735 loss)
-I0511 02:04:25.418179  5307 sgd_solver.cpp:172] Iteration 64500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:05:25.953708  5307 solver.cpp:352] Iteration 64600 (1.65195 iter/s, 60.5346s/100 iter), 124.9/232ep, loss = 3.072
-I0511 02:05:25.953817  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88575 (* 1 = 2.88575 loss)
-I0511 02:05:25.953832  5307 sgd_solver.cpp:172] Iteration 64600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:05:46.779067  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:06:26.804708  5307 solver.cpp:352] Iteration 64700 (1.64339 iter/s, 60.85s/100 iter), 125.1/232ep, loss = 3.16899
-I0511 02:06:26.805696  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.78591 (* 1 = 2.78591 loss)
-I0511 02:06:26.805712  5307 sgd_solver.cpp:172] Iteration 64700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:07:27.332586  5307 solver.cpp:352] Iteration 64800 (1.65216 iter/s, 60.5269s/100 iter), 125.3/232ep, loss = 3.11116
-I0511 02:07:27.332701  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53597 (* 1 = 3.53597 loss)
-I0511 02:07:27.332718  5307 sgd_solver.cpp:172] Iteration 64800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:08:27.384068  5307 solver.cpp:352] Iteration 64900 (1.66527 iter/s, 60.0505s/100 iter), 125.5/232ep, loss = 3.25568
-I0511 02:08:27.384121  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64235 (* 1 = 3.64235 loss)
-I0511 02:08:27.384130  5307 sgd_solver.cpp:172] Iteration 64900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:09:32.242856  5307 solver.cpp:352] Iteration 65000 (1.54184 iter/s, 64.8577s/100 iter), 125.7/232ep, loss = 3.19532
-I0511 02:09:32.245679  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05203 (* 1 = 3.05203 loss)
-I0511 02:09:32.245710  5307 sgd_solver.cpp:172] Iteration 65000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:10:40.086432  5307 solver.cpp:352] Iteration 65100 (1.474 iter/s, 67.8424s/100 iter), 125.9/232ep, loss = 3.23919
-I0511 02:10:40.086539  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31138 (* 1 = 3.31138 loss)
-I0511 02:10:40.086555  5307 sgd_solver.cpp:172] Iteration 65100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:11:11.076592  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:11:40.491904  5307 solver.cpp:352] Iteration 65200 (1.65551 iter/s, 60.4044s/100 iter), 126.1/232ep, loss = 3.29238
-I0511 02:11:40.491936  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03786 (* 1 = 3.03786 loss)
-I0511 02:11:40.491945  5307 sgd_solver.cpp:172] Iteration 65200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:12:41.340348  5307 solver.cpp:352] Iteration 65300 (1.64346 iter/s, 60.8474s/100 iter), 126.3/232ep, loss = 3.20961
-I0511 02:12:41.340802  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.39202 (* 1 = 4.39202 loss)
-I0511 02:12:41.340811  5307 sgd_solver.cpp:172] Iteration 65300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:13:40.918337  5307 solver.cpp:352] Iteration 65400 (1.6785 iter/s, 59.577s/100 iter), 126.4/232ep, loss = 3.12944
-I0511 02:13:40.918462  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88578 (* 1 = 2.88578 loss)
-I0511 02:13:40.918475  5307 sgd_solver.cpp:172] Iteration 65400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:14:41.663523  5307 solver.cpp:352] Iteration 65500 (1.64625 iter/s, 60.7442s/100 iter), 126.6/232ep, loss = 3.17585
-I0511 02:14:41.663591  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27108 (* 1 = 3.27108 loss)
-I0511 02:14:41.663600  5307 sgd_solver.cpp:172] Iteration 65500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:15:41.835770  5307 solver.cpp:352] Iteration 65600 (1.66192 iter/s, 60.1712s/100 iter), 126.8/232ep, loss = 3.22622
-I0511 02:15:41.835837  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64396 (* 1 = 3.64396 loss)
-I0511 02:15:41.835847  5307 sgd_solver.cpp:172] Iteration 65600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:16:23.883992  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:16:42.569505  5307 solver.cpp:352] Iteration 65700 (1.64656 iter/s, 60.7327s/100 iter), 127/232ep, loss = 3.21759
-I0511 02:16:42.569663  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.02444 (* 1 = 3.02444 loss)
-I0511 02:16:42.569728  5307 sgd_solver.cpp:172] Iteration 65700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:17:44.531523  5307 solver.cpp:352] Iteration 65800 (1.61392 iter/s, 61.961s/100 iter), 127.2/232ep, loss = 3.1564
-I0511 02:17:44.531584  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46917 (* 1 = 3.46917 loss)
-I0511 02:17:44.531592  5307 sgd_solver.cpp:172] Iteration 65800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:18:45.268631  5307 solver.cpp:352] Iteration 65900 (1.64647 iter/s, 60.7361s/100 iter), 127.4/232ep, loss = 3.09757
-I0511 02:18:45.268702  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.98101 (* 1 = 2.98101 loss)
-I0511 02:18:45.268712  5307 sgd_solver.cpp:172] Iteration 65900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:19:45.910188  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_66000.caffemodel
-I0511 02:19:45.926357  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_66000.solverstate
-I0511 02:19:45.931254  5307 solver.cpp:635] Iteration 66000, Testing net (#0)
-I0511 02:20:26.794226  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:20:27.040277  5307 solver.cpp:747] class AP 1: 0.64229
-I0511 02:20:27.040701  5307 solver.cpp:747] class AP 2: 0.706363
-I0511 02:20:27.047019  5307 solver.cpp:747] class AP 3: 0.531507
-I0511 02:20:27.050629  5307 solver.cpp:747] class AP 4: 0.49355
-I0511 02:20:27.070884  5307 solver.cpp:747] class AP 5: 0.323647
-I0511 02:20:27.071313  5307 solver.cpp:747] class AP 6: 0.704733
-I0511 02:20:27.079596  5307 solver.cpp:747] class AP 7: 0.697777
-I0511 02:20:27.080271  5307 solver.cpp:747] class AP 8: 0.798769
-I0511 02:20:27.099870  5307 solver.cpp:747] class AP 9: 0.412927
-I0511 02:20:27.100630  5307 solver.cpp:747] class AP 10: 0.632788
-I0511 02:20:27.101251  5307 solver.cpp:747] class AP 11: 0.571624
-I0511 02:20:27.102129  5307 solver.cpp:747] class AP 12: 0.718176
-I0511 02:20:27.102501  5307 solver.cpp:747] class AP 13: 0.786534
-I0511 02:20:27.102790  5307 solver.cpp:747] class AP 14: 0.73184
-I0511 02:20:27.153549  5307 solver.cpp:747] class AP 15: 0.714214
-I0511 02:20:27.160442  5307 solver.cpp:747] class AP 16: 0.342798
-I0511 02:20:27.163242  5307 solver.cpp:747] class AP 17: 0.582979
-I0511 02:20:27.163986  5307 solver.cpp:747] class AP 18: 0.620496
-I0511 02:20:27.164631  5307 solver.cpp:747] class AP 19: 0.743935
-I0511 02:20:27.166348  5307 solver.cpp:747] class AP 20: 0.586294
-I0511 02:20:27.166357  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.617162
-I0511 02:20:27.166574  5307 solver.cpp:283] Tests completed in 101.896s
-I0511 02:20:27.747750  5307 solver.cpp:352] Iteration 66000 (0.981391 iter/s, 101.896s/100 iter), 127.6/232ep, loss = 3.06323
-I0511 02:20:27.747782  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37556 (* 1 = 3.37556 loss)
-I0511 02:20:27.747792  5307 sgd_solver.cpp:172] Iteration 66000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:21:28.306773  5307 solver.cpp:352] Iteration 66100 (1.65131 iter/s, 60.558s/100 iter), 127.8/232ep, loss = 3.12489
-I0511 02:21:28.306880  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96524 (* 1 = 2.96524 loss)
-I0511 02:21:28.306896  5307 sgd_solver.cpp:172] Iteration 66100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:22:19.897558  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:22:28.833058  5307 solver.cpp:352] Iteration 66200 (1.6522 iter/s, 60.5252s/100 iter), 128/232ep, loss = 3.16999
-I0511 02:22:28.833091  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08489 (* 1 = 3.08489 loss)
-I0511 02:22:28.833099  5307 sgd_solver.cpp:172] Iteration 66200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:23:28.684754  5307 solver.cpp:352] Iteration 66300 (1.67083 iter/s, 59.8507s/100 iter), 128.2/232ep, loss = 3.05533
-I0511 02:23:28.684828  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32332 (* 1 = 3.32332 loss)
-I0511 02:23:28.684836  5307 sgd_solver.cpp:172] Iteration 66300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:24:29.196430  5307 solver.cpp:352] Iteration 66400 (1.6526 iter/s, 60.5106s/100 iter), 128.4/232ep, loss = 3.15909
-I0511 02:24:29.196501  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.45537 (* 1 = 2.45537 loss)
-I0511 02:24:29.196511  5307 sgd_solver.cpp:172] Iteration 66400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:25:29.284615  5307 solver.cpp:352] Iteration 66500 (1.66425 iter/s, 60.0871s/100 iter), 128.6/232ep, loss = 3.17891
-I0511 02:25:29.284759  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.80693 (* 1 = 2.80693 loss)
-I0511 02:25:29.284773  5307 sgd_solver.cpp:172] Iteration 66500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:26:29.177669  5307 solver.cpp:352] Iteration 66600 (1.66967 iter/s, 59.8921s/100 iter), 128.8/232ep, loss = 3.04129
-I0511 02:26:29.177758  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.84487 (* 1 = 3.84487 loss)
-I0511 02:26:29.177778  5307 sgd_solver.cpp:172] Iteration 66600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:27:29.551985  5307 solver.cpp:352] Iteration 66700 (1.65636 iter/s, 60.3733s/100 iter), 129/232ep, loss = 3.10101
-I0511 02:27:29.552503  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.98461 (* 1 = 2.98461 loss)
-I0511 02:27:29.552539  5307 sgd_solver.cpp:172] Iteration 66700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:27:31.497298  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:28:29.639467  5307 solver.cpp:352] Iteration 66800 (1.66427 iter/s, 60.0865s/100 iter), 129.2/232ep, loss = 3.27425
-I0511 02:28:29.639585  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99742 (* 1 = 2.99742 loss)
-I0511 02:28:29.639600  5307 sgd_solver.cpp:172] Iteration 66800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:29:30.188894  5307 solver.cpp:352] Iteration 66900 (1.65157 iter/s, 60.5484s/100 iter), 129.3/232ep, loss = 3.07127
-I0511 02:29:30.189085  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.49614 (* 1 = 2.49614 loss)
-I0511 02:29:30.189118  5307 sgd_solver.cpp:172] Iteration 66900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:30:30.186563  5307 solver.cpp:352] Iteration 67000 (1.66676 iter/s, 59.9967s/100 iter), 129.5/232ep, loss = 3.04688
-I0511 02:30:30.186645  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31019 (* 1 = 3.31019 loss)
-I0511 02:30:30.186655  5307 sgd_solver.cpp:172] Iteration 67000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:31:30.200628  5307 solver.cpp:352] Iteration 67100 (1.6663 iter/s, 60.013s/100 iter), 129.7/232ep, loss = 3.24378
-I0511 02:31:30.200717  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95658 (* 1 = 2.95658 loss)
-I0511 02:31:30.200726  5307 sgd_solver.cpp:172] Iteration 67100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:32:30.827069  5307 solver.cpp:352] Iteration 67200 (1.64947 iter/s, 60.6254s/100 iter), 129.9/232ep, loss = 3.10399
-I0511 02:32:30.827136  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.56074 (* 1 = 3.56074 loss)
-I0511 02:32:30.827142  5307 sgd_solver.cpp:172] Iteration 67200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:32:43.731626  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:33:30.801796  5307 solver.cpp:352] Iteration 67300 (1.6674 iter/s, 59.9737s/100 iter), 130.1/232ep, loss = 3.18025
-I0511 02:33:30.801970  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09506 (* 1 = 3.09506 loss)
-I0511 02:33:30.801990  5307 sgd_solver.cpp:172] Iteration 67300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:34:31.469436  5307 solver.cpp:352] Iteration 67400 (1.64835 iter/s, 60.6666s/100 iter), 130.3/232ep, loss = 3.25361
-I0511 02:34:31.469583  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88847 (* 1 = 2.88847 loss)
-I0511 02:34:31.469594  5307 sgd_solver.cpp:172] Iteration 67400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:35:31.926903  5307 solver.cpp:352] Iteration 67500 (1.65408 iter/s, 60.4565s/100 iter), 130.5/232ep, loss = 3.20026
-I0511 02:35:31.927027  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.99033 (* 1 = 3.99033 loss)
-I0511 02:35:31.927047  5307 sgd_solver.cpp:172] Iteration 67500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:36:32.995633  5307 solver.cpp:352] Iteration 67600 (1.63753 iter/s, 61.0677s/100 iter), 130.7/232ep, loss = 3.14645
-I0511 02:36:33.001457  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.64913 (* 1 = 2.64913 loss)
-I0511 02:36:33.001477  5307 sgd_solver.cpp:172] Iteration 67600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:37:34.313900  5307 solver.cpp:352] Iteration 67700 (1.63086 iter/s, 61.3172s/100 iter), 130.9/232ep, loss = 3.0593
-I0511 02:37:34.314021  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51218 (* 1 = 2.51218 loss)
-I0511 02:37:34.314043  5307 sgd_solver.cpp:172] Iteration 67700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:37:56.572094  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:38:34.731317  5307 solver.cpp:352] Iteration 67800 (1.65518 iter/s, 60.4164s/100 iter), 131.1/232ep, loss = 3.07228
-I0511 02:38:34.731390  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85683 (* 1 = 3.85683 loss)
-I0511 02:38:34.731400  5307 sgd_solver.cpp:172] Iteration 67800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:39:35.165295  5307 solver.cpp:352] Iteration 67900 (1.65473 iter/s, 60.4329s/100 iter), 131.3/232ep, loss = 3.21763
-I0511 02:39:35.168763  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.18548 (* 1 = 4.18548 loss)
-I0511 02:39:35.168782  5307 sgd_solver.cpp:172] Iteration 67900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:40:35.312610  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_68000.caffemodel
-I0511 02:40:35.335475  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_68000.solverstate
-I0511 02:40:35.341565  5307 solver.cpp:635] Iteration 68000, Testing net (#0)
-I0511 02:41:15.746647  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:41:15.956759  5307 solver.cpp:747] class AP 1: 0.659079
-I0511 02:41:15.957516  5307 solver.cpp:747] class AP 2: 0.732531
-I0511 02:41:15.964699  5307 solver.cpp:747] class AP 3: 0.534657
-I0511 02:41:15.968891  5307 solver.cpp:747] class AP 4: 0.510083
-I0511 02:41:15.988533  5307 solver.cpp:747] class AP 5: 0.312808
-I0511 02:41:15.988878  5307 solver.cpp:747] class AP 6: 0.711184
-I0511 02:41:15.996846  5307 solver.cpp:747] class AP 7: 0.695885
-I0511 02:41:15.997467  5307 solver.cpp:747] class AP 8: 0.791351
-I0511 02:41:16.014248  5307 solver.cpp:747] class AP 9: 0.415975
-I0511 02:41:16.014916  5307 solver.cpp:747] class AP 10: 0.608569
-I0511 02:41:16.015545  5307 solver.cpp:747] class AP 11: 0.562536
-I0511 02:41:16.016479  5307 solver.cpp:747] class AP 12: 0.72295
-I0511 02:41:16.016935  5307 solver.cpp:747] class AP 13: 0.788439
-I0511 02:41:16.017293  5307 solver.cpp:747] class AP 14: 0.726442
-I0511 02:41:16.068330  5307 solver.cpp:747] class AP 15: 0.720163
-I0511 02:41:16.074450  5307 solver.cpp:747] class AP 16: 0.357333
-I0511 02:41:16.076555  5307 solver.cpp:747] class AP 17: 0.573487
-I0511 02:41:16.077015  5307 solver.cpp:747] class AP 18: 0.621755
-I0511 02:41:16.077679  5307 solver.cpp:747] class AP 19: 0.750308
-I0511 02:41:16.078996  5307 solver.cpp:747] class AP 20: 0.58943
-I0511 02:41:16.079004  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.619248
-I0511 02:41:16.079181  5307 solver.cpp:283] Tests completed in 100.912s
-I0511 02:41:16.621726  5307 solver.cpp:352] Iteration 68000 (0.990961 iter/s, 100.912s/100 iter), 131.5/232ep, loss = 3.21332
-I0511 02:41:16.621757  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.426 (* 1 = 2.426 loss)
-I0511 02:41:16.621765  5307 sgd_solver.cpp:172] Iteration 68000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:42:17.548768  5307 solver.cpp:352] Iteration 68100 (1.64134 iter/s, 60.926s/100 iter), 131.7/232ep, loss = 3.23785
-I0511 02:42:17.548938  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05499 (* 1 = 3.05499 loss)
-I0511 02:42:17.548955  5307 sgd_solver.cpp:172] Iteration 68100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:43:18.543166  5307 solver.cpp:352] Iteration 68200 (1.63952 iter/s, 60.9933s/100 iter), 131.9/232ep, loss = 3.18542
-I0511 02:43:18.543371  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21433 (* 1 = 3.21433 loss)
-I0511 02:43:18.543467  5307 sgd_solver.cpp:172] Iteration 68200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:43:52.088322  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:44:19.328593  5307 solver.cpp:352] Iteration 68300 (1.64516 iter/s, 60.7844s/100 iter), 132.1/232ep, loss = 3.15519
-I0511 02:44:19.328624  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33395 (* 1 = 3.33395 loss)
-I0511 02:44:19.328634  5307 sgd_solver.cpp:172] Iteration 68300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:45:19.909802  5307 solver.cpp:352] Iteration 68400 (1.6507 iter/s, 60.5802s/100 iter), 132.2/232ep, loss = 3.1727
-I0511 02:45:19.909880  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32494 (* 1 = 3.32494 loss)
-I0511 02:45:19.909890  5307 sgd_solver.cpp:172] Iteration 68400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:46:21.203446  5307 solver.cpp:352] Iteration 68500 (1.63152 iter/s, 61.2926s/100 iter), 132.4/232ep, loss = 3.02053
-I0511 02:46:21.203536  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99906 (* 1 = 2.99906 loss)
-I0511 02:46:21.203547  5307 sgd_solver.cpp:172] Iteration 68500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:47:22.625470  5307 solver.cpp:352] Iteration 68600 (1.62811 iter/s, 61.421s/100 iter), 132.6/232ep, loss = 3.19481
-I0511 02:47:22.625568  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63442 (* 1 = 2.63442 loss)
-I0511 02:47:22.625591  5307 sgd_solver.cpp:172] Iteration 68600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:48:22.788887  5307 solver.cpp:352] Iteration 68700 (1.66217 iter/s, 60.1624s/100 iter), 132.8/232ep, loss = 3.31883
-I0511 02:48:22.788957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53685 (* 1 = 3.53685 loss)
-I0511 02:48:22.788977  5307 sgd_solver.cpp:172] Iteration 68700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:49:07.016917  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:49:23.496430  5307 solver.cpp:352] Iteration 68800 (1.64727 iter/s, 60.7065s/100 iter), 133/232ep, loss = 3.31059
-I0511 02:49:23.496461  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.60516 (* 1 = 4.60516 loss)
-I0511 02:49:23.496469  5307 sgd_solver.cpp:172] Iteration 68800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:50:23.810361  5307 solver.cpp:352] Iteration 68900 (1.65802 iter/s, 60.3129s/100 iter), 133.2/232ep, loss = 3.13913
-I0511 02:50:23.810559  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73763 (* 1 = 3.73763 loss)
-I0511 02:50:23.810570  5307 sgd_solver.cpp:172] Iteration 68900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:51:24.725180  5307 solver.cpp:352] Iteration 69000 (1.64167 iter/s, 60.9138s/100 iter), 133.4/232ep, loss = 3.34018
-I0511 02:51:24.725426  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.06818 (* 1 = 4.06818 loss)
-I0511 02:51:24.725502  5307 sgd_solver.cpp:172] Iteration 69000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:52:25.565292  5307 solver.cpp:352] Iteration 69100 (1.64368 iter/s, 60.8391s/100 iter), 133.6/232ep, loss = 2.98946
-I0511 02:52:25.565399  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90528 (* 1 = 2.90528 loss)
-I0511 02:52:25.565416  5307 sgd_solver.cpp:172] Iteration 69100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:53:26.489583  5307 solver.cpp:352] Iteration 69200 (1.64141 iter/s, 60.9233s/100 iter), 133.8/232ep, loss = 3.04981
-I0511 02:53:26.489715  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.82091 (* 1 = 2.82091 loss)
-I0511 02:53:26.489738  5307 sgd_solver.cpp:172] Iteration 69200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:54:20.484907  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 02:54:26.980163  5307 solver.cpp:352] Iteration 69300 (1.65318 iter/s, 60.4896s/100 iter), 134/232ep, loss = 3.16001
-I0511 02:54:26.980187  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88092 (* 1 = 2.88092 loss)
-I0511 02:54:26.980195  5307 sgd_solver.cpp:172] Iteration 69300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:55:28.371501  5307 solver.cpp:352] Iteration 69400 (1.62892 iter/s, 61.3903s/100 iter), 134.2/232ep, loss = 3.13472
-I0511 02:55:28.372318  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85003 (* 1 = 2.85003 loss)
-I0511 02:55:28.372362  5307 sgd_solver.cpp:172] Iteration 69400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:56:28.697196  5307 solver.cpp:352] Iteration 69500 (1.6577 iter/s, 60.3247s/100 iter), 134.4/232ep, loss = 3.218
-I0511 02:56:28.697268  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.90315 (* 1 = 3.90315 loss)
-I0511 02:56:28.697279  5307 sgd_solver.cpp:172] Iteration 69500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:57:29.238632  5307 solver.cpp:352] Iteration 69600 (1.65179 iter/s, 60.5404s/100 iter), 134.6/232ep, loss = 3.18379
-I0511 02:57:29.238732  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.60102 (* 1 = 4.60102 loss)
-I0511 02:57:29.238746  5307 sgd_solver.cpp:172] Iteration 69600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:58:29.184934  5307 solver.cpp:352] Iteration 69700 (1.66819 iter/s, 59.9453s/100 iter), 134.8/232ep, loss = 3.2003
-I0511 02:58:29.185029  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8632 (* 1 = 2.8632 loss)
-I0511 02:58:29.185047  5307 sgd_solver.cpp:172] Iteration 69700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:59:30.345985  5307 solver.cpp:352] Iteration 69800 (1.63506 iter/s, 61.16s/100 iter), 135/232ep, loss = 3.04563
-I0511 02:59:30.347682  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74515 (* 1 = 2.74515 loss)
-I0511 02:59:30.347692  5307 sgd_solver.cpp:172] Iteration 69800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 02:59:34.952587  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:00:31.122530  5307 solver.cpp:352] Iteration 69900 (1.6454 iter/s, 60.7755s/100 iter), 135.1/232ep, loss = 2.95089
-I0511 03:00:31.124117  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21105 (* 1 = 3.21105 loss)
-I0511 03:00:31.124151  5307 sgd_solver.cpp:172] Iteration 69900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:01:31.175557  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_70000.caffemodel
-I0511 03:01:31.191851  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_70000.solverstate
-I0511 03:01:31.197576  5307 solver.cpp:635] Iteration 70000, Testing net (#0)
-I0511 03:02:11.462358  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:02:11.687438  5307 solver.cpp:747] class AP 1: 0.633928
-I0511 03:02:11.688009  5307 solver.cpp:747] class AP 2: 0.722257
-I0511 03:02:11.696943  5307 solver.cpp:747] class AP 3: 0.52554
-I0511 03:02:11.702378  5307 solver.cpp:747] class AP 4: 0.506187
-I0511 03:02:11.728567  5307 solver.cpp:747] class AP 5: 0.317221
-I0511 03:02:11.729123  5307 solver.cpp:747] class AP 6: 0.700389
-I0511 03:02:11.741091  5307 solver.cpp:747] class AP 7: 0.690578
-I0511 03:02:11.742168  5307 solver.cpp:747] class AP 8: 0.793709
-I0511 03:02:11.760407  5307 solver.cpp:747] class AP 9: 0.412928
-I0511 03:02:11.761131  5307 solver.cpp:747] class AP 10: 0.626752
-I0511 03:02:11.761754  5307 solver.cpp:747] class AP 11: 0.569649
-I0511 03:02:11.762750  5307 solver.cpp:747] class AP 12: 0.728977
-I0511 03:02:11.763142  5307 solver.cpp:747] class AP 13: 0.79404
-I0511 03:02:11.763547  5307 solver.cpp:747] class AP 14: 0.739371
-I0511 03:02:11.816392  5307 solver.cpp:747] class AP 15: 0.716036
-I0511 03:02:11.822613  5307 solver.cpp:747] class AP 16: 0.345662
-I0511 03:02:11.825171  5307 solver.cpp:747] class AP 17: 0.588648
-I0511 03:02:11.825748  5307 solver.cpp:747] class AP 18: 0.597739
-I0511 03:02:11.826503  5307 solver.cpp:747] class AP 19: 0.748818
-I0511 03:02:11.827986  5307 solver.cpp:747] class AP 20: 0.585734
-I0511 03:02:11.827993  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.617208
-I0511 03:02:11.828169  5307 solver.cpp:283] Tests completed in 100.704s
-I0511 03:02:12.381124  5307 solver.cpp:352] Iteration 70000 (0.99301 iter/s, 100.704s/100 iter), 135.3/232ep, loss = 3.35481
-I0511 03:02:12.381147  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59581 (* 1 = 3.59581 loss)
-I0511 03:02:12.381155  5307 sgd_solver.cpp:172] Iteration 70000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:03:12.412638  5307 solver.cpp:352] Iteration 70100 (1.66582 iter/s, 60.0305s/100 iter), 135.5/232ep, loss = 3.06649
-I0511 03:03:12.412716  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05734 (* 1 = 3.05734 loss)
-I0511 03:03:12.412726  5307 sgd_solver.cpp:172] Iteration 70100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:04:13.535756  5307 solver.cpp:352] Iteration 70200 (1.63607 iter/s, 61.1221s/100 iter), 135.7/232ep, loss = 3.11306
-I0511 03:04:13.535823  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.97389 (* 1 = 2.97389 loss)
-I0511 03:04:13.535832  5307 sgd_solver.cpp:172] Iteration 70200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:05:13.983336  5307 solver.cpp:352] Iteration 70300 (1.65435 iter/s, 60.4465s/100 iter), 135.9/232ep, loss = 3.06026
-I0511 03:05:13.983414  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.14835 (* 1 = 2.14835 loss)
-I0511 03:05:13.983424  5307 sgd_solver.cpp:172] Iteration 70300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:05:27.617794  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:06:14.169797  5307 solver.cpp:352] Iteration 70400 (1.66153 iter/s, 60.1854s/100 iter), 136.1/232ep, loss = 3.23885
-I0511 03:06:14.172082  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.23922 (* 1 = 3.23922 loss)
-I0511 03:06:14.172091  5307 sgd_solver.cpp:172] Iteration 70400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:07:14.290994  5307 solver.cpp:352] Iteration 70500 (1.66334 iter/s, 60.1202s/100 iter), 136.3/232ep, loss = 3.11523
-I0511 03:07:14.291625  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.43783 (* 1 = 2.43783 loss)
-I0511 03:07:14.291651  5307 sgd_solver.cpp:172] Iteration 70500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:08:15.169945  5307 solver.cpp:352] Iteration 70600 (1.64263 iter/s, 60.8779s/100 iter), 136.5/232ep, loss = 3.23688
-I0511 03:08:15.170079  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11832 (* 1 = 3.11832 loss)
-I0511 03:08:15.170087  5307 sgd_solver.cpp:172] Iteration 70600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:09:16.588992  5307 solver.cpp:352] Iteration 70700 (1.62819 iter/s, 61.418s/100 iter), 136.7/232ep, loss = 3.16966
-I0511 03:09:16.589047  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9083 (* 1 = 2.9083 loss)
-I0511 03:09:16.589054  5307 sgd_solver.cpp:172] Iteration 70700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:10:17.104252  5307 solver.cpp:352] Iteration 70800 (1.6525 iter/s, 60.5142s/100 iter), 136.9/232ep, loss = 2.9313
-I0511 03:10:17.104343  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.13385 (* 1 = 3.13385 loss)
-I0511 03:10:17.104352  5307 sgd_solver.cpp:172] Iteration 70800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:10:42.343801  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:11:18.667933  5307 solver.cpp:352] Iteration 70900 (1.62436 iter/s, 61.5626s/100 iter), 137.1/232ep, loss = 3.02674
-I0511 03:11:18.668010  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.99819 (* 1 = 3.99819 loss)
-I0511 03:11:18.668016  5307 sgd_solver.cpp:172] Iteration 70900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:12:20.048511  5307 solver.cpp:352] Iteration 71000 (1.62921 iter/s, 61.3795s/100 iter), 137.3/232ep, loss = 3.13359
-I0511 03:12:20.051676  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.6327 (* 1 = 3.6327 loss)
-I0511 03:12:20.051697  5307 sgd_solver.cpp:172] Iteration 71000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:13:21.222898  5307 solver.cpp:352] Iteration 71100 (1.6347 iter/s, 61.1733s/100 iter), 137.5/232ep, loss = 3.08443
-I0511 03:13:21.225001  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2047 (* 1 = 3.2047 loss)
-I0511 03:13:21.225018  5307 sgd_solver.cpp:172] Iteration 71100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:14:21.752249  5307 solver.cpp:352] Iteration 71200 (1.65212 iter/s, 60.5283s/100 iter), 137.7/232ep, loss = 2.94043
-I0511 03:14:21.752353  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73582 (* 1 = 2.73582 loss)
-I0511 03:14:21.752368  5307 sgd_solver.cpp:172] Iteration 71200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:15:23.472234  5307 solver.cpp:352] Iteration 71300 (1.62025 iter/s, 61.7189s/100 iter), 137.9/232ep, loss = 3.25058
-I0511 03:15:23.476651  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54697 (* 1 = 3.54697 loss)
-I0511 03:15:23.476688  5307 sgd_solver.cpp:172] Iteration 71300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:15:59.221091  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:16:24.756625  5307 solver.cpp:352] Iteration 71400 (1.63176 iter/s, 61.2834s/100 iter), 138/232ep, loss = 3.00779
-I0511 03:16:24.756692  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.75285 (* 1 = 2.75285 loss)
-I0511 03:16:24.756788  5307 sgd_solver.cpp:172] Iteration 71400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:17:33.508616  5307 solver.cpp:352] Iteration 71500 (1.45453 iter/s, 68.7508s/100 iter), 138.2/232ep, loss = 3.13443
-I0511 03:17:33.508985  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40484 (* 1 = 3.40484 loss)
-I0511 03:17:33.508996  5307 sgd_solver.cpp:172] Iteration 71500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:18:36.579047  5307 solver.cpp:352] Iteration 71600 (1.58556 iter/s, 63.0693s/100 iter), 138.4/232ep, loss = 3.07886
-I0511 03:18:36.579121  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.34027 (* 1 = 3.34027 loss)
-I0511 03:18:36.579138  5307 sgd_solver.cpp:172] Iteration 71600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:19:37.170053  5307 solver.cpp:352] Iteration 71700 (1.65044 iter/s, 60.59s/100 iter), 138.6/232ep, loss = 3.27583
-I0511 03:19:37.170119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00287 (* 1 = 3.00287 loss)
-I0511 03:19:37.170125  5307 sgd_solver.cpp:172] Iteration 71700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:20:37.967916  5307 solver.cpp:352] Iteration 71800 (1.64482 iter/s, 60.7968s/100 iter), 138.8/232ep, loss = 3.22436
-I0511 03:20:37.967975  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.96683 (* 1 = 3.96683 loss)
-I0511 03:20:37.967983  5307 sgd_solver.cpp:172] Iteration 71800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:21:24.001253  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:21:39.559343  5307 solver.cpp:352] Iteration 71900 (1.62363 iter/s, 61.5904s/100 iter), 139/232ep, loss = 3.02662
-I0511 03:21:39.559372  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.47239 (* 1 = 2.47239 loss)
-I0511 03:21:39.559381  5307 sgd_solver.cpp:172] Iteration 71900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:22:39.245753  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_72000.caffemodel
-I0511 03:22:39.260543  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_72000.solverstate
-I0511 03:22:39.265848  5307 solver.cpp:635] Iteration 72000, Testing net (#0)
-I0511 03:23:19.926988  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:23:20.152026  5307 solver.cpp:747] class AP 1: 0.643178
-I0511 03:23:20.152619  5307 solver.cpp:747] class AP 2: 0.730592
-I0511 03:23:20.158911  5307 solver.cpp:747] class AP 3: 0.525441
-I0511 03:23:20.163348  5307 solver.cpp:747] class AP 4: 0.490848
-I0511 03:23:20.185232  5307 solver.cpp:747] class AP 5: 0.323959
-I0511 03:23:20.185839  5307 solver.cpp:747] class AP 6: 0.7124
-I0511 03:23:20.197413  5307 solver.cpp:747] class AP 7: 0.699418
-I0511 03:23:20.197970  5307 solver.cpp:747] class AP 8: 0.796918
-I0511 03:23:20.217874  5307 solver.cpp:747] class AP 9: 0.412358
-I0511 03:23:20.218621  5307 solver.cpp:747] class AP 10: 0.612703
-I0511 03:23:20.219408  5307 solver.cpp:747] class AP 11: 0.583159
-I0511 03:23:20.220283  5307 solver.cpp:747] class AP 12: 0.718245
-I0511 03:23:20.220710  5307 solver.cpp:747] class AP 13: 0.788613
-I0511 03:23:20.221154  5307 solver.cpp:747] class AP 14: 0.743379
-I0511 03:23:20.272939  5307 solver.cpp:747] class AP 15: 0.721877
-I0511 03:23:20.278545  5307 solver.cpp:747] class AP 16: 0.348866
-I0511 03:23:20.281221  5307 solver.cpp:747] class AP 17: 0.583127
-I0511 03:23:20.281805  5307 solver.cpp:747] class AP 18: 0.60061
-I0511 03:23:20.282523  5307 solver.cpp:747] class AP 19: 0.748297
-I0511 03:23:20.283898  5307 solver.cpp:747] class AP 20: 0.59774
-I0511 03:23:20.283905  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.619087
-I0511 03:23:20.284065  5307 solver.cpp:283] Tests completed in 100.723s
-I0511 03:23:20.840155  5307 solver.cpp:352] Iteration 72000 (0.992822 iter/s, 100.723s/100 iter), 139.2/232ep, loss = 3.05155
-I0511 03:23:20.840183  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95617 (* 1 = 2.95617 loss)
-I0511 03:23:20.840191  5307 sgd_solver.cpp:172] Iteration 72000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:24:21.332583  5307 solver.cpp:352] Iteration 72100 (1.65313 iter/s, 60.4914s/100 iter), 139.4/232ep, loss = 3.07664
-I0511 03:24:21.332656  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57719 (* 1 = 3.57719 loss)
-I0511 03:24:21.332665  5307 sgd_solver.cpp:172] Iteration 72100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:25:21.916609  5307 solver.cpp:352] Iteration 72200 (1.65063 iter/s, 60.583s/100 iter), 139.6/232ep, loss = 3.06678
-I0511 03:25:21.920967  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38199 (* 1 = 3.38199 loss)
-I0511 03:25:21.921028  5307 sgd_solver.cpp:172] Iteration 72200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:26:22.121351  5307 solver.cpp:352] Iteration 72300 (1.66103 iter/s, 60.2037s/100 iter), 139.8/232ep, loss = 3.00508
-I0511 03:26:22.121433  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74731 (* 1 = 2.74731 loss)
-I0511 03:26:22.121441  5307 sgd_solver.cpp:172] Iteration 72300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:27:18.519220  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:27:22.728324  5307 solver.cpp:352] Iteration 72400 (1.65 iter/s, 60.6059s/100 iter), 140/232ep, loss = 3.1278
-I0511 03:27:22.728421  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.64797 (* 1 = 2.64797 loss)
-I0511 03:27:22.728431  5307 sgd_solver.cpp:172] Iteration 72400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:28:23.054373  5307 solver.cpp:352] Iteration 72500 (1.65769 iter/s, 60.325s/100 iter), 140.2/232ep, loss = 3.01141
-I0511 03:28:23.054436  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71092 (* 1 = 2.71092 loss)
-I0511 03:28:23.054445  5307 sgd_solver.cpp:172] Iteration 72500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:29:23.481869  5307 solver.cpp:352] Iteration 72600 (1.6549 iter/s, 60.4265s/100 iter), 140.4/232ep, loss = 3.26152
-I0511 03:29:23.481925  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14742 (* 1 = 3.14742 loss)
-I0511 03:29:23.481932  5307 sgd_solver.cpp:172] Iteration 72600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:30:23.728221  5307 solver.cpp:352] Iteration 72700 (1.65988 iter/s, 60.2453s/100 iter), 140.6/232ep, loss = 3.17499
-I0511 03:30:23.728341  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.33493 (* 1 = 4.33493 loss)
-I0511 03:30:23.728349  5307 sgd_solver.cpp:172] Iteration 72700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:31:23.844614  5307 solver.cpp:352] Iteration 72800 (1.66347 iter/s, 60.1154s/100 iter), 140.8/232ep, loss = 3.15664
-I0511 03:31:23.844673  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.66648 (* 1 = 3.66648 loss)
-I0511 03:31:23.844682  5307 sgd_solver.cpp:172] Iteration 72800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:32:24.520457  5307 solver.cpp:352] Iteration 72900 (1.64813 iter/s, 60.6748s/100 iter), 140.9/232ep, loss = 2.99479
-I0511 03:32:24.520572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.53888 (* 1 = 2.53888 loss)
-I0511 03:32:24.520582  5307 sgd_solver.cpp:172] Iteration 72900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:32:30.003759  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:33:25.126344  5307 solver.cpp:352] Iteration 73000 (1.65003 iter/s, 60.6049s/100 iter), 141.1/232ep, loss = 2.92323
-I0511 03:33:25.126405  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.59324 (* 1 = 2.59324 loss)
-I0511 03:33:25.126415  5307 sgd_solver.cpp:172] Iteration 73000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:34:25.279366  5307 solver.cpp:352] Iteration 73100 (1.66246 iter/s, 60.152s/100 iter), 141.3/232ep, loss = 3.19742
-I0511 03:34:25.279520  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.23241 (* 1 = 3.23241 loss)
-I0511 03:34:25.279536  5307 sgd_solver.cpp:172] Iteration 73100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:35:25.761797  5307 solver.cpp:352] Iteration 73200 (1.6534 iter/s, 60.4814s/100 iter), 141.5/232ep, loss = 3.00938
-I0511 03:35:25.761957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9753 (* 1 = 2.9753 loss)
-I0511 03:35:25.761970  5307 sgd_solver.cpp:172] Iteration 73200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:36:26.001161  5307 solver.cpp:352] Iteration 73300 (1.66007 iter/s, 60.2383s/100 iter), 141.7/232ep, loss = 3.24271
-I0511 03:36:26.001288  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25406 (* 1 = 3.25406 loss)
-I0511 03:36:26.001312  5307 sgd_solver.cpp:172] Iteration 73300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:37:26.115409  5307 solver.cpp:352] Iteration 73400 (1.66353 iter/s, 60.1132s/100 iter), 141.9/232ep, loss = 2.95538
-I0511 03:37:26.115499  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.21927 (* 1 = 4.21927 loss)
-I0511 03:37:26.115511  5307 sgd_solver.cpp:172] Iteration 73400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:37:42.700953  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:38:27.965601  5307 solver.cpp:352] Iteration 73500 (1.61684 iter/s, 61.8491s/100 iter), 142.1/232ep, loss = 2.98142
-I0511 03:38:27.965658  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88538 (* 1 = 2.88538 loss)
-I0511 03:38:27.965667  5307 sgd_solver.cpp:172] Iteration 73500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:39:28.462384  5307 solver.cpp:352] Iteration 73600 (1.65301 iter/s, 60.4957s/100 iter), 142.3/232ep, loss = 3.18136
-I0511 03:39:28.462545  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7183 (* 1 = 2.7183 loss)
-I0511 03:39:28.462556  5307 sgd_solver.cpp:172] Iteration 73600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:40:29.701385  5307 solver.cpp:352] Iteration 73700 (1.63297 iter/s, 61.2379s/100 iter), 142.5/232ep, loss = 3.24209
-I0511 03:40:29.701820  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14435 (* 1 = 3.14435 loss)
-I0511 03:40:29.701833  5307 sgd_solver.cpp:172] Iteration 73700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:41:30.354627  5307 solver.cpp:352] Iteration 73800 (1.64874 iter/s, 60.6522s/100 iter), 142.7/232ep, loss = 3.10667
-I0511 03:41:30.360618  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50329 (* 1 = 3.50329 loss)
-I0511 03:41:30.360646  5307 sgd_solver.cpp:172] Iteration 73800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:42:30.918884  5307 solver.cpp:352] Iteration 73900 (1.65117 iter/s, 60.5632s/100 iter), 142.9/232ep, loss = 2.98285
-I0511 03:42:30.918987  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23428 (* 1 = 2.23428 loss)
-I0511 03:42:30.918998  5307 sgd_solver.cpp:172] Iteration 73900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:42:57.789077  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:43:30.908464  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_74000.caffemodel
-I0511 03:43:30.925472  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_74000.solverstate
-I0511 03:43:30.930797  5307 solver.cpp:635] Iteration 74000, Testing net (#0)
-I0511 03:44:11.253901  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:44:11.489528  5307 solver.cpp:747] class AP 1: 0.641228
-I0511 03:44:11.490033  5307 solver.cpp:747] class AP 2: 0.726448
-I0511 03:44:11.495765  5307 solver.cpp:747] class AP 3: 0.532019
-I0511 03:44:11.499542  5307 solver.cpp:747] class AP 4: 0.513854
-I0511 03:44:11.519951  5307 solver.cpp:747] class AP 5: 0.325712
-I0511 03:44:11.520368  5307 solver.cpp:747] class AP 6: 0.730229
-I0511 03:44:11.529734  5307 solver.cpp:747] class AP 7: 0.697817
-I0511 03:44:11.530369  5307 solver.cpp:747] class AP 8: 0.799968
-I0511 03:44:11.547799  5307 solver.cpp:747] class AP 9: 0.416313
-I0511 03:44:11.548456  5307 solver.cpp:747] class AP 10: 0.634536
-I0511 03:44:11.549134  5307 solver.cpp:747] class AP 11: 0.569721
-I0511 03:44:11.549952  5307 solver.cpp:747] class AP 12: 0.724131
-I0511 03:44:11.550333  5307 solver.cpp:747] class AP 13: 0.784362
-I0511 03:44:11.550717  5307 solver.cpp:747] class AP 14: 0.745329
-I0511 03:44:11.598302  5307 solver.cpp:747] class AP 15: 0.721109
-I0511 03:44:11.605280  5307 solver.cpp:747] class AP 16: 0.365057
-I0511 03:44:11.607946  5307 solver.cpp:747] class AP 17: 0.59138
-I0511 03:44:11.608561  5307 solver.cpp:747] class AP 18: 0.597681
-I0511 03:44:11.609176  5307 solver.cpp:747] class AP 19: 0.748637
-I0511 03:44:11.610620  5307 solver.cpp:747] class AP 20: 0.598941
-I0511 03:44:11.610625  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.623223
-I0511 03:44:11.610837  5307 solver.cpp:283] Tests completed in 100.69s
-I0511 03:44:12.156131  5307 solver.cpp:352] Iteration 74000 (0.993144 iter/s, 100.69s/100 iter), 143.1/232ep, loss = 3.17362
-I0511 03:44:12.156162  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.56647 (* 1 = 2.56647 loss)
-I0511 03:44:12.156170  5307 sgd_solver.cpp:172] Iteration 74000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:45:12.416200  5307 solver.cpp:352] Iteration 74100 (1.6595 iter/s, 60.259s/100 iter), 143.3/232ep, loss = 3.02609
-I0511 03:45:12.416337  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.72373 (* 1 = 2.72373 loss)
-I0511 03:45:12.416348  5307 sgd_solver.cpp:172] Iteration 74100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:46:12.726747  5307 solver.cpp:352] Iteration 74200 (1.65811 iter/s, 60.3095s/100 iter), 143.5/232ep, loss = 3.04684
-I0511 03:46:12.726939  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.64403 (* 1 = 2.64403 loss)
-I0511 03:46:12.726958  5307 sgd_solver.cpp:172] Iteration 74200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:47:13.618039  5307 solver.cpp:352] Iteration 74300 (1.6423 iter/s, 60.8902s/100 iter), 143.7/232ep, loss = 3.13517
-I0511 03:47:13.618142  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.88684 (* 1 = 2.88684 loss)
-I0511 03:47:13.618157  5307 sgd_solver.cpp:172] Iteration 74300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:48:14.861030  5307 solver.cpp:352] Iteration 74400 (1.63287 iter/s, 61.242s/100 iter), 143.8/232ep, loss = 3.45337
-I0511 03:48:14.861167  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3419 (* 1 = 3.3419 loss)
-I0511 03:48:14.861178  5307 sgd_solver.cpp:172] Iteration 74400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:48:51.966392  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:49:15.283468  5307 solver.cpp:352] Iteration 74500 (1.65504 iter/s, 60.4214s/100 iter), 144/232ep, loss = 2.85047
-I0511 03:49:15.283495  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.93082 (* 1 = 2.93082 loss)
-I0511 03:49:15.283504  5307 sgd_solver.cpp:172] Iteration 74500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:50:15.385535  5307 solver.cpp:352] Iteration 74600 (1.66386 iter/s, 60.1011s/100 iter), 144.2/232ep, loss = 3.20432
-I0511 03:50:15.385777  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.67358 (* 1 = 2.67358 loss)
-I0511 03:50:15.385788  5307 sgd_solver.cpp:172] Iteration 74600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:51:15.879094  5307 solver.cpp:352] Iteration 74700 (1.6531 iter/s, 60.4925s/100 iter), 144.4/232ep, loss = 3.25151
-I0511 03:51:15.879184  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59463 (* 1 = 3.59463 loss)
-I0511 03:51:15.879199  5307 sgd_solver.cpp:172] Iteration 74700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:52:16.319046  5307 solver.cpp:352] Iteration 74800 (1.65456 iter/s, 60.4389s/100 iter), 144.6/232ep, loss = 3.18278
-I0511 03:52:16.319164  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4493 (* 1 = 3.4493 loss)
-I0511 03:52:16.319173  5307 sgd_solver.cpp:172] Iteration 74800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:53:17.035173  5307 solver.cpp:352] Iteration 74900 (1.64704 iter/s, 60.7151s/100 iter), 144.8/232ep, loss = 2.96317
-I0511 03:53:17.035262  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10215 (* 1 = 3.10215 loss)
-I0511 03:53:17.035274  5307 sgd_solver.cpp:172] Iteration 74900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:54:04.660311  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:54:17.287374  5307 solver.cpp:352] Iteration 75000 (1.65972 iter/s, 60.2512s/100 iter), 145/232ep, loss = 3.04642
-I0511 03:54:17.287405  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91731 (* 1 = 2.91731 loss)
-I0511 03:54:17.287411  5307 sgd_solver.cpp:172] Iteration 75000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:55:16.952937  5307 solver.cpp:352] Iteration 75100 (1.67604 iter/s, 59.6646s/100 iter), 145.2/232ep, loss = 3.07866
-I0511 03:55:16.953037  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96777 (* 1 = 2.96777 loss)
-I0511 03:55:16.953059  5307 sgd_solver.cpp:172] Iteration 75100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:56:17.980620  5307 solver.cpp:352] Iteration 75200 (1.63863 iter/s, 61.0266s/100 iter), 145.4/232ep, loss = 3.0594
-I0511 03:56:17.980721  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.35611 (* 1 = 3.35611 loss)
-I0511 03:56:17.980746  5307 sgd_solver.cpp:172] Iteration 75200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:57:19.051538  5307 solver.cpp:352] Iteration 75300 (1.63747 iter/s, 61.0699s/100 iter), 145.6/232ep, loss = 3.14592
-I0511 03:57:19.051651  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.43066 (* 1 = 2.43066 loss)
-I0511 03:57:19.051674  5307 sgd_solver.cpp:172] Iteration 75300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:58:20.779593  5307 solver.cpp:352] Iteration 75400 (1.62004 iter/s, 61.727s/100 iter), 145.8/232ep, loss = 2.98371
-I0511 03:58:20.780081  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68028 (* 1 = 3.68028 loss)
-I0511 03:58:20.780143  5307 sgd_solver.cpp:172] Iteration 75400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 03:59:19.123008  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 03:59:22.062898  5307 solver.cpp:352] Iteration 75500 (1.63179 iter/s, 61.2823s/100 iter), 146/232ep, loss = 3.34483
-I0511 03:59:22.062996  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.76846 (* 1 = 3.76846 loss)
-I0511 03:59:22.063019  5307 sgd_solver.cpp:172] Iteration 75500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:00:23.406405  5307 solver.cpp:352] Iteration 75600 (1.63019 iter/s, 61.3425s/100 iter), 146.2/232ep, loss = 2.99761
-I0511 04:00:23.406504  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.74646 (* 1 = 2.74646 loss)
-I0511 04:00:23.406527  5307 sgd_solver.cpp:172] Iteration 75600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:01:25.636024  5307 solver.cpp:352] Iteration 75700 (1.60698 iter/s, 62.2285s/100 iter), 146.4/232ep, loss = 3.04397
-I0511 04:01:25.636116  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0651 (* 1 = 4.0651 loss)
-I0511 04:01:25.636124  5307 sgd_solver.cpp:172] Iteration 75700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:02:27.433805  5307 solver.cpp:352] Iteration 75800 (1.61821 iter/s, 61.7967s/100 iter), 146.6/232ep, loss = 3.0474
-I0511 04:02:27.433866  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96175 (* 1 = 2.96175 loss)
-I0511 04:02:27.433876  5307 sgd_solver.cpp:172] Iteration 75800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:03:28.920656  5307 solver.cpp:352] Iteration 75900 (1.62639 iter/s, 61.4858s/100 iter), 146.7/232ep, loss = 3.04129
-I0511 04:03:28.921588  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.01541 (* 1 = 2.01541 loss)
-I0511 04:03:28.921612  5307 sgd_solver.cpp:172] Iteration 75900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:04:29.593194  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_76000.caffemodel
-I0511 04:04:29.607446  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_76000.solverstate
-I0511 04:04:29.613701  5307 solver.cpp:635] Iteration 76000, Testing net (#0)
-I0511 04:05:10.383334  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:05:10.593204  5307 solver.cpp:747] class AP 1: 0.637343
-I0511 04:05:10.593714  5307 solver.cpp:747] class AP 2: 0.725514
-I0511 04:05:10.600751  5307 solver.cpp:747] class AP 3: 0.543728
-I0511 04:05:10.604346  5307 solver.cpp:747] class AP 4: 0.513556
-I0511 04:05:10.624176  5307 solver.cpp:747] class AP 5: 0.327433
-I0511 04:05:10.624552  5307 solver.cpp:747] class AP 6: 0.710337
-I0511 04:05:10.632586  5307 solver.cpp:747] class AP 7: 0.696507
-I0511 04:05:10.633287  5307 solver.cpp:747] class AP 8: 0.80158
-I0511 04:05:10.653848  5307 solver.cpp:747] class AP 9: 0.424203
-I0511 04:05:10.654513  5307 solver.cpp:747] class AP 10: 0.638241
-I0511 04:05:10.655176  5307 solver.cpp:747] class AP 11: 0.585361
-I0511 04:05:10.656023  5307 solver.cpp:747] class AP 12: 0.714094
-I0511 04:05:10.656427  5307 solver.cpp:747] class AP 13: 0.791293
-I0511 04:05:10.656805  5307 solver.cpp:747] class AP 14: 0.739938
-I0511 04:05:10.705305  5307 solver.cpp:747] class AP 15: 0.721612
-I0511 04:05:10.712443  5307 solver.cpp:747] class AP 16: 0.353075
-I0511 04:05:10.715252  5307 solver.cpp:747] class AP 17: 0.607122
-I0511 04:05:10.715829  5307 solver.cpp:747] class AP 18: 0.608899
-I0511 04:05:10.716554  5307 solver.cpp:747] class AP 19: 0.746024
-I0511 04:05:10.718053  5307 solver.cpp:747] class AP 20: 0.601709
-I0511 04:05:10.718061  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.624378
-I0511 04:05:10.718263  5307 solver.cpp:283] Tests completed in 101.796s
-I0511 04:05:11.252502  5307 solver.cpp:352] Iteration 76000 (0.982358 iter/s, 101.796s/100 iter), 146.9/232ep, loss = 2.94222
-I0511 04:05:11.252539  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.04738 (* 1 = 4.04738 loss)
-I0511 04:05:11.252548  5307 sgd_solver.cpp:172] Iteration 76000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:05:19.245709  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:06:11.964781  5307 solver.cpp:352] Iteration 76100 (1.64714 iter/s, 60.7112s/100 iter), 147.1/232ep, loss = 2.95309
-I0511 04:06:11.964931  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.86256 (* 1 = 2.86256 loss)
-I0511 04:06:11.964942  5307 sgd_solver.cpp:172] Iteration 76100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:07:12.802561  5307 solver.cpp:352] Iteration 76200 (1.64374 iter/s, 60.8367s/100 iter), 147.3/232ep, loss = 3.25318
-I0511 04:07:12.802662  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.17985 (* 1 = 4.17985 loss)
-I0511 04:07:12.802690  5307 sgd_solver.cpp:172] Iteration 76200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:08:14.762794  5307 solver.cpp:352] Iteration 76300 (1.61397 iter/s, 61.9592s/100 iter), 147.5/232ep, loss = 2.94757
-I0511 04:08:14.762857  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23976 (* 1 = 2.23976 loss)
-I0511 04:08:14.762864  5307 sgd_solver.cpp:172] Iteration 76300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:09:16.026989  5307 solver.cpp:352] Iteration 76400 (1.6323 iter/s, 61.2631s/100 iter), 147.7/232ep, loss = 3.11323
-I0511 04:09:16.027123  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.97677 (* 1 = 3.97677 loss)
-I0511 04:09:16.027142  5307 sgd_solver.cpp:172] Iteration 76400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:10:17.014519  5307 solver.cpp:352] Iteration 76500 (1.63971 iter/s, 60.9865s/100 iter), 147.9/232ep, loss = 3.02502
-I0511 04:10:17.014600  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14904 (* 1 = 3.14904 loss)
-I0511 04:10:17.014618  5307 sgd_solver.cpp:172] Iteration 76500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:10:36.196403  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:11:19.378612  5307 solver.cpp:352] Iteration 76600 (1.60351 iter/s, 62.363s/100 iter), 148.1/232ep, loss = 3.1812
-I0511 04:11:19.380671  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.34103 (* 1 = 3.34103 loss)
-I0511 04:11:19.380684  5307 sgd_solver.cpp:172] Iteration 76600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:12:21.259330  5307 solver.cpp:352] Iteration 76700 (1.61604 iter/s, 61.8797s/100 iter), 148.3/232ep, loss = 3.13056
-I0511 04:12:21.259500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73742 (* 1 = 2.73742 loss)
-I0511 04:12:21.259526  5307 sgd_solver.cpp:172] Iteration 76700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:13:23.125416  5307 solver.cpp:352] Iteration 76800 (1.61642 iter/s, 61.865s/100 iter), 148.5/232ep, loss = 3.21444
-I0511 04:13:23.125500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94929 (* 1 = 2.94929 loss)
-I0511 04:13:23.125511  5307 sgd_solver.cpp:172] Iteration 76800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:14:24.983587  5307 solver.cpp:352] Iteration 76900 (1.61663 iter/s, 61.8571s/100 iter), 148.7/232ep, loss = 2.99404
-I0511 04:14:24.983664  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85883 (* 1 = 2.85883 loss)
-I0511 04:14:24.983672  5307 sgd_solver.cpp:172] Iteration 76900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:15:26.783061  5307 solver.cpp:352] Iteration 77000 (1.61816 iter/s, 61.7984s/100 iter), 148.9/232ep, loss = 2.95391
-I0511 04:15:26.783149  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.34189 (* 1 = 2.34189 loss)
-I0511 04:15:26.783167  5307 sgd_solver.cpp:172] Iteration 77000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:15:55.960445  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:16:28.692605  5307 solver.cpp:352] Iteration 77100 (1.61529 iter/s, 61.9085s/100 iter), 149.1/232ep, loss = 3.08061
-I0511 04:16:28.693063  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6037 (* 1 = 2.6037 loss)
-I0511 04:16:28.693089  5307 sgd_solver.cpp:172] Iteration 77100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:17:30.074394  5307 solver.cpp:352] Iteration 77200 (1.62918 iter/s, 61.3808s/100 iter), 149.3/232ep, loss = 3.09659
-I0511 04:17:30.074466  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.57682 (* 1 = 2.57682 loss)
-I0511 04:17:30.074475  5307 sgd_solver.cpp:172] Iteration 77200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:18:31.458698  5307 solver.cpp:352] Iteration 77300 (1.62911 iter/s, 61.3832s/100 iter), 149.5/232ep, loss = 3.17427
-I0511 04:18:31.458783  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.77503 (* 1 = 3.77503 loss)
-I0511 04:18:31.458793  5307 sgd_solver.cpp:172] Iteration 77300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:19:33.653574  5307 solver.cpp:352] Iteration 77400 (1.60788 iter/s, 62.1938s/100 iter), 149.6/232ep, loss = 3.12145
-I0511 04:19:33.653671  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94468 (* 1 = 2.94468 loss)
-I0511 04:19:33.653678  5307 sgd_solver.cpp:172] Iteration 77400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:20:35.175375  5307 solver.cpp:352] Iteration 77500 (1.62547 iter/s, 61.5207s/100 iter), 149.8/232ep, loss = 3.29141
-I0511 04:20:35.175492  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.42403 (* 1 = 2.42403 loss)
-I0511 04:20:35.175504  5307 sgd_solver.cpp:172] Iteration 77500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:21:14.659782  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:21:35.705682  5307 solver.cpp:352] Iteration 77600 (1.65209 iter/s, 60.5293s/100 iter), 150/232ep, loss = 3.04855
-I0511 04:21:35.705739  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83429 (* 1 = 2.83429 loss)
-I0511 04:21:35.705750  5307 sgd_solver.cpp:172] Iteration 77600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:22:36.228951  5307 solver.cpp:352] Iteration 77700 (1.65228 iter/s, 60.5223s/100 iter), 150.2/232ep, loss = 3.05063
-I0511 04:22:36.229099  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.06361 (* 1 = 3.06361 loss)
-I0511 04:22:36.229125  5307 sgd_solver.cpp:172] Iteration 77700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:23:37.886205  5307 solver.cpp:352] Iteration 77800 (1.6219 iter/s, 61.6562s/100 iter), 150.4/232ep, loss = 3.20392
-I0511 04:23:37.886261  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.26003 (* 1 = 4.26003 loss)
-I0511 04:23:37.886270  5307 sgd_solver.cpp:172] Iteration 77800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:24:45.856096  5307 solver.cpp:352] Iteration 77900 (1.47126 iter/s, 67.9687s/100 iter), 150.6/232ep, loss = 3.197
-I0511 04:24:45.856202  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5935 (* 1 = 3.5935 loss)
-I0511 04:24:45.856223  5307 sgd_solver.cpp:172] Iteration 77900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:25:50.988086  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_78000.caffemodel
-I0511 04:25:51.005568  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_78000.solverstate
-I0511 04:25:51.010843  5307 solver.cpp:635] Iteration 78000, Testing net (#0)
-I0511 04:26:31.213625  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:26:31.416895  5307 solver.cpp:747] class AP 1: 0.632267
-I0511 04:26:31.417551  5307 solver.cpp:747] class AP 2: 0.7226
-I0511 04:26:31.424793  5307 solver.cpp:747] class AP 3: 0.54852
-I0511 04:26:31.428757  5307 solver.cpp:747] class AP 4: 0.509979
-I0511 04:26:31.444545  5307 solver.cpp:747] class AP 5: 0.316974
-I0511 04:26:31.444928  5307 solver.cpp:747] class AP 6: 0.724555
-I0511 04:26:31.455165  5307 solver.cpp:747] class AP 7: 0.705174
-I0511 04:26:31.455703  5307 solver.cpp:747] class AP 8: 0.798495
-I0511 04:26:31.472879  5307 solver.cpp:747] class AP 9: 0.411551
-I0511 04:26:31.473654  5307 solver.cpp:747] class AP 10: 0.616103
-I0511 04:26:31.474263  5307 solver.cpp:747] class AP 11: 0.570838
-I0511 04:26:31.475164  5307 solver.cpp:747] class AP 12: 0.724401
-I0511 04:26:31.475595  5307 solver.cpp:747] class AP 13: 0.79868
-I0511 04:26:31.476016  5307 solver.cpp:747] class AP 14: 0.739518
-I0511 04:26:31.527408  5307 solver.cpp:747] class AP 15: 0.72125
-I0511 04:26:31.532173  5307 solver.cpp:747] class AP 16: 0.356912
-I0511 04:26:31.535329  5307 solver.cpp:747] class AP 17: 0.57359
-I0511 04:26:31.535961  5307 solver.cpp:747] class AP 18: 0.596406
-I0511 04:26:31.536696  5307 solver.cpp:747] class AP 19: 0.74554
-I0511 04:26:31.538126  5307 solver.cpp:747] class AP 20: 0.598131
-I0511 04:26:31.538133  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.620574
-I0511 04:26:31.538298  5307 solver.cpp:283] Tests completed in 105.68s
-I0511 04:26:32.080586  5307 solver.cpp:352] Iteration 78000 (0.946249 iter/s, 105.68s/100 iter), 150.8/232ep, loss = 2.87031
-I0511 04:26:32.080616  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.55553 (* 1 = 2.55553 loss)
-I0511 04:26:32.080626  5307 sgd_solver.cpp:172] Iteration 78000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:27:21.375700  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:27:32.847172  5307 solver.cpp:352] Iteration 78100 (1.64567 iter/s, 60.7655s/100 iter), 151/232ep, loss = 3.09697
-I0511 04:27:32.847259  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.07398 (* 1 = 4.07398 loss)
-I0511 04:27:32.847275  5307 sgd_solver.cpp:172] Iteration 78100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:28:33.441352  5307 solver.cpp:352] Iteration 78200 (1.65035 iter/s, 60.5931s/100 iter), 151.2/232ep, loss = 2.97198
-I0511 04:28:33.441449  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01782 (* 1 = 3.01782 loss)
-I0511 04:28:33.441468  5307 sgd_solver.cpp:172] Iteration 78200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:29:34.452617  5307 solver.cpp:352] Iteration 78300 (1.63907 iter/s, 61.0102s/100 iter), 151.4/232ep, loss = 2.90562
-I0511 04:29:34.452863  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.22756 (* 1 = 2.22756 loss)
-I0511 04:29:34.452874  5307 sgd_solver.cpp:172] Iteration 78300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:30:34.917018  5307 solver.cpp:352] Iteration 78400 (1.65389 iter/s, 60.4634s/100 iter), 151.6/232ep, loss = 3.18169
-I0511 04:30:34.917094  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8036 (* 1 = 2.8036 loss)
-I0511 04:30:34.917109  5307 sgd_solver.cpp:172] Iteration 78400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:31:36.095175  5307 solver.cpp:352] Iteration 78500 (1.6346 iter/s, 61.1771s/100 iter), 151.8/232ep, loss = 3.01962
-I0511 04:31:36.095235  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8123 (* 1 = 2.8123 loss)
-I0511 04:31:36.095243  5307 sgd_solver.cpp:172] Iteration 78500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:32:35.911156  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:32:36.532106  5307 solver.cpp:352] Iteration 78600 (1.65465 iter/s, 60.4359s/100 iter), 152/232ep, loss = 3.21632
-I0511 04:32:36.532129  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.63883 (* 1 = 3.63883 loss)
-I0511 04:32:36.532133  5307 sgd_solver.cpp:172] Iteration 78600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:33:38.368151  5307 solver.cpp:352] Iteration 78700 (1.61721 iter/s, 61.835s/100 iter), 152.2/232ep, loss = 3.0718
-I0511 04:33:38.368247  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00937 (* 1 = 3.00937 loss)
-I0511 04:33:38.368254  5307 sgd_solver.cpp:172] Iteration 78700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:34:39.152809  5307 solver.cpp:352] Iteration 78800 (1.64518 iter/s, 60.7836s/100 iter), 152.4/232ep, loss = 3.26289
-I0511 04:34:39.152863  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.34513 (* 1 = 2.34513 loss)
-I0511 04:34:39.152868  5307 sgd_solver.cpp:172] Iteration 78800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:35:39.979418  5307 solver.cpp:352] Iteration 78900 (1.64405 iter/s, 60.8256s/100 iter), 152.5/232ep, loss = 2.99703
-I0511 04:35:39.979521  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28211 (* 1 = 3.28211 loss)
-I0511 04:35:39.979542  5307 sgd_solver.cpp:172] Iteration 78900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:36:41.730059  5307 solver.cpp:352] Iteration 79000 (1.61944 iter/s, 61.7496s/100 iter), 152.7/232ep, loss = 3.15469
-I0511 04:36:41.730115  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83027 (* 1 = 2.83027 loss)
-I0511 04:36:41.730124  5307 sgd_solver.cpp:172] Iteration 79000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:37:43.383158  5307 solver.cpp:352] Iteration 79100 (1.62201 iter/s, 61.652s/100 iter), 152.9/232ep, loss = 3.03458
-I0511 04:37:43.383288  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.40238 (* 1 = 3.40238 loss)
-I0511 04:37:43.383308  5307 sgd_solver.cpp:172] Iteration 79100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:37:54.007740  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:38:44.456564  5307 solver.cpp:352] Iteration 79200 (1.6374 iter/s, 61.0724s/100 iter), 153.1/232ep, loss = 3.09404
-I0511 04:38:44.456629  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.76522 (* 1 = 2.76522 loss)
-I0511 04:38:44.456636  5307 sgd_solver.cpp:172] Iteration 79200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:39:46.192864  5307 solver.cpp:352] Iteration 79300 (1.61982 iter/s, 61.7352s/100 iter), 153.3/232ep, loss = 3.07999
-I0511 04:39:46.192991  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25264 (* 1 = 3.25264 loss)
-I0511 04:39:46.193011  5307 sgd_solver.cpp:172] Iteration 79300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:40:47.734508  5307 solver.cpp:352] Iteration 79400 (1.62494 iter/s, 61.5406s/100 iter), 153.5/232ep, loss = 3.03022
-I0511 04:40:47.734652  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10661 (* 1 = 3.10661 loss)
-I0511 04:40:47.734671  5307 sgd_solver.cpp:172] Iteration 79400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:41:48.032901  5307 solver.cpp:352] Iteration 79500 (1.65845 iter/s, 60.2974s/100 iter), 153.7/232ep, loss = 3.18149
-I0511 04:41:48.032958  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.84987 (* 1 = 4.84987 loss)
-I0511 04:41:48.032968  5307 sgd_solver.cpp:172] Iteration 79500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:42:48.269826  5307 solver.cpp:352] Iteration 79600 (1.66014 iter/s, 60.2359s/100 iter), 153.9/232ep, loss = 3.0324
-I0511 04:42:48.269889  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.51017 (* 1 = 3.51017 loss)
-I0511 04:42:48.269898  5307 sgd_solver.cpp:172] Iteration 79600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:43:08.215611  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:43:48.437150  5307 solver.cpp:352] Iteration 79700 (1.66206 iter/s, 60.1663s/100 iter), 154.1/232ep, loss = 3.10614
-I0511 04:43:48.437216  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.18151 (* 1 = 3.18151 loss)
-I0511 04:43:48.437223  5307 sgd_solver.cpp:172] Iteration 79700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:44:49.525799  5307 solver.cpp:352] Iteration 79800 (1.63699 iter/s, 61.0876s/100 iter), 154.3/232ep, loss = 2.98906
-I0511 04:44:49.525918  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.24818 (* 1 = 2.24818 loss)
-I0511 04:44:49.525928  5307 sgd_solver.cpp:172] Iteration 79800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:45:50.659781  5307 solver.cpp:352] Iteration 79900 (1.63578 iter/s, 61.133s/100 iter), 154.5/232ep, loss = 3.13227
-I0511 04:45:50.659904  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.23574 (* 1 = 3.23574 loss)
-I0511 04:45:50.659934  5307 sgd_solver.cpp:172] Iteration 79900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:46:51.066712  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_80000.caffemodel
-I0511 04:46:51.080826  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_80000.solverstate
-I0511 04:46:51.084496  5307 solver.cpp:635] Iteration 80000, Testing net (#0)
-I0511 04:47:31.970968  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:47:32.214776  5307 solver.cpp:747] class AP 1: 0.656922
-I0511 04:47:32.215538  5307 solver.cpp:747] class AP 2: 0.736532
-I0511 04:47:32.223600  5307 solver.cpp:747] class AP 3: 0.537648
-I0511 04:47:32.228229  5307 solver.cpp:747] class AP 4: 0.508865
-I0511 04:47:32.246457  5307 solver.cpp:747] class AP 5: 0.331343
-I0511 04:47:32.246815  5307 solver.cpp:747] class AP 6: 0.724548
-I0511 04:47:32.254050  5307 solver.cpp:747] class AP 7: 0.694589
-I0511 04:47:32.254701  5307 solver.cpp:747] class AP 8: 0.803459
-I0511 04:47:32.274544  5307 solver.cpp:747] class AP 9: 0.431811
-I0511 04:47:32.275423  5307 solver.cpp:747] class AP 10: 0.626501
-I0511 04:47:32.276293  5307 solver.cpp:747] class AP 11: 0.587636
-I0511 04:47:32.277295  5307 solver.cpp:747] class AP 12: 0.712719
-I0511 04:47:32.277781  5307 solver.cpp:747] class AP 13: 0.787989
-I0511 04:47:32.278138  5307 solver.cpp:747] class AP 14: 0.731135
-I0511 04:47:32.329286  5307 solver.cpp:747] class AP 15: 0.721379
-I0511 04:47:32.335880  5307 solver.cpp:747] class AP 16: 0.358117
-I0511 04:47:32.338951  5307 solver.cpp:747] class AP 17: 0.586319
-I0511 04:47:32.339478  5307 solver.cpp:747] class AP 18: 0.602769
-I0511 04:47:32.340133  5307 solver.cpp:747] class AP 19: 0.74245
-I0511 04:47:32.341581  5307 solver.cpp:747] class AP 20: 0.596077
-I0511 04:47:32.341706  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.62394
-I0511 04:47:32.341799  5307 solver.cpp:283] Tests completed in 101.68s
-I0511 04:47:32.905565  5307 solver.cpp:352] Iteration 80000 (0.983475 iter/s, 101.68s/100 iter), 154.7/232ep, loss = 2.99031
-I0511 04:47:32.905604  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96569 (* 1 = 2.96569 loss)
-I0511 04:47:32.905612  5307 sgd_solver.cpp:172] Iteration 80000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:48:34.126289  5307 solver.cpp:352] Iteration 80100 (1.63346 iter/s, 61.2196s/100 iter), 154.9/232ep, loss = 2.95308
-I0511 04:48:34.126351  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89951 (* 1 = 2.89951 loss)
-I0511 04:48:34.126360  5307 sgd_solver.cpp:172] Iteration 80100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:49:05.360407  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:49:35.240214  5307 solver.cpp:352] Iteration 80200 (1.63632 iter/s, 61.1129s/100 iter), 155.1/232ep, loss = 3.06651
-I0511 04:49:35.240325  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07834 (* 1 = 3.07834 loss)
-I0511 04:49:35.240341  5307 sgd_solver.cpp:172] Iteration 80200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:50:35.741667  5307 solver.cpp:352] Iteration 80300 (1.65288 iter/s, 60.5004s/100 iter), 155.3/232ep, loss = 3.06086
-I0511 04:50:35.741739  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.36068 (* 1 = 3.36068 loss)
-I0511 04:50:35.741750  5307 sgd_solver.cpp:172] Iteration 80300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:51:37.026394  5307 solver.cpp:352] Iteration 80400 (1.63176 iter/s, 61.2837s/100 iter), 155.4/232ep, loss = 3.0957
-I0511 04:51:37.026475  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44752 (* 1 = 3.44752 loss)
-I0511 04:51:37.026511  5307 sgd_solver.cpp:172] Iteration 80400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:52:38.957073  5307 solver.cpp:352] Iteration 80500 (1.61474 iter/s, 61.9296s/100 iter), 155.6/232ep, loss = 3.05734
-I0511 04:52:38.957156  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89145 (* 1 = 2.89145 loss)
-I0511 04:52:38.957165  5307 sgd_solver.cpp:172] Iteration 80500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:53:40.124766  5307 solver.cpp:352] Iteration 80600 (1.63488 iter/s, 61.1666s/100 iter), 155.8/232ep, loss = 3.12808
-I0511 04:53:40.124861  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.12121 (* 1 = 4.12121 loss)
-I0511 04:53:40.124873  5307 sgd_solver.cpp:172] Iteration 80600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:54:22.535035  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:54:41.483376  5307 solver.cpp:352] Iteration 80700 (1.62979 iter/s, 61.3576s/100 iter), 156/232ep, loss = 3.07514
-I0511 04:54:41.483403  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65612 (* 1 = 2.65612 loss)
-I0511 04:54:41.483409  5307 sgd_solver.cpp:172] Iteration 80700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:55:43.258492  5307 solver.cpp:352] Iteration 80800 (1.6188 iter/s, 61.7741s/100 iter), 156.2/232ep, loss = 3.16967
-I0511 04:55:43.261402  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26641 (* 1 = 3.26641 loss)
-I0511 04:55:43.261415  5307 sgd_solver.cpp:172] Iteration 80800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:56:44.410297  5307 solver.cpp:352] Iteration 80900 (1.6353 iter/s, 61.1508s/100 iter), 156.4/232ep, loss = 2.97334
-I0511 04:56:44.410429  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81958 (* 1 = 2.81958 loss)
-I0511 04:56:44.410444  5307 sgd_solver.cpp:172] Iteration 80900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:57:45.559784  5307 solver.cpp:352] Iteration 81000 (1.63536 iter/s, 61.1484s/100 iter), 156.6/232ep, loss = 3.06272
-I0511 04:57:45.559870  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.07643 (* 1 = 4.07643 loss)
-I0511 04:57:45.559885  5307 sgd_solver.cpp:172] Iteration 81000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:58:47.035486  5307 solver.cpp:352] Iteration 81100 (1.62669 iter/s, 61.4747s/100 iter), 156.8/232ep, loss = 3.18442
-I0511 04:58:47.035533  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.86006 (* 1 = 1.86006 loss)
-I0511 04:58:47.035540  5307 sgd_solver.cpp:172] Iteration 81100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 04:59:39.381413  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 04:59:48.628669  5307 solver.cpp:352] Iteration 81200 (1.62358 iter/s, 61.5921s/100 iter), 157/232ep, loss = 2.97539
-I0511 04:59:48.628701  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.39648 (* 1 = 2.39648 loss)
-I0511 04:59:48.628711  5307 sgd_solver.cpp:172] Iteration 81200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:00:50.158447  5307 solver.cpp:352] Iteration 81300 (1.62526 iter/s, 61.5287s/100 iter), 157.2/232ep, loss = 3.16712
-I0511 05:00:50.158540  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.19337 (* 1 = 3.19337 loss)
-I0511 05:00:50.158632  5307 sgd_solver.cpp:172] Iteration 81300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:01:50.419970  5307 solver.cpp:352] Iteration 81400 (1.65946 iter/s, 60.2605s/100 iter), 157.4/232ep, loss = 2.95731
-I0511 05:01:50.420078  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30601 (* 1 = 3.30601 loss)
-I0511 05:01:50.420086  5307 sgd_solver.cpp:172] Iteration 81400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:02:51.010126  5307 solver.cpp:352] Iteration 81500 (1.65046 iter/s, 60.5891s/100 iter), 157.6/232ep, loss = 3.17708
-I0511 05:02:51.012492  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81883 (* 1 = 2.81883 loss)
-I0511 05:02:51.012545  5307 sgd_solver.cpp:172] Iteration 81500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:03:51.385087  5307 solver.cpp:352] Iteration 81600 (1.65634 iter/s, 60.3739s/100 iter), 157.8/232ep, loss = 3.05348
-I0511 05:03:51.385354  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47478 (* 1 = 3.47478 loss)
-I0511 05:03:51.385385  5307 sgd_solver.cpp:172] Iteration 81600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:04:52.400323  5307 solver.cpp:352] Iteration 81700 (1.63896 iter/s, 61.0142s/100 iter), 158/232ep, loss = 3.07452
-I0511 05:04:52.401495  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68926 (* 1 = 3.68926 loss)
-I0511 05:04:52.401525  5307 sgd_solver.cpp:172] Iteration 81700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:04:54.259804  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:05:52.793665  5307 solver.cpp:352] Iteration 81800 (1.65584 iter/s, 60.3923s/100 iter), 158.2/232ep, loss = 3.01624
-I0511 05:05:52.793802  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.86283 (* 1 = 2.86283 loss)
-I0511 05:05:52.793817  5307 sgd_solver.cpp:172] Iteration 81800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:06:54.638144  5307 solver.cpp:352] Iteration 81900 (1.61699 iter/s, 61.8434s/100 iter), 158.3/232ep, loss = 3.15624
-I0511 05:06:54.638219  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.09845 (* 1 = 4.09845 loss)
-I0511 05:06:54.638228  5307 sgd_solver.cpp:172] Iteration 81900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:07:55.882076  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_82000.caffemodel
-I0511 05:07:55.897613  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_82000.solverstate
-I0511 05:07:55.919564  5307 solver.cpp:635] Iteration 82000, Testing net (#0)
-I0511 05:08:36.424590  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:08:36.650754  5307 solver.cpp:747] class AP 1: 0.655134
-I0511 05:08:36.651391  5307 solver.cpp:747] class AP 2: 0.733262
-I0511 05:08:36.658165  5307 solver.cpp:747] class AP 3: 0.534205
-I0511 05:08:36.661967  5307 solver.cpp:747] class AP 4: 0.499522
-I0511 05:08:36.679430  5307 solver.cpp:747] class AP 5: 0.335833
-I0511 05:08:36.679822  5307 solver.cpp:747] class AP 6: 0.722328
-I0511 05:08:36.688561  5307 solver.cpp:747] class AP 7: 0.701715
-I0511 05:08:36.689237  5307 solver.cpp:747] class AP 8: 0.803519
-I0511 05:08:36.707600  5307 solver.cpp:747] class AP 9: 0.419425
-I0511 05:08:36.708217  5307 solver.cpp:747] class AP 10: 0.598135
-I0511 05:08:36.708843  5307 solver.cpp:747] class AP 11: 0.574544
-I0511 05:08:36.709736  5307 solver.cpp:747] class AP 12: 0.72618
-I0511 05:08:36.710386  5307 solver.cpp:747] class AP 13: 0.787962
-I0511 05:08:36.710856  5307 solver.cpp:747] class AP 14: 0.746405
-I0511 05:08:36.762650  5307 solver.cpp:747] class AP 15: 0.723499
-I0511 05:08:36.768735  5307 solver.cpp:747] class AP 16: 0.363718
-I0511 05:08:36.771150  5307 solver.cpp:747] class AP 17: 0.580612
-I0511 05:08:36.771631  5307 solver.cpp:747] class AP 18: 0.586409
-I0511 05:08:36.772302  5307 solver.cpp:747] class AP 19: 0.74642
-I0511 05:08:36.773516  5307 solver.cpp:747] class AP 20: 0.599333
-I0511 05:08:36.773522  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.621908
-I0511 05:08:36.773705  5307 solver.cpp:283] Tests completed in 102.134s
-I0511 05:08:37.404319  5307 solver.cpp:352] Iteration 82000 (0.979107 iter/s, 102.134s/100 iter), 158.5/232ep, loss = 3.12407
-I0511 05:08:37.404367  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05297 (* 1 = 3.05297 loss)
-I0511 05:08:37.404381  5307 sgd_solver.cpp:172] Iteration 82000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:09:38.488523  5307 solver.cpp:352] Iteration 82100 (1.63711 iter/s, 61.0832s/100 iter), 158.7/232ep, loss = 3.17095
-I0511 05:09:38.489747  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8145 (* 1 = 2.8145 loss)
-I0511 05:09:38.489768  5307 sgd_solver.cpp:172] Iteration 82100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:10:40.255704  5307 solver.cpp:352] Iteration 82200 (1.61901 iter/s, 61.7661s/100 iter), 158.9/232ep, loss = 3.03422
-I0511 05:10:40.255859  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23898 (* 1 = 2.23898 loss)
-I0511 05:10:40.256000  5307 sgd_solver.cpp:172] Iteration 82200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:10:51.850184  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:11:40.704710  5307 solver.cpp:352] Iteration 82300 (1.65432 iter/s, 60.448s/100 iter), 159.1/232ep, loss = 3.07507
-I0511 05:11:40.704779  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08429 (* 1 = 3.08429 loss)
-I0511 05:11:40.704788  5307 sgd_solver.cpp:172] Iteration 82300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:12:41.458498  5307 solver.cpp:352] Iteration 82400 (1.64602 iter/s, 60.7528s/100 iter), 159.3/232ep, loss = 3.13112
-I0511 05:12:41.458572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09384 (* 1 = 3.09384 loss)
-I0511 05:12:41.458581  5307 sgd_solver.cpp:172] Iteration 82400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:13:42.341801  5307 solver.cpp:352] Iteration 82500 (1.64251 iter/s, 60.8823s/100 iter), 159.5/232ep, loss = 2.99072
-I0511 05:13:42.341908  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91019 (* 1 = 2.91019 loss)
-I0511 05:13:42.341918  5307 sgd_solver.cpp:172] Iteration 82500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:14:42.496304  5307 solver.cpp:352] Iteration 82600 (1.66241 iter/s, 60.1535s/100 iter), 159.7/232ep, loss = 3.11013
-I0511 05:14:42.496400  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.54618 (* 1 = 2.54618 loss)
-I0511 05:14:42.496408  5307 sgd_solver.cpp:172] Iteration 82600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:15:43.573561  5307 solver.cpp:352] Iteration 82700 (1.6373 iter/s, 61.0762s/100 iter), 159.9/232ep, loss = 3.14549
-I0511 05:15:43.573624  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.76109 (* 1 = 3.76109 loss)
-I0511 05:15:43.573633  5307 sgd_solver.cpp:172] Iteration 82700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:16:06.394397  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:16:43.689371  5307 solver.cpp:352] Iteration 82800 (1.66348 iter/s, 60.1148s/100 iter), 160.1/232ep, loss = 3.16714
-I0511 05:16:43.689472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.97011 (* 1 = 4.97011 loss)
-I0511 05:16:43.689481  5307 sgd_solver.cpp:172] Iteration 82800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:17:43.947782  5307 solver.cpp:352] Iteration 82900 (1.65955 iter/s, 60.2574s/100 iter), 160.3/232ep, loss = 3.14576
-I0511 05:17:43.947850  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03271 (* 1 = 3.03271 loss)
-I0511 05:17:43.947860  5307 sgd_solver.cpp:172] Iteration 82900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:18:44.860479  5307 solver.cpp:352] Iteration 83000 (1.64172 iter/s, 60.9117s/100 iter), 160.5/232ep, loss = 3.07304
-I0511 05:18:44.860572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.58383 (* 1 = 2.58383 loss)
-I0511 05:18:44.860581  5307 sgd_solver.cpp:172] Iteration 83000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:19:45.264725  5307 solver.cpp:352] Iteration 83100 (1.65554 iter/s, 60.4032s/100 iter), 160.7/232ep, loss = 3.1804
-I0511 05:19:45.264848  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89042 (* 1 = 2.89042 loss)
-I0511 05:19:45.264878  5307 sgd_solver.cpp:172] Iteration 83100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:20:46.261476  5307 solver.cpp:352] Iteration 83200 (1.63946 iter/s, 60.9957s/100 iter), 160.9/232ep, loss = 3.1519
-I0511 05:20:46.261567  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90517 (* 1 = 2.90517 loss)
-I0511 05:20:46.261579  5307 sgd_solver.cpp:172] Iteration 83200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:21:19.365172  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:21:47.061985  5307 solver.cpp:352] Iteration 83300 (1.64475 iter/s, 60.7995s/100 iter), 161.1/232ep, loss = 3.04006
-I0511 05:21:47.062106  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.31735 (* 1 = 2.31735 loss)
-I0511 05:21:47.062114  5307 sgd_solver.cpp:172] Iteration 83300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:22:48.098809  5307 solver.cpp:352] Iteration 83400 (1.63838 iter/s, 61.0358s/100 iter), 161.2/232ep, loss = 2.98619
-I0511 05:22:48.098963  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.46974 (* 1 = 2.46974 loss)
-I0511 05:22:48.098987  5307 sgd_solver.cpp:172] Iteration 83400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:23:48.358436  5307 solver.cpp:352] Iteration 83500 (1.65951 iter/s, 60.2586s/100 iter), 161.4/232ep, loss = 3.22008
-I0511 05:23:48.359045  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.2878 (* 1 = 4.2878 loss)
-I0511 05:23:48.359057  5307 sgd_solver.cpp:172] Iteration 83500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:24:48.559589  5307 solver.cpp:352] Iteration 83600 (1.66113 iter/s, 60.2001s/100 iter), 161.6/232ep, loss = 3.22677
-I0511 05:24:48.559682  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.00922 (* 1 = 4.00922 loss)
-I0511 05:24:48.559692  5307 sgd_solver.cpp:172] Iteration 83600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:25:49.113479  5307 solver.cpp:352] Iteration 83700 (1.65145 iter/s, 60.5528s/100 iter), 161.8/232ep, loss = 3.1475
-I0511 05:25:49.113591  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92199 (* 1 = 2.92199 loss)
-I0511 05:25:49.113601  5307 sgd_solver.cpp:172] Iteration 83700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:26:32.403017  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:26:49.811486  5307 solver.cpp:352] Iteration 83800 (1.64753 iter/s, 60.697s/100 iter), 162/232ep, loss = 2.86257
-I0511 05:26:49.811573  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.61325 (* 1 = 2.61325 loss)
-I0511 05:26:49.811594  5307 sgd_solver.cpp:172] Iteration 83800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:27:51.098587  5307 solver.cpp:352] Iteration 83900 (1.63169 iter/s, 61.2861s/100 iter), 162.2/232ep, loss = 3.01158
-I0511 05:27:51.098793  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96056 (* 1 = 2.96056 loss)
-I0511 05:27:51.098819  5307 sgd_solver.cpp:172] Iteration 83900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:28:51.532718  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_84000.caffemodel
-I0511 05:28:51.545850  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_84000.solverstate
-I0511 05:28:51.549816  5307 solver.cpp:635] Iteration 84000, Testing net (#0)
-I0511 05:29:32.318837  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:29:32.539342  5307 solver.cpp:747] class AP 1: 0.657814
-I0511 05:29:32.539938  5307 solver.cpp:747] class AP 2: 0.710111
-I0511 05:29:32.546946  5307 solver.cpp:747] class AP 3: 0.538842
-I0511 05:29:32.551157  5307 solver.cpp:747] class AP 4: 0.516887
-I0511 05:29:32.570926  5307 solver.cpp:747] class AP 5: 0.332202
-I0511 05:29:32.571310  5307 solver.cpp:747] class AP 6: 0.720453
-I0511 05:29:32.581048  5307 solver.cpp:747] class AP 7: 0.69799
-I0511 05:29:32.581704  5307 solver.cpp:747] class AP 8: 0.808262
-I0511 05:29:32.599418  5307 solver.cpp:747] class AP 9: 0.417677
-I0511 05:29:32.600200  5307 solver.cpp:747] class AP 10: 0.610413
-I0511 05:29:32.600850  5307 solver.cpp:747] class AP 11: 0.601455
-I0511 05:29:32.601739  5307 solver.cpp:747] class AP 12: 0.726204
-I0511 05:29:32.602188  5307 solver.cpp:747] class AP 13: 0.7924
-I0511 05:29:32.602545  5307 solver.cpp:747] class AP 14: 0.737359
-I0511 05:29:32.656461  5307 solver.cpp:747] class AP 15: 0.727442
-I0511 05:29:32.663388  5307 solver.cpp:747] class AP 16: 0.360737
-I0511 05:29:32.666069  5307 solver.cpp:747] class AP 17: 0.601944
-I0511 05:29:32.666663  5307 solver.cpp:747] class AP 18: 0.595583
-I0511 05:29:32.667361  5307 solver.cpp:747] class AP 19: 0.750944
-I0511 05:29:32.668655  5307 solver.cpp:747] class AP 20: 0.604164
-I0511 05:29:32.668670  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.625444
-I0511 05:29:32.668895  5307 solver.cpp:283] Tests completed in 101.569s
-I0511 05:29:33.352635  5307 solver.cpp:352] Iteration 84000 (0.984556 iter/s, 101.569s/100 iter), 162.4/232ep, loss = 3.15069
-I0511 05:29:33.352704  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23146 (* 1 = 2.23146 loss)
-I0511 05:29:33.352723  5307 sgd_solver.cpp:172] Iteration 84000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:30:34.203102  5307 solver.cpp:352] Iteration 84100 (1.6434 iter/s, 60.8494s/100 iter), 162.6/232ep, loss = 3.1621
-I0511 05:30:34.203176  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85364 (* 1 = 3.85364 loss)
-I0511 05:30:34.203222  5307 sgd_solver.cpp:172] Iteration 84100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:31:38.800949  5307 solver.cpp:352] Iteration 84200 (1.54807 iter/s, 64.5967s/100 iter), 162.8/232ep, loss = 2.92466
-I0511 05:31:38.804613  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.49924 (* 1 = 2.49924 loss)
-I0511 05:31:38.804641  5307 sgd_solver.cpp:172] Iteration 84200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:32:40.326196  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:32:47.100292  5307 solver.cpp:352] Iteration 84300 (1.46417 iter/s, 68.2982s/100 iter), 163/232ep, loss = 3.00704
-I0511 05:32:47.100380  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16228 (* 1 = 3.16228 loss)
-I0511 05:32:47.100400  5307 sgd_solver.cpp:172] Iteration 84300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:33:48.171579  5307 solver.cpp:352] Iteration 84400 (1.63746 iter/s, 61.0702s/100 iter), 163.2/232ep, loss = 3.09693
-I0511 05:33:48.171639  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22999 (* 1 = 3.22999 loss)
-I0511 05:33:48.171648  5307 sgd_solver.cpp:172] Iteration 84400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:34:49.438040  5307 solver.cpp:352] Iteration 84500 (1.63224 iter/s, 61.2654s/100 iter), 163.4/232ep, loss = 3.14147
-I0511 05:34:49.438123  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30156 (* 1 = 3.30156 loss)
-I0511 05:34:49.438133  5307 sgd_solver.cpp:172] Iteration 84500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:35:50.558140  5307 solver.cpp:352] Iteration 84600 (1.63615 iter/s, 61.119s/100 iter), 163.6/232ep, loss = 3.1531
-I0511 05:35:50.558445  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08956 (* 1 = 3.08956 loss)
-I0511 05:35:50.558482  5307 sgd_solver.cpp:172] Iteration 84600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:36:51.441037  5307 solver.cpp:352] Iteration 84700 (1.64252 iter/s, 60.8819s/100 iter), 163.8/232ep, loss = 3.01361
-I0511 05:36:51.442643  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2958 (* 1 = 3.2958 loss)
-I0511 05:36:51.442658  5307 sgd_solver.cpp:172] Iteration 84700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:37:51.773715  5307 solver.cpp:352] Iteration 84800 (1.6575 iter/s, 60.3316s/100 iter), 164/232ep, loss = 3.08956
-I0511 05:37:51.773800  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61149 (* 1 = 3.61149 loss)
-I0511 05:37:51.773808  5307 sgd_solver.cpp:172] Iteration 84800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:37:54.923580  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:38:52.148077  5307 solver.cpp:352] Iteration 84900 (1.65636 iter/s, 60.3733s/100 iter), 164.1/232ep, loss = 2.88072
-I0511 05:38:52.148218  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33891 (* 1 = 3.33891 loss)
-I0511 05:38:52.148241  5307 sgd_solver.cpp:172] Iteration 84900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:39:52.873411  5307 solver.cpp:352] Iteration 85000 (1.64679 iter/s, 60.7243s/100 iter), 164.3/232ep, loss = 3.03843
-I0511 05:39:52.873515  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.0034 (* 1 = 3.0034 loss)
-I0511 05:39:52.873525  5307 sgd_solver.cpp:172] Iteration 85000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:40:53.578524  5307 solver.cpp:352] Iteration 85100 (1.64734 iter/s, 60.7041s/100 iter), 164.5/232ep, loss = 2.99282
-I0511 05:40:53.579010  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.06392 (* 1 = 3.06392 loss)
-I0511 05:40:53.579025  5307 sgd_solver.cpp:172] Iteration 85100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:41:54.347714  5307 solver.cpp:352] Iteration 85200 (1.6456 iter/s, 60.7682s/100 iter), 164.7/232ep, loss = 3.18014
-I0511 05:41:54.347831  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2297 (* 1 = 3.2297 loss)
-I0511 05:41:54.347851  5307 sgd_solver.cpp:172] Iteration 85200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:42:56.362783  5307 solver.cpp:352] Iteration 85300 (1.61254 iter/s, 62.014s/100 iter), 164.9/232ep, loss = 2.98081
-I0511 05:42:56.362850  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.67103 (* 1 = 2.67103 loss)
-I0511 05:42:56.362859  5307 sgd_solver.cpp:172] Iteration 85300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:43:10.316454  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:43:56.733450  5307 solver.cpp:352] Iteration 85400 (1.65646 iter/s, 60.3696s/100 iter), 165.1/232ep, loss = 3.11945
-I0511 05:43:56.733593  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08746 (* 1 = 3.08746 loss)
-I0511 05:43:56.733611  5307 sgd_solver.cpp:172] Iteration 85400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:44:58.045892  5307 solver.cpp:352] Iteration 85500 (1.63102 iter/s, 61.3114s/100 iter), 165.3/232ep, loss = 3.0195
-I0511 05:44:58.045987  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.69612 (* 1 = 2.69612 loss)
-I0511 05:44:58.046008  5307 sgd_solver.cpp:172] Iteration 85500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:45:58.778966  5307 solver.cpp:352] Iteration 85600 (1.64658 iter/s, 60.732s/100 iter), 165.5/232ep, loss = 2.96903
-I0511 05:45:58.781806  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53359 (* 1 = 3.53359 loss)
-I0511 05:45:58.781831  5307 sgd_solver.cpp:172] Iteration 85600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:46:59.483292  5307 solver.cpp:352] Iteration 85700 (1.64736 iter/s, 60.7033s/100 iter), 165.7/232ep, loss = 3.0415
-I0511 05:46:59.483381  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.60919 (* 1 = 2.60919 loss)
-I0511 05:46:59.483388  5307 sgd_solver.cpp:172] Iteration 85700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:47:59.298246  5307 solver.cpp:352] Iteration 85800 (1.67185 iter/s, 59.8139s/100 iter), 165.9/232ep, loss = 2.86475
-I0511 05:47:59.298338  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01744 (* 1 = 3.01744 loss)
-I0511 05:47:59.298348  5307 sgd_solver.cpp:172] Iteration 85800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:48:24.107800  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:48:59.673207  5307 solver.cpp:352] Iteration 85900 (1.65634 iter/s, 60.3739s/100 iter), 166.1/232ep, loss = 2.76809
-I0511 05:48:59.673928  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.84943 (* 1 = 2.84943 loss)
-I0511 05:48:59.674026  5307 sgd_solver.cpp:172] Iteration 85900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:50:00.043298  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_86000.caffemodel
-I0511 05:50:00.075486  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_86000.solverstate
-I0511 05:50:00.080802  5307 solver.cpp:635] Iteration 86000, Testing net (#0)
-I0511 05:50:40.533110  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:50:40.757798  5307 solver.cpp:747] class AP 1: 0.644248
-I0511 05:50:40.758245  5307 solver.cpp:747] class AP 2: 0.7234
-I0511 05:50:40.767001  5307 solver.cpp:747] class AP 3: 0.546652
-I0511 05:50:40.770838  5307 solver.cpp:747] class AP 4: 0.505063
-I0511 05:50:40.789113  5307 solver.cpp:747] class AP 5: 0.336162
-I0511 05:50:40.789417  5307 solver.cpp:747] class AP 6: 0.731788
-I0511 05:50:40.798163  5307 solver.cpp:747] class AP 7: 0.704465
-I0511 05:50:40.798924  5307 solver.cpp:747] class AP 8: 0.799013
-I0511 05:50:40.818701  5307 solver.cpp:747] class AP 9: 0.418467
-I0511 05:50:40.819725  5307 solver.cpp:747] class AP 10: 0.618901
-I0511 05:50:40.820538  5307 solver.cpp:747] class AP 11: 0.581964
-I0511 05:50:40.821631  5307 solver.cpp:747] class AP 12: 0.724035
-I0511 05:50:40.822109  5307 solver.cpp:747] class AP 13: 0.787672
-I0511 05:50:40.822438  5307 solver.cpp:747] class AP 14: 0.737262
-I0511 05:50:40.870316  5307 solver.cpp:747] class AP 15: 0.724478
-I0511 05:50:40.876652  5307 solver.cpp:747] class AP 16: 0.359236
-I0511 05:50:40.879967  5307 solver.cpp:747] class AP 17: 0.581703
-I0511 05:50:40.880720  5307 solver.cpp:747] class AP 18: 0.595236
-I0511 05:50:40.881427  5307 solver.cpp:747] class AP 19: 0.748551
-I0511 05:50:40.882745  5307 solver.cpp:747] class AP 20: 0.608915
-I0511 05:50:40.882756  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.62386
-I0511 05:50:40.882899  5307 solver.cpp:283] Tests completed in 101.208s
-I0511 05:50:41.464840  5307 solver.cpp:352] Iteration 86000 (0.988064 iter/s, 101.208s/100 iter), 166.3/232ep, loss = 2.9692
-I0511 05:50:41.464874  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.43173 (* 1 = 3.43173 loss)
-I0511 05:50:41.464881  5307 sgd_solver.cpp:172] Iteration 86000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:51:42.045100  5307 solver.cpp:352] Iteration 86100 (1.65073 iter/s, 60.5792s/100 iter), 166.5/232ep, loss = 3.0519
-I0511 05:51:42.045164  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30511 (* 1 = 3.30511 loss)
-I0511 05:51:42.045173  5307 sgd_solver.cpp:172] Iteration 86100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:52:42.345363  5307 solver.cpp:352] Iteration 86200 (1.6584 iter/s, 60.2992s/100 iter), 166.7/232ep, loss = 3.13449
-I0511 05:52:42.345502  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16417 (* 1 = 3.16417 loss)
-I0511 05:52:42.345513  5307 sgd_solver.cpp:172] Iteration 86200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:53:44.037740  5307 solver.cpp:352] Iteration 86300 (1.62097 iter/s, 61.6913s/100 iter), 166.9/232ep, loss = 3.16945
-I0511 05:53:44.037837  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6172 (* 1 = 2.6172 loss)
-I0511 05:53:44.037858  5307 sgd_solver.cpp:172] Iteration 86300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:54:18.505733  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:54:44.654685  5307 solver.cpp:352] Iteration 86400 (1.64973 iter/s, 60.6159s/100 iter), 167/232ep, loss = 2.95208
-I0511 05:54:44.654716  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.17169 (* 1 = 3.17169 loss)
-I0511 05:54:44.654723  5307 sgd_solver.cpp:172] Iteration 86400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:55:45.467463  5307 solver.cpp:352] Iteration 86500 (1.64442 iter/s, 60.8117s/100 iter), 167.2/232ep, loss = 3.02727
-I0511 05:55:45.467547  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26439 (* 1 = 3.26439 loss)
-I0511 05:55:45.467557  5307 sgd_solver.cpp:172] Iteration 86500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:56:45.926738  5307 solver.cpp:352] Iteration 86600 (1.65403 iter/s, 60.4583s/100 iter), 167.4/232ep, loss = 3.08285
-I0511 05:56:45.926811  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81787 (* 1 = 2.81787 loss)
-I0511 05:56:45.926820  5307 sgd_solver.cpp:172] Iteration 86600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:57:46.451650  5307 solver.cpp:352] Iteration 86700 (1.65224 iter/s, 60.5239s/100 iter), 167.6/232ep, loss = 3.07502
-I0511 05:57:46.451722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93777 (* 1 = 3.93777 loss)
-I0511 05:57:46.451735  5307 sgd_solver.cpp:172] Iteration 86700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:58:47.215143  5307 solver.cpp:352] Iteration 86800 (1.64575 iter/s, 60.7625s/100 iter), 167.8/232ep, loss = 3.04614
-I0511 05:58:47.215207  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.41199 (* 1 = 3.41199 loss)
-I0511 05:58:47.215215  5307 sgd_solver.cpp:172] Iteration 86800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 05:59:32.973482  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 05:59:48.104275  5307 solver.cpp:352] Iteration 86900 (1.64236 iter/s, 60.8881s/100 iter), 168/232ep, loss = 3.05184
-I0511 05:59:48.104303  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73959 (* 1 = 2.73959 loss)
-I0511 05:59:48.104311  5307 sgd_solver.cpp:172] Iteration 86900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:00:48.318265  5307 solver.cpp:352] Iteration 87000 (1.66077 iter/s, 60.213s/100 iter), 168.2/232ep, loss = 2.91989
-I0511 06:00:48.318336  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71483 (* 1 = 2.71483 loss)
-I0511 06:00:48.318347  5307 sgd_solver.cpp:172] Iteration 87000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:01:48.634670  5307 solver.cpp:352] Iteration 87100 (1.65795 iter/s, 60.3154s/100 iter), 168.4/232ep, loss = 2.80193
-I0511 06:01:48.635248  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.13481 (* 1 = 2.13481 loss)
-I0511 06:01:48.635268  5307 sgd_solver.cpp:172] Iteration 87100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:02:48.851761  5307 solver.cpp:352] Iteration 87200 (1.66069 iter/s, 60.2161s/100 iter), 168.6/232ep, loss = 3.02473
-I0511 06:02:48.851871  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85324 (* 1 = 2.85324 loss)
-I0511 06:02:48.851884  5307 sgd_solver.cpp:172] Iteration 87200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:03:50.542805  5307 solver.cpp:352] Iteration 87300 (1.62101 iter/s, 61.69s/100 iter), 168.8/232ep, loss = 3.01181
-I0511 06:03:50.542874  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.18435 (* 1 = 3.18435 loss)
-I0511 06:03:50.542882  5307 sgd_solver.cpp:172] Iteration 87300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:04:46.543390  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:04:52.260768  5307 solver.cpp:352] Iteration 87400 (1.6203 iter/s, 61.7169s/100 iter), 169/232ep, loss = 3.18492
-I0511 06:04:52.261236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20891 (* 1 = 3.20891 loss)
-I0511 06:04:52.261292  5307 sgd_solver.cpp:172] Iteration 87400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:05:54.376600  5307 solver.cpp:352] Iteration 87500 (1.60992 iter/s, 62.1148s/100 iter), 169.2/232ep, loss = 2.98092
-I0511 06:05:54.376689  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77034 (* 1 = 2.77034 loss)
-I0511 06:05:54.376699  5307 sgd_solver.cpp:172] Iteration 87500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:06:56.324757  5307 solver.cpp:352] Iteration 87600 (1.61428 iter/s, 61.9471s/100 iter), 169.4/232ep, loss = 3.09123
-I0511 06:06:56.324951  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.59935 (* 1 = 2.59935 loss)
-I0511 06:06:56.324972  5307 sgd_solver.cpp:172] Iteration 87600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:07:58.232978  5307 solver.cpp:352] Iteration 87700 (1.61532 iter/s, 61.9072s/100 iter), 169.6/232ep, loss = 2.86781
-I0511 06:07:58.233054  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15377 (* 1 = 3.15377 loss)
-I0511 06:07:58.233119  5307 sgd_solver.cpp:172] Iteration 87700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:09:00.459904  5307 solver.cpp:352] Iteration 87800 (1.60705 iter/s, 62.2258s/100 iter), 169.8/232ep, loss = 3.03055
-I0511 06:09:00.460453  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51731 (* 1 = 2.51731 loss)
-I0511 06:09:00.460474  5307 sgd_solver.cpp:172] Iteration 87800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:10:01.098047  5307 solver.cpp:352] Iteration 87900 (1.64916 iter/s, 60.6371s/100 iter), 169.9/232ep, loss = 2.96504
-I0511 06:10:01.098119  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.47514 (* 1 = 2.47514 loss)
-I0511 06:10:01.098127  5307 sgd_solver.cpp:172] Iteration 87900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:10:06.589433  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:11:01.903599  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_88000.caffemodel
-I0511 06:11:01.921385  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_88000.solverstate
-I0511 06:11:01.929335  5307 solver.cpp:635] Iteration 88000, Testing net (#0)
-I0511 06:11:42.505491  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:11:42.742010  5307 solver.cpp:747] class AP 1: 0.660187
-I0511 06:11:42.742581  5307 solver.cpp:747] class AP 2: 0.72923
-I0511 06:11:42.749033  5307 solver.cpp:747] class AP 3: 0.554101
-I0511 06:11:42.752707  5307 solver.cpp:747] class AP 4: 0.490957
-I0511 06:11:42.773998  5307 solver.cpp:747] class AP 5: 0.331025
-I0511 06:11:42.774334  5307 solver.cpp:747] class AP 6: 0.724311
-I0511 06:11:42.783169  5307 solver.cpp:747] class AP 7: 0.705649
-I0511 06:11:42.783768  5307 solver.cpp:747] class AP 8: 0.79094
-I0511 06:11:42.803867  5307 solver.cpp:747] class AP 9: 0.44045
-I0511 06:11:42.804479  5307 solver.cpp:747] class AP 10: 0.621599
-I0511 06:11:42.805268  5307 solver.cpp:747] class AP 11: 0.60273
-I0511 06:11:42.806205  5307 solver.cpp:747] class AP 12: 0.717561
-I0511 06:11:42.806623  5307 solver.cpp:747] class AP 13: 0.788349
-I0511 06:11:42.806979  5307 solver.cpp:747] class AP 14: 0.743536
-I0511 06:11:42.860196  5307 solver.cpp:747] class AP 15: 0.724921
-I0511 06:11:42.868512  5307 solver.cpp:747] class AP 16: 0.353575
-I0511 06:11:42.871130  5307 solver.cpp:747] class AP 17: 0.587968
-I0511 06:11:42.871780  5307 solver.cpp:747] class AP 18: 0.601266
-I0511 06:11:42.872375  5307 solver.cpp:747] class AP 19: 0.739207
-I0511 06:11:42.873889  5307 solver.cpp:747] class AP 20: 0.605896
-I0511 06:11:42.873899  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.625673
-I0511 06:11:42.874081  5307 solver.cpp:283] Tests completed in 101.774s
-I0511 06:11:43.418345  5307 solver.cpp:352] Iteration 88000 (0.982566 iter/s, 101.774s/100 iter), 170.1/232ep, loss = 3.05336
-I0511 06:11:43.418370  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.2318 (* 1 = 3.2318 loss)
-I0511 06:11:43.418378  5307 sgd_solver.cpp:172] Iteration 88000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:12:44.214612  5307 solver.cpp:352] Iteration 88100 (1.64487 iter/s, 60.7952s/100 iter), 170.3/232ep, loss = 3.18775
-I0511 06:12:44.214668  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04814 (* 1 = 3.04814 loss)
-I0511 06:12:44.214675  5307 sgd_solver.cpp:172] Iteration 88100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:13:45.426923  5307 solver.cpp:352] Iteration 88200 (1.63369 iter/s, 61.2112s/100 iter), 170.5/232ep, loss = 2.93526
-I0511 06:13:45.427034  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69837 (* 1 = 3.69837 loss)
-I0511 06:13:45.427053  5307 sgd_solver.cpp:172] Iteration 88200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:14:47.090023  5307 solver.cpp:352] Iteration 88300 (1.62174 iter/s, 61.662s/100 iter), 170.7/232ep, loss = 3.13437
-I0511 06:14:47.090090  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11089 (* 1 = 3.11089 loss)
-I0511 06:14:47.090100  5307 sgd_solver.cpp:172] Iteration 88300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:15:48.794766  5307 solver.cpp:352] Iteration 88400 (1.62065 iter/s, 61.7037s/100 iter), 170.9/232ep, loss = 3.03478
-I0511 06:15:48.795208  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.87982 (* 1 = 3.87982 loss)
-I0511 06:15:48.795225  5307 sgd_solver.cpp:172] Iteration 88400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:16:05.361198  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:16:50.024565  5307 solver.cpp:352] Iteration 88500 (1.63322 iter/s, 61.2287s/100 iter), 171.1/232ep, loss = 2.96032
-I0511 06:16:50.024686  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.97389 (* 1 = 2.97389 loss)
-I0511 06:16:50.024703  5307 sgd_solver.cpp:172] Iteration 88500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:17:52.224668  5307 solver.cpp:352] Iteration 88600 (1.60774 iter/s, 62.1991s/100 iter), 171.3/232ep, loss = 3.26774
-I0511 06:17:52.225001  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02001 (* 1 = 4.02001 loss)
-I0511 06:17:52.225014  5307 sgd_solver.cpp:172] Iteration 88600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:18:54.006628  5307 solver.cpp:352] Iteration 88700 (1.61862 iter/s, 61.7809s/100 iter), 171.5/232ep, loss = 2.90802
-I0511 06:18:54.006784  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11486 (* 1 = 3.11486 loss)
-I0511 06:18:54.006793  5307 sgd_solver.cpp:172] Iteration 88700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:19:56.394021  5307 solver.cpp:352] Iteration 88800 (1.60292 iter/s, 62.3863s/100 iter), 171.7/232ep, loss = 3.09054
-I0511 06:19:56.394305  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.78126 (* 1 = 2.78126 loss)
-I0511 06:19:56.394325  5307 sgd_solver.cpp:172] Iteration 88800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:20:57.952348  5307 solver.cpp:352] Iteration 88900 (1.6245 iter/s, 61.5573s/100 iter), 171.9/232ep, loss = 2.90461
-I0511 06:20:57.960649  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.8149 (* 1 = 2.8149 loss)
-I0511 06:20:57.960680  5307 sgd_solver.cpp:172] Iteration 88900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:21:24.568037  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:21:59.451285  5307 solver.cpp:352] Iteration 89000 (1.62607 iter/s, 61.4979s/100 iter), 172.1/232ep, loss = 2.94432
-I0511 06:21:59.451416  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15219 (* 1 = 3.15219 loss)
-I0511 06:21:59.451439  5307 sgd_solver.cpp:172] Iteration 89000, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:23:01.246716  5307 solver.cpp:352] Iteration 89100 (1.61827 iter/s, 61.7944s/100 iter), 172.3/232ep, loss = 3.05031
-I0511 06:23:01.248620  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08868 (* 1 = 3.08868 loss)
-I0511 06:23:01.248646  5307 sgd_solver.cpp:172] Iteration 89100, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:24:03.109206  5307 solver.cpp:352] Iteration 89200 (1.61652 iter/s, 61.8614s/100 iter), 172.5/232ep, loss = 2.96362
-I0511 06:24:03.109306  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3566 (* 1 = 3.3566 loss)
-I0511 06:24:03.109318  5307 sgd_solver.cpp:172] Iteration 89200, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:25:04.702862  5307 solver.cpp:352] Iteration 89300 (1.62357 iter/s, 61.5926s/100 iter), 172.7/232ep, loss = 3.08537
-I0511 06:25:04.706243  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38645 (* 1 = 3.38645 loss)
-I0511 06:25:04.706276  5307 sgd_solver.cpp:172] Iteration 89300, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:26:04.479785  5307 solver.cpp:352] Iteration 89400 (1.67292 iter/s, 59.7759s/100 iter), 172.8/232ep, loss = 3.3297
-I0511 06:26:04.480430  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.15903 (* 1 = 2.15903 loss)
-I0511 06:26:04.482417  5307 sgd_solver.cpp:172] Iteration 89400, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:26:41.524902  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:27:05.238521  5307 solver.cpp:352] Iteration 89500 (1.64588 iter/s, 60.7577s/100 iter), 173/232ep, loss = 2.87615
-I0511 06:27:05.238606  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.73996 (* 1 = 2.73996 loss)
-I0511 06:27:05.238634  5307 sgd_solver.cpp:172] Iteration 89500, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:28:05.023437  5307 solver.cpp:352] Iteration 89600 (1.67269 iter/s, 59.7839s/100 iter), 173.2/232ep, loss = 3.24382
-I0511 06:28:05.023519  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9831 (* 1 = 2.9831 loss)
-I0511 06:28:05.023528  5307 sgd_solver.cpp:172] Iteration 89600, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:29:06.104635  5307 solver.cpp:352] Iteration 89700 (1.63719 iter/s, 61.0802s/100 iter), 173.4/232ep, loss = 2.88581
-I0511 06:29:06.104703  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50106 (* 1 = 3.50106 loss)
-I0511 06:29:06.104714  5307 sgd_solver.cpp:172] Iteration 89700, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:30:05.908205  5307 solver.cpp:352] Iteration 89800 (1.67217 iter/s, 59.8026s/100 iter), 173.6/232ep, loss = 3.19147
-I0511 06:30:05.908301  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82678 (* 1 = 3.82678 loss)
-I0511 06:30:05.908309  5307 sgd_solver.cpp:172] Iteration 89800, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:31:06.240638  5307 solver.cpp:352] Iteration 89900 (1.65751 iter/s, 60.3314s/100 iter), 173.8/232ep, loss = 2.92829
-I0511 06:31:06.244410  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.11302 (* 1 = 2.11302 loss)
-I0511 06:31:06.244437  5307 sgd_solver.cpp:172] Iteration 89900, lr = 0.001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:31:54.437822  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:32:06.440652  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_90000.caffemodel
-I0511 06:32:06.464042  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_90000.solverstate
-I0511 06:32:06.470664  5307 solver.cpp:635] Iteration 90000, Testing net (#0)
-I0511 06:32:46.600402  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:32:46.823004  5307 solver.cpp:747] class AP 1: 0.652784
-I0511 06:32:46.823493  5307 solver.cpp:747] class AP 2: 0.729538
-I0511 06:32:46.831249  5307 solver.cpp:747] class AP 3: 0.55649
-I0511 06:32:46.834486  5307 solver.cpp:747] class AP 4: 0.508623
-I0511 06:32:46.852995  5307 solver.cpp:747] class AP 5: 0.329417
-I0511 06:32:46.853309  5307 solver.cpp:747] class AP 6: 0.730925
-I0511 06:32:46.861941  5307 solver.cpp:747] class AP 7: 0.694457
-I0511 06:32:46.862560  5307 solver.cpp:747] class AP 8: 0.807829
-I0511 06:32:46.881888  5307 solver.cpp:747] class AP 9: 0.420227
-I0511 06:32:46.882714  5307 solver.cpp:747] class AP 10: 0.632828
-I0511 06:32:46.883391  5307 solver.cpp:747] class AP 11: 0.577087
-I0511 06:32:46.884311  5307 solver.cpp:747] class AP 12: 0.722598
-I0511 06:32:46.884766  5307 solver.cpp:747] class AP 13: 0.793949
-I0511 06:32:46.885109  5307 solver.cpp:747] class AP 14: 0.735033
-I0511 06:32:46.930568  5307 solver.cpp:747] class AP 15: 0.723676
-I0511 06:32:46.937418  5307 solver.cpp:747] class AP 16: 0.361499
-I0511 06:32:46.940719  5307 solver.cpp:747] class AP 17: 0.601625
-I0511 06:32:46.941234  5307 solver.cpp:747] class AP 18: 0.612741
-I0511 06:32:46.941953  5307 solver.cpp:747] class AP 19: 0.744411
-I0511 06:32:46.943197  5307 solver.cpp:747] class AP 20: 0.607792
-I0511 06:32:46.943202  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.627176
-I0511 06:32:46.943362  5307 solver.cpp:283] Tests completed in 100.701s
-I0511 06:32:47.283601  5355 sgd_solver.cpp:50] MultiStep Status: Iteration 90000, step = 2
-I0511 06:32:47.528645  5307 solver.cpp:352] Iteration 90000 (0.993038 iter/s, 100.701s/100 iter), 174/232ep, loss = 3.06175
-I0511 06:32:47.528715  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.88285 (* 1 = 3.88285 loss)
-I0511 06:32:47.528735  5307 sgd_solver.cpp:172] Iteration 90000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:33:48.304985  5307 solver.cpp:352] Iteration 90100 (1.64541 iter/s, 60.7753s/100 iter), 174.2/232ep, loss = 2.96418
-I0511 06:33:48.305083  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5118 (* 1 = 2.5118 loss)
-I0511 06:33:48.305094  5307 sgd_solver.cpp:172] Iteration 90100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:34:49.420004  5307 solver.cpp:352] Iteration 90200 (1.63629 iter/s, 61.114s/100 iter), 174.4/232ep, loss = 2.87708
-I0511 06:34:49.420078  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.96865 (* 1 = 1.96865 loss)
-I0511 06:34:49.420086  5307 sgd_solver.cpp:172] Iteration 90200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:35:50.142431  5307 solver.cpp:352] Iteration 90300 (1.64687 iter/s, 60.7214s/100 iter), 174.6/232ep, loss = 3.06197
-I0511 06:35:50.142529  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.39679 (* 1 = 2.39679 loss)
-I0511 06:35:50.142539  5307 sgd_solver.cpp:172] Iteration 90300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:36:50.662226  5307 solver.cpp:352] Iteration 90400 (1.65238 iter/s, 60.5188s/100 iter), 174.8/232ep, loss = 2.87284
-I0511 06:36:50.662303  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83573 (* 1 = 2.83573 loss)
-I0511 06:36:50.662312  5307 sgd_solver.cpp:172] Iteration 90400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:37:48.705770  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:37:51.686559  5307 solver.cpp:352] Iteration 90500 (1.63872 iter/s, 61.0233s/100 iter), 175/232ep, loss = 3.05013
-I0511 06:37:51.686622  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23287 (* 1 = 2.23287 loss)
-I0511 06:37:51.686633  5307 sgd_solver.cpp:172] Iteration 90500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:38:55.799005  5307 solver.cpp:352] Iteration 90600 (1.55979 iter/s, 64.1114s/100 iter), 175.2/232ep, loss = 3.02569
-I0511 06:38:55.804631  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77855 (* 1 = 2.77855 loss)
-I0511 06:38:55.804669  5307 sgd_solver.cpp:172] Iteration 90600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:40:04.341732  5307 solver.cpp:352] Iteration 90700 (1.45897 iter/s, 68.5415s/100 iter), 175.4/232ep, loss = 3.20002
-I0511 06:40:04.341799  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9114 (* 1 = 2.9114 loss)
-I0511 06:40:04.341811  5307 sgd_solver.cpp:172] Iteration 90700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:41:06.142693  5307 solver.cpp:352] Iteration 90800 (1.61813 iter/s, 61.7999s/100 iter), 175.6/232ep, loss = 2.92238
-I0511 06:41:06.142745  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.49991 (* 1 = 2.49991 loss)
-I0511 06:41:06.142753  5307 sgd_solver.cpp:172] Iteration 90800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:42:06.225172  5307 solver.cpp:352] Iteration 90900 (1.66441 iter/s, 60.0814s/100 iter), 175.7/232ep, loss = 3.06205
-I0511 06:42:06.225240  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38434 (* 1 = 3.38434 loss)
-I0511 06:42:06.225250  5307 sgd_solver.cpp:172] Iteration 90900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:43:06.774168  5307 solver.cpp:352] Iteration 91000 (1.65158 iter/s, 60.548s/100 iter), 175.9/232ep, loss = 2.8425
-I0511 06:43:06.774284  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09239 (* 1 = 3.09239 loss)
-I0511 06:43:06.774297  5307 sgd_solver.cpp:172] Iteration 91000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:43:14.753564  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:44:06.892729  5307 solver.cpp:352] Iteration 91100 (1.66341 iter/s, 60.1176s/100 iter), 176.1/232ep, loss = 2.96822
-I0511 06:44:06.892796  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7695 (* 1 = 2.7695 loss)
-I0511 06:44:06.892803  5307 sgd_solver.cpp:172] Iteration 91100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:45:07.706563  5307 solver.cpp:352] Iteration 91200 (1.64439 iter/s, 60.8128s/100 iter), 176.3/232ep, loss = 3.08933
-I0511 06:45:07.706674  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11674 (* 1 = 3.11674 loss)
-I0511 06:45:07.706684  5307 sgd_solver.cpp:172] Iteration 91200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:46:08.655390  5307 solver.cpp:352] Iteration 91300 (1.64075 iter/s, 60.9478s/100 iter), 176.5/232ep, loss = 2.94552
-I0511 06:46:08.655488  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26752 (* 1 = 3.26752 loss)
-I0511 06:46:08.655509  5307 sgd_solver.cpp:172] Iteration 91300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:47:09.975742  5307 solver.cpp:352] Iteration 91400 (1.63081 iter/s, 61.3193s/100 iter), 176.7/232ep, loss = 2.98143
-I0511 06:47:09.975798  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4964 (* 1 = 3.4964 loss)
-I0511 06:47:09.975806  5307 sgd_solver.cpp:172] Iteration 91400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:48:10.877688  5307 solver.cpp:352] Iteration 91500 (1.64201 iter/s, 60.9009s/100 iter), 176.9/232ep, loss = 2.77348
-I0511 06:48:10.877744  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87046 (* 1 = 2.87046 loss)
-I0511 06:48:10.877751  5307 sgd_solver.cpp:172] Iteration 91500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:48:28.336748  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:49:11.077268  5307 solver.cpp:352] Iteration 91600 (1.66117 iter/s, 60.1986s/100 iter), 177.1/232ep, loss = 2.87366
-I0511 06:49:11.077348  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.23284 (* 1 = 2.23284 loss)
-I0511 06:49:11.077368  5307 sgd_solver.cpp:172] Iteration 91600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:50:12.198155  5307 solver.cpp:352] Iteration 91700 (1.63613 iter/s, 61.1199s/100 iter), 177.3/232ep, loss = 3.02639
-I0511 06:50:12.198213  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30429 (* 1 = 3.30429 loss)
-I0511 06:50:12.198221  5307 sgd_solver.cpp:172] Iteration 91700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:51:12.915246  5307 solver.cpp:352] Iteration 91800 (1.64701 iter/s, 60.7161s/100 iter), 177.5/232ep, loss = 3.15878
-I0511 06:51:12.916009  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44774 (* 1 = 3.44774 loss)
-I0511 06:51:12.916018  5307 sgd_solver.cpp:172] Iteration 91800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:52:13.195530  5307 solver.cpp:352] Iteration 91900 (1.65895 iter/s, 60.2793s/100 iter), 177.7/232ep, loss = 2.94377
-I0511 06:52:13.195955  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51839 (* 1 = 2.51839 loss)
-I0511 06:52:13.195963  5307 sgd_solver.cpp:172] Iteration 91900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:53:13.970113  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_92000.caffemodel
-I0511 06:53:13.984675  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_92000.solverstate
-I0511 06:53:13.989930  5307 solver.cpp:635] Iteration 92000, Testing net (#0)
-I0511 06:53:54.539722  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:53:54.751148  5307 solver.cpp:747] class AP 1: 0.6524
-I0511 06:53:54.751955  5307 solver.cpp:747] class AP 2: 0.72956
-I0511 06:53:54.760458  5307 solver.cpp:747] class AP 3: 0.558785
-I0511 06:53:54.765637  5307 solver.cpp:747] class AP 4: 0.518879
-I0511 06:53:54.789904  5307 solver.cpp:747] class AP 5: 0.337961
-I0511 06:53:54.790262  5307 solver.cpp:747] class AP 6: 0.732748
-I0511 06:53:54.799666  5307 solver.cpp:747] class AP 7: 0.701902
-I0511 06:53:54.800206  5307 solver.cpp:747] class AP 8: 0.804724
-I0511 06:53:54.820778  5307 solver.cpp:747] class AP 9: 0.430797
-I0511 06:53:54.821504  5307 solver.cpp:747] class AP 10: 0.621646
-I0511 06:53:54.822299  5307 solver.cpp:747] class AP 11: 0.589305
-I0511 06:53:54.823139  5307 solver.cpp:747] class AP 12: 0.718752
-I0511 06:53:54.823617  5307 solver.cpp:747] class AP 13: 0.795582
-I0511 06:53:54.823979  5307 solver.cpp:747] class AP 14: 0.749374
-I0511 06:53:54.879411  5307 solver.cpp:747] class AP 15: 0.726554
-I0511 06:53:54.886247  5307 solver.cpp:747] class AP 16: 0.357537
-I0511 06:53:54.888780  5307 solver.cpp:747] class AP 17: 0.593442
-I0511 06:53:54.889374  5307 solver.cpp:747] class AP 18: 0.619407
-I0511 06:53:54.890004  5307 solver.cpp:747] class AP 19: 0.7472
-I0511 06:53:54.891474  5307 solver.cpp:747] class AP 20: 0.609963
-I0511 06:53:54.891482  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.629826
-I0511 06:53:54.891830  5307 solver.cpp:283] Tests completed in 101.695s
-I0511 06:53:55.485334  5307 solver.cpp:352] Iteration 92000 (0.983336 iter/s, 101.695s/100 iter), 177.9/232ep, loss = 2.87393
-I0511 06:53:55.485361  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63063 (* 1 = 2.63063 loss)
-I0511 06:53:55.485369  5307 sgd_solver.cpp:172] Iteration 92000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:54:23.681706  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:54:55.911607  5307 solver.cpp:352] Iteration 92100 (1.65494 iter/s, 60.4252s/100 iter), 178.1/232ep, loss = 2.93419
-I0511 06:54:55.911684  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47136 (* 1 = 3.47136 loss)
-I0511 06:54:55.911695  5307 sgd_solver.cpp:172] Iteration 92100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:55:56.659097  5307 solver.cpp:352] Iteration 92200 (1.64619 iter/s, 60.7464s/100 iter), 178.3/232ep, loss = 3.30948
-I0511 06:55:56.659168  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.13782 (* 1 = 4.13782 loss)
-I0511 06:55:56.659178  5307 sgd_solver.cpp:172] Iteration 92200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:56:56.856077  5307 solver.cpp:352] Iteration 92300 (1.66124 iter/s, 60.1959s/100 iter), 178.5/232ep, loss = 2.98758
-I0511 06:56:56.856153  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08614 (* 1 = 3.08614 loss)
-I0511 06:56:56.856160  5307 sgd_solver.cpp:172] Iteration 92300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:57:57.516736  5307 solver.cpp:352] Iteration 92400 (1.64854 iter/s, 60.6596s/100 iter), 178.6/232ep, loss = 3.00875
-I0511 06:57:57.516957  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.93811 (* 1 = 2.93811 loss)
-I0511 06:57:57.516968  5307 sgd_solver.cpp:172] Iteration 92400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:58:58.128021  5307 solver.cpp:352] Iteration 92500 (1.64989 iter/s, 60.6103s/100 iter), 178.8/232ep, loss = 3.06919
-I0511 06:58:58.128134  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.60397 (* 1 = 3.60397 loss)
-I0511 06:58:58.128156  5307 sgd_solver.cpp:172] Iteration 92500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 06:59:37.560575  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 06:59:58.865466  5307 solver.cpp:352] Iteration 92600 (1.64646 iter/s, 60.7364s/100 iter), 179/232ep, loss = 2.9328
-I0511 06:59:58.865562  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.717 (* 1 = 2.717 loss)
-I0511 06:59:58.865584  5307 sgd_solver.cpp:172] Iteration 92600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:00:59.504809  5307 solver.cpp:352] Iteration 92700 (1.64912 iter/s, 60.6383s/100 iter), 179.2/232ep, loss = 3.177
-I0511 07:00:59.504895  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27882 (* 1 = 3.27882 loss)
-I0511 07:00:59.504904  5307 sgd_solver.cpp:172] Iteration 92700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:01:59.805862  5307 solver.cpp:352] Iteration 92800 (1.65837 iter/s, 60.3s/100 iter), 179.4/232ep, loss = 3.05714
-I0511 07:01:59.805963  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5165 (* 1 = 2.5165 loss)
-I0511 07:01:59.806018  5307 sgd_solver.cpp:172] Iteration 92800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:03:00.626083  5307 solver.cpp:352] Iteration 92900 (1.64422 iter/s, 60.8192s/100 iter), 179.6/232ep, loss = 2.963
-I0511 07:03:00.626170  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00387 (* 1 = 3.00387 loss)
-I0511 07:03:00.626179  5307 sgd_solver.cpp:172] Iteration 92900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:04:01.318279  5307 solver.cpp:352] Iteration 93000 (1.64769 iter/s, 60.6912s/100 iter), 179.8/232ep, loss = 2.90055
-I0511 07:04:01.320188  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65029 (* 1 = 2.65029 loss)
-I0511 07:04:01.320212  5307 sgd_solver.cpp:172] Iteration 93000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:04:50.817641  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:05:02.257743  5307 solver.cpp:352] Iteration 93100 (1.641 iter/s, 60.9384s/100 iter), 180/232ep, loss = 3.23961
-I0511 07:05:02.257766  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14786 (* 1 = 3.14786 loss)
-I0511 07:05:02.257772  5307 sgd_solver.cpp:172] Iteration 93100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:06:03.299690  5307 solver.cpp:352] Iteration 93200 (1.63825 iter/s, 61.0409s/100 iter), 180.2/232ep, loss = 2.91292
-I0511 07:06:03.299780  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25663 (* 1 = 3.25663 loss)
-I0511 07:06:03.299795  5307 sgd_solver.cpp:172] Iteration 93200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:07:04.007691  5307 solver.cpp:352] Iteration 93300 (1.64726 iter/s, 60.7069s/100 iter), 180.4/232ep, loss = 2.8366
-I0511 07:07:04.007822  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.76125 (* 1 = 2.76125 loss)
-I0511 07:07:04.007833  5307 sgd_solver.cpp:172] Iteration 93300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:08:05.674250  5307 solver.cpp:352] Iteration 93400 (1.62165 iter/s, 61.6655s/100 iter), 180.6/232ep, loss = 2.9875
-I0511 07:08:05.674376  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.00216 (* 1 = 3.00216 loss)
-I0511 07:08:05.674407  5307 sgd_solver.cpp:172] Iteration 93400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:09:06.510345  5307 solver.cpp:352] Iteration 93500 (1.64379 iter/s, 60.835s/100 iter), 180.8/232ep, loss = 2.91242
-I0511 07:09:06.510448  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.26614 (* 1 = 3.26614 loss)
-I0511 07:09:06.510457  5307 sgd_solver.cpp:172] Iteration 93500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:10:07.199136  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:10:07.692203  5307 solver.cpp:352] Iteration 93600 (1.6345 iter/s, 61.1808s/100 iter), 181/232ep, loss = 2.92701
-I0511 07:10:07.692236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92543 (* 1 = 2.92543 loss)
-I0511 07:10:07.692245  5307 sgd_solver.cpp:172] Iteration 93600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:11:08.276374  5307 solver.cpp:352] Iteration 93700 (1.65063 iter/s, 60.5831s/100 iter), 181.2/232ep, loss = 2.97391
-I0511 07:11:08.276445  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.84651 (* 1 = 2.84651 loss)
-I0511 07:11:08.276464  5307 sgd_solver.cpp:172] Iteration 93700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:12:09.098157  5307 solver.cpp:352] Iteration 93800 (1.64418 iter/s, 60.8207s/100 iter), 181.4/232ep, loss = 3.05575
-I0511 07:12:09.098242  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10997 (* 1 = 3.10997 loss)
-I0511 07:12:09.098258  5307 sgd_solver.cpp:172] Iteration 93800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:13:09.135836  5307 solver.cpp:352] Iteration 93900 (1.66565 iter/s, 60.0366s/100 iter), 181.5/232ep, loss = 2.79365
-I0511 07:13:09.135907  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.80829 (* 1 = 2.80829 loss)
-I0511 07:13:09.135917  5307 sgd_solver.cpp:172] Iteration 93900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:14:09.049873  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_94000.caffemodel
-I0511 07:14:09.067451  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_94000.solverstate
-I0511 07:14:09.073073  5307 solver.cpp:635] Iteration 94000, Testing net (#0)
-I0511 07:14:49.386508  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:14:49.603636  5307 solver.cpp:747] class AP 1: 0.653359
-I0511 07:14:49.604197  5307 solver.cpp:747] class AP 2: 0.73238
-I0511 07:14:49.610410  5307 solver.cpp:747] class AP 3: 0.551173
-I0511 07:14:49.614192  5307 solver.cpp:747] class AP 4: 0.511015
-I0511 07:14:49.632762  5307 solver.cpp:747] class AP 5: 0.343197
-I0511 07:14:49.633168  5307 solver.cpp:747] class AP 6: 0.732664
-I0511 07:14:49.642177  5307 solver.cpp:747] class AP 7: 0.703703
-I0511 07:14:49.642736  5307 solver.cpp:747] class AP 8: 0.806241
-I0511 07:14:49.660897  5307 solver.cpp:747] class AP 9: 0.430877
-I0511 07:14:49.661641  5307 solver.cpp:747] class AP 10: 0.626487
-I0511 07:14:49.662276  5307 solver.cpp:747] class AP 11: 0.582946
-I0511 07:14:49.663098  5307 solver.cpp:747] class AP 12: 0.72
-I0511 07:14:49.663549  5307 solver.cpp:747] class AP 13: 0.795215
-I0511 07:14:49.663914  5307 solver.cpp:747] class AP 14: 0.756727
-I0511 07:14:49.716935  5307 solver.cpp:747] class AP 15: 0.725841
-I0511 07:14:49.723117  5307 solver.cpp:747] class AP 16: 0.352762
-I0511 07:14:49.725605  5307 solver.cpp:747] class AP 17: 0.594063
-I0511 07:14:49.726192  5307 solver.cpp:747] class AP 18: 0.607985
-I0511 07:14:49.726879  5307 solver.cpp:747] class AP 19: 0.752284
-I0511 07:14:49.728354  5307 solver.cpp:747] class AP 20: 0.612051
-I0511 07:14:49.728365  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.629548
-I0511 07:14:49.728660  5307 solver.cpp:283] Tests completed in 100.591s
-I0511 07:14:50.404428  5307 solver.cpp:352] Iteration 94000 (0.994125 iter/s, 100.591s/100 iter), 181.7/232ep, loss = 3.00078
-I0511 07:14:50.404458  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03151 (* 1 = 3.03151 loss)
-I0511 07:14:50.404465  5307 sgd_solver.cpp:172] Iteration 94000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:15:51.333745  5307 solver.cpp:352] Iteration 94100 (1.64128 iter/s, 60.9282s/100 iter), 181.9/232ep, loss = 3.00365
-I0511 07:15:51.333849  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.65699 (* 1 = 1.65699 loss)
-I0511 07:15:51.333858  5307 sgd_solver.cpp:172] Iteration 94100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:16:00.422384  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:16:52.949550  5307 solver.cpp:352] Iteration 94200 (1.62299 iter/s, 61.6147s/100 iter), 182.1/232ep, loss = 2.99714
-I0511 07:16:52.949631  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91074 (* 1 = 2.91074 loss)
-I0511 07:16:52.949641  5307 sgd_solver.cpp:172] Iteration 94200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:17:53.041024  5307 solver.cpp:352] Iteration 94300 (1.66416 iter/s, 60.0903s/100 iter), 182.3/232ep, loss = 2.97779
-I0511 07:17:53.041158  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01335 (* 1 = 3.01335 loss)
-I0511 07:17:53.041172  5307 sgd_solver.cpp:172] Iteration 94300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:18:53.639108  5307 solver.cpp:352] Iteration 94400 (1.65025 iter/s, 60.597s/100 iter), 182.5/232ep, loss = 2.9533
-I0511 07:18:53.639197  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15735 (* 1 = 3.15735 loss)
-I0511 07:18:53.639212  5307 sgd_solver.cpp:172] Iteration 94400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:19:54.755478  5307 solver.cpp:352] Iteration 94500 (1.63625 iter/s, 61.1153s/100 iter), 182.7/232ep, loss = 3.05215
-I0511 07:19:54.755560  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.78547 (* 1 = 1.78547 loss)
-I0511 07:19:54.755575  5307 sgd_solver.cpp:172] Iteration 94500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:20:55.250944  5307 solver.cpp:352] Iteration 94600 (1.65305 iter/s, 60.4943s/100 iter), 182.9/232ep, loss = 2.91921
-I0511 07:20:55.251121  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6026 (* 1 = 2.6026 loss)
-I0511 07:20:55.251130  5307 sgd_solver.cpp:172] Iteration 94600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:21:15.316819  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:21:55.952729  5307 solver.cpp:352] Iteration 94700 (1.64743 iter/s, 60.7007s/100 iter), 183.1/232ep, loss = 2.97533
-I0511 07:21:55.958325  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.53738 (* 1 = 2.53738 loss)
-I0511 07:21:55.958407  5307 sgd_solver.cpp:172] Iteration 94700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:22:56.539149  5307 solver.cpp:352] Iteration 94800 (1.65056 iter/s, 60.5853s/100 iter), 183.3/232ep, loss = 2.88534
-I0511 07:22:56.551717  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51739 (* 1 = 2.51739 loss)
-I0511 07:22:56.551738  5307 sgd_solver.cpp:172] Iteration 94800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:23:57.239343  5307 solver.cpp:352] Iteration 94900 (1.64747 iter/s, 60.6991s/100 iter), 183.5/232ep, loss = 3.07979
-I0511 07:23:57.239454  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.56482 (* 1 = 2.56482 loss)
-I0511 07:23:57.239470  5307 sgd_solver.cpp:172] Iteration 94900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:24:57.647054  5307 solver.cpp:352] Iteration 95000 (1.65545 iter/s, 60.4066s/100 iter), 183.7/232ep, loss = 2.9111
-I0511 07:24:57.647584  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51917 (* 1 = 2.51917 loss)
-I0511 07:24:57.647593  5307 sgd_solver.cpp:172] Iteration 95000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:25:58.006286  5307 solver.cpp:352] Iteration 95100 (1.65678 iter/s, 60.3581s/100 iter), 183.9/232ep, loss = 2.91394
-I0511 07:25:58.006376  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.16777 (* 1 = 2.16777 loss)
-I0511 07:25:58.006386  5307 sgd_solver.cpp:172] Iteration 95100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:26:29.239646  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:26:58.534366  5307 solver.cpp:352] Iteration 95200 (1.65216 iter/s, 60.527s/100 iter), 184.1/232ep, loss = 2.99329
-I0511 07:26:58.534436  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.20944 (* 1 = 4.20944 loss)
-I0511 07:26:58.534467  5307 sgd_solver.cpp:172] Iteration 95200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:28:00.180697  5307 solver.cpp:352] Iteration 95300 (1.62219 iter/s, 61.6452s/100 iter), 184.3/232ep, loss = 3.05895
-I0511 07:28:00.180809  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.2327 (* 1 = 2.2327 loss)
-I0511 07:28:00.180820  5307 sgd_solver.cpp:172] Iteration 95300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:29:01.828652  5307 solver.cpp:352] Iteration 95400 (1.62214 iter/s, 61.6468s/100 iter), 184.4/232ep, loss = 3.03341
-I0511 07:29:01.828793  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.27634 (* 1 = 2.27634 loss)
-I0511 07:29:01.828820  5307 sgd_solver.cpp:172] Iteration 95400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:30:02.710813  5307 solver.cpp:352] Iteration 95500 (1.64255 iter/s, 60.881s/100 iter), 184.6/232ep, loss = 2.95368
-I0511 07:30:02.710907  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.47872 (* 1 = 2.47872 loss)
-I0511 07:30:02.710917  5307 sgd_solver.cpp:172] Iteration 95500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:31:03.373091  5307 solver.cpp:352] Iteration 95600 (1.6485 iter/s, 60.6612s/100 iter), 184.8/232ep, loss = 3.00084
-I0511 07:31:03.373272  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63916 (* 1 = 2.63916 loss)
-I0511 07:31:03.373291  5307 sgd_solver.cpp:172] Iteration 95600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:31:44.715602  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:32:04.248646  5307 solver.cpp:352] Iteration 95700 (1.64273 iter/s, 60.8744s/100 iter), 185/232ep, loss = 3.05273
-I0511 07:32:04.248762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04961 (* 1 = 3.04961 loss)
-I0511 07:32:04.248780  5307 sgd_solver.cpp:172] Iteration 95700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:33:04.989846  5307 solver.cpp:352] Iteration 95800 (1.64636 iter/s, 60.7401s/100 iter), 185.2/232ep, loss = 3.06251
-I0511 07:33:04.989917  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85397 (* 1 = 2.85397 loss)
-I0511 07:33:04.989924  5307 sgd_solver.cpp:172] Iteration 95800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:34:04.922678  5307 solver.cpp:352] Iteration 95900 (1.66857 iter/s, 59.9317s/100 iter), 185.4/232ep, loss = 3.11436
-I0511 07:34:04.922744  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51926 (* 1 = 2.51926 loss)
-I0511 07:34:04.922751  5307 sgd_solver.cpp:172] Iteration 95900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:35:04.914889  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_96000.caffemodel
-I0511 07:35:04.936225  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_96000.solverstate
-I0511 07:35:04.941499  5307 solver.cpp:635] Iteration 96000, Testing net (#0)
-I0511 07:35:23.672327  5352 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0511 07:35:45.077711  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:35:45.308502  5307 solver.cpp:747] class AP 1: 0.650321
-I0511 07:35:45.309023  5307 solver.cpp:747] class AP 2: 0.734017
-I0511 07:35:45.315362  5307 solver.cpp:747] class AP 3: 0.555505
-I0511 07:35:45.319352  5307 solver.cpp:747] class AP 4: 0.501021
-I0511 07:35:45.337565  5307 solver.cpp:747] class AP 5: 0.344569
-I0511 07:35:45.337915  5307 solver.cpp:747] class AP 6: 0.733044
-I0511 07:35:45.346527  5307 solver.cpp:747] class AP 7: 0.704343
-I0511 07:35:45.347060  5307 solver.cpp:747] class AP 8: 0.813259
-I0511 07:35:45.364531  5307 solver.cpp:747] class AP 9: 0.425829
-I0511 07:35:45.365254  5307 solver.cpp:747] class AP 10: 0.624562
-I0511 07:35:45.365865  5307 solver.cpp:747] class AP 11: 0.58426
-I0511 07:35:45.366700  5307 solver.cpp:747] class AP 12: 0.722605
-I0511 07:35:45.367126  5307 solver.cpp:747] class AP 13: 0.789451
-I0511 07:35:45.367465  5307 solver.cpp:747] class AP 14: 0.745061
-I0511 07:35:45.415539  5307 solver.cpp:747] class AP 15: 0.725725
-I0511 07:35:45.421653  5307 solver.cpp:747] class AP 16: 0.354737
-I0511 07:35:45.424113  5307 solver.cpp:747] class AP 17: 0.597748
-I0511 07:35:45.424669  5307 solver.cpp:747] class AP 18: 0.618047
-I0511 07:35:45.425331  5307 solver.cpp:747] class AP 19: 0.744493
-I0511 07:35:45.426846  5307 solver.cpp:747] class AP 20: 0.608665
-I0511 07:35:45.426854  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.628863
-I0511 07:35:45.427047  5307 solver.cpp:283] Tests completed in 100.503s
-I0511 07:35:45.994454  5307 solver.cpp:352] Iteration 96000 (0.995 iter/s, 100.503s/100 iter), 185.6/232ep, loss = 2.9123
-I0511 07:35:45.994532  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39141 (* 1 = 3.39141 loss)
-I0511 07:35:45.994559  5307 sgd_solver.cpp:172] Iteration 96000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:36:46.702077  5307 solver.cpp:352] Iteration 96100 (1.64727 iter/s, 60.7065s/100 iter), 185.8/232ep, loss = 3.05719
-I0511 07:36:46.702152  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16969 (* 1 = 3.16969 loss)
-I0511 07:36:46.702162  5307 sgd_solver.cpp:172] Iteration 96100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:37:38.127743  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:37:47.506345  5307 solver.cpp:352] Iteration 96200 (1.64465 iter/s, 60.8031s/100 iter), 186/232ep, loss = 2.96958
-I0511 07:37:47.506371  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.18929 (* 1 = 3.18929 loss)
-I0511 07:37:47.506381  5307 sgd_solver.cpp:172] Iteration 96200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:38:47.357182  5307 solver.cpp:352] Iteration 96300 (1.67085 iter/s, 59.8498s/100 iter), 186.2/232ep, loss = 3.00744
-I0511 07:38:47.357235  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.54607 (* 1 = 2.54607 loss)
-I0511 07:38:47.357244  5307 sgd_solver.cpp:172] Iteration 96300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:39:46.934804  5307 solver.cpp:352] Iteration 96400 (1.67851 iter/s, 59.5765s/100 iter), 186.4/232ep, loss = 2.90113
-I0511 07:39:46.934885  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7434 (* 1 = 2.7434 loss)
-I0511 07:39:46.934895  5307 sgd_solver.cpp:172] Iteration 96400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:40:46.563388  5307 solver.cpp:352] Iteration 96500 (1.67708 iter/s, 59.6275s/100 iter), 186.6/232ep, loss = 3.30584
-I0511 07:40:46.563503  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.42639 (* 1 = 3.42639 loss)
-I0511 07:40:46.563514  5307 sgd_solver.cpp:172] Iteration 96500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:41:46.848609  5307 solver.cpp:352] Iteration 96600 (1.65881 iter/s, 60.2841s/100 iter), 186.8/232ep, loss = 2.93792
-I0511 07:41:46.848676  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63076 (* 1 = 2.63076 loss)
-I0511 07:41:46.848685  5307 sgd_solver.cpp:172] Iteration 96600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:42:47.210800  5307 solver.cpp:352] Iteration 96700 (1.6567 iter/s, 60.3611s/100 iter), 187/232ep, loss = 3.05603
-I0511 07:42:47.212236  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73215 (* 1 = 3.73215 loss)
-I0511 07:42:47.212250  5307 sgd_solver.cpp:172] Iteration 96700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:42:47.932543  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:43:47.787328  5307 solver.cpp:352] Iteration 96800 (1.65083 iter/s, 60.5754s/100 iter), 187.2/232ep, loss = 3.03419
-I0511 07:43:47.787413  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.96915 (* 1 = 2.96915 loss)
-I0511 07:43:47.787425  5307 sgd_solver.cpp:172] Iteration 96800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:44:49.099545  5307 solver.cpp:352] Iteration 96900 (1.63103 iter/s, 61.3111s/100 iter), 187.3/232ep, loss = 3.09535
-I0511 07:44:49.099644  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.93823 (* 1 = 3.93823 loss)
-I0511 07:44:49.099663  5307 sgd_solver.cpp:172] Iteration 96900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:45:52.576695  5307 solver.cpp:352] Iteration 97000 (1.5754 iter/s, 63.476s/100 iter), 187.5/232ep, loss = 2.80578
-I0511 07:45:52.578472  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.33847 (* 1 = 2.33847 loss)
-I0511 07:45:52.578514  5307 sgd_solver.cpp:172] Iteration 97000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:47:00.539968  5307 solver.cpp:352] Iteration 97100 (1.47141 iter/s, 67.962s/100 iter), 187.7/232ep, loss = 2.9538
-I0511 07:47:00.540072  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27623 (* 1 = 3.27623 loss)
-I0511 07:47:00.540093  5307 sgd_solver.cpp:172] Iteration 97100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:48:01.684559  5307 solver.cpp:352] Iteration 97200 (1.6355 iter/s, 61.1434s/100 iter), 187.9/232ep, loss = 2.9581
-I0511 07:48:01.684702  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46043 (* 1 = 3.46043 loss)
-I0511 07:48:01.684712  5307 sgd_solver.cpp:172] Iteration 97200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:48:13.198102  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:49:01.896059  5307 solver.cpp:352] Iteration 97300 (1.66084 iter/s, 60.2104s/100 iter), 188.1/232ep, loss = 3.00296
-I0511 07:49:01.899176  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.27139 (* 1 = 2.27139 loss)
-I0511 07:49:01.899194  5307 sgd_solver.cpp:172] Iteration 97300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:50:02.053539  5307 solver.cpp:352] Iteration 97400 (1.66234 iter/s, 60.1563s/100 iter), 188.3/232ep, loss = 2.91776
-I0511 07:50:02.054003  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90872 (* 1 = 2.90872 loss)
-I0511 07:50:02.054015  5307 sgd_solver.cpp:172] Iteration 97400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:51:02.951967  5307 solver.cpp:352] Iteration 97500 (1.64211 iter/s, 60.8973s/100 iter), 188.5/232ep, loss = 2.875
-I0511 07:51:02.952033  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22074 (* 1 = 3.22074 loss)
-I0511 07:51:02.952041  5307 sgd_solver.cpp:172] Iteration 97500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:52:04.163118  5307 solver.cpp:352] Iteration 97600 (1.63372 iter/s, 61.21s/100 iter), 188.7/232ep, loss = 2.90709
-I0511 07:52:04.163497  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.6202 (* 1 = 3.6202 loss)
-I0511 07:52:04.163509  5307 sgd_solver.cpp:172] Iteration 97600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:53:05.139300  5307 solver.cpp:352] Iteration 97700 (1.64001 iter/s, 60.9751s/100 iter), 188.9/232ep, loss = 3.0651
-I0511 07:53:05.139398  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82895 (* 1 = 3.82895 loss)
-I0511 07:53:05.139415  5307 sgd_solver.cpp:172] Iteration 97700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:53:27.015391  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:54:05.430426  5307 solver.cpp:352] Iteration 97800 (1.65865 iter/s, 60.29s/100 iter), 189.1/232ep, loss = 2.91936
-I0511 07:54:05.430500  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.72138 (* 1 = 3.72138 loss)
-I0511 07:54:05.430510  5307 sgd_solver.cpp:172] Iteration 97800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:55:06.594501  5307 solver.cpp:352] Iteration 97900 (1.63498 iter/s, 61.163s/100 iter), 189.3/232ep, loss = 3.04614
-I0511 07:55:06.594552  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.68441 (* 1 = 2.68441 loss)
-I0511 07:55:06.594559  5307 sgd_solver.cpp:172] Iteration 97900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:56:06.258683  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_98000.caffemodel
-I0511 07:56:06.280103  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_98000.solverstate
-I0511 07:56:06.286790  5307 solver.cpp:635] Iteration 98000, Testing net (#0)
-I0511 07:56:46.613548  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:56:46.815506  5307 solver.cpp:747] class AP 1: 0.654648
-I0511 07:56:46.816174  5307 solver.cpp:747] class AP 2: 0.729718
-I0511 07:56:46.824645  5307 solver.cpp:747] class AP 3: 0.556767
-I0511 07:56:46.830163  5307 solver.cpp:747] class AP 4: 0.509277
-I0511 07:56:46.853922  5307 solver.cpp:747] class AP 5: 0.343129
-I0511 07:56:46.854557  5307 solver.cpp:747] class AP 6: 0.733831
-I0511 07:56:46.863710  5307 solver.cpp:747] class AP 7: 0.699716
-I0511 07:56:46.864267  5307 solver.cpp:747] class AP 8: 0.818443
-I0511 07:56:46.883057  5307 solver.cpp:747] class AP 9: 0.426093
-I0511 07:56:46.883762  5307 solver.cpp:747] class AP 10: 0.628663
-I0511 07:56:46.884393  5307 solver.cpp:747] class AP 11: 0.58388
-I0511 07:56:46.885224  5307 solver.cpp:747] class AP 12: 0.71764
-I0511 07:56:46.885659  5307 solver.cpp:747] class AP 13: 0.794358
-I0511 07:56:46.885994  5307 solver.cpp:747] class AP 14: 0.74868
-I0511 07:56:46.938817  5307 solver.cpp:747] class AP 15: 0.724842
-I0511 07:56:46.946049  5307 solver.cpp:747] class AP 16: 0.359878
-I0511 07:56:46.948588  5307 solver.cpp:747] class AP 17: 0.593851
-I0511 07:56:46.949234  5307 solver.cpp:747] class AP 18: 0.609637
-I0511 07:56:46.950158  5307 solver.cpp:747] class AP 19: 0.747296
-I0511 07:56:46.951679  5307 solver.cpp:747] class AP 20: 0.611734
-I0511 07:56:46.951694  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.629604
-I0511 07:56:46.951939  5307 solver.cpp:283] Tests completed in 100.356s
-I0511 07:56:47.491531  5307 solver.cpp:352] Iteration 98000 (0.996456 iter/s, 100.356s/100 iter), 189.5/232ep, loss = 3.20631
-I0511 07:56:47.491556  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01891 (* 1 = 3.01891 loss)
-I0511 07:56:47.491564  5307 sgd_solver.cpp:172] Iteration 98000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:57:47.971768  5307 solver.cpp:352] Iteration 98100 (1.65346 iter/s, 60.4791s/100 iter), 189.7/232ep, loss = 3.06749
-I0511 07:57:47.972045  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03684 (* 1 = 3.03684 loss)
-I0511 07:57:47.972064  5307 sgd_solver.cpp:172] Iteration 98100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:58:50.075870  5307 solver.cpp:352] Iteration 98200 (1.61023 iter/s, 62.103s/100 iter), 189.9/232ep, loss = 2.9852
-I0511 07:58:50.076016  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37209 (* 1 = 3.37209 loss)
-I0511 07:58:50.076025  5307 sgd_solver.cpp:172] Iteration 98200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 07:59:22.351446  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 07:59:50.813318  5307 solver.cpp:352] Iteration 98300 (1.64646 iter/s, 60.7363s/100 iter), 190.1/232ep, loss = 2.70888
-I0511 07:59:50.813359  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.57383 (* 1 = 2.57383 loss)
-I0511 07:59:50.813371  5307 sgd_solver.cpp:172] Iteration 98300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:00:51.706754  5307 solver.cpp:352] Iteration 98400 (1.64224 iter/s, 60.8923s/100 iter), 190.2/232ep, loss = 3.08315
-I0511 08:00:51.706881  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.79268 (* 1 = 2.79268 loss)
-I0511 08:00:51.706892  5307 sgd_solver.cpp:172] Iteration 98400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:01:52.966831  5307 solver.cpp:352] Iteration 98500 (1.63241 iter/s, 61.259s/100 iter), 190.4/232ep, loss = 3.01733
-I0511 08:01:52.966913  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21688 (* 1 = 3.21688 loss)
-I0511 08:01:52.966922  5307 sgd_solver.cpp:172] Iteration 98500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:02:53.233733  5307 solver.cpp:352] Iteration 98600 (1.65932 iter/s, 60.2658s/100 iter), 190.6/232ep, loss = 3.05306
-I0511 08:02:53.233789  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07683 (* 1 = 3.07683 loss)
-I0511 08:02:53.233798  5307 sgd_solver.cpp:172] Iteration 98600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:03:54.616510  5307 solver.cpp:352] Iteration 98700 (1.62915 iter/s, 61.3816s/100 iter), 190.8/232ep, loss = 3.10036
-I0511 08:03:54.616595  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22673 (* 1 = 3.22673 loss)
-I0511 08:03:54.616603  5307 sgd_solver.cpp:172] Iteration 98700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:04:38.339814  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:04:55.744252  5307 solver.cpp:352] Iteration 98800 (1.63595 iter/s, 61.1266s/100 iter), 191/232ep, loss = 2.97291
-I0511 08:04:55.744356  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05587 (* 1 = 3.05587 loss)
-I0511 08:04:55.744379  5307 sgd_solver.cpp:172] Iteration 98800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:05:56.503899  5307 solver.cpp:352] Iteration 98900 (1.64586 iter/s, 60.7585s/100 iter), 191.2/232ep, loss = 2.95962
-I0511 08:05:56.503983  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.0435 (* 1 = 3.0435 loss)
-I0511 08:05:56.503996  5307 sgd_solver.cpp:172] Iteration 98900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:06:58.032640  5307 solver.cpp:352] Iteration 99000 (1.62529 iter/s, 61.5276s/100 iter), 191.4/232ep, loss = 3.08671
-I0511 08:06:58.032723  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94509 (* 1 = 2.94509 loss)
-I0511 08:06:58.032732  5307 sgd_solver.cpp:172] Iteration 99000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:07:59.002532  5307 solver.cpp:352] Iteration 99100 (1.64018 iter/s, 60.9688s/100 iter), 191.6/232ep, loss = 3.02594
-I0511 08:07:59.002626  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.53134 (* 1 = 3.53134 loss)
-I0511 08:07:59.002635  5307 sgd_solver.cpp:172] Iteration 99100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:09:00.493904  5307 solver.cpp:352] Iteration 99200 (1.62627 iter/s, 61.4902s/100 iter), 191.8/232ep, loss = 3.0374
-I0511 08:09:00.494019  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.23447 (* 1 = 4.23447 loss)
-I0511 08:09:00.494030  5307 sgd_solver.cpp:172] Iteration 99200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:09:53.119544  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:10:01.056978  5307 solver.cpp:352] Iteration 99300 (1.6512 iter/s, 60.5619s/100 iter), 192/232ep, loss = 3.03007
-I0511 08:10:01.057054  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11184 (* 1 = 3.11184 loss)
-I0511 08:10:01.057076  5307 sgd_solver.cpp:172] Iteration 99300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:11:02.474581  5307 solver.cpp:352] Iteration 99400 (1.62823 iter/s, 61.4164s/100 iter), 192.2/232ep, loss = 3.02644
-I0511 08:11:02.474658  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58186 (* 1 = 3.58186 loss)
-I0511 08:11:02.474666  5307 sgd_solver.cpp:172] Iteration 99400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:12:03.639566  5307 solver.cpp:352] Iteration 99500 (1.63495 iter/s, 61.1639s/100 iter), 192.4/232ep, loss = 3.0477
-I0511 08:12:03.639678  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54568 (* 1 = 3.54568 loss)
-I0511 08:12:03.639699  5307 sgd_solver.cpp:172] Iteration 99500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:13:04.248728  5307 solver.cpp:352] Iteration 99600 (1.64995 iter/s, 60.608s/100 iter), 192.6/232ep, loss = 3.26572
-I0511 08:13:04.248836  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.48364 (* 1 = 3.48364 loss)
-I0511 08:13:04.248863  5307 sgd_solver.cpp:172] Iteration 99600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:14:04.842027  5307 solver.cpp:352] Iteration 99700 (1.65038 iter/s, 60.5922s/100 iter), 192.8/232ep, loss = 2.9188
-I0511 08:14:04.842499  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09875 (* 1 = 3.09875 loss)
-I0511 08:14:04.842510  5307 sgd_solver.cpp:172] Iteration 99700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:15:05.169956  5307 solver.cpp:352] Iteration 99800 (1.65764 iter/s, 60.3268s/100 iter), 193/232ep, loss = 2.89835
-I0511 08:15:05.170317  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.32569 (* 1 = 4.32569 loss)
-I0511 08:15:05.170327  5307 sgd_solver.cpp:172] Iteration 99800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:15:08.292088  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:16:06.441372  5307 solver.cpp:352] Iteration 99900 (1.63211 iter/s, 61.2703s/100 iter), 193.1/232ep, loss = 3.01729
-I0511 08:16:06.441478  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73704 (* 1 = 3.73704 loss)
-I0511 08:16:06.441498  5307 sgd_solver.cpp:172] Iteration 99900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:17:08.110452  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_100000.caffemodel
-I0511 08:17:08.130551  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_100000.solverstate
-I0511 08:17:08.136447  5307 solver.cpp:635] Iteration 100000, Testing net (#0)
-I0511 08:17:48.875803  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:17:49.103816  5307 solver.cpp:747] class AP 1: 0.665005
-I0511 08:17:49.104339  5307 solver.cpp:747] class AP 2: 0.730937
-I0511 08:17:49.110823  5307 solver.cpp:747] class AP 3: 0.558327
-I0511 08:17:49.114506  5307 solver.cpp:747] class AP 4: 0.507206
-I0511 08:17:49.132952  5307 solver.cpp:747] class AP 5: 0.34404
-I0511 08:17:49.133280  5307 solver.cpp:747] class AP 6: 0.735807
-I0511 08:17:49.141923  5307 solver.cpp:747] class AP 7: 0.701335
-I0511 08:17:49.142475  5307 solver.cpp:747] class AP 8: 0.815496
-I0511 08:17:49.160322  5307 solver.cpp:747] class AP 9: 0.425556
-I0511 08:17:49.161043  5307 solver.cpp:747] class AP 10: 0.626299
-I0511 08:17:49.161677  5307 solver.cpp:747] class AP 11: 0.592111
-I0511 08:17:49.162549  5307 solver.cpp:747] class AP 12: 0.718074
-I0511 08:17:49.162979  5307 solver.cpp:747] class AP 13: 0.792086
-I0511 08:17:49.163327  5307 solver.cpp:747] class AP 14: 0.756043
-I0511 08:17:49.222995  5307 solver.cpp:747] class AP 15: 0.725033
-I0511 08:17:49.231612  5307 solver.cpp:747] class AP 16: 0.357034
-I0511 08:17:49.234997  5307 solver.cpp:747] class AP 17: 0.597503
-I0511 08:17:49.235782  5307 solver.cpp:747] class AP 18: 0.606173
-I0511 08:17:49.236677  5307 solver.cpp:747] class AP 19: 0.749204
-I0511 08:17:49.238603  5307 solver.cpp:747] class AP 20: 0.617463
-I0511 08:17:49.238801  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631037
-I0511 08:17:49.238991  5307 solver.cpp:283] Tests completed in 102.796s
-I0511 08:17:49.832324  5307 solver.cpp:352] Iteration 100000 (0.972803 iter/s, 102.796s/100 iter), 193.3/232ep, loss = 3.0267
-I0511 08:17:49.832352  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.33654 (* 1 = 2.33654 loss)
-I0511 08:17:49.832360  5307 sgd_solver.cpp:172] Iteration 100000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:18:51.388283  5307 solver.cpp:352] Iteration 100100 (1.62457 iter/s, 61.5548s/100 iter), 193.5/232ep, loss = 2.84996
-I0511 08:18:51.388463  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.45932 (* 1 = 2.45932 loss)
-I0511 08:18:51.388489  5307 sgd_solver.cpp:172] Iteration 100100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:19:53.190773  5307 solver.cpp:352] Iteration 100200 (1.61809 iter/s, 61.8014s/100 iter), 193.7/232ep, loss = 3.15988
-I0511 08:19:53.190889  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.08743 (* 1 = 3.08743 loss)
-I0511 08:19:53.190897  5307 sgd_solver.cpp:172] Iteration 100200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:20:54.608816  5307 solver.cpp:352] Iteration 100300 (1.62822 iter/s, 61.4169s/100 iter), 193.9/232ep, loss = 2.97717
-I0511 08:20:54.608924  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.59103 (* 1 = 3.59103 loss)
-I0511 08:20:54.608954  5307 sgd_solver.cpp:172] Iteration 100300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:21:08.816452  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:21:55.471817  5307 solver.cpp:352] Iteration 100400 (1.64306 iter/s, 60.8619s/100 iter), 194.1/232ep, loss = 2.97832
-I0511 08:21:55.471938  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.36064 (* 1 = 2.36064 loss)
-I0511 08:21:55.471957  5307 sgd_solver.cpp:172] Iteration 100400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:22:56.358227  5307 solver.cpp:352] Iteration 100500 (1.64243 iter/s, 60.8853s/100 iter), 194.3/232ep, loss = 2.98626
-I0511 08:22:56.358577  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.43856 (* 1 = 2.43856 loss)
-I0511 08:22:56.358593  5307 sgd_solver.cpp:172] Iteration 100500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:23:57.579596  5307 solver.cpp:352] Iteration 100600 (1.63345 iter/s, 61.2203s/100 iter), 194.5/232ep, loss = 3.05359
-I0511 08:23:57.582028  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.41592 (* 1 = 2.41592 loss)
-I0511 08:23:57.582038  5307 sgd_solver.cpp:172] Iteration 100600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:24:58.344626  5307 solver.cpp:352] Iteration 100700 (1.64571 iter/s, 60.7639s/100 iter), 194.7/232ep, loss = 2.91428
-I0511 08:24:58.344753  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1572 (* 1 = 3.1572 loss)
-I0511 08:24:58.344775  5307 sgd_solver.cpp:172] Iteration 100700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:25:59.356418  5307 solver.cpp:352] Iteration 100800 (1.63906 iter/s, 61.0107s/100 iter), 194.9/232ep, loss = 3.0662
-I0511 08:25:59.356564  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50593 (* 1 = 3.50593 loss)
-I0511 08:25:59.356577  5307 sgd_solver.cpp:172] Iteration 100800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:26:23.589988  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:27:00.902576  5307 solver.cpp:352] Iteration 100900 (1.62483 iter/s, 61.5451s/100 iter), 195.1/232ep, loss = 2.96019
-I0511 08:27:00.902674  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.54178 (* 1 = 2.54178 loss)
-I0511 08:27:00.902681  5307 sgd_solver.cpp:172] Iteration 100900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:28:02.828667  5307 solver.cpp:352] Iteration 101000 (1.61486 iter/s, 61.9249s/100 iter), 195.3/232ep, loss = 2.93848
-I0511 08:28:02.828826  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.41082 (* 1 = 2.41082 loss)
-I0511 08:28:02.828871  5307 sgd_solver.cpp:172] Iteration 101000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:29:04.057327  5307 solver.cpp:352] Iteration 101100 (1.63325 iter/s, 61.2275s/100 iter), 195.5/232ep, loss = 3.148
-I0511 08:29:04.057379  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.57206 (* 1 = 3.57206 loss)
-I0511 08:29:04.057386  5307 sgd_solver.cpp:172] Iteration 101100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:30:05.313616  5307 solver.cpp:352] Iteration 101200 (1.63252 iter/s, 61.2551s/100 iter), 195.7/232ep, loss = 3.03246
-I0511 08:30:05.313746  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.61708 (* 1 = 3.61708 loss)
-I0511 08:30:05.313758  5307 sgd_solver.cpp:172] Iteration 101200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:31:07.408694  5307 solver.cpp:352] Iteration 101300 (1.61046 iter/s, 62.0939s/100 iter), 195.9/232ep, loss = 3.11302
-I0511 08:31:07.408802  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83745 (* 1 = 2.83745 loss)
-I0511 08:31:07.408816  5307 sgd_solver.cpp:172] Iteration 101300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:31:42.815610  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:32:09.252004  5307 solver.cpp:352] Iteration 101400 (1.61702 iter/s, 61.8422s/100 iter), 196/232ep, loss = 2.79151
-I0511 08:32:09.252032  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.39979 (* 1 = 2.39979 loss)
-I0511 08:32:09.252040  5307 sgd_solver.cpp:172] Iteration 101400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:33:10.985529  5307 solver.cpp:352] Iteration 101500 (1.6199 iter/s, 61.7324s/100 iter), 196.2/232ep, loss = 2.91793
-I0511 08:33:10.985631  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04143 (* 1 = 3.04143 loss)
-I0511 08:33:10.985642  5307 sgd_solver.cpp:172] Iteration 101500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:34:12.504964  5307 solver.cpp:352] Iteration 101600 (1.62553 iter/s, 61.5183s/100 iter), 196.4/232ep, loss = 2.99502
-I0511 08:34:12.505041  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.19517 (* 1 = 2.19517 loss)
-I0511 08:34:12.505050  5307 sgd_solver.cpp:172] Iteration 101600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:35:13.790604  5307 solver.cpp:352] Iteration 101700 (1.63173 iter/s, 61.2845s/100 iter), 196.6/232ep, loss = 3.06827
-I0511 08:35:13.790659  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38886 (* 1 = 3.38886 loss)
-I0511 08:35:13.790666  5307 sgd_solver.cpp:172] Iteration 101700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:36:15.784857  5307 solver.cpp:352] Iteration 101800 (1.61308 iter/s, 61.9931s/100 iter), 196.8/232ep, loss = 3.18449
-I0511 08:36:15.784955  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28257 (* 1 = 3.28257 loss)
-I0511 08:36:15.784977  5307 sgd_solver.cpp:172] Iteration 101800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:37:01.141197  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:37:16.739065  5307 solver.cpp:352] Iteration 101900 (1.64061 iter/s, 60.9531s/100 iter), 197/232ep, loss = 3.02052
-I0511 08:37:16.739158  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.42314 (* 1 = 3.42314 loss)
-I0511 08:37:16.739177  5307 sgd_solver.cpp:172] Iteration 101900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:38:16.737043  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_102000.caffemodel
-I0511 08:38:16.749049  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_102000.solverstate
-I0511 08:38:16.753746  5307 solver.cpp:635] Iteration 102000, Testing net (#0)
-I0511 08:38:57.167840  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:38:57.375763  5307 solver.cpp:747] class AP 1: 0.662877
-I0511 08:38:57.376477  5307 solver.cpp:747] class AP 2: 0.729423
-I0511 08:38:57.385727  5307 solver.cpp:747] class AP 3: 0.558048
-I0511 08:38:57.391151  5307 solver.cpp:747] class AP 4: 0.501808
-I0511 08:38:57.416709  5307 solver.cpp:747] class AP 5: 0.339622
-I0511 08:38:57.417057  5307 solver.cpp:747] class AP 6: 0.734243
-I0511 08:38:57.425725  5307 solver.cpp:747] class AP 7: 0.703979
-I0511 08:38:57.426270  5307 solver.cpp:747] class AP 8: 0.820063
-I0511 08:38:57.444169  5307 solver.cpp:747] class AP 9: 0.430973
-I0511 08:38:57.444890  5307 solver.cpp:747] class AP 10: 0.627212
-I0511 08:38:57.445516  5307 solver.cpp:747] class AP 11: 0.598763
-I0511 08:38:57.446367  5307 solver.cpp:747] class AP 12: 0.727264
-I0511 08:38:57.446800  5307 solver.cpp:747] class AP 13: 0.795383
-I0511 08:38:57.447157  5307 solver.cpp:747] class AP 14: 0.742447
-I0511 08:38:57.496114  5307 solver.cpp:747] class AP 15: 0.724216
-I0511 08:38:57.502737  5307 solver.cpp:747] class AP 16: 0.360335
-I0511 08:38:57.505149  5307 solver.cpp:747] class AP 17: 0.59934
-I0511 08:38:57.505834  5307 solver.cpp:747] class AP 18: 0.609809
-I0511 08:38:57.506490  5307 solver.cpp:747] class AP 19: 0.750395
-I0511 08:38:57.507906  5307 solver.cpp:747] class AP 20: 0.613732
-I0511 08:38:57.507915  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631497
-I0511 08:38:57.508059  5307 solver.cpp:283] Tests completed in 100.767s
-I0511 08:38:58.034000  5307 solver.cpp:352] Iteration 102000 (0.992386 iter/s, 100.767s/100 iter), 197.2/232ep, loss = 2.96189
-I0511 08:38:58.034025  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.47859 (* 1 = 3.47859 loss)
-I0511 08:38:58.034032  5307 sgd_solver.cpp:172] Iteration 102000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:39:59.308593  5307 solver.cpp:352] Iteration 102100 (1.63203 iter/s, 61.2734s/100 iter), 197.4/232ep, loss = 3.01728
-I0511 08:39:59.308722  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22398 (* 1 = 3.22398 loss)
-I0511 08:39:59.308735  5307 sgd_solver.cpp:172] Iteration 102100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:40:59.338691  5307 solver.cpp:352] Iteration 102200 (1.66586 iter/s, 60.0291s/100 iter), 197.6/232ep, loss = 2.97617
-I0511 08:40:59.338783  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.49093 (* 1 = 2.49093 loss)
-I0511 08:40:59.338793  5307 sgd_solver.cpp:172] Iteration 102200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:42:01.744545  5307 solver.cpp:352] Iteration 102300 (1.60244 iter/s, 62.4047s/100 iter), 197.8/232ep, loss = 3.03357
-I0511 08:42:01.744637  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25867 (* 1 = 3.25867 loss)
-I0511 08:42:01.744647  5307 sgd_solver.cpp:172] Iteration 102300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:42:57.391222  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:43:02.803563  5307 solver.cpp:352] Iteration 102400 (1.63779 iter/s, 61.058s/100 iter), 198/232ep, loss = 3.22251
-I0511 08:43:02.803596  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6136 (* 1 = 2.6136 loss)
-I0511 08:43:02.803603  5307 sgd_solver.cpp:172] Iteration 102400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:44:04.976128  5307 solver.cpp:352] Iteration 102500 (1.60845 iter/s, 62.1715s/100 iter), 198.2/232ep, loss = 3.14362
-I0511 08:44:04.976188  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.12992 (* 1 = 3.12992 loss)
-I0511 08:44:04.976194  5307 sgd_solver.cpp:172] Iteration 102500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:45:06.639672  5307 solver.cpp:352] Iteration 102600 (1.62173 iter/s, 61.6625s/100 iter), 198.4/232ep, loss = 3.05518
-I0511 08:45:06.640053  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95388 (* 1 = 2.95388 loss)
-I0511 08:45:06.640072  5307 sgd_solver.cpp:172] Iteration 102600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:46:07.664664  5307 solver.cpp:352] Iteration 102700 (1.6387 iter/s, 61.0239s/100 iter), 198.6/232ep, loss = 2.99007
-I0511 08:46:07.667974  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39835 (* 1 = 3.39835 loss)
-I0511 08:46:07.668041  5307 sgd_solver.cpp:172] Iteration 102700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:47:09.222339  5307 solver.cpp:352] Iteration 102800 (1.62452 iter/s, 61.5566s/100 iter), 198.8/232ep, loss = 2.92772
-I0511 08:47:09.222436  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.22916 (* 1 = 2.22916 loss)
-I0511 08:47:09.222455  5307 sgd_solver.cpp:172] Iteration 102800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:48:10.972451  5307 solver.cpp:352] Iteration 102900 (1.61946 iter/s, 61.749s/100 iter), 198.9/232ep, loss = 2.97089
-I0511 08:48:10.972628  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.5179 (* 1 = 3.5179 loss)
-I0511 08:48:10.972647  5307 sgd_solver.cpp:172] Iteration 102900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:48:16.512580  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:49:12.852767  5307 solver.cpp:352] Iteration 103000 (1.61605 iter/s, 61.8792s/100 iter), 199.1/232ep, loss = 2.86671
-I0511 08:49:12.853016  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73384 (* 1 = 3.73384 loss)
-I0511 08:49:12.853035  5307 sgd_solver.cpp:172] Iteration 103000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:50:14.537976  5307 solver.cpp:352] Iteration 103100 (1.62116 iter/s, 61.6841s/100 iter), 199.3/232ep, loss = 3.3114
-I0511 08:50:14.538293  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.01035 (* 1 = 3.01035 loss)
-I0511 08:50:14.538347  5307 sgd_solver.cpp:172] Iteration 103100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:51:16.029994  5307 solver.cpp:352] Iteration 103200 (1.62626 iter/s, 61.4909s/100 iter), 199.5/232ep, loss = 3.06903
-I0511 08:51:16.036649  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.0684 (* 1 = 4.0684 loss)
-I0511 08:51:16.036679  5307 sgd_solver.cpp:172] Iteration 103200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:52:17.581897  5307 solver.cpp:352] Iteration 103300 (1.62468 iter/s, 61.5508s/100 iter), 199.7/232ep, loss = 3.08515
-I0511 08:52:17.582022  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87733 (* 1 = 2.87733 loss)
-I0511 08:52:17.582093  5307 sgd_solver.cpp:172] Iteration 103300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:53:25.213412  5307 solver.cpp:352] Iteration 103400 (1.47863 iter/s, 67.6302s/100 iter), 199.9/232ep, loss = 2.89853
-I0511 08:53:25.213524  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.3616 (* 1 = 3.3616 loss)
-I0511 08:53:25.213547  5307 sgd_solver.cpp:172] Iteration 103400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:53:42.453626  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:54:30.902637  5307 solver.cpp:352] Iteration 103500 (1.52235 iter/s, 65.688s/100 iter), 200.1/232ep, loss = 2.97316
-I0511 08:54:30.902704  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.48358 (* 1 = 2.48358 loss)
-I0511 08:54:30.902714  5307 sgd_solver.cpp:172] Iteration 103500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:55:32.001219  5307 solver.cpp:352] Iteration 103600 (1.63673 iter/s, 61.0974s/100 iter), 200.3/232ep, loss = 3.12863
-I0511 08:55:32.001878  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65934 (* 1 = 2.65934 loss)
-I0511 08:55:32.001896  5307 sgd_solver.cpp:172] Iteration 103600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:56:32.925688  5307 solver.cpp:352] Iteration 103700 (1.64141 iter/s, 60.9234s/100 iter), 200.5/232ep, loss = 3.02484
-I0511 08:56:32.930019  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6127 (* 1 = 2.6127 loss)
-I0511 08:56:32.930043  5307 sgd_solver.cpp:172] Iteration 103700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:57:34.563419  5307 solver.cpp:352] Iteration 103800 (1.62241 iter/s, 61.6366s/100 iter), 200.7/232ep, loss = 3.00477
-I0511 08:57:34.564416  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.82427 (* 1 = 3.82427 loss)
-I0511 08:57:34.564426  5307 sgd_solver.cpp:172] Iteration 103800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:58:35.047950  5307 solver.cpp:352] Iteration 103900 (1.65335 iter/s, 60.4834s/100 iter), 200.9/232ep, loss = 2.86798
-I0511 08:58:35.048068  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92458 (* 1 = 2.92458 loss)
-I0511 08:58:35.048089  5307 sgd_solver.cpp:172] Iteration 103900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 08:59:01.674793  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 08:59:35.537987  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_104000.caffemodel
-I0511 08:59:35.552865  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_104000.solverstate
-I0511 08:59:35.557982  5307 solver.cpp:635] Iteration 104000, Testing net (#0)
-I0511 09:00:15.941030  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:00:16.171171  5307 solver.cpp:747] class AP 1: 0.658912
-I0511 09:00:16.171667  5307 solver.cpp:747] class AP 2: 0.733622
-I0511 09:00:16.178172  5307 solver.cpp:747] class AP 3: 0.560076
-I0511 09:00:16.181856  5307 solver.cpp:747] class AP 4: 0.507364
-I0511 09:00:16.200403  5307 solver.cpp:747] class AP 5: 0.342464
-I0511 09:00:16.200734  5307 solver.cpp:747] class AP 6: 0.737497
-I0511 09:00:16.209339  5307 solver.cpp:747] class AP 7: 0.704001
-I0511 09:00:16.209879  5307 solver.cpp:747] class AP 8: 0.816034
-I0511 09:00:16.228055  5307 solver.cpp:747] class AP 9: 0.434627
-I0511 09:00:16.228770  5307 solver.cpp:747] class AP 10: 0.626055
-I0511 09:00:16.229395  5307 solver.cpp:747] class AP 11: 0.601497
-I0511 09:00:16.230235  5307 solver.cpp:747] class AP 12: 0.720504
-I0511 09:00:16.230667  5307 solver.cpp:747] class AP 13: 0.798838
-I0511 09:00:16.231020  5307 solver.cpp:747] class AP 14: 0.741948
-I0511 09:00:16.281016  5307 solver.cpp:747] class AP 15: 0.727061
-I0511 09:00:16.287535  5307 solver.cpp:747] class AP 16: 0.36246
-I0511 09:00:16.290091  5307 solver.cpp:747] class AP 17: 0.598146
-I0511 09:00:16.290707  5307 solver.cpp:747] class AP 18: 0.609144
-I0511 09:00:16.291417  5307 solver.cpp:747] class AP 19: 0.747257
-I0511 09:00:16.292925  5307 solver.cpp:747] class AP 20: 0.609945
-I0511 09:00:16.292943  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631873
-I0511 09:00:16.293195  5307 solver.cpp:283] Tests completed in 101.243s
-I0511 09:00:16.893482  5307 solver.cpp:352] Iteration 104000 (0.987718 iter/s, 101.243s/100 iter), 201.1/232ep, loss = 2.84492
-I0511 09:00:16.893506  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.13108 (* 1 = 2.13108 loss)
-I0511 09:00:16.893512  5307 sgd_solver.cpp:172] Iteration 104000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:01:18.301661  5307 solver.cpp:352] Iteration 104100 (1.62848 iter/s, 61.4071s/100 iter), 201.3/232ep, loss = 3.17149
-I0511 09:01:18.301719  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.66412 (* 1 = 2.66412 loss)
-I0511 09:01:18.301728  5307 sgd_solver.cpp:172] Iteration 104100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:02:19.057096  5307 solver.cpp:352] Iteration 104200 (1.64597 iter/s, 60.7543s/100 iter), 201.5/232ep, loss = 2.97307
-I0511 09:02:19.057158  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.79797 (* 1 = 2.79797 loss)
-I0511 09:02:19.057164  5307 sgd_solver.cpp:172] Iteration 104200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:03:19.339989  5307 solver.cpp:352] Iteration 104300 (1.65888 iter/s, 60.2818s/100 iter), 201.7/232ep, loss = 2.97009
-I0511 09:03:19.340106  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71737 (* 1 = 2.71737 loss)
-I0511 09:03:19.340113  5307 sgd_solver.cpp:172] Iteration 104300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:04:19.700664  5307 solver.cpp:352] Iteration 104400 (1.65674 iter/s, 60.3596s/100 iter), 201.8/232ep, loss = 3.18266
-I0511 09:04:19.700740  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.75174 (* 1 = 2.75174 loss)
-I0511 09:04:19.700747  5307 sgd_solver.cpp:172] Iteration 104400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:04:55.972400  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:05:19.960947  5307 solver.cpp:352] Iteration 104500 (1.6595 iter/s, 60.2592s/100 iter), 202/232ep, loss = 3.00151
-I0511 09:05:19.960974  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.33216 (* 1 = 4.33216 loss)
-I0511 09:05:19.960983  5307 sgd_solver.cpp:172] Iteration 104500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:06:21.572664  5307 solver.cpp:352] Iteration 104600 (1.6231 iter/s, 61.6106s/100 iter), 202.2/232ep, loss = 2.96726
-I0511 09:06:21.574237  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63491 (* 1 = 2.63491 loss)
-I0511 09:06:21.574266  5307 sgd_solver.cpp:172] Iteration 104600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:07:22.228152  5307 solver.cpp:352] Iteration 104700 (1.64868 iter/s, 60.6544s/100 iter), 202.4/232ep, loss = 2.94288
-I0511 09:07:22.228384  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.29353 (* 1 = 2.29353 loss)
-I0511 09:07:22.228392  5307 sgd_solver.cpp:172] Iteration 104700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:08:22.898113  5307 solver.cpp:352] Iteration 104800 (1.64829 iter/s, 60.6688s/100 iter), 202.6/232ep, loss = 2.97853
-I0511 09:08:22.899556  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.0337 (* 1 = 2.0337 loss)
-I0511 09:08:22.899595  5307 sgd_solver.cpp:172] Iteration 104800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:09:23.892618  5307 solver.cpp:352] Iteration 104900 (1.63952 iter/s, 60.9934s/100 iter), 202.8/232ep, loss = 2.9735
-I0511 09:09:23.892762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.52497 (* 1 = 3.52497 loss)
-I0511 09:09:23.892772  5307 sgd_solver.cpp:172] Iteration 104900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:10:10.349397  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:10:24.394165  5307 solver.cpp:352] Iteration 105000 (1.65288 iter/s, 60.5004s/100 iter), 203/232ep, loss = 3.00669
-I0511 09:10:24.394269  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.04437 (* 1 = 3.04437 loss)
-I0511 09:10:24.394306  5307 sgd_solver.cpp:172] Iteration 105000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:11:26.353379  5307 solver.cpp:352] Iteration 105100 (1.61399 iter/s, 61.9581s/100 iter), 203.2/232ep, loss = 2.88185
-I0511 09:11:26.353467  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6082 (* 1 = 2.6082 loss)
-I0511 09:11:26.353478  5307 sgd_solver.cpp:172] Iteration 105100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:12:27.174247  5307 solver.cpp:352] Iteration 105200 (1.6442 iter/s, 60.8197s/100 iter), 203.4/232ep, loss = 2.87346
-I0511 09:12:27.174407  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.02363 (* 1 = 4.02363 loss)
-I0511 09:12:27.174417  5307 sgd_solver.cpp:172] Iteration 105200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:13:28.831068  5307 solver.cpp:352] Iteration 105300 (1.62191 iter/s, 61.6557s/100 iter), 203.6/232ep, loss = 3.00454
-I0511 09:13:28.831135  5307 solver.cpp:376]     Train net output #0: mbox_loss = 4.38076 (* 1 = 4.38076 loss)
-I0511 09:13:28.831141  5307 sgd_solver.cpp:172] Iteration 105300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:14:30.143863  5307 solver.cpp:352] Iteration 105400 (1.63101 iter/s, 61.3116s/100 iter), 203.8/232ep, loss = 2.85613
-I0511 09:14:30.144198  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.83625 (* 1 = 2.83625 loss)
-I0511 09:14:30.144227  5307 sgd_solver.cpp:172] Iteration 105400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:15:28.410624  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:15:31.289784  5307 solver.cpp:352] Iteration 105500 (1.63546 iter/s, 61.1448s/100 iter), 204/232ep, loss = 3.07666
-I0511 09:15:31.289810  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81599 (* 1 = 2.81599 loss)
-I0511 09:15:31.289819  5307 sgd_solver.cpp:172] Iteration 105500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:16:31.947705  5307 solver.cpp:352] Iteration 105600 (1.64862 iter/s, 60.6568s/100 iter), 204.2/232ep, loss = 2.84988
-I0511 09:16:31.947778  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81488 (* 1 = 2.81488 loss)
-I0511 09:16:31.947788  5307 sgd_solver.cpp:172] Iteration 105600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:17:32.886667  5307 solver.cpp:352] Iteration 105700 (1.64102 iter/s, 60.9379s/100 iter), 204.4/232ep, loss = 3.18043
-I0511 09:17:32.886966  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.54316 (* 1 = 2.54316 loss)
-I0511 09:17:32.886976  5307 sgd_solver.cpp:172] Iteration 105700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:18:34.355509  5307 solver.cpp:352] Iteration 105800 (1.62687 iter/s, 61.4677s/100 iter), 204.6/232ep, loss = 3.05276
-I0511 09:18:34.355572  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07529 (* 1 = 3.07529 loss)
-I0511 09:18:34.355579  5307 sgd_solver.cpp:172] Iteration 105800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:19:35.041429  5307 solver.cpp:352] Iteration 105900 (1.64786 iter/s, 60.6848s/100 iter), 204.7/232ep, loss = 2.9841
-I0511 09:19:35.041501  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95786 (* 1 = 2.95786 loss)
-I0511 09:19:35.041512  5307 sgd_solver.cpp:172] Iteration 105900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:20:35.229087  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_106000.caffemodel
-I0511 09:20:35.249084  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_106000.solverstate
-I0511 09:20:35.255237  5307 solver.cpp:635] Iteration 106000, Testing net (#0)
-I0511 09:21:15.721871  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:21:15.931792  5307 solver.cpp:747] class AP 1: 0.660411
-I0511 09:21:15.932317  5307 solver.cpp:747] class AP 2: 0.730086
-I0511 09:21:15.938953  5307 solver.cpp:747] class AP 3: 0.557565
-I0511 09:21:15.942739  5307 solver.cpp:747] class AP 4: 0.505904
-I0511 09:21:15.962241  5307 solver.cpp:747] class AP 5: 0.345831
-I0511 09:21:15.962599  5307 solver.cpp:747] class AP 6: 0.736774
-I0511 09:21:15.971547  5307 solver.cpp:747] class AP 7: 0.705488
-I0511 09:21:15.972134  5307 solver.cpp:747] class AP 8: 0.819378
-I0511 09:21:15.990371  5307 solver.cpp:747] class AP 9: 0.429442
-I0511 09:21:15.991097  5307 solver.cpp:747] class AP 10: 0.633304
-I0511 09:21:15.991744  5307 solver.cpp:747] class AP 11: 0.595445
-I0511 09:21:15.992588  5307 solver.cpp:747] class AP 12: 0.721519
-I0511 09:21:15.993032  5307 solver.cpp:747] class AP 13: 0.796779
-I0511 09:21:15.993393  5307 solver.cpp:747] class AP 14: 0.748903
-I0511 09:21:16.041465  5307 solver.cpp:747] class AP 15: 0.725762
-I0511 09:21:16.047837  5307 solver.cpp:747] class AP 16: 0.364806
-I0511 09:21:16.050380  5307 solver.cpp:747] class AP 17: 0.598963
-I0511 09:21:16.050945  5307 solver.cpp:747] class AP 18: 0.604041
-I0511 09:21:16.051612  5307 solver.cpp:747] class AP 19: 0.749612
-I0511 09:21:16.053093  5307 solver.cpp:747] class AP 20: 0.610039
-I0511 09:21:16.053099  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.632003
-I0511 09:21:16.053356  5307 solver.cpp:283] Tests completed in 101.01s
-I0511 09:21:16.605718  5307 solver.cpp:352] Iteration 106000 (0.99 iter/s, 101.01s/100 iter), 204.9/232ep, loss = 2.97081
-I0511 09:21:16.605746  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91581 (* 1 = 2.91581 loss)
-I0511 09:21:16.605754  5307 sgd_solver.cpp:172] Iteration 106000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:21:23.239075  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:22:16.511878  5307 solver.cpp:352] Iteration 106100 (1.66931 iter/s, 59.9051s/100 iter), 205.1/232ep, loss = 2.79096
-I0511 09:22:16.511988  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.9052 (* 1 = 2.9052 loss)
-I0511 09:22:16.512006  5307 sgd_solver.cpp:172] Iteration 106100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:23:17.654028  5307 solver.cpp:352] Iteration 106200 (1.63556 iter/s, 61.141s/100 iter), 205.3/232ep, loss = 2.99165
-I0511 09:23:17.654165  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.20889 (* 1 = 3.20889 loss)
-I0511 09:23:17.654181  5307 sgd_solver.cpp:172] Iteration 106200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:24:18.296691  5307 solver.cpp:352] Iteration 106300 (1.64903 iter/s, 60.6416s/100 iter), 205.5/232ep, loss = 3.0056
-I0511 09:24:18.296780  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.80644 (* 1 = 3.80644 loss)
-I0511 09:24:18.296798  5307 sgd_solver.cpp:172] Iteration 106300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:25:18.281538  5307 solver.cpp:352] Iteration 106400 (1.66712 iter/s, 59.9838s/100 iter), 205.7/232ep, loss = 2.94822
-I0511 09:25:18.281648  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.13342 (* 1 = 2.13342 loss)
-I0511 09:25:18.281662  5307 sgd_solver.cpp:172] Iteration 106400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:26:18.623312  5307 solver.cpp:352] Iteration 106500 (1.65726 iter/s, 60.3407s/100 iter), 205.9/232ep, loss = 2.91705
-I0511 09:26:18.623702  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31356 (* 1 = 3.31356 loss)
-I0511 09:26:18.623710  5307 sgd_solver.cpp:172] Iteration 106500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:26:36.457285  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:27:19.887410  5307 solver.cpp:352] Iteration 106600 (1.63231 iter/s, 61.263s/100 iter), 206.1/232ep, loss = 3.00814
-I0511 09:27:19.889544  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.25941 (* 1 = 3.25941 loss)
-I0511 09:27:19.889564  5307 sgd_solver.cpp:172] Iteration 106600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:28:21.581161  5307 solver.cpp:352] Iteration 106700 (1.62094 iter/s, 61.6927s/100 iter), 206.3/232ep, loss = 3.08816
-I0511 09:28:21.581254  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.27414 (* 1 = 3.27414 loss)
-I0511 09:28:21.581272  5307 sgd_solver.cpp:172] Iteration 106700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:29:24.353520  5307 solver.cpp:352] Iteration 106800 (1.59309 iter/s, 62.7713s/100 iter), 206.5/232ep, loss = 2.97322
-I0511 09:29:24.353602  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.45352 (* 1 = 3.45352 loss)
-I0511 09:29:24.353622  5307 sgd_solver.cpp:172] Iteration 106800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:30:25.825932  5307 solver.cpp:352] Iteration 106900 (1.62678 iter/s, 61.4713s/100 iter), 206.7/232ep, loss = 2.96496
-I0511 09:30:25.826134  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6223 (* 1 = 2.6223 loss)
-I0511 09:30:25.826148  5307 sgd_solver.cpp:172] Iteration 106900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:31:27.199806  5307 solver.cpp:352] Iteration 107000 (1.62939 iter/s, 61.3728s/100 iter), 206.9/232ep, loss = 2.87001
-I0511 09:31:27.199870  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.64079 (* 1 = 3.64079 loss)
-I0511 09:31:27.199879  5307 sgd_solver.cpp:172] Iteration 107000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:31:55.909417  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:32:28.962905  5307 solver.cpp:352] Iteration 107100 (1.61912 iter/s, 61.762s/100 iter), 207.1/232ep, loss = 3.00419
-I0511 09:32:28.963433  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91865 (* 1 = 2.91865 loss)
-I0511 09:32:28.963446  5307 sgd_solver.cpp:172] Iteration 107100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:33:30.509364  5307 solver.cpp:352] Iteration 107200 (1.62482 iter/s, 61.5453s/100 iter), 207.3/232ep, loss = 3.30159
-I0511 09:33:30.511792  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6854 (* 1 = 2.6854 loss)
-I0511 09:33:30.511801  5307 sgd_solver.cpp:172] Iteration 107200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:34:31.048547  5307 solver.cpp:352] Iteration 107300 (1.65185 iter/s, 60.5381s/100 iter), 207.5/232ep, loss = 3.02911
-I0511 09:34:31.048740  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.60675 (* 1 = 3.60675 loss)
-I0511 09:34:31.048806  5307 sgd_solver.cpp:172] Iteration 107300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:35:32.531407  5307 solver.cpp:352] Iteration 107400 (1.6265 iter/s, 61.4817s/100 iter), 207.6/232ep, loss = 2.8751
-I0511 09:35:32.532121  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31164 (* 1 = 3.31164 loss)
-I0511 09:35:32.532130  5307 sgd_solver.cpp:172] Iteration 107400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:36:33.544476  5307 solver.cpp:352] Iteration 107500 (1.63902 iter/s, 61.0119s/100 iter), 207.8/232ep, loss = 3.05105
-I0511 09:36:33.544617  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65433 (* 1 = 2.65433 loss)
-I0511 09:36:33.544636  5307 sgd_solver.cpp:172] Iteration 107500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:37:11.896042  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:37:34.432308  5307 solver.cpp:352] Iteration 107600 (1.64239 iter/s, 60.8867s/100 iter), 208/232ep, loss = 2.922
-I0511 09:37:34.432337  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.57429 (* 1 = 2.57429 loss)
-I0511 09:37:34.432345  5307 sgd_solver.cpp:172] Iteration 107600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:38:36.154429  5307 solver.cpp:352] Iteration 107700 (1.62019 iter/s, 61.721s/100 iter), 208.2/232ep, loss = 2.95121
-I0511 09:38:36.156332  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.72509 (* 1 = 2.72509 loss)
-I0511 09:38:36.156342  5307 sgd_solver.cpp:172] Iteration 107700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:39:37.661792  5307 solver.cpp:352] Iteration 107800 (1.62585 iter/s, 61.5062s/100 iter), 208.4/232ep, loss = 2.9885
-I0511 09:39:37.662276  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4115 (* 1 = 3.4115 loss)
-I0511 09:39:37.662286  5307 sgd_solver.cpp:172] Iteration 107800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:40:38.793115  5307 solver.cpp:352] Iteration 107900 (1.63585 iter/s, 61.1302s/100 iter), 208.6/232ep, loss = 3.15024
-I0511 09:40:38.794373  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.24121 (* 1 = 3.24121 loss)
-I0511 09:40:38.794384  5307 sgd_solver.cpp:172] Iteration 107900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:41:39.421762  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_108000.caffemodel
-I0511 09:41:39.435892  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_108000.solverstate
-I0511 09:41:39.441318  5307 solver.cpp:635] Iteration 108000, Testing net (#0)
-I0511 09:42:19.909317  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:42:20.142171  5307 solver.cpp:747] class AP 1: 0.656404
-I0511 09:42:20.142681  5307 solver.cpp:747] class AP 2: 0.728707
-I0511 09:42:20.149108  5307 solver.cpp:747] class AP 3: 0.554245
-I0511 09:42:20.152906  5307 solver.cpp:747] class AP 4: 0.51111
-I0511 09:42:20.172255  5307 solver.cpp:747] class AP 5: 0.346773
-I0511 09:42:20.172605  5307 solver.cpp:747] class AP 6: 0.744805
-I0511 09:42:20.181558  5307 solver.cpp:747] class AP 7: 0.703511
-I0511 09:42:20.182119  5307 solver.cpp:747] class AP 8: 0.818978
-I0511 09:42:20.200107  5307 solver.cpp:747] class AP 9: 0.432783
-I0511 09:42:20.200898  5307 solver.cpp:747] class AP 10: 0.628323
-I0511 09:42:20.201720  5307 solver.cpp:747] class AP 11: 0.588869
-I0511 09:42:20.202574  5307 solver.cpp:747] class AP 12: 0.720254
-I0511 09:42:20.203035  5307 solver.cpp:747] class AP 13: 0.798658
-I0511 09:42:20.203418  5307 solver.cpp:747] class AP 14: 0.747712
-I0511 09:42:20.259835  5307 solver.cpp:747] class AP 15: 0.726384
-I0511 09:42:20.266482  5307 solver.cpp:747] class AP 16: 0.356199
-I0511 09:42:20.269019  5307 solver.cpp:747] class AP 17: 0.598237
-I0511 09:42:20.269618  5307 solver.cpp:747] class AP 18: 0.603476
-I0511 09:42:20.270298  5307 solver.cpp:747] class AP 19: 0.759944
-I0511 09:42:20.271759  5307 solver.cpp:747] class AP 20: 0.615325
-I0511 09:42:20.271777  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.632035
-I0511 09:42:20.272122  5307 solver.cpp:283] Tests completed in 101.477s
-I0511 09:42:20.826761  5307 solver.cpp:352] Iteration 108000 (0.985443 iter/s, 101.477s/100 iter), 208.8/232ep, loss = 2.9927
-I0511 09:42:20.827028  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90072 (* 1 = 2.90072 loss)
-I0511 09:42:20.827039  5307 sgd_solver.cpp:172] Iteration 108000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:43:10.224517  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:43:22.015218  5307 solver.cpp:352] Iteration 108100 (1.63432 iter/s, 61.1873s/100 iter), 209/232ep, loss = 3.04481
-I0511 09:43:22.015246  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63587 (* 1 = 2.63587 loss)
-I0511 09:43:22.015254  5307 sgd_solver.cpp:172] Iteration 108100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:44:23.599179  5307 solver.cpp:352] Iteration 108200 (1.62383 iter/s, 61.5828s/100 iter), 209.2/232ep, loss = 2.92217
-I0511 09:44:23.600044  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.41159 (* 1 = 2.41159 loss)
-I0511 09:44:23.600061  5307 sgd_solver.cpp:172] Iteration 108200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:45:25.352929  5307 solver.cpp:352] Iteration 108300 (1.61936 iter/s, 61.7527s/100 iter), 209.4/232ep, loss = 2.88494
-I0511 09:45:25.352996  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.46943 (* 1 = 3.46943 loss)
-I0511 09:45:25.353006  5307 sgd_solver.cpp:172] Iteration 108300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:46:27.529007  5307 solver.cpp:352] Iteration 108400 (1.60836 iter/s, 62.1749s/100 iter), 209.6/232ep, loss = 3.15808
-I0511 09:46:27.531289  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.35382 (* 1 = 2.35382 loss)
-I0511 09:46:27.531325  5307 sgd_solver.cpp:172] Iteration 108400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:47:28.979347  5307 solver.cpp:352] Iteration 108500 (1.62736 iter/s, 61.4493s/100 iter), 209.8/232ep, loss = 3.06685
-I0511 09:47:28.979426  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.57391 (* 1 = 2.57391 loss)
-I0511 09:47:28.979434  5307 sgd_solver.cpp:172] Iteration 108500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:48:29.157548  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:48:30.958716  5307 solver.cpp:352] Iteration 108600 (1.61347 iter/s, 61.9783s/100 iter), 210/232ep, loss = 3.16514
-I0511 09:48:30.958742  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.32524 (* 1 = 3.32524 loss)
-I0511 09:48:30.958748  5307 sgd_solver.cpp:172] Iteration 108600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:49:31.946439  5307 solver.cpp:352] Iteration 108700 (1.6397 iter/s, 60.9866s/100 iter), 210.2/232ep, loss = 3.11442
-I0511 09:49:31.946703  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.58374 (* 1 = 3.58374 loss)
-I0511 09:49:31.946714  5307 sgd_solver.cpp:172] Iteration 108700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:50:33.278905  5307 solver.cpp:352] Iteration 108800 (1.63049 iter/s, 61.3314s/100 iter), 210.4/232ep, loss = 3.11977
-I0511 09:50:33.279023  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.24816 (* 1 = 3.24816 loss)
-I0511 09:50:33.279034  5307 sgd_solver.cpp:172] Iteration 108800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:51:35.136703  5307 solver.cpp:352] Iteration 108900 (1.61664 iter/s, 61.8567s/100 iter), 210.5/232ep, loss = 2.79067
-I0511 09:51:35.138720  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.31322 (* 1 = 3.31322 loss)
-I0511 09:51:35.138751  5307 sgd_solver.cpp:172] Iteration 108900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:52:36.540758  5307 solver.cpp:352] Iteration 109000 (1.62859 iter/s, 61.403s/100 iter), 210.7/232ep, loss = 3.03206
-I0511 09:52:36.543386  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.53034 (* 1 = 2.53034 loss)
-I0511 09:52:36.543408  5307 sgd_solver.cpp:172] Iteration 109000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:53:36.958336  5307 solver.cpp:352] Iteration 109100 (1.65518 iter/s, 60.4165s/100 iter), 210.9/232ep, loss = 2.81642
-I0511 09:53:36.958397  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.55472 (* 1 = 3.55472 loss)
-I0511 09:53:36.958406  5307 sgd_solver.cpp:172] Iteration 109100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:53:46.445642  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:54:39.186568  5307 solver.cpp:352] Iteration 109200 (1.60702 iter/s, 62.2271s/100 iter), 211.1/232ep, loss = 2.96823
-I0511 09:54:39.186671  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5983 (* 1 = 2.5983 loss)
-I0511 09:54:39.186682  5307 sgd_solver.cpp:172] Iteration 109200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:55:41.894292  5307 solver.cpp:352] Iteration 109300 (1.59473 iter/s, 62.7066s/100 iter), 211.3/232ep, loss = 3.0341
-I0511 09:55:41.894351  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.34157 (* 1 = 3.34157 loss)
-I0511 09:55:41.894359  5307 sgd_solver.cpp:172] Iteration 109300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:56:43.293130  5307 solver.cpp:352] Iteration 109400 (1.62873 iter/s, 61.3977s/100 iter), 211.5/232ep, loss = 2.94719
-I0511 09:56:43.293259  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.5932 (* 1 = 2.5932 loss)
-I0511 09:56:43.293289  5307 sgd_solver.cpp:172] Iteration 109400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:57:44.943948  5307 solver.cpp:352] Iteration 109500 (1.62207 iter/s, 61.6497s/100 iter), 211.7/232ep, loss = 3.04132
-I0511 09:57:44.944041  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.2802 (* 1 = 2.2802 loss)
-I0511 09:57:44.944051  5307 sgd_solver.cpp:172] Iteration 109500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:58:46.472889  5307 solver.cpp:352] Iteration 109600 (1.62528 iter/s, 61.5278s/100 iter), 211.9/232ep, loss = 3.05654
-I0511 09:58:46.476739  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87819 (* 1 = 2.87819 loss)
-I0511 09:58:46.476758  5307 sgd_solver.cpp:172] Iteration 109600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 09:59:07.274627  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 09:59:48.034642  5307 solver.cpp:352] Iteration 109700 (1.62442 iter/s, 61.5606s/100 iter), 212.1/232ep, loss = 3.04314
-I0511 09:59:48.034703  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15212 (* 1 = 3.15212 loss)
-I0511 09:59:48.034711  5307 sgd_solver.cpp:172] Iteration 109700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:00:57.823367  5307 solver.cpp:352] Iteration 109800 (1.43292 iter/s, 69.7874s/100 iter), 212.3/232ep, loss = 3.09853
-I0511 10:00:57.823479  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.29951 (* 1 = 3.29951 loss)
-I0511 10:00:57.823501  5307 sgd_solver.cpp:172] Iteration 109800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:02:03.153767  5307 solver.cpp:352] Iteration 109900 (1.53071 iter/s, 65.3292s/100 iter), 212.5/232ep, loss = 3.13834
-I0511 10:02:03.153846  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.69669 (* 1 = 3.69669 loss)
-I0511 10:02:03.153853  5307 sgd_solver.cpp:172] Iteration 109900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:03:03.416615  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_110000.caffemodel
-I0511 10:03:03.433248  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_110000.solverstate
-I0511 10:03:03.438459  5307 solver.cpp:635] Iteration 110000, Testing net (#0)
-I0511 10:03:25.448328  5354 blocking_queue.cpp:40] Waiting for data
-I0511 10:03:43.845228  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:03:44.052278  5307 solver.cpp:747] class AP 1: 0.65293
-I0511 10:03:44.052799  5307 solver.cpp:747] class AP 2: 0.733623
-I0511 10:03:44.059448  5307 solver.cpp:747] class AP 3: 0.557503
-I0511 10:03:44.063221  5307 solver.cpp:747] class AP 4: 0.512509
-I0511 10:03:44.082121  5307 solver.cpp:747] class AP 5: 0.345366
-I0511 10:03:44.082494  5307 solver.cpp:747] class AP 6: 0.739828
-I0511 10:03:44.091215  5307 solver.cpp:747] class AP 7: 0.703411
-I0511 10:03:44.091783  5307 solver.cpp:747] class AP 8: 0.816873
-I0511 10:03:44.110553  5307 solver.cpp:747] class AP 9: 0.43649
-I0511 10:03:44.111286  5307 solver.cpp:747] class AP 10: 0.631253
-I0511 10:03:44.112057  5307 solver.cpp:747] class AP 11: 0.589722
-I0511 10:03:44.113168  5307 solver.cpp:747] class AP 12: 0.720832
-I0511 10:03:44.113615  5307 solver.cpp:747] class AP 13: 0.79909
-I0511 10:03:44.113967  5307 solver.cpp:747] class AP 14: 0.74729
-I0511 10:03:44.163322  5307 solver.cpp:747] class AP 15: 0.725755
-I0511 10:03:44.169760  5307 solver.cpp:747] class AP 16: 0.358302
-I0511 10:03:44.172224  5307 solver.cpp:747] class AP 17: 0.598111
-I0511 10:03:44.172845  5307 solver.cpp:747] class AP 18: 0.601112
-I0511 10:03:44.173518  5307 solver.cpp:747] class AP 19: 0.752073
-I0511 10:03:44.175300  5307 solver.cpp:747] class AP 20: 0.609423
-I0511 10:03:44.175433  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631575
-I0511 10:03:44.175595  5307 solver.cpp:283] Tests completed in 101.02s
-I0511 10:03:44.715556  5307 solver.cpp:352] Iteration 110000 (0.989903 iter/s, 101.02s/100 iter), 212.7/232ep, loss = 2.89916
-I0511 10:03:44.715628  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63487 (* 1 = 2.63487 loss)
-I0511 10:03:44.715646  5307 sgd_solver.cpp:172] Iteration 110000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:04:45.138458  5307 solver.cpp:352] Iteration 110100 (1.65503 iter/s, 60.4218s/100 iter), 212.9/232ep, loss = 3.00876
-I0511 10:04:45.138525  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1163 (* 1 = 3.1163 loss)
-I0511 10:04:45.138535  5307 sgd_solver.cpp:172] Iteration 110100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:05:14.963007  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:05:46.285318  5307 solver.cpp:352] Iteration 110200 (1.63544 iter/s, 61.1457s/100 iter), 213.1/232ep, loss = 3.04647
-I0511 10:05:46.285425  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90314 (* 1 = 2.90314 loss)
-I0511 10:05:46.285439  5307 sgd_solver.cpp:172] Iteration 110200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:06:46.456821  5307 solver.cpp:352] Iteration 110300 (1.66195 iter/s, 60.1704s/100 iter), 213.3/232ep, loss = 3.11642
-I0511 10:06:46.456908  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.70813 (* 1 = 2.70813 loss)
-I0511 10:06:46.456918  5307 sgd_solver.cpp:172] Iteration 110300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:07:47.811429  5307 solver.cpp:352] Iteration 110400 (1.6299 iter/s, 61.3535s/100 iter), 213.4/232ep, loss = 3.08903
-I0511 10:07:47.811530  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.70512 (* 1 = 2.70512 loss)
-I0511 10:07:47.811553  5307 sgd_solver.cpp:172] Iteration 110400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:08:48.071257  5307 solver.cpp:352] Iteration 110500 (1.65951 iter/s, 60.2587s/100 iter), 213.6/232ep, loss = 2.86229
-I0511 10:08:48.071324  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.34643 (* 1 = 3.34643 loss)
-I0511 10:08:48.071367  5307 sgd_solver.cpp:172] Iteration 110500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:09:49.470010  5307 solver.cpp:352] Iteration 110600 (1.62872 iter/s, 61.3977s/100 iter), 213.8/232ep, loss = 3.12379
-I0511 10:09:49.470111  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.75619 (* 1 = 2.75619 loss)
-I0511 10:09:49.470121  5307 sgd_solver.cpp:172] Iteration 110600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:10:30.507227  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:10:50.539381  5307 solver.cpp:352] Iteration 110700 (1.63751 iter/s, 61.0683s/100 iter), 214/232ep, loss = 2.99424
-I0511 10:10:50.539412  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89221 (* 1 = 2.89221 loss)
-I0511 10:10:50.539420  5307 sgd_solver.cpp:172] Iteration 110700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:11:52.147364  5307 solver.cpp:352] Iteration 110800 (1.62319 iter/s, 61.6069s/100 iter), 214.2/232ep, loss = 3.14237
-I0511 10:11:52.147531  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.78656 (* 1 = 2.78656 loss)
-I0511 10:11:52.147547  5307 sgd_solver.cpp:172] Iteration 110800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:12:52.570505  5307 solver.cpp:352] Iteration 110900 (1.65502 iter/s, 60.4221s/100 iter), 214.4/232ep, loss = 3.02799
-I0511 10:12:52.570567  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.16478 (* 1 = 2.16478 loss)
-I0511 10:12:52.570576  5307 sgd_solver.cpp:172] Iteration 110900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:13:53.284628  5307 solver.cpp:352] Iteration 111000 (1.64709 iter/s, 60.7131s/100 iter), 214.6/232ep, loss = 2.94168
-I0511 10:13:53.284693  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99242 (* 1 = 2.99242 loss)
-I0511 10:13:53.284700  5307 sgd_solver.cpp:172] Iteration 111000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:14:53.858494  5307 solver.cpp:352] Iteration 111100 (1.65091 iter/s, 60.5728s/100 iter), 214.8/232ep, loss = 2.93955
-I0511 10:14:53.858589  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.69679 (* 1 = 2.69679 loss)
-I0511 10:14:53.858608  5307 sgd_solver.cpp:172] Iteration 111100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:15:44.839627  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:15:55.098361  5307 solver.cpp:352] Iteration 111200 (1.63295 iter/s, 61.2388s/100 iter), 215/232ep, loss = 2.86403
-I0511 10:15:55.098414  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.10467 (* 1 = 3.10467 loss)
-I0511 10:15:55.098424  5307 sgd_solver.cpp:172] Iteration 111200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:16:55.731014  5307 solver.cpp:352] Iteration 111300 (1.6493 iter/s, 60.6316s/100 iter), 215.2/232ep, loss = 3.04527
-I0511 10:16:55.731109  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95204 (* 1 = 2.95204 loss)
-I0511 10:16:55.731127  5307 sgd_solver.cpp:172] Iteration 111300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:17:56.691306  5307 solver.cpp:352] Iteration 111400 (1.64044 iter/s, 60.9592s/100 iter), 215.4/232ep, loss = 2.94958
-I0511 10:17:56.691378  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.11284 (* 1 = 3.11284 loss)
-I0511 10:17:56.691396  5307 sgd_solver.cpp:172] Iteration 111400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:18:57.145282  5307 solver.cpp:352] Iteration 111500 (1.65418 iter/s, 60.4529s/100 iter), 215.6/232ep, loss = 3.01524
-I0511 10:18:57.145421  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94067 (* 1 = 2.94067 loss)
-I0511 10:18:57.145431  5307 sgd_solver.cpp:172] Iteration 111500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:19:58.131446  5307 solver.cpp:352] Iteration 111600 (1.63975 iter/s, 60.9851s/100 iter), 215.8/232ep, loss = 2.99065
-I0511 10:19:58.131516  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92307 (* 1 = 2.92307 loss)
-I0511 10:19:58.131525  5307 sgd_solver.cpp:172] Iteration 111600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:20:59.895972  5307 solver.cpp:352] Iteration 111700 (1.61908 iter/s, 61.7634s/100 iter), 216/232ep, loss = 2.88708
-I0511 10:20:59.896270  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.31386 (* 1 = 2.31386 loss)
-I0511 10:20:59.896335  5307 sgd_solver.cpp:172] Iteration 111700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:21:00.557533  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:22:00.743355  5307 solver.cpp:352] Iteration 111800 (1.64349 iter/s, 60.8463s/100 iter), 216.2/232ep, loss = 3.08605
-I0511 10:22:00.746047  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7764 (* 1 = 2.7764 loss)
-I0511 10:22:00.746073  5307 sgd_solver.cpp:172] Iteration 111800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:23:01.987576  5307 solver.cpp:352] Iteration 111900 (1.63284 iter/s, 61.2431s/100 iter), 216.3/232ep, loss = 3.08897
-I0511 10:23:01.987634  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.6799 (* 1 = 2.6799 loss)
-I0511 10:23:01.987643  5307 sgd_solver.cpp:172] Iteration 111900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:24:03.145884  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_112000.caffemodel
-I0511 10:24:03.165766  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_112000.solverstate
-I0511 10:24:03.171766  5307 solver.cpp:635] Iteration 112000, Testing net (#0)
-I0511 10:24:43.817241  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:24:44.021019  5307 solver.cpp:747] class AP 1: 0.652025
-I0511 10:24:44.021556  5307 solver.cpp:747] class AP 2: 0.735424
-I0511 10:24:44.027999  5307 solver.cpp:747] class AP 3: 0.562478
-I0511 10:24:44.031703  5307 solver.cpp:747] class AP 4: 0.510381
-I0511 10:24:44.049821  5307 solver.cpp:747] class AP 5: 0.346569
-I0511 10:24:44.050158  5307 solver.cpp:747] class AP 6: 0.736914
-I0511 10:24:44.058876  5307 solver.cpp:747] class AP 7: 0.704268
-I0511 10:24:44.059409  5307 solver.cpp:747] class AP 8: 0.818155
-I0511 10:24:44.077251  5307 solver.cpp:747] class AP 9: 0.431948
-I0511 10:24:44.078028  5307 solver.cpp:747] class AP 10: 0.627871
-I0511 10:24:44.078682  5307 solver.cpp:747] class AP 11: 0.593541
-I0511 10:24:44.079497  5307 solver.cpp:747] class AP 12: 0.724921
-I0511 10:24:44.079932  5307 solver.cpp:747] class AP 13: 0.804708
-I0511 10:24:44.080291  5307 solver.cpp:747] class AP 14: 0.748014
-I0511 10:24:44.131726  5307 solver.cpp:747] class AP 15: 0.726007
-I0511 10:24:44.138413  5307 solver.cpp:747] class AP 16: 0.365348
-I0511 10:24:44.140985  5307 solver.cpp:747] class AP 17: 0.598858
-I0511 10:24:44.141667  5307 solver.cpp:747] class AP 18: 0.608303
-I0511 10:24:44.142585  5307 solver.cpp:747] class AP 19: 0.754497
-I0511 10:24:44.144356  5307 solver.cpp:747] class AP 20: 0.611097
-I0511 10:24:44.144549  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.633066
-I0511 10:24:44.144703  5307 solver.cpp:283] Tests completed in 102.155s
-I0511 10:24:44.779572  5307 solver.cpp:352] Iteration 112000 (0.978902 iter/s, 102.155s/100 iter), 216.5/232ep, loss = 2.84662
-I0511 10:24:44.779598  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.99714 (* 1 = 2.99714 loss)
-I0511 10:24:44.779605  5307 sgd_solver.cpp:172] Iteration 112000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:25:45.657253  5307 solver.cpp:352] Iteration 112100 (1.64267 iter/s, 60.8766s/100 iter), 216.7/232ep, loss = 2.94875
-I0511 10:25:45.657313  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.73282 (* 1 = 3.73282 loss)
-I0511 10:25:45.657322  5307 sgd_solver.cpp:172] Iteration 112100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:26:47.189956  5307 solver.cpp:352] Iteration 112200 (1.62518 iter/s, 61.5316s/100 iter), 216.9/232ep, loss = 2.94758
-I0511 10:26:47.190044  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77857 (* 1 = 2.77857 loss)
-I0511 10:26:47.190053  5307 sgd_solver.cpp:172] Iteration 112200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:26:58.774957  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:27:48.748471  5307 solver.cpp:352] Iteration 112300 (1.6245 iter/s, 61.5574s/100 iter), 217.1/232ep, loss = 3.19982
-I0511 10:27:48.748627  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.7726 (* 1 = 3.7726 loss)
-I0511 10:27:48.748638  5307 sgd_solver.cpp:172] Iteration 112300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:28:51.163944  5307 solver.cpp:352] Iteration 112400 (1.60219 iter/s, 62.4144s/100 iter), 217.3/232ep, loss = 3.03614
-I0511 10:28:51.166050  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.94561 (* 1 = 2.94561 loss)
-I0511 10:28:51.166059  5307 sgd_solver.cpp:172] Iteration 112400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:29:52.775889  5307 solver.cpp:352] Iteration 112500 (1.62309 iter/s, 61.6109s/100 iter), 217.5/232ep, loss = 3.00284
-I0511 10:29:52.775948  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1787 (* 1 = 3.1787 loss)
-I0511 10:29:52.775956  5307 sgd_solver.cpp:172] Iteration 112500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:30:53.999619  5307 solver.cpp:352] Iteration 112600 (1.63338 iter/s, 61.2226s/100 iter), 217.7/232ep, loss = 3.09079
-I0511 10:30:53.999730  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.16119 (* 1 = 3.16119 loss)
-I0511 10:30:53.999747  5307 sgd_solver.cpp:172] Iteration 112600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:31:55.897014  5307 solver.cpp:352] Iteration 112700 (1.61561 iter/s, 61.8963s/100 iter), 217.9/232ep, loss = 3.09488
-I0511 10:31:55.899727  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.09322 (* 1 = 3.09322 loss)
-I0511 10:31:55.899747  5307 sgd_solver.cpp:172] Iteration 112700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:32:17.061614  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:32:56.688714  5307 solver.cpp:352] Iteration 112800 (1.64499 iter/s, 60.7906s/100 iter), 218.1/232ep, loss = 2.89371
-I0511 10:32:56.688843  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.51754 (* 1 = 2.51754 loss)
-I0511 10:32:56.688855  5307 sgd_solver.cpp:172] Iteration 112800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:33:57.503278  5307 solver.cpp:352] Iteration 112900 (1.64437 iter/s, 60.8135s/100 iter), 218.3/232ep, loss = 3.04521
-I0511 10:33:57.503353  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81041 (* 1 = 2.81041 loss)
-I0511 10:33:57.503362  5307 sgd_solver.cpp:172] Iteration 112900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:34:58.744582  5307 solver.cpp:352] Iteration 113000 (1.63291 iter/s, 61.2402s/100 iter), 218.5/232ep, loss = 3.17241
-I0511 10:34:58.744669  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.21981 (* 1 = 3.21981 loss)
-I0511 10:34:58.744678  5307 sgd_solver.cpp:172] Iteration 113000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:35:59.644662  5307 solver.cpp:352] Iteration 113100 (1.64206 iter/s, 60.899s/100 iter), 218.7/232ep, loss = 2.95082
-I0511 10:35:59.644762  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39512 (* 1 = 3.39512 loss)
-I0511 10:35:59.644781  5307 sgd_solver.cpp:172] Iteration 113100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:37:00.493922  5307 solver.cpp:352] Iteration 113200 (1.64343 iter/s, 60.8482s/100 iter), 218.9/232ep, loss = 2.90385
-I0511 10:37:00.494029  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.05948 (* 1 = 3.05948 loss)
-I0511 10:37:00.494048  5307 sgd_solver.cpp:172] Iteration 113200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:37:33.207693  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:38:01.939122  5307 solver.cpp:352] Iteration 113300 (1.6275 iter/s, 61.4441s/100 iter), 219.1/232ep, loss = 2.96832
-I0511 10:38:01.939155  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.38524 (* 1 = 3.38524 loss)
-I0511 10:38:01.939164  5307 sgd_solver.cpp:172] Iteration 113300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:39:02.934594  5307 solver.cpp:352] Iteration 113400 (1.6395 iter/s, 60.9944s/100 iter), 219.2/232ep, loss = 2.95074
-I0511 10:39:02.934692  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.87529 (* 1 = 2.87529 loss)
-I0511 10:39:02.934710  5307 sgd_solver.cpp:172] Iteration 113400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:40:03.528507  5307 solver.cpp:352] Iteration 113500 (1.65036 iter/s, 60.5928s/100 iter), 219.4/232ep, loss = 3.19723
-I0511 10:40:03.533421  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77092 (* 1 = 2.77092 loss)
-I0511 10:40:03.533440  5307 sgd_solver.cpp:172] Iteration 113500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:41:03.971828  5307 solver.cpp:352] Iteration 113600 (1.65447 iter/s, 60.4422s/100 iter), 219.6/232ep, loss = 2.86982
-I0511 10:41:03.972090  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.33419 (* 1 = 3.33419 loss)
-I0511 10:41:03.972113  5307 sgd_solver.cpp:172] Iteration 113600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:42:05.621686  5307 solver.cpp:352] Iteration 113700 (1.62209 iter/s, 61.6487s/100 iter), 219.8/232ep, loss = 3.13368
-I0511 10:42:05.621779  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.27146 (* 1 = 2.27146 loss)
-I0511 10:42:05.621790  5307 sgd_solver.cpp:172] Iteration 113700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:42:48.676345  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:43:06.615356  5307 solver.cpp:352] Iteration 113800 (1.63955 iter/s, 60.9925s/100 iter), 220/232ep, loss = 2.8886
-I0511 10:43:06.615412  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.03967 (* 1 = 3.03967 loss)
-I0511 10:43:06.615424  5307 sgd_solver.cpp:172] Iteration 113800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:44:08.389992  5307 solver.cpp:352] Iteration 113900 (1.61882 iter/s, 61.7735s/100 iter), 220.2/232ep, loss = 2.9446
-I0511 10:44:08.390053  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.37132 (* 1 = 3.37132 loss)
-I0511 10:44:08.390061  5307 sgd_solver.cpp:172] Iteration 113900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:45:08.962965  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_114000.caffemodel
-I0511 10:45:08.976925  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_114000.solverstate
-I0511 10:45:08.981122  5307 solver.cpp:635] Iteration 114000, Testing net (#0)
-I0511 10:45:49.198523  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:45:49.415805  5307 solver.cpp:747] class AP 1: 0.662198
-I0511 10:45:49.416313  5307 solver.cpp:747] class AP 2: 0.729406
-I0511 10:45:49.422883  5307 solver.cpp:747] class AP 3: 0.557192
-I0511 10:45:49.426580  5307 solver.cpp:747] class AP 4: 0.507719
-I0511 10:45:49.445612  5307 solver.cpp:747] class AP 5: 0.345573
-I0511 10:45:49.445950  5307 solver.cpp:747] class AP 6: 0.74042
-I0511 10:45:49.454557  5307 solver.cpp:747] class AP 7: 0.705059
-I0511 10:45:49.455088  5307 solver.cpp:747] class AP 8: 0.816973
-I0511 10:45:49.473081  5307 solver.cpp:747] class AP 9: 0.431518
-I0511 10:45:49.473772  5307 solver.cpp:747] class AP 10: 0.628521
-I0511 10:45:49.474426  5307 solver.cpp:747] class AP 11: 0.587503
-I0511 10:45:49.475253  5307 solver.cpp:747] class AP 12: 0.720823
-I0511 10:45:49.475683  5307 solver.cpp:747] class AP 13: 0.790295
-I0511 10:45:49.476042  5307 solver.cpp:747] class AP 14: 0.743502
-I0511 10:45:49.524214  5307 solver.cpp:747] class AP 15: 0.723762
-I0511 10:45:49.530274  5307 solver.cpp:747] class AP 16: 0.361899
-I0511 10:45:49.532704  5307 solver.cpp:747] class AP 17: 0.596467
-I0511 10:45:49.533264  5307 solver.cpp:747] class AP 18: 0.607036
-I0511 10:45:49.533893  5307 solver.cpp:747] class AP 19: 0.745844
-I0511 10:45:49.535290  5307 solver.cpp:747] class AP 20: 0.614507
-I0511 10:45:49.535298  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.630811
-I0511 10:45:49.535538  5307 solver.cpp:283] Tests completed in 101.144s
-I0511 10:45:50.078846  5307 solver.cpp:352] Iteration 114000 (0.988692 iter/s, 101.144s/100 iter), 220.4/232ep, loss = 3.01824
-I0511 10:45:50.078913  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.92418 (* 1 = 2.92418 loss)
-I0511 10:45:50.079262  5307 sgd_solver.cpp:172] Iteration 114000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:46:51.070911  5307 solver.cpp:352] Iteration 114100 (1.63959 iter/s, 60.9909s/100 iter), 220.6/232ep, loss = 2.88598
-I0511 10:46:51.071024  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1741 (* 1 = 3.1741 loss)
-I0511 10:46:51.071035  5307 sgd_solver.cpp:172] Iteration 114100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:47:52.394845  5307 solver.cpp:352] Iteration 114200 (1.63071 iter/s, 61.3228s/100 iter), 220.8/232ep, loss = 2.99809
-I0511 10:47:52.394902  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.29741 (* 1 = 3.29741 loss)
-I0511 10:47:52.394942  5307 sgd_solver.cpp:172] Iteration 114200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:48:46.215500  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:48:53.950975  5307 solver.cpp:352] Iteration 114300 (1.62456 iter/s, 61.555s/100 iter), 221/232ep, loss = 2.97063
-I0511 10:48:53.951047  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.24911 (* 1 = 3.24911 loss)
-I0511 10:48:53.951067  5307 sgd_solver.cpp:172] Iteration 114300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:49:54.352638  5307 solver.cpp:352] Iteration 114400 (1.65561 iter/s, 60.4006s/100 iter), 221.2/232ep, loss = 2.91539
-I0511 10:49:54.353127  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65132 (* 1 = 3.65132 loss)
-I0511 10:49:54.353137  5307 sgd_solver.cpp:172] Iteration 114400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:50:55.012678  5307 solver.cpp:352] Iteration 114500 (1.64856 iter/s, 60.659s/100 iter), 221.4/232ep, loss = 2.86124
-I0511 10:50:55.012753  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.58102 (* 1 = 2.58102 loss)
-I0511 10:50:55.012768  5307 sgd_solver.cpp:172] Iteration 114500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:51:56.122793  5307 solver.cpp:352] Iteration 114600 (1.63642 iter/s, 61.109s/100 iter), 221.6/232ep, loss = 3.12296
-I0511 10:51:56.122936  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.54923 (* 1 = 3.54923 loss)
-I0511 10:51:56.122951  5307 sgd_solver.cpp:172] Iteration 114600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:52:58.023329  5307 solver.cpp:352] Iteration 114700 (1.61552 iter/s, 61.8994s/100 iter), 221.8/232ep, loss = 2.80427
-I0511 10:52:58.023398  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.63464 (* 1 = 2.63464 loss)
-I0511 10:52:58.023407  5307 sgd_solver.cpp:172] Iteration 114700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:53:59.532196  5307 solver.cpp:352] Iteration 114800 (1.62581 iter/s, 61.5078s/100 iter), 222/232ep, loss = 2.89953
-I0511 10:53:59.532305  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.07735 (* 1 = 3.07735 loss)
-I0511 10:53:59.532322  5307 sgd_solver.cpp:172] Iteration 114800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:54:02.501703  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 10:55:02.028355  5307 solver.cpp:352] Iteration 114900 (1.60013 iter/s, 62.4951s/100 iter), 222.1/232ep, loss = 2.98781
-I0511 10:55:02.028434  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15999 (* 1 = 3.15999 loss)
-I0511 10:55:02.028443  5307 sgd_solver.cpp:172] Iteration 114900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:56:03.357002  5307 solver.cpp:352] Iteration 115000 (1.63059 iter/s, 61.3276s/100 iter), 222.3/232ep, loss = 3.05279
-I0511 10:56:03.364600  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.97168 (* 1 = 1.97168 loss)
-I0511 10:56:03.364627  5307 sgd_solver.cpp:172] Iteration 115000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:57:05.293462  5307 solver.cpp:352] Iteration 115100 (1.61459 iter/s, 61.9354s/100 iter), 222.5/232ep, loss = 2.94648
-I0511 10:57:05.293543  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.89315 (* 1 = 2.89315 loss)
-I0511 10:57:05.293552  5307 sgd_solver.cpp:172] Iteration 115100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:58:06.643431  5307 solver.cpp:352] Iteration 115200 (1.63002 iter/s, 61.3489s/100 iter), 222.7/232ep, loss = 2.99899
-I0511 10:58:06.643540  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.02968 (* 1 = 3.02968 loss)
-I0511 10:58:06.643551  5307 sgd_solver.cpp:172] Iteration 115200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:59:08.695617  5307 solver.cpp:352] Iteration 115300 (1.61158 iter/s, 62.0511s/100 iter), 222.9/232ep, loss = 3.02161
-I0511 10:59:08.695713  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.39698 (* 1 = 3.39698 loss)
-I0511 10:59:08.695724  5307 sgd_solver.cpp:172] Iteration 115300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 10:59:21.704402  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:00:09.808604  5307 solver.cpp:352] Iteration 115400 (1.63634 iter/s, 61.1119s/100 iter), 223.1/232ep, loss = 2.98201
-I0511 11:00:09.808735  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.65728 (* 1 = 2.65728 loss)
-I0511 11:00:09.808758  5307 sgd_solver.cpp:172] Iteration 115400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:01:10.817817  5307 solver.cpp:352] Iteration 115500 (1.63913 iter/s, 61.0081s/100 iter), 223.3/232ep, loss = 2.86876
-I0511 11:01:10.817908  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.74372 (* 1 = 3.74372 loss)
-I0511 11:01:10.817925  5307 sgd_solver.cpp:172] Iteration 115500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:02:12.303939  5307 solver.cpp:352] Iteration 115600 (1.62641 iter/s, 61.485s/100 iter), 223.5/232ep, loss = 2.99374
-I0511 11:02:12.307034  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.66607 (* 1 = 2.66607 loss)
-I0511 11:02:12.307056  5307 sgd_solver.cpp:172] Iteration 115600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:03:12.455924  5307 solver.cpp:352] Iteration 115700 (1.66249 iter/s, 60.1509s/100 iter), 223.7/232ep, loss = 3.09511
-I0511 11:03:12.455989  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.1523 (* 1 = 3.1523 loss)
-I0511 11:03:12.455998  5307 sgd_solver.cpp:172] Iteration 115700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:04:13.109742  5307 solver.cpp:352] Iteration 115800 (1.64873 iter/s, 60.6527s/100 iter), 223.9/232ep, loss = 2.8967
-I0511 11:04:13.109834  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7674 (* 1 = 2.7674 loss)
-I0511 11:04:13.109855  5307 sgd_solver.cpp:172] Iteration 115800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:04:37.028450  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:05:14.281826  5307 solver.cpp:352] Iteration 115900 (1.63476 iter/s, 61.171s/100 iter), 224.1/232ep, loss = 2.95257
-I0511 11:05:14.281886  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.62779 (* 1 = 2.62779 loss)
-I0511 11:05:14.281895  5307 sgd_solver.cpp:172] Iteration 115900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:06:14.788892  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_116000.caffemodel
-I0511 11:06:14.807366  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_116000.solverstate
-I0511 11:06:14.813482  5307 solver.cpp:635] Iteration 116000, Testing net (#0)
-I0511 11:06:55.290019  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:06:55.517653  5307 solver.cpp:747] class AP 1: 0.650297
-I0511 11:06:55.518486  5307 solver.cpp:747] class AP 2: 0.731171
-I0511 11:06:55.527159  5307 solver.cpp:747] class AP 3: 0.55694
-I0511 11:06:55.532552  5307 solver.cpp:747] class AP 4: 0.516235
-I0511 11:06:55.556718  5307 solver.cpp:747] class AP 5: 0.347945
-I0511 11:06:55.557184  5307 solver.cpp:747] class AP 6: 0.737584
-I0511 11:06:55.568270  5307 solver.cpp:747] class AP 7: 0.704858
-I0511 11:06:55.569039  5307 solver.cpp:747] class AP 8: 0.81655
-I0511 11:06:55.593116  5307 solver.cpp:747] class AP 9: 0.433403
-I0511 11:06:55.593871  5307 solver.cpp:747] class AP 10: 0.627933
-I0511 11:06:55.594524  5307 solver.cpp:747] class AP 11: 0.592362
-I0511 11:06:55.595378  5307 solver.cpp:747] class AP 12: 0.722884
-I0511 11:06:55.595813  5307 solver.cpp:747] class AP 13: 0.802147
-I0511 11:06:55.596138  5307 solver.cpp:747] class AP 14: 0.744025
-I0511 11:06:55.643785  5307 solver.cpp:747] class AP 15: 0.726057
-I0511 11:06:55.650180  5307 solver.cpp:747] class AP 16: 0.359646
-I0511 11:06:55.652637  5307 solver.cpp:747] class AP 17: 0.594529
-I0511 11:06:55.653204  5307 solver.cpp:747] class AP 18: 0.609831
-I0511 11:06:55.653875  5307 solver.cpp:747] class AP 19: 0.743373
-I0511 11:06:55.655283  5307 solver.cpp:747] class AP 20: 0.619952
-I0511 11:06:55.655295  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.631886
-I0511 11:06:55.655506  5307 solver.cpp:283] Tests completed in 101.372s
-I0511 11:06:56.292500  5307 solver.cpp:352] Iteration 116000 (0.986467 iter/s, 101.372s/100 iter), 224.3/232ep, loss = 3.11957
-I0511 11:06:56.292546  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71054 (* 1 = 2.71054 loss)
-I0511 11:06:56.292552  5307 sgd_solver.cpp:172] Iteration 116000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:08:02.647570  5307 solver.cpp:352] Iteration 116100 (1.50707 iter/s, 66.3538s/100 iter), 224.5/232ep, loss = 3.17559
-I0511 11:08:02.647683  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.4876 (* 1 = 3.4876 loss)
-I0511 11:08:02.647696  5307 sgd_solver.cpp:172] Iteration 116100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:09:08.393443  5307 solver.cpp:352] Iteration 116200 (1.52104 iter/s, 65.7447s/100 iter), 224.7/232ep, loss = 2.99814
-I0511 11:09:08.396077  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22462 (* 1 = 3.22462 loss)
-I0511 11:09:08.396090  5307 sgd_solver.cpp:172] Iteration 116200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:10:09.231055  5307 solver.cpp:352] Iteration 116300 (1.64375 iter/s, 60.8365s/100 iter), 224.9/232ep, loss = 3.04884
-I0511 11:10:09.231128  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.9264 (* 1 = 3.9264 loss)
-I0511 11:10:09.231138  5307 sgd_solver.cpp:172] Iteration 116300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:10:43.547654  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:11:09.930076  5307 solver.cpp:352] Iteration 116400 (1.6475 iter/s, 60.6979s/100 iter), 225/232ep, loss = 3.0008
-I0511 11:11:09.930106  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.90725 (* 1 = 2.90725 loss)
-I0511 11:11:09.930115  5307 sgd_solver.cpp:172] Iteration 116400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:12:09.585803  5307 solver.cpp:352] Iteration 116500 (1.67631 iter/s, 59.6547s/100 iter), 225.2/232ep, loss = 3.17016
-I0511 11:12:09.585994  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.0389 (* 1 = 3.0389 loss)
-I0511 11:12:09.586025  5307 sgd_solver.cpp:172] Iteration 116500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:13:10.186215  5307 solver.cpp:352] Iteration 116600 (1.65018 iter/s, 60.5993s/100 iter), 225.4/232ep, loss = 2.88852
-I0511 11:13:10.186285  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.17429 (* 1 = 3.17429 loss)
-I0511 11:13:10.186295  5307 sgd_solver.cpp:172] Iteration 116600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:14:09.787925  5307 solver.cpp:352] Iteration 116700 (1.67783 iter/s, 59.6007s/100 iter), 225.6/232ep, loss = 3.10487
-I0511 11:14:09.788018  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.28151 (* 1 = 3.28151 loss)
-I0511 11:14:09.788035  5307 sgd_solver.cpp:172] Iteration 116700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:15:11.139684  5307 solver.cpp:352] Iteration 116800 (1.62997 iter/s, 61.3507s/100 iter), 225.8/232ep, loss = 3.23564
-I0511 11:15:11.139751  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.45886 (* 1 = 3.45886 loss)
-I0511 11:15:11.139758  5307 sgd_solver.cpp:172] Iteration 116800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:15:55.356794  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:16:11.635367  5307 solver.cpp:352] Iteration 116900 (1.65304 iter/s, 60.4946s/100 iter), 226/232ep, loss = 3.05684
-I0511 11:16:11.635630  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91783 (* 1 = 2.91783 loss)
-I0511 11:16:11.635658  5307 sgd_solver.cpp:172] Iteration 116900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:17:12.995401  5307 solver.cpp:352] Iteration 117000 (1.62975 iter/s, 61.359s/100 iter), 226.2/232ep, loss = 2.99461
-I0511 11:17:12.995496  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.50326 (* 1 = 3.50326 loss)
-I0511 11:17:12.995514  5307 sgd_solver.cpp:172] Iteration 117000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:18:13.218389  5307 solver.cpp:352] Iteration 117100 (1.66052 iter/s, 60.2219s/100 iter), 226.4/232ep, loss = 3.03247
-I0511 11:18:13.218454  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68845 (* 1 = 3.68845 loss)
-I0511 11:18:13.218463  5307 sgd_solver.cpp:172] Iteration 117100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:19:13.291749  5307 solver.cpp:352] Iteration 117200 (1.66466 iter/s, 60.0723s/100 iter), 226.6/232ep, loss = 2.87023
-I0511 11:19:13.291846  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.85732 (* 1 = 2.85732 loss)
-I0511 11:19:13.291857  5307 sgd_solver.cpp:172] Iteration 117200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:20:13.224674  5307 solver.cpp:352] Iteration 117300 (1.66856 iter/s, 59.9319s/100 iter), 226.8/232ep, loss = 2.96887
-I0511 11:20:13.225811  5307 solver.cpp:376]     Train net output #0: mbox_loss = 1.86509 (* 1 = 1.86509 loss)
-I0511 11:20:13.225838  5307 sgd_solver.cpp:172] Iteration 117300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:21:08.103113  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:21:13.299240  5307 solver.cpp:352] Iteration 117400 (1.66463 iter/s, 60.0735s/100 iter), 227/232ep, loss = 3.09113
-I0511 11:21:13.299270  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.52411 (* 1 = 2.52411 loss)
-I0511 11:21:13.299278  5307 sgd_solver.cpp:172] Iteration 117400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:22:13.700301  5307 solver.cpp:352] Iteration 117500 (1.65563 iter/s, 60.4s/100 iter), 227.2/232ep, loss = 3.03423
-I0511 11:22:13.700546  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.85504 (* 1 = 3.85504 loss)
-I0511 11:22:13.700562  5307 sgd_solver.cpp:172] Iteration 117500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:23:14.520663  5307 solver.cpp:352] Iteration 117600 (1.64422 iter/s, 60.8193s/100 iter), 227.4/232ep, loss = 2.91665
-I0511 11:23:14.520825  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.40878 (* 1 = 2.40878 loss)
-I0511 11:23:14.520834  5307 sgd_solver.cpp:172] Iteration 117600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:24:15.486469  5307 solver.cpp:352] Iteration 117700 (1.64029 iter/s, 60.9647s/100 iter), 227.6/232ep, loss = 3.19194
-I0511 11:24:15.486999  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.24722 (* 1 = 3.24722 loss)
-I0511 11:24:15.487007  5307 sgd_solver.cpp:172] Iteration 117700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:25:16.517316  5307 solver.cpp:352] Iteration 117800 (1.63855 iter/s, 61.0297s/100 iter), 227.8/232ep, loss = 2.87382
-I0511 11:25:16.517437  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.81489 (* 1 = 2.81489 loss)
-I0511 11:25:16.517447  5307 sgd_solver.cpp:172] Iteration 117800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:26:16.765038  5307 solver.cpp:352] Iteration 117900 (1.65984 iter/s, 60.2466s/100 iter), 227.9/232ep, loss = 2.99439
-I0511 11:26:16.765139  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.282 (* 1 = 2.282 loss)
-I0511 11:26:16.765159  5307 sgd_solver.cpp:172] Iteration 117900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:26:21.159152  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:27:17.238680  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_118000.caffemodel
-I0511 11:27:17.257541  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_118000.solverstate
-I0511 11:27:17.263979  5307 solver.cpp:635] Iteration 118000, Testing net (#0)
-I0511 11:27:57.641331  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:27:57.861429  5307 solver.cpp:747] class AP 1: 0.654472
-I0511 11:27:57.861944  5307 solver.cpp:747] class AP 2: 0.731609
-I0511 11:27:57.868554  5307 solver.cpp:747] class AP 3: 0.557668
-I0511 11:27:57.872315  5307 solver.cpp:747] class AP 4: 0.517042
-I0511 11:27:57.891069  5307 solver.cpp:747] class AP 5: 0.345227
-I0511 11:27:57.891412  5307 solver.cpp:747] class AP 6: 0.738804
-I0511 11:27:57.900190  5307 solver.cpp:747] class AP 7: 0.703705
-I0511 11:27:57.900959  5307 solver.cpp:747] class AP 8: 0.817978
-I0511 11:27:57.920097  5307 solver.cpp:747] class AP 9: 0.430764
-I0511 11:27:57.920806  5307 solver.cpp:747] class AP 10: 0.635427
-I0511 11:27:57.921437  5307 solver.cpp:747] class AP 11: 0.594552
-I0511 11:27:57.922281  5307 solver.cpp:747] class AP 12: 0.719994
-I0511 11:27:57.922788  5307 solver.cpp:747] class AP 13: 0.788424
-I0511 11:27:57.923264  5307 solver.cpp:747] class AP 14: 0.745163
-I0511 11:27:57.972834  5307 solver.cpp:747] class AP 15: 0.725318
-I0511 11:27:57.979189  5307 solver.cpp:747] class AP 16: 0.368298
-I0511 11:27:57.981844  5307 solver.cpp:747] class AP 17: 0.596233
-I0511 11:27:57.982441  5307 solver.cpp:747] class AP 18: 0.610433
-I0511 11:27:57.983145  5307 solver.cpp:747] class AP 19: 0.751794
-I0511 11:27:57.984674  5307 solver.cpp:747] class AP 20: 0.617365
-I0511 11:27:57.984683  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.632513
-I0511 11:27:57.984807  5307 solver.cpp:283] Tests completed in 101.218s
-I0511 11:27:58.641021  5307 solver.cpp:352] Iteration 118000 (0.987967 iter/s, 101.218s/100 iter), 228.1/232ep, loss = 2.9497
-I0511 11:27:58.641055  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.12983 (* 1 = 3.12983 loss)
-I0511 11:27:58.641063  5307 sgd_solver.cpp:172] Iteration 118000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:28:58.839681  5307 solver.cpp:352] Iteration 118100 (1.6612 iter/s, 60.1975s/100 iter), 228.3/232ep, loss = 3.24715
-I0511 11:28:58.839756  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.65285 (* 1 = 3.65285 loss)
-I0511 11:28:58.839774  5307 sgd_solver.cpp:172] Iteration 118100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:30:00.189913  5307 solver.cpp:352] Iteration 118200 (1.63002 iter/s, 61.3491s/100 iter), 228.5/232ep, loss = 2.8064
-I0511 11:30:00.191293  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.91214 (* 1 = 2.91214 loss)
-I0511 11:30:00.191314  5307 sgd_solver.cpp:172] Iteration 118200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:31:00.269927  5307 solver.cpp:352] Iteration 118300 (1.66448 iter/s, 60.0789s/100 iter), 228.7/232ep, loss = 3.06632
-I0511 11:31:00.270061  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44544 (* 1 = 3.44544 loss)
-I0511 11:31:00.270086  5307 sgd_solver.cpp:172] Iteration 118300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:32:01.229151  5307 solver.cpp:352] Iteration 118400 (1.64047 iter/s, 60.9581s/100 iter), 228.9/232ep, loss = 2.92896
-I0511 11:32:01.229290  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.68048 (* 1 = 3.68048 loss)
-I0511 11:32:01.229305  5307 sgd_solver.cpp:172] Iteration 118400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:32:16.214731  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:33:01.567019  5307 solver.cpp:352] Iteration 118500 (1.65736 iter/s, 60.3368s/100 iter), 229.1/232ep, loss = 3.13304
-I0511 11:33:01.567117  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.15197 (* 1 = 3.15197 loss)
-I0511 11:33:01.567138  5307 sgd_solver.cpp:172] Iteration 118500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:34:01.775032  5307 solver.cpp:352] Iteration 118600 (1.66094 iter/s, 60.207s/100 iter), 229.3/232ep, loss = 3.0296
-I0511 11:34:01.775141  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.71965 (* 1 = 2.71965 loss)
-I0511 11:34:01.775158  5307 sgd_solver.cpp:172] Iteration 118600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:35:02.408643  5307 solver.cpp:352] Iteration 118700 (1.64928 iter/s, 60.6325s/100 iter), 229.5/232ep, loss = 2.91601
-I0511 11:35:02.408749  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.7621 (* 1 = 2.7621 loss)
-I0511 11:35:02.408767  5307 sgd_solver.cpp:172] Iteration 118700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:36:03.211777  5307 solver.cpp:352] Iteration 118800 (1.64468 iter/s, 60.8021s/100 iter), 229.7/232ep, loss = 3.03007
-I0511 11:36:03.211851  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.71402 (* 1 = 3.71402 loss)
-I0511 11:36:03.211863  5307 sgd_solver.cpp:172] Iteration 118800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:37:03.776070  5307 solver.cpp:352] Iteration 118900 (1.65117 iter/s, 60.5632s/100 iter), 229.9/232ep, loss = 2.9015
-I0511 11:37:03.776235  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.77313 (* 1 = 2.77313 loss)
-I0511 11:37:03.776248  5307 sgd_solver.cpp:172] Iteration 118900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:37:29.550253  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:38:03.689391  5307 solver.cpp:352] Iteration 119000 (1.66911 iter/s, 59.9123s/100 iter), 230.1/232ep, loss = 2.88679
-I0511 11:38:03.689962  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.22293 (* 1 = 3.22293 loss)
-I0511 11:38:03.690055  5307 sgd_solver.cpp:172] Iteration 119000, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:39:03.612455  5307 solver.cpp:352] Iteration 119100 (1.66884 iter/s, 59.922s/100 iter), 230.3/232ep, loss = 3.19493
-I0511 11:39:03.612581  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.60366 (* 1 = 2.60366 loss)
-I0511 11:39:03.612608  5307 sgd_solver.cpp:172] Iteration 119100, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:40:04.584720  5307 solver.cpp:352] Iteration 119200 (1.64012 iter/s, 60.9712s/100 iter), 230.5/232ep, loss = 3.04357
-I0511 11:40:04.584801  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.52593 (* 1 = 3.52593 loss)
-I0511 11:40:04.584810  5307 sgd_solver.cpp:172] Iteration 119200, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:41:06.064980  5307 solver.cpp:352] Iteration 119300 (1.62657 iter/s, 61.4792s/100 iter), 230.7/232ep, loss = 2.91227
-I0511 11:41:06.065052  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.61844 (* 1 = 2.61844 loss)
-I0511 11:41:06.065062  5307 sgd_solver.cpp:172] Iteration 119300, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:42:06.932260  5307 solver.cpp:352] Iteration 119400 (1.64295 iter/s, 60.8662s/100 iter), 230.9/232ep, loss = 3.17262
-I0511 11:42:06.932314  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.95531 (* 1 = 2.95531 loss)
-I0511 11:42:06.932320  5307 sgd_solver.cpp:172] Iteration 119400, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:42:42.828730  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:43:07.304044  5307 solver.cpp:352] Iteration 119500 (1.65643 iter/s, 60.3707s/100 iter), 231/232ep, loss = 2.80561
-I0511 11:43:07.304111  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.30471 (* 1 = 3.30471 loss)
-I0511 11:43:07.304133  5307 sgd_solver.cpp:172] Iteration 119500, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:44:08.021536  5307 solver.cpp:352] Iteration 119600 (1.647 iter/s, 60.7164s/100 iter), 231.2/232ep, loss = 2.93156
-I0511 11:44:08.021646  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.35993 (* 1 = 2.35993 loss)
-I0511 11:44:08.021667  5307 sgd_solver.cpp:172] Iteration 119600, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:45:08.781613  5307 solver.cpp:352] Iteration 119700 (1.64585 iter/s, 60.759s/100 iter), 231.4/232ep, loss = 3.03697
-I0511 11:45:08.781715  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.44033 (* 1 = 3.44033 loss)
-I0511 11:45:08.781733  5307 sgd_solver.cpp:172] Iteration 119700, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:46:10.104699  5307 solver.cpp:352] Iteration 119800 (1.63074 iter/s, 61.322s/100 iter), 231.6/232ep, loss = 3.10778
-I0511 11:46:10.104800  5307 solver.cpp:376]     Train net output #0: mbox_loss = 2.60798 (* 1 = 2.60798 loss)
-I0511 11:46:10.104815  5307 sgd_solver.cpp:172] Iteration 119800, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:47:10.143796  5307 solver.cpp:352] Iteration 119900 (1.66561 iter/s, 60.038s/100 iter), 231.8/232ep, loss = 2.83629
-I0511 11:47:10.143863  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.14731 (* 1 = 3.14731 loss)
-I0511 11:47:10.143874  5307 sgd_solver.cpp:172] Iteration 119900, lr = 0.0001, m = 0.9, wd = 0.0001, gs = 1
-I0511 11:47:56.251756  5323 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:48:09.220212  5307 solver.cpp:352] Iteration 119999 (1.67583 iter/s, 59.0753s/99 iter), 232/232ep, loss = 3.15551
-I0511 11:48:09.220237  5307 solver.cpp:376]     Train net output #0: mbox_loss = 3.67871 (* 1 = 3.67871 loss)
-I0511 11:48:09.220245  5307 solver.cpp:905] Snapshotting to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel
-I0511 11:48:09.232520  5307 sgd_solver.cpp:398] Snapshotting solver state to binary proto file training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.solverstate
-I0511 11:48:09.280829  5307 solver.cpp:501] Iteration 120000, loss = 3.15029
-I0511 11:48:09.280858  5307 solver.cpp:635] Iteration 120000, Testing net (#0)
-I0511 11:48:49.480348  5353 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:48:49.715391  5307 solver.cpp:747] class AP 1: 0.651863
-I0511 11:48:49.715903  5307 solver.cpp:747] class AP 2: 0.731042
-I0511 11:48:49.722532  5307 solver.cpp:747] class AP 3: 0.56037
-I0511 11:48:49.726208  5307 solver.cpp:747] class AP 4: 0.508346
-I0511 11:48:49.744891  5307 solver.cpp:747] class AP 5: 0.337747
-I0511 11:48:49.745234  5307 solver.cpp:747] class AP 6: 0.737946
-I0511 11:48:49.753764  5307 solver.cpp:747] class AP 7: 0.703266
-I0511 11:48:49.754317  5307 solver.cpp:747] class AP 8: 0.816119
-I0511 11:48:49.772083  5307 solver.cpp:747] class AP 9: 0.429319
-I0511 11:48:49.772775  5307 solver.cpp:747] class AP 10: 0.63832
-I0511 11:48:49.773403  5307 solver.cpp:747] class AP 11: 0.596956
-I0511 11:48:49.774240  5307 solver.cpp:747] class AP 12: 0.725066
-I0511 11:48:49.774662  5307 solver.cpp:747] class AP 13: 0.799125
-I0511 11:48:49.775009  5307 solver.cpp:747] class AP 14: 0.745774
-I0511 11:48:49.823776  5307 solver.cpp:747] class AP 15: 0.727146
-I0511 11:48:49.830077  5307 solver.cpp:747] class AP 16: 0.366462
-I0511 11:48:49.832449  5307 solver.cpp:747] class AP 17: 0.600338
-I0511 11:48:49.833067  5307 solver.cpp:747] class AP 18: 0.609607
-I0511 11:48:49.833757  5307 solver.cpp:747] class AP 19: 0.750236
-I0511 11:48:49.835151  5307 solver.cpp:747] class AP 20: 0.617223
-I0511 11:48:49.835160  5307 solver.cpp:753] Test net output mAP #0: detection_eval = 0.632614
-I0511 11:48:49.835372  5307 caffe.cpp:268] Solver performance on device 0: 1.589 * 16 = 50.85 img/sec (120000 itr in 7.551e+04 sec)
-I0511 11:48:49.835388  5307 caffe.cpp:271] Optimization Done in 21h 0m 20s
-I0511 11:48:50.933817  4597 caffe.cpp:902] This is NVCaffe 0.17.0 started at Fri May 11 11:48:50 2018
-I0511 11:48:50.933930  4597 caffe.cpp:904] CuDNN version: 7003
-I0511 11:48:50.933935  4597 caffe.cpp:905] CuBLAS version: 9000
-I0511 11:48:50.933938  4597 caffe.cpp:906] CUDA version: 9000
-I0511 11:48:50.933940  4597 caffe.cpp:907] CUDA driver version: 9000
-I0511 11:48:50.933944  4597 caffe.cpp:908] Arguments: 
-[0]: /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-[1]: test_detection
-[2]: --model=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test/test.prototxt
-[3]: --iterations=496
-[4]: --display_sparsity=1
-[5]: --weights=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel
-[6]: --gpu
-[7]: 0
-I0511 11:48:51.207144  4597 gpu_memory.cpp:105] GPUMemory::Manager initialized
-I0511 11:48:51.207890  4597 gpu_memory.cpp:107] Total memory: 11713708032, Free: 11223957504, dev_info[0]: total=11713708032 free=11223957504
-I0511 11:48:51.207895  4597 caffe.cpp:406] Use GPU with device ID 0
-I0511 11:48:51.208423  4597 caffe.cpp:409] GPU device name: GeForce GTX 1080 Ti
-I0511 11:48:51.235842  4597 net.cpp:80] Initializing net from parameters: 
-name: "mobiledetnet-0.5_test"
-state {
-  phase: TEST
-  level: 0
-}
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 10
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
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-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
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-    decay_mult: 0.01
-  }
-  convolution_param {
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-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
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-    weight_filler {
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-    }
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-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
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-  }
-}
-layer {
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-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  top: "conv6/sep"
-  param {
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-    decay_mult: 1
-  }
-  convolution_param {
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-    pad: 0
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-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
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-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
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-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
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-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
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-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
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-  }
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-    decay_mult: 0
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-    weight_filler {
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-    }
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-    dilation: 1
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-layer {
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-  top: "ctx_output1/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  top: "ctx_output1/1x1"
-}
-layer {
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-  top: "ctx_output1"
-  param {
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-  param {
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-    decay_mult: 0
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-    kernel_size: 3
-    group: 512
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-    weight_filler {
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-    }
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-layer {
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-layer {
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-  top: "ctx_output1"
-}
-layer {
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-  top: "ctx_output2/1x1"
-  param {
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-  }
-  param {
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-    decay_mult: 0
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-  convolution_param {
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-    weight_filler {
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-    }
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-      value: 0
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-    dilation: 1
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-layer {
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-  top: "ctx_output2/1x1"
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
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-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
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-    decay_mult: 0.01
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-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
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-layer {
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-  top: "ctx_output2"
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-    scale_bias: true
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-layer {
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-  bottom: "ctx_output2"
-  top: "ctx_output2"
-}
-layer {
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-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-      value: 0
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-    dilation: 1
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-layer {
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-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output3/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output3/relu"
-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19
-    max_size: 88
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx
-I0511 11:48:51.236408  4597 net.cpp:110] Using FLOAT as default forward math type
-I0511 11:48:51.236418  4597 net.cpp:116] Using FLOAT as default backward math type
-I0511 11:48:51.236423  4597 layer_factory.hpp:172] Creating layer 'data' of type 'AnnotatedData'
-I0511 11:48:51.236428  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.236750  4597 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:48:51.238076  4637 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0511 11:48:51.238101  4597 net.cpp:200] Created Layer data (0)
-I0511 11:48:51.238112  4597 net.cpp:542] data -> data
-I0511 11:48:51.238126  4597 net.cpp:542] data -> label
-I0511 11:48:51.238138  4597 data_reader.cpp:58] Data Reader threads: 1, out queues: 1, depth: 10
-I0511 11:48:51.238150  4597 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:48:51.319651  4638 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb
-I0511 11:48:51.321449  4597 annotated_data_layer.cpp:105] output data size: 10,3,256,512
-I0511 11:48:51.321525  4597 annotated_data_layer.cpp:150] (0) Output data size: 10, 3, 256, 512
-I0511 11:48:51.321573  4597 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:48:51.321605  4597 net.cpp:260] Setting up data
-I0511 11:48:51.322369  4643 data_layer.cpp:105] (0) Parser threads: 1
-I0511 11:48:51.322378  4643 data_layer.cpp:107] (0) Transformer threads: 1
-I0511 11:48:51.322372  4597 net.cpp:267] TEST Top shape for layer 0 'data' 10 3 256 512 (3932160)
-I0511 11:48:51.322409  4597 net.cpp:267] TEST Top shape for layer 0 'data' 1 1 2 8 (16)
-I0511 11:48:51.322435  4597 layer_factory.hpp:172] Creating layer 'data_data_0_split' of type 'Split'
-I0511 11:48:51.322450  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.322470  4597 net.cpp:200] Created Layer data_data_0_split (1)
-I0511 11:48:51.322485  4597 net.cpp:572] data_data_0_split <- data
-I0511 11:48:51.322504  4597 net.cpp:542] data_data_0_split -> data_data_0_split_0
-I0511 11:48:51.322520  4597 net.cpp:542] data_data_0_split -> data_data_0_split_1
-I0511 11:48:51.322532  4597 net.cpp:542] data_data_0_split -> data_data_0_split_2
-I0511 11:48:51.322547  4597 net.cpp:542] data_data_0_split -> data_data_0_split_3
-I0511 11:48:51.322561  4597 net.cpp:542] data_data_0_split -> data_data_0_split_4
-I0511 11:48:51.322572  4597 net.cpp:542] data_data_0_split -> data_data_0_split_5
-I0511 11:48:51.322645  4597 net.cpp:260] Setting up data_data_0_split
-I0511 11:48:51.322661  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322674  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322687  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322700  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322715  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322727  4597 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:48:51.322739  4597 layer_factory.hpp:172] Creating layer 'data/bias' of type 'Bias'
-I0511 11:48:51.322751  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.322769  4597 net.cpp:200] Created Layer data/bias (2)
-I0511 11:48:51.322782  4597 net.cpp:572] data/bias <- data_data_0_split_0
-I0511 11:48:51.322794  4597 net.cpp:542] data/bias -> data/bias
-I0511 11:48:51.323726  4597 net.cpp:260] Setting up data/bias
-I0511 11:48:51.323755  4597 net.cpp:267] TEST Top shape for layer 2 'data/bias' 10 3 256 512 (3932160)
-I0511 11:48:51.323776  4597 layer_factory.hpp:172] Creating layer 'conv1' of type 'Convolution'
-I0511 11:48:51.323792  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.323827  4597 net.cpp:200] Created Layer conv1 (3)
-I0511 11:48:51.323849  4597 net.cpp:572] conv1 <- data/bias
-I0511 11:48:51.323865  4597 net.cpp:542] conv1 -> conv1
-I0511 11:48:51.908941  4597 net.cpp:260] Setting up conv1
-I0511 11:48:51.908967  4597 net.cpp:267] TEST Top shape for layer 3 'conv1' 10 16 128 256 (5242880)
-I0511 11:48:51.908978  4597 layer_factory.hpp:172] Creating layer 'conv1/bn' of type 'BatchNorm'
-I0511 11:48:51.908983  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.908998  4597 net.cpp:200] Created Layer conv1/bn (4)
-I0511 11:48:51.909003  4597 net.cpp:572] conv1/bn <- conv1
-I0511 11:48:51.909006  4597 net.cpp:527] conv1/bn -> conv1 (in-place)
-I0511 11:48:51.909968  4597 net.cpp:260] Setting up conv1/bn
-I0511 11:48:51.909979  4597 net.cpp:267] TEST Top shape for layer 4 'conv1/bn' 10 16 128 256 (5242880)
-I0511 11:48:51.909987  4597 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Scale'
-I0511 11:48:51.909991  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.909998  4597 net.cpp:200] Created Layer conv1/scale (5)
-I0511 11:48:51.910001  4597 net.cpp:572] conv1/scale <- conv1
-I0511 11:48:51.910006  4597 net.cpp:527] conv1/scale -> conv1 (in-place)
-I0511 11:48:51.910037  4597 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Bias'
-I0511 11:48:51.910043  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.910143  4597 net.cpp:260] Setting up conv1/scale
-I0511 11:48:51.910148  4597 net.cpp:267] TEST Top shape for layer 5 'conv1/scale' 10 16 128 256 (5242880)
-I0511 11:48:51.910163  4597 layer_factory.hpp:172] Creating layer 'relu1' of type 'ReLU'
-I0511 11:48:51.910167  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.910171  4597 net.cpp:200] Created Layer relu1 (6)
-I0511 11:48:51.910173  4597 net.cpp:572] relu1 <- conv1
-I0511 11:48:51.910176  4597 net.cpp:527] relu1 -> conv1 (in-place)
-I0511 11:48:51.910190  4597 net.cpp:260] Setting up relu1
-I0511 11:48:51.910195  4597 net.cpp:267] TEST Top shape for layer 6 'relu1' 10 16 128 256 (5242880)
-I0511 11:48:51.910198  4597 layer_factory.hpp:172] Creating layer 'conv2_1/dw' of type 'Convolution'
-I0511 11:48:51.910202  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.910209  4597 net.cpp:200] Created Layer conv2_1/dw (7)
-I0511 11:48:51.910212  4597 net.cpp:572] conv2_1/dw <- conv1
-I0511 11:48:51.910215  4597 net.cpp:542] conv2_1/dw -> conv2_1/dw
-I0511 11:48:51.911314  4597 net.cpp:260] Setting up conv2_1/dw
-I0511 11:48:51.911322  4597 net.cpp:267] TEST Top shape for layer 7 'conv2_1/dw' 10 16 128 256 (5242880)
-I0511 11:48:51.911327  4597 layer_factory.hpp:172] Creating layer 'conv2_1/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.911330  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911335  4597 net.cpp:200] Created Layer conv2_1/dw/bn (8)
-I0511 11:48:51.911337  4597 net.cpp:572] conv2_1/dw/bn <- conv2_1/dw
-I0511 11:48:51.911340  4597 net.cpp:527] conv2_1/dw/bn -> conv2_1/dw (in-place)
-I0511 11:48:51.911597  4597 net.cpp:260] Setting up conv2_1/dw/bn
-I0511 11:48:51.911607  4597 net.cpp:267] TEST Top shape for layer 8 'conv2_1/dw/bn' 10 16 128 256 (5242880)
-I0511 11:48:51.911615  4597 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Scale'
-I0511 11:48:51.911619  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911624  4597 net.cpp:200] Created Layer conv2_1/dw/scale (9)
-I0511 11:48:51.911628  4597 net.cpp:572] conv2_1/dw/scale <- conv2_1/dw
-I0511 11:48:51.911631  4597 net.cpp:527] conv2_1/dw/scale -> conv2_1/dw (in-place)
-I0511 11:48:51.911661  4597 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Bias'
-I0511 11:48:51.911667  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911798  4597 net.cpp:260] Setting up conv2_1/dw/scale
-I0511 11:48:51.911806  4597 net.cpp:267] TEST Top shape for layer 9 'conv2_1/dw/scale' 10 16 128 256 (5242880)
-I0511 11:48:51.911813  4597 layer_factory.hpp:172] Creating layer 'relu2_1/dw' of type 'ReLU'
-I0511 11:48:51.911816  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911821  4597 net.cpp:200] Created Layer relu2_1/dw (10)
-I0511 11:48:51.911825  4597 net.cpp:572] relu2_1/dw <- conv2_1/dw
-I0511 11:48:51.911829  4597 net.cpp:527] relu2_1/dw -> conv2_1/dw (in-place)
-I0511 11:48:51.911835  4597 net.cpp:260] Setting up relu2_1/dw
-I0511 11:48:51.911841  4597 net.cpp:267] TEST Top shape for layer 10 'relu2_1/dw' 10 16 128 256 (5242880)
-I0511 11:48:51.911846  4597 layer_factory.hpp:172] Creating layer 'conv2_1/sep' of type 'Convolution'
-I0511 11:48:51.911850  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.911860  4597 net.cpp:200] Created Layer conv2_1/sep (11)
-I0511 11:48:51.911865  4597 net.cpp:572] conv2_1/sep <- conv2_1/dw
-I0511 11:48:51.911870  4597 net.cpp:542] conv2_1/sep -> conv2_1/sep
-I0511 11:48:51.912060  4597 net.cpp:260] Setting up conv2_1/sep
-I0511 11:48:51.912070  4597 net.cpp:267] TEST Top shape for layer 11 'conv2_1/sep' 10 32 128 256 (10485760)
-I0511 11:48:51.912076  4597 layer_factory.hpp:172] Creating layer 'conv2_1/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.912081  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912088  4597 net.cpp:200] Created Layer conv2_1/sep/bn (12)
-I0511 11:48:51.912103  4597 net.cpp:572] conv2_1/sep/bn <- conv2_1/sep
-I0511 11:48:51.912108  4597 net.cpp:527] conv2_1/sep/bn -> conv2_1/sep (in-place)
-I0511 11:48:51.912474  4597 net.cpp:260] Setting up conv2_1/sep/bn
-I0511 11:48:51.912482  4597 net.cpp:267] TEST Top shape for layer 12 'conv2_1/sep/bn' 10 32 128 256 (10485760)
-I0511 11:48:51.912493  4597 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Scale'
-I0511 11:48:51.912498  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912505  4597 net.cpp:200] Created Layer conv2_1/sep/scale (13)
-I0511 11:48:51.912510  4597 net.cpp:572] conv2_1/sep/scale <- conv2_1/sep
-I0511 11:48:51.912515  4597 net.cpp:527] conv2_1/sep/scale -> conv2_1/sep (in-place)
-I0511 11:48:51.912554  4597 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Bias'
-I0511 11:48:51.912559  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912694  4597 net.cpp:260] Setting up conv2_1/sep/scale
-I0511 11:48:51.912701  4597 net.cpp:267] TEST Top shape for layer 13 'conv2_1/sep/scale' 10 32 128 256 (10485760)
-I0511 11:48:51.912708  4597 layer_factory.hpp:172] Creating layer 'relu2_1/sep' of type 'ReLU'
-I0511 11:48:51.912714  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912719  4597 net.cpp:200] Created Layer relu2_1/sep (14)
-I0511 11:48:51.912722  4597 net.cpp:572] relu2_1/sep <- conv2_1/sep
-I0511 11:48:51.912727  4597 net.cpp:527] relu2_1/sep -> conv2_1/sep (in-place)
-I0511 11:48:51.912734  4597 net.cpp:260] Setting up relu2_1/sep
-I0511 11:48:51.912739  4597 net.cpp:267] TEST Top shape for layer 14 'relu2_1/sep' 10 32 128 256 (10485760)
-I0511 11:48:51.912744  4597 layer_factory.hpp:172] Creating layer 'conv2_2/dw' of type 'Convolution'
-I0511 11:48:51.912747  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912756  4597 net.cpp:200] Created Layer conv2_2/dw (15)
-I0511 11:48:51.912761  4597 net.cpp:572] conv2_2/dw <- conv2_1/sep
-I0511 11:48:51.912766  4597 net.cpp:542] conv2_2/dw -> conv2_2/dw
-I0511 11:48:51.912925  4597 net.cpp:260] Setting up conv2_2/dw
-I0511 11:48:51.912931  4597 net.cpp:267] TEST Top shape for layer 15 'conv2_2/dw' 10 32 64 128 (2621440)
-I0511 11:48:51.912936  4597 layer_factory.hpp:172] Creating layer 'conv2_2/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.912940  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.912945  4597 net.cpp:200] Created Layer conv2_2/dw/bn (16)
-I0511 11:48:51.912948  4597 net.cpp:572] conv2_2/dw/bn <- conv2_2/dw
-I0511 11:48:51.912950  4597 net.cpp:527] conv2_2/dw/bn -> conv2_2/dw (in-place)
-I0511 11:48:51.913966  4597 net.cpp:260] Setting up conv2_2/dw/bn
-I0511 11:48:51.913981  4597 net.cpp:267] TEST Top shape for layer 16 'conv2_2/dw/bn' 10 32 64 128 (2621440)
-I0511 11:48:51.913990  4597 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Scale'
-I0511 11:48:51.913993  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.914002  4597 net.cpp:200] Created Layer conv2_2/dw/scale (17)
-I0511 11:48:51.914006  4597 net.cpp:572] conv2_2/dw/scale <- conv2_2/dw
-I0511 11:48:51.914011  4597 net.cpp:527] conv2_2/dw/scale -> conv2_2/dw (in-place)
-I0511 11:48:51.914037  4597 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Bias'
-I0511 11:48:51.914041  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.914115  4597 net.cpp:260] Setting up conv2_2/dw/scale
-I0511 11:48:51.914120  4597 net.cpp:267] TEST Top shape for layer 17 'conv2_2/dw/scale' 10 32 64 128 (2621440)
-I0511 11:48:51.914125  4597 layer_factory.hpp:172] Creating layer 'relu2_2/dw' of type 'ReLU'
-I0511 11:48:51.914129  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.914132  4597 net.cpp:200] Created Layer relu2_2/dw (18)
-I0511 11:48:51.914149  4597 net.cpp:572] relu2_2/dw <- conv2_2/dw
-I0511 11:48:51.914152  4597 net.cpp:527] relu2_2/dw -> conv2_2/dw (in-place)
-I0511 11:48:51.914157  4597 net.cpp:260] Setting up relu2_2/dw
-I0511 11:48:51.914162  4597 net.cpp:267] TEST Top shape for layer 18 'relu2_2/dw' 10 32 64 128 (2621440)
-I0511 11:48:51.914166  4597 layer_factory.hpp:172] Creating layer 'conv2_2/sep' of type 'Convolution'
-I0511 11:48:51.914170  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.914180  4597 net.cpp:200] Created Layer conv2_2/sep (19)
-I0511 11:48:51.914191  4597 net.cpp:572] conv2_2/sep <- conv2_2/dw
-I0511 11:48:51.914196  4597 net.cpp:542] conv2_2/sep -> conv2_2/sep
-I0511 11:48:51.915102  4597 net.cpp:260] Setting up conv2_2/sep
-I0511 11:48:51.915114  4597 net.cpp:267] TEST Top shape for layer 19 'conv2_2/sep' 10 64 64 128 (5242880)
-I0511 11:48:51.915120  4597 layer_factory.hpp:172] Creating layer 'conv2_2/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.915127  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915134  4597 net.cpp:200] Created Layer conv2_2/sep/bn (20)
-I0511 11:48:51.915139  4597 net.cpp:572] conv2_2/sep/bn <- conv2_2/sep
-I0511 11:48:51.915143  4597 net.cpp:527] conv2_2/sep/bn -> conv2_2/sep (in-place)
-I0511 11:48:51.915386  4597 net.cpp:260] Setting up conv2_2/sep/bn
-I0511 11:48:51.915393  4597 net.cpp:267] TEST Top shape for layer 20 'conv2_2/sep/bn' 10 64 64 128 (5242880)
-I0511 11:48:51.915401  4597 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Scale'
-I0511 11:48:51.915406  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915412  4597 net.cpp:200] Created Layer conv2_2/sep/scale (21)
-I0511 11:48:51.915416  4597 net.cpp:572] conv2_2/sep/scale <- conv2_2/sep
-I0511 11:48:51.915421  4597 net.cpp:527] conv2_2/sep/scale -> conv2_2/sep (in-place)
-I0511 11:48:51.915449  4597 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Bias'
-I0511 11:48:51.915454  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915532  4597 net.cpp:260] Setting up conv2_2/sep/scale
-I0511 11:48:51.915539  4597 net.cpp:267] TEST Top shape for layer 21 'conv2_2/sep/scale' 10 64 64 128 (5242880)
-I0511 11:48:51.915545  4597 layer_factory.hpp:172] Creating layer 'relu2_2/sep' of type 'ReLU'
-I0511 11:48:51.915549  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915555  4597 net.cpp:200] Created Layer relu2_2/sep (22)
-I0511 11:48:51.915560  4597 net.cpp:572] relu2_2/sep <- conv2_2/sep
-I0511 11:48:51.915563  4597 net.cpp:527] relu2_2/sep -> conv2_2/sep (in-place)
-I0511 11:48:51.915570  4597 net.cpp:260] Setting up relu2_2/sep
-I0511 11:48:51.915575  4597 net.cpp:267] TEST Top shape for layer 22 'relu2_2/sep' 10 64 64 128 (5242880)
-I0511 11:48:51.915580  4597 layer_factory.hpp:172] Creating layer 'conv3_1/dw' of type 'Convolution'
-I0511 11:48:51.915585  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.915596  4597 net.cpp:200] Created Layer conv3_1/dw (23)
-I0511 11:48:51.915598  4597 net.cpp:572] conv3_1/dw <- conv2_2/sep
-I0511 11:48:51.915603  4597 net.cpp:542] conv3_1/dw -> conv3_1/dw
-I0511 11:48:51.916445  4597 net.cpp:260] Setting up conv3_1/dw
-I0511 11:48:51.916452  4597 net.cpp:267] TEST Top shape for layer 23 'conv3_1/dw' 10 64 64 128 (5242880)
-I0511 11:48:51.916460  4597 layer_factory.hpp:172] Creating layer 'conv3_1/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.916463  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916471  4597 net.cpp:200] Created Layer conv3_1/dw/bn (24)
-I0511 11:48:51.916474  4597 net.cpp:572] conv3_1/dw/bn <- conv3_1/dw
-I0511 11:48:51.916479  4597 net.cpp:527] conv3_1/dw/bn -> conv3_1/dw (in-place)
-I0511 11:48:51.916718  4597 net.cpp:260] Setting up conv3_1/dw/bn
-I0511 11:48:51.916731  4597 net.cpp:267] TEST Top shape for layer 24 'conv3_1/dw/bn' 10 64 64 128 (5242880)
-I0511 11:48:51.916745  4597 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Scale'
-I0511 11:48:51.916750  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916756  4597 net.cpp:200] Created Layer conv3_1/dw/scale (25)
-I0511 11:48:51.916761  4597 net.cpp:572] conv3_1/dw/scale <- conv3_1/dw
-I0511 11:48:51.916765  4597 net.cpp:527] conv3_1/dw/scale -> conv3_1/dw (in-place)
-I0511 11:48:51.916792  4597 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Bias'
-I0511 11:48:51.916797  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916874  4597 net.cpp:260] Setting up conv3_1/dw/scale
-I0511 11:48:51.916882  4597 net.cpp:267] TEST Top shape for layer 25 'conv3_1/dw/scale' 10 64 64 128 (5242880)
-I0511 11:48:51.916888  4597 layer_factory.hpp:172] Creating layer 'relu3_1/dw' of type 'ReLU'
-I0511 11:48:51.916893  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916898  4597 net.cpp:200] Created Layer relu3_1/dw (26)
-I0511 11:48:51.916901  4597 net.cpp:572] relu3_1/dw <- conv3_1/dw
-I0511 11:48:51.916906  4597 net.cpp:527] relu3_1/dw -> conv3_1/dw (in-place)
-I0511 11:48:51.916913  4597 net.cpp:260] Setting up relu3_1/dw
-I0511 11:48:51.916918  4597 net.cpp:267] TEST Top shape for layer 26 'relu3_1/dw' 10 64 64 128 (5242880)
-I0511 11:48:51.916923  4597 layer_factory.hpp:172] Creating layer 'conv3_1/sep' of type 'Convolution'
-I0511 11:48:51.916926  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.916937  4597 net.cpp:200] Created Layer conv3_1/sep (27)
-I0511 11:48:51.916941  4597 net.cpp:572] conv3_1/sep <- conv3_1/dw
-I0511 11:48:51.916945  4597 net.cpp:542] conv3_1/sep -> conv3_1/sep
-I0511 11:48:51.917141  4597 net.cpp:260] Setting up conv3_1/sep
-I0511 11:48:51.917148  4597 net.cpp:267] TEST Top shape for layer 27 'conv3_1/sep' 10 64 64 128 (5242880)
-I0511 11:48:51.917155  4597 layer_factory.hpp:172] Creating layer 'conv3_1/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.917160  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917165  4597 net.cpp:200] Created Layer conv3_1/sep/bn (28)
-I0511 11:48:51.917170  4597 net.cpp:572] conv3_1/sep/bn <- conv3_1/sep
-I0511 11:48:51.917174  4597 net.cpp:527] conv3_1/sep/bn -> conv3_1/sep (in-place)
-I0511 11:48:51.917400  4597 net.cpp:260] Setting up conv3_1/sep/bn
-I0511 11:48:51.917407  4597 net.cpp:267] TEST Top shape for layer 28 'conv3_1/sep/bn' 10 64 64 128 (5242880)
-I0511 11:48:51.917414  4597 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Scale'
-I0511 11:48:51.917418  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917425  4597 net.cpp:200] Created Layer conv3_1/sep/scale (29)
-I0511 11:48:51.917429  4597 net.cpp:572] conv3_1/sep/scale <- conv3_1/sep
-I0511 11:48:51.917433  4597 net.cpp:527] conv3_1/sep/scale -> conv3_1/sep (in-place)
-I0511 11:48:51.917460  4597 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Bias'
-I0511 11:48:51.917465  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917541  4597 net.cpp:260] Setting up conv3_1/sep/scale
-I0511 11:48:51.917547  4597 net.cpp:267] TEST Top shape for layer 29 'conv3_1/sep/scale' 10 64 64 128 (5242880)
-I0511 11:48:51.917554  4597 layer_factory.hpp:172] Creating layer 'relu3_1/sep' of type 'ReLU'
-I0511 11:48:51.917558  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917563  4597 net.cpp:200] Created Layer relu3_1/sep (30)
-I0511 11:48:51.917567  4597 net.cpp:572] relu3_1/sep <- conv3_1/sep
-I0511 11:48:51.917572  4597 net.cpp:527] relu3_1/sep -> conv3_1/sep (in-place)
-I0511 11:48:51.917583  4597 net.cpp:260] Setting up relu3_1/sep
-I0511 11:48:51.917589  4597 net.cpp:267] TEST Top shape for layer 30 'relu3_1/sep' 10 64 64 128 (5242880)
-I0511 11:48:51.917593  4597 layer_factory.hpp:172] Creating layer 'conv3_2/dw' of type 'Convolution'
-I0511 11:48:51.917598  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917606  4597 net.cpp:200] Created Layer conv3_2/dw (31)
-I0511 11:48:51.917610  4597 net.cpp:572] conv3_2/dw <- conv3_1/sep
-I0511 11:48:51.917614  4597 net.cpp:542] conv3_2/dw -> conv3_2/dw
-I0511 11:48:51.917747  4597 net.cpp:260] Setting up conv3_2/dw
-I0511 11:48:51.917753  4597 net.cpp:267] TEST Top shape for layer 31 'conv3_2/dw' 10 64 32 64 (1310720)
-I0511 11:48:51.917759  4597 layer_factory.hpp:172] Creating layer 'conv3_2/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.917764  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.917770  4597 net.cpp:200] Created Layer conv3_2/dw/bn (32)
-I0511 11:48:51.917774  4597 net.cpp:572] conv3_2/dw/bn <- conv3_2/dw
-I0511 11:48:51.917779  4597 net.cpp:527] conv3_2/dw/bn -> conv3_2/dw (in-place)
-I0511 11:48:51.918004  4597 net.cpp:260] Setting up conv3_2/dw/bn
-I0511 11:48:51.918011  4597 net.cpp:267] TEST Top shape for layer 32 'conv3_2/dw/bn' 10 64 32 64 (1310720)
-I0511 11:48:51.918018  4597 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Scale'
-I0511 11:48:51.918022  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918028  4597 net.cpp:200] Created Layer conv3_2/dw/scale (33)
-I0511 11:48:51.918033  4597 net.cpp:572] conv3_2/dw/scale <- conv3_2/dw
-I0511 11:48:51.918037  4597 net.cpp:527] conv3_2/dw/scale -> conv3_2/dw (in-place)
-I0511 11:48:51.918066  4597 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Bias'
-I0511 11:48:51.918071  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918138  4597 net.cpp:260] Setting up conv3_2/dw/scale
-I0511 11:48:51.918144  4597 net.cpp:267] TEST Top shape for layer 33 'conv3_2/dw/scale' 10 64 32 64 (1310720)
-I0511 11:48:51.918150  4597 layer_factory.hpp:172] Creating layer 'relu3_2/dw' of type 'ReLU'
-I0511 11:48:51.918155  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918160  4597 net.cpp:200] Created Layer relu3_2/dw (34)
-I0511 11:48:51.918164  4597 net.cpp:572] relu3_2/dw <- conv3_2/dw
-I0511 11:48:51.918169  4597 net.cpp:527] relu3_2/dw -> conv3_2/dw (in-place)
-I0511 11:48:51.918175  4597 net.cpp:260] Setting up relu3_2/dw
-I0511 11:48:51.918180  4597 net.cpp:267] TEST Top shape for layer 34 'relu3_2/dw' 10 64 32 64 (1310720)
-I0511 11:48:51.918184  4597 layer_factory.hpp:172] Creating layer 'conv3_2/sep' of type 'Convolution'
-I0511 11:48:51.918190  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918197  4597 net.cpp:200] Created Layer conv3_2/sep (35)
-I0511 11:48:51.918200  4597 net.cpp:572] conv3_2/sep <- conv3_2/dw
-I0511 11:48:51.918205  4597 net.cpp:542] conv3_2/sep -> conv3_2/sep
-I0511 11:48:51.918478  4597 net.cpp:260] Setting up conv3_2/sep
-I0511 11:48:51.918483  4597 net.cpp:267] TEST Top shape for layer 35 'conv3_2/sep' 10 128 32 64 (2621440)
-I0511 11:48:51.918490  4597 layer_factory.hpp:172] Creating layer 'conv3_2/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.918494  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918500  4597 net.cpp:200] Created Layer conv3_2/sep/bn (36)
-I0511 11:48:51.918505  4597 net.cpp:572] conv3_2/sep/bn <- conv3_2/sep
-I0511 11:48:51.918509  4597 net.cpp:527] conv3_2/sep/bn -> conv3_2/sep (in-place)
-I0511 11:48:51.918715  4597 net.cpp:260] Setting up conv3_2/sep/bn
-I0511 11:48:51.918721  4597 net.cpp:267] TEST Top shape for layer 36 'conv3_2/sep/bn' 10 128 32 64 (2621440)
-I0511 11:48:51.918728  4597 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Scale'
-I0511 11:48:51.918737  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918746  4597 net.cpp:200] Created Layer conv3_2/sep/scale (37)
-I0511 11:48:51.918751  4597 net.cpp:572] conv3_2/sep/scale <- conv3_2/sep
-I0511 11:48:51.918756  4597 net.cpp:527] conv3_2/sep/scale -> conv3_2/sep (in-place)
-I0511 11:48:51.918781  4597 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Bias'
-I0511 11:48:51.918787  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918850  4597 net.cpp:260] Setting up conv3_2/sep/scale
-I0511 11:48:51.918856  4597 net.cpp:267] TEST Top shape for layer 37 'conv3_2/sep/scale' 10 128 32 64 (2621440)
-I0511 11:48:51.918864  4597 layer_factory.hpp:172] Creating layer 'relu3_2/sep' of type 'ReLU'
-I0511 11:48:51.918867  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918874  4597 net.cpp:200] Created Layer relu3_2/sep (38)
-I0511 11:48:51.918877  4597 net.cpp:572] relu3_2/sep <- conv3_2/sep
-I0511 11:48:51.918882  4597 net.cpp:527] relu3_2/sep -> conv3_2/sep (in-place)
-I0511 11:48:51.918887  4597 net.cpp:260] Setting up relu3_2/sep
-I0511 11:48:51.918893  4597 net.cpp:267] TEST Top shape for layer 38 'relu3_2/sep' 10 128 32 64 (2621440)
-I0511 11:48:51.918897  4597 layer_factory.hpp:172] Creating layer 'conv4_1/dw' of type 'Convolution'
-I0511 11:48:51.918902  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.918910  4597 net.cpp:200] Created Layer conv4_1/dw (39)
-I0511 11:48:51.918913  4597 net.cpp:572] conv4_1/dw <- conv3_2/sep
-I0511 11:48:51.918918  4597 net.cpp:542] conv4_1/dw -> conv4_1/dw
-I0511 11:48:51.919057  4597 net.cpp:260] Setting up conv4_1/dw
-I0511 11:48:51.919064  4597 net.cpp:267] TEST Top shape for layer 39 'conv4_1/dw' 10 128 32 64 (2621440)
-I0511 11:48:51.919070  4597 layer_factory.hpp:172] Creating layer 'conv4_1/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.919075  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919081  4597 net.cpp:200] Created Layer conv4_1/dw/bn (40)
-I0511 11:48:51.919085  4597 net.cpp:572] conv4_1/dw/bn <- conv4_1/dw
-I0511 11:48:51.919090  4597 net.cpp:527] conv4_1/dw/bn -> conv4_1/dw (in-place)
-I0511 11:48:51.919296  4597 net.cpp:260] Setting up conv4_1/dw/bn
-I0511 11:48:51.919301  4597 net.cpp:267] TEST Top shape for layer 40 'conv4_1/dw/bn' 10 128 32 64 (2621440)
-I0511 11:48:51.919309  4597 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Scale'
-I0511 11:48:51.919313  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919318  4597 net.cpp:200] Created Layer conv4_1/dw/scale (41)
-I0511 11:48:51.919323  4597 net.cpp:572] conv4_1/dw/scale <- conv4_1/dw
-I0511 11:48:51.919327  4597 net.cpp:527] conv4_1/dw/scale -> conv4_1/dw (in-place)
-I0511 11:48:51.919354  4597 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Bias'
-I0511 11:48:51.919359  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919420  4597 net.cpp:260] Setting up conv4_1/dw/scale
-I0511 11:48:51.919425  4597 net.cpp:267] TEST Top shape for layer 41 'conv4_1/dw/scale' 10 128 32 64 (2621440)
-I0511 11:48:51.919432  4597 layer_factory.hpp:172] Creating layer 'relu4_1/dw' of type 'ReLU'
-I0511 11:48:51.919436  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919441  4597 net.cpp:200] Created Layer relu4_1/dw (42)
-I0511 11:48:51.919446  4597 net.cpp:572] relu4_1/dw <- conv4_1/dw
-I0511 11:48:51.919450  4597 net.cpp:527] relu4_1/dw -> conv4_1/dw (in-place)
-I0511 11:48:51.919456  4597 net.cpp:260] Setting up relu4_1/dw
-I0511 11:48:51.919461  4597 net.cpp:267] TEST Top shape for layer 42 'relu4_1/dw' 10 128 32 64 (2621440)
-I0511 11:48:51.919466  4597 layer_factory.hpp:172] Creating layer 'conv4_1/sep' of type 'Convolution'
-I0511 11:48:51.919474  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919483  4597 net.cpp:200] Created Layer conv4_1/sep (43)
-I0511 11:48:51.919486  4597 net.cpp:572] conv4_1/sep <- conv4_1/dw
-I0511 11:48:51.919492  4597 net.cpp:542] conv4_1/sep -> conv4_1/sep
-I0511 11:48:51.919926  4597 net.cpp:260] Setting up conv4_1/sep
-I0511 11:48:51.919934  4597 net.cpp:267] TEST Top shape for layer 43 'conv4_1/sep' 10 128 32 64 (2621440)
-I0511 11:48:51.919939  4597 layer_factory.hpp:172] Creating layer 'conv4_1/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.919944  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.919950  4597 net.cpp:200] Created Layer conv4_1/sep/bn (44)
-I0511 11:48:51.919955  4597 net.cpp:572] conv4_1/sep/bn <- conv4_1/sep
-I0511 11:48:51.919958  4597 net.cpp:527] conv4_1/sep/bn -> conv4_1/sep (in-place)
-I0511 11:48:51.920169  4597 net.cpp:260] Setting up conv4_1/sep/bn
-I0511 11:48:51.920176  4597 net.cpp:267] TEST Top shape for layer 44 'conv4_1/sep/bn' 10 128 32 64 (2621440)
-I0511 11:48:51.920186  4597 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Scale'
-I0511 11:48:51.920192  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920197  4597 net.cpp:200] Created Layer conv4_1/sep/scale (45)
-I0511 11:48:51.920202  4597 net.cpp:572] conv4_1/sep/scale <- conv4_1/sep
-I0511 11:48:51.920207  4597 net.cpp:527] conv4_1/sep/scale -> conv4_1/sep (in-place)
-I0511 11:48:51.920234  4597 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Bias'
-I0511 11:48:51.920239  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920303  4597 net.cpp:260] Setting up conv4_1/sep/scale
-I0511 11:48:51.920310  4597 net.cpp:267] TEST Top shape for layer 45 'conv4_1/sep/scale' 10 128 32 64 (2621440)
-I0511 11:48:51.920316  4597 layer_factory.hpp:172] Creating layer 'relu4_1/sep' of type 'ReLU'
-I0511 11:48:51.920320  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920325  4597 net.cpp:200] Created Layer relu4_1/sep (46)
-I0511 11:48:51.920331  4597 net.cpp:572] relu4_1/sep <- conv4_1/sep
-I0511 11:48:51.920334  4597 net.cpp:527] relu4_1/sep -> conv4_1/sep (in-place)
-I0511 11:48:51.920341  4597 net.cpp:260] Setting up relu4_1/sep
-I0511 11:48:51.920346  4597 net.cpp:267] TEST Top shape for layer 46 'relu4_1/sep' 10 128 32 64 (2621440)
-I0511 11:48:51.920351  4597 layer_factory.hpp:172] Creating layer 'conv4_2/dw' of type 'Convolution'
-I0511 11:48:51.920356  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920367  4597 net.cpp:200] Created Layer conv4_2/dw (47)
-I0511 11:48:51.920369  4597 net.cpp:572] conv4_2/dw <- conv4_1/sep
-I0511 11:48:51.920375  4597 net.cpp:542] conv4_2/dw -> conv4_2/dw
-I0511 11:48:51.920519  4597 net.cpp:260] Setting up conv4_2/dw
-I0511 11:48:51.920532  4597 net.cpp:267] TEST Top shape for layer 47 'conv4_2/dw' 10 128 16 32 (655360)
-I0511 11:48:51.920552  4597 layer_factory.hpp:172] Creating layer 'conv4_2/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.920557  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920562  4597 net.cpp:200] Created Layer conv4_2/dw/bn (48)
-I0511 11:48:51.920567  4597 net.cpp:572] conv4_2/dw/bn <- conv4_2/dw
-I0511 11:48:51.920572  4597 net.cpp:527] conv4_2/dw/bn -> conv4_2/dw (in-place)
-I0511 11:48:51.920794  4597 net.cpp:260] Setting up conv4_2/dw/bn
-I0511 11:48:51.920800  4597 net.cpp:267] TEST Top shape for layer 48 'conv4_2/dw/bn' 10 128 16 32 (655360)
-I0511 11:48:51.920809  4597 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Scale'
-I0511 11:48:51.920814  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920819  4597 net.cpp:200] Created Layer conv4_2/dw/scale (49)
-I0511 11:48:51.920831  4597 net.cpp:572] conv4_2/dw/scale <- conv4_2/dw
-I0511 11:48:51.920836  4597 net.cpp:527] conv4_2/dw/scale -> conv4_2/dw (in-place)
-I0511 11:48:51.920866  4597 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Bias'
-I0511 11:48:51.920871  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920940  4597 net.cpp:260] Setting up conv4_2/dw/scale
-I0511 11:48:51.920946  4597 net.cpp:267] TEST Top shape for layer 49 'conv4_2/dw/scale' 10 128 16 32 (655360)
-I0511 11:48:51.920953  4597 layer_factory.hpp:172] Creating layer 'relu4_2/dw' of type 'ReLU'
-I0511 11:48:51.920958  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.920964  4597 net.cpp:200] Created Layer relu4_2/dw (50)
-I0511 11:48:51.920969  4597 net.cpp:572] relu4_2/dw <- conv4_2/dw
-I0511 11:48:51.920974  4597 net.cpp:527] relu4_2/dw -> conv4_2/dw (in-place)
-I0511 11:48:51.920980  4597 net.cpp:260] Setting up relu4_2/dw
-I0511 11:48:51.920986  4597 net.cpp:267] TEST Top shape for layer 50 'relu4_2/dw' 10 128 16 32 (655360)
-I0511 11:48:51.920991  4597 layer_factory.hpp:172] Creating layer 'conv4_2/sep' of type 'Convolution'
-I0511 11:48:51.920996  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.921006  4597 net.cpp:200] Created Layer conv4_2/sep (51)
-I0511 11:48:51.921010  4597 net.cpp:572] conv4_2/sep <- conv4_2/dw
-I0511 11:48:51.921015  4597 net.cpp:542] conv4_2/sep -> conv4_2/sep
-I0511 11:48:51.921761  4597 net.cpp:260] Setting up conv4_2/sep
-I0511 11:48:51.921768  4597 net.cpp:267] TEST Top shape for layer 51 'conv4_2/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.921774  4597 layer_factory.hpp:172] Creating layer 'conv4_2/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.921779  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.921787  4597 net.cpp:200] Created Layer conv4_2/sep/bn (52)
-I0511 11:48:51.921792  4597 net.cpp:572] conv4_2/sep/bn <- conv4_2/sep
-I0511 11:48:51.921797  4597 net.cpp:527] conv4_2/sep/bn -> conv4_2/sep (in-place)
-I0511 11:48:51.922013  4597 net.cpp:260] Setting up conv4_2/sep/bn
-I0511 11:48:51.922019  4597 net.cpp:267] TEST Top shape for layer 52 'conv4_2/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.922026  4597 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Scale'
-I0511 11:48:51.922031  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922037  4597 net.cpp:200] Created Layer conv4_2/sep/scale (53)
-I0511 11:48:51.922042  4597 net.cpp:572] conv4_2/sep/scale <- conv4_2/sep
-I0511 11:48:51.922047  4597 net.cpp:527] conv4_2/sep/scale -> conv4_2/sep (in-place)
-I0511 11:48:51.922075  4597 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Bias'
-I0511 11:48:51.922080  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922147  4597 net.cpp:260] Setting up conv4_2/sep/scale
-I0511 11:48:51.922152  4597 net.cpp:267] TEST Top shape for layer 53 'conv4_2/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.922159  4597 layer_factory.hpp:172] Creating layer 'relu4_2/sep' of type 'ReLU'
-I0511 11:48:51.922164  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922170  4597 net.cpp:200] Created Layer relu4_2/sep (54)
-I0511 11:48:51.922175  4597 net.cpp:572] relu4_2/sep <- conv4_2/sep
-I0511 11:48:51.922180  4597 net.cpp:527] relu4_2/sep -> conv4_2/sep (in-place)
-I0511 11:48:51.922186  4597 net.cpp:260] Setting up relu4_2/sep
-I0511 11:48:51.922192  4597 net.cpp:267] TEST Top shape for layer 54 'relu4_2/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.922197  4597 layer_factory.hpp:172] Creating layer 'conv5_1/dw' of type 'Convolution'
-I0511 11:48:51.922202  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922216  4597 net.cpp:200] Created Layer conv5_1/dw (55)
-I0511 11:48:51.922225  4597 net.cpp:572] conv5_1/dw <- conv4_2/sep
-I0511 11:48:51.922230  4597 net.cpp:542] conv5_1/dw -> conv5_1/dw
-I0511 11:48:51.922397  4597 net.cpp:260] Setting up conv5_1/dw
-I0511 11:48:51.922405  4597 net.cpp:267] TEST Top shape for layer 55 'conv5_1/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.922410  4597 layer_factory.hpp:172] Creating layer 'conv5_1/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.922415  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922421  4597 net.cpp:200] Created Layer conv5_1/dw/bn (56)
-I0511 11:48:51.922426  4597 net.cpp:572] conv5_1/dw/bn <- conv5_1/dw
-I0511 11:48:51.922431  4597 net.cpp:527] conv5_1/dw/bn -> conv5_1/dw (in-place)
-I0511 11:48:51.922638  4597 net.cpp:260] Setting up conv5_1/dw/bn
-I0511 11:48:51.922644  4597 net.cpp:267] TEST Top shape for layer 56 'conv5_1/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.922652  4597 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Scale'
-I0511 11:48:51.922657  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922662  4597 net.cpp:200] Created Layer conv5_1/dw/scale (57)
-I0511 11:48:51.922667  4597 net.cpp:572] conv5_1/dw/scale <- conv5_1/dw
-I0511 11:48:51.922672  4597 net.cpp:527] conv5_1/dw/scale -> conv5_1/dw (in-place)
-I0511 11:48:51.922701  4597 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Bias'
-I0511 11:48:51.922705  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922770  4597 net.cpp:260] Setting up conv5_1/dw/scale
-I0511 11:48:51.922775  4597 net.cpp:267] TEST Top shape for layer 57 'conv5_1/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.922782  4597 layer_factory.hpp:172] Creating layer 'relu5_1/dw' of type 'ReLU'
-I0511 11:48:51.922786  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922792  4597 net.cpp:200] Created Layer relu5_1/dw (58)
-I0511 11:48:51.922796  4597 net.cpp:572] relu5_1/dw <- conv5_1/dw
-I0511 11:48:51.922801  4597 net.cpp:527] relu5_1/dw -> conv5_1/dw (in-place)
-I0511 11:48:51.922808  4597 net.cpp:260] Setting up relu5_1/dw
-I0511 11:48:51.922813  4597 net.cpp:267] TEST Top shape for layer 58 'relu5_1/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.922818  4597 layer_factory.hpp:172] Creating layer 'conv5_1/sep' of type 'Convolution'
-I0511 11:48:51.922823  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.922832  4597 net.cpp:200] Created Layer conv5_1/sep (59)
-I0511 11:48:51.922837  4597 net.cpp:572] conv5_1/sep <- conv5_1/dw
-I0511 11:48:51.922842  4597 net.cpp:542] conv5_1/sep -> conv5_1/sep
-I0511 11:48:51.924191  4597 net.cpp:260] Setting up conv5_1/sep
-I0511 11:48:51.924198  4597 net.cpp:267] TEST Top shape for layer 59 'conv5_1/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.924204  4597 layer_factory.hpp:172] Creating layer 'conv5_1/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.924209  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924216  4597 net.cpp:200] Created Layer conv5_1/sep/bn (60)
-I0511 11:48:51.924221  4597 net.cpp:572] conv5_1/sep/bn <- conv5_1/sep
-I0511 11:48:51.924226  4597 net.cpp:527] conv5_1/sep/bn -> conv5_1/sep (in-place)
-I0511 11:48:51.924439  4597 net.cpp:260] Setting up conv5_1/sep/bn
-I0511 11:48:51.924445  4597 net.cpp:267] TEST Top shape for layer 60 'conv5_1/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.924453  4597 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Scale'
-I0511 11:48:51.924458  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924468  4597 net.cpp:200] Created Layer conv5_1/sep/scale (61)
-I0511 11:48:51.924473  4597 net.cpp:572] conv5_1/sep/scale <- conv5_1/sep
-I0511 11:48:51.924476  4597 net.cpp:527] conv5_1/sep/scale -> conv5_1/sep (in-place)
-I0511 11:48:51.924505  4597 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Bias'
-I0511 11:48:51.924516  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924602  4597 net.cpp:260] Setting up conv5_1/sep/scale
-I0511 11:48:51.924609  4597 net.cpp:267] TEST Top shape for layer 61 'conv5_1/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.924615  4597 layer_factory.hpp:172] Creating layer 'relu5_1/sep' of type 'ReLU'
-I0511 11:48:51.924620  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924625  4597 net.cpp:200] Created Layer relu5_1/sep (62)
-I0511 11:48:51.924630  4597 net.cpp:572] relu5_1/sep <- conv5_1/sep
-I0511 11:48:51.924634  4597 net.cpp:527] relu5_1/sep -> conv5_1/sep (in-place)
-I0511 11:48:51.924641  4597 net.cpp:260] Setting up relu5_1/sep
-I0511 11:48:51.924648  4597 net.cpp:267] TEST Top shape for layer 62 'relu5_1/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.924652  4597 layer_factory.hpp:172] Creating layer 'conv5_2/dw' of type 'Convolution'
-I0511 11:48:51.924656  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924669  4597 net.cpp:200] Created Layer conv5_2/dw (63)
-I0511 11:48:51.924674  4597 net.cpp:572] conv5_2/dw <- conv5_1/sep
-I0511 11:48:51.924677  4597 net.cpp:542] conv5_2/dw -> conv5_2/dw
-I0511 11:48:51.924844  4597 net.cpp:260] Setting up conv5_2/dw
-I0511 11:48:51.924850  4597 net.cpp:267] TEST Top shape for layer 63 'conv5_2/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.924856  4597 layer_factory.hpp:172] Creating layer 'conv5_2/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.924861  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.924870  4597 net.cpp:200] Created Layer conv5_2/dw/bn (64)
-I0511 11:48:51.924875  4597 net.cpp:572] conv5_2/dw/bn <- conv5_2/dw
-I0511 11:48:51.924880  4597 net.cpp:527] conv5_2/dw/bn -> conv5_2/dw (in-place)
-I0511 11:48:51.925089  4597 net.cpp:260] Setting up conv5_2/dw/bn
-I0511 11:48:51.925096  4597 net.cpp:267] TEST Top shape for layer 64 'conv5_2/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.925103  4597 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Scale'
-I0511 11:48:51.925107  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.925113  4597 net.cpp:200] Created Layer conv5_2/dw/scale (65)
-I0511 11:48:51.925118  4597 net.cpp:572] conv5_2/dw/scale <- conv5_2/dw
-I0511 11:48:51.925123  4597 net.cpp:527] conv5_2/dw/scale -> conv5_2/dw (in-place)
-I0511 11:48:51.925153  4597 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Bias'
-I0511 11:48:51.925158  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.925225  4597 net.cpp:260] Setting up conv5_2/dw/scale
-I0511 11:48:51.925231  4597 net.cpp:267] TEST Top shape for layer 65 'conv5_2/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.925238  4597 layer_factory.hpp:172] Creating layer 'relu5_2/dw' of type 'ReLU'
-I0511 11:48:51.925242  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.925249  4597 net.cpp:200] Created Layer relu5_2/dw (66)
-I0511 11:48:51.925254  4597 net.cpp:572] relu5_2/dw <- conv5_2/dw
-I0511 11:48:51.925258  4597 net.cpp:527] relu5_2/dw -> conv5_2/dw (in-place)
-I0511 11:48:51.925266  4597 net.cpp:260] Setting up relu5_2/dw
-I0511 11:48:51.925271  4597 net.cpp:267] TEST Top shape for layer 66 'relu5_2/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.925277  4597 layer_factory.hpp:172] Creating layer 'conv5_2/sep' of type 'Convolution'
-I0511 11:48:51.925282  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.925292  4597 net.cpp:200] Created Layer conv5_2/sep (67)
-I0511 11:48:51.925297  4597 net.cpp:572] conv5_2/sep <- conv5_2/dw
-I0511 11:48:51.925302  4597 net.cpp:542] conv5_2/sep -> conv5_2/sep
-I0511 11:48:51.926657  4597 net.cpp:260] Setting up conv5_2/sep
-I0511 11:48:51.926679  4597 net.cpp:267] TEST Top shape for layer 67 'conv5_2/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.926686  4597 layer_factory.hpp:172] Creating layer 'conv5_2/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.926692  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.926698  4597 net.cpp:200] Created Layer conv5_2/sep/bn (68)
-I0511 11:48:51.926703  4597 net.cpp:572] conv5_2/sep/bn <- conv5_2/sep
-I0511 11:48:51.926708  4597 net.cpp:527] conv5_2/sep/bn -> conv5_2/sep (in-place)
-I0511 11:48:51.926934  4597 net.cpp:260] Setting up conv5_2/sep/bn
-I0511 11:48:51.926939  4597 net.cpp:267] TEST Top shape for layer 68 'conv5_2/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.926959  4597 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Scale'
-I0511 11:48:51.926965  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.926978  4597 net.cpp:200] Created Layer conv5_2/sep/scale (69)
-I0511 11:48:51.926982  4597 net.cpp:572] conv5_2/sep/scale <- conv5_2/sep
-I0511 11:48:51.926987  4597 net.cpp:527] conv5_2/sep/scale -> conv5_2/sep (in-place)
-I0511 11:48:51.927028  4597 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Bias'
-I0511 11:48:51.927033  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927104  4597 net.cpp:260] Setting up conv5_2/sep/scale
-I0511 11:48:51.927110  4597 net.cpp:267] TEST Top shape for layer 69 'conv5_2/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.927129  4597 layer_factory.hpp:172] Creating layer 'relu5_2/sep' of type 'ReLU'
-I0511 11:48:51.927134  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927139  4597 net.cpp:200] Created Layer relu5_2/sep (70)
-I0511 11:48:51.927145  4597 net.cpp:572] relu5_2/sep <- conv5_2/sep
-I0511 11:48:51.927155  4597 net.cpp:527] relu5_2/sep -> conv5_2/sep (in-place)
-I0511 11:48:51.927161  4597 net.cpp:260] Setting up relu5_2/sep
-I0511 11:48:51.927167  4597 net.cpp:267] TEST Top shape for layer 70 'relu5_2/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.927173  4597 layer_factory.hpp:172] Creating layer 'conv5_3/dw' of type 'Convolution'
-I0511 11:48:51.927183  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927196  4597 net.cpp:200] Created Layer conv5_3/dw (71)
-I0511 11:48:51.927199  4597 net.cpp:572] conv5_3/dw <- conv5_2/sep
-I0511 11:48:51.927204  4597 net.cpp:542] conv5_3/dw -> conv5_3/dw
-I0511 11:48:51.927382  4597 net.cpp:260] Setting up conv5_3/dw
-I0511 11:48:51.927389  4597 net.cpp:267] TEST Top shape for layer 71 'conv5_3/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.927397  4597 layer_factory.hpp:172] Creating layer 'conv5_3/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.927402  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927414  4597 net.cpp:200] Created Layer conv5_3/dw/bn (72)
-I0511 11:48:51.927418  4597 net.cpp:572] conv5_3/dw/bn <- conv5_3/dw
-I0511 11:48:51.927423  4597 net.cpp:527] conv5_3/dw/bn -> conv5_3/dw (in-place)
-I0511 11:48:51.927647  4597 net.cpp:260] Setting up conv5_3/dw/bn
-I0511 11:48:51.927654  4597 net.cpp:267] TEST Top shape for layer 72 'conv5_3/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.927669  4597 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Scale'
-I0511 11:48:51.927672  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927678  4597 net.cpp:200] Created Layer conv5_3/dw/scale (73)
-I0511 11:48:51.927683  4597 net.cpp:572] conv5_3/dw/scale <- conv5_3/dw
-I0511 11:48:51.927695  4597 net.cpp:527] conv5_3/dw/scale -> conv5_3/dw (in-place)
-I0511 11:48:51.927726  4597 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Bias'
-I0511 11:48:51.927731  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927804  4597 net.cpp:260] Setting up conv5_3/dw/scale
-I0511 11:48:51.927816  4597 net.cpp:267] TEST Top shape for layer 73 'conv5_3/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.927829  4597 layer_factory.hpp:172] Creating layer 'relu5_3/dw' of type 'ReLU'
-I0511 11:48:51.927834  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927839  4597 net.cpp:200] Created Layer relu5_3/dw (74)
-I0511 11:48:51.927845  4597 net.cpp:572] relu5_3/dw <- conv5_3/dw
-I0511 11:48:51.927850  4597 net.cpp:527] relu5_3/dw -> conv5_3/dw (in-place)
-I0511 11:48:51.927860  4597 net.cpp:260] Setting up relu5_3/dw
-I0511 11:48:51.927865  4597 net.cpp:267] TEST Top shape for layer 74 'relu5_3/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.927870  4597 layer_factory.hpp:172] Creating layer 'conv5_3/sep' of type 'Convolution'
-I0511 11:48:51.927873  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.927882  4597 net.cpp:200] Created Layer conv5_3/sep (75)
-I0511 11:48:51.927887  4597 net.cpp:572] conv5_3/sep <- conv5_3/dw
-I0511 11:48:51.927891  4597 net.cpp:542] conv5_3/sep -> conv5_3/sep
-I0511 11:48:51.929265  4597 net.cpp:260] Setting up conv5_3/sep
-I0511 11:48:51.929272  4597 net.cpp:267] TEST Top shape for layer 75 'conv5_3/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.929286  4597 layer_factory.hpp:172] Creating layer 'conv5_3/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.929291  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929297  4597 net.cpp:200] Created Layer conv5_3/sep/bn (76)
-I0511 11:48:51.929302  4597 net.cpp:572] conv5_3/sep/bn <- conv5_3/sep
-I0511 11:48:51.929312  4597 net.cpp:527] conv5_3/sep/bn -> conv5_3/sep (in-place)
-I0511 11:48:51.929533  4597 net.cpp:260] Setting up conv5_3/sep/bn
-I0511 11:48:51.929539  4597 net.cpp:267] TEST Top shape for layer 76 'conv5_3/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.929548  4597 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Scale'
-I0511 11:48:51.929553  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929558  4597 net.cpp:200] Created Layer conv5_3/sep/scale (77)
-I0511 11:48:51.929563  4597 net.cpp:572] conv5_3/sep/scale <- conv5_3/sep
-I0511 11:48:51.929569  4597 net.cpp:527] conv5_3/sep/scale -> conv5_3/sep (in-place)
-I0511 11:48:51.929597  4597 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Bias'
-I0511 11:48:51.929602  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929668  4597 net.cpp:260] Setting up conv5_3/sep/scale
-I0511 11:48:51.929674  4597 net.cpp:267] TEST Top shape for layer 77 'conv5_3/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.929682  4597 layer_factory.hpp:172] Creating layer 'relu5_3/sep' of type 'ReLU'
-I0511 11:48:51.929687  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929692  4597 net.cpp:200] Created Layer relu5_3/sep (78)
-I0511 11:48:51.929697  4597 net.cpp:572] relu5_3/sep <- conv5_3/sep
-I0511 11:48:51.929702  4597 net.cpp:527] relu5_3/sep -> conv5_3/sep (in-place)
-I0511 11:48:51.929708  4597 net.cpp:260] Setting up relu5_3/sep
-I0511 11:48:51.929713  4597 net.cpp:267] TEST Top shape for layer 78 'relu5_3/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.929718  4597 layer_factory.hpp:172] Creating layer 'conv5_4/dw' of type 'Convolution'
-I0511 11:48:51.929723  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929731  4597 net.cpp:200] Created Layer conv5_4/dw (79)
-I0511 11:48:51.929736  4597 net.cpp:572] conv5_4/dw <- conv5_3/sep
-I0511 11:48:51.929740  4597 net.cpp:542] conv5_4/dw -> conv5_4/dw
-I0511 11:48:51.929903  4597 net.cpp:260] Setting up conv5_4/dw
-I0511 11:48:51.929910  4597 net.cpp:267] TEST Top shape for layer 79 'conv5_4/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.929916  4597 layer_factory.hpp:172] Creating layer 'conv5_4/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.929926  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.929934  4597 net.cpp:200] Created Layer conv5_4/dw/bn (80)
-I0511 11:48:51.929939  4597 net.cpp:572] conv5_4/dw/bn <- conv5_4/dw
-I0511 11:48:51.929944  4597 net.cpp:527] conv5_4/dw/bn -> conv5_4/dw (in-place)
-I0511 11:48:51.930160  4597 net.cpp:260] Setting up conv5_4/dw/bn
-I0511 11:48:51.930166  4597 net.cpp:267] TEST Top shape for layer 80 'conv5_4/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.930174  4597 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Scale'
-I0511 11:48:51.930178  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.930184  4597 net.cpp:200] Created Layer conv5_4/dw/scale (81)
-I0511 11:48:51.930189  4597 net.cpp:572] conv5_4/dw/scale <- conv5_4/dw
-I0511 11:48:51.930194  4597 net.cpp:527] conv5_4/dw/scale -> conv5_4/dw (in-place)
-I0511 11:48:51.930224  4597 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Bias'
-I0511 11:48:51.930229  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.930294  4597 net.cpp:260] Setting up conv5_4/dw/scale
-I0511 11:48:51.930299  4597 net.cpp:267] TEST Top shape for layer 81 'conv5_4/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.930306  4597 layer_factory.hpp:172] Creating layer 'relu5_4/dw' of type 'ReLU'
-I0511 11:48:51.930311  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.930316  4597 net.cpp:200] Created Layer relu5_4/dw (82)
-I0511 11:48:51.930321  4597 net.cpp:572] relu5_4/dw <- conv5_4/dw
-I0511 11:48:51.930325  4597 net.cpp:527] relu5_4/dw -> conv5_4/dw (in-place)
-I0511 11:48:51.930332  4597 net.cpp:260] Setting up relu5_4/dw
-I0511 11:48:51.930337  4597 net.cpp:267] TEST Top shape for layer 82 'relu5_4/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.930342  4597 layer_factory.hpp:172] Creating layer 'conv5_4/sep' of type 'Convolution'
-I0511 11:48:51.930347  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.930356  4597 net.cpp:200] Created Layer conv5_4/sep (83)
-I0511 11:48:51.930361  4597 net.cpp:572] conv5_4/sep <- conv5_4/dw
-I0511 11:48:51.930366  4597 net.cpp:542] conv5_4/sep -> conv5_4/sep
-I0511 11:48:51.932469  4597 net.cpp:260] Setting up conv5_4/sep
-I0511 11:48:51.932483  4597 net.cpp:267] TEST Top shape for layer 83 'conv5_4/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.932492  4597 layer_factory.hpp:172] Creating layer 'conv5_4/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.932497  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932505  4597 net.cpp:200] Created Layer conv5_4/sep/bn (84)
-I0511 11:48:51.932512  4597 net.cpp:572] conv5_4/sep/bn <- conv5_4/sep
-I0511 11:48:51.932518  4597 net.cpp:527] conv5_4/sep/bn -> conv5_4/sep (in-place)
-I0511 11:48:51.932780  4597 net.cpp:260] Setting up conv5_4/sep/bn
-I0511 11:48:51.932786  4597 net.cpp:267] TEST Top shape for layer 84 'conv5_4/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.932795  4597 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Scale'
-I0511 11:48:51.932801  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932807  4597 net.cpp:200] Created Layer conv5_4/sep/scale (85)
-I0511 11:48:51.932812  4597 net.cpp:572] conv5_4/sep/scale <- conv5_4/sep
-I0511 11:48:51.932817  4597 net.cpp:527] conv5_4/sep/scale -> conv5_4/sep (in-place)
-I0511 11:48:51.932848  4597 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Bias'
-I0511 11:48:51.932853  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932924  4597 net.cpp:260] Setting up conv5_4/sep/scale
-I0511 11:48:51.932930  4597 net.cpp:267] TEST Top shape for layer 85 'conv5_4/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.932937  4597 layer_factory.hpp:172] Creating layer 'relu5_4/sep' of type 'ReLU'
-I0511 11:48:51.932948  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932955  4597 net.cpp:200] Created Layer relu5_4/sep (86)
-I0511 11:48:51.932960  4597 net.cpp:572] relu5_4/sep <- conv5_4/sep
-I0511 11:48:51.932965  4597 net.cpp:527] relu5_4/sep -> conv5_4/sep (in-place)
-I0511 11:48:51.932972  4597 net.cpp:260] Setting up relu5_4/sep
-I0511 11:48:51.932977  4597 net.cpp:267] TEST Top shape for layer 86 'relu5_4/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.932982  4597 layer_factory.hpp:172] Creating layer 'conv5_5/dw' of type 'Convolution'
-I0511 11:48:51.932987  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.932997  4597 net.cpp:200] Created Layer conv5_5/dw (87)
-I0511 11:48:51.933001  4597 net.cpp:572] conv5_5/dw <- conv5_4/sep
-I0511 11:48:51.933006  4597 net.cpp:542] conv5_5/dw -> conv5_5/dw
-I0511 11:48:51.933207  4597 net.cpp:260] Setting up conv5_5/dw
-I0511 11:48:51.933217  4597 net.cpp:267] TEST Top shape for layer 87 'conv5_5/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.933223  4597 layer_factory.hpp:172] Creating layer 'conv5_5/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.933228  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933235  4597 net.cpp:200] Created Layer conv5_5/dw/bn (88)
-I0511 11:48:51.933240  4597 net.cpp:572] conv5_5/dw/bn <- conv5_5/dw
-I0511 11:48:51.933245  4597 net.cpp:527] conv5_5/dw/bn -> conv5_5/dw (in-place)
-I0511 11:48:51.933557  4597 net.cpp:260] Setting up conv5_5/dw/bn
-I0511 11:48:51.933564  4597 net.cpp:267] TEST Top shape for layer 88 'conv5_5/dw/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.933581  4597 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Scale'
-I0511 11:48:51.933586  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933593  4597 net.cpp:200] Created Layer conv5_5/dw/scale (89)
-I0511 11:48:51.933598  4597 net.cpp:572] conv5_5/dw/scale <- conv5_5/dw
-I0511 11:48:51.933603  4597 net.cpp:527] conv5_5/dw/scale -> conv5_5/dw (in-place)
-I0511 11:48:51.933639  4597 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Bias'
-I0511 11:48:51.933645  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933737  4597 net.cpp:260] Setting up conv5_5/dw/scale
-I0511 11:48:51.933744  4597 net.cpp:267] TEST Top shape for layer 89 'conv5_5/dw/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.933751  4597 layer_factory.hpp:172] Creating layer 'relu5_5/dw' of type 'ReLU'
-I0511 11:48:51.933756  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933761  4597 net.cpp:200] Created Layer relu5_5/dw (90)
-I0511 11:48:51.933766  4597 net.cpp:572] relu5_5/dw <- conv5_5/dw
-I0511 11:48:51.933770  4597 net.cpp:527] relu5_5/dw -> conv5_5/dw (in-place)
-I0511 11:48:51.933776  4597 net.cpp:260] Setting up relu5_5/dw
-I0511 11:48:51.933782  4597 net.cpp:267] TEST Top shape for layer 90 'relu5_5/dw' 10 256 16 32 (1310720)
-I0511 11:48:51.933786  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep' of type 'Convolution'
-I0511 11:48:51.933791  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.933801  4597 net.cpp:200] Created Layer conv5_5/sep (91)
-I0511 11:48:51.933805  4597 net.cpp:572] conv5_5/sep <- conv5_5/dw
-I0511 11:48:51.933811  4597 net.cpp:542] conv5_5/sep -> conv5_5/sep
-I0511 11:48:51.935364  4597 net.cpp:260] Setting up conv5_5/sep
-I0511 11:48:51.935371  4597 net.cpp:267] TEST Top shape for layer 91 'conv5_5/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.935379  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.935385  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935391  4597 net.cpp:200] Created Layer conv5_5/sep/bn (92)
-I0511 11:48:51.935402  4597 net.cpp:572] conv5_5/sep/bn <- conv5_5/sep
-I0511 11:48:51.935408  4597 net.cpp:527] conv5_5/sep/bn -> conv5_5/sep (in-place)
-I0511 11:48:51.935642  4597 net.cpp:260] Setting up conv5_5/sep/bn
-I0511 11:48:51.935647  4597 net.cpp:267] TEST Top shape for layer 92 'conv5_5/sep/bn' 10 256 16 32 (1310720)
-I0511 11:48:51.935655  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Scale'
-I0511 11:48:51.935660  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935667  4597 net.cpp:200] Created Layer conv5_5/sep/scale (93)
-I0511 11:48:51.935672  4597 net.cpp:572] conv5_5/sep/scale <- conv5_5/sep
-I0511 11:48:51.935678  4597 net.cpp:527] conv5_5/sep/scale -> conv5_5/sep (in-place)
-I0511 11:48:51.935708  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Bias'
-I0511 11:48:51.935711  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935781  4597 net.cpp:260] Setting up conv5_5/sep/scale
-I0511 11:48:51.935786  4597 net.cpp:267] TEST Top shape for layer 93 'conv5_5/sep/scale' 10 256 16 32 (1310720)
-I0511 11:48:51.935792  4597 layer_factory.hpp:172] Creating layer 'relu5_5/sep' of type 'ReLU'
-I0511 11:48:51.935797  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935803  4597 net.cpp:200] Created Layer relu5_5/sep (94)
-I0511 11:48:51.935808  4597 net.cpp:572] relu5_5/sep <- conv5_5/sep
-I0511 11:48:51.935813  4597 net.cpp:527] relu5_5/sep -> conv5_5/sep (in-place)
-I0511 11:48:51.935819  4597 net.cpp:260] Setting up relu5_5/sep
-I0511 11:48:51.935825  4597 net.cpp:267] TEST Top shape for layer 94 'relu5_5/sep' 10 256 16 32 (1310720)
-I0511 11:48:51.935830  4597 layer_factory.hpp:172] Creating layer 'conv5_5/sep_relu5_5/sep_0_split' of type 'Split'
-I0511 11:48:51.935835  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935842  4597 net.cpp:200] Created Layer conv5_5/sep_relu5_5/sep_0_split (95)
-I0511 11:48:51.935847  4597 net.cpp:572] conv5_5/sep_relu5_5/sep_0_split <- conv5_5/sep
-I0511 11:48:51.935851  4597 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_0
-I0511 11:48:51.935859  4597 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_1
-I0511 11:48:51.935889  4597 net.cpp:260] Setting up conv5_5/sep_relu5_5/sep_0_split
-I0511 11:48:51.935894  4597 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 10 256 16 32 (1310720)
-I0511 11:48:51.935900  4597 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 10 256 16 32 (1310720)
-I0511 11:48:51.935905  4597 layer_factory.hpp:172] Creating layer 'conv5_6/dw' of type 'Convolution'
-I0511 11:48:51.935910  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.935925  4597 net.cpp:200] Created Layer conv5_6/dw (96)
-I0511 11:48:51.935930  4597 net.cpp:572] conv5_6/dw <- conv5_5/sep_relu5_5/sep_0_split_0
-I0511 11:48:51.935935  4597 net.cpp:542] conv5_6/dw -> conv5_6/dw
-I0511 11:48:51.940685  4597 net.cpp:260] Setting up conv5_6/dw
-I0511 11:48:51.940699  4597 net.cpp:267] TEST Top shape for layer 96 'conv5_6/dw' 10 256 8 16 (327680)
-I0511 11:48:51.940706  4597 layer_factory.hpp:172] Creating layer 'conv5_6/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.940711  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.940719  4597 net.cpp:200] Created Layer conv5_6/dw/bn (97)
-I0511 11:48:51.940726  4597 net.cpp:572] conv5_6/dw/bn <- conv5_6/dw
-I0511 11:48:51.940731  4597 net.cpp:527] conv5_6/dw/bn -> conv5_6/dw (in-place)
-I0511 11:48:51.940969  4597 net.cpp:260] Setting up conv5_6/dw/bn
-I0511 11:48:51.940975  4597 net.cpp:267] TEST Top shape for layer 97 'conv5_6/dw/bn' 10 256 8 16 (327680)
-I0511 11:48:51.940984  4597 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Scale'
-I0511 11:48:51.940995  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.941002  4597 net.cpp:200] Created Layer conv5_6/dw/scale (98)
-I0511 11:48:51.941007  4597 net.cpp:572] conv5_6/dw/scale <- conv5_6/dw
-I0511 11:48:51.941012  4597 net.cpp:527] conv5_6/dw/scale -> conv5_6/dw (in-place)
-I0511 11:48:51.941043  4597 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Bias'
-I0511 11:48:51.941047  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.941123  4597 net.cpp:260] Setting up conv5_6/dw/scale
-I0511 11:48:51.941128  4597 net.cpp:267] TEST Top shape for layer 98 'conv5_6/dw/scale' 10 256 8 16 (327680)
-I0511 11:48:51.941135  4597 layer_factory.hpp:172] Creating layer 'relu5_6/dw' of type 'ReLU'
-I0511 11:48:51.941140  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.941145  4597 net.cpp:200] Created Layer relu5_6/dw (99)
-I0511 11:48:51.941150  4597 net.cpp:572] relu5_6/dw <- conv5_6/dw
-I0511 11:48:51.941155  4597 net.cpp:527] relu5_6/dw -> conv5_6/dw (in-place)
-I0511 11:48:51.941162  4597 net.cpp:260] Setting up relu5_6/dw
-I0511 11:48:51.941169  4597 net.cpp:267] TEST Top shape for layer 99 'relu5_6/dw' 10 256 8 16 (327680)
-I0511 11:48:51.941174  4597 layer_factory.hpp:172] Creating layer 'conv5_6/sep' of type 'Convolution'
-I0511 11:48:51.941177  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.941192  4597 net.cpp:200] Created Layer conv5_6/sep (100)
-I0511 11:48:51.941196  4597 net.cpp:572] conv5_6/sep <- conv5_6/dw
-I0511 11:48:51.941200  4597 net.cpp:542] conv5_6/sep -> conv5_6/sep
-I0511 11:48:51.943786  4597 net.cpp:260] Setting up conv5_6/sep
-I0511 11:48:51.943795  4597 net.cpp:267] TEST Top shape for layer 100 'conv5_6/sep' 10 512 8 16 (655360)
-I0511 11:48:51.943801  4597 layer_factory.hpp:172] Creating layer 'conv5_6/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.943806  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.943814  4597 net.cpp:200] Created Layer conv5_6/sep/bn (101)
-I0511 11:48:51.943819  4597 net.cpp:572] conv5_6/sep/bn <- conv5_6/sep
-I0511 11:48:51.943825  4597 net.cpp:527] conv5_6/sep/bn -> conv5_6/sep (in-place)
-I0511 11:48:51.944082  4597 net.cpp:260] Setting up conv5_6/sep/bn
-I0511 11:48:51.944088  4597 net.cpp:267] TEST Top shape for layer 101 'conv5_6/sep/bn' 10 512 8 16 (655360)
-I0511 11:48:51.944095  4597 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Scale'
-I0511 11:48:51.944102  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944108  4597 net.cpp:200] Created Layer conv5_6/sep/scale (102)
-I0511 11:48:51.944113  4597 net.cpp:572] conv5_6/sep/scale <- conv5_6/sep
-I0511 11:48:51.944119  4597 net.cpp:527] conv5_6/sep/scale -> conv5_6/sep (in-place)
-I0511 11:48:51.944154  4597 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Bias'
-I0511 11:48:51.944159  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944239  4597 net.cpp:260] Setting up conv5_6/sep/scale
-I0511 11:48:51.944245  4597 net.cpp:267] TEST Top shape for layer 102 'conv5_6/sep/scale' 10 512 8 16 (655360)
-I0511 11:48:51.944252  4597 layer_factory.hpp:172] Creating layer 'relu5_6/sep' of type 'ReLU'
-I0511 11:48:51.944258  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944263  4597 net.cpp:200] Created Layer relu5_6/sep (103)
-I0511 11:48:51.944268  4597 net.cpp:572] relu5_6/sep <- conv5_6/sep
-I0511 11:48:51.944273  4597 net.cpp:527] relu5_6/sep -> conv5_6/sep (in-place)
-I0511 11:48:51.944279  4597 net.cpp:260] Setting up relu5_6/sep
-I0511 11:48:51.944285  4597 net.cpp:267] TEST Top shape for layer 103 'relu5_6/sep' 10 512 8 16 (655360)
-I0511 11:48:51.944290  4597 layer_factory.hpp:172] Creating layer 'conv6/dw' of type 'Convolution'
-I0511 11:48:51.944303  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944311  4597 net.cpp:200] Created Layer conv6/dw (104)
-I0511 11:48:51.944315  4597 net.cpp:572] conv6/dw <- conv5_6/sep
-I0511 11:48:51.944320  4597 net.cpp:542] conv6/dw -> conv6/dw
-I0511 11:48:51.944545  4597 net.cpp:260] Setting up conv6/dw
-I0511 11:48:51.944552  4597 net.cpp:267] TEST Top shape for layer 104 'conv6/dw' 10 512 8 16 (655360)
-I0511 11:48:51.944559  4597 layer_factory.hpp:172] Creating layer 'conv6/dw/bn' of type 'BatchNorm'
-I0511 11:48:51.944564  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944571  4597 net.cpp:200] Created Layer conv6/dw/bn (105)
-I0511 11:48:51.944576  4597 net.cpp:572] conv6/dw/bn <- conv6/dw
-I0511 11:48:51.944581  4597 net.cpp:527] conv6/dw/bn -> conv6/dw (in-place)
-I0511 11:48:51.944815  4597 net.cpp:260] Setting up conv6/dw/bn
-I0511 11:48:51.944821  4597 net.cpp:267] TEST Top shape for layer 105 'conv6/dw/bn' 10 512 8 16 (655360)
-I0511 11:48:51.944829  4597 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Scale'
-I0511 11:48:51.944834  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944849  4597 net.cpp:200] Created Layer conv6/dw/scale (106)
-I0511 11:48:51.944852  4597 net.cpp:572] conv6/dw/scale <- conv6/dw
-I0511 11:48:51.944856  4597 net.cpp:527] conv6/dw/scale -> conv6/dw (in-place)
-I0511 11:48:51.944886  4597 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Bias'
-I0511 11:48:51.944891  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944967  4597 net.cpp:260] Setting up conv6/dw/scale
-I0511 11:48:51.944973  4597 net.cpp:267] TEST Top shape for layer 106 'conv6/dw/scale' 10 512 8 16 (655360)
-I0511 11:48:51.944979  4597 layer_factory.hpp:172] Creating layer 'relu6/dw' of type 'ReLU'
-I0511 11:48:51.944984  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.944990  4597 net.cpp:200] Created Layer relu6/dw (107)
-I0511 11:48:51.944995  4597 net.cpp:572] relu6/dw <- conv6/dw
-I0511 11:48:51.945000  4597 net.cpp:527] relu6/dw -> conv6/dw (in-place)
-I0511 11:48:51.945008  4597 net.cpp:260] Setting up relu6/dw
-I0511 11:48:51.945013  4597 net.cpp:267] TEST Top shape for layer 107 'relu6/dw' 10 512 8 16 (655360)
-I0511 11:48:51.945017  4597 layer_factory.hpp:172] Creating layer 'conv6/sep' of type 'Convolution'
-I0511 11:48:51.945022  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.945031  4597 net.cpp:200] Created Layer conv6/sep (108)
-I0511 11:48:51.945035  4597 net.cpp:572] conv6/sep <- conv6/dw
-I0511 11:48:51.945040  4597 net.cpp:542] conv6/sep -> conv6/sep
-I0511 11:48:51.950122  4597 net.cpp:260] Setting up conv6/sep
-I0511 11:48:51.950141  4597 net.cpp:267] TEST Top shape for layer 108 'conv6/sep' 10 512 8 16 (655360)
-I0511 11:48:51.950148  4597 layer_factory.hpp:172] Creating layer 'conv6/sep/bn' of type 'BatchNorm'
-I0511 11:48:51.950155  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950165  4597 net.cpp:200] Created Layer conv6/sep/bn (109)
-I0511 11:48:51.950170  4597 net.cpp:572] conv6/sep/bn <- conv6/sep
-I0511 11:48:51.950176  4597 net.cpp:527] conv6/sep/bn -> conv6/sep (in-place)
-I0511 11:48:51.950459  4597 net.cpp:260] Setting up conv6/sep/bn
-I0511 11:48:51.950464  4597 net.cpp:267] TEST Top shape for layer 109 'conv6/sep/bn' 10 512 8 16 (655360)
-I0511 11:48:51.950474  4597 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Scale'
-I0511 11:48:51.950477  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950484  4597 net.cpp:200] Created Layer conv6/sep/scale (110)
-I0511 11:48:51.950489  4597 net.cpp:572] conv6/sep/scale <- conv6/sep
-I0511 11:48:51.950495  4597 net.cpp:527] conv6/sep/scale -> conv6/sep (in-place)
-I0511 11:48:51.950534  4597 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Bias'
-I0511 11:48:51.950539  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950619  4597 net.cpp:260] Setting up conv6/sep/scale
-I0511 11:48:51.950626  4597 net.cpp:267] TEST Top shape for layer 110 'conv6/sep/scale' 10 512 8 16 (655360)
-I0511 11:48:51.950633  4597 layer_factory.hpp:172] Creating layer 'relu6/sep' of type 'ReLU'
-I0511 11:48:51.950637  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950644  4597 net.cpp:200] Created Layer relu6/sep (111)
-I0511 11:48:51.950647  4597 net.cpp:572] relu6/sep <- conv6/sep
-I0511 11:48:51.950652  4597 net.cpp:527] relu6/sep -> conv6/sep (in-place)
-I0511 11:48:51.950660  4597 net.cpp:260] Setting up relu6/sep
-I0511 11:48:51.950666  4597 net.cpp:267] TEST Top shape for layer 111 'relu6/sep' 10 512 8 16 (655360)
-I0511 11:48:51.950671  4597 layer_factory.hpp:172] Creating layer 'conv6/sep_relu6/sep_0_split' of type 'Split'
-I0511 11:48:51.950676  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950683  4597 net.cpp:200] Created Layer conv6/sep_relu6/sep_0_split (112)
-I0511 11:48:51.950688  4597 net.cpp:572] conv6/sep_relu6/sep_0_split <- conv6/sep
-I0511 11:48:51.950693  4597 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_0
-I0511 11:48:51.950700  4597 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_1
-I0511 11:48:51.950736  4597 net.cpp:260] Setting up conv6/sep_relu6/sep_0_split
-I0511 11:48:51.950742  4597 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.950747  4597 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.950752  4597 layer_factory.hpp:172] Creating layer 'pool6' of type 'Pooling'
-I0511 11:48:51.950757  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950768  4597 net.cpp:200] Created Layer pool6 (113)
-I0511 11:48:51.950773  4597 net.cpp:572] pool6 <- conv6/sep_relu6/sep_0_split_0
-I0511 11:48:51.950778  4597 net.cpp:542] pool6 -> pool6
-I0511 11:48:51.950829  4597 net.cpp:260] Setting up pool6
-I0511 11:48:51.950834  4597 net.cpp:267] TEST Top shape for layer 113 'pool6' 10 512 5 9 (230400)
-I0511 11:48:51.950839  4597 layer_factory.hpp:172] Creating layer 'pool6_pool6_0_split' of type 'Split'
-I0511 11:48:51.950844  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950850  4597 net.cpp:200] Created Layer pool6_pool6_0_split (114)
-I0511 11:48:51.950855  4597 net.cpp:572] pool6_pool6_0_split <- pool6
-I0511 11:48:51.950860  4597 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_0
-I0511 11:48:51.950866  4597 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_1
-I0511 11:48:51.950892  4597 net.cpp:260] Setting up pool6_pool6_0_split
-I0511 11:48:51.950898  4597 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.950903  4597 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.950908  4597 layer_factory.hpp:172] Creating layer 'pool7' of type 'Pooling'
-I0511 11:48:51.950913  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950919  4597 net.cpp:200] Created Layer pool7 (115)
-I0511 11:48:51.950925  4597 net.cpp:572] pool7 <- pool6_pool6_0_split_0
-I0511 11:48:51.950930  4597 net.cpp:542] pool7 -> pool7
-I0511 11:48:51.950965  4597 net.cpp:260] Setting up pool7
-I0511 11:48:51.950970  4597 net.cpp:267] TEST Top shape for layer 115 'pool7' 10 512 3 5 (76800)
-I0511 11:48:51.950975  4597 layer_factory.hpp:172] Creating layer 'pool7_pool7_0_split' of type 'Split'
-I0511 11:48:51.950980  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.950991  4597 net.cpp:200] Created Layer pool7_pool7_0_split (116)
-I0511 11:48:51.950996  4597 net.cpp:572] pool7_pool7_0_split <- pool7
-I0511 11:48:51.951001  4597 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_0
-I0511 11:48:51.951007  4597 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_1
-I0511 11:48:51.951033  4597 net.cpp:260] Setting up pool7_pool7_0_split
-I0511 11:48:51.951038  4597 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.951045  4597 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.951050  4597 layer_factory.hpp:172] Creating layer 'pool8' of type 'Pooling'
-I0511 11:48:51.951055  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.951061  4597 net.cpp:200] Created Layer pool8 (117)
-I0511 11:48:51.951066  4597 net.cpp:572] pool8 <- pool7_pool7_0_split_0
-I0511 11:48:51.951071  4597 net.cpp:542] pool8 -> pool8
-I0511 11:48:51.951110  4597 net.cpp:260] Setting up pool8
-I0511 11:48:51.951122  4597 net.cpp:267] TEST Top shape for layer 117 'pool8' 10 512 3 5 (76800)
-I0511 11:48:51.951126  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1' of type 'Convolution'
-I0511 11:48:51.951131  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.951143  4597 net.cpp:200] Created Layer ctx_output1/1x1 (118)
-I0511 11:48:51.951148  4597 net.cpp:572] ctx_output1/1x1 <- conv5_5/sep_relu5_5/sep_0_split_1
-I0511 11:48:51.951153  4597 net.cpp:542] ctx_output1/1x1 -> ctx_output1/1x1
-I0511 11:48:51.955041  4597 net.cpp:260] Setting up ctx_output1/1x1
-I0511 11:48:51.955075  4597 net.cpp:267] TEST Top shape for layer 118 'ctx_output1/1x1' 10 512 16 32 (2621440)
-I0511 11:48:51.955086  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.955096  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.955118  4597 net.cpp:200] Created Layer ctx_output1/1x1/bn (119)
-I0511 11:48:51.955126  4597 net.cpp:572] ctx_output1/1x1/bn <- ctx_output1/1x1
-I0511 11:48:51.955133  4597 net.cpp:527] ctx_output1/1x1/bn -> ctx_output1/1x1 (in-place)
-I0511 11:48:51.955387  4597 net.cpp:260] Setting up ctx_output1/1x1/bn
-I0511 11:48:51.955394  4597 net.cpp:267] TEST Top shape for layer 119 'ctx_output1/1x1/bn' 10 512 16 32 (2621440)
-I0511 11:48:51.955404  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/relu' of type 'ReLU'
-I0511 11:48:51.955409  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.955415  4597 net.cpp:200] Created Layer ctx_output1/1x1/relu (120)
-I0511 11:48:51.955420  4597 net.cpp:572] ctx_output1/1x1/relu <- ctx_output1/1x1
-I0511 11:48:51.955425  4597 net.cpp:527] ctx_output1/1x1/relu -> ctx_output1/1x1 (in-place)
-I0511 11:48:51.955432  4597 net.cpp:260] Setting up ctx_output1/1x1/relu
-I0511 11:48:51.955438  4597 net.cpp:267] TEST Top shape for layer 120 'ctx_output1/1x1/relu' 10 512 16 32 (2621440)
-I0511 11:48:51.955442  4597 layer_factory.hpp:172] Creating layer 'ctx_output1' of type 'Convolution'
-I0511 11:48:51.955447  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.955459  4597 net.cpp:200] Created Layer ctx_output1 (121)
-I0511 11:48:51.955463  4597 net.cpp:572] ctx_output1 <- ctx_output1/1x1
-I0511 11:48:51.955468  4597 net.cpp:542] ctx_output1 -> ctx_output1
-I0511 11:48:51.955727  4597 net.cpp:260] Setting up ctx_output1
-I0511 11:48:51.955734  4597 net.cpp:267] TEST Top shape for layer 121 'ctx_output1' 10 512 16 32 (2621440)
-I0511 11:48:51.955741  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/bn' of type 'BatchNorm'
-I0511 11:48:51.955746  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.955754  4597 net.cpp:200] Created Layer ctx_output1/bn (122)
-I0511 11:48:51.955757  4597 net.cpp:572] ctx_output1/bn <- ctx_output1
-I0511 11:48:51.955773  4597 net.cpp:527] ctx_output1/bn -> ctx_output1 (in-place)
-I0511 11:48:51.956012  4597 net.cpp:260] Setting up ctx_output1/bn
-I0511 11:48:51.956018  4597 net.cpp:267] TEST Top shape for layer 122 'ctx_output1/bn' 10 512 16 32 (2621440)
-I0511 11:48:51.956028  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu' of type 'ReLU'
-I0511 11:48:51.956032  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.956037  4597 net.cpp:200] Created Layer ctx_output1/relu (123)
-I0511 11:48:51.956043  4597 net.cpp:572] ctx_output1/relu <- ctx_output1
-I0511 11:48:51.956048  4597 net.cpp:527] ctx_output1/relu -> ctx_output1 (in-place)
-I0511 11:48:51.956053  4597 net.cpp:260] Setting up ctx_output1/relu
-I0511 11:48:51.956059  4597 net.cpp:267] TEST Top shape for layer 123 'ctx_output1/relu' 10 512 16 32 (2621440)
-I0511 11:48:51.956064  4597 layer_factory.hpp:172] Creating layer 'ctx_output1_ctx_output1/relu_0_split' of type 'Split'
-I0511 11:48:51.956069  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.956075  4597 net.cpp:200] Created Layer ctx_output1_ctx_output1/relu_0_split (124)
-I0511 11:48:51.956080  4597 net.cpp:572] ctx_output1_ctx_output1/relu_0_split <- ctx_output1
-I0511 11:48:51.956085  4597 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_0
-I0511 11:48:51.956092  4597 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_1
-I0511 11:48:51.956099  4597 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_2
-I0511 11:48:51.956133  4597 net.cpp:260] Setting up ctx_output1_ctx_output1/relu_0_split
-I0511 11:48:51.956140  4597 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:48:51.956145  4597 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:48:51.956151  4597 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:48:51.956156  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1' of type 'Convolution'
-I0511 11:48:51.956161  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.956173  4597 net.cpp:200] Created Layer ctx_output2/1x1 (125)
-I0511 11:48:51.956177  4597 net.cpp:572] ctx_output2/1x1 <- conv6/sep_relu6/sep_0_split_1
-I0511 11:48:51.956183  4597 net.cpp:542] ctx_output2/1x1 -> ctx_output2/1x1
-I0511 11:48:51.961294  4597 net.cpp:260] Setting up ctx_output2/1x1
-I0511 11:48:51.961310  4597 net.cpp:267] TEST Top shape for layer 125 'ctx_output2/1x1' 10 512 8 16 (655360)
-I0511 11:48:51.961318  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.961324  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.961341  4597 net.cpp:200] Created Layer ctx_output2/1x1/bn (126)
-I0511 11:48:51.961345  4597 net.cpp:572] ctx_output2/1x1/bn <- ctx_output2/1x1
-I0511 11:48:51.961351  4597 net.cpp:527] ctx_output2/1x1/bn -> ctx_output2/1x1 (in-place)
-I0511 11:48:51.961596  4597 net.cpp:260] Setting up ctx_output2/1x1/bn
-I0511 11:48:51.961601  4597 net.cpp:267] TEST Top shape for layer 126 'ctx_output2/1x1/bn' 10 512 8 16 (655360)
-I0511 11:48:51.961611  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/relu' of type 'ReLU'
-I0511 11:48:51.961614  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.961621  4597 net.cpp:200] Created Layer ctx_output2/1x1/relu (127)
-I0511 11:48:51.961625  4597 net.cpp:572] ctx_output2/1x1/relu <- ctx_output2/1x1
-I0511 11:48:51.961630  4597 net.cpp:527] ctx_output2/1x1/relu -> ctx_output2/1x1 (in-place)
-I0511 11:48:51.961637  4597 net.cpp:260] Setting up ctx_output2/1x1/relu
-I0511 11:48:51.961642  4597 net.cpp:267] TEST Top shape for layer 127 'ctx_output2/1x1/relu' 10 512 8 16 (655360)
-I0511 11:48:51.961654  4597 layer_factory.hpp:172] Creating layer 'ctx_output2' of type 'Convolution'
-I0511 11:48:51.961659  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.961673  4597 net.cpp:200] Created Layer ctx_output2 (128)
-I0511 11:48:51.961678  4597 net.cpp:572] ctx_output2 <- ctx_output2/1x1
-I0511 11:48:51.961681  4597 net.cpp:542] ctx_output2 -> ctx_output2
-I0511 11:48:51.961938  4597 net.cpp:260] Setting up ctx_output2
-I0511 11:48:51.961946  4597 net.cpp:267] TEST Top shape for layer 128 'ctx_output2' 10 512 8 16 (655360)
-I0511 11:48:51.961952  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/bn' of type 'BatchNorm'
-I0511 11:48:51.961957  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.961963  4597 net.cpp:200] Created Layer ctx_output2/bn (129)
-I0511 11:48:51.961968  4597 net.cpp:572] ctx_output2/bn <- ctx_output2
-I0511 11:48:51.961973  4597 net.cpp:527] ctx_output2/bn -> ctx_output2 (in-place)
-I0511 11:48:51.962201  4597 net.cpp:260] Setting up ctx_output2/bn
-I0511 11:48:51.962208  4597 net.cpp:267] TEST Top shape for layer 129 'ctx_output2/bn' 10 512 8 16 (655360)
-I0511 11:48:51.962218  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu' of type 'ReLU'
-I0511 11:48:51.962221  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.962226  4597 net.cpp:200] Created Layer ctx_output2/relu (130)
-I0511 11:48:51.962231  4597 net.cpp:572] ctx_output2/relu <- ctx_output2
-I0511 11:48:51.962236  4597 net.cpp:527] ctx_output2/relu -> ctx_output2 (in-place)
-I0511 11:48:51.962242  4597 net.cpp:260] Setting up ctx_output2/relu
-I0511 11:48:51.962249  4597 net.cpp:267] TEST Top shape for layer 130 'ctx_output2/relu' 10 512 8 16 (655360)
-I0511 11:48:51.962254  4597 layer_factory.hpp:172] Creating layer 'ctx_output2_ctx_output2/relu_0_split' of type 'Split'
-I0511 11:48:51.962258  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.962265  4597 net.cpp:200] Created Layer ctx_output2_ctx_output2/relu_0_split (131)
-I0511 11:48:51.962270  4597 net.cpp:572] ctx_output2_ctx_output2/relu_0_split <- ctx_output2
-I0511 11:48:51.962275  4597 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_0
-I0511 11:48:51.962280  4597 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_1
-I0511 11:48:51.962286  4597 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_2
-I0511 11:48:51.962332  4597 net.cpp:260] Setting up ctx_output2_ctx_output2/relu_0_split
-I0511 11:48:51.962337  4597 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.962342  4597 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.962347  4597 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:48:51.962352  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1' of type 'Convolution'
-I0511 11:48:51.962357  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.962366  4597 net.cpp:200] Created Layer ctx_output3/1x1 (132)
-I0511 11:48:51.962371  4597 net.cpp:572] ctx_output3/1x1 <- pool6_pool6_0_split_1
-I0511 11:48:51.962378  4597 net.cpp:542] ctx_output3/1x1 -> ctx_output3/1x1
-I0511 11:48:51.968237  4597 net.cpp:260] Setting up ctx_output3/1x1
-I0511 11:48:51.968262  4597 net.cpp:267] TEST Top shape for layer 132 'ctx_output3/1x1' 10 512 5 9 (230400)
-I0511 11:48:51.968271  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.968276  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.968287  4597 net.cpp:200] Created Layer ctx_output3/1x1/bn (133)
-I0511 11:48:51.968305  4597 net.cpp:572] ctx_output3/1x1/bn <- ctx_output3/1x1
-I0511 11:48:51.968313  4597 net.cpp:527] ctx_output3/1x1/bn -> ctx_output3/1x1 (in-place)
-I0511 11:48:51.968598  4597 net.cpp:260] Setting up ctx_output3/1x1/bn
-I0511 11:48:51.968605  4597 net.cpp:267] TEST Top shape for layer 133 'ctx_output3/1x1/bn' 10 512 5 9 (230400)
-I0511 11:48:51.968616  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/relu' of type 'ReLU'
-I0511 11:48:51.968621  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.968627  4597 net.cpp:200] Created Layer ctx_output3/1x1/relu (134)
-I0511 11:48:51.968632  4597 net.cpp:572] ctx_output3/1x1/relu <- ctx_output3/1x1
-I0511 11:48:51.968637  4597 net.cpp:527] ctx_output3/1x1/relu -> ctx_output3/1x1 (in-place)
-I0511 11:48:51.968644  4597 net.cpp:260] Setting up ctx_output3/1x1/relu
-I0511 11:48:51.968650  4597 net.cpp:267] TEST Top shape for layer 134 'ctx_output3/1x1/relu' 10 512 5 9 (230400)
-I0511 11:48:51.968655  4597 layer_factory.hpp:172] Creating layer 'ctx_output3' of type 'Convolution'
-I0511 11:48:51.968659  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.968670  4597 net.cpp:200] Created Layer ctx_output3 (135)
-I0511 11:48:51.968675  4597 net.cpp:572] ctx_output3 <- ctx_output3/1x1
-I0511 11:48:51.968679  4597 net.cpp:542] ctx_output3 -> ctx_output3
-I0511 11:48:51.979056  4597 net.cpp:260] Setting up ctx_output3
-I0511 11:48:51.979081  4597 net.cpp:267] TEST Top shape for layer 135 'ctx_output3' 10 512 5 9 (230400)
-I0511 11:48:51.979090  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/bn' of type 'BatchNorm'
-I0511 11:48:51.979096  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.979120  4597 net.cpp:200] Created Layer ctx_output3/bn (136)
-I0511 11:48:51.979126  4597 net.cpp:572] ctx_output3/bn <- ctx_output3
-I0511 11:48:51.979130  4597 net.cpp:527] ctx_output3/bn -> ctx_output3 (in-place)
-I0511 11:48:51.979403  4597 net.cpp:260] Setting up ctx_output3/bn
-I0511 11:48:51.979410  4597 net.cpp:267] TEST Top shape for layer 136 'ctx_output3/bn' 10 512 5 9 (230400)
-I0511 11:48:51.979416  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu' of type 'ReLU'
-I0511 11:48:51.979418  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.979425  4597 net.cpp:200] Created Layer ctx_output3/relu (137)
-I0511 11:48:51.979429  4597 net.cpp:572] ctx_output3/relu <- ctx_output3
-I0511 11:48:51.979431  4597 net.cpp:527] ctx_output3/relu -> ctx_output3 (in-place)
-I0511 11:48:51.979435  4597 net.cpp:260] Setting up ctx_output3/relu
-I0511 11:48:51.979439  4597 net.cpp:267] TEST Top shape for layer 137 'ctx_output3/relu' 10 512 5 9 (230400)
-I0511 11:48:51.979441  4597 layer_factory.hpp:172] Creating layer 'ctx_output3_ctx_output3/relu_0_split' of type 'Split'
-I0511 11:48:51.979445  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.979451  4597 net.cpp:200] Created Layer ctx_output3_ctx_output3/relu_0_split (138)
-I0511 11:48:51.979457  4597 net.cpp:572] ctx_output3_ctx_output3/relu_0_split <- ctx_output3
-I0511 11:48:51.979463  4597 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_0
-I0511 11:48:51.979471  4597 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_1
-I0511 11:48:51.979476  4597 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_2
-I0511 11:48:51.979514  4597 net.cpp:260] Setting up ctx_output3_ctx_output3/relu_0_split
-I0511 11:48:51.979521  4597 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.979524  4597 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.979529  4597 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:48:51.979543  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1' of type 'Convolution'
-I0511 11:48:51.979548  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.979558  4597 net.cpp:200] Created Layer ctx_output4/1x1 (139)
-I0511 11:48:51.979563  4597 net.cpp:572] ctx_output4/1x1 <- pool7_pool7_0_split_1
-I0511 11:48:51.979568  4597 net.cpp:542] ctx_output4/1x1 -> ctx_output4/1x1
-I0511 11:48:51.984747  4597 net.cpp:260] Setting up ctx_output4/1x1
-I0511 11:48:51.984766  4597 net.cpp:267] TEST Top shape for layer 139 'ctx_output4/1x1' 10 512 3 5 (76800)
-I0511 11:48:51.984771  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.984776  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.984782  4597 net.cpp:200] Created Layer ctx_output4/1x1/bn (140)
-I0511 11:48:51.984786  4597 net.cpp:572] ctx_output4/1x1/bn <- ctx_output4/1x1
-I0511 11:48:51.984791  4597 net.cpp:527] ctx_output4/1x1/bn -> ctx_output4/1x1 (in-place)
-I0511 11:48:51.985059  4597 net.cpp:260] Setting up ctx_output4/1x1/bn
-I0511 11:48:51.985064  4597 net.cpp:267] TEST Top shape for layer 140 'ctx_output4/1x1/bn' 10 512 3 5 (76800)
-I0511 11:48:51.985070  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/relu' of type 'ReLU'
-I0511 11:48:51.985074  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985076  4597 net.cpp:200] Created Layer ctx_output4/1x1/relu (141)
-I0511 11:48:51.985079  4597 net.cpp:572] ctx_output4/1x1/relu <- ctx_output4/1x1
-I0511 11:48:51.985081  4597 net.cpp:527] ctx_output4/1x1/relu -> ctx_output4/1x1 (in-place)
-I0511 11:48:51.985085  4597 net.cpp:260] Setting up ctx_output4/1x1/relu
-I0511 11:48:51.985088  4597 net.cpp:267] TEST Top shape for layer 141 'ctx_output4/1x1/relu' 10 512 3 5 (76800)
-I0511 11:48:51.985091  4597 layer_factory.hpp:172] Creating layer 'ctx_output4' of type 'Convolution'
-I0511 11:48:51.985093  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985102  4597 net.cpp:200] Created Layer ctx_output4 (142)
-I0511 11:48:51.985117  4597 net.cpp:572] ctx_output4 <- ctx_output4/1x1
-I0511 11:48:51.985124  4597 net.cpp:542] ctx_output4 -> ctx_output4
-I0511 11:48:51.985402  4597 net.cpp:260] Setting up ctx_output4
-I0511 11:48:51.985409  4597 net.cpp:267] TEST Top shape for layer 142 'ctx_output4' 10 512 3 5 (76800)
-I0511 11:48:51.985414  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/bn' of type 'BatchNorm'
-I0511 11:48:51.985416  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985420  4597 net.cpp:200] Created Layer ctx_output4/bn (143)
-I0511 11:48:51.985424  4597 net.cpp:572] ctx_output4/bn <- ctx_output4
-I0511 11:48:51.985425  4597 net.cpp:527] ctx_output4/bn -> ctx_output4 (in-place)
-I0511 11:48:51.985668  4597 net.cpp:260] Setting up ctx_output4/bn
-I0511 11:48:51.985675  4597 net.cpp:267] TEST Top shape for layer 143 'ctx_output4/bn' 10 512 3 5 (76800)
-I0511 11:48:51.985683  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu' of type 'ReLU'
-I0511 11:48:51.985688  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985692  4597 net.cpp:200] Created Layer ctx_output4/relu (144)
-I0511 11:48:51.985697  4597 net.cpp:572] ctx_output4/relu <- ctx_output4
-I0511 11:48:51.985702  4597 net.cpp:527] ctx_output4/relu -> ctx_output4 (in-place)
-I0511 11:48:51.985707  4597 net.cpp:260] Setting up ctx_output4/relu
-I0511 11:48:51.985713  4597 net.cpp:267] TEST Top shape for layer 144 'ctx_output4/relu' 10 512 3 5 (76800)
-I0511 11:48:51.985718  4597 layer_factory.hpp:172] Creating layer 'ctx_output4_ctx_output4/relu_0_split' of type 'Split'
-I0511 11:48:51.985723  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985735  4597 net.cpp:200] Created Layer ctx_output4_ctx_output4/relu_0_split (145)
-I0511 11:48:51.985740  4597 net.cpp:572] ctx_output4_ctx_output4/relu_0_split <- ctx_output4
-I0511 11:48:51.985746  4597 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_0
-I0511 11:48:51.985754  4597 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_1
-I0511 11:48:51.985759  4597 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_2
-I0511 11:48:51.985796  4597 net.cpp:260] Setting up ctx_output4_ctx_output4/relu_0_split
-I0511 11:48:51.985801  4597 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.985806  4597 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.985812  4597 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.985817  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1' of type 'Convolution'
-I0511 11:48:51.985822  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.985836  4597 net.cpp:200] Created Layer ctx_output5/1x1 (146)
-I0511 11:48:51.985841  4597 net.cpp:572] ctx_output5/1x1 <- pool8
-I0511 11:48:51.985846  4597 net.cpp:542] ctx_output5/1x1 -> ctx_output5/1x1
-I0511 11:48:51.992885  4597 net.cpp:260] Setting up ctx_output5/1x1
-I0511 11:48:51.992913  4597 net.cpp:267] TEST Top shape for layer 146 'ctx_output5/1x1' 10 512 3 5 (76800)
-I0511 11:48:51.992920  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/bn' of type 'BatchNorm'
-I0511 11:48:51.992925  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.992934  4597 net.cpp:200] Created Layer ctx_output5/1x1/bn (147)
-I0511 11:48:51.992940  4597 net.cpp:572] ctx_output5/1x1/bn <- ctx_output5/1x1
-I0511 11:48:51.992944  4597 net.cpp:527] ctx_output5/1x1/bn -> ctx_output5/1x1 (in-place)
-I0511 11:48:51.993245  4597 net.cpp:260] Setting up ctx_output5/1x1/bn
-I0511 11:48:51.993252  4597 net.cpp:267] TEST Top shape for layer 147 'ctx_output5/1x1/bn' 10 512 3 5 (76800)
-I0511 11:48:51.993258  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/relu' of type 'ReLU'
-I0511 11:48:51.993261  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993265  4597 net.cpp:200] Created Layer ctx_output5/1x1/relu (148)
-I0511 11:48:51.993268  4597 net.cpp:572] ctx_output5/1x1/relu <- ctx_output5/1x1
-I0511 11:48:51.993270  4597 net.cpp:527] ctx_output5/1x1/relu -> ctx_output5/1x1 (in-place)
-I0511 11:48:51.993279  4597 net.cpp:260] Setting up ctx_output5/1x1/relu
-I0511 11:48:51.993283  4597 net.cpp:267] TEST Top shape for layer 148 'ctx_output5/1x1/relu' 10 512 3 5 (76800)
-I0511 11:48:51.993289  4597 layer_factory.hpp:172] Creating layer 'ctx_output5' of type 'Convolution'
-I0511 11:48:51.993294  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993304  4597 net.cpp:200] Created Layer ctx_output5 (149)
-I0511 11:48:51.993309  4597 net.cpp:572] ctx_output5 <- ctx_output5/1x1
-I0511 11:48:51.993314  4597 net.cpp:542] ctx_output5 -> ctx_output5
-I0511 11:48:51.993585  4597 net.cpp:260] Setting up ctx_output5
-I0511 11:48:51.993592  4597 net.cpp:267] TEST Top shape for layer 149 'ctx_output5' 10 512 3 5 (76800)
-I0511 11:48:51.993597  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/bn' of type 'BatchNorm'
-I0511 11:48:51.993599  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993603  4597 net.cpp:200] Created Layer ctx_output5/bn (150)
-I0511 11:48:51.993607  4597 net.cpp:572] ctx_output5/bn <- ctx_output5
-I0511 11:48:51.993609  4597 net.cpp:527] ctx_output5/bn -> ctx_output5 (in-place)
-I0511 11:48:51.993860  4597 net.cpp:260] Setting up ctx_output5/bn
-I0511 11:48:51.993875  4597 net.cpp:267] TEST Top shape for layer 150 'ctx_output5/bn' 10 512 3 5 (76800)
-I0511 11:48:51.993880  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu' of type 'ReLU'
-I0511 11:48:51.993883  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993886  4597 net.cpp:200] Created Layer ctx_output5/relu (151)
-I0511 11:48:51.993888  4597 net.cpp:572] ctx_output5/relu <- ctx_output5
-I0511 11:48:51.993891  4597 net.cpp:527] ctx_output5/relu -> ctx_output5 (in-place)
-I0511 11:48:51.993894  4597 net.cpp:260] Setting up ctx_output5/relu
-I0511 11:48:51.993897  4597 net.cpp:267] TEST Top shape for layer 151 'ctx_output5/relu' 10 512 3 5 (76800)
-I0511 11:48:51.993899  4597 layer_factory.hpp:172] Creating layer 'ctx_output5_ctx_output5/relu_0_split' of type 'Split'
-I0511 11:48:51.993902  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.993906  4597 net.cpp:200] Created Layer ctx_output5_ctx_output5/relu_0_split (152)
-I0511 11:48:51.993908  4597 net.cpp:572] ctx_output5_ctx_output5/relu_0_split <- ctx_output5
-I0511 11:48:51.993911  4597 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_0
-I0511 11:48:51.993916  4597 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_1
-I0511 11:48:51.993922  4597 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_2
-I0511 11:48:51.993968  4597 net.cpp:260] Setting up ctx_output5_ctx_output5/relu_0_split
-I0511 11:48:51.993973  4597 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.993978  4597 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.993983  4597 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:48:51.993988  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:51.993993  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.994004  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc (153)
-I0511 11:48:51.994009  4597 net.cpp:572] ctx_output1/relu_mbox_loc <- ctx_output1_ctx_output1/relu_0_split_0
-I0511 11:48:51.994014  4597 net.cpp:542] ctx_output1/relu_mbox_loc -> ctx_output1/relu_mbox_loc
-I0511 11:48:51.994343  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_loc
-I0511 11:48:51.994350  4597 net.cpp:267] TEST Top shape for layer 153 'ctx_output1/relu_mbox_loc' 10 16 16 32 (81920)
-I0511 11:48:51.994359  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:51.994364  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.994374  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_perm (154)
-I0511 11:48:51.994380  4597 net.cpp:572] ctx_output1/relu_mbox_loc_perm <- ctx_output1/relu_mbox_loc
-I0511 11:48:51.994385  4597 net.cpp:542] ctx_output1/relu_mbox_loc_perm -> ctx_output1/relu_mbox_loc_perm
-I0511 11:48:51.994464  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_perm
-I0511 11:48:51.994470  4597 net.cpp:267] TEST Top shape for layer 154 'ctx_output1/relu_mbox_loc_perm' 10 16 32 16 (81920)
-I0511 11:48:51.994475  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:51.994480  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.994488  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_flat (155)
-I0511 11:48:51.994493  4597 net.cpp:572] ctx_output1/relu_mbox_loc_flat <- ctx_output1/relu_mbox_loc_perm
-I0511 11:48:51.994498  4597 net.cpp:542] ctx_output1/relu_mbox_loc_flat -> ctx_output1/relu_mbox_loc_flat
-I0511 11:48:51.994599  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_flat
-I0511 11:48:51.994606  4597 net.cpp:267] TEST Top shape for layer 155 'ctx_output1/relu_mbox_loc_flat' 10 8192 (81920)
-I0511 11:48:51.994617  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:51.994622  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.994632  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf (156)
-I0511 11:48:51.994637  4597 net.cpp:572] ctx_output1/relu_mbox_conf <- ctx_output1_ctx_output1/relu_0_split_1
-I0511 11:48:51.994642  4597 net.cpp:542] ctx_output1/relu_mbox_conf -> ctx_output1/relu_mbox_conf
-I0511 11:48:51.995640  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_conf
-I0511 11:48:51.995647  4597 net.cpp:267] TEST Top shape for layer 156 'ctx_output1/relu_mbox_conf' 10 84 16 32 (430080)
-I0511 11:48:51.995656  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:51.995661  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.995667  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_perm (157)
-I0511 11:48:51.995673  4597 net.cpp:572] ctx_output1/relu_mbox_conf_perm <- ctx_output1/relu_mbox_conf
-I0511 11:48:51.995678  4597 net.cpp:542] ctx_output1/relu_mbox_conf_perm -> ctx_output1/relu_mbox_conf_perm
-I0511 11:48:51.995750  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_perm
-I0511 11:48:51.995756  4597 net.cpp:267] TEST Top shape for layer 157 'ctx_output1/relu_mbox_conf_perm' 10 16 32 84 (430080)
-I0511 11:48:51.995762  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:51.995766  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.995774  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_flat (158)
-I0511 11:48:51.995779  4597 net.cpp:572] ctx_output1/relu_mbox_conf_flat <- ctx_output1/relu_mbox_conf_perm
-I0511 11:48:51.995784  4597 net.cpp:542] ctx_output1/relu_mbox_conf_flat -> ctx_output1/relu_mbox_conf_flat
-I0511 11:48:51.997581  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_flat
-I0511 11:48:51.997593  4597 net.cpp:267] TEST Top shape for layer 158 'ctx_output1/relu_mbox_conf_flat' 10 43008 (430080)
-I0511 11:48:51.997599  4597 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:51.997606  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.997628  4597 net.cpp:200] Created Layer ctx_output1/relu_mbox_priorbox (159)
-I0511 11:48:51.997633  4597 net.cpp:572] ctx_output1/relu_mbox_priorbox <- ctx_output1_ctx_output1/relu_0_split_2
-I0511 11:48:51.997640  4597 net.cpp:572] ctx_output1/relu_mbox_priorbox <- data_data_0_split_1
-I0511 11:48:51.997648  4597 net.cpp:542] ctx_output1/relu_mbox_priorbox -> ctx_output1/relu_mbox_priorbox
-I0511 11:48:51.997680  4597 net.cpp:260] Setting up ctx_output1/relu_mbox_priorbox
-I0511 11:48:51.997687  4597 net.cpp:267] TEST Top shape for layer 159 'ctx_output1/relu_mbox_priorbox' 1 2 8192 (16384)
-I0511 11:48:51.997694  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:51.997697  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.997716  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc (160)
-I0511 11:48:51.997721  4597 net.cpp:572] ctx_output2/relu_mbox_loc <- ctx_output2_ctx_output2/relu_0_split_0
-I0511 11:48:51.997732  4597 net.cpp:542] ctx_output2/relu_mbox_loc -> ctx_output2/relu_mbox_loc
-I0511 11:48:51.998186  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_loc
-I0511 11:48:51.998195  4597 net.cpp:267] TEST Top shape for layer 160 'ctx_output2/relu_mbox_loc' 10 24 8 16 (30720)
-I0511 11:48:51.998203  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:51.998217  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.998236  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_perm (161)
-I0511 11:48:51.998241  4597 net.cpp:572] ctx_output2/relu_mbox_loc_perm <- ctx_output2/relu_mbox_loc
-I0511 11:48:51.998251  4597 net.cpp:542] ctx_output2/relu_mbox_loc_perm -> ctx_output2/relu_mbox_loc_perm
-I0511 11:48:51.998319  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_perm
-I0511 11:48:51.998325  4597 net.cpp:267] TEST Top shape for layer 161 'ctx_output2/relu_mbox_loc_perm' 10 8 16 24 (30720)
-I0511 11:48:51.998330  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:51.998340  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.998351  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_flat (162)
-I0511 11:48:51.998356  4597 net.cpp:572] ctx_output2/relu_mbox_loc_flat <- ctx_output2/relu_mbox_loc_perm
-I0511 11:48:51.998366  4597 net.cpp:542] ctx_output2/relu_mbox_loc_flat -> ctx_output2/relu_mbox_loc_flat
-I0511 11:48:51.998435  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_flat
-I0511 11:48:51.998442  4597 net.cpp:267] TEST Top shape for layer 162 'ctx_output2/relu_mbox_loc_flat' 10 3072 (30720)
-I0511 11:48:51.998447  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:51.998451  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.998466  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf (163)
-I0511 11:48:51.998471  4597 net.cpp:572] ctx_output2/relu_mbox_conf <- ctx_output2_ctx_output2/relu_0_split_1
-I0511 11:48:51.998481  4597 net.cpp:542] ctx_output2/relu_mbox_conf -> ctx_output2/relu_mbox_conf
-I0511 11:48:51.999861  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_conf
-I0511 11:48:51.999869  4597 net.cpp:267] TEST Top shape for layer 163 'ctx_output2/relu_mbox_conf' 10 126 8 16 (161280)
-I0511 11:48:51.999877  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:51.999882  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.999888  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_perm (164)
-I0511 11:48:51.999892  4597 net.cpp:572] ctx_output2/relu_mbox_conf_perm <- ctx_output2/relu_mbox_conf
-I0511 11:48:51.999898  4597 net.cpp:542] ctx_output2/relu_mbox_conf_perm -> ctx_output2/relu_mbox_conf_perm
-I0511 11:48:51.999964  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_perm
-I0511 11:48:51.999971  4597 net.cpp:267] TEST Top shape for layer 164 'ctx_output2/relu_mbox_conf_perm' 10 8 16 126 (161280)
-I0511 11:48:51.999976  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:51.999981  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:51.999986  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_flat (165)
-I0511 11:48:51.999991  4597 net.cpp:572] ctx_output2/relu_mbox_conf_flat <- ctx_output2/relu_mbox_conf_perm
-I0511 11:48:51.999997  4597 net.cpp:542] ctx_output2/relu_mbox_conf_flat -> ctx_output2/relu_mbox_conf_flat
-I0511 11:48:52.001277  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_flat
-I0511 11:48:52.001291  4597 net.cpp:267] TEST Top shape for layer 165 'ctx_output2/relu_mbox_conf_flat' 10 16128 (161280)
-I0511 11:48:52.001296  4597 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:52.001302  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.001309  4597 net.cpp:200] Created Layer ctx_output2/relu_mbox_priorbox (166)
-I0511 11:48:52.001314  4597 net.cpp:572] ctx_output2/relu_mbox_priorbox <- ctx_output2_ctx_output2/relu_0_split_2
-I0511 11:48:52.001322  4597 net.cpp:572] ctx_output2/relu_mbox_priorbox <- data_data_0_split_2
-I0511 11:48:52.001327  4597 net.cpp:542] ctx_output2/relu_mbox_priorbox -> ctx_output2/relu_mbox_priorbox
-I0511 11:48:52.001364  4597 net.cpp:260] Setting up ctx_output2/relu_mbox_priorbox
-I0511 11:48:52.001370  4597 net.cpp:267] TEST Top shape for layer 166 'ctx_output2/relu_mbox_priorbox' 1 2 3072 (6144)
-I0511 11:48:52.001375  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:52.001380  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.001397  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc (167)
-I0511 11:48:52.001401  4597 net.cpp:572] ctx_output3/relu_mbox_loc <- ctx_output3_ctx_output3/relu_0_split_0
-I0511 11:48:52.001407  4597 net.cpp:542] ctx_output3/relu_mbox_loc -> ctx_output3/relu_mbox_loc
-I0511 11:48:52.001842  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_loc
-I0511 11:48:52.001850  4597 net.cpp:267] TEST Top shape for layer 167 'ctx_output3/relu_mbox_loc' 10 24 5 9 (10800)
-I0511 11:48:52.001858  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:52.001863  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.001870  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_perm (168)
-I0511 11:48:52.001874  4597 net.cpp:572] ctx_output3/relu_mbox_loc_perm <- ctx_output3/relu_mbox_loc
-I0511 11:48:52.001880  4597 net.cpp:542] ctx_output3/relu_mbox_loc_perm -> ctx_output3/relu_mbox_loc_perm
-I0511 11:48:52.001947  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_perm
-I0511 11:48:52.001953  4597 net.cpp:267] TEST Top shape for layer 168 'ctx_output3/relu_mbox_loc_perm' 10 5 9 24 (10800)
-I0511 11:48:52.001958  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:52.001962  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.001969  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_flat (169)
-I0511 11:48:52.001973  4597 net.cpp:572] ctx_output3/relu_mbox_loc_flat <- ctx_output3/relu_mbox_loc_perm
-I0511 11:48:52.001979  4597 net.cpp:542] ctx_output3/relu_mbox_loc_flat -> ctx_output3/relu_mbox_loc_flat
-I0511 11:48:52.002033  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_flat
-I0511 11:48:52.002039  4597 net.cpp:267] TEST Top shape for layer 169 'ctx_output3/relu_mbox_loc_flat' 10 1080 (10800)
-I0511 11:48:52.002044  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:52.002049  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.002058  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf (170)
-I0511 11:48:52.002063  4597 net.cpp:572] ctx_output3/relu_mbox_conf <- ctx_output3_ctx_output3/relu_0_split_1
-I0511 11:48:52.002068  4597 net.cpp:542] ctx_output3/relu_mbox_conf -> ctx_output3/relu_mbox_conf
-I0511 11:48:52.003453  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_conf
-I0511 11:48:52.003460  4597 net.cpp:267] TEST Top shape for layer 170 'ctx_output3/relu_mbox_conf' 10 126 5 9 (56700)
-I0511 11:48:52.003468  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:52.003471  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.003485  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_perm (171)
-I0511 11:48:52.003491  4597 net.cpp:572] ctx_output3/relu_mbox_conf_perm <- ctx_output3/relu_mbox_conf
-I0511 11:48:52.003505  4597 net.cpp:542] ctx_output3/relu_mbox_conf_perm -> ctx_output3/relu_mbox_conf_perm
-I0511 11:48:52.003578  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_perm
-I0511 11:48:52.003585  4597 net.cpp:267] TEST Top shape for layer 171 'ctx_output3/relu_mbox_conf_perm' 10 5 9 126 (56700)
-I0511 11:48:52.003595  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:52.003600  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.003617  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_flat (172)
-I0511 11:48:52.003623  4597 net.cpp:572] ctx_output3/relu_mbox_conf_flat <- ctx_output3/relu_mbox_conf_perm
-I0511 11:48:52.003631  4597 net.cpp:542] ctx_output3/relu_mbox_conf_flat -> ctx_output3/relu_mbox_conf_flat
-I0511 11:48:52.003716  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_flat
-I0511 11:48:52.003723  4597 net.cpp:267] TEST Top shape for layer 172 'ctx_output3/relu_mbox_conf_flat' 10 5670 (56700)
-I0511 11:48:52.003732  4597 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:52.003737  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.003747  4597 net.cpp:200] Created Layer ctx_output3/relu_mbox_priorbox (173)
-I0511 11:48:52.003752  4597 net.cpp:572] ctx_output3/relu_mbox_priorbox <- ctx_output3_ctx_output3/relu_0_split_2
-I0511 11:48:52.003762  4597 net.cpp:572] ctx_output3/relu_mbox_priorbox <- data_data_0_split_3
-I0511 11:48:52.003768  4597 net.cpp:542] ctx_output3/relu_mbox_priorbox -> ctx_output3/relu_mbox_priorbox
-I0511 11:48:52.003793  4597 net.cpp:260] Setting up ctx_output3/relu_mbox_priorbox
-I0511 11:48:52.003799  4597 net.cpp:267] TEST Top shape for layer 173 'ctx_output3/relu_mbox_priorbox' 1 2 1080 (2160)
-I0511 11:48:52.003808  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:52.003813  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.003829  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc (174)
-I0511 11:48:52.003834  4597 net.cpp:572] ctx_output4/relu_mbox_loc <- ctx_output4_ctx_output4/relu_0_split_0
-I0511 11:48:52.003844  4597 net.cpp:542] ctx_output4/relu_mbox_loc -> ctx_output4/relu_mbox_loc
-I0511 11:48:52.004180  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_loc
-I0511 11:48:52.004187  4597 net.cpp:267] TEST Top shape for layer 174 'ctx_output4/relu_mbox_loc' 10 16 3 5 (2400)
-I0511 11:48:52.004200  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:52.004205  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.004216  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_perm (175)
-I0511 11:48:52.004220  4597 net.cpp:572] ctx_output4/relu_mbox_loc_perm <- ctx_output4/relu_mbox_loc
-I0511 11:48:52.004230  4597 net.cpp:542] ctx_output4/relu_mbox_loc_perm -> ctx_output4/relu_mbox_loc_perm
-I0511 11:48:52.004302  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_perm
-I0511 11:48:52.004309  4597 net.cpp:267] TEST Top shape for layer 175 'ctx_output4/relu_mbox_loc_perm' 10 3 5 16 (2400)
-I0511 11:48:52.004319  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:52.004323  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.004333  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_flat (176)
-I0511 11:48:52.004338  4597 net.cpp:572] ctx_output4/relu_mbox_loc_flat <- ctx_output4/relu_mbox_loc_perm
-I0511 11:48:52.004348  4597 net.cpp:542] ctx_output4/relu_mbox_loc_flat -> ctx_output4/relu_mbox_loc_flat
-I0511 11:48:52.004396  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_flat
-I0511 11:48:52.004403  4597 net.cpp:267] TEST Top shape for layer 176 'ctx_output4/relu_mbox_loc_flat' 10 240 (2400)
-I0511 11:48:52.004413  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:52.004417  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.004431  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf (177)
-I0511 11:48:52.004434  4597 net.cpp:572] ctx_output4/relu_mbox_conf <- ctx_output4_ctx_output4/relu_0_split_1
-I0511 11:48:52.004446  4597 net.cpp:542] ctx_output4/relu_mbox_conf -> ctx_output4/relu_mbox_conf
-I0511 11:48:52.005472  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_conf
-I0511 11:48:52.005484  4597 net.cpp:267] TEST Top shape for layer 177 'ctx_output4/relu_mbox_conf' 10 84 3 5 (12600)
-I0511 11:48:52.005498  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:52.005503  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.005515  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_perm (178)
-I0511 11:48:52.005520  4597 net.cpp:572] ctx_output4/relu_mbox_conf_perm <- ctx_output4/relu_mbox_conf
-I0511 11:48:52.005530  4597 net.cpp:542] ctx_output4/relu_mbox_conf_perm -> ctx_output4/relu_mbox_conf_perm
-I0511 11:48:52.005607  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_perm
-I0511 11:48:52.005614  4597 net.cpp:267] TEST Top shape for layer 178 'ctx_output4/relu_mbox_conf_perm' 10 3 5 84 (12600)
-I0511 11:48:52.005625  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:52.005630  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.005635  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_flat (179)
-I0511 11:48:52.005640  4597 net.cpp:572] ctx_output4/relu_mbox_conf_flat <- ctx_output4/relu_mbox_conf_perm
-I0511 11:48:52.005645  4597 net.cpp:542] ctx_output4/relu_mbox_conf_flat -> ctx_output4/relu_mbox_conf_flat
-I0511 11:48:52.005698  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_flat
-I0511 11:48:52.005704  4597 net.cpp:267] TEST Top shape for layer 179 'ctx_output4/relu_mbox_conf_flat' 10 1260 (12600)
-I0511 11:48:52.005709  4597 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:52.005714  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.005722  4597 net.cpp:200] Created Layer ctx_output4/relu_mbox_priorbox (180)
-I0511 11:48:52.005728  4597 net.cpp:572] ctx_output4/relu_mbox_priorbox <- ctx_output4_ctx_output4/relu_0_split_2
-I0511 11:48:52.005734  4597 net.cpp:572] ctx_output4/relu_mbox_priorbox <- data_data_0_split_4
-I0511 11:48:52.005740  4597 net.cpp:542] ctx_output4/relu_mbox_priorbox -> ctx_output4/relu_mbox_priorbox
-I0511 11:48:52.005762  4597 net.cpp:260] Setting up ctx_output4/relu_mbox_priorbox
-I0511 11:48:52.005767  4597 net.cpp:267] TEST Top shape for layer 180 'ctx_output4/relu_mbox_priorbox' 1 2 240 (480)
-I0511 11:48:52.005770  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc' of type 'Convolution'
-I0511 11:48:52.005776  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.005862  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc (181)
-I0511 11:48:52.005868  4597 net.cpp:572] ctx_output5/relu_mbox_loc <- ctx_output5_ctx_output5/relu_0_split_0
-I0511 11:48:52.005872  4597 net.cpp:542] ctx_output5/relu_mbox_loc -> ctx_output5/relu_mbox_loc
-I0511 11:48:52.006203  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_loc
-I0511 11:48:52.006211  4597 net.cpp:267] TEST Top shape for layer 181 'ctx_output5/relu_mbox_loc' 10 16 3 5 (2400)
-I0511 11:48:52.006217  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:48:52.006222  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.006228  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_perm (182)
-I0511 11:48:52.006234  4597 net.cpp:572] ctx_output5/relu_mbox_loc_perm <- ctx_output5/relu_mbox_loc
-I0511 11:48:52.006240  4597 net.cpp:542] ctx_output5/relu_mbox_loc_perm -> ctx_output5/relu_mbox_loc_perm
-I0511 11:48:52.006319  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_perm
-I0511 11:48:52.006323  4597 net.cpp:267] TEST Top shape for layer 182 'ctx_output5/relu_mbox_loc_perm' 10 3 5 16 (2400)
-I0511 11:48:52.006327  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:48:52.006340  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.006346  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_flat (183)
-I0511 11:48:52.006351  4597 net.cpp:572] ctx_output5/relu_mbox_loc_flat <- ctx_output5/relu_mbox_loc_perm
-I0511 11:48:52.006357  4597 net.cpp:542] ctx_output5/relu_mbox_loc_flat -> ctx_output5/relu_mbox_loc_flat
-I0511 11:48:52.006407  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_flat
-I0511 11:48:52.006413  4597 net.cpp:267] TEST Top shape for layer 183 'ctx_output5/relu_mbox_loc_flat' 10 240 (2400)
-I0511 11:48:52.006418  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf' of type 'Convolution'
-I0511 11:48:52.006423  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.006434  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf (184)
-I0511 11:48:52.006438  4597 net.cpp:572] ctx_output5/relu_mbox_conf <- ctx_output5_ctx_output5/relu_0_split_1
-I0511 11:48:52.006443  4597 net.cpp:542] ctx_output5/relu_mbox_conf -> ctx_output5/relu_mbox_conf
-I0511 11:48:52.007438  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_conf
-I0511 11:48:52.007445  4597 net.cpp:267] TEST Top shape for layer 184 'ctx_output5/relu_mbox_conf' 10 84 3 5 (12600)
-I0511 11:48:52.007452  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:48:52.007457  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007464  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_perm (185)
-I0511 11:48:52.007469  4597 net.cpp:572] ctx_output5/relu_mbox_conf_perm <- ctx_output5/relu_mbox_conf
-I0511 11:48:52.007475  4597 net.cpp:542] ctx_output5/relu_mbox_conf_perm -> ctx_output5/relu_mbox_conf_perm
-I0511 11:48:52.007549  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_perm
-I0511 11:48:52.007555  4597 net.cpp:267] TEST Top shape for layer 185 'ctx_output5/relu_mbox_conf_perm' 10 3 5 84 (12600)
-I0511 11:48:52.007560  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:48:52.007565  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007570  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_flat (186)
-I0511 11:48:52.007576  4597 net.cpp:572] ctx_output5/relu_mbox_conf_flat <- ctx_output5/relu_mbox_conf_perm
-I0511 11:48:52.007582  4597 net.cpp:542] ctx_output5/relu_mbox_conf_flat -> ctx_output5/relu_mbox_conf_flat
-I0511 11:48:52.007635  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_flat
-I0511 11:48:52.007642  4597 net.cpp:267] TEST Top shape for layer 186 'ctx_output5/relu_mbox_conf_flat' 10 1260 (12600)
-I0511 11:48:52.007647  4597 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:48:52.007652  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007663  4597 net.cpp:200] Created Layer ctx_output5/relu_mbox_priorbox (187)
-I0511 11:48:52.007666  4597 net.cpp:572] ctx_output5/relu_mbox_priorbox <- ctx_output5_ctx_output5/relu_0_split_2
-I0511 11:48:52.007671  4597 net.cpp:572] ctx_output5/relu_mbox_priorbox <- data_data_0_split_5
-I0511 11:48:52.007678  4597 net.cpp:542] ctx_output5/relu_mbox_priorbox -> ctx_output5/relu_mbox_priorbox
-I0511 11:48:52.007699  4597 net.cpp:260] Setting up ctx_output5/relu_mbox_priorbox
-I0511 11:48:52.007704  4597 net.cpp:267] TEST Top shape for layer 187 'ctx_output5/relu_mbox_priorbox' 1 2 240 (480)
-I0511 11:48:52.007709  4597 layer_factory.hpp:172] Creating layer 'mbox_loc' of type 'Concat'
-I0511 11:48:52.007714  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007722  4597 net.cpp:200] Created Layer mbox_loc (188)
-I0511 11:48:52.007726  4597 net.cpp:572] mbox_loc <- ctx_output1/relu_mbox_loc_flat
-I0511 11:48:52.007737  4597 net.cpp:572] mbox_loc <- ctx_output2/relu_mbox_loc_flat
-I0511 11:48:52.007743  4597 net.cpp:572] mbox_loc <- ctx_output3/relu_mbox_loc_flat
-I0511 11:48:52.007750  4597 net.cpp:572] mbox_loc <- ctx_output4/relu_mbox_loc_flat
-I0511 11:48:52.007755  4597 net.cpp:572] mbox_loc <- ctx_output5/relu_mbox_loc_flat
-I0511 11:48:52.007761  4597 net.cpp:542] mbox_loc -> mbox_loc
-I0511 11:48:52.007786  4597 net.cpp:260] Setting up mbox_loc
-I0511 11:48:52.007792  4597 net.cpp:267] TEST Top shape for layer 188 'mbox_loc' 10 12824 (128240)
-I0511 11:48:52.007797  4597 layer_factory.hpp:172] Creating layer 'mbox_conf' of type 'Concat'
-I0511 11:48:52.007802  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007808  4597 net.cpp:200] Created Layer mbox_conf (189)
-I0511 11:48:52.007814  4597 net.cpp:572] mbox_conf <- ctx_output1/relu_mbox_conf_flat
-I0511 11:48:52.007820  4597 net.cpp:572] mbox_conf <- ctx_output2/relu_mbox_conf_flat
-I0511 11:48:52.007827  4597 net.cpp:572] mbox_conf <- ctx_output3/relu_mbox_conf_flat
-I0511 11:48:52.007833  4597 net.cpp:572] mbox_conf <- ctx_output4/relu_mbox_conf_flat
-I0511 11:48:52.007838  4597 net.cpp:572] mbox_conf <- ctx_output5/relu_mbox_conf_flat
-I0511 11:48:52.007843  4597 net.cpp:542] mbox_conf -> mbox_conf
-I0511 11:48:52.007863  4597 net.cpp:260] Setting up mbox_conf
-I0511 11:48:52.007867  4597 net.cpp:267] TEST Top shape for layer 189 'mbox_conf' 10 67326 (673260)
-I0511 11:48:52.007872  4597 layer_factory.hpp:172] Creating layer 'mbox_priorbox' of type 'Concat'
-I0511 11:48:52.007877  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007884  4597 net.cpp:200] Created Layer mbox_priorbox (190)
-I0511 11:48:52.007889  4597 net.cpp:572] mbox_priorbox <- ctx_output1/relu_mbox_priorbox
-I0511 11:48:52.007894  4597 net.cpp:572] mbox_priorbox <- ctx_output2/relu_mbox_priorbox
-I0511 11:48:52.007900  4597 net.cpp:572] mbox_priorbox <- ctx_output3/relu_mbox_priorbox
-I0511 11:48:52.007905  4597 net.cpp:572] mbox_priorbox <- ctx_output4/relu_mbox_priorbox
-I0511 11:48:52.007910  4597 net.cpp:572] mbox_priorbox <- ctx_output5/relu_mbox_priorbox
-I0511 11:48:52.007916  4597 net.cpp:542] mbox_priorbox -> mbox_priorbox
-I0511 11:48:52.007941  4597 net.cpp:260] Setting up mbox_priorbox
-I0511 11:48:52.007946  4597 net.cpp:267] TEST Top shape for layer 190 'mbox_priorbox' 1 2 12824 (25648)
-I0511 11:48:52.007951  4597 layer_factory.hpp:172] Creating layer 'mbox_conf_reshape' of type 'Reshape'
-I0511 11:48:52.007956  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.007964  4597 net.cpp:200] Created Layer mbox_conf_reshape (191)
-I0511 11:48:52.007969  4597 net.cpp:572] mbox_conf_reshape <- mbox_conf
-I0511 11:48:52.007973  4597 net.cpp:542] mbox_conf_reshape -> mbox_conf_reshape
-I0511 11:48:52.007993  4597 net.cpp:260] Setting up mbox_conf_reshape
-I0511 11:48:52.007998  4597 net.cpp:267] TEST Top shape for layer 191 'mbox_conf_reshape' 10 3206 21 (673260)
-I0511 11:48:52.008003  4597 layer_factory.hpp:172] Creating layer 'mbox_conf_softmax' of type 'Softmax'
-I0511 11:48:52.008008  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.008021  4597 net.cpp:200] Created Layer mbox_conf_softmax (192)
-I0511 11:48:52.008025  4597 net.cpp:572] mbox_conf_softmax <- mbox_conf_reshape
-I0511 11:48:52.008029  4597 net.cpp:542] mbox_conf_softmax -> mbox_conf_softmax
-I0511 11:48:52.008078  4597 net.cpp:260] Setting up mbox_conf_softmax
-I0511 11:48:52.008083  4597 net.cpp:267] TEST Top shape for layer 192 'mbox_conf_softmax' 10 3206 21 (673260)
-I0511 11:48:52.008090  4597 layer_factory.hpp:172] Creating layer 'mbox_conf_flatten' of type 'Flatten'
-I0511 11:48:52.008095  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.008098  4597 net.cpp:200] Created Layer mbox_conf_flatten (193)
-I0511 11:48:52.008101  4597 net.cpp:572] mbox_conf_flatten <- mbox_conf_softmax
-I0511 11:48:52.008108  4597 net.cpp:542] mbox_conf_flatten -> mbox_conf_flatten
-I0511 11:48:52.011179  4597 net.cpp:260] Setting up mbox_conf_flatten
-I0511 11:48:52.011201  4597 net.cpp:267] TEST Top shape for layer 193 'mbox_conf_flatten' 10 67326 (673260)
-I0511 11:48:52.011207  4597 layer_factory.hpp:172] Creating layer 'detection_out' of type 'DetectionOutput'
-I0511 11:48:52.011212  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.011232  4597 net.cpp:200] Created Layer detection_out (194)
-I0511 11:48:52.011236  4597 net.cpp:572] detection_out <- mbox_loc
-I0511 11:48:52.011241  4597 net.cpp:572] detection_out <- mbox_conf_flatten
-I0511 11:48:52.011245  4597 net.cpp:572] detection_out <- mbox_priorbox
-I0511 11:48:52.011247  4597 net.cpp:542] detection_out -> detection_out
-I0511 11:48:52.037533  4597 net.cpp:260] Setting up detection_out
-I0511 11:48:52.037564  4597 net.cpp:267] TEST Top shape for layer 194 'detection_out' 1 1 1 7 (7)
-I0511 11:48:52.037573  4597 layer_factory.hpp:172] Creating layer 'detection_eval' of type 'DetectionEvaluate'
-I0511 11:48:52.037580  4597 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:48:52.037603  4597 net.cpp:200] Created Layer detection_eval (195)
-I0511 11:48:52.037611  4597 net.cpp:572] detection_eval <- detection_out
-I0511 11:48:52.037619  4597 net.cpp:572] detection_eval <- label
-I0511 11:48:52.037627  4597 net.cpp:542] detection_eval -> detection_eval
-I0511 11:48:52.038914  4597 net.cpp:260] Setting up detection_eval
-I0511 11:48:52.038928  4597 net.cpp:267] TEST Top shape for layer 195 'detection_eval' 1 1 21 5 (105)
-I0511 11:48:52.038936  4597 net.cpp:338] detection_eval does not need backward computation.
-I0511 11:48:52.038940  4597 net.cpp:338] detection_out does not need backward computation.
-I0511 11:48:52.038944  4597 net.cpp:338] mbox_conf_flatten does not need backward computation.
-I0511 11:48:52.038949  4597 net.cpp:338] mbox_conf_softmax does not need backward computation.
-I0511 11:48:52.038951  4597 net.cpp:338] mbox_conf_reshape does not need backward computation.
-I0511 11:48:52.038954  4597 net.cpp:338] mbox_priorbox does not need backward computation.
-I0511 11:48:52.038960  4597 net.cpp:338] mbox_conf does not need backward computation.
-I0511 11:48:52.038974  4597 net.cpp:338] mbox_loc does not need backward computation.
-I0511 11:48:52.038980  4597 net.cpp:338] ctx_output5/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.038986  4597 net.cpp:338] ctx_output5/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.038991  4597 net.cpp:338] ctx_output5/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.038996  4597 net.cpp:338] ctx_output5/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039001  4597 net.cpp:338] ctx_output5/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039006  4597 net.cpp:338] ctx_output5/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039011  4597 net.cpp:338] ctx_output5/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039016  4597 net.cpp:338] ctx_output4/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.039021  4597 net.cpp:338] ctx_output4/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.039026  4597 net.cpp:338] ctx_output4/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.039032  4597 net.cpp:338] ctx_output4/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039037  4597 net.cpp:338] ctx_output4/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039042  4597 net.cpp:338] ctx_output4/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039047  4597 net.cpp:338] ctx_output4/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039052  4597 net.cpp:338] ctx_output3/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.039057  4597 net.cpp:338] ctx_output3/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.039075  4597 net.cpp:338] ctx_output3/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.039080  4597 net.cpp:338] ctx_output3/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039085  4597 net.cpp:338] ctx_output3/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039090  4597 net.cpp:338] ctx_output3/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039095  4597 net.cpp:338] ctx_output3/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039100  4597 net.cpp:338] ctx_output2/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.039104  4597 net.cpp:338] ctx_output2/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.039109  4597 net.cpp:338] ctx_output2/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.039114  4597 net.cpp:338] ctx_output2/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039119  4597 net.cpp:338] ctx_output2/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039124  4597 net.cpp:338] ctx_output2/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039129  4597 net.cpp:338] ctx_output2/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039134  4597 net.cpp:338] ctx_output1/relu_mbox_priorbox does not need backward computation.
-I0511 11:48:52.039139  4597 net.cpp:338] ctx_output1/relu_mbox_conf_flat does not need backward computation.
-I0511 11:48:52.039144  4597 net.cpp:338] ctx_output1/relu_mbox_conf_perm does not need backward computation.
-I0511 11:48:52.039149  4597 net.cpp:338] ctx_output1/relu_mbox_conf does not need backward computation.
-I0511 11:48:52.039153  4597 net.cpp:338] ctx_output1/relu_mbox_loc_flat does not need backward computation.
-I0511 11:48:52.039157  4597 net.cpp:338] ctx_output1/relu_mbox_loc_perm does not need backward computation.
-I0511 11:48:52.039162  4597 net.cpp:338] ctx_output1/relu_mbox_loc does not need backward computation.
-I0511 11:48:52.039168  4597 net.cpp:338] ctx_output5_ctx_output5/relu_0_split does not need backward computation.
-I0511 11:48:52.039173  4597 net.cpp:338] ctx_output5/relu does not need backward computation.
-I0511 11:48:52.039178  4597 net.cpp:338] ctx_output5/bn does not need backward computation.
-I0511 11:48:52.039182  4597 net.cpp:338] ctx_output5 does not need backward computation.
-I0511 11:48:52.039187  4597 net.cpp:338] ctx_output5/1x1/relu does not need backward computation.
-I0511 11:48:52.039192  4597 net.cpp:338] ctx_output5/1x1/bn does not need backward computation.
-I0511 11:48:52.039197  4597 net.cpp:338] ctx_output5/1x1 does not need backward computation.
-I0511 11:48:52.039202  4597 net.cpp:338] ctx_output4_ctx_output4/relu_0_split does not need backward computation.
-I0511 11:48:52.039207  4597 net.cpp:338] ctx_output4/relu does not need backward computation.
-I0511 11:48:52.039212  4597 net.cpp:338] ctx_output4/bn does not need backward computation.
-I0511 11:48:52.039216  4597 net.cpp:338] ctx_output4 does not need backward computation.
-I0511 11:48:52.039222  4597 net.cpp:338] ctx_output4/1x1/relu does not need backward computation.
-I0511 11:48:52.039227  4597 net.cpp:338] ctx_output4/1x1/bn does not need backward computation.
-I0511 11:48:52.039230  4597 net.cpp:338] ctx_output4/1x1 does not need backward computation.
-I0511 11:48:52.039237  4597 net.cpp:338] ctx_output3_ctx_output3/relu_0_split does not need backward computation.
-I0511 11:48:52.039242  4597 net.cpp:338] ctx_output3/relu does not need backward computation.
-I0511 11:48:52.039247  4597 net.cpp:338] ctx_output3/bn does not need backward computation.
-I0511 11:48:52.039252  4597 net.cpp:338] ctx_output3 does not need backward computation.
-I0511 11:48:52.039257  4597 net.cpp:338] ctx_output3/1x1/relu does not need backward computation.
-I0511 11:48:52.039261  4597 net.cpp:338] ctx_output3/1x1/bn does not need backward computation.
-I0511 11:48:52.039266  4597 net.cpp:338] ctx_output3/1x1 does not need backward computation.
-I0511 11:48:52.039278  4597 net.cpp:338] ctx_output2_ctx_output2/relu_0_split does not need backward computation.
-I0511 11:48:52.039283  4597 net.cpp:338] ctx_output2/relu does not need backward computation.
-I0511 11:48:52.039288  4597 net.cpp:338] ctx_output2/bn does not need backward computation.
-I0511 11:48:52.039291  4597 net.cpp:338] ctx_output2 does not need backward computation.
-I0511 11:48:52.039296  4597 net.cpp:338] ctx_output2/1x1/relu does not need backward computation.
-I0511 11:48:52.039301  4597 net.cpp:338] ctx_output2/1x1/bn does not need backward computation.
-I0511 11:48:52.039305  4597 net.cpp:338] ctx_output2/1x1 does not need backward computation.
-I0511 11:48:52.039311  4597 net.cpp:338] ctx_output1_ctx_output1/relu_0_split does not need backward computation.
-I0511 11:48:52.039316  4597 net.cpp:338] ctx_output1/relu does not need backward computation.
-I0511 11:48:52.039321  4597 net.cpp:338] ctx_output1/bn does not need backward computation.
-I0511 11:48:52.039325  4597 net.cpp:338] ctx_output1 does not need backward computation.
-I0511 11:48:52.039330  4597 net.cpp:338] ctx_output1/1x1/relu does not need backward computation.
-I0511 11:48:52.039335  4597 net.cpp:338] ctx_output1/1x1/bn does not need backward computation.
-I0511 11:48:52.039340  4597 net.cpp:338] ctx_output1/1x1 does not need backward computation.
-I0511 11:48:52.039345  4597 net.cpp:338] pool8 does not need backward computation.
-I0511 11:48:52.039351  4597 net.cpp:338] pool7_pool7_0_split does not need backward computation.
-I0511 11:48:52.039356  4597 net.cpp:338] pool7 does not need backward computation.
-I0511 11:48:52.039361  4597 net.cpp:338] pool6_pool6_0_split does not need backward computation.
-I0511 11:48:52.039366  4597 net.cpp:338] pool6 does not need backward computation.
-I0511 11:48:52.039371  4597 net.cpp:338] conv6/sep_relu6/sep_0_split does not need backward computation.
-I0511 11:48:52.039376  4597 net.cpp:338] relu6/sep does not need backward computation.
-I0511 11:48:52.039381  4597 net.cpp:338] conv6/sep/scale does not need backward computation.
-I0511 11:48:52.039386  4597 net.cpp:338] conv6/sep/bn does not need backward computation.
-I0511 11:48:52.039389  4597 net.cpp:338] conv6/sep does not need backward computation.
-I0511 11:48:52.039394  4597 net.cpp:338] relu6/dw does not need backward computation.
-I0511 11:48:52.039399  4597 net.cpp:338] conv6/dw/scale does not need backward computation.
-I0511 11:48:52.039404  4597 net.cpp:338] conv6/dw/bn does not need backward computation.
-I0511 11:48:52.039408  4597 net.cpp:338] conv6/dw does not need backward computation.
-I0511 11:48:52.039413  4597 net.cpp:338] relu5_6/sep does not need backward computation.
-I0511 11:48:52.039418  4597 net.cpp:338] conv5_6/sep/scale does not need backward computation.
-I0511 11:48:52.039422  4597 net.cpp:338] conv5_6/sep/bn does not need backward computation.
-I0511 11:48:52.039427  4597 net.cpp:338] conv5_6/sep does not need backward computation.
-I0511 11:48:52.039433  4597 net.cpp:338] relu5_6/dw does not need backward computation.
-I0511 11:48:52.039436  4597 net.cpp:338] conv5_6/dw/scale does not need backward computation.
-I0511 11:48:52.039441  4597 net.cpp:338] conv5_6/dw/bn does not need backward computation.
-I0511 11:48:52.039446  4597 net.cpp:338] conv5_6/dw does not need backward computation.
-I0511 11:48:52.039451  4597 net.cpp:338] conv5_5/sep_relu5_5/sep_0_split does not need backward computation.
-I0511 11:48:52.039456  4597 net.cpp:338] relu5_5/sep does not need backward computation.
-I0511 11:48:52.039461  4597 net.cpp:338] conv5_5/sep/scale does not need backward computation.
-I0511 11:48:52.039465  4597 net.cpp:338] conv5_5/sep/bn does not need backward computation.
-I0511 11:48:52.039470  4597 net.cpp:338] conv5_5/sep does not need backward computation.
-I0511 11:48:52.039475  4597 net.cpp:338] relu5_5/dw does not need backward computation.
-I0511 11:48:52.039480  4597 net.cpp:338] conv5_5/dw/scale does not need backward computation.
-I0511 11:48:52.039484  4597 net.cpp:338] conv5_5/dw/bn does not need backward computation.
-I0511 11:48:52.039492  4597 net.cpp:338] conv5_5/dw does not need backward computation.
-I0511 11:48:52.039499  4597 net.cpp:338] relu5_4/sep does not need backward computation.
-I0511 11:48:52.039502  4597 net.cpp:338] conv5_4/sep/scale does not need backward computation.
-I0511 11:48:52.039507  4597 net.cpp:338] conv5_4/sep/bn does not need backward computation.
-I0511 11:48:52.039511  4597 net.cpp:338] conv5_4/sep does not need backward computation.
-I0511 11:48:52.039516  4597 net.cpp:338] relu5_4/dw does not need backward computation.
-I0511 11:48:52.039521  4597 net.cpp:338] conv5_4/dw/scale does not need backward computation.
-I0511 11:48:52.039525  4597 net.cpp:338] conv5_4/dw/bn does not need backward computation.
-I0511 11:48:52.039530  4597 net.cpp:338] conv5_4/dw does not need backward computation.
-I0511 11:48:52.039535  4597 net.cpp:338] relu5_3/sep does not need backward computation.
-I0511 11:48:52.039539  4597 net.cpp:338] conv5_3/sep/scale does not need backward computation.
-I0511 11:48:52.039544  4597 net.cpp:338] conv5_3/sep/bn does not need backward computation.
-I0511 11:48:52.039548  4597 net.cpp:338] conv5_3/sep does not need backward computation.
-I0511 11:48:52.039553  4597 net.cpp:338] relu5_3/dw does not need backward computation.
-I0511 11:48:52.039558  4597 net.cpp:338] conv5_3/dw/scale does not need backward computation.
-I0511 11:48:52.039562  4597 net.cpp:338] conv5_3/dw/bn does not need backward computation.
-I0511 11:48:52.039567  4597 net.cpp:338] conv5_3/dw does not need backward computation.
-I0511 11:48:52.039572  4597 net.cpp:338] relu5_2/sep does not need backward computation.
-I0511 11:48:52.039577  4597 net.cpp:338] conv5_2/sep/scale does not need backward computation.
-I0511 11:48:52.039582  4597 net.cpp:338] conv5_2/sep/bn does not need backward computation.
-I0511 11:48:52.039585  4597 net.cpp:338] conv5_2/sep does not need backward computation.
-I0511 11:48:52.039590  4597 net.cpp:338] relu5_2/dw does not need backward computation.
-I0511 11:48:52.039594  4597 net.cpp:338] conv5_2/dw/scale does not need backward computation.
-I0511 11:48:52.039599  4597 net.cpp:338] conv5_2/dw/bn does not need backward computation.
-I0511 11:48:52.039603  4597 net.cpp:338] conv5_2/dw does not need backward computation.
-I0511 11:48:52.039609  4597 net.cpp:338] relu5_1/sep does not need backward computation.
-I0511 11:48:52.039613  4597 net.cpp:338] conv5_1/sep/scale does not need backward computation.
-I0511 11:48:52.039618  4597 net.cpp:338] conv5_1/sep/bn does not need backward computation.
-I0511 11:48:52.039623  4597 net.cpp:338] conv5_1/sep does not need backward computation.
-I0511 11:48:52.039628  4597 net.cpp:338] relu5_1/dw does not need backward computation.
-I0511 11:48:52.039633  4597 net.cpp:338] conv5_1/dw/scale does not need backward computation.
-I0511 11:48:52.039638  4597 net.cpp:338] conv5_1/dw/bn does not need backward computation.
-I0511 11:48:52.039641  4597 net.cpp:338] conv5_1/dw does not need backward computation.
-I0511 11:48:52.039646  4597 net.cpp:338] relu4_2/sep does not need backward computation.
-I0511 11:48:52.039650  4597 net.cpp:338] conv4_2/sep/scale does not need backward computation.
-I0511 11:48:52.039655  4597 net.cpp:338] conv4_2/sep/bn does not need backward computation.
-I0511 11:48:52.039660  4597 net.cpp:338] conv4_2/sep does not need backward computation.
-I0511 11:48:52.039665  4597 net.cpp:338] relu4_2/dw does not need backward computation.
-I0511 11:48:52.039669  4597 net.cpp:338] conv4_2/dw/scale does not need backward computation.
-I0511 11:48:52.039674  4597 net.cpp:338] conv4_2/dw/bn does not need backward computation.
-I0511 11:48:52.039678  4597 net.cpp:338] conv4_2/dw does not need backward computation.
-I0511 11:48:52.039683  4597 net.cpp:338] relu4_1/sep does not need backward computation.
-I0511 11:48:52.039687  4597 net.cpp:338] conv4_1/sep/scale does not need backward computation.
-I0511 11:48:52.039692  4597 net.cpp:338] conv4_1/sep/bn does not need backward computation.
-I0511 11:48:52.039697  4597 net.cpp:338] conv4_1/sep does not need backward computation.
-I0511 11:48:52.039705  4597 net.cpp:338] relu4_1/dw does not need backward computation.
-I0511 11:48:52.039710  4597 net.cpp:338] conv4_1/dw/scale does not need backward computation.
-I0511 11:48:52.039716  4597 net.cpp:338] conv4_1/dw/bn does not need backward computation.
-I0511 11:48:52.039719  4597 net.cpp:338] conv4_1/dw does not need backward computation.
-I0511 11:48:52.039724  4597 net.cpp:338] relu3_2/sep does not need backward computation.
-I0511 11:48:52.039728  4597 net.cpp:338] conv3_2/sep/scale does not need backward computation.
-I0511 11:48:52.039733  4597 net.cpp:338] conv3_2/sep/bn does not need backward computation.
-I0511 11:48:52.039738  4597 net.cpp:338] conv3_2/sep does not need backward computation.
-I0511 11:48:52.039743  4597 net.cpp:338] relu3_2/dw does not need backward computation.
-I0511 11:48:52.039747  4597 net.cpp:338] conv3_2/dw/scale does not need backward computation.
-I0511 11:48:52.039752  4597 net.cpp:338] conv3_2/dw/bn does not need backward computation.
-I0511 11:48:52.039757  4597 net.cpp:338] conv3_2/dw does not need backward computation.
-I0511 11:48:52.039762  4597 net.cpp:338] relu3_1/sep does not need backward computation.
-I0511 11:48:52.039765  4597 net.cpp:338] conv3_1/sep/scale does not need backward computation.
-I0511 11:48:52.039769  4597 net.cpp:338] conv3_1/sep/bn does not need backward computation.
-I0511 11:48:52.039774  4597 net.cpp:338] conv3_1/sep does not need backward computation.
-I0511 11:48:52.039778  4597 net.cpp:338] relu3_1/dw does not need backward computation.
-I0511 11:48:52.039783  4597 net.cpp:338] conv3_1/dw/scale does not need backward computation.
-I0511 11:48:52.039788  4597 net.cpp:338] conv3_1/dw/bn does not need backward computation.
-I0511 11:48:52.039793  4597 net.cpp:338] conv3_1/dw does not need backward computation.
-I0511 11:48:52.039796  4597 net.cpp:338] relu2_2/sep does not need backward computation.
-I0511 11:48:52.039801  4597 net.cpp:338] conv2_2/sep/scale does not need backward computation.
-I0511 11:48:52.039806  4597 net.cpp:338] conv2_2/sep/bn does not need backward computation.
-I0511 11:48:52.039810  4597 net.cpp:338] conv2_2/sep does not need backward computation.
-I0511 11:48:52.039815  4597 net.cpp:338] relu2_2/dw does not need backward computation.
-I0511 11:48:52.039819  4597 net.cpp:338] conv2_2/dw/scale does not need backward computation.
-I0511 11:48:52.039824  4597 net.cpp:338] conv2_2/dw/bn does not need backward computation.
-I0511 11:48:52.039829  4597 net.cpp:338] conv2_2/dw does not need backward computation.
-I0511 11:48:52.039834  4597 net.cpp:338] relu2_1/sep does not need backward computation.
-I0511 11:48:52.039839  4597 net.cpp:338] conv2_1/sep/scale does not need backward computation.
-I0511 11:48:52.039842  4597 net.cpp:338] conv2_1/sep/bn does not need backward computation.
-I0511 11:48:52.039847  4597 net.cpp:338] conv2_1/sep does not need backward computation.
-I0511 11:48:52.039851  4597 net.cpp:338] relu2_1/dw does not need backward computation.
-I0511 11:48:52.039855  4597 net.cpp:338] conv2_1/dw/scale does not need backward computation.
-I0511 11:48:52.039860  4597 net.cpp:338] conv2_1/dw/bn does not need backward computation.
-I0511 11:48:52.039863  4597 net.cpp:338] conv2_1/dw does not need backward computation.
-I0511 11:48:52.039867  4597 net.cpp:338] relu1 does not need backward computation.
-I0511 11:48:52.039871  4597 net.cpp:338] conv1/scale does not need backward computation.
-I0511 11:48:52.039875  4597 net.cpp:338] conv1/bn does not need backward computation.
-I0511 11:48:52.039880  4597 net.cpp:338] conv1 does not need backward computation.
-I0511 11:48:52.039883  4597 net.cpp:338] data/bias does not need backward computation.
-I0511 11:48:52.039888  4597 net.cpp:338] data_data_0_split does not need backward computation.
-I0511 11:48:52.039893  4597 net.cpp:338] data does not need backward computation.
-I0511 11:48:52.039897  4597 net.cpp:380] This network produces output detection_eval
-I0511 11:48:52.040083  4597 net.cpp:403] Top memory (TEST) required for data: 1352267864 diff: 1352267864
-I0511 11:48:52.040091  4597 net.cpp:406] Bottom memory (TEST) required for data: 1352267440 diff: 1352267440
-I0511 11:48:52.040100  4597 net.cpp:409] Shared (in-place) memory (TEST) by data: 848936960 diff: 848936960
-I0511 11:48:52.040104  4597 net.cpp:412] Parameters memory (TEST) required for data: 9462808 diff: 9462808
-I0511 11:48:52.040108  4597 net.cpp:415] Parameters shared memory (TEST) by data: 0 diff: 0
-I0511 11:48:52.040112  4597 net.cpp:421] Network initialization done.
-I0511 11:48:52.047904  4597 net.cpp:1144] Copying source layer data Type:AnnotatedData #blobs=0
-I0511 11:48:52.047925  4597 net.cpp:1144] Copying source layer data_data_0_split Type:Split #blobs=0
-I0511 11:48:52.047929  4597 net.cpp:1144] Copying source layer data/bias Type:Bias #blobs=1
-I0511 11:48:52.047973  4597 net.cpp:1144] Copying source layer conv1 Type:Convolution #blobs=1
-I0511 11:48:52.047991  4597 net.cpp:1144] Copying source layer conv1/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048012  4597 net.cpp:1144] Copying source layer conv1/scale Type:Scale #blobs=2
-I0511 11:48:52.048028  4597 net.cpp:1144] Copying source layer relu1 Type:ReLU #blobs=0
-I0511 11:48:52.048033  4597 net.cpp:1144] Copying source layer conv2_1/dw Type:Convolution #blobs=1
-I0511 11:48:52.048043  4597 net.cpp:1144] Copying source layer conv2_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048063  4597 net.cpp:1144] Copying source layer conv2_1/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048079  4597 net.cpp:1144] Copying source layer relu2_1/dw Type:ReLU #blobs=0
-I0511 11:48:52.048084  4597 net.cpp:1144] Copying source layer conv2_1/sep Type:Convolution #blobs=1
-I0511 11:48:52.048094  4597 net.cpp:1144] Copying source layer conv2_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048113  4597 net.cpp:1144] Copying source layer conv2_1/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048128  4597 net.cpp:1144] Copying source layer relu2_1/sep Type:ReLU #blobs=0
-I0511 11:48:52.048132  4597 net.cpp:1144] Copying source layer conv2_2/dw Type:Convolution #blobs=1
-I0511 11:48:52.048141  4597 net.cpp:1144] Copying source layer conv2_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048158  4597 net.cpp:1144] Copying source layer conv2_2/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048174  4597 net.cpp:1144] Copying source layer relu2_2/dw Type:ReLU #blobs=0
-I0511 11:48:52.048179  4597 net.cpp:1144] Copying source layer conv2_2/sep Type:Convolution #blobs=1
-I0511 11:48:52.048192  4597 net.cpp:1144] Copying source layer conv2_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048211  4597 net.cpp:1144] Copying source layer conv2_2/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048229  4597 net.cpp:1144] Copying source layer relu2_2/sep Type:ReLU #blobs=0
-I0511 11:48:52.048234  4597 net.cpp:1144] Copying source layer conv3_1/dw Type:Convolution #blobs=1
-I0511 11:48:52.048244  4597 net.cpp:1144] Copying source layer conv3_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048264  4597 net.cpp:1144] Copying source layer conv3_1/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048280  4597 net.cpp:1144] Copying source layer relu3_1/dw Type:ReLU #blobs=0
-I0511 11:48:52.048285  4597 net.cpp:1144] Copying source layer conv3_1/sep Type:Convolution #blobs=1
-I0511 11:48:52.048300  4597 net.cpp:1144] Copying source layer conv3_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048338  4597 net.cpp:1144] Copying source layer conv3_1/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048365  4597 net.cpp:1144] Copying source layer relu3_1/sep Type:ReLU #blobs=0
-I0511 11:48:52.048377  4597 net.cpp:1144] Copying source layer conv3_2/dw Type:Convolution #blobs=1
-I0511 11:48:52.048394  4597 net.cpp:1144] Copying source layer conv3_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048420  4597 net.cpp:1144] Copying source layer conv3_2/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048441  4597 net.cpp:1144] Copying source layer relu3_2/dw Type:ReLU #blobs=0
-I0511 11:48:52.048452  4597 net.cpp:1144] Copying source layer conv3_2/sep Type:Convolution #blobs=1
-I0511 11:48:52.048477  4597 net.cpp:1144] Copying source layer conv3_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048512  4597 net.cpp:1144] Copying source layer conv3_2/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048576  4597 net.cpp:1144] Copying source layer relu3_2/sep Type:ReLU #blobs=0
-I0511 11:48:52.048589  4597 net.cpp:1144] Copying source layer conv4_1/dw Type:Convolution #blobs=1
-I0511 11:48:52.048606  4597 net.cpp:1144] Copying source layer conv4_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048631  4597 net.cpp:1144] Copying source layer conv4_1/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048655  4597 net.cpp:1144] Copying source layer relu4_1/dw Type:ReLU #blobs=0
-I0511 11:48:52.048666  4597 net.cpp:1144] Copying source layer conv4_1/sep Type:Convolution #blobs=1
-I0511 11:48:52.048691  4597 net.cpp:1144] Copying source layer conv4_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048717  4597 net.cpp:1144] Copying source layer conv4_1/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048740  4597 net.cpp:1144] Copying source layer relu4_1/sep Type:ReLU #blobs=0
-I0511 11:48:52.048750  4597 net.cpp:1144] Copying source layer conv4_2/dw Type:Convolution #blobs=1
-I0511 11:48:52.048768  4597 net.cpp:1144] Copying source layer conv4_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048794  4597 net.cpp:1144] Copying source layer conv4_2/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.048815  4597 net.cpp:1144] Copying source layer relu4_2/dw Type:ReLU #blobs=0
-I0511 11:48:52.048827  4597 net.cpp:1144] Copying source layer conv4_2/sep Type:Convolution #blobs=1
-I0511 11:48:52.048866  4597 net.cpp:1144] Copying source layer conv4_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048892  4597 net.cpp:1144] Copying source layer conv4_2/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.048921  4597 net.cpp:1144] Copying source layer relu4_2/sep Type:ReLU #blobs=0
-I0511 11:48:52.048933  4597 net.cpp:1144] Copying source layer conv5_1/dw Type:Convolution #blobs=1
-I0511 11:48:52.048951  4597 net.cpp:1144] Copying source layer conv5_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.048977  4597 net.cpp:1144] Copying source layer conv5_1/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049000  4597 net.cpp:1144] Copying source layer relu5_1/dw Type:ReLU #blobs=0
-I0511 11:48:52.049012  4597 net.cpp:1144] Copying source layer conv5_1/sep Type:Convolution #blobs=1
-I0511 11:48:52.049068  4597 net.cpp:1144] Copying source layer conv5_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049089  4597 net.cpp:1144] Copying source layer conv5_1/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049105  4597 net.cpp:1144] Copying source layer relu5_1/sep Type:ReLU #blobs=0
-I0511 11:48:52.049111  4597 net.cpp:1144] Copying source layer conv5_2/dw Type:Convolution #blobs=1
-I0511 11:48:52.049123  4597 net.cpp:1144] Copying source layer conv5_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049142  4597 net.cpp:1144] Copying source layer conv5_2/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049157  4597 net.cpp:1144] Copying source layer relu5_2/dw Type:ReLU #blobs=0
-I0511 11:48:52.049162  4597 net.cpp:1144] Copying source layer conv5_2/sep Type:Convolution #blobs=1
-I0511 11:48:52.049208  4597 net.cpp:1144] Copying source layer conv5_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049229  4597 net.cpp:1144] Copying source layer conv5_2/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049244  4597 net.cpp:1144] Copying source layer relu5_2/sep Type:ReLU #blobs=0
-I0511 11:48:52.049250  4597 net.cpp:1144] Copying source layer conv5_3/dw Type:Convolution #blobs=1
-I0511 11:48:52.049262  4597 net.cpp:1144] Copying source layer conv5_3/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049280  4597 net.cpp:1144] Copying source layer conv5_3/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049298  4597 net.cpp:1144] Copying source layer relu5_3/dw Type:ReLU #blobs=0
-I0511 11:48:52.049302  4597 net.cpp:1144] Copying source layer conv5_3/sep Type:Convolution #blobs=1
-I0511 11:48:52.049358  4597 net.cpp:1144] Copying source layer conv5_3/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049381  4597 net.cpp:1144] Copying source layer conv5_3/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049397  4597 net.cpp:1144] Copying source layer relu5_3/sep Type:ReLU #blobs=0
-I0511 11:48:52.049412  4597 net.cpp:1144] Copying source layer conv5_4/dw Type:Convolution #blobs=1
-I0511 11:48:52.049424  4597 net.cpp:1144] Copying source layer conv5_4/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049444  4597 net.cpp:1144] Copying source layer conv5_4/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049460  4597 net.cpp:1144] Copying source layer relu5_4/dw Type:ReLU #blobs=0
-I0511 11:48:52.049466  4597 net.cpp:1144] Copying source layer conv5_4/sep Type:Convolution #blobs=1
-I0511 11:48:52.049511  4597 net.cpp:1144] Copying source layer conv5_4/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049535  4597 net.cpp:1144] Copying source layer conv5_4/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049551  4597 net.cpp:1144] Copying source layer relu5_4/sep Type:ReLU #blobs=0
-I0511 11:48:52.049556  4597 net.cpp:1144] Copying source layer conv5_5/dw Type:Convolution #blobs=1
-I0511 11:48:52.049567  4597 net.cpp:1144] Copying source layer conv5_5/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049588  4597 net.cpp:1144] Copying source layer conv5_5/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049605  4597 net.cpp:1144] Copying source layer relu5_5/dw Type:ReLU #blobs=0
-I0511 11:48:52.049612  4597 net.cpp:1144] Copying source layer conv5_5/sep Type:Convolution #blobs=1
-I0511 11:48:52.049654  4597 net.cpp:1144] Copying source layer conv5_5/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049676  4597 net.cpp:1144] Copying source layer conv5_5/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049693  4597 net.cpp:1144] Copying source layer relu5_5/sep Type:ReLU #blobs=0
-I0511 11:48:52.049700  4597 net.cpp:1144] Copying source layer conv5_5/sep_relu5_5/sep_0_split Type:Split #blobs=0
-I0511 11:48:52.049705  4597 net.cpp:1144] Copying source layer conv5_6/dw Type:Convolution #blobs=1
-I0511 11:48:52.049717  4597 net.cpp:1144] Copying source layer conv5_6/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049738  4597 net.cpp:1144] Copying source layer conv5_6/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049756  4597 net.cpp:1144] Copying source layer relu5_6/dw Type:ReLU #blobs=0
-I0511 11:48:52.049762  4597 net.cpp:1144] Copying source layer conv5_6/sep Type:Convolution #blobs=1
-I0511 11:48:52.049834  4597 net.cpp:1144] Copying source layer conv5_6/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049860  4597 net.cpp:1144] Copying source layer conv5_6/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.049876  4597 net.cpp:1144] Copying source layer relu5_6/sep Type:ReLU #blobs=0
-I0511 11:48:52.049882  4597 net.cpp:1144] Copying source layer conv6/dw Type:Convolution #blobs=1
-I0511 11:48:52.049896  4597 net.cpp:1144] Copying source layer conv6/dw/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.049916  4597 net.cpp:1144] Copying source layer conv6/dw/scale Type:Scale #blobs=2
-I0511 11:48:52.049933  4597 net.cpp:1144] Copying source layer relu6/dw Type:ReLU #blobs=0
-I0511 11:48:52.049939  4597 net.cpp:1144] Copying source layer conv6/sep Type:Convolution #blobs=1
-I0511 11:48:52.050068  4597 net.cpp:1144] Copying source layer conv6/sep/bn Type:BatchNorm #blobs=3
-I0511 11:48:52.050092  4597 net.cpp:1144] Copying source layer conv6/sep/scale Type:Scale #blobs=2
-I0511 11:48:52.050107  4597 net.cpp:1144] Copying source layer relu6/sep Type:ReLU #blobs=0
-I0511 11:48:52.050113  4597 net.cpp:1144] Copying source layer conv6/sep_relu6/sep_0_split Type:Split #blobs=0
-I0511 11:48:52.050117  4597 net.cpp:1144] Copying source layer pool6 Type:Pooling #blobs=0
-I0511 11:48:52.050122  4597 net.cpp:1144] Copying source layer pool6_pool6_0_split Type:Split #blobs=0
-I0511 11:48:52.050127  4597 net.cpp:1144] Copying source layer pool7 Type:Pooling #blobs=0
-I0511 11:48:52.050130  4597 net.cpp:1144] Copying source layer pool7_pool7_0_split Type:Split #blobs=0
-I0511 11:48:52.050135  4597 net.cpp:1144] Copying source layer pool8 Type:Pooling #blobs=0
-I0511 11:48:52.050139  4597 net.cpp:1144] Copying source layer ctx_output1/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.050209  4597 net.cpp:1144] Copying source layer ctx_output1/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050246  4597 net.cpp:1144] Copying source layer ctx_output1/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050253  4597 net.cpp:1144] Copying source layer ctx_output1 Type:Convolution #blobs=2
-I0511 11:48:52.050271  4597 net.cpp:1144] Copying source layer ctx_output1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050297  4597 net.cpp:1144] Copying source layer ctx_output1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050302  4597 net.cpp:1144] Copying source layer ctx_output1_ctx_output1/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.050307  4597 net.cpp:1144] Copying source layer ctx_output2/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.050436  4597 net.cpp:1144] Copying source layer ctx_output2/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050464  4597 net.cpp:1144] Copying source layer ctx_output2/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050470  4597 net.cpp:1144] Copying source layer ctx_output2 Type:Convolution #blobs=2
-I0511 11:48:52.050487  4597 net.cpp:1144] Copying source layer ctx_output2/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050514  4597 net.cpp:1144] Copying source layer ctx_output2/relu Type:ReLU #blobs=0
-I0511 11:48:52.050520  4597 net.cpp:1144] Copying source layer ctx_output2_ctx_output2/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.050525  4597 net.cpp:1144] Copying source layer ctx_output3/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.050652  4597 net.cpp:1144] Copying source layer ctx_output3/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050681  4597 net.cpp:1144] Copying source layer ctx_output3/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050688  4597 net.cpp:1144] Copying source layer ctx_output3 Type:Convolution #blobs=2
-I0511 11:48:52.050704  4597 net.cpp:1144] Copying source layer ctx_output3/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050730  4597 net.cpp:1144] Copying source layer ctx_output3/relu Type:ReLU #blobs=0
-I0511 11:48:52.050736  4597 net.cpp:1144] Copying source layer ctx_output3_ctx_output3/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.050740  4597 net.cpp:1144] Copying source layer ctx_output4/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.050871  4597 net.cpp:1144] Copying source layer ctx_output4/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.050900  4597 net.cpp:1144] Copying source layer ctx_output4/1x1/relu Type:ReLU #blobs=0
-I0511 11:48:52.050906  4597 net.cpp:1144] Copying source layer ctx_output4 Type:Convolution #blobs=2
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-I0511 11:48:52.050956  4597 net.cpp:1144] Copying source layer ctx_output4_ctx_output4/relu_0_split Type:Split #blobs=0
-I0511 11:48:52.050961  4597 net.cpp:1144] Copying source layer ctx_output5/1x1 Type:Convolution #blobs=2
-I0511 11:48:52.051087  4597 net.cpp:1144] Copying source layer ctx_output5/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:48:52.051113  4597 net.cpp:1144] Copying source layer ctx_output5/1x1/relu Type:ReLU #blobs=0
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-I0511 11:48:52.051167  4597 net.cpp:1144] Copying source layer ctx_output5/relu Type:ReLU #blobs=0
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-I0511 11:48:52.051177  4597 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc Type:Convolution #blobs=2
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-I0511 11:48:52.051607  4597 net.cpp:1136] Ignoring source layer mbox_loss
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-I0511 11:49:27.126497  4597 caffe.cpp:501] detection_eval = -1
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-I0511 11:49:27.126543  4597 caffe.cpp:501] detection_eval = -1
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-I0511 11:49:27.126600  4597 caffe.cpp:501] detection_eval = 0.679435
-I0511 11:49:27.126616  4597 caffe.cpp:501] detection_eval = -1
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-I0511 11:49:27.126672  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.126687  4597 caffe.cpp:501] detection_eval = -1
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-I0511 11:49:27.126736  4597 caffe.cpp:501] detection_eval = 4
-I0511 11:49:27.126750  4597 caffe.cpp:501] detection_eval = 0.530242
-I0511 11:49:27.126765  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126780  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126793  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126807  4597 caffe.cpp:501] detection_eval = 5
-I0511 11:49:27.126821  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.126835  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126849  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126863  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126878  4597 caffe.cpp:501] detection_eval = 6
-I0511 11:49:27.126893  4597 caffe.cpp:501] detection_eval = 0.429435
-I0511 11:49:27.126906  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126920  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126935  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126948  4597 caffe.cpp:501] detection_eval = 7
-I0511 11:49:27.126962  4597 caffe.cpp:501] detection_eval = 2.43548
-I0511 11:49:27.126976  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.126991  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127004  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127018  4597 caffe.cpp:501] detection_eval = 8
-I0511 11:49:27.127033  4597 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:49:27.127048  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127065  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127079  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127094  4597 caffe.cpp:501] detection_eval = 9
-I0511 11:49:27.127108  4597 caffe.cpp:501] detection_eval = 1.53226
-I0511 11:49:27.127122  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127136  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127151  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127164  4597 caffe.cpp:501] detection_eval = 10
-I0511 11:49:27.127179  4597 caffe.cpp:501] detection_eval = 0.491935
-I0511 11:49:27.127193  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127208  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127223  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127236  4597 caffe.cpp:501] detection_eval = 11
-I0511 11:49:27.127250  4597 caffe.cpp:501] detection_eval = 0.417339
-I0511 11:49:27.127264  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127287  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127301  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127315  4597 caffe.cpp:501] detection_eval = 12
-I0511 11:49:27.127331  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.127344  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127358  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127372  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127387  4597 caffe.cpp:501] detection_eval = 13
-I0511 11:49:27.127400  4597 caffe.cpp:501] detection_eval = 0.703629
-I0511 11:49:27.127414  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127429  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127442  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127457  4597 caffe.cpp:501] detection_eval = 14
-I0511 11:49:27.127471  4597 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:49:27.127485  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127499  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127513  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127526  4597 caffe.cpp:501] detection_eval = 15
-I0511 11:49:27.127542  4597 caffe.cpp:501] detection_eval = 9.13306
-I0511 11:49:27.127555  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127569  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127583  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127598  4597 caffe.cpp:501] detection_eval = 16
-I0511 11:49:27.127612  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.127626  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127645  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127658  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127672  4597 caffe.cpp:501] detection_eval = 17
-I0511 11:49:27.127686  4597 caffe.cpp:501] detection_eval = 0.487903
-I0511 11:49:27.127701  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127714  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127728  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127743  4597 caffe.cpp:501] detection_eval = 18
-I0511 11:49:27.127758  4597 caffe.cpp:501] detection_eval = 0.483871
-I0511 11:49:27.127771  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127785  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127799  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127813  4597 caffe.cpp:501] detection_eval = 19
-I0511 11:49:27.127827  4597 caffe.cpp:501] detection_eval = 0.570565
-I0511 11:49:27.127841  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127856  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127869  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127883  4597 caffe.cpp:501] detection_eval = 20
-I0511 11:49:27.127897  4597 caffe.cpp:501] detection_eval = 0.620968
-I0511 11:49:27.127912  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127925  4597 caffe.cpp:501] detection_eval = -1
-I0511 11:49:27.127939  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.127954  4597 caffe.cpp:501] detection_eval = 3.19556
-I0511 11:49:27.127967  4597 caffe.cpp:501] detection_eval = 0.155836
-I0511 11:49:27.127985  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.128000  4597 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:49:27.128013  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128027  4597 caffe.cpp:501] detection_eval = 3.58871
-I0511 11:49:27.128041  4597 caffe.cpp:501] detection_eval = 0.100137
-I0511 11:49:27.128056  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.128069  4597 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:49:27.128083  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128098  4597 caffe.cpp:501] detection_eval = 3.79637
-I0511 11:49:27.128111  4597 caffe.cpp:501] detection_eval = 0.0758775
-I0511 11:49:27.128126  4597 caffe.cpp:501] detection_eval = 0.0403226
-I0511 11:49:27.128140  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.128154  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128168  4597 caffe.cpp:501] detection_eval = 3.92339
-I0511 11:49:27.128187  4597 caffe.cpp:501] detection_eval = 0.0664227
-I0511 11:49:27.128201  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.128216  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.128231  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128244  4597 caffe.cpp:501] detection_eval = 4.0746
-I0511 11:49:27.128258  4597 caffe.cpp:501] detection_eval = 0.0578036
-I0511 11:49:27.128273  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.128286  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.128300  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.128314  4597 caffe.cpp:501] detection_eval = 4.1875
-I0511 11:49:27.128329  4597 caffe.cpp:501] detection_eval = 0.0488079
-I0511 11:49:27.128343  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.128357  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.128371  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128386  4597 caffe.cpp:501] detection_eval = 4.26411
-I0511 11:49:27.128401  4597 caffe.cpp:501] detection_eval = 0.0514011
-I0511 11:49:27.128414  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.128428  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.128443  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128458  4597 caffe.cpp:501] detection_eval = 4.375
-I0511 11:49:27.128470  4597 caffe.cpp:501] detection_eval = 0.0565917
-I0511 11:49:27.128484  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.128499  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.128516  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128537  4597 caffe.cpp:501] detection_eval = 4.4375
-I0511 11:49:27.128553  4597 caffe.cpp:501] detection_eval = 0.0425472
-I0511 11:49:27.128567  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.128582  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.128595  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128609  4597 caffe.cpp:501] detection_eval = 4.49798
-I0511 11:49:27.128623  4597 caffe.cpp:501] detection_eval = 0.0395933
-I0511 11:49:27.128638  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.128653  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.128666  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128680  4597 caffe.cpp:501] detection_eval = 4.54637
-I0511 11:49:27.128695  4597 caffe.cpp:501] detection_eval = 0.0453336
-I0511 11:49:27.128708  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.128722  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.128736  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128751  4597 caffe.cpp:501] detection_eval = 4.65323
-I0511 11:49:27.128765  4597 caffe.cpp:501] detection_eval = 0.0416205
-I0511 11:49:27.128778  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.128793  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.128806  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.128820  4597 caffe.cpp:501] detection_eval = 4.77016
-I0511 11:49:27.128837  4597 caffe.cpp:501] detection_eval = 0.0486904
-I0511 11:49:27.128852  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.128866  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.128880  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.128895  4597 caffe.cpp:501] detection_eval = 4.80444
-I0511 11:49:27.128908  4597 caffe.cpp:501] detection_eval = 0.0418979
-I0511 11:49:27.128922  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.128937  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.128950  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.128964  4597 caffe.cpp:501] detection_eval = 4.85685
-I0511 11:49:27.128978  4597 caffe.cpp:501] detection_eval = 0.042125
-I0511 11:49:27.128993  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.129006  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.129021  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129035  4597 caffe.cpp:501] detection_eval = 4.87702
-I0511 11:49:27.129055  4597 caffe.cpp:501] detection_eval = 0.0416501
-I0511 11:49:27.129070  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.129083  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.129097  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129112  4597 caffe.cpp:501] detection_eval = 4.95968
-I0511 11:49:27.129124  4597 caffe.cpp:501] detection_eval = 0.037758
-I0511 11:49:27.129137  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129148  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.129159  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129171  4597 caffe.cpp:501] detection_eval = 5.02218
-I0511 11:49:27.129184  4597 caffe.cpp:501] detection_eval = 0.0439259
-I0511 11:49:27.129195  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.129207  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.129218  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129230  4597 caffe.cpp:501] detection_eval = 5.09073
-I0511 11:49:27.129242  4597 caffe.cpp:501] detection_eval = 0.0430185
-I0511 11:49:27.129254  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.129266  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.129277  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129289  4597 caffe.cpp:501] detection_eval = 5.18548
-I0511 11:49:27.129302  4597 caffe.cpp:501] detection_eval = 0.0427662
-I0511 11:49:27.129312  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.129326  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.129338  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129350  4597 caffe.cpp:501] detection_eval = 5.26008
-I0511 11:49:27.129362  4597 caffe.cpp:501] detection_eval = 0.0448038
-I0511 11:49:27.129374  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129387  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.129400  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129413  4597 caffe.cpp:501] detection_eval = 5.33669
-I0511 11:49:27.129426  4597 caffe.cpp:501] detection_eval = 0.0424197
-I0511 11:49:27.129439  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.129452  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.129465  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.129478  4597 caffe.cpp:501] detection_eval = 5.39718
-I0511 11:49:27.129490  4597 caffe.cpp:501] detection_eval = 0.0494331
-I0511 11:49:27.129503  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.129516  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.129528  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.129541  4597 caffe.cpp:501] detection_eval = 5.44153
-I0511 11:49:27.129554  4597 caffe.cpp:501] detection_eval = 0.0412754
-I0511 11:49:27.129567  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129580  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.129592  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.129609  4597 caffe.cpp:501] detection_eval = 5.50202
-I0511 11:49:27.129622  4597 caffe.cpp:501] detection_eval = 0.0410487
-I0511 11:49:27.129636  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129648  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.129662  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.129673  4597 caffe.cpp:501] detection_eval = 5.56452
-I0511 11:49:27.129686  4597 caffe.cpp:501] detection_eval = 0.0476251
-I0511 11:49:27.129699  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.129714  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.129726  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.129739  4597 caffe.cpp:501] detection_eval = 5.61694
-I0511 11:49:27.129752  4597 caffe.cpp:501] detection_eval = 0.0399715
-I0511 11:49:27.129765  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.129778  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.129791  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.129809  4597 caffe.cpp:501] detection_eval = 5.65726
-I0511 11:49:27.129823  4597 caffe.cpp:501] detection_eval = 0.0359377
-I0511 11:49:27.129837  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129850  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.129864  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.129878  4597 caffe.cpp:501] detection_eval = 5.71976
-I0511 11:49:27.129892  4597 caffe.cpp:501] detection_eval = 0.0411324
-I0511 11:49:27.129906  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.129921  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.129935  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.129951  4597 caffe.cpp:501] detection_eval = 5.80242
-I0511 11:49:27.129963  4597 caffe.cpp:501] detection_eval = 0.0412029
-I0511 11:49:27.129977  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.129992  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.130005  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130019  4597 caffe.cpp:501] detection_eval = 5.89315
-I0511 11:49:27.130033  4597 caffe.cpp:501] detection_eval = 0.0388007
-I0511 11:49:27.130048  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.130062  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.130076  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130090  4597 caffe.cpp:501] detection_eval = 5.94556
-I0511 11:49:27.130103  4597 caffe.cpp:501] detection_eval = 0.0353795
-I0511 11:49:27.130120  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.130136  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.130149  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130163  4597 caffe.cpp:501] detection_eval = 6.04637
-I0511 11:49:27.130177  4597 caffe.cpp:501] detection_eval = 0.0426654
-I0511 11:49:27.130192  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.130205  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.130219  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130231  4597 caffe.cpp:501] detection_eval = 6.15121
-I0511 11:49:27.130242  4597 caffe.cpp:501] detection_eval = 0.038799
-I0511 11:49:27.130254  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.130264  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.130276  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.130290  4597 caffe.cpp:501] detection_eval = 6.18347
-I0511 11:49:27.130303  4597 caffe.cpp:501] detection_eval = 0.0411229
-I0511 11:49:27.130316  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.130331  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.130343  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.130357  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.130372  4597 caffe.cpp:501] detection_eval = 0.0462864
-I0511 11:49:27.130385  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.130399  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.130414  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.130425  4597 caffe.cpp:501] detection_eval = 6.36089
-I0511 11:49:27.130436  4597 caffe.cpp:501] detection_eval = 0.0456047
-I0511 11:49:27.130447  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.130460  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.130475  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130486  4597 caffe.cpp:501] detection_eval = 6.39718
-I0511 11:49:27.130501  4597 caffe.cpp:501] detection_eval = 0.0444649
-I0511 11:49:27.130514  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.130527  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.130542  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130555  4597 caffe.cpp:501] detection_eval = 6.45968
-I0511 11:49:27.130569  4597 caffe.cpp:501] detection_eval = 0.03753
-I0511 11:49:27.130584  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.130597  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.130616  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130631  4597 caffe.cpp:501] detection_eval = 6.52823
-I0511 11:49:27.130645  4597 caffe.cpp:501] detection_eval = 0.0426885
-I0511 11:49:27.130659  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.130673  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.130687  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130702  4597 caffe.cpp:501] detection_eval = 6.62903
-I0511 11:49:27.130715  4597 caffe.cpp:501] detection_eval = 0.0381812
-I0511 11:49:27.130729  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.130744  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.130758  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130771  4597 caffe.cpp:501] detection_eval = 6.72984
-I0511 11:49:27.130785  4597 caffe.cpp:501] detection_eval = 0.0387956
-I0511 11:49:27.130800  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.130813  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.130827  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130841  4597 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:49:27.130856  4597 caffe.cpp:501] detection_eval = 0.040319
-I0511 11:49:27.130869  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.130883  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.130897  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130911  4597 caffe.cpp:501] detection_eval = 6.85484
-I0511 11:49:27.130928  4597 caffe.cpp:501] detection_eval = 0.0379203
-I0511 11:49:27.130941  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.130956  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.130971  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.130985  4597 caffe.cpp:501] detection_eval = 6.93145
-I0511 11:49:27.131000  4597 caffe.cpp:501] detection_eval = 0.0380551
-I0511 11:49:27.131014  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.131028  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.131042  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.131057  4597 caffe.cpp:501] detection_eval = 7.07056
-I0511 11:49:27.131072  4597 caffe.cpp:501] detection_eval = 0.0413856
-I0511 11:49:27.131085  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.131099  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131114  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.131127  4597 caffe.cpp:501] detection_eval = 7.19556
-I0511 11:49:27.131141  4597 caffe.cpp:501] detection_eval = 0.0445879
-I0511 11:49:27.131155  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.131170  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.131183  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131198  4597 caffe.cpp:501] detection_eval = 7.21169
-I0511 11:49:27.131212  4597 caffe.cpp:501] detection_eval = 0.0456281
-I0511 11:49:27.131227  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.131244  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131258  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131273  4597 caffe.cpp:501] detection_eval = 7.26411
-I0511 11:49:27.131287  4597 caffe.cpp:501] detection_eval = 0.0398665
-I0511 11:49:27.131301  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.131316  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.131330  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131345  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.131358  4597 caffe.cpp:501] detection_eval = 0.0426693
-I0511 11:49:27.131372  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.131387  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.131402  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131415  4597 caffe.cpp:501] detection_eval = 7.49194
-I0511 11:49:27.131429  4597 caffe.cpp:501] detection_eval = 0.0411533
-I0511 11:49:27.131443  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.131464  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.131479  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131491  4597 caffe.cpp:501] detection_eval = 7.58669
-I0511 11:49:27.131505  4597 caffe.cpp:501] detection_eval = 0.0420787
-I0511 11:49:27.131520  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.131533  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.131547  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.131561  4597 caffe.cpp:501] detection_eval = 7.73185
-I0511 11:49:27.131575  4597 caffe.cpp:501] detection_eval = 0.0470093
-I0511 11:49:27.131589  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.131603  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131618  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131631  4597 caffe.cpp:501] detection_eval = 7.78427
-I0511 11:49:27.131645  4597 caffe.cpp:501] detection_eval = 0.0409579
-I0511 11:49:27.131659  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.131673  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.131687  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131701  4597 caffe.cpp:501] detection_eval = 7.89516
-I0511 11:49:27.131716  4597 caffe.cpp:501] detection_eval = 0.0434188
-I0511 11:49:27.131729  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.131743  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.131757  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131774  4597 caffe.cpp:501] detection_eval = 7.92944
-I0511 11:49:27.131788  4597 caffe.cpp:501] detection_eval = 0.0427699
-I0511 11:49:27.131803  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.131817  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131831  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131845  4597 caffe.cpp:501] detection_eval = 7.97177
-I0511 11:49:27.131860  4597 caffe.cpp:501] detection_eval = 0.0375143
-I0511 11:49:27.131872  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.131887  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.131901  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.131916  4597 caffe.cpp:501] detection_eval = 8.08266
-I0511 11:49:27.131929  4597 caffe.cpp:501] detection_eval = 0.0442452
-I0511 11:49:27.131943  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.131958  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.131971  4597 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:49:27.131985  4597 caffe.cpp:501] detection_eval = 8.16129
-I0511 11:49:27.131999  4597 caffe.cpp:501] detection_eval = 0.0438716
-I0511 11:49:27.132014  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.132027  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.132041  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132055  4597 caffe.cpp:501] detection_eval = 8.19556
-I0511 11:49:27.132069  4597 caffe.cpp:501] detection_eval = 0.0454496
-I0511 11:49:27.132086  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.132102  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.132115  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132129  4597 caffe.cpp:501] detection_eval = 8.25806
-I0511 11:49:27.132143  4597 caffe.cpp:501] detection_eval = 0.0422392
-I0511 11:49:27.132158  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.132171  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.132185  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132200  4597 caffe.cpp:501] detection_eval = 8.37903
-I0511 11:49:27.132213  4597 caffe.cpp:501] detection_eval = 0.0462827
-I0511 11:49:27.132226  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.132241  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.132254  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132268  4597 caffe.cpp:501] detection_eval = 8.44556
-I0511 11:49:27.132282  4597 caffe.cpp:501] detection_eval = 0.0395954
-I0511 11:49:27.132302  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.132318  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.132331  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132345  4597 caffe.cpp:501] detection_eval = 8.55847
-I0511 11:49:27.132359  4597 caffe.cpp:501] detection_eval = 0.04636
-I0511 11:49:27.132374  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.132387  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.132401  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.132416  4597 caffe.cpp:501] detection_eval = 8.63508
-I0511 11:49:27.132429  4597 caffe.cpp:501] detection_eval = 0.0432603
-I0511 11:49:27.132443  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.132457  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.132472  4597 caffe.cpp:501] detection_eval = 0.0342742
-I0511 11:49:27.132485  4597 caffe.cpp:501] detection_eval = 8.68548
-I0511 11:49:27.132499  4597 caffe.cpp:501] detection_eval = 0.0452855
-I0511 11:49:27.132513  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.132535  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.132550  4597 caffe.cpp:501] detection_eval = 0.0342742
-I0511 11:49:27.132562  4597 caffe.cpp:501] detection_eval = 8.75605
-I0511 11:49:27.132575  4597 caffe.cpp:501] detection_eval = 0.0379097
-I0511 11:49:27.132588  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.132602  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.132619  4597 caffe.cpp:501] detection_eval = 0.0362903
-I0511 11:49:27.132634  4597 caffe.cpp:501] detection_eval = 8.79435
-I0511 11:49:27.132647  4597 caffe.cpp:501] detection_eval = 0.0433688
-I0511 11:49:27.132661  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.132675  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.132689  4597 caffe.cpp:501] detection_eval = 0.0362903
-I0511 11:49:27.132704  4597 caffe.cpp:501] detection_eval = 8.89919
-I0511 11:49:27.132719  4597 caffe.cpp:501] detection_eval = 0.0470879
-I0511 11:49:27.132732  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.132746  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.132761  4597 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:49:27.132774  4597 caffe.cpp:501] detection_eval = 8.91935
-I0511 11:49:27.132788  4597 caffe.cpp:501] detection_eval = 0.0427316
-I0511 11:49:27.132802  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.132817  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.132830  4597 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:49:27.132845  4597 caffe.cpp:501] detection_eval = 9.03427
-I0511 11:49:27.132858  4597 caffe.cpp:501] detection_eval = 0.0459964
-I0511 11:49:27.132872  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.132886  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.132900  4597 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:49:27.132915  4597 caffe.cpp:501] detection_eval = 9.08468
-I0511 11:49:27.132930  4597 caffe.cpp:501] detection_eval = 0.0470074
-I0511 11:49:27.132946  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.132959  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.132973  4597 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:49:27.132987  4597 caffe.cpp:501] detection_eval = 9.16734
-I0511 11:49:27.133002  4597 caffe.cpp:501] detection_eval = 0.0436674
-I0511 11:49:27.133015  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.133029  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.133042  4597 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:49:27.133057  4597 caffe.cpp:501] detection_eval = 9.19153
-I0511 11:49:27.133070  4597 caffe.cpp:501] detection_eval = 0.0432862
-I0511 11:49:27.133085  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.133100  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.133113  4597 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:49:27.133127  4597 caffe.cpp:501] detection_eval = 9.25806
-I0511 11:49:27.133149  4597 caffe.cpp:501] detection_eval = 0.041063
-I0511 11:49:27.133163  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.133177  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133191  4597 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:49:27.133205  4597 caffe.cpp:501] detection_eval = 9.35484
-I0511 11:49:27.133219  4597 caffe.cpp:501] detection_eval = 0.0500139
-I0511 11:49:27.133234  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.133247  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.133261  4597 caffe.cpp:501] detection_eval = 0.0443548
-I0511 11:49:27.133275  4597 caffe.cpp:501] detection_eval = 9.36895
-I0511 11:49:27.133289  4597 caffe.cpp:501] detection_eval = 0.0411816
-I0511 11:49:27.133303  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.133317  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133332  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.133345  4597 caffe.cpp:501] detection_eval = 9.39315
-I0511 11:49:27.133359  4597 caffe.cpp:501] detection_eval = 0.0391489
-I0511 11:49:27.133373  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.133388  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.133401  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.133415  4597 caffe.cpp:501] detection_eval = 9.47379
-I0511 11:49:27.133428  4597 caffe.cpp:501] detection_eval = 0.0395449
-I0511 11:49:27.133442  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.133460  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133473  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.133487  4597 caffe.cpp:501] detection_eval = 9.55847
-I0511 11:49:27.133502  4597 caffe.cpp:501] detection_eval = 0.0414796
-I0511 11:49:27.133515  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.133529  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133543  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.133558  4597 caffe.cpp:501] detection_eval = 9.64919
-I0511 11:49:27.133571  4597 caffe.cpp:501] detection_eval = 0.041218
-I0511 11:49:27.133585  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.133599  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.133612  4597 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:49:27.133626  4597 caffe.cpp:501] detection_eval = 9.69153
-I0511 11:49:27.133641  4597 caffe.cpp:501] detection_eval = 0.0393077
-I0511 11:49:27.133654  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.133668  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.133682  4597 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:49:27.133697  4597 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:49:27.133710  4597 caffe.cpp:501] detection_eval = 0.0442791
-I0511 11:49:27.133724  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.133738  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.133752  4597 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:49:27.133769  4597 caffe.cpp:501] detection_eval = 9.875
-I0511 11:49:27.133783  4597 caffe.cpp:501] detection_eval = 0.0439502
-I0511 11:49:27.133797  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.133811  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.133826  4597 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:49:27.133839  4597 caffe.cpp:501] detection_eval = 9.90726
-I0511 11:49:27.133853  4597 caffe.cpp:501] detection_eval = 0.0385435
-I0511 11:49:27.133867  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.133882  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.133895  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.133909  4597 caffe.cpp:501] detection_eval = 9.96371
-I0511 11:49:27.133924  4597 caffe.cpp:501] detection_eval = 0.0408335
-I0511 11:49:27.133937  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.133951  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.133965  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.133985  4597 caffe.cpp:501] detection_eval = 10.0383
-I0511 11:49:27.133999  4597 caffe.cpp:501] detection_eval = 0.0407894
-I0511 11:49:27.134013  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.134027  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.134042  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.134055  4597 caffe.cpp:501] detection_eval = 10.1149
-I0511 11:49:27.134069  4597 caffe.cpp:501] detection_eval = 0.0367908
-I0511 11:49:27.134083  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.134099  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.134112  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.134126  4597 caffe.cpp:501] detection_eval = 10.1956
-I0511 11:49:27.134140  4597 caffe.cpp:501] detection_eval = 0.0403792
-I0511 11:49:27.134155  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.134168  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.134182  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.134196  4597 caffe.cpp:501] detection_eval = 10.2419
-I0511 11:49:27.134210  4597 caffe.cpp:501] detection_eval = 0.0411727
-I0511 11:49:27.134225  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.134239  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.134253  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.134268  4597 caffe.cpp:501] detection_eval = 10.2843
-I0511 11:49:27.134281  4597 caffe.cpp:501] detection_eval = 0.0438232
-I0511 11:49:27.134297  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.134312  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.134326  4597 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:49:27.134341  4597 caffe.cpp:501] detection_eval = 10.3105
-I0511 11:49:27.134354  4597 caffe.cpp:501] detection_eval = 0.0407584
-I0511 11:49:27.134368  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.134382  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.134397  4597 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:49:27.134410  4597 caffe.cpp:501] detection_eval = 10.4194
-I0511 11:49:27.134424  4597 caffe.cpp:501] detection_eval = 0.0432809
-I0511 11:49:27.134438  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.134452  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.134466  4597 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:49:27.134480  4597 caffe.cpp:501] detection_eval = 10.5161
-I0511 11:49:27.134495  4597 caffe.cpp:501] detection_eval = 0.0394205
-I0511 11:49:27.134508  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.134522  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.134536  4597 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:49:27.134551  4597 caffe.cpp:501] detection_eval = 10.6169
-I0511 11:49:27.134564  4597 caffe.cpp:501] detection_eval = 0.0418179
-I0511 11:49:27.134578  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.134593  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.134610  4597 caffe.cpp:501] detection_eval = 0.0564516
-I0511 11:49:27.134624  4597 caffe.cpp:501] detection_eval = 10.6673
-I0511 11:49:27.134639  4597 caffe.cpp:501] detection_eval = 0.0497172
-I0511 11:49:27.134654  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.134667  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.134681  4597 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:49:27.134696  4597 caffe.cpp:501] detection_eval = 10.7198
-I0511 11:49:27.134709  4597 caffe.cpp:501] detection_eval = 0.0484078
-I0511 11:49:27.134723  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.134737  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.134752  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.134764  4597 caffe.cpp:501] detection_eval = 10.8065
-I0511 11:49:27.134779  4597 caffe.cpp:501] detection_eval = 0.0451504
-I0511 11:49:27.134793  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.134807  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.134825  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.134840  4597 caffe.cpp:501] detection_eval = 10.9375
-I0511 11:49:27.134855  4597 caffe.cpp:501] detection_eval = 0.0483512
-I0511 11:49:27.134868  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.134882  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.134896  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.134910  4597 caffe.cpp:501] detection_eval = 11.0181
-I0511 11:49:27.134924  4597 caffe.cpp:501] detection_eval = 0.0471296
-I0511 11:49:27.134938  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.134953  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.134966  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.134980  4597 caffe.cpp:501] detection_eval = 11.0706
-I0511 11:49:27.134994  4597 caffe.cpp:501] detection_eval = 0.046401
-I0511 11:49:27.135008  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.135022  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.135036  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.135051  4597 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:49:27.135064  4597 caffe.cpp:501] detection_eval = 0.0402911
-I0511 11:49:27.135078  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.135092  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.135107  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.135120  4597 caffe.cpp:501] detection_eval = 11.2077
-I0511 11:49:27.135138  4597 caffe.cpp:501] detection_eval = 0.0443586
-I0511 11:49:27.135151  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.135166  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.135180  4597 caffe.cpp:501] detection_eval = 0.0625
-I0511 11:49:27.135195  4597 caffe.cpp:501] detection_eval = 11.2742
-I0511 11:49:27.135208  4597 caffe.cpp:501] detection_eval = 0.0453521
-I0511 11:49:27.135222  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.135236  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.135251  4597 caffe.cpp:501] detection_eval = 0.0625
-I0511 11:49:27.135264  4597 caffe.cpp:501] detection_eval = 11.3387
-I0511 11:49:27.135279  4597 caffe.cpp:501] detection_eval = 0.0460164
-I0511 11:49:27.135293  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.135308  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.135320  4597 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:49:27.135335  4597 caffe.cpp:501] detection_eval = 11.3831
-I0511 11:49:27.135349  4597 caffe.cpp:501] detection_eval = 0.0495264
-I0511 11:49:27.135363  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.135377  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.135390  4597 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:49:27.135404  4597 caffe.cpp:501] detection_eval = 11.506
-I0511 11:49:27.135419  4597 caffe.cpp:501] detection_eval = 0.0499466
-I0511 11:49:27.135432  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.135449  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.135464  4597 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:49:27.135478  4597 caffe.cpp:501] detection_eval = 11.5202
-I0511 11:49:27.135493  4597 caffe.cpp:501] detection_eval = 0.0448316
-I0511 11:49:27.135506  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.135520  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.135535  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135547  4597 caffe.cpp:501] detection_eval = 11.5363
-I0511 11:49:27.135562  4597 caffe.cpp:501] detection_eval = 0.0465377
-I0511 11:49:27.135576  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.135591  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.135603  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135617  4597 caffe.cpp:501] detection_eval = 11.6028
-I0511 11:49:27.135632  4597 caffe.cpp:501] detection_eval = 0.0402731
-I0511 11:49:27.135645  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.135664  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.135679  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135692  4597 caffe.cpp:501] detection_eval = 11.6351
-I0511 11:49:27.135707  4597 caffe.cpp:501] detection_eval = 0.0384965
-I0511 11:49:27.135721  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.135735  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.135749  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135763  4597 caffe.cpp:501] detection_eval = 11.6996
-I0511 11:49:27.135777  4597 caffe.cpp:501] detection_eval = 0.035633
-I0511 11:49:27.135792  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.135805  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.135819  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135833  4597 caffe.cpp:501] detection_eval = 11.746
-I0511 11:49:27.135848  4597 caffe.cpp:501] detection_eval = 0.0382949
-I0511 11:49:27.135861  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.135875  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.135890  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135903  4597 caffe.cpp:501] detection_eval = 11.7823
-I0511 11:49:27.135917  4597 caffe.cpp:501] detection_eval = 0.0356282
-I0511 11:49:27.135931  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.135946  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.135959  4597 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:49:27.135975  4597 caffe.cpp:501] detection_eval = 11.8629
-I0511 11:49:27.135990  4597 caffe.cpp:501] detection_eval = 0.0370107
-I0511 11:49:27.136004  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.136019  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.136034  4597 caffe.cpp:501] detection_eval = 0.0745968
-I0511 11:49:27.136046  4597 caffe.cpp:501] detection_eval = 11.9234
-I0511 11:49:27.136061  4597 caffe.cpp:501] detection_eval = 0.0394983
-I0511 11:49:27.136075  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.136090  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.136103  4597 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:49:27.136117  4597 caffe.cpp:501] detection_eval = 11.9738
-I0511 11:49:27.136132  4597 caffe.cpp:501] detection_eval = 0.0436015
-I0511 11:49:27.136145  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.136159  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.136173  4597 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:49:27.136188  4597 caffe.cpp:501] detection_eval = 11.996
-I0511 11:49:27.136201  4597 caffe.cpp:501] detection_eval = 0.0392789
-I0511 11:49:27.136215  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.136229  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.136243  4597 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:49:27.136257  4597 caffe.cpp:501] detection_eval = 12.0524
-I0511 11:49:27.136271  4597 caffe.cpp:501] detection_eval = 0.0396812
-I0511 11:49:27.136287  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.136302  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.136317  4597 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:49:27.136330  4597 caffe.cpp:501] detection_eval = 12.127
-I0511 11:49:27.136344  4597 caffe.cpp:501] detection_eval = 0.0433486
-I0511 11:49:27.136358  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.136373  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.136386  4597 caffe.cpp:501] detection_eval = 0.0806452
-I0511 11:49:27.136400  4597 caffe.cpp:501] detection_eval = 12.1653
-I0511 11:49:27.136415  4597 caffe.cpp:501] detection_eval = 0.044022
-I0511 11:49:27.136428  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.136442  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.136456  4597 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:49:27.136471  4597 caffe.cpp:501] detection_eval = 12.1976
-I0511 11:49:27.136484  4597 caffe.cpp:501] detection_eval = 0.0452797
-I0511 11:49:27.136502  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.136518  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.136536  4597 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:49:27.136553  4597 caffe.cpp:501] detection_eval = 12.254
-I0511 11:49:27.136566  4597 caffe.cpp:501] detection_eval = 0.0420392
-I0511 11:49:27.136580  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.136595  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.136608  4597 caffe.cpp:501] detection_eval = 0.0866935
-I0511 11:49:27.136622  4597 caffe.cpp:501] detection_eval = 12.2984
-I0511 11:49:27.136634  4597 caffe.cpp:501] detection_eval = 0.0416046
-I0511 11:49:27.136646  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.136657  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.136669  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136680  4597 caffe.cpp:501] detection_eval = 12.3448
-I0511 11:49:27.136693  4597 caffe.cpp:501] detection_eval = 0.0415534
-I0511 11:49:27.136703  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.136715  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.136726  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136739  4597 caffe.cpp:501] detection_eval = 12.4234
-I0511 11:49:27.136750  4597 caffe.cpp:501] detection_eval = 0.0421341
-I0511 11:49:27.136761  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.136773  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.136785  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136798  4597 caffe.cpp:501] detection_eval = 12.4919
-I0511 11:49:27.136811  4597 caffe.cpp:501] detection_eval = 0.0411038
-I0511 11:49:27.136821  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.136833  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.136845  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136857  4597 caffe.cpp:501] detection_eval = 12.5847
-I0511 11:49:27.136868  4597 caffe.cpp:501] detection_eval = 0.0455635
-I0511 11:49:27.136879  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.136890  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.136903  4597 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:49:27.136914  4597 caffe.cpp:501] detection_eval = 12.6653
-I0511 11:49:27.136926  4597 caffe.cpp:501] detection_eval = 0.0447624
-I0511 11:49:27.136937  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.136950  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.136960  4597 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:49:27.136972  4597 caffe.cpp:501] detection_eval = 12.7298
-I0511 11:49:27.136983  4597 caffe.cpp:501] detection_eval = 0.0437253
-I0511 11:49:27.136994  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.137006  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.137015  4597 caffe.cpp:501] detection_eval = 0.0927419
-I0511 11:49:27.137025  4597 caffe.cpp:501] detection_eval = 12.8266
-I0511 11:49:27.137035  4597 caffe.cpp:501] detection_eval = 0.0534464
-I0511 11:49:27.137049  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.137060  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.137071  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137081  4597 caffe.cpp:501] detection_eval = 12.871
-I0511 11:49:27.137091  4597 caffe.cpp:501] detection_eval = 0.0465589
-I0511 11:49:27.137101  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137114  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.137125  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137136  4597 caffe.cpp:501] detection_eval = 12.9435
-I0511 11:49:27.137148  4597 caffe.cpp:501] detection_eval = 0.0445296
-I0511 11:49:27.137159  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.137171  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.137182  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137193  4597 caffe.cpp:501] detection_eval = 13.0262
-I0511 11:49:27.137209  4597 caffe.cpp:501] detection_eval = 0.0512573
-I0511 11:49:27.137221  4597 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:49:27.137233  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.137244  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137256  4597 caffe.cpp:501] detection_eval = 13.1169
-I0511 11:49:27.137267  4597 caffe.cpp:501] detection_eval = 0.04829
-I0511 11:49:27.137279  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.137290  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.137301  4597 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:49:27.137312  4597 caffe.cpp:501] detection_eval = 13.1472
-I0511 11:49:27.137325  4597 caffe.cpp:501] detection_eval = 0.0414065
-I0511 11:49:27.137336  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.137346  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.137357  4597 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:49:27.137368  4597 caffe.cpp:501] detection_eval = 13.1613
-I0511 11:49:27.137380  4597 caffe.cpp:501] detection_eval = 0.0442636
-I0511 11:49:27.137392  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137403  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.137414  4597 caffe.cpp:501] detection_eval = 0.0987903
-I0511 11:49:27.137425  4597 caffe.cpp:501] detection_eval = 13.1935
-I0511 11:49:27.137437  4597 caffe.cpp:501] detection_eval = 0.0424333
-I0511 11:49:27.137449  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.137459  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.137473  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137485  4597 caffe.cpp:501] detection_eval = 13.1855
-I0511 11:49:27.137496  4597 caffe.cpp:501] detection_eval = 0.0424543
-I0511 11:49:27.137507  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137518  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.137529  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137542  4597 caffe.cpp:501] detection_eval = 13.2379
-I0511 11:49:27.137552  4597 caffe.cpp:501] detection_eval = 0.0420954
-I0511 11:49:27.137563  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.137575  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.137588  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137598  4597 caffe.cpp:501] detection_eval = 13.2923
-I0511 11:49:27.137609  4597 caffe.cpp:501] detection_eval = 0.0400218
-I0511 11:49:27.137620  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137632  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.137643  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137655  4597 caffe.cpp:501] detection_eval = 13.3448
-I0511 11:49:27.137666  4597 caffe.cpp:501] detection_eval = 0.0361185
-I0511 11:49:27.137677  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.137688  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.137699  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137711  4597 caffe.cpp:501] detection_eval = 13.4214
-I0511 11:49:27.137724  4597 caffe.cpp:501] detection_eval = 0.0387783
-I0511 11:49:27.137737  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.137748  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.137759  4597 caffe.cpp:501] detection_eval = 0.102823
-I0511 11:49:27.137770  4597 caffe.cpp:501] detection_eval = 13.4677
-I0511 11:49:27.137782  4597 caffe.cpp:501] detection_eval = 0.0393879
-I0511 11:49:27.137794  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.137806  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.137821  4597 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:49:27.137835  4597 caffe.cpp:501] detection_eval = 13.5101
-I0511 11:49:27.137848  4597 caffe.cpp:501] detection_eval = 0.0445567
-I0511 11:49:27.137861  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.137873  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.137887  4597 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:49:27.137904  4597 caffe.cpp:501] detection_eval = 13.5504
-I0511 11:49:27.137917  4597 caffe.cpp:501] detection_eval = 0.0398496
-I0511 11:49:27.137930  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.137943  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.137955  4597 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:49:27.137969  4597 caffe.cpp:501] detection_eval = 13.5786
-I0511 11:49:27.137981  4597 caffe.cpp:501] detection_eval = 0.0361707
-I0511 11:49:27.137995  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138007  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.138020  4597 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:49:27.138032  4597 caffe.cpp:501] detection_eval = 13.5968
-I0511 11:49:27.138046  4597 caffe.cpp:501] detection_eval = 0.0382904
-I0511 11:49:27.138057  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138070  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.138083  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138095  4597 caffe.cpp:501] detection_eval = 13.627
-I0511 11:49:27.138108  4597 caffe.cpp:501] detection_eval = 0.0435423
-I0511 11:49:27.138121  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.138134  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.138146  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138159  4597 caffe.cpp:501] detection_eval = 13.6976
-I0511 11:49:27.138171  4597 caffe.cpp:501] detection_eval = 0.0371483
-I0511 11:49:27.138185  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138200  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.138213  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138226  4597 caffe.cpp:501] detection_eval = 13.7581
-I0511 11:49:27.138238  4597 caffe.cpp:501] detection_eval = 0.0372349
-I0511 11:49:27.138252  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.138265  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.138278  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138290  4597 caffe.cpp:501] detection_eval = 13.8185
-I0511 11:49:27.138303  4597 caffe.cpp:501] detection_eval = 0.0346949
-I0511 11:49:27.138316  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.138329  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.138341  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138355  4597 caffe.cpp:501] detection_eval = 13.8347
-I0511 11:49:27.138367  4597 caffe.cpp:501] detection_eval = 0.036285
-I0511 11:49:27.138381  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138393  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.138406  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138419  4597 caffe.cpp:501] detection_eval = 13.8649
-I0511 11:49:27.138432  4597 caffe.cpp:501] detection_eval = 0.034692
-I0511 11:49:27.138444  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.138458  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.138470  4597 caffe.cpp:501] detection_eval = 0.110887
-I0511 11:49:27.138486  4597 caffe.cpp:501] detection_eval = 13.9113
-I0511 11:49:27.138499  4597 caffe.cpp:501] detection_eval = 0.0342626
-I0511 11:49:27.138512  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.138525  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.138538  4597 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:49:27.138551  4597 caffe.cpp:501] detection_eval = 13.9556
-I0511 11:49:27.138564  4597 caffe.cpp:501] detection_eval = 0.0420291
-I0511 11:49:27.138577  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.138590  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.138603  4597 caffe.cpp:501] detection_eval = 0.116935
-I0511 11:49:27.138617  4597 caffe.cpp:501] detection_eval = 13.9899
-I0511 11:49:27.138629  4597 caffe.cpp:501] detection_eval = 0.0428096
-I0511 11:49:27.138643  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.138655  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.138672  4597 caffe.cpp:501] detection_eval = 0.116935
-I0511 11:49:27.138686  4597 caffe.cpp:501] detection_eval = 14.0504
-I0511 11:49:27.138700  4597 caffe.cpp:501] detection_eval = 0.0409506
-I0511 11:49:27.138711  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.138725  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.138737  4597 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:49:27.138751  4597 caffe.cpp:501] detection_eval = 14.0645
-I0511 11:49:27.138763  4597 caffe.cpp:501] detection_eval = 0.0405591
-I0511 11:49:27.138777  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.138789  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.138801  4597 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:49:27.138814  4597 caffe.cpp:501] detection_eval = 14.0927
-I0511 11:49:27.138828  4597 caffe.cpp:501] detection_eval = 0.0365014
-I0511 11:49:27.138840  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.138854  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.138866  4597 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:49:27.138878  4597 caffe.cpp:501] detection_eval = 14.1351
-I0511 11:49:27.138891  4597 caffe.cpp:501] detection_eval = 0.0343148
-I0511 11:49:27.138903  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.138916  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.138929  4597 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:49:27.138942  4597 caffe.cpp:501] detection_eval = 14.1593
-I0511 11:49:27.138955  4597 caffe.cpp:501] detection_eval = 0.0369762
-I0511 11:49:27.138972  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.138986  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.138999  4597 caffe.cpp:501] detection_eval = 0.120968
-I0511 11:49:27.139015  4597 caffe.cpp:501] detection_eval = 14.1573
-I0511 11:49:27.139029  4597 caffe.cpp:501] detection_eval = 0.035061
-I0511 11:49:27.139042  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139055  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.139070  4597 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:49:27.139083  4597 caffe.cpp:501] detection_eval = 14.1512
-I0511 11:49:27.139096  4597 caffe.cpp:501] detection_eval = 0.035864
-I0511 11:49:27.139109  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139123  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.139140  4597 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:49:27.139153  4597 caffe.cpp:501] detection_eval = 14.1855
-I0511 11:49:27.139166  4597 caffe.cpp:501] detection_eval = 0.0329432
-I0511 11:49:27.139179  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139192  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139205  4597 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:49:27.139219  4597 caffe.cpp:501] detection_eval = 14.1694
-I0511 11:49:27.139231  4597 caffe.cpp:501] detection_eval = 0.0330096
-I0511 11:49:27.139245  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139257  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139272  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139286  4597 caffe.cpp:501] detection_eval = 14.252
-I0511 11:49:27.139299  4597 caffe.cpp:501] detection_eval = 0.0325234
-I0511 11:49:27.139312  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.139325  4597 caffe.cpp:501] detection_eval = 1
-I0511 11:49:27.139338  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139350  4597 caffe.cpp:501] detection_eval = 14.2742
-I0511 11:49:27.139364  4597 caffe.cpp:501] detection_eval = 0.0301755
-I0511 11:49:27.139376  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.139389  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.139401  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139415  4597 caffe.cpp:501] detection_eval = 14.3004
-I0511 11:49:27.139428  4597 caffe.cpp:501] detection_eval = 0.0304516
-I0511 11:49:27.139441  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139453  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.139472  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139484  4597 caffe.cpp:501] detection_eval = 14.3226
-I0511 11:49:27.139497  4597 caffe.cpp:501] detection_eval = 0.0326873
-I0511 11:49:27.139510  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.139523  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.139536  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139549  4597 caffe.cpp:501] detection_eval = 14.373
-I0511 11:49:27.139561  4597 caffe.cpp:501] detection_eval = 0.0322298
-I0511 11:49:27.139575  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139588  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139601  4597 caffe.cpp:501] detection_eval = 0.129032
-I0511 11:49:27.139614  4597 caffe.cpp:501] detection_eval = 14.4375
-I0511 11:49:27.139627  4597 caffe.cpp:501] detection_eval = 0.0339324
-I0511 11:49:27.139641  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.139653  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.139667  4597 caffe.cpp:501] detection_eval = 0.131048
-I0511 11:49:27.139678  4597 caffe.cpp:501] detection_eval = 14.4435
-I0511 11:49:27.139691  4597 caffe.cpp:501] detection_eval = 0.0360259
-I0511 11:49:27.139704  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.139717  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.139730  4597 caffe.cpp:501] detection_eval = 0.131048
-I0511 11:49:27.139744  4597 caffe.cpp:501] detection_eval = 14.4819
-I0511 11:49:27.139758  4597 caffe.cpp:501] detection_eval = 0.0316306
-I0511 11:49:27.139771  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139784  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139797  4597 caffe.cpp:501] detection_eval = 0.131048
-I0511 11:49:27.139809  4597 caffe.cpp:501] detection_eval = 14.5484
-I0511 11:49:27.139822  4597 caffe.cpp:501] detection_eval = 0.0332233
-I0511 11:49:27.139835  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139848  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139861  4597 caffe.cpp:501] detection_eval = 0.133065
-I0511 11:49:27.139874  4597 caffe.cpp:501] detection_eval = 14.5786
-I0511 11:49:27.139888  4597 caffe.cpp:501] detection_eval = 0.0363158
-I0511 11:49:27.139899  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.139912  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.139925  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.139938  4597 caffe.cpp:501] detection_eval = 14.5847
-I0511 11:49:27.139951  4597 caffe.cpp:501] detection_eval = 0.0350456
-I0511 11:49:27.139964  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.139976  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.139989  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140002  4597 caffe.cpp:501] detection_eval = 14.623
-I0511 11:49:27.140015  4597 caffe.cpp:501] detection_eval = 0.0356263
-I0511 11:49:27.140028  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140043  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140056  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140069  4597 caffe.cpp:501] detection_eval = 14.6431
-I0511 11:49:27.140082  4597 caffe.cpp:501] detection_eval = 0.0318447
-I0511 11:49:27.140095  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.140108  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140121  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140135  4597 caffe.cpp:501] detection_eval = 14.6935
-I0511 11:49:27.140147  4597 caffe.cpp:501] detection_eval = 0.03345
-I0511 11:49:27.140161  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.140173  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.140187  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140200  4597 caffe.cpp:501] detection_eval = 14.7399
-I0511 11:49:27.140213  4597 caffe.cpp:501] detection_eval = 0.0338787
-I0511 11:49:27.140226  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140244  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140257  4597 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:49:27.140270  4597 caffe.cpp:501] detection_eval = 14.7903
-I0511 11:49:27.140283  4597 caffe.cpp:501] detection_eval = 0.0337207
-I0511 11:49:27.140295  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.140308  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.140321  4597 caffe.cpp:501] detection_eval = 0.143145
-I0511 11:49:27.140333  4597 caffe.cpp:501] detection_eval = 14.75
-I0511 11:49:27.140347  4597 caffe.cpp:501] detection_eval = 0.036413
-I0511 11:49:27.140359  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.140372  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140385  4597 caffe.cpp:501] detection_eval = 0.143145
-I0511 11:49:27.140398  4597 caffe.cpp:501] detection_eval = 14.8105
-I0511 11:49:27.140410  4597 caffe.cpp:501] detection_eval = 0.0325231
-I0511 11:49:27.140424  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.140436  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140450  4597 caffe.cpp:501] detection_eval = 0.145161
-I0511 11:49:27.140461  4597 caffe.cpp:501] detection_eval = 14.8266
-I0511 11:49:27.140475  4597 caffe.cpp:501] detection_eval = 0.0326505
-I0511 11:49:27.140487  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140501  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140512  4597 caffe.cpp:501] detection_eval = 0.147177
-I0511 11:49:27.140534  4597 caffe.cpp:501] detection_eval = 14.8851
-I0511 11:49:27.140550  4597 caffe.cpp:501] detection_eval = 0.0387736
-I0511 11:49:27.140563  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140576  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140589  4597 caffe.cpp:501] detection_eval = 0.15121
-I0511 11:49:27.140602  4597 caffe.cpp:501] detection_eval = 14.8831
-I0511 11:49:27.140615  4597 caffe.cpp:501] detection_eval = 0.0343417
-I0511 11:49:27.140628  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.140641  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140655  4597 caffe.cpp:501] detection_eval = 0.155242
-I0511 11:49:27.140666  4597 caffe.cpp:501] detection_eval = 14.9315
-I0511 11:49:27.140681  4597 caffe.cpp:501] detection_eval = 0.0331358
-I0511 11:49:27.140692  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140705  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.140718  4597 caffe.cpp:501] detection_eval = 0.157258
-I0511 11:49:27.140732  4597 caffe.cpp:501] detection_eval = 14.9718
-I0511 11:49:27.140745  4597 caffe.cpp:501] detection_eval = 0.0350309
-I0511 11:49:27.140758  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.140771  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.140784  4597 caffe.cpp:501] detection_eval = 0.159274
-I0511 11:49:27.140796  4597 caffe.cpp:501] detection_eval = 14.9879
-I0511 11:49:27.140810  4597 caffe.cpp:501] detection_eval = 0.0314733
-I0511 11:49:27.140825  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.140838  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.140851  4597 caffe.cpp:501] detection_eval = 0.159274
-I0511 11:49:27.140863  4597 caffe.cpp:501] detection_eval = 15.0565
-I0511 11:49:27.140877  4597 caffe.cpp:501] detection_eval = 0.0325432
-I0511 11:49:27.140889  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.140902  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.140915  4597 caffe.cpp:501] detection_eval = 0.159274
-I0511 11:49:27.140928  4597 caffe.cpp:501] detection_eval = 15.2016
-I0511 11:49:27.140941  4597 caffe.cpp:501] detection_eval = 0.0410111
-I0511 11:49:27.140954  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.140966  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.140980  4597 caffe.cpp:501] detection_eval = 0.159274
-I0511 11:49:27.140992  4597 caffe.cpp:501] detection_eval = 15.3327
-I0511 11:49:27.141005  4597 caffe.cpp:501] detection_eval = 0.0373448
-I0511 11:49:27.141023  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.141036  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.141049  4597 caffe.cpp:501] detection_eval = 0.167339
-I0511 11:49:27.141062  4597 caffe.cpp:501] detection_eval = 15.3649
-I0511 11:49:27.141075  4597 caffe.cpp:501] detection_eval = 0.0424123
-I0511 11:49:27.141088  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.141101  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.141113  4597 caffe.cpp:501] detection_eval = 0.167339
-I0511 11:49:27.141126  4597 caffe.cpp:501] detection_eval = 15.4859
-I0511 11:49:27.141139  4597 caffe.cpp:501] detection_eval = 0.0360478
-I0511 11:49:27.141153  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.141166  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.141180  4597 caffe.cpp:501] detection_eval = 0.167339
-I0511 11:49:27.141192  4597 caffe.cpp:501] detection_eval = 15.6391
-I0511 11:49:27.141206  4597 caffe.cpp:501] detection_eval = 0.0404236
-I0511 11:49:27.141218  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.141230  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.141243  4597 caffe.cpp:501] detection_eval = 0.169355
-I0511 11:49:27.141257  4597 caffe.cpp:501] detection_eval = 15.8105
-I0511 11:49:27.141269  4597 caffe.cpp:501] detection_eval = 0.03665
-I0511 11:49:27.141283  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.141294  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.141310  4597 caffe.cpp:501] detection_eval = 0.173387
-I0511 11:49:27.141324  4597 caffe.cpp:501] detection_eval = 15.9738
-I0511 11:49:27.141336  4597 caffe.cpp:501] detection_eval = 0.0364727
-I0511 11:49:27.141350  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.141362  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.141376  4597 caffe.cpp:501] detection_eval = 0.173387
-I0511 11:49:27.141387  4597 caffe.cpp:501] detection_eval = 16.3206
-I0511 11:49:27.141402  4597 caffe.cpp:501] detection_eval = 0.0422899
-I0511 11:49:27.141413  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.141427  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.141439  4597 caffe.cpp:501] detection_eval = 0.175403
-I0511 11:49:27.141450  4597 caffe.cpp:501] detection_eval = 16.7742
-I0511 11:49:27.141463  4597 caffe.cpp:501] detection_eval = 0.0304554
-I0511 11:49:27.141476  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.141489  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.141502  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141515  4597 caffe.cpp:501] detection_eval = 4.12702
-I0511 11:49:27.141528  4597 caffe.cpp:501] detection_eval = 0.149664
-I0511 11:49:27.141541  4597 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:49:27.141556  4597 caffe.cpp:501] detection_eval = 0.875
-I0511 11:49:27.141567  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141580  4597 caffe.cpp:501] detection_eval = 4.40726
-I0511 11:49:27.141593  4597 caffe.cpp:501] detection_eval = 0.0784179
-I0511 11:49:27.141608  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.141623  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.141635  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141649  4597 caffe.cpp:501] detection_eval = 4.62298
-I0511 11:49:27.141661  4597 caffe.cpp:501] detection_eval = 0.0701486
-I0511 11:49:27.141674  4597 caffe.cpp:501] detection_eval = 0.0443548
-I0511 11:49:27.141688  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.141701  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141715  4597 caffe.cpp:501] detection_eval = 4.79234
-I0511 11:49:27.141726  4597 caffe.cpp:501] detection_eval = 0.0624976
-I0511 11:49:27.141739  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.141752  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.141765  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141778  4597 caffe.cpp:501] detection_eval = 4.95565
-I0511 11:49:27.141795  4597 caffe.cpp:501] detection_eval = 0.0622305
-I0511 11:49:27.141809  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.141821  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.141834  4597 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:49:27.141847  4597 caffe.cpp:501] detection_eval = 5.0746
-I0511 11:49:27.141861  4597 caffe.cpp:501] detection_eval = 0.0590016
-I0511 11:49:27.141875  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.141887  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.141901  4597 caffe.cpp:501] detection_eval = 1.01411
-I0511 11:49:27.141912  4597 caffe.cpp:501] detection_eval = 5.16734
-I0511 11:49:27.141925  4597 caffe.cpp:501] detection_eval = 0.0508263
-I0511 11:49:27.141938  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.141952  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.141964  4597 caffe.cpp:501] detection_eval = 1.01613
-I0511 11:49:27.141976  4597 caffe.cpp:501] detection_eval = 5.27016
-I0511 11:49:27.141989  4597 caffe.cpp:501] detection_eval = 0.0498147
-I0511 11:49:27.142002  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.142014  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.142027  4597 caffe.cpp:501] detection_eval = 1.01815
-I0511 11:49:27.142040  4597 caffe.cpp:501] detection_eval = 5.30645
-I0511 11:49:27.142053  4597 caffe.cpp:501] detection_eval = 0.045917
-I0511 11:49:27.142066  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142078  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.142093  4597 caffe.cpp:501] detection_eval = 1.01815
-I0511 11:49:27.142107  4597 caffe.cpp:501] detection_eval = 5.39516
-I0511 11:49:27.142119  4597 caffe.cpp:501] detection_eval = 0.045753
-I0511 11:49:27.142132  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142146  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.142159  4597 caffe.cpp:501] detection_eval = 1.01815
-I0511 11:49:27.142172  4597 caffe.cpp:501] detection_eval = 5.4496
-I0511 11:49:27.142185  4597 caffe.cpp:501] detection_eval = 0.0404288
-I0511 11:49:27.142199  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.142211  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.142225  4597 caffe.cpp:501] detection_eval = 1.02016
-I0511 11:49:27.142237  4597 caffe.cpp:501] detection_eval = 5.47177
-I0511 11:49:27.142249  4597 caffe.cpp:501] detection_eval = 0.0440242
-I0511 11:49:27.142262  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.142276  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.142288  4597 caffe.cpp:501] detection_eval = 1.02016
-I0511 11:49:27.142300  4597 caffe.cpp:501] detection_eval = 5.56855
-I0511 11:49:27.142313  4597 caffe.cpp:501] detection_eval = 0.0451199
-I0511 11:49:27.142326  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142339  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.142351  4597 caffe.cpp:501] detection_eval = 1.02218
-I0511 11:49:27.142364  4597 caffe.cpp:501] detection_eval = 5.59879
-I0511 11:49:27.142380  4597 caffe.cpp:501] detection_eval = 0.0448299
-I0511 11:49:27.142395  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.142407  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.142419  4597 caffe.cpp:501] detection_eval = 1.02419
-I0511 11:49:27.142432  4597 caffe.cpp:501] detection_eval = 5.63508
-I0511 11:49:27.142446  4597 caffe.cpp:501] detection_eval = 0.0521873
-I0511 11:49:27.142458  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.142470  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.142483  4597 caffe.cpp:501] detection_eval = 1.02621
-I0511 11:49:27.142496  4597 caffe.cpp:501] detection_eval = 5.66935
-I0511 11:49:27.142509  4597 caffe.cpp:501] detection_eval = 0.0443965
-I0511 11:49:27.142521  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.142534  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.142547  4597 caffe.cpp:501] detection_eval = 1.02621
-I0511 11:49:27.142560  4597 caffe.cpp:501] detection_eval = 5.76411
-I0511 11:49:27.142577  4597 caffe.cpp:501] detection_eval = 0.0405536
-I0511 11:49:27.142591  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142603  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.142616  4597 caffe.cpp:501] detection_eval = 1.02621
-I0511 11:49:27.142633  4597 caffe.cpp:501] detection_eval = 5.85081
-I0511 11:49:27.142647  4597 caffe.cpp:501] detection_eval = 0.042654
-I0511 11:49:27.142663  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.142676  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.142691  4597 caffe.cpp:501] detection_eval = 1.03024
-I0511 11:49:27.142705  4597 caffe.cpp:501] detection_eval = 5.90121
-I0511 11:49:27.142719  4597 caffe.cpp:501] detection_eval = 0.0400547
-I0511 11:49:27.142732  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.142745  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.142758  4597 caffe.cpp:501] detection_eval = 1.03024
-I0511 11:49:27.142771  4597 caffe.cpp:501] detection_eval = 5.98589
-I0511 11:49:27.142786  4597 caffe.cpp:501] detection_eval = 0.0409764
-I0511 11:49:27.142798  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.142812  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.142825  4597 caffe.cpp:501] detection_eval = 1.03226
-I0511 11:49:27.142838  4597 caffe.cpp:501] detection_eval = 6.02823
-I0511 11:49:27.142851  4597 caffe.cpp:501] detection_eval = 0.0386796
-I0511 11:49:27.142864  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.142880  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.142894  4597 caffe.cpp:501] detection_eval = 1.03226
-I0511 11:49:27.142907  4597 caffe.cpp:501] detection_eval = 6.09879
-I0511 11:49:27.142921  4597 caffe.cpp:501] detection_eval = 0.0445525
-I0511 11:49:27.142935  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.142949  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.142963  4597 caffe.cpp:501] detection_eval = 1.03629
-I0511 11:49:27.142977  4597 caffe.cpp:501] detection_eval = 6.12097
-I0511 11:49:27.142990  4597 caffe.cpp:501] detection_eval = 0.0419441
-I0511 11:49:27.143004  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.143018  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.143030  4597 caffe.cpp:501] detection_eval = 1.03831
-I0511 11:49:27.143044  4597 caffe.cpp:501] detection_eval = 6.19758
-I0511 11:49:27.143057  4597 caffe.cpp:501] detection_eval = 0.0432385
-I0511 11:49:27.143071  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.143085  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.143097  4597 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:49:27.143111  4597 caffe.cpp:501] detection_eval = 6.23185
-I0511 11:49:27.143126  4597 caffe.cpp:501] detection_eval = 0.0413859
-I0511 11:49:27.143142  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143157  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.143172  4597 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:49:27.143190  4597 caffe.cpp:501] detection_eval = 6.30847
-I0511 11:49:27.143204  4597 caffe.cpp:501] detection_eval = 0.0380197
-I0511 11:49:27.143219  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.143234  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.143249  4597 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:49:27.143263  4597 caffe.cpp:501] detection_eval = 6.40323
-I0511 11:49:27.143277  4597 caffe.cpp:501] detection_eval = 0.0423985
-I0511 11:49:27.143292  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.143306  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.143321  4597 caffe.cpp:501] detection_eval = 1.04234
-I0511 11:49:27.143335  4597 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:49:27.143349  4597 caffe.cpp:501] detection_eval = 0.0383202
-I0511 11:49:27.143364  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.143379  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.143393  4597 caffe.cpp:501] detection_eval = 1.04637
-I0511 11:49:27.143412  4597 caffe.cpp:501] detection_eval = 6.45363
-I0511 11:49:27.143427  4597 caffe.cpp:501] detection_eval = 0.0365058
-I0511 11:49:27.143441  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143457  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.143472  4597 caffe.cpp:501] detection_eval = 1.04637
-I0511 11:49:27.143486  4597 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:49:27.143501  4597 caffe.cpp:501] detection_eval = 0.0359437
-I0511 11:49:27.143515  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143529  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.143544  4597 caffe.cpp:501] detection_eval = 1.04637
-I0511 11:49:27.143558  4597 caffe.cpp:501] detection_eval = 6.6371
-I0511 11:49:27.143574  4597 caffe.cpp:501] detection_eval = 0.0397337
-I0511 11:49:27.143590  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.143604  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.143620  4597 caffe.cpp:501] detection_eval = 1.04839
-I0511 11:49:27.143635  4597 caffe.cpp:501] detection_eval = 6.70161
-I0511 11:49:27.143649  4597 caffe.cpp:501] detection_eval = 0.0413847
-I0511 11:49:27.143666  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143682  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.143697  4597 caffe.cpp:501] detection_eval = 1.04839
-I0511 11:49:27.143728  4597 caffe.cpp:501] detection_eval = 6.77016
-I0511 11:49:27.143749  4597 caffe.cpp:501] detection_eval = 0.0406304
-I0511 11:49:27.143764  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.143781  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.143796  4597 caffe.cpp:501] detection_eval = 1.04839
-I0511 11:49:27.143810  4597 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:49:27.143824  4597 caffe.cpp:501] detection_eval = 0.0351328
-I0511 11:49:27.143837  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.143852  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.143867  4597 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:49:27.143879  4597 caffe.cpp:501] detection_eval = 6.88105
-I0511 11:49:27.143893  4597 caffe.cpp:501] detection_eval = 0.0374926
-I0511 11:49:27.143908  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.143921  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.143936  4597 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:49:27.143950  4597 caffe.cpp:501] detection_eval = 6.99798
-I0511 11:49:27.143963  4597 caffe.cpp:501] detection_eval = 0.0416074
-I0511 11:49:27.143977  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.143992  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.144006  4597 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:49:27.144019  4597 caffe.cpp:501] detection_eval = 7.14516
-I0511 11:49:27.144033  4597 caffe.cpp:501] detection_eval = 0.0420148
-I0511 11:49:27.144048  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.144062  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144075  4597 caffe.cpp:501] detection_eval = 1.05444
-I0511 11:49:27.144093  4597 caffe.cpp:501] detection_eval = 7.15323
-I0511 11:49:27.144109  4597 caffe.cpp:501] detection_eval = 0.0411047
-I0511 11:49:27.144122  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144137  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.144151  4597 caffe.cpp:501] detection_eval = 1.05645
-I0511 11:49:27.144165  4597 caffe.cpp:501] detection_eval = 7.22581
-I0511 11:49:27.144179  4597 caffe.cpp:501] detection_eval = 0.0394439
-I0511 11:49:27.144193  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144207  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144220  4597 caffe.cpp:501] detection_eval = 1.05645
-I0511 11:49:27.144234  4597 caffe.cpp:501] detection_eval = 7.31048
-I0511 11:49:27.144248  4597 caffe.cpp:501] detection_eval = 0.0354345
-I0511 11:49:27.144263  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144276  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144292  4597 caffe.cpp:501] detection_eval = 1.05645
-I0511 11:49:27.144304  4597 caffe.cpp:501] detection_eval = 7.40927
-I0511 11:49:27.144313  4597 caffe.cpp:501] detection_eval = 0.0408727
-I0511 11:49:27.144322  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144331  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.144341  4597 caffe.cpp:501] detection_eval = 1.05847
-I0511 11:49:27.144351  4597 caffe.cpp:501] detection_eval = 7.48589
-I0511 11:49:27.144358  4597 caffe.cpp:501] detection_eval = 0.0395751
-I0511 11:49:27.144367  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.144377  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144387  4597 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:49:27.144394  4597 caffe.cpp:501] detection_eval = 7.53831
-I0511 11:49:27.144402  4597 caffe.cpp:501] detection_eval = 0.0404673
-I0511 11:49:27.144412  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144423  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.144431  4597 caffe.cpp:501] detection_eval = 1.0625
-I0511 11:49:27.144439  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.144448  4597 caffe.cpp:501] detection_eval = 0.0437643
-I0511 11:49:27.144456  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144466  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.144476  4597 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:49:27.144484  4597 caffe.cpp:501] detection_eval = 7.66331
-I0511 11:49:27.144492  4597 caffe.cpp:501] detection_eval = 0.0436936
-I0511 11:49:27.144501  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.144510  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.144518  4597 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:49:27.144536  4597 caffe.cpp:501] detection_eval = 7.75605
-I0511 11:49:27.144546  4597 caffe.cpp:501] detection_eval = 0.0451707
-I0511 11:49:27.144556  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144564  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.144573  4597 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:49:27.144582  4597 caffe.cpp:501] detection_eval = 7.85685
-I0511 11:49:27.144589  4597 caffe.cpp:501] detection_eval = 0.0391205
-I0511 11:49:27.144598  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144605  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.144614  4597 caffe.cpp:501] detection_eval = 1.06855
-I0511 11:49:27.144624  4597 caffe.cpp:501] detection_eval = 7.90323
-I0511 11:49:27.144634  4597 caffe.cpp:501] detection_eval = 0.0425444
-I0511 11:49:27.144641  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.144649  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.144657  4597 caffe.cpp:501] detection_eval = 1.07056
-I0511 11:49:27.144666  4597 caffe.cpp:501] detection_eval = 7.93347
-I0511 11:49:27.144675  4597 caffe.cpp:501] detection_eval = 0.0481662
-I0511 11:49:27.144683  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.144692  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.144706  4597 caffe.cpp:501] detection_eval = 1.07056
-I0511 11:49:27.144714  4597 caffe.cpp:501] detection_eval = 8.01411
-I0511 11:49:27.144723  4597 caffe.cpp:501] detection_eval = 0.0398225
-I0511 11:49:27.144731  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.144740  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.144748  4597 caffe.cpp:501] detection_eval = 1.07661
-I0511 11:49:27.144757  4597 caffe.cpp:501] detection_eval = 7.99395
-I0511 11:49:27.144764  4597 caffe.cpp:501] detection_eval = 0.0411763
-I0511 11:49:27.144774  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144783  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144793  4597 caffe.cpp:501] detection_eval = 1.07661
-I0511 11:49:27.144801  4597 caffe.cpp:501] detection_eval = 8.03226
-I0511 11:49:27.144809  4597 caffe.cpp:501] detection_eval = 0.0390111
-I0511 11:49:27.144817  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.144825  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144840  4597 caffe.cpp:501] detection_eval = 1.07863
-I0511 11:49:27.144847  4597 caffe.cpp:501] detection_eval = 8.10282
-I0511 11:49:27.144857  4597 caffe.cpp:501] detection_eval = 0.0432689
-I0511 11:49:27.144867  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144876  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.144884  4597 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:49:27.144893  4597 caffe.cpp:501] detection_eval = 8.11492
-I0511 11:49:27.144901  4597 caffe.cpp:501] detection_eval = 0.0395303
-I0511 11:49:27.144909  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.144918  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144927  4597 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:49:27.144934  4597 caffe.cpp:501] detection_eval = 8.16331
-I0511 11:49:27.144944  4597 caffe.cpp:501] detection_eval = 0.0367415
-I0511 11:49:27.144953  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.144963  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.144970  4597 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:49:27.144979  4597 caffe.cpp:501] detection_eval = 8.22379
-I0511 11:49:27.144984  4597 caffe.cpp:501] detection_eval = 0.0368785
-I0511 11:49:27.144989  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.144992  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.144997  4597 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:49:27.145001  4597 caffe.cpp:501] detection_eval = 8.31048
-I0511 11:49:27.145006  4597 caffe.cpp:501] detection_eval = 0.039801
-I0511 11:49:27.145011  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145016  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145020  4597 caffe.cpp:501] detection_eval = 1.08266
-I0511 11:49:27.145023  4597 caffe.cpp:501] detection_eval = 8.38105
-I0511 11:49:27.145028  4597 caffe.cpp:501] detection_eval = 0.0395155
-I0511 11:49:27.145033  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145043  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145050  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145054  4597 caffe.cpp:501] detection_eval = 8.41935
-I0511 11:49:27.145064  4597 caffe.cpp:501] detection_eval = 0.0432269
-I0511 11:49:27.145069  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145073  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145078  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145082  4597 caffe.cpp:501] detection_eval = 8.5121
-I0511 11:49:27.145087  4597 caffe.cpp:501] detection_eval = 0.0442923
-I0511 11:49:27.145092  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145095  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145100  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145104  4597 caffe.cpp:501] detection_eval = 8.60484
-I0511 11:49:27.145109  4597 caffe.cpp:501] detection_eval = 0.0466011
-I0511 11:49:27.145114  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145118  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145123  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145126  4597 caffe.cpp:501] detection_eval = 8.6754
-I0511 11:49:27.145130  4597 caffe.cpp:501] detection_eval = 0.0382274
-I0511 11:49:27.145135  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145139  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.145144  4597 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:49:27.145148  4597 caffe.cpp:501] detection_eval = 8.76411
-I0511 11:49:27.145153  4597 caffe.cpp:501] detection_eval = 0.0373927
-I0511 11:49:27.145157  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145162  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145166  4597 caffe.cpp:501] detection_eval = 1.08871
-I0511 11:49:27.145171  4597 caffe.cpp:501] detection_eval = 8.79032
-I0511 11:49:27.145176  4597 caffe.cpp:501] detection_eval = 0.0388855
-I0511 11:49:27.145180  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145190  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145195  4597 caffe.cpp:501] detection_eval = 1.08871
-I0511 11:49:27.145198  4597 caffe.cpp:501] detection_eval = 8.91734
-I0511 11:49:27.145203  4597 caffe.cpp:501] detection_eval = 0.0389421
-I0511 11:49:27.145207  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.145211  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.145215  4597 caffe.cpp:501] detection_eval = 1.09476
-I0511 11:49:27.145220  4597 caffe.cpp:501] detection_eval = 8.90524
-I0511 11:49:27.145225  4597 caffe.cpp:501] detection_eval = 0.0407377
-I0511 11:49:27.145226  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145229  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145231  4597 caffe.cpp:501] detection_eval = 1.09476
-I0511 11:49:27.145233  4597 caffe.cpp:501] detection_eval = 9.02016
-I0511 11:49:27.145236  4597 caffe.cpp:501] detection_eval = 0.0462407
-I0511 11:49:27.145238  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145241  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145244  4597 caffe.cpp:501] detection_eval = 1.09476
-I0511 11:49:27.145247  4597 caffe.cpp:501] detection_eval = 9.08669
-I0511 11:49:27.145249  4597 caffe.cpp:501] detection_eval = 0.0400719
-I0511 11:49:27.145252  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145254  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145257  4597 caffe.cpp:501] detection_eval = 1.09677
-I0511 11:49:27.145259  4597 caffe.cpp:501] detection_eval = 9.23992
-I0511 11:49:27.145262  4597 caffe.cpp:501] detection_eval = 0.0503495
-I0511 11:49:27.145264  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.145267  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.145269  4597 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:49:27.145272  4597 caffe.cpp:501] detection_eval = 9.27823
-I0511 11:49:27.145274  4597 caffe.cpp:501] detection_eval = 0.0405731
-I0511 11:49:27.145277  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145278  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145282  4597 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:49:27.145283  4597 caffe.cpp:501] detection_eval = 9.36694
-I0511 11:49:27.145287  4597 caffe.cpp:501] detection_eval = 0.040862
-I0511 11:49:27.145288  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145292  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145293  4597 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:49:27.145296  4597 caffe.cpp:501] detection_eval = 9.48185
-I0511 11:49:27.145298  4597 caffe.cpp:501] detection_eval = 0.0391158
-I0511 11:49:27.145301  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145303  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145306  4597 caffe.cpp:501] detection_eval = 1.10282
-I0511 11:49:27.145308  4597 caffe.cpp:501] detection_eval = 9.56048
-I0511 11:49:27.145310  4597 caffe.cpp:501] detection_eval = 0.039909
-I0511 11:49:27.145313  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145315  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145318  4597 caffe.cpp:501] detection_eval = 1.10685
-I0511 11:49:27.145320  4597 caffe.cpp:501] detection_eval = 9.59073
-I0511 11:49:27.145323  4597 caffe.cpp:501] detection_eval = 0.0405835
-I0511 11:49:27.145325  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.145328  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.145329  4597 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:49:27.145332  4597 caffe.cpp:501] detection_eval = 9.72984
-I0511 11:49:27.145334  4597 caffe.cpp:501] detection_eval = 0.0489761
-I0511 11:49:27.145337  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145339  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145342  4597 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:49:27.145344  4597 caffe.cpp:501] detection_eval = 9.80444
-I0511 11:49:27.145347  4597 caffe.cpp:501] detection_eval = 0.0469686
-I0511 11:49:27.145354  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145356  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145359  4597 caffe.cpp:501] detection_eval = 1.1129
-I0511 11:49:27.145361  4597 caffe.cpp:501] detection_eval = 9.87298
-I0511 11:49:27.145364  4597 caffe.cpp:501] detection_eval = 0.0530507
-I0511 11:49:27.145365  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.145368  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.145370  4597 caffe.cpp:501] detection_eval = 1.11694
-I0511 11:49:27.145372  4597 caffe.cpp:501] detection_eval = 9.94556
-I0511 11:49:27.145375  4597 caffe.cpp:501] detection_eval = 0.0506045
-I0511 11:49:27.145377  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145380  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.145382  4597 caffe.cpp:501] detection_eval = 1.11895
-I0511 11:49:27.145385  4597 caffe.cpp:501] detection_eval = 9.96774
-I0511 11:49:27.145387  4597 caffe.cpp:501] detection_eval = 0.0446408
-I0511 11:49:27.145390  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145392  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145395  4597 caffe.cpp:501] detection_eval = 1.12298
-I0511 11:49:27.145397  4597 caffe.cpp:501] detection_eval = 10.0181
-I0511 11:49:27.145401  4597 caffe.cpp:501] detection_eval = 0.0450307
-I0511 11:49:27.145402  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145406  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145407  4597 caffe.cpp:501] detection_eval = 1.12298
-I0511 11:49:27.145411  4597 caffe.cpp:501] detection_eval = 10.123
-I0511 11:49:27.145413  4597 caffe.cpp:501] detection_eval = 0.0510043
-I0511 11:49:27.145416  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.145418  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.145421  4597 caffe.cpp:501] detection_eval = 1.12903
-I0511 11:49:27.145423  4597 caffe.cpp:501] detection_eval = 10.0806
-I0511 11:49:27.145426  4597 caffe.cpp:501] detection_eval = 0.0439102
-I0511 11:49:27.145428  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145431  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145433  4597 caffe.cpp:501] detection_eval = 1.13105
-I0511 11:49:27.145437  4597 caffe.cpp:501] detection_eval = 10.1411
-I0511 11:49:27.145438  4597 caffe.cpp:501] detection_eval = 0.0428833
-I0511 11:49:27.145442  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145443  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145447  4597 caffe.cpp:501] detection_eval = 1.13105
-I0511 11:49:27.145448  4597 caffe.cpp:501] detection_eval = 10.246
-I0511 11:49:27.145452  4597 caffe.cpp:501] detection_eval = 0.0500312
-I0511 11:49:27.145453  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145455  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145458  4597 caffe.cpp:501] detection_eval = 1.13306
-I0511 11:49:27.145460  4597 caffe.cpp:501] detection_eval = 10.2681
-I0511 11:49:27.145463  4597 caffe.cpp:501] detection_eval = 0.0444223
-I0511 11:49:27.145465  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145467  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145470  4597 caffe.cpp:501] detection_eval = 1.13508
-I0511 11:49:27.145473  4597 caffe.cpp:501] detection_eval = 10.3004
-I0511 11:49:27.145475  4597 caffe.cpp:501] detection_eval = 0.0467727
-I0511 11:49:27.145478  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145480  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.145483  4597 caffe.cpp:501] detection_eval = 1.1371
-I0511 11:49:27.145484  4597 caffe.cpp:501] detection_eval = 10.3972
-I0511 11:49:27.145488  4597 caffe.cpp:501] detection_eval = 0.047602
-I0511 11:49:27.145490  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145493  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145495  4597 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:49:27.145498  4597 caffe.cpp:501] detection_eval = 10.4214
-I0511 11:49:27.145501  4597 caffe.cpp:501] detection_eval = 0.0430616
-I0511 11:49:27.145506  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145509  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145512  4597 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:49:27.145514  4597 caffe.cpp:501] detection_eval = 10.4516
-I0511 11:49:27.145517  4597 caffe.cpp:501] detection_eval = 0.040741
-I0511 11:49:27.145519  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145522  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145524  4597 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:49:27.145526  4597 caffe.cpp:501] detection_eval = 10.5323
-I0511 11:49:27.145529  4597 caffe.cpp:501] detection_eval = 0.0401114
-I0511 11:49:27.145532  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145534  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145536  4597 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:49:27.145539  4597 caffe.cpp:501] detection_eval = 10.6028
-I0511 11:49:27.145542  4597 caffe.cpp:501] detection_eval = 0.0464177
-I0511 11:49:27.145545  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145546  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.145550  4597 caffe.cpp:501] detection_eval = 1.14315
-I0511 11:49:27.145551  4597 caffe.cpp:501] detection_eval = 10.6552
-I0511 11:49:27.145555  4597 caffe.cpp:501] detection_eval = 0.0518352
-I0511 11:49:27.145556  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.145560  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145561  4597 caffe.cpp:501] detection_eval = 1.14315
-I0511 11:49:27.145565  4597 caffe.cpp:501] detection_eval = 10.7379
-I0511 11:49:27.145566  4597 caffe.cpp:501] detection_eval = 0.0485364
-I0511 11:49:27.145570  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145571  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145575  4597 caffe.cpp:501] detection_eval = 1.14516
-I0511 11:49:27.145576  4597 caffe.cpp:501] detection_eval = 10.7823
-I0511 11:49:27.145579  4597 caffe.cpp:501] detection_eval = 0.0425106
-I0511 11:49:27.145581  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145584  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145586  4597 caffe.cpp:501] detection_eval = 1.14516
-I0511 11:49:27.145588  4597 caffe.cpp:501] detection_eval = 10.8851
-I0511 11:49:27.145592  4597 caffe.cpp:501] detection_eval = 0.0433279
-I0511 11:49:27.145594  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145597  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.145599  4597 caffe.cpp:501] detection_eval = 1.14718
-I0511 11:49:27.145602  4597 caffe.cpp:501] detection_eval = 10.9294
-I0511 11:49:27.145604  4597 caffe.cpp:501] detection_eval = 0.0416914
-I0511 11:49:27.145607  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145611  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145612  4597 caffe.cpp:501] detection_eval = 1.14919
-I0511 11:49:27.145615  4597 caffe.cpp:501] detection_eval = 11
-I0511 11:49:27.145618  4597 caffe.cpp:501] detection_eval = 0.0450898
-I0511 11:49:27.145620  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145623  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145625  4597 caffe.cpp:501] detection_eval = 1.15121
-I0511 11:49:27.145628  4597 caffe.cpp:501] detection_eval = 11.1048
-I0511 11:49:27.145630  4597 caffe.cpp:501] detection_eval = 0.0448681
-I0511 11:49:27.145633  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145635  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145638  4597 caffe.cpp:501] detection_eval = 1.15121
-I0511 11:49:27.145640  4597 caffe.cpp:501] detection_eval = 11.1915
-I0511 11:49:27.145643  4597 caffe.cpp:501] detection_eval = 0.0498553
-I0511 11:49:27.145645  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145648  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.145650  4597 caffe.cpp:501] detection_eval = 1.15121
-I0511 11:49:27.145653  4597 caffe.cpp:501] detection_eval = 11.2379
-I0511 11:49:27.145658  4597 caffe.cpp:501] detection_eval = 0.0413096
-I0511 11:49:27.145661  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145663  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145666  4597 caffe.cpp:501] detection_eval = 1.15121
-I0511 11:49:27.145669  4597 caffe.cpp:501] detection_eval = 11.3387
-I0511 11:49:27.145671  4597 caffe.cpp:501] detection_eval = 0.0436923
-I0511 11:49:27.145674  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145678  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145679  4597 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:49:27.145682  4597 caffe.cpp:501] detection_eval = 11.3569
-I0511 11:49:27.145684  4597 caffe.cpp:501] detection_eval = 0.0404503
-I0511 11:49:27.145687  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145689  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145691  4597 caffe.cpp:501] detection_eval = 1.15726
-I0511 11:49:27.145694  4597 caffe.cpp:501] detection_eval = 11.3125
-I0511 11:49:27.145696  4597 caffe.cpp:501] detection_eval = 0.042096
-I0511 11:49:27.145699  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145701  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145704  4597 caffe.cpp:501] detection_eval = 1.16129
-I0511 11:49:27.145706  4597 caffe.cpp:501] detection_eval = 11.3024
-I0511 11:49:27.145709  4597 caffe.cpp:501] detection_eval = 0.0446841
-I0511 11:49:27.145711  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145714  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145716  4597 caffe.cpp:501] detection_eval = 1.16331
-I0511 11:49:27.145720  4597 caffe.cpp:501] detection_eval = 11.3387
-I0511 11:49:27.145722  4597 caffe.cpp:501] detection_eval = 0.0416956
-I0511 11:49:27.145725  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145727  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145730  4597 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:49:27.145731  4597 caffe.cpp:501] detection_eval = 11.3851
-I0511 11:49:27.145735  4597 caffe.cpp:501] detection_eval = 0.043156
-I0511 11:49:27.145736  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145738  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145741  4597 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:49:27.145743  4597 caffe.cpp:501] detection_eval = 11.4758
-I0511 11:49:27.145746  4597 caffe.cpp:501] detection_eval = 0.0440364
-I0511 11:49:27.145748  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145750  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145753  4597 caffe.cpp:501] detection_eval = 1.16935
-I0511 11:49:27.145756  4597 caffe.cpp:501] detection_eval = 11.5081
-I0511 11:49:27.145758  4597 caffe.cpp:501] detection_eval = 0.0416945
-I0511 11:49:27.145761  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145763  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.145766  4597 caffe.cpp:501] detection_eval = 1.17339
-I0511 11:49:27.145768  4597 caffe.cpp:501] detection_eval = 11.5282
-I0511 11:49:27.145771  4597 caffe.cpp:501] detection_eval = 0.0406592
-I0511 11:49:27.145774  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.145776  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145778  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145781  4597 caffe.cpp:501] detection_eval = 11.5847
-I0511 11:49:27.145783  4597 caffe.cpp:501] detection_eval = 0.041443
-I0511 11:49:27.145787  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145788  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145792  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145793  4597 caffe.cpp:501] detection_eval = 11.6573
-I0511 11:49:27.145797  4597 caffe.cpp:501] detection_eval = 0.0402786
-I0511 11:49:27.145798  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.145802  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.145803  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145805  4597 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:49:27.145812  4597 caffe.cpp:501] detection_eval = 0.0423552
-I0511 11:49:27.145817  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145819  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145822  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145824  4597 caffe.cpp:501] detection_eval = 11.8145
-I0511 11:49:27.145826  4597 caffe.cpp:501] detection_eval = 0.0458264
-I0511 11:49:27.145829  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145831  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.145834  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145836  4597 caffe.cpp:501] detection_eval = 11.8609
-I0511 11:49:27.145839  4597 caffe.cpp:501] detection_eval = 0.0438705
-I0511 11:49:27.145841  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145843  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.145846  4597 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:49:27.145848  4597 caffe.cpp:501] detection_eval = 11.9577
-I0511 11:49:27.145851  4597 caffe.cpp:501] detection_eval = 0.0431666
-I0511 11:49:27.145853  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145855  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145859  4597 caffe.cpp:501] detection_eval = 1.17944
-I0511 11:49:27.145860  4597 caffe.cpp:501] detection_eval = 11.9738
-I0511 11:49:27.145864  4597 caffe.cpp:501] detection_eval = 0.0449846
-I0511 11:49:27.145865  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145869  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145870  4597 caffe.cpp:501] detection_eval = 1.18145
-I0511 11:49:27.145874  4597 caffe.cpp:501] detection_eval = 12.0323
-I0511 11:49:27.145875  4597 caffe.cpp:501] detection_eval = 0.0450107
-I0511 11:49:27.145879  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145880  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145884  4597 caffe.cpp:501] detection_eval = 1.18145
-I0511 11:49:27.145885  4597 caffe.cpp:501] detection_eval = 12.119
-I0511 11:49:27.145889  4597 caffe.cpp:501] detection_eval = 0.0485021
-I0511 11:49:27.145890  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145893  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145895  4597 caffe.cpp:501] detection_eval = 1.18145
-I0511 11:49:27.145897  4597 caffe.cpp:501] detection_eval = 12.1774
-I0511 11:49:27.145900  4597 caffe.cpp:501] detection_eval = 0.0465926
-I0511 11:49:27.145902  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145905  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.145907  4597 caffe.cpp:501] detection_eval = 1.18347
-I0511 11:49:27.145910  4597 caffe.cpp:501] detection_eval = 12.244
-I0511 11:49:27.145912  4597 caffe.cpp:501] detection_eval = 0.0446817
-I0511 11:49:27.145915  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.145917  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145920  4597 caffe.cpp:501] detection_eval = 1.18548
-I0511 11:49:27.145922  4597 caffe.cpp:501] detection_eval = 12.3206
-I0511 11:49:27.145925  4597 caffe.cpp:501] detection_eval = 0.0488514
-I0511 11:49:27.145926  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.145929  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145931  4597 caffe.cpp:501] detection_eval = 1.1875
-I0511 11:49:27.145934  4597 caffe.cpp:501] detection_eval = 12.3589
-I0511 11:49:27.145936  4597 caffe.cpp:501] detection_eval = 0.0448765
-I0511 11:49:27.145939  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.145941  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.145944  4597 caffe.cpp:501] detection_eval = 1.18952
-I0511 11:49:27.145946  4597 caffe.cpp:501] detection_eval = 12.3972
-I0511 11:49:27.145951  4597 caffe.cpp:501] detection_eval = 0.0514622
-I0511 11:49:27.145952  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.145956  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.145957  4597 caffe.cpp:501] detection_eval = 1.19355
-I0511 11:49:27.145962  4597 caffe.cpp:501] detection_eval = 12.4032
-I0511 11:49:27.145965  4597 caffe.cpp:501] detection_eval = 0.0471194
-I0511 11:49:27.145968  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145970  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.145973  4597 caffe.cpp:501] detection_eval = 1.19556
-I0511 11:49:27.145975  4597 caffe.cpp:501] detection_eval = 12.4335
-I0511 11:49:27.145978  4597 caffe.cpp:501] detection_eval = 0.0434861
-I0511 11:49:27.145980  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.145983  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.145985  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.145988  4597 caffe.cpp:501] detection_eval = 12.4395
-I0511 11:49:27.145990  4597 caffe.cpp:501] detection_eval = 0.0407979
-I0511 11:49:27.145993  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.145995  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.145998  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.146000  4597 caffe.cpp:501] detection_eval = 12.498
-I0511 11:49:27.146003  4597 caffe.cpp:501] detection_eval = 0.0435581
-I0511 11:49:27.146005  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.146008  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.146010  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.146013  4597 caffe.cpp:501] detection_eval = 12.5827
-I0511 11:49:27.146016  4597 caffe.cpp:501] detection_eval = 0.0457352
-I0511 11:49:27.146018  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146021  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146023  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.146025  4597 caffe.cpp:501] detection_eval = 12.6613
-I0511 11:49:27.146028  4597 caffe.cpp:501] detection_eval = 0.0438167
-I0511 11:49:27.146030  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146034  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146035  4597 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:49:27.146039  4597 caffe.cpp:501] detection_eval = 12.7238
-I0511 11:49:27.146040  4597 caffe.cpp:501] detection_eval = 0.0418078
-I0511 11:49:27.146042  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146045  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146047  4597 caffe.cpp:501] detection_eval = 1.20766
-I0511 11:49:27.146050  4597 caffe.cpp:501] detection_eval = 12.6895
-I0511 11:49:27.146052  4597 caffe.cpp:501] detection_eval = 0.0447596
-I0511 11:49:27.146055  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146057  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146060  4597 caffe.cpp:501] detection_eval = 1.20766
-I0511 11:49:27.146062  4597 caffe.cpp:501] detection_eval = 12.756
-I0511 11:49:27.146065  4597 caffe.cpp:501] detection_eval = 0.0435381
-I0511 11:49:27.146067  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146070  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146072  4597 caffe.cpp:501] detection_eval = 1.20968
-I0511 11:49:27.146075  4597 caffe.cpp:501] detection_eval = 12.7802
-I0511 11:49:27.146077  4597 caffe.cpp:501] detection_eval = 0.0456512
-I0511 11:49:27.146080  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146081  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146085  4597 caffe.cpp:501] detection_eval = 1.21169
-I0511 11:49:27.146086  4597 caffe.cpp:501] detection_eval = 12.8266
-I0511 11:49:27.146090  4597 caffe.cpp:501] detection_eval = 0.0449135
-I0511 11:49:27.146092  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.146095  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.146097  4597 caffe.cpp:501] detection_eval = 1.21573
-I0511 11:49:27.146100  4597 caffe.cpp:501] detection_eval = 12.8347
-I0511 11:49:27.146102  4597 caffe.cpp:501] detection_eval = 0.04379
-I0511 11:49:27.146106  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146107  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146111  4597 caffe.cpp:501] detection_eval = 1.21573
-I0511 11:49:27.146116  4597 caffe.cpp:501] detection_eval = 12.9073
-I0511 11:49:27.146118  4597 caffe.cpp:501] detection_eval = 0.0412596
-I0511 11:49:27.146121  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146123  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146126  4597 caffe.cpp:501] detection_eval = 1.22177
-I0511 11:49:27.146128  4597 caffe.cpp:501] detection_eval = 12.8831
-I0511 11:49:27.146131  4597 caffe.cpp:501] detection_eval = 0.0390567
-I0511 11:49:27.146133  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146136  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146138  4597 caffe.cpp:501] detection_eval = 1.22581
-I0511 11:49:27.146142  4597 caffe.cpp:501] detection_eval = 12.875
-I0511 11:49:27.146143  4597 caffe.cpp:501] detection_eval = 0.0453133
-I0511 11:49:27.146147  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146148  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146152  4597 caffe.cpp:501] detection_eval = 1.23185
-I0511 11:49:27.146153  4597 caffe.cpp:501] detection_eval = 12.8468
-I0511 11:49:27.146157  4597 caffe.cpp:501] detection_eval = 0.041157
-I0511 11:49:27.146158  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146162  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146163  4597 caffe.cpp:501] detection_eval = 1.23387
-I0511 11:49:27.146167  4597 caffe.cpp:501] detection_eval = 12.877
-I0511 11:49:27.146169  4597 caffe.cpp:501] detection_eval = 0.0393585
-I0511 11:49:27.146172  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146173  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146176  4597 caffe.cpp:501] detection_eval = 1.23589
-I0511 11:49:27.146178  4597 caffe.cpp:501] detection_eval = 12.9315
-I0511 11:49:27.146181  4597 caffe.cpp:501] detection_eval = 0.0382644
-I0511 11:49:27.146184  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146186  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146189  4597 caffe.cpp:501] detection_eval = 1.23589
-I0511 11:49:27.146193  4597 caffe.cpp:501] detection_eval = 12.9738
-I0511 11:49:27.146194  4597 caffe.cpp:501] detection_eval = 0.0372697
-I0511 11:49:27.146198  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146199  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146201  4597 caffe.cpp:501] detection_eval = 1.23589
-I0511 11:49:27.146204  4597 caffe.cpp:501] detection_eval = 13.0645
-I0511 11:49:27.146206  4597 caffe.cpp:501] detection_eval = 0.0392381
-I0511 11:49:27.146209  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146211  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146214  4597 caffe.cpp:501] detection_eval = 1.23992
-I0511 11:49:27.146216  4597 caffe.cpp:501] detection_eval = 13.0706
-I0511 11:49:27.146219  4597 caffe.cpp:501] detection_eval = 0.0395565
-I0511 11:49:27.146221  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146224  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146226  4597 caffe.cpp:501] detection_eval = 1.24395
-I0511 11:49:27.146229  4597 caffe.cpp:501] detection_eval = 13.0484
-I0511 11:49:27.146231  4597 caffe.cpp:501] detection_eval = 0.0409841
-I0511 11:49:27.146234  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146236  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146239  4597 caffe.cpp:501] detection_eval = 1.24597
-I0511 11:49:27.146241  4597 caffe.cpp:501] detection_eval = 13.0927
-I0511 11:49:27.146245  4597 caffe.cpp:501] detection_eval = 0.0409264
-I0511 11:49:27.146246  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.146250  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.146251  4597 caffe.cpp:501] detection_eval = 1.24597
-I0511 11:49:27.146255  4597 caffe.cpp:501] detection_eval = 13.1613
-I0511 11:49:27.146257  4597 caffe.cpp:501] detection_eval = 0.0407683
-I0511 11:49:27.146260  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146262  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146267  4597 caffe.cpp:501] detection_eval = 1.25
-I0511 11:49:27.146270  4597 caffe.cpp:501] detection_eval = 13.1532
-I0511 11:49:27.146272  4597 caffe.cpp:501] detection_eval = 0.0435359
-I0511 11:49:27.146275  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.146277  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.146281  4597 caffe.cpp:501] detection_eval = 1.25202
-I0511 11:49:27.146282  4597 caffe.cpp:501] detection_eval = 13.1714
-I0511 11:49:27.146286  4597 caffe.cpp:501] detection_eval = 0.0407399
-I0511 11:49:27.146287  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146291  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146292  4597 caffe.cpp:501] detection_eval = 1.25202
-I0511 11:49:27.146294  4597 caffe.cpp:501] detection_eval = 13.2077
-I0511 11:49:27.146297  4597 caffe.cpp:501] detection_eval = 0.0377397
-I0511 11:49:27.146301  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146302  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146304  4597 caffe.cpp:501] detection_eval = 1.25202
-I0511 11:49:27.146307  4597 caffe.cpp:501] detection_eval = 13.2641
-I0511 11:49:27.146309  4597 caffe.cpp:501] detection_eval = 0.0362508
-I0511 11:49:27.146312  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146314  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146317  4597 caffe.cpp:501] detection_eval = 1.25605
-I0511 11:49:27.146319  4597 caffe.cpp:501] detection_eval = 13.2984
-I0511 11:49:27.146322  4597 caffe.cpp:501] detection_eval = 0.0408606
-I0511 11:49:27.146324  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146327  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146329  4597 caffe.cpp:501] detection_eval = 1.25806
-I0511 11:49:27.146332  4597 caffe.cpp:501] detection_eval = 13.3004
-I0511 11:49:27.146335  4597 caffe.cpp:501] detection_eval = 0.0369961
-I0511 11:49:27.146337  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146340  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146342  4597 caffe.cpp:501] detection_eval = 1.25806
-I0511 11:49:27.146345  4597 caffe.cpp:501] detection_eval = 13.3427
-I0511 11:49:27.146348  4597 caffe.cpp:501] detection_eval = 0.0363474
-I0511 11:49:27.146350  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146353  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146356  4597 caffe.cpp:501] detection_eval = 1.25806
-I0511 11:49:27.146358  4597 caffe.cpp:501] detection_eval = 13.3911
-I0511 11:49:27.146361  4597 caffe.cpp:501] detection_eval = 0.0379257
-I0511 11:49:27.146363  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146366  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146368  4597 caffe.cpp:501] detection_eval = 1.2621
-I0511 11:49:27.146371  4597 caffe.cpp:501] detection_eval = 13.377
-I0511 11:49:27.146374  4597 caffe.cpp:501] detection_eval = 0.0377221
-I0511 11:49:27.146376  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146378  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146381  4597 caffe.cpp:501] detection_eval = 1.26613
-I0511 11:49:27.146384  4597 caffe.cpp:501] detection_eval = 13.375
-I0511 11:49:27.146385  4597 caffe.cpp:501] detection_eval = 0.0383149
-I0511 11:49:27.146387  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146390  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146392  4597 caffe.cpp:501] detection_eval = 1.26613
-I0511 11:49:27.146395  4597 caffe.cpp:501] detection_eval = 13.4355
-I0511 11:49:27.146397  4597 caffe.cpp:501] detection_eval = 0.040566
-I0511 11:49:27.146400  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146402  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146405  4597 caffe.cpp:501] detection_eval = 1.26613
-I0511 11:49:27.146407  4597 caffe.cpp:501] detection_eval = 13.4637
-I0511 11:49:27.146410  4597 caffe.cpp:501] detection_eval = 0.0353715
-I0511 11:49:27.146412  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146417  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146420  4597 caffe.cpp:501] detection_eval = 1.26815
-I0511 11:49:27.146423  4597 caffe.cpp:501] detection_eval = 13.4758
-I0511 11:49:27.146425  4597 caffe.cpp:501] detection_eval = 0.0362634
-I0511 11:49:27.146428  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146430  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146432  4597 caffe.cpp:501] detection_eval = 1.26815
-I0511 11:49:27.146435  4597 caffe.cpp:501] detection_eval = 13.5101
-I0511 11:49:27.146438  4597 caffe.cpp:501] detection_eval = 0.0366599
-I0511 11:49:27.146440  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146442  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146445  4597 caffe.cpp:501] detection_eval = 1.27218
-I0511 11:49:27.146447  4597 caffe.cpp:501] detection_eval = 13.5101
-I0511 11:49:27.146450  4597 caffe.cpp:501] detection_eval = 0.0381063
-I0511 11:49:27.146452  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146455  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146456  4597 caffe.cpp:501] detection_eval = 1.27823
-I0511 11:49:27.146459  4597 caffe.cpp:501] detection_eval = 13.4637
-I0511 11:49:27.146462  4597 caffe.cpp:501] detection_eval = 0.0346172
-I0511 11:49:27.146464  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146467  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146469  4597 caffe.cpp:501] detection_eval = 1.28226
-I0511 11:49:27.146472  4597 caffe.cpp:501] detection_eval = 13.4456
-I0511 11:49:27.146476  4597 caffe.cpp:501] detection_eval = 0.0336624
-I0511 11:49:27.146477  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146481  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146482  4597 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:49:27.146486  4597 caffe.cpp:501] detection_eval = 13.4194
-I0511 11:49:27.146488  4597 caffe.cpp:501] detection_eval = 0.0336696
-I0511 11:49:27.146490  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146493  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146495  4597 caffe.cpp:501] detection_eval = 1.28831
-I0511 11:49:27.146498  4597 caffe.cpp:501] detection_eval = 13.4375
-I0511 11:49:27.146500  4597 caffe.cpp:501] detection_eval = 0.037632
-I0511 11:49:27.146503  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146505  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146508  4597 caffe.cpp:501] detection_eval = 1.29032
-I0511 11:49:27.146510  4597 caffe.cpp:501] detection_eval = 13.4355
-I0511 11:49:27.146513  4597 caffe.cpp:501] detection_eval = 0.0397644
-I0511 11:49:27.146515  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146517  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146520  4597 caffe.cpp:501] detection_eval = 1.29032
-I0511 11:49:27.146522  4597 caffe.cpp:501] detection_eval = 13.4839
-I0511 11:49:27.146525  4597 caffe.cpp:501] detection_eval = 0.0340828
-I0511 11:49:27.146528  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146530  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146533  4597 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:49:27.146534  4597 caffe.cpp:501] detection_eval = 13.4899
-I0511 11:49:27.146538  4597 caffe.cpp:501] detection_eval = 0.0370037
-I0511 11:49:27.146540  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146543  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146545  4597 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:49:27.146548  4597 caffe.cpp:501] detection_eval = 13.5141
-I0511 11:49:27.146550  4597 caffe.cpp:501] detection_eval = 0.0316733
-I0511 11:49:27.146553  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.146556  4597 caffe.cpp:501] detection_eval = 1
-I0511 11:49:27.146559  4597 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:49:27.146561  4597 caffe.cpp:501] detection_eval = 13.5827
-I0511 11:49:27.146564  4597 caffe.cpp:501] detection_eval = 0.035012
-I0511 11:49:27.146566  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146572  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146575  4597 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:49:27.146577  4597 caffe.cpp:501] detection_eval = 13.6149
-I0511 11:49:27.146580  4597 caffe.cpp:501] detection_eval = 0.0362268
-I0511 11:49:27.146582  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146585  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146587  4597 caffe.cpp:501] detection_eval = 1.29637
-I0511 11:49:27.146589  4597 caffe.cpp:501] detection_eval = 13.5968
-I0511 11:49:27.146594  4597 caffe.cpp:501] detection_eval = 0.032313
-I0511 11:49:27.146595  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146598  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146600  4597 caffe.cpp:501] detection_eval = 1.29637
-I0511 11:49:27.146602  4597 caffe.cpp:501] detection_eval = 13.6532
-I0511 11:49:27.146606  4597 caffe.cpp:501] detection_eval = 0.0374724
-I0511 11:49:27.146608  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146611  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146613  4597 caffe.cpp:501] detection_eval = 1.29839
-I0511 11:49:27.146615  4597 caffe.cpp:501] detection_eval = 13.6835
-I0511 11:49:27.146620  4597 caffe.cpp:501] detection_eval = 0.0350892
-I0511 11:49:27.146622  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146625  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146626  4597 caffe.cpp:501] detection_eval = 1.30242
-I0511 11:49:27.146630  4597 caffe.cpp:501] detection_eval = 13.6552
-I0511 11:49:27.146631  4597 caffe.cpp:501] detection_eval = 0.0345291
-I0511 11:49:27.146634  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146636  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146639  4597 caffe.cpp:501] detection_eval = 1.30645
-I0511 11:49:27.146641  4597 caffe.cpp:501] detection_eval = 13.6512
-I0511 11:49:27.146646  4597 caffe.cpp:501] detection_eval = 0.0392117
-I0511 11:49:27.146647  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146649  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146652  4597 caffe.cpp:501] detection_eval = 1.30847
-I0511 11:49:27.146654  4597 caffe.cpp:501] detection_eval = 13.6694
-I0511 11:49:27.146657  4597 caffe.cpp:501] detection_eval = 0.0382653
-I0511 11:49:27.146661  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146662  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146664  4597 caffe.cpp:501] detection_eval = 1.30847
-I0511 11:49:27.146667  4597 caffe.cpp:501] detection_eval = 13.7198
-I0511 11:49:27.146669  4597 caffe.cpp:501] detection_eval = 0.0359233
-I0511 11:49:27.146672  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146674  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146677  4597 caffe.cpp:501] detection_eval = 1.3125
-I0511 11:49:27.146679  4597 caffe.cpp:501] detection_eval = 13.7077
-I0511 11:49:27.146683  4597 caffe.cpp:501] detection_eval = 0.035042
-I0511 11:49:27.146685  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146687  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146690  4597 caffe.cpp:501] detection_eval = 1.31653
-I0511 11:49:27.146692  4597 caffe.cpp:501] detection_eval = 13.6915
-I0511 11:49:27.146694  4597 caffe.cpp:501] detection_eval = 0.0348875
-I0511 11:49:27.146697  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.146699  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.146703  4597 caffe.cpp:501] detection_eval = 1.31855
-I0511 11:49:27.146704  4597 caffe.cpp:501] detection_eval = 13.7198
-I0511 11:49:27.146708  4597 caffe.cpp:501] detection_eval = 0.0367038
-I0511 11:49:27.146709  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146713  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.146714  4597 caffe.cpp:501] detection_eval = 1.32661
-I0511 11:49:27.146716  4597 caffe.cpp:501] detection_eval = 13.6552
-I0511 11:49:27.146719  4597 caffe.cpp:501] detection_eval = 0.0385572
-I0511 11:49:27.146724  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146728  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146730  4597 caffe.cpp:501] detection_eval = 1.32661
-I0511 11:49:27.146733  4597 caffe.cpp:501] detection_eval = 13.7419
-I0511 11:49:27.146736  4597 caffe.cpp:501] detection_eval = 0.0396626
-I0511 11:49:27.146739  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146741  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146744  4597 caffe.cpp:501] detection_eval = 1.33266
-I0511 11:49:27.146746  4597 caffe.cpp:501] detection_eval = 13.7641
-I0511 11:49:27.146749  4597 caffe.cpp:501] detection_eval = 0.0398071
-I0511 11:49:27.146752  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146754  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146757  4597 caffe.cpp:501] detection_eval = 1.33468
-I0511 11:49:27.146759  4597 caffe.cpp:501] detection_eval = 13.7964
-I0511 11:49:27.146764  4597 caffe.cpp:501] detection_eval = 0.0363419
-I0511 11:49:27.146765  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146767  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146770  4597 caffe.cpp:501] detection_eval = 1.33871
-I0511 11:49:27.146773  4597 caffe.cpp:501] detection_eval = 13.8387
-I0511 11:49:27.146775  4597 caffe.cpp:501] detection_eval = 0.0390332
-I0511 11:49:27.146778  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146781  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146785  4597 caffe.cpp:501] detection_eval = 1.34274
-I0511 11:49:27.146786  4597 caffe.cpp:501] detection_eval = 13.8427
-I0511 11:49:27.146790  4597 caffe.cpp:501] detection_eval = 0.0365928
-I0511 11:49:27.146792  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146795  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146797  4597 caffe.cpp:501] detection_eval = 1.34476
-I0511 11:49:27.146800  4597 caffe.cpp:501] detection_eval = 13.9173
-I0511 11:49:27.146802  4597 caffe.cpp:501] detection_eval = 0.035152
-I0511 11:49:27.146806  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146808  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146811  4597 caffe.cpp:501] detection_eval = 1.34677
-I0511 11:49:27.146812  4597 caffe.cpp:501] detection_eval = 14.002
-I0511 11:49:27.146816  4597 caffe.cpp:501] detection_eval = 0.0362133
-I0511 11:49:27.146819  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146822  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.146824  4597 caffe.cpp:501] detection_eval = 1.34677
-I0511 11:49:27.146827  4597 caffe.cpp:501] detection_eval = 14.0907
-I0511 11:49:27.146831  4597 caffe.cpp:501] detection_eval = 0.0410121
-I0511 11:49:27.146832  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.146836  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.146837  4597 caffe.cpp:501] detection_eval = 1.34677
-I0511 11:49:27.146841  4597 caffe.cpp:501] detection_eval = 14.2258
-I0511 11:49:27.146842  4597 caffe.cpp:501] detection_eval = 0.0446848
-I0511 11:49:27.146845  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.146847  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146849  4597 caffe.cpp:501] detection_eval = 1.34879
-I0511 11:49:27.146852  4597 caffe.cpp:501] detection_eval = 14.2621
-I0511 11:49:27.146854  4597 caffe.cpp:501] detection_eval = 0.0358699
-I0511 11:49:27.146857  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146860  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146863  4597 caffe.cpp:501] detection_eval = 1.3629
-I0511 11:49:27.146865  4597 caffe.cpp:501] detection_eval = 14.1754
-I0511 11:49:27.146868  4597 caffe.cpp:501] detection_eval = 0.0348599
-I0511 11:49:27.146870  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146873  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.146875  4597 caffe.cpp:501] detection_eval = 1.3629
-I0511 11:49:27.146878  4597 caffe.cpp:501] detection_eval = 14.2581
-I0511 11:49:27.146880  4597 caffe.cpp:501] detection_eval = 0.0377557
-I0511 11:49:27.146886  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146889  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146893  4597 caffe.cpp:501] detection_eval = 1.36492
-I0511 11:49:27.146894  4597 caffe.cpp:501] detection_eval = 14.3468
-I0511 11:49:27.146898  4597 caffe.cpp:501] detection_eval = 0.035452
-I0511 11:49:27.146899  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.146901  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.146903  4597 caffe.cpp:501] detection_eval = 1.36694
-I0511 11:49:27.146906  4597 caffe.cpp:501] detection_eval = 14.4718
-I0511 11:49:27.146908  4597 caffe.cpp:501] detection_eval = 0.0382334
-I0511 11:49:27.146910  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146914  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146915  4597 caffe.cpp:501] detection_eval = 1.37097
-I0511 11:49:27.146917  4597 caffe.cpp:501] detection_eval = 14.5948
-I0511 11:49:27.146920  4597 caffe.cpp:501] detection_eval = 0.0380794
-I0511 11:49:27.146922  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.146925  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146927  4597 caffe.cpp:501] detection_eval = 1.37097
-I0511 11:49:27.146929  4597 caffe.cpp:501] detection_eval = 14.9194
-I0511 11:49:27.146932  4597 caffe.cpp:501] detection_eval = 0.0322236
-I0511 11:49:27.146934  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146936  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.146939  4597 caffe.cpp:501] detection_eval = 1.37298
-I0511 11:49:27.146941  4597 caffe.cpp:501] detection_eval = 15.2298
-I0511 11:49:27.146944  4597 caffe.cpp:501] detection_eval = 0.0331973
-I0511 11:49:27.146946  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.146948  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.146950  4597 caffe.cpp:501] detection_eval = 2.04234
-I0511 11:49:27.146953  4597 caffe.cpp:501] detection_eval = 5.3004
-I0511 11:49:27.146956  4597 caffe.cpp:501] detection_eval = 0.133413
-I0511 11:49:27.146960  4597 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:49:27.146962  4597 caffe.cpp:501] detection_eval = 0.885081
-I0511 11:49:27.146965  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.146968  4597 caffe.cpp:501] detection_eval = 5.52218
-I0511 11:49:27.146970  4597 caffe.cpp:501] detection_eval = 0.0676833
-I0511 11:49:27.146973  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.146976  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.146978  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.146981  4597 caffe.cpp:501] detection_eval = 5.72581
-I0511 11:49:27.146983  4597 caffe.cpp:501] detection_eval = 0.0587982
-I0511 11:49:27.146986  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.146988  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.146991  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.146992  4597 caffe.cpp:501] detection_eval = 5.90524
-I0511 11:49:27.146996  4597 caffe.cpp:501] detection_eval = 0.0458608
-I0511 11:49:27.146998  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147001  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.147002  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.147006  4597 caffe.cpp:501] detection_eval = 6.05444
-I0511 11:49:27.147007  4597 caffe.cpp:501] detection_eval = 0.0518086
-I0511 11:49:27.147011  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.147012  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147014  4597 caffe.cpp:501] detection_eval = 2.04637
-I0511 11:49:27.147017  4597 caffe.cpp:501] detection_eval = 6.18347
-I0511 11:49:27.147019  4597 caffe.cpp:501] detection_eval = 0.0473676
-I0511 11:49:27.147022  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.147024  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147027  4597 caffe.cpp:501] detection_eval = 2.04839
-I0511 11:49:27.147029  4597 caffe.cpp:501] detection_eval = 6.21976
-I0511 11:49:27.147035  4597 caffe.cpp:501] detection_eval = 0.0447459
-I0511 11:49:27.147037  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.147040  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.147042  4597 caffe.cpp:501] detection_eval = 2.05242
-I0511 11:49:27.147045  4597 caffe.cpp:501] detection_eval = 6.21774
-I0511 11:49:27.147047  4597 caffe.cpp:501] detection_eval = 0.0400823
-I0511 11:49:27.147050  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147053  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147055  4597 caffe.cpp:501] detection_eval = 2.05645
-I0511 11:49:27.147058  4597 caffe.cpp:501] detection_eval = 6.22581
-I0511 11:49:27.147060  4597 caffe.cpp:501] detection_eval = 0.0409995
-I0511 11:49:27.147063  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147065  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.147068  4597 caffe.cpp:501] detection_eval = 2.05645
-I0511 11:49:27.147070  4597 caffe.cpp:501] detection_eval = 6.30444
-I0511 11:49:27.147073  4597 caffe.cpp:501] detection_eval = 0.0415906
-I0511 11:49:27.147075  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147078  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147079  4597 caffe.cpp:501] detection_eval = 2.05645
-I0511 11:49:27.147083  4597 caffe.cpp:501] detection_eval = 6.41935
-I0511 11:49:27.147085  4597 caffe.cpp:501] detection_eval = 0.0442366
-I0511 11:49:27.147087  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147090  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147092  4597 caffe.cpp:501] detection_eval = 2.06048
-I0511 11:49:27.147095  4597 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:49:27.147097  4597 caffe.cpp:501] detection_eval = 0.0427659
-I0511 11:49:27.147099  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.147102  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147104  4597 caffe.cpp:501] detection_eval = 2.06048
-I0511 11:49:27.147107  4597 caffe.cpp:501] detection_eval = 6.58669
-I0511 11:49:27.147109  4597 caffe.cpp:501] detection_eval = 0.0390561
-I0511 11:49:27.147111  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.147114  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147116  4597 caffe.cpp:501] detection_eval = 2.0625
-I0511 11:49:27.147119  4597 caffe.cpp:501] detection_eval = 6.63306
-I0511 11:49:27.147122  4597 caffe.cpp:501] detection_eval = 0.0400544
-I0511 11:49:27.147125  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147130  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147135  4597 caffe.cpp:501] detection_eval = 2.06452
-I0511 11:49:27.147138  4597 caffe.cpp:501] detection_eval = 6.64315
-I0511 11:49:27.147143  4597 caffe.cpp:501] detection_eval = 0.0356438
-I0511 11:49:27.147147  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.147152  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147156  4597 caffe.cpp:501] detection_eval = 2.06653
-I0511 11:49:27.147161  4597 caffe.cpp:501] detection_eval = 6.67742
-I0511 11:49:27.147166  4597 caffe.cpp:501] detection_eval = 0.0377647
-I0511 11:49:27.147171  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147174  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147179  4597 caffe.cpp:501] detection_eval = 2.07056
-I0511 11:49:27.147184  4597 caffe.cpp:501] detection_eval = 6.71573
-I0511 11:49:27.147188  4597 caffe.cpp:501] detection_eval = 0.041873
-I0511 11:49:27.147193  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147197  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147202  4597 caffe.cpp:501] detection_eval = 2.07056
-I0511 11:49:27.147207  4597 caffe.cpp:501] detection_eval = 6.78831
-I0511 11:49:27.147212  4597 caffe.cpp:501] detection_eval = 0.0421586
-I0511 11:49:27.147215  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147220  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147225  4597 caffe.cpp:501] detection_eval = 2.0746
-I0511 11:49:27.147233  4597 caffe.cpp:501] detection_eval = 6.84073
-I0511 11:49:27.147238  4597 caffe.cpp:501] detection_eval = 0.0416998
-I0511 11:49:27.147243  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147246  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.147250  4597 caffe.cpp:501] detection_eval = 2.0746
-I0511 11:49:27.147254  4597 caffe.cpp:501] detection_eval = 6.95565
-I0511 11:49:27.147258  4597 caffe.cpp:501] detection_eval = 0.047217
-I0511 11:49:27.147263  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.147266  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.147271  4597 caffe.cpp:501] detection_eval = 2.07661
-I0511 11:49:27.147275  4597 caffe.cpp:501] detection_eval = 7.06048
-I0511 11:49:27.147279  4597 caffe.cpp:501] detection_eval = 0.0413395
-I0511 11:49:27.147282  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147286  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147290  4597 caffe.cpp:501] detection_eval = 2.07661
-I0511 11:49:27.147294  4597 caffe.cpp:501] detection_eval = 7.13306
-I0511 11:49:27.147297  4597 caffe.cpp:501] detection_eval = 0.0413058
-I0511 11:49:27.147302  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147305  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147310  4597 caffe.cpp:501] detection_eval = 2.07863
-I0511 11:49:27.147313  4597 caffe.cpp:501] detection_eval = 7.16734
-I0511 11:49:27.147317  4597 caffe.cpp:501] detection_eval = 0.0348343
-I0511 11:49:27.147321  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.147325  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.147328  4597 caffe.cpp:501] detection_eval = 2.08871
-I0511 11:49:27.147332  4597 caffe.cpp:501] detection_eval = 7.1371
-I0511 11:49:27.147336  4597 caffe.cpp:501] detection_eval = 0.0393197
-I0511 11:49:27.147339  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147343  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147348  4597 caffe.cpp:501] detection_eval = 2.09073
-I0511 11:49:27.147351  4597 caffe.cpp:501] detection_eval = 7.17944
-I0511 11:49:27.147356  4597 caffe.cpp:501] detection_eval = 0.0418969
-I0511 11:49:27.147359  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147363  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147367  4597 caffe.cpp:501] detection_eval = 2.09073
-I0511 11:49:27.147372  4597 caffe.cpp:501] detection_eval = 7.25806
-I0511 11:49:27.147374  4597 caffe.cpp:501] detection_eval = 0.0447404
-I0511 11:49:27.147378  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147382  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147387  4597 caffe.cpp:501] detection_eval = 2.09677
-I0511 11:49:27.147390  4597 caffe.cpp:501] detection_eval = 7.26008
-I0511 11:49:27.147394  4597 caffe.cpp:501] detection_eval = 0.0433293
-I0511 11:49:27.147397  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147402  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147405  4597 caffe.cpp:501] detection_eval = 2.10081
-I0511 11:49:27.147409  4597 caffe.cpp:501] detection_eval = 7.26815
-I0511 11:49:27.147413  4597 caffe.cpp:501] detection_eval = 0.0421945
-I0511 11:49:27.147418  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147421  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.147425  4597 caffe.cpp:501] detection_eval = 2.10282
-I0511 11:49:27.147429  4597 caffe.cpp:501] detection_eval = 7.33065
-I0511 11:49:27.147433  4597 caffe.cpp:501] detection_eval = 0.0455296
-I0511 11:49:27.147438  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147442  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147446  4597 caffe.cpp:501] detection_eval = 2.10282
-I0511 11:49:27.147450  4597 caffe.cpp:501] detection_eval = 7.42137
-I0511 11:49:27.147454  4597 caffe.cpp:501] detection_eval = 0.0425508
-I0511 11:49:27.147457  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147460  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147464  4597 caffe.cpp:501] detection_eval = 2.10282
-I0511 11:49:27.147476  4597 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:49:27.147480  4597 caffe.cpp:501] detection_eval = 0.0372372
-I0511 11:49:27.147485  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147487  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.147490  4597 caffe.cpp:501] detection_eval = 2.10685
-I0511 11:49:27.147495  4597 caffe.cpp:501] detection_eval = 7.52016
-I0511 11:49:27.147498  4597 caffe.cpp:501] detection_eval = 0.0412541
-I0511 11:49:27.147502  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147506  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147511  4597 caffe.cpp:501] detection_eval = 2.10887
-I0511 11:49:27.147514  4597 caffe.cpp:501] detection_eval = 7.57863
-I0511 11:49:27.147519  4597 caffe.cpp:501] detection_eval = 0.0397699
-I0511 11:49:27.147523  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147528  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147533  4597 caffe.cpp:501] detection_eval = 2.10887
-I0511 11:49:27.147537  4597 caffe.cpp:501] detection_eval = 7.625
-I0511 11:49:27.147542  4597 caffe.cpp:501] detection_eval = 0.0385895
-I0511 11:49:27.147547  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.147552  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.147555  4597 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:49:27.147560  4597 caffe.cpp:501] detection_eval = 7.64919
-I0511 11:49:27.147565  4597 caffe.cpp:501] detection_eval = 0.041084
-I0511 11:49:27.147569  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147573  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.147578  4597 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:49:27.147583  4597 caffe.cpp:501] detection_eval = 7.75
-I0511 11:49:27.147588  4597 caffe.cpp:501] detection_eval = 0.0403033
-I0511 11:49:27.147593  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147596  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.147601  4597 caffe.cpp:501] detection_eval = 2.1129
-I0511 11:49:27.147605  4597 caffe.cpp:501] detection_eval = 7.77823
-I0511 11:49:27.147610  4597 caffe.cpp:501] detection_eval = 0.0425358
-I0511 11:49:27.147614  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.147619  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.147624  4597 caffe.cpp:501] detection_eval = 2.11694
-I0511 11:49:27.147629  4597 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:49:27.147632  4597 caffe.cpp:501] detection_eval = 0.0427766
-I0511 11:49:27.147637  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147641  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147646  4597 caffe.cpp:501] detection_eval = 2.11895
-I0511 11:49:27.147650  4597 caffe.cpp:501] detection_eval = 7.83065
-I0511 11:49:27.147667  4597 caffe.cpp:501] detection_eval = 0.0400002
-I0511 11:49:27.147680  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147688  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147697  4597 caffe.cpp:501] detection_eval = 2.11895
-I0511 11:49:27.147708  4597 caffe.cpp:501] detection_eval = 7.89919
-I0511 11:49:27.147713  4597 caffe.cpp:501] detection_eval = 0.0405098
-I0511 11:49:27.147718  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147723  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147727  4597 caffe.cpp:501] detection_eval = 2.11895
-I0511 11:49:27.147732  4597 caffe.cpp:501] detection_eval = 7.97177
-I0511 11:49:27.147737  4597 caffe.cpp:501] detection_eval = 0.0406517
-I0511 11:49:27.147742  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147747  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147750  4597 caffe.cpp:501] detection_eval = 2.12298
-I0511 11:49:27.147755  4597 caffe.cpp:501] detection_eval = 8.02016
-I0511 11:49:27.147760  4597 caffe.cpp:501] detection_eval = 0.0412307
-I0511 11:49:27.147764  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147769  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147780  4597 caffe.cpp:501] detection_eval = 2.125
-I0511 11:49:27.147785  4597 caffe.cpp:501] detection_eval = 8.08468
-I0511 11:49:27.147790  4597 caffe.cpp:501] detection_eval = 0.0389765
-I0511 11:49:27.147795  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147799  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147804  4597 caffe.cpp:501] detection_eval = 2.12903
-I0511 11:49:27.147809  4597 caffe.cpp:501] detection_eval = 8.14718
-I0511 11:49:27.147814  4597 caffe.cpp:501] detection_eval = 0.035977
-I0511 11:49:27.147817  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.147822  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.147827  4597 caffe.cpp:501] detection_eval = 2.13105
-I0511 11:49:27.147831  4597 caffe.cpp:501] detection_eval = 8.19355
-I0511 11:49:27.147835  4597 caffe.cpp:501] detection_eval = 0.039489
-I0511 11:49:27.147840  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.147845  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.147850  4597 caffe.cpp:501] detection_eval = 2.13105
-I0511 11:49:27.147855  4597 caffe.cpp:501] detection_eval = 8.28629
-I0511 11:49:27.147859  4597 caffe.cpp:501] detection_eval = 0.0397669
-I0511 11:49:27.147863  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.147868  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147873  4597 caffe.cpp:501] detection_eval = 2.13306
-I0511 11:49:27.147877  4597 caffe.cpp:501] detection_eval = 8.34476
-I0511 11:49:27.147882  4597 caffe.cpp:501] detection_eval = 0.0432779
-I0511 11:49:27.147886  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147891  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147895  4597 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:49:27.147900  4597 caffe.cpp:501] detection_eval = 8.35081
-I0511 11:49:27.147904  4597 caffe.cpp:501] detection_eval = 0.0477884
-I0511 11:49:27.147909  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.147913  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.147918  4597 caffe.cpp:501] detection_eval = 2.14315
-I0511 11:49:27.147923  4597 caffe.cpp:501] detection_eval = 8.41935
-I0511 11:49:27.147927  4597 caffe.cpp:501] detection_eval = 0.0443906
-I0511 11:49:27.147931  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147936  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.147941  4597 caffe.cpp:501] detection_eval = 2.14516
-I0511 11:49:27.147945  4597 caffe.cpp:501] detection_eval = 8.44153
-I0511 11:49:27.147950  4597 caffe.cpp:501] detection_eval = 0.0463691
-I0511 11:49:27.147954  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.147959  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.147964  4597 caffe.cpp:501] detection_eval = 2.14919
-I0511 11:49:27.147967  4597 caffe.cpp:501] detection_eval = 8.46976
-I0511 11:49:27.147972  4597 caffe.cpp:501] detection_eval = 0.0425091
-I0511 11:49:27.147977  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.147981  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.147986  4597 caffe.cpp:501] detection_eval = 2.14919
-I0511 11:49:27.147990  4597 caffe.cpp:501] detection_eval = 8.53831
-I0511 11:49:27.147995  4597 caffe.cpp:501] detection_eval = 0.0396673
-I0511 11:49:27.148000  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.148005  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.148008  4597 caffe.cpp:501] detection_eval = 2.15121
-I0511 11:49:27.148012  4597 caffe.cpp:501] detection_eval = 8.58266
-I0511 11:49:27.148017  4597 caffe.cpp:501] detection_eval = 0.0346807
-I0511 11:49:27.148022  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.148026  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.148031  4597 caffe.cpp:501] detection_eval = 2.15121
-I0511 11:49:27.148036  4597 caffe.cpp:501] detection_eval = 8.66129
-I0511 11:49:27.148041  4597 caffe.cpp:501] detection_eval = 0.0385228
-I0511 11:49:27.148046  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.148054  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148059  4597 caffe.cpp:501] detection_eval = 2.15323
-I0511 11:49:27.148064  4597 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:49:27.148068  4597 caffe.cpp:501] detection_eval = 0.0394484
-I0511 11:49:27.148073  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148077  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148082  4597 caffe.cpp:501] detection_eval = 2.15323
-I0511 11:49:27.148087  4597 caffe.cpp:501] detection_eval = 8.75403
-I0511 11:49:27.148092  4597 caffe.cpp:501] detection_eval = 0.0413556
-I0511 11:49:27.148097  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148102  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148106  4597 caffe.cpp:501] detection_eval = 2.15524
-I0511 11:49:27.148110  4597 caffe.cpp:501] detection_eval = 8.83468
-I0511 11:49:27.148115  4597 caffe.cpp:501] detection_eval = 0.0427899
-I0511 11:49:27.148119  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148124  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148128  4597 caffe.cpp:501] detection_eval = 2.15726
-I0511 11:49:27.148133  4597 caffe.cpp:501] detection_eval = 8.8871
-I0511 11:49:27.148138  4597 caffe.cpp:501] detection_eval = 0.0401683
-I0511 11:49:27.148142  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148146  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148151  4597 caffe.cpp:501] detection_eval = 2.16129
-I0511 11:49:27.148155  4597 caffe.cpp:501] detection_eval = 8.88105
-I0511 11:49:27.148160  4597 caffe.cpp:501] detection_eval = 0.0469561
-I0511 11:49:27.148164  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.148169  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148174  4597 caffe.cpp:501] detection_eval = 2.16331
-I0511 11:49:27.148178  4597 caffe.cpp:501] detection_eval = 8.91935
-I0511 11:49:27.148182  4597 caffe.cpp:501] detection_eval = 0.0382685
-I0511 11:49:27.148187  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.148191  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148196  4597 caffe.cpp:501] detection_eval = 2.16331
-I0511 11:49:27.148201  4597 caffe.cpp:501] detection_eval = 8.96976
-I0511 11:49:27.148205  4597 caffe.cpp:501] detection_eval = 0.0368055
-I0511 11:49:27.148211  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148214  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148219  4597 caffe.cpp:501] detection_eval = 2.16331
-I0511 11:49:27.148223  4597 caffe.cpp:501] detection_eval = 9.02823
-I0511 11:49:27.148228  4597 caffe.cpp:501] detection_eval = 0.0371279
-I0511 11:49:27.148232  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.148237  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.148241  4597 caffe.cpp:501] detection_eval = 2.16532
-I0511 11:49:27.148247  4597 caffe.cpp:501] detection_eval = 9.08065
-I0511 11:49:27.148250  4597 caffe.cpp:501] detection_eval = 0.0445336
-I0511 11:49:27.148255  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.148259  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148264  4597 caffe.cpp:501] detection_eval = 2.16734
-I0511 11:49:27.148269  4597 caffe.cpp:501] detection_eval = 9.14113
-I0511 11:49:27.148273  4597 caffe.cpp:501] detection_eval = 0.0473416
-I0511 11:49:27.148278  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148283  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148288  4597 caffe.cpp:501] detection_eval = 2.16734
-I0511 11:49:27.148291  4597 caffe.cpp:501] detection_eval = 9.27218
-I0511 11:49:27.148296  4597 caffe.cpp:501] detection_eval = 0.036409
-I0511 11:49:27.148300  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.148305  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.148310  4597 caffe.cpp:501] detection_eval = 2.17137
-I0511 11:49:27.148314  4597 caffe.cpp:501] detection_eval = 9.28427
-I0511 11:49:27.148319  4597 caffe.cpp:501] detection_eval = 0.0450085
-I0511 11:49:27.148324  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.148332  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.148337  4597 caffe.cpp:501] detection_eval = 2.17137
-I0511 11:49:27.148342  4597 caffe.cpp:501] detection_eval = 9.40726
-I0511 11:49:27.148346  4597 caffe.cpp:501] detection_eval = 0.0398951
-I0511 11:49:27.148351  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.148355  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.148360  4597 caffe.cpp:501] detection_eval = 2.17339
-I0511 11:49:27.148365  4597 caffe.cpp:501] detection_eval = 9.46169
-I0511 11:49:27.148370  4597 caffe.cpp:501] detection_eval = 0.0432768
-I0511 11:49:27.148373  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148378  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.148382  4597 caffe.cpp:501] detection_eval = 2.17339
-I0511 11:49:27.148387  4597 caffe.cpp:501] detection_eval = 9.63306
-I0511 11:49:27.148391  4597 caffe.cpp:501] detection_eval = 0.0467469
-I0511 11:49:27.148396  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.148401  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.148406  4597 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:49:27.148411  4597 caffe.cpp:501] detection_eval = 9.65524
-I0511 11:49:27.148414  4597 caffe.cpp:501] detection_eval = 0.0482485
-I0511 11:49:27.148419  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148423  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148428  4597 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:49:27.148432  4597 caffe.cpp:501] detection_eval = 9.79435
-I0511 11:49:27.148437  4597 caffe.cpp:501] detection_eval = 0.047979
-I0511 11:49:27.148442  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148447  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148450  4597 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:49:27.148455  4597 caffe.cpp:501] detection_eval = 9.87298
-I0511 11:49:27.148459  4597 caffe.cpp:501] detection_eval = 0.0429694
-I0511 11:49:27.148463  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.148468  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.148473  4597 caffe.cpp:501] detection_eval = 2.18145
-I0511 11:49:27.148478  4597 caffe.cpp:501] detection_eval = 9.86492
-I0511 11:49:27.148483  4597 caffe.cpp:501] detection_eval = 0.0423322
-I0511 11:49:27.148486  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148491  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148496  4597 caffe.cpp:501] detection_eval = 2.18548
-I0511 11:49:27.148501  4597 caffe.cpp:501] detection_eval = 9.95766
-I0511 11:49:27.148505  4597 caffe.cpp:501] detection_eval = 0.0468316
-I0511 11:49:27.148510  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.148514  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148519  4597 caffe.cpp:501] detection_eval = 2.18952
-I0511 11:49:27.148530  4597 caffe.cpp:501] detection_eval = 9.98589
-I0511 11:49:27.148535  4597 caffe.cpp:501] detection_eval = 0.040069
-I0511 11:49:27.148540  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148543  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148547  4597 caffe.cpp:501] detection_eval = 2.18952
-I0511 11:49:27.148551  4597 caffe.cpp:501] detection_eval = 10.1149
-I0511 11:49:27.148556  4597 caffe.cpp:501] detection_eval = 0.0409916
-I0511 11:49:27.148561  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.148566  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.148571  4597 caffe.cpp:501] detection_eval = 2.19556
-I0511 11:49:27.148576  4597 caffe.cpp:501] detection_eval = 10.0867
-I0511 11:49:27.148579  4597 caffe.cpp:501] detection_eval = 0.0399014
-I0511 11:49:27.148584  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.148589  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.148593  4597 caffe.cpp:501] detection_eval = 2.20161
-I0511 11:49:27.148598  4597 caffe.cpp:501] detection_eval = 10.125
-I0511 11:49:27.148602  4597 caffe.cpp:501] detection_eval = 0.0449894
-I0511 11:49:27.148612  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148617  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148622  4597 caffe.cpp:501] detection_eval = 2.20363
-I0511 11:49:27.148625  4597 caffe.cpp:501] detection_eval = 10.1794
-I0511 11:49:27.148630  4597 caffe.cpp:501] detection_eval = 0.0426234
-I0511 11:49:27.148635  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148639  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148644  4597 caffe.cpp:501] detection_eval = 2.20766
-I0511 11:49:27.148648  4597 caffe.cpp:501] detection_eval = 10.1714
-I0511 11:49:27.148653  4597 caffe.cpp:501] detection_eval = 0.04198
-I0511 11:49:27.148658  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148663  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148667  4597 caffe.cpp:501] detection_eval = 2.20766
-I0511 11:49:27.148671  4597 caffe.cpp:501] detection_eval = 10.2621
-I0511 11:49:27.148676  4597 caffe.cpp:501] detection_eval = 0.0417781
-I0511 11:49:27.148681  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148685  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148690  4597 caffe.cpp:501] detection_eval = 2.21371
-I0511 11:49:27.148694  4597 caffe.cpp:501] detection_eval = 10.2621
-I0511 11:49:27.148699  4597 caffe.cpp:501] detection_eval = 0.0426701
-I0511 11:49:27.148705  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148708  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.148713  4597 caffe.cpp:501] detection_eval = 2.21573
-I0511 11:49:27.148717  4597 caffe.cpp:501] detection_eval = 10.3165
-I0511 11:49:27.148722  4597 caffe.cpp:501] detection_eval = 0.04341
-I0511 11:49:27.148726  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148731  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148736  4597 caffe.cpp:501] detection_eval = 2.21573
-I0511 11:49:27.148741  4597 caffe.cpp:501] detection_eval = 10.4173
-I0511 11:49:27.148746  4597 caffe.cpp:501] detection_eval = 0.0415825
-I0511 11:49:27.148749  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.148754  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148758  4597 caffe.cpp:501] detection_eval = 2.21976
-I0511 11:49:27.148762  4597 caffe.cpp:501] detection_eval = 10.4496
-I0511 11:49:27.148767  4597 caffe.cpp:501] detection_eval = 0.0436784
-I0511 11:49:27.148772  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148777  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.148780  4597 caffe.cpp:501] detection_eval = 2.22177
-I0511 11:49:27.148784  4597 caffe.cpp:501] detection_eval = 10.4617
-I0511 11:49:27.148788  4597 caffe.cpp:501] detection_eval = 0.0425902
-I0511 11:49:27.148792  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148797  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148802  4597 caffe.cpp:501] detection_eval = 2.22379
-I0511 11:49:27.148805  4597 caffe.cpp:501] detection_eval = 10.5141
-I0511 11:49:27.148810  4597 caffe.cpp:501] detection_eval = 0.0450279
-I0511 11:49:27.148814  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.148818  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.148823  4597 caffe.cpp:501] detection_eval = 2.22984
-I0511 11:49:27.148825  4597 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:49:27.148829  4597 caffe.cpp:501] detection_eval = 0.0487626
-I0511 11:49:27.148834  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.148839  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.148844  4597 caffe.cpp:501] detection_eval = 2.23185
-I0511 11:49:27.148849  4597 caffe.cpp:501] detection_eval = 10.5484
-I0511 11:49:27.148852  4597 caffe.cpp:501] detection_eval = 0.0416015
-I0511 11:49:27.148857  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.148861  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.148866  4597 caffe.cpp:501] detection_eval = 2.23185
-I0511 11:49:27.148870  4597 caffe.cpp:501] detection_eval = 10.6472
-I0511 11:49:27.148875  4597 caffe.cpp:501] detection_eval = 0.0393731
-I0511 11:49:27.148883  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148888  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.148892  4597 caffe.cpp:501] detection_eval = 2.23185
-I0511 11:49:27.148897  4597 caffe.cpp:501] detection_eval = 10.6996
-I0511 11:49:27.148902  4597 caffe.cpp:501] detection_eval = 0.0403121
-I0511 11:49:27.148906  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.148911  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.148916  4597 caffe.cpp:501] detection_eval = 2.2379
-I0511 11:49:27.148921  4597 caffe.cpp:501] detection_eval = 10.6754
-I0511 11:49:27.148924  4597 caffe.cpp:501] detection_eval = 0.0437596
-I0511 11:49:27.148929  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.148934  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.148939  4597 caffe.cpp:501] detection_eval = 2.2379
-I0511 11:49:27.148944  4597 caffe.cpp:501] detection_eval = 10.7903
-I0511 11:49:27.148949  4597 caffe.cpp:501] detection_eval = 0.0443543
-I0511 11:49:27.148953  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.148958  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.148962  4597 caffe.cpp:501] detection_eval = 2.23992
-I0511 11:49:27.148967  4597 caffe.cpp:501] detection_eval = 10.8226
-I0511 11:49:27.148972  4597 caffe.cpp:501] detection_eval = 0.0393024
-I0511 11:49:27.148977  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.148980  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.148985  4597 caffe.cpp:501] detection_eval = 2.23992
-I0511 11:49:27.148989  4597 caffe.cpp:501] detection_eval = 10.9073
-I0511 11:49:27.148994  4597 caffe.cpp:501] detection_eval = 0.0388229
-I0511 11:49:27.148999  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149003  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149008  4597 caffe.cpp:501] detection_eval = 2.24194
-I0511 11:49:27.149013  4597 caffe.cpp:501] detection_eval = 10.9536
-I0511 11:49:27.149018  4597 caffe.cpp:501] detection_eval = 0.0373147
-I0511 11:49:27.149021  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.149026  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.149031  4597 caffe.cpp:501] detection_eval = 2.24597
-I0511 11:49:27.149035  4597 caffe.cpp:501] detection_eval = 10.9456
-I0511 11:49:27.149040  4597 caffe.cpp:501] detection_eval = 0.0377576
-I0511 11:49:27.149044  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.149049  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149055  4597 caffe.cpp:501] detection_eval = 2.24798
-I0511 11:49:27.149058  4597 caffe.cpp:501] detection_eval = 10.9899
-I0511 11:49:27.149063  4597 caffe.cpp:501] detection_eval = 0.0406665
-I0511 11:49:27.149067  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149072  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149076  4597 caffe.cpp:501] detection_eval = 2.25
-I0511 11:49:27.149081  4597 caffe.cpp:501] detection_eval = 11.0484
-I0511 11:49:27.149086  4597 caffe.cpp:501] detection_eval = 0.040189
-I0511 11:49:27.149091  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149096  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149101  4597 caffe.cpp:501] detection_eval = 2.25
-I0511 11:49:27.149104  4597 caffe.cpp:501] detection_eval = 11.121
-I0511 11:49:27.149109  4597 caffe.cpp:501] detection_eval = 0.0411637
-I0511 11:49:27.149114  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.149118  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.149123  4597 caffe.cpp:501] detection_eval = 2.25202
-I0511 11:49:27.149127  4597 caffe.cpp:501] detection_eval = 11.1875
-I0511 11:49:27.149132  4597 caffe.cpp:501] detection_eval = 0.0421608
-I0511 11:49:27.149137  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149142  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149147  4597 caffe.cpp:501] detection_eval = 2.25202
-I0511 11:49:27.149152  4597 caffe.cpp:501] detection_eval = 11.2782
-I0511 11:49:27.149160  4597 caffe.cpp:501] detection_eval = 0.0465724
-I0511 11:49:27.149165  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149170  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.149175  4597 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:49:27.149179  4597 caffe.cpp:501] detection_eval = 11.2581
-I0511 11:49:27.149184  4597 caffe.cpp:501] detection_eval = 0.0395285
-I0511 11:49:27.149188  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149194  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149199  4597 caffe.cpp:501] detection_eval = 2.26411
-I0511 11:49:27.149202  4597 caffe.cpp:501] detection_eval = 11.1855
-I0511 11:49:27.149207  4597 caffe.cpp:501] detection_eval = 0.0422078
-I0511 11:49:27.149211  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149216  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149220  4597 caffe.cpp:501] detection_eval = 2.27016
-I0511 11:49:27.149225  4597 caffe.cpp:501] detection_eval = 11.1613
-I0511 11:49:27.149230  4597 caffe.cpp:501] detection_eval = 0.0413146
-I0511 11:49:27.149235  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149240  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149245  4597 caffe.cpp:501] detection_eval = 2.27218
-I0511 11:49:27.149248  4597 caffe.cpp:501] detection_eval = 11.2641
-I0511 11:49:27.149253  4597 caffe.cpp:501] detection_eval = 0.051111
-I0511 11:49:27.149257  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.149262  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.149266  4597 caffe.cpp:501] detection_eval = 2.27419
-I0511 11:49:27.149271  4597 caffe.cpp:501] detection_eval = 11.3226
-I0511 11:49:27.149276  4597 caffe.cpp:501] detection_eval = 0.0490444
-I0511 11:49:27.149281  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149286  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149289  4597 caffe.cpp:501] detection_eval = 2.27823
-I0511 11:49:27.149294  4597 caffe.cpp:501] detection_eval = 11.3468
-I0511 11:49:27.149298  4597 caffe.cpp:501] detection_eval = 0.046179
-I0511 11:49:27.149303  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149308  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149312  4597 caffe.cpp:501] detection_eval = 2.28226
-I0511 11:49:27.149317  4597 caffe.cpp:501] detection_eval = 11.3992
-I0511 11:49:27.149322  4597 caffe.cpp:501] detection_eval = 0.050707
-I0511 11:49:27.149327  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.149330  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.149335  4597 caffe.cpp:501] detection_eval = 2.28629
-I0511 11:49:27.149346  4597 caffe.cpp:501] detection_eval = 11.4234
-I0511 11:49:27.149356  4597 caffe.cpp:501] detection_eval = 0.0476655
-I0511 11:49:27.149365  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149374  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.149381  4597 caffe.cpp:501] detection_eval = 2.28629
-I0511 11:49:27.149389  4597 caffe.cpp:501] detection_eval = 11.4899
-I0511 11:49:27.149395  4597 caffe.cpp:501] detection_eval = 0.0419335
-I0511 11:49:27.149399  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.149405  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.149408  4597 caffe.cpp:501] detection_eval = 2.28629
-I0511 11:49:27.149413  4597 caffe.cpp:501] detection_eval = 11.5625
-I0511 11:49:27.149418  4597 caffe.cpp:501] detection_eval = 0.0424994
-I0511 11:49:27.149422  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.149427  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149431  4597 caffe.cpp:501] detection_eval = 2.28629
-I0511 11:49:27.149436  4597 caffe.cpp:501] detection_eval = 11.6472
-I0511 11:49:27.149441  4597 caffe.cpp:501] detection_eval = 0.0458754
-I0511 11:49:27.149446  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149449  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.149454  4597 caffe.cpp:501] detection_eval = 2.28831
-I0511 11:49:27.149458  4597 caffe.cpp:501] detection_eval = 11.6754
-I0511 11:49:27.149467  4597 caffe.cpp:501] detection_eval = 0.0457525
-I0511 11:49:27.149472  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.149477  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.149482  4597 caffe.cpp:501] detection_eval = 2.29032
-I0511 11:49:27.149487  4597 caffe.cpp:501] detection_eval = 11.7137
-I0511 11:49:27.149492  4597 caffe.cpp:501] detection_eval = 0.0428728
-I0511 11:49:27.149495  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149500  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149504  4597 caffe.cpp:501] detection_eval = 2.29435
-I0511 11:49:27.149509  4597 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:49:27.149513  4597 caffe.cpp:501] detection_eval = 0.0429885
-I0511 11:49:27.149518  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149523  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149528  4597 caffe.cpp:501] detection_eval = 2.29839
-I0511 11:49:27.149531  4597 caffe.cpp:501] detection_eval = 11.6875
-I0511 11:49:27.149536  4597 caffe.cpp:501] detection_eval = 0.0391875
-I0511 11:49:27.149541  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.149545  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149549  4597 caffe.cpp:501] detection_eval = 2.3004
-I0511 11:49:27.149552  4597 caffe.cpp:501] detection_eval = 11.7177
-I0511 11:49:27.149556  4597 caffe.cpp:501] detection_eval = 0.041563
-I0511 11:49:27.149561  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149566  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149570  4597 caffe.cpp:501] detection_eval = 2.3004
-I0511 11:49:27.149575  4597 caffe.cpp:501] detection_eval = 11.7944
-I0511 11:49:27.149580  4597 caffe.cpp:501] detection_eval = 0.0366132
-I0511 11:49:27.149585  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.149590  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.149593  4597 caffe.cpp:501] detection_eval = 2.30242
-I0511 11:49:27.149598  4597 caffe.cpp:501] detection_eval = 11.8609
-I0511 11:49:27.149602  4597 caffe.cpp:501] detection_eval = 0.036291
-I0511 11:49:27.149607  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.149611  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149616  4597 caffe.cpp:501] detection_eval = 2.30444
-I0511 11:49:27.149621  4597 caffe.cpp:501] detection_eval = 11.9395
-I0511 11:49:27.149626  4597 caffe.cpp:501] detection_eval = 0.0379277
-I0511 11:49:27.149629  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.149634  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.149639  4597 caffe.cpp:501] detection_eval = 2.30645
-I0511 11:49:27.149643  4597 caffe.cpp:501] detection_eval = 11.9819
-I0511 11:49:27.149648  4597 caffe.cpp:501] detection_eval = 0.0395199
-I0511 11:49:27.149652  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.149657  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149662  4597 caffe.cpp:501] detection_eval = 2.31048
-I0511 11:49:27.149667  4597 caffe.cpp:501] detection_eval = 12.0202
-I0511 11:49:27.149670  4597 caffe.cpp:501] detection_eval = 0.040769
-I0511 11:49:27.149675  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149679  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149684  4597 caffe.cpp:501] detection_eval = 2.31653
-I0511 11:49:27.149688  4597 caffe.cpp:501] detection_eval = 11.9839
-I0511 11:49:27.149693  4597 caffe.cpp:501] detection_eval = 0.0399254
-I0511 11:49:27.149698  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.149703  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.149708  4597 caffe.cpp:501] detection_eval = 2.32258
-I0511 11:49:27.149711  4597 caffe.cpp:501] detection_eval = 11.9536
-I0511 11:49:27.149716  4597 caffe.cpp:501] detection_eval = 0.0350768
-I0511 11:49:27.149721  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.149725  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.149730  4597 caffe.cpp:501] detection_eval = 2.32661
-I0511 11:49:27.149739  4597 caffe.cpp:501] detection_eval = 11.9778
-I0511 11:49:27.149744  4597 caffe.cpp:501] detection_eval = 0.0423888
-I0511 11:49:27.149747  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149752  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149756  4597 caffe.cpp:501] detection_eval = 2.32661
-I0511 11:49:27.149761  4597 caffe.cpp:501] detection_eval = 12.0242
-I0511 11:49:27.149765  4597 caffe.cpp:501] detection_eval = 0.0381201
-I0511 11:49:27.149770  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149775  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149780  4597 caffe.cpp:501] detection_eval = 2.32863
-I0511 11:49:27.149790  4597 caffe.cpp:501] detection_eval = 12.0665
-I0511 11:49:27.149798  4597 caffe.cpp:501] detection_eval = 0.0392492
-I0511 11:49:27.149806  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149816  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.149823  4597 caffe.cpp:501] detection_eval = 2.32863
-I0511 11:49:27.149832  4597 caffe.cpp:501] detection_eval = 12.1391
-I0511 11:49:27.149837  4597 caffe.cpp:501] detection_eval = 0.0379095
-I0511 11:49:27.149842  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.149847  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.149852  4597 caffe.cpp:501] detection_eval = 2.32863
-I0511 11:49:27.149855  4597 caffe.cpp:501] detection_eval = 12.2157
-I0511 11:49:27.149860  4597 caffe.cpp:501] detection_eval = 0.0364523
-I0511 11:49:27.149864  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.149869  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149874  4597 caffe.cpp:501] detection_eval = 2.33669
-I0511 11:49:27.149878  4597 caffe.cpp:501] detection_eval = 12.1875
-I0511 11:49:27.149883  4597 caffe.cpp:501] detection_eval = 0.0422583
-I0511 11:49:27.149888  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.149893  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.149896  4597 caffe.cpp:501] detection_eval = 2.33669
-I0511 11:49:27.149901  4597 caffe.cpp:501] detection_eval = 12.2722
-I0511 11:49:27.149906  4597 caffe.cpp:501] detection_eval = 0.0403973
-I0511 11:49:27.149910  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149914  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.149919  4597 caffe.cpp:501] detection_eval = 2.33871
-I0511 11:49:27.149924  4597 caffe.cpp:501] detection_eval = 12.3206
-I0511 11:49:27.149929  4597 caffe.cpp:501] detection_eval = 0.0492333
-I0511 11:49:27.149933  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.149937  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.149942  4597 caffe.cpp:501] detection_eval = 2.34476
-I0511 11:49:27.149946  4597 caffe.cpp:501] detection_eval = 12.2762
-I0511 11:49:27.149951  4597 caffe.cpp:501] detection_eval = 0.0394243
-I0511 11:49:27.149955  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.149960  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.149965  4597 caffe.cpp:501] detection_eval = 2.34879
-I0511 11:49:27.149969  4597 caffe.cpp:501] detection_eval = 12.256
-I0511 11:49:27.149974  4597 caffe.cpp:501] detection_eval = 0.0380893
-I0511 11:49:27.149978  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.149983  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.149987  4597 caffe.cpp:501] detection_eval = 2.35081
-I0511 11:49:27.149992  4597 caffe.cpp:501] detection_eval = 12.2702
-I0511 11:49:27.149997  4597 caffe.cpp:501] detection_eval = 0.0336209
-I0511 11:49:27.150002  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150007  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.150010  4597 caffe.cpp:501] detection_eval = 2.35484
-I0511 11:49:27.150015  4597 caffe.cpp:501] detection_eval = 12.2762
-I0511 11:49:27.150019  4597 caffe.cpp:501] detection_eval = 0.041551
-I0511 11:49:27.150024  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150028  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150038  4597 caffe.cpp:501] detection_eval = 2.35887
-I0511 11:49:27.150043  4597 caffe.cpp:501] detection_eval = 12.2802
-I0511 11:49:27.150048  4597 caffe.cpp:501] detection_eval = 0.0416252
-I0511 11:49:27.150053  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150056  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150061  4597 caffe.cpp:501] detection_eval = 2.36694
-I0511 11:49:27.150065  4597 caffe.cpp:501] detection_eval = 12.25
-I0511 11:49:27.150070  4597 caffe.cpp:501] detection_eval = 0.0402391
-I0511 11:49:27.150074  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.150079  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150084  4597 caffe.cpp:501] detection_eval = 2.36895
-I0511 11:49:27.150089  4597 caffe.cpp:501] detection_eval = 12.2903
-I0511 11:49:27.150094  4597 caffe.cpp:501] detection_eval = 0.0380401
-I0511 11:49:27.150097  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150102  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150106  4597 caffe.cpp:501] detection_eval = 2.37298
-I0511 11:49:27.150111  4597 caffe.cpp:501] detection_eval = 12.2762
-I0511 11:49:27.150115  4597 caffe.cpp:501] detection_eval = 0.0418109
-I0511 11:49:27.150120  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150125  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.150130  4597 caffe.cpp:501] detection_eval = 2.37298
-I0511 11:49:27.150133  4597 caffe.cpp:501] detection_eval = 12.3528
-I0511 11:49:27.150138  4597 caffe.cpp:501] detection_eval = 0.0400792
-I0511 11:49:27.150143  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150147  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150151  4597 caffe.cpp:501] detection_eval = 2.375
-I0511 11:49:27.150156  4597 caffe.cpp:501] detection_eval = 12.3972
-I0511 11:49:27.150161  4597 caffe.cpp:501] detection_eval = 0.0392371
-I0511 11:49:27.150166  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150171  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150174  4597 caffe.cpp:501] detection_eval = 2.38105
-I0511 11:49:27.150179  4597 caffe.cpp:501] detection_eval = 12.3427
-I0511 11:49:27.150184  4597 caffe.cpp:501] detection_eval = 0.0415699
-I0511 11:49:27.150188  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.150193  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.150197  4597 caffe.cpp:501] detection_eval = 2.38911
-I0511 11:49:27.150202  4597 caffe.cpp:501] detection_eval = 12.2782
-I0511 11:49:27.150207  4597 caffe.cpp:501] detection_eval = 0.0471242
-I0511 11:49:27.150216  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150225  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150234  4597 caffe.cpp:501] detection_eval = 2.39113
-I0511 11:49:27.150243  4597 caffe.cpp:501] detection_eval = 12.375
-I0511 11:49:27.150251  4597 caffe.cpp:501] detection_eval = 0.0439591
-I0511 11:49:27.150259  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150265  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.150270  4597 caffe.cpp:501] detection_eval = 2.39113
-I0511 11:49:27.150274  4597 caffe.cpp:501] detection_eval = 12.4234
-I0511 11:49:27.150279  4597 caffe.cpp:501] detection_eval = 0.0383429
-I0511 11:49:27.150283  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150288  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.150293  4597 caffe.cpp:501] detection_eval = 2.39113
-I0511 11:49:27.150297  4597 caffe.cpp:501] detection_eval = 12.4778
-I0511 11:49:27.150302  4597 caffe.cpp:501] detection_eval = 0.0366566
-I0511 11:49:27.150306  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150311  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150316  4597 caffe.cpp:501] detection_eval = 2.39315
-I0511 11:49:27.150321  4597 caffe.cpp:501] detection_eval = 12.5141
-I0511 11:49:27.150326  4597 caffe.cpp:501] detection_eval = 0.0373185
-I0511 11:49:27.150329  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150334  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150342  4597 caffe.cpp:501] detection_eval = 2.39315
-I0511 11:49:27.150347  4597 caffe.cpp:501] detection_eval = 12.5585
-I0511 11:49:27.150352  4597 caffe.cpp:501] detection_eval = 0.0350957
-I0511 11:49:27.150355  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150359  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150363  4597 caffe.cpp:501] detection_eval = 2.39516
-I0511 11:49:27.150368  4597 caffe.cpp:501] detection_eval = 12.5927
-I0511 11:49:27.150373  4597 caffe.cpp:501] detection_eval = 0.0371443
-I0511 11:49:27.150377  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150382  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150387  4597 caffe.cpp:501] detection_eval = 2.39718
-I0511 11:49:27.150391  4597 caffe.cpp:501] detection_eval = 12.6593
-I0511 11:49:27.150395  4597 caffe.cpp:501] detection_eval = 0.0382026
-I0511 11:49:27.150400  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.150404  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150409  4597 caffe.cpp:501] detection_eval = 2.40121
-I0511 11:49:27.150413  4597 caffe.cpp:501] detection_eval = 12.6371
-I0511 11:49:27.150418  4597 caffe.cpp:501] detection_eval = 0.0410381
-I0511 11:49:27.150424  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150427  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.150432  4597 caffe.cpp:501] detection_eval = 2.40121
-I0511 11:49:27.150436  4597 caffe.cpp:501] detection_eval = 12.6835
-I0511 11:49:27.150441  4597 caffe.cpp:501] detection_eval = 0.0402094
-I0511 11:49:27.150445  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150450  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150454  4597 caffe.cpp:501] detection_eval = 2.40323
-I0511 11:49:27.150460  4597 caffe.cpp:501] detection_eval = 12.6956
-I0511 11:49:27.150465  4597 caffe.cpp:501] detection_eval = 0.0408201
-I0511 11:49:27.150468  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150473  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150478  4597 caffe.cpp:501] detection_eval = 2.40927
-I0511 11:49:27.150482  4597 caffe.cpp:501] detection_eval = 12.6875
-I0511 11:49:27.150487  4597 caffe.cpp:501] detection_eval = 0.0416168
-I0511 11:49:27.150491  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.150496  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.150501  4597 caffe.cpp:501] detection_eval = 2.41331
-I0511 11:49:27.150506  4597 caffe.cpp:501] detection_eval = 12.6633
-I0511 11:49:27.150509  4597 caffe.cpp:501] detection_eval = 0.039459
-I0511 11:49:27.150514  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150519  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150523  4597 caffe.cpp:501] detection_eval = 2.41331
-I0511 11:49:27.150528  4597 caffe.cpp:501] detection_eval = 12.7198
-I0511 11:49:27.150532  4597 caffe.cpp:501] detection_eval = 0.0383806
-I0511 11:49:27.150537  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.150542  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.150547  4597 caffe.cpp:501] detection_eval = 2.41532
-I0511 11:49:27.150552  4597 caffe.cpp:501] detection_eval = 12.7702
-I0511 11:49:27.150557  4597 caffe.cpp:501] detection_eval = 0.0405816
-I0511 11:49:27.150560  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150565  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.150569  4597 caffe.cpp:501] detection_eval = 2.41734
-I0511 11:49:27.150574  4597 caffe.cpp:501] detection_eval = 12.7823
-I0511 11:49:27.150578  4597 caffe.cpp:501] detection_eval = 0.0382321
-I0511 11:49:27.150583  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150588  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150593  4597 caffe.cpp:501] detection_eval = 2.41734
-I0511 11:49:27.150598  4597 caffe.cpp:501] detection_eval = 12.8528
-I0511 11:49:27.150601  4597 caffe.cpp:501] detection_eval = 0.0418643
-I0511 11:49:27.150606  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.150614  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.150619  4597 caffe.cpp:501] detection_eval = 2.42339
-I0511 11:49:27.150624  4597 caffe.cpp:501] detection_eval = 12.8044
-I0511 11:49:27.150629  4597 caffe.cpp:501] detection_eval = 0.0426642
-I0511 11:49:27.150632  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150637  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150642  4597 caffe.cpp:501] detection_eval = 2.42944
-I0511 11:49:27.150646  4597 caffe.cpp:501] detection_eval = 12.8105
-I0511 11:49:27.150656  4597 caffe.cpp:501] detection_eval = 0.0378261
-I0511 11:49:27.150665  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150674  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150682  4597 caffe.cpp:501] detection_eval = 2.4375
-I0511 11:49:27.150691  4597 caffe.cpp:501] detection_eval = 12.75
-I0511 11:49:27.150699  4597 caffe.cpp:501] detection_eval = 0.0351373
-I0511 11:49:27.150704  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.150709  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.150714  4597 caffe.cpp:501] detection_eval = 2.44153
-I0511 11:49:27.150719  4597 caffe.cpp:501] detection_eval = 12.7681
-I0511 11:49:27.150723  4597 caffe.cpp:501] detection_eval = 0.0400386
-I0511 11:49:27.150728  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150732  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.150738  4597 caffe.cpp:501] detection_eval = 2.44556
-I0511 11:49:27.150741  4597 caffe.cpp:501] detection_eval = 12.7823
-I0511 11:49:27.150746  4597 caffe.cpp:501] detection_eval = 0.0394807
-I0511 11:49:27.150751  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150755  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150760  4597 caffe.cpp:501] detection_eval = 2.4496
-I0511 11:49:27.150765  4597 caffe.cpp:501] detection_eval = 12.7661
-I0511 11:49:27.150769  4597 caffe.cpp:501] detection_eval = 0.0382113
-I0511 11:49:27.150774  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150779  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150784  4597 caffe.cpp:501] detection_eval = 2.4496
-I0511 11:49:27.150787  4597 caffe.cpp:501] detection_eval = 12.8185
-I0511 11:49:27.150792  4597 caffe.cpp:501] detection_eval = 0.0357022
-I0511 11:49:27.150796  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.150801  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150805  4597 caffe.cpp:501] detection_eval = 2.45363
-I0511 11:49:27.150810  4597 caffe.cpp:501] detection_eval = 12.8125
-I0511 11:49:27.150815  4597 caffe.cpp:501] detection_eval = 0.03798
-I0511 11:49:27.150820  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150825  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150830  4597 caffe.cpp:501] detection_eval = 2.45363
-I0511 11:49:27.150833  4597 caffe.cpp:501] detection_eval = 12.8952
-I0511 11:49:27.150838  4597 caffe.cpp:501] detection_eval = 0.042409
-I0511 11:49:27.150842  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.150847  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150851  4597 caffe.cpp:501] detection_eval = 2.45565
-I0511 11:49:27.150856  4597 caffe.cpp:501] detection_eval = 12.9234
-I0511 11:49:27.150861  4597 caffe.cpp:501] detection_eval = 0.0380439
-I0511 11:49:27.150866  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.150869  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.150874  4597 caffe.cpp:501] detection_eval = 2.45565
-I0511 11:49:27.150878  4597 caffe.cpp:501] detection_eval = 12.9758
-I0511 11:49:27.150883  4597 caffe.cpp:501] detection_eval = 0.0350995
-I0511 11:49:27.150888  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.150892  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150897  4597 caffe.cpp:501] detection_eval = 2.45968
-I0511 11:49:27.150902  4597 caffe.cpp:501] detection_eval = 12.998
-I0511 11:49:27.150907  4597 caffe.cpp:501] detection_eval = 0.039502
-I0511 11:49:27.150915  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.150919  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.150924  4597 caffe.cpp:501] detection_eval = 2.45968
-I0511 11:49:27.150928  4597 caffe.cpp:501] detection_eval = 13.0827
-I0511 11:49:27.150933  4597 caffe.cpp:501] detection_eval = 0.0368795
-I0511 11:49:27.150938  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150943  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.150948  4597 caffe.cpp:501] detection_eval = 2.46169
-I0511 11:49:27.150951  4597 caffe.cpp:501] detection_eval = 13.1331
-I0511 11:49:27.150956  4597 caffe.cpp:501] detection_eval = 0.0381957
-I0511 11:49:27.150960  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.150965  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.150970  4597 caffe.cpp:501] detection_eval = 2.46573
-I0511 11:49:27.150974  4597 caffe.cpp:501] detection_eval = 13.1351
-I0511 11:49:27.150979  4597 caffe.cpp:501] detection_eval = 0.0448654
-I0511 11:49:27.150985  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.150988  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.150993  4597 caffe.cpp:501] detection_eval = 2.46976
-I0511 11:49:27.150997  4597 caffe.cpp:501] detection_eval = 13.1069
-I0511 11:49:27.151002  4597 caffe.cpp:501] detection_eval = 0.0377625
-I0511 11:49:27.151006  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.151011  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151015  4597 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:49:27.151021  4597 caffe.cpp:501] detection_eval = 13.1472
-I0511 11:49:27.151026  4597 caffe.cpp:501] detection_eval = 0.0362461
-I0511 11:49:27.151029  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151033  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151038  4597 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:49:27.151043  4597 caffe.cpp:501] detection_eval = 13.2177
-I0511 11:49:27.151047  4597 caffe.cpp:501] detection_eval = 0.0344065
-I0511 11:49:27.151052  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151057  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151062  4597 caffe.cpp:501] detection_eval = 2.47581
-I0511 11:49:27.151067  4597 caffe.cpp:501] detection_eval = 13.2258
-I0511 11:49:27.151072  4597 caffe.cpp:501] detection_eval = 0.0381641
-I0511 11:49:27.151075  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151087  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151095  4597 caffe.cpp:501] detection_eval = 2.47782
-I0511 11:49:27.151104  4597 caffe.cpp:501] detection_eval = 13.2782
-I0511 11:49:27.151113  4597 caffe.cpp:501] detection_eval = 0.0390413
-I0511 11:49:27.151121  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151129  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151134  4597 caffe.cpp:501] detection_eval = 2.47984
-I0511 11:49:27.151139  4597 caffe.cpp:501] detection_eval = 13.2823
-I0511 11:49:27.151144  4597 caffe.cpp:501] detection_eval = 0.0340876
-I0511 11:49:27.151147  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.151151  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.151156  4597 caffe.cpp:501] detection_eval = 2.49395
-I0511 11:49:27.151160  4597 caffe.cpp:501] detection_eval = 13.1532
-I0511 11:49:27.151165  4597 caffe.cpp:501] detection_eval = 0.0371462
-I0511 11:49:27.151170  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.151175  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151178  4597 caffe.cpp:501] detection_eval = 2.49395
-I0511 11:49:27.151183  4597 caffe.cpp:501] detection_eval = 13.2419
-I0511 11:49:27.151188  4597 caffe.cpp:501] detection_eval = 0.0375995
-I0511 11:49:27.151192  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151197  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151201  4597 caffe.cpp:501] detection_eval = 2.49798
-I0511 11:49:27.151206  4597 caffe.cpp:501] detection_eval = 13.2198
-I0511 11:49:27.151211  4597 caffe.cpp:501] detection_eval = 0.0327908
-I0511 11:49:27.151219  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151224  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.151228  4597 caffe.cpp:501] detection_eval = 2.49798
-I0511 11:49:27.151233  4597 caffe.cpp:501] detection_eval = 13.2984
-I0511 11:49:27.151237  4597 caffe.cpp:501] detection_eval = 0.0408301
-I0511 11:49:27.151242  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.151247  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.151252  4597 caffe.cpp:501] detection_eval = 2.50202
-I0511 11:49:27.151255  4597 caffe.cpp:501] detection_eval = 13.3185
-I0511 11:49:27.151260  4597 caffe.cpp:501] detection_eval = 0.0363852
-I0511 11:49:27.151265  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151269  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151274  4597 caffe.cpp:501] detection_eval = 2.50806
-I0511 11:49:27.151278  4597 caffe.cpp:501] detection_eval = 13.3105
-I0511 11:49:27.151283  4597 caffe.cpp:501] detection_eval = 0.0423162
-I0511 11:49:27.151288  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151293  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.151296  4597 caffe.cpp:501] detection_eval = 2.50806
-I0511 11:49:27.151301  4597 caffe.cpp:501] detection_eval = 13.3891
-I0511 11:49:27.151306  4597 caffe.cpp:501] detection_eval = 0.0378473
-I0511 11:49:27.151310  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151315  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151319  4597 caffe.cpp:501] detection_eval = 2.51008
-I0511 11:49:27.151324  4597 caffe.cpp:501] detection_eval = 13.4214
-I0511 11:49:27.151329  4597 caffe.cpp:501] detection_eval = 0.0358066
-I0511 11:49:27.151334  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.151337  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151342  4597 caffe.cpp:501] detection_eval = 2.51008
-I0511 11:49:27.151346  4597 caffe.cpp:501] detection_eval = 13.494
-I0511 11:49:27.151351  4597 caffe.cpp:501] detection_eval = 0.0365599
-I0511 11:49:27.151356  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151360  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151365  4597 caffe.cpp:501] detection_eval = 2.5121
-I0511 11:49:27.151371  4597 caffe.cpp:501] detection_eval = 13.5746
-I0511 11:49:27.151374  4597 caffe.cpp:501] detection_eval = 0.0346992
-I0511 11:49:27.151379  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151383  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151388  4597 caffe.cpp:501] detection_eval = 2.51411
-I0511 11:49:27.151392  4597 caffe.cpp:501] detection_eval = 13.629
-I0511 11:49:27.151397  4597 caffe.cpp:501] detection_eval = 0.0378362
-I0511 11:49:27.151401  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.151407  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151410  4597 caffe.cpp:501] detection_eval = 2.52621
-I0511 11:49:27.151415  4597 caffe.cpp:501] detection_eval = 13.5806
-I0511 11:49:27.151420  4597 caffe.cpp:501] detection_eval = 0.0434219
-I0511 11:49:27.151424  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.151429  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.151433  4597 caffe.cpp:501] detection_eval = 2.52621
-I0511 11:49:27.151438  4597 caffe.cpp:501] detection_eval = 13.7097
-I0511 11:49:27.151443  4597 caffe.cpp:501] detection_eval = 0.0425423
-I0511 11:49:27.151448  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.151453  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.151456  4597 caffe.cpp:501] detection_eval = 2.52823
-I0511 11:49:27.151461  4597 caffe.cpp:501] detection_eval = 13.7661
-I0511 11:49:27.151465  4597 caffe.cpp:501] detection_eval = 0.0360792
-I0511 11:49:27.151470  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151474  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151479  4597 caffe.cpp:501] detection_eval = 2.53024
-I0511 11:49:27.151484  4597 caffe.cpp:501] detection_eval = 13.9153
-I0511 11:49:27.151499  4597 caffe.cpp:501] detection_eval = 0.0414179
-I0511 11:49:27.151507  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151516  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.151525  4597 caffe.cpp:501] detection_eval = 2.53427
-I0511 11:49:27.151532  4597 caffe.cpp:501] detection_eval = 14.0524
-I0511 11:49:27.151538  4597 caffe.cpp:501] detection_eval = 0.033771
-I0511 11:49:27.151543  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.151547  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.151552  4597 caffe.cpp:501] detection_eval = 2.53629
-I0511 11:49:27.151556  4597 caffe.cpp:501] detection_eval = 14.2319
-I0511 11:49:27.151561  4597 caffe.cpp:501] detection_eval = 0.0354508
-I0511 11:49:27.151566  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151571  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.151576  4597 caffe.cpp:501] detection_eval = 2.53831
-I0511 11:49:27.151581  4597 caffe.cpp:501] detection_eval = 14.6028
-I0511 11:49:27.151584  4597 caffe.cpp:501] detection_eval = 0.0349725
-I0511 11:49:27.151589  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151593  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.151598  4597 caffe.cpp:501] detection_eval = 3.08468
-I0511 11:49:27.151603  4597 caffe.cpp:501] detection_eval = 6.43548
-I0511 11:49:27.151607  4597 caffe.cpp:501] detection_eval = 0.112306
-I0511 11:49:27.151612  4597 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:49:27.151616  4597 caffe.cpp:501] detection_eval = 0.923387
-I0511 11:49:27.151621  4597 caffe.cpp:501] detection_eval = 3.08871
-I0511 11:49:27.151625  4597 caffe.cpp:501] detection_eval = 6.65524
-I0511 11:49:27.151630  4597 caffe.cpp:501] detection_eval = 0.0733243
-I0511 11:49:27.151635  4597 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:49:27.151639  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.151644  4597 caffe.cpp:501] detection_eval = 3.09073
-I0511 11:49:27.151648  4597 caffe.cpp:501] detection_eval = 6.78831
-I0511 11:49:27.151654  4597 caffe.cpp:501] detection_eval = 0.0606407
-I0511 11:49:27.151657  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.151662  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.151666  4597 caffe.cpp:501] detection_eval = 3.09073
-I0511 11:49:27.151671  4597 caffe.cpp:501] detection_eval = 6.91129
-I0511 11:49:27.151675  4597 caffe.cpp:501] detection_eval = 0.0614009
-I0511 11:49:27.151680  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.151685  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.151690  4597 caffe.cpp:501] detection_eval = 3.09073
-I0511 11:49:27.151695  4597 caffe.cpp:501] detection_eval = 7.00202
-I0511 11:49:27.151698  4597 caffe.cpp:501] detection_eval = 0.052092
-I0511 11:49:27.151703  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.151707  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.151712  4597 caffe.cpp:501] detection_eval = 3.09274
-I0511 11:49:27.151717  4597 caffe.cpp:501] detection_eval = 7.06048
-I0511 11:49:27.151721  4597 caffe.cpp:501] detection_eval = 0.0492056
-I0511 11:49:27.151726  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151731  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151736  4597 caffe.cpp:501] detection_eval = 3.09476
-I0511 11:49:27.151739  4597 caffe.cpp:501] detection_eval = 7.12097
-I0511 11:49:27.151744  4597 caffe.cpp:501] detection_eval = 0.0503446
-I0511 11:49:27.151748  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.151753  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.151758  4597 caffe.cpp:501] detection_eval = 3.09879
-I0511 11:49:27.151762  4597 caffe.cpp:501] detection_eval = 7.16935
-I0511 11:49:27.151767  4597 caffe.cpp:501] detection_eval = 0.0471233
-I0511 11:49:27.151772  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.151777  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151780  4597 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:49:27.151789  4597 caffe.cpp:501] detection_eval = 7.21371
-I0511 11:49:27.151794  4597 caffe.cpp:501] detection_eval = 0.0537842
-I0511 11:49:27.151798  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.151803  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.151808  4597 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:49:27.151813  4597 caffe.cpp:501] detection_eval = 7.29234
-I0511 11:49:27.151816  4597 caffe.cpp:501] detection_eval = 0.051197
-I0511 11:49:27.151821  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.151825  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.151830  4597 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:49:27.151834  4597 caffe.cpp:501] detection_eval = 7.35484
-I0511 11:49:27.151839  4597 caffe.cpp:501] detection_eval = 0.0515726
-I0511 11:49:27.151844  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.151849  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.151852  4597 caffe.cpp:501] detection_eval = 3.10887
-I0511 11:49:27.151857  4597 caffe.cpp:501] detection_eval = 7.30444
-I0511 11:49:27.151861  4597 caffe.cpp:501] detection_eval = 0.0465375
-I0511 11:49:27.151866  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.151870  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151875  4597 caffe.cpp:501] detection_eval = 3.10887
-I0511 11:49:27.151878  4597 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:49:27.151882  4597 caffe.cpp:501] detection_eval = 0.0428972
-I0511 11:49:27.151886  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151890  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151895  4597 caffe.cpp:501] detection_eval = 3.11089
-I0511 11:49:27.151899  4597 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:49:27.151904  4597 caffe.cpp:501] detection_eval = 0.043998
-I0511 11:49:27.151909  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.151914  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.151918  4597 caffe.cpp:501] detection_eval = 3.11089
-I0511 11:49:27.151923  4597 caffe.cpp:501] detection_eval = 7.50605
-I0511 11:49:27.151927  4597 caffe.cpp:501] detection_eval = 0.0434543
-I0511 11:49:27.151932  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.151937  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.151942  4597 caffe.cpp:501] detection_eval = 3.1129
-I0511 11:49:27.151947  4597 caffe.cpp:501] detection_eval = 7.52016
-I0511 11:49:27.151950  4597 caffe.cpp:501] detection_eval = 0.0409318
-I0511 11:49:27.151954  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.151959  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.151964  4597 caffe.cpp:501] detection_eval = 3.11492
-I0511 11:49:27.151968  4597 caffe.cpp:501] detection_eval = 7.53226
-I0511 11:49:27.151973  4597 caffe.cpp:501] detection_eval = 0.0373753
-I0511 11:49:27.151978  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.151983  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.151986  4597 caffe.cpp:501] detection_eval = 3.11492
-I0511 11:49:27.151990  4597 caffe.cpp:501] detection_eval = 7.625
-I0511 11:49:27.151995  4597 caffe.cpp:501] detection_eval = 0.0456734
-I0511 11:49:27.152000  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152004  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152009  4597 caffe.cpp:501] detection_eval = 3.11895
-I0511 11:49:27.152014  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.152019  4597 caffe.cpp:501] detection_eval = 0.0405715
-I0511 11:49:27.152022  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152027  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152031  4597 caffe.cpp:501] detection_eval = 3.11895
-I0511 11:49:27.152036  4597 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:49:27.152040  4597 caffe.cpp:501] detection_eval = 0.0450406
-I0511 11:49:27.152045  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152050  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.152055  4597 caffe.cpp:501] detection_eval = 3.12097
-I0511 11:49:27.152062  4597 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:49:27.152067  4597 caffe.cpp:501] detection_eval = 0.0423403
-I0511 11:49:27.152072  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152076  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152081  4597 caffe.cpp:501] detection_eval = 3.12097
-I0511 11:49:27.152086  4597 caffe.cpp:501] detection_eval = 7.85282
-I0511 11:49:27.152091  4597 caffe.cpp:501] detection_eval = 0.0402714
-I0511 11:49:27.152094  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152099  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152103  4597 caffe.cpp:501] detection_eval = 3.125
-I0511 11:49:27.152108  4597 caffe.cpp:501] detection_eval = 7.87097
-I0511 11:49:27.152112  4597 caffe.cpp:501] detection_eval = 0.040527
-I0511 11:49:27.152117  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.152122  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152127  4597 caffe.cpp:501] detection_eval = 3.13508
-I0511 11:49:27.152132  4597 caffe.cpp:501] detection_eval = 7.84879
-I0511 11:49:27.152135  4597 caffe.cpp:501] detection_eval = 0.0440069
-I0511 11:49:27.152140  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152144  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152149  4597 caffe.cpp:501] detection_eval = 3.1371
-I0511 11:49:27.152153  4597 caffe.cpp:501] detection_eval = 7.875
-I0511 11:49:27.152158  4597 caffe.cpp:501] detection_eval = 0.0388546
-I0511 11:49:27.152163  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152168  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152171  4597 caffe.cpp:501] detection_eval = 3.1371
-I0511 11:49:27.152176  4597 caffe.cpp:501] detection_eval = 8
-I0511 11:49:27.152180  4597 caffe.cpp:501] detection_eval = 0.0440461
-I0511 11:49:27.152185  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152189  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152194  4597 caffe.cpp:501] detection_eval = 3.14516
-I0511 11:49:27.152199  4597 caffe.cpp:501] detection_eval = 7.93548
-I0511 11:49:27.152204  4597 caffe.cpp:501] detection_eval = 0.0448261
-I0511 11:49:27.152209  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.152212  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.152217  4597 caffe.cpp:501] detection_eval = 3.14718
-I0511 11:49:27.152220  4597 caffe.cpp:501] detection_eval = 8.02218
-I0511 11:49:27.152225  4597 caffe.cpp:501] detection_eval = 0.0461768
-I0511 11:49:27.152228  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152233  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.152237  4597 caffe.cpp:501] detection_eval = 3.14919
-I0511 11:49:27.152242  4597 caffe.cpp:501] detection_eval = 8.08065
-I0511 11:49:27.152246  4597 caffe.cpp:501] detection_eval = 0.0410155
-I0511 11:49:27.152251  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152256  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152261  4597 caffe.cpp:501] detection_eval = 3.14919
-I0511 11:49:27.152264  4597 caffe.cpp:501] detection_eval = 8.13306
-I0511 11:49:27.152269  4597 caffe.cpp:501] detection_eval = 0.041873
-I0511 11:49:27.152273  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152278  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152283  4597 caffe.cpp:501] detection_eval = 3.15323
-I0511 11:49:27.152287  4597 caffe.cpp:501] detection_eval = 8.14718
-I0511 11:49:27.152292  4597 caffe.cpp:501] detection_eval = 0.0416011
-I0511 11:49:27.152297  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152302  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152307  4597 caffe.cpp:501] detection_eval = 3.15323
-I0511 11:49:27.152310  4597 caffe.cpp:501] detection_eval = 8.23589
-I0511 11:49:27.152315  4597 caffe.cpp:501] detection_eval = 0.0392452
-I0511 11:49:27.152319  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152324  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.152334  4597 caffe.cpp:501] detection_eval = 3.15524
-I0511 11:49:27.152338  4597 caffe.cpp:501] detection_eval = 8.28427
-I0511 11:49:27.152343  4597 caffe.cpp:501] detection_eval = 0.0397426
-I0511 11:49:27.152348  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152351  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152355  4597 caffe.cpp:501] detection_eval = 3.15927
-I0511 11:49:27.152359  4597 caffe.cpp:501] detection_eval = 8.3125
-I0511 11:49:27.152362  4597 caffe.cpp:501] detection_eval = 0.0466889
-I0511 11:49:27.152366  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152370  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.152374  4597 caffe.cpp:501] detection_eval = 3.16129
-I0511 11:49:27.152379  4597 caffe.cpp:501] detection_eval = 8.3125
-I0511 11:49:27.152381  4597 caffe.cpp:501] detection_eval = 0.0369168
-I0511 11:49:27.152385  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.152390  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.152393  4597 caffe.cpp:501] detection_eval = 3.16129
-I0511 11:49:27.152396  4597 caffe.cpp:501] detection_eval = 8.35685
-I0511 11:49:27.152400  4597 caffe.cpp:501] detection_eval = 0.0391665
-I0511 11:49:27.152405  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152408  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152411  4597 caffe.cpp:501] detection_eval = 3.16129
-I0511 11:49:27.152415  4597 caffe.cpp:501] detection_eval = 8.42137
-I0511 11:49:27.152420  4597 caffe.cpp:501] detection_eval = 0.0390195
-I0511 11:49:27.152422  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.152426  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152431  4597 caffe.cpp:501] detection_eval = 3.16532
-I0511 11:49:27.152433  4597 caffe.cpp:501] detection_eval = 8.48185
-I0511 11:49:27.152437  4597 caffe.cpp:501] detection_eval = 0.0436286
-I0511 11:49:27.152441  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152444  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152448  4597 caffe.cpp:501] detection_eval = 3.16734
-I0511 11:49:27.152452  4597 caffe.cpp:501] detection_eval = 8.51008
-I0511 11:49:27.152456  4597 caffe.cpp:501] detection_eval = 0.0411691
-I0511 11:49:27.152459  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152463  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152467  4597 caffe.cpp:501] detection_eval = 3.16935
-I0511 11:49:27.152470  4597 caffe.cpp:501] detection_eval = 8.52621
-I0511 11:49:27.152474  4597 caffe.cpp:501] detection_eval = 0.0441648
-I0511 11:49:27.152477  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.152482  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.152485  4597 caffe.cpp:501] detection_eval = 3.16935
-I0511 11:49:27.152489  4597 caffe.cpp:501] detection_eval = 8.60685
-I0511 11:49:27.152493  4597 caffe.cpp:501] detection_eval = 0.0394599
-I0511 11:49:27.152496  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152499  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152503  4597 caffe.cpp:501] detection_eval = 3.17742
-I0511 11:49:27.152508  4597 caffe.cpp:501] detection_eval = 8.5625
-I0511 11:49:27.152510  4597 caffe.cpp:501] detection_eval = 0.0389344
-I0511 11:49:27.152514  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152518  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152521  4597 caffe.cpp:501] detection_eval = 3.17944
-I0511 11:49:27.152530  4597 caffe.cpp:501] detection_eval = 8.62298
-I0511 11:49:27.152534  4597 caffe.cpp:501] detection_eval = 0.0426356
-I0511 11:49:27.152537  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152541  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152545  4597 caffe.cpp:501] detection_eval = 3.18548
-I0511 11:49:27.152549  4597 caffe.cpp:501] detection_eval = 8.57056
-I0511 11:49:27.152552  4597 caffe.cpp:501] detection_eval = 0.0415749
-I0511 11:49:27.152556  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152560  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152570  4597 caffe.cpp:501] detection_eval = 3.18952
-I0511 11:49:27.152573  4597 caffe.cpp:501] detection_eval = 8.55645
-I0511 11:49:27.152577  4597 caffe.cpp:501] detection_eval = 0.0385256
-I0511 11:49:27.152585  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152590  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152593  4597 caffe.cpp:501] detection_eval = 3.18952
-I0511 11:49:27.152597  4597 caffe.cpp:501] detection_eval = 8.625
-I0511 11:49:27.152601  4597 caffe.cpp:501] detection_eval = 0.0368843
-I0511 11:49:27.152604  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.152608  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152612  4597 caffe.cpp:501] detection_eval = 3.19556
-I0511 11:49:27.152616  4597 caffe.cpp:501] detection_eval = 8.625
-I0511 11:49:27.152619  4597 caffe.cpp:501] detection_eval = 0.0435754
-I0511 11:49:27.152623  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152627  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152631  4597 caffe.cpp:501] detection_eval = 3.20161
-I0511 11:49:27.152634  4597 caffe.cpp:501] detection_eval = 8.61089
-I0511 11:49:27.152637  4597 caffe.cpp:501] detection_eval = 0.043302
-I0511 11:49:27.152639  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152642  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152645  4597 caffe.cpp:501] detection_eval = 3.20565
-I0511 11:49:27.152649  4597 caffe.cpp:501] detection_eval = 8.6371
-I0511 11:49:27.152652  4597 caffe.cpp:501] detection_eval = 0.0506126
-I0511 11:49:27.152657  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.152659  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152663  4597 caffe.cpp:501] detection_eval = 3.20766
-I0511 11:49:27.152667  4597 caffe.cpp:501] detection_eval = 8.68347
-I0511 11:49:27.152671  4597 caffe.cpp:501] detection_eval = 0.0452079
-I0511 11:49:27.152674  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152678  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.152683  4597 caffe.cpp:501] detection_eval = 3.20968
-I0511 11:49:27.152686  4597 caffe.cpp:501] detection_eval = 8.76613
-I0511 11:49:27.152689  4597 caffe.cpp:501] detection_eval = 0.0383057
-I0511 11:49:27.152693  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152698  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.152700  4597 caffe.cpp:501] detection_eval = 3.21169
-I0511 11:49:27.152704  4597 caffe.cpp:501] detection_eval = 8.83266
-I0511 11:49:27.152709  4597 caffe.cpp:501] detection_eval = 0.0444229
-I0511 11:49:27.152712  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152715  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152719  4597 caffe.cpp:501] detection_eval = 3.21774
-I0511 11:49:27.152724  4597 caffe.cpp:501] detection_eval = 8.86492
-I0511 11:49:27.152727  4597 caffe.cpp:501] detection_eval = 0.0452755
-I0511 11:49:27.152730  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152734  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152739  4597 caffe.cpp:501] detection_eval = 3.21774
-I0511 11:49:27.152742  4597 caffe.cpp:501] detection_eval = 8.95968
-I0511 11:49:27.152746  4597 caffe.cpp:501] detection_eval = 0.0407374
-I0511 11:49:27.152750  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152753  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152757  4597 caffe.cpp:501] detection_eval = 3.22177
-I0511 11:49:27.152761  4597 caffe.cpp:501] detection_eval = 9.01411
-I0511 11:49:27.152765  4597 caffe.cpp:501] detection_eval = 0.0426849
-I0511 11:49:27.152768  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152772  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.152776  4597 caffe.cpp:501] detection_eval = 3.22177
-I0511 11:49:27.152781  4597 caffe.cpp:501] detection_eval = 9.05847
-I0511 11:49:27.152783  4597 caffe.cpp:501] detection_eval = 0.0415161
-I0511 11:49:27.152787  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152796  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152801  4597 caffe.cpp:501] detection_eval = 3.22379
-I0511 11:49:27.152803  4597 caffe.cpp:501] detection_eval = 9.1371
-I0511 11:49:27.152807  4597 caffe.cpp:501] detection_eval = 0.0415253
-I0511 11:49:27.152812  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152815  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.152818  4597 caffe.cpp:501] detection_eval = 3.22581
-I0511 11:49:27.152822  4597 caffe.cpp:501] detection_eval = 9.16532
-I0511 11:49:27.152827  4597 caffe.cpp:501] detection_eval = 0.0399029
-I0511 11:49:27.152829  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152833  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152837  4597 caffe.cpp:501] detection_eval = 3.22984
-I0511 11:49:27.152840  4597 caffe.cpp:501] detection_eval = 9.20766
-I0511 11:49:27.152844  4597 caffe.cpp:501] detection_eval = 0.044318
-I0511 11:49:27.152848  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.152853  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152856  4597 caffe.cpp:501] detection_eval = 3.23185
-I0511 11:49:27.152860  4597 caffe.cpp:501] detection_eval = 9.27621
-I0511 11:49:27.152863  4597 caffe.cpp:501] detection_eval = 0.0447398
-I0511 11:49:27.152866  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.152869  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152873  4597 caffe.cpp:501] detection_eval = 3.23185
-I0511 11:49:27.152875  4597 caffe.cpp:501] detection_eval = 9.37298
-I0511 11:49:27.152878  4597 caffe.cpp:501] detection_eval = 0.036686
-I0511 11:49:27.152881  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.152884  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152887  4597 caffe.cpp:501] detection_eval = 3.23185
-I0511 11:49:27.152891  4597 caffe.cpp:501] detection_eval = 9.43145
-I0511 11:49:27.152894  4597 caffe.cpp:501] detection_eval = 0.0405621
-I0511 11:49:27.152897  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152900  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.152904  4597 caffe.cpp:501] detection_eval = 3.23387
-I0511 11:49:27.152906  4597 caffe.cpp:501] detection_eval = 9.52016
-I0511 11:49:27.152909  4597 caffe.cpp:501] detection_eval = 0.0485003
-I0511 11:49:27.152912  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152916  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152920  4597 caffe.cpp:501] detection_eval = 3.2379
-I0511 11:49:27.152922  4597 caffe.cpp:501] detection_eval = 9.55242
-I0511 11:49:27.152925  4597 caffe.cpp:501] detection_eval = 0.046264
-I0511 11:49:27.152928  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.152931  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.152935  4597 caffe.cpp:501] detection_eval = 3.23992
-I0511 11:49:27.152938  4597 caffe.cpp:501] detection_eval = 9.61694
-I0511 11:49:27.152941  4597 caffe.cpp:501] detection_eval = 0.045028
-I0511 11:49:27.152945  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152947  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152951  4597 caffe.cpp:501] detection_eval = 3.24395
-I0511 11:49:27.152954  4597 caffe.cpp:501] detection_eval = 9.64113
-I0511 11:49:27.152957  4597 caffe.cpp:501] detection_eval = 0.0462392
-I0511 11:49:27.152961  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.152963  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.152966  4597 caffe.cpp:501] detection_eval = 3.24597
-I0511 11:49:27.152971  4597 caffe.cpp:501] detection_eval = 9.6875
-I0511 11:49:27.152973  4597 caffe.cpp:501] detection_eval = 0.0422627
-I0511 11:49:27.152976  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.152979  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.152982  4597 caffe.cpp:501] detection_eval = 3.25
-I0511 11:49:27.152987  4597 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:49:27.152989  4597 caffe.cpp:501] detection_eval = 0.0485173
-I0511 11:49:27.152992  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153002  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.153005  4597 caffe.cpp:501] detection_eval = 3.25
-I0511 11:49:27.153008  4597 caffe.cpp:501] detection_eval = 9.77621
-I0511 11:49:27.153012  4597 caffe.cpp:501] detection_eval = 0.0414143
-I0511 11:49:27.153015  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153018  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153021  4597 caffe.cpp:501] detection_eval = 3.25403
-I0511 11:49:27.153024  4597 caffe.cpp:501] detection_eval = 9.79032
-I0511 11:49:27.153028  4597 caffe.cpp:501] detection_eval = 0.0382315
-I0511 11:49:27.153031  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.153034  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153038  4597 caffe.cpp:501] detection_eval = 3.25403
-I0511 11:49:27.153040  4597 caffe.cpp:501] detection_eval = 9.91532
-I0511 11:49:27.153043  4597 caffe.cpp:501] detection_eval = 0.0424618
-I0511 11:49:27.153046  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153050  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153053  4597 caffe.cpp:501] detection_eval = 3.25403
-I0511 11:49:27.153056  4597 caffe.cpp:501] detection_eval = 10.002
-I0511 11:49:27.153060  4597 caffe.cpp:501] detection_eval = 0.0471143
-I0511 11:49:27.153064  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153066  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153069  4597 caffe.cpp:501] detection_eval = 3.25605
-I0511 11:49:27.153072  4597 caffe.cpp:501] detection_eval = 10.0544
-I0511 11:49:27.153076  4597 caffe.cpp:501] detection_eval = 0.0453307
-I0511 11:49:27.153079  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153082  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153085  4597 caffe.cpp:501] detection_eval = 3.26008
-I0511 11:49:27.153089  4597 caffe.cpp:501] detection_eval = 10.129
-I0511 11:49:27.153091  4597 caffe.cpp:501] detection_eval = 0.0452135
-I0511 11:49:27.153095  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153098  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153102  4597 caffe.cpp:501] detection_eval = 3.26613
-I0511 11:49:27.153106  4597 caffe.cpp:501] detection_eval = 10.1512
-I0511 11:49:27.153111  4597 caffe.cpp:501] detection_eval = 0.0456583
-I0511 11:49:27.153115  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153120  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153123  4597 caffe.cpp:501] detection_eval = 3.26613
-I0511 11:49:27.153128  4597 caffe.cpp:501] detection_eval = 10.2782
-I0511 11:49:27.153132  4597 caffe.cpp:501] detection_eval = 0.0444525
-I0511 11:49:27.153137  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153141  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153144  4597 caffe.cpp:501] detection_eval = 3.27218
-I0511 11:49:27.153148  4597 caffe.cpp:501] detection_eval = 10.248
-I0511 11:49:27.153151  4597 caffe.cpp:501] detection_eval = 0.0425943
-I0511 11:49:27.153156  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.153159  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.153162  4597 caffe.cpp:501] detection_eval = 3.28024
-I0511 11:49:27.153165  4597 caffe.cpp:501] detection_eval = 10.1694
-I0511 11:49:27.153169  4597 caffe.cpp:501] detection_eval = 0.0454558
-I0511 11:49:27.153174  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153177  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153182  4597 caffe.cpp:501] detection_eval = 3.28226
-I0511 11:49:27.153185  4597 caffe.cpp:501] detection_eval = 10.1976
-I0511 11:49:27.153188  4597 caffe.cpp:501] detection_eval = 0.0412913
-I0511 11:49:27.153192  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153195  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153199  4597 caffe.cpp:501] detection_eval = 3.28629
-I0511 11:49:27.153203  4597 caffe.cpp:501] detection_eval = 10.1754
-I0511 11:49:27.153206  4597 caffe.cpp:501] detection_eval = 0.0441255
-I0511 11:49:27.153213  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.153218  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.153223  4597 caffe.cpp:501] detection_eval = 3.28831
-I0511 11:49:27.153228  4597 caffe.cpp:501] detection_eval = 10.1976
-I0511 11:49:27.153231  4597 caffe.cpp:501] detection_eval = 0.0426045
-I0511 11:49:27.153235  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153240  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153244  4597 caffe.cpp:501] detection_eval = 3.29234
-I0511 11:49:27.153247  4597 caffe.cpp:501] detection_eval = 10.2198
-I0511 11:49:27.153250  4597 caffe.cpp:501] detection_eval = 0.0416863
-I0511 11:49:27.153254  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153257  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153261  4597 caffe.cpp:501] detection_eval = 3.29435
-I0511 11:49:27.153265  4597 caffe.cpp:501] detection_eval = 10.2883
-I0511 11:49:27.153270  4597 caffe.cpp:501] detection_eval = 0.049003
-I0511 11:49:27.153272  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153275  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153280  4597 caffe.cpp:501] detection_eval = 3.29839
-I0511 11:49:27.153282  4597 caffe.cpp:501] detection_eval = 10.3226
-I0511 11:49:27.153285  4597 caffe.cpp:501] detection_eval = 0.0428636
-I0511 11:49:27.153290  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153292  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153296  4597 caffe.cpp:501] detection_eval = 3.30444
-I0511 11:49:27.153300  4597 caffe.cpp:501] detection_eval = 10.3065
-I0511 11:49:27.153302  4597 caffe.cpp:501] detection_eval = 0.0454338
-I0511 11:49:27.153306  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153309  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153312  4597 caffe.cpp:501] detection_eval = 3.30645
-I0511 11:49:27.153316  4597 caffe.cpp:501] detection_eval = 10.3407
-I0511 11:49:27.153319  4597 caffe.cpp:501] detection_eval = 0.040954
-I0511 11:49:27.153323  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153326  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153329  4597 caffe.cpp:501] detection_eval = 3.30847
-I0511 11:49:27.153333  4597 caffe.cpp:501] detection_eval = 10.4093
-I0511 11:49:27.153337  4597 caffe.cpp:501] detection_eval = 0.0444435
-I0511 11:49:27.153340  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.153343  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153347  4597 caffe.cpp:501] detection_eval = 3.31653
-I0511 11:49:27.153349  4597 caffe.cpp:501] detection_eval = 10.3851
-I0511 11:49:27.153353  4597 caffe.cpp:501] detection_eval = 0.0424642
-I0511 11:49:27.153357  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153360  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153363  4597 caffe.cpp:501] detection_eval = 3.31855
-I0511 11:49:27.153367  4597 caffe.cpp:501] detection_eval = 10.4496
-I0511 11:49:27.153370  4597 caffe.cpp:501] detection_eval = 0.0432248
-I0511 11:49:27.153373  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.153378  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.153383  4597 caffe.cpp:501] detection_eval = 3.31855
-I0511 11:49:27.153385  4597 caffe.cpp:501] detection_eval = 10.5343
-I0511 11:49:27.153389  4597 caffe.cpp:501] detection_eval = 0.046504
-I0511 11:49:27.153393  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153395  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153398  4597 caffe.cpp:501] detection_eval = 3.32056
-I0511 11:49:27.153403  4597 caffe.cpp:501] detection_eval = 10.5383
-I0511 11:49:27.153405  4597 caffe.cpp:501] detection_eval = 0.0392196
-I0511 11:49:27.153409  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153412  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153415  4597 caffe.cpp:501] detection_eval = 3.32661
-I0511 11:49:27.153419  4597 caffe.cpp:501] detection_eval = 10.4778
-I0511 11:49:27.153422  4597 caffe.cpp:501] detection_eval = 0.048008
-I0511 11:49:27.153429  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153434  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.153436  4597 caffe.cpp:501] detection_eval = 3.32863
-I0511 11:49:27.153439  4597 caffe.cpp:501] detection_eval = 10.5121
-I0511 11:49:27.153443  4597 caffe.cpp:501] detection_eval = 0.0472867
-I0511 11:49:27.153446  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153450  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153453  4597 caffe.cpp:501] detection_eval = 3.33266
-I0511 11:49:27.153456  4597 caffe.cpp:501] detection_eval = 10.5
-I0511 11:49:27.153460  4597 caffe.cpp:501] detection_eval = 0.0381142
-I0511 11:49:27.153463  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153466  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153470  4597 caffe.cpp:501] detection_eval = 3.33266
-I0511 11:49:27.153473  4597 caffe.cpp:501] detection_eval = 10.5645
-I0511 11:49:27.153476  4597 caffe.cpp:501] detection_eval = 0.042484
-I0511 11:49:27.153479  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153482  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153486  4597 caffe.cpp:501] detection_eval = 3.33468
-I0511 11:49:27.153489  4597 caffe.cpp:501] detection_eval = 10.5827
-I0511 11:49:27.153492  4597 caffe.cpp:501] detection_eval = 0.0410557
-I0511 11:49:27.153496  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153499  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.153502  4597 caffe.cpp:501] detection_eval = 3.33871
-I0511 11:49:27.153506  4597 caffe.cpp:501] detection_eval = 10.5806
-I0511 11:49:27.153508  4597 caffe.cpp:501] detection_eval = 0.0408412
-I0511 11:49:27.153512  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153515  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153519  4597 caffe.cpp:501] detection_eval = 3.34073
-I0511 11:49:27.153522  4597 caffe.cpp:501] detection_eval = 10.623
-I0511 11:49:27.153525  4597 caffe.cpp:501] detection_eval = 0.0379402
-I0511 11:49:27.153529  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.153532  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.153535  4597 caffe.cpp:501] detection_eval = 3.34274
-I0511 11:49:27.153539  4597 caffe.cpp:501] detection_eval = 10.6673
-I0511 11:49:27.153542  4597 caffe.cpp:501] detection_eval = 0.0444984
-I0511 11:49:27.153547  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.153549  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153553  4597 caffe.cpp:501] detection_eval = 3.34274
-I0511 11:49:27.153555  4597 caffe.cpp:501] detection_eval = 10.7137
-I0511 11:49:27.153558  4597 caffe.cpp:501] detection_eval = 0.0387068
-I0511 11:49:27.153563  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153565  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153568  4597 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:49:27.153573  4597 caffe.cpp:501] detection_eval = 10.7883
-I0511 11:49:27.153578  4597 caffe.cpp:501] detection_eval = 0.0405686
-I0511 11:49:27.153583  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.153587  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153591  4597 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:49:27.153595  4597 caffe.cpp:501] detection_eval = 10.8589
-I0511 11:49:27.153599  4597 caffe.cpp:501] detection_eval = 0.0389239
-I0511 11:49:27.153604  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153606  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153609  4597 caffe.cpp:501] detection_eval = 3.34879
-I0511 11:49:27.153614  4597 caffe.cpp:501] detection_eval = 10.8972
-I0511 11:49:27.153616  4597 caffe.cpp:501] detection_eval = 0.0452635
-I0511 11:49:27.153620  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.153625  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.153628  4597 caffe.cpp:501] detection_eval = 3.35484
-I0511 11:49:27.153632  4597 caffe.cpp:501] detection_eval = 10.871
-I0511 11:49:27.153641  4597 caffe.cpp:501] detection_eval = 0.0455467
-I0511 11:49:27.153647  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153651  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153656  4597 caffe.cpp:501] detection_eval = 3.35887
-I0511 11:49:27.153659  4597 caffe.cpp:501] detection_eval = 10.9214
-I0511 11:49:27.153663  4597 caffe.cpp:501] detection_eval = 0.0479988
-I0511 11:49:27.153667  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153671  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.153674  4597 caffe.cpp:501] detection_eval = 3.36089
-I0511 11:49:27.153679  4597 caffe.cpp:501] detection_eval = 10.9395
-I0511 11:49:27.153683  4597 caffe.cpp:501] detection_eval = 0.0459227
-I0511 11:49:27.153687  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.153690  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.153694  4597 caffe.cpp:501] detection_eval = 3.3629
-I0511 11:49:27.153698  4597 caffe.cpp:501] detection_eval = 10.998
-I0511 11:49:27.153702  4597 caffe.cpp:501] detection_eval = 0.0506618
-I0511 11:49:27.153707  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.153710  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.153713  4597 caffe.cpp:501] detection_eval = 3.36492
-I0511 11:49:27.153717  4597 caffe.cpp:501] detection_eval = 11.0202
-I0511 11:49:27.153722  4597 caffe.cpp:501] detection_eval = 0.043561
-I0511 11:49:27.153725  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153729  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153733  4597 caffe.cpp:501] detection_eval = 3.37097
-I0511 11:49:27.153738  4597 caffe.cpp:501] detection_eval = 11
-I0511 11:49:27.153741  4597 caffe.cpp:501] detection_eval = 0.0421032
-I0511 11:49:27.153745  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.153748  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.153753  4597 caffe.cpp:501] detection_eval = 3.37298
-I0511 11:49:27.153756  4597 caffe.cpp:501] detection_eval = 11.0222
-I0511 11:49:27.153760  4597 caffe.cpp:501] detection_eval = 0.0413465
-I0511 11:49:27.153764  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153769  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153771  4597 caffe.cpp:501] detection_eval = 3.37298
-I0511 11:49:27.153775  4597 caffe.cpp:501] detection_eval = 11.1069
-I0511 11:49:27.153779  4597 caffe.cpp:501] detection_eval = 0.0478731
-I0511 11:49:27.153784  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153787  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153790  4597 caffe.cpp:501] detection_eval = 3.37298
-I0511 11:49:27.153795  4597 caffe.cpp:501] detection_eval = 11.1331
-I0511 11:49:27.153798  4597 caffe.cpp:501] detection_eval = 0.0393092
-I0511 11:49:27.153802  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.153805  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.153810  4597 caffe.cpp:501] detection_eval = 3.37298
-I0511 11:49:27.153813  4597 caffe.cpp:501] detection_eval = 11.1956
-I0511 11:49:27.153817  4597 caffe.cpp:501] detection_eval = 0.0357141
-I0511 11:49:27.153821  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153825  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153828  4597 caffe.cpp:501] detection_eval = 3.375
-I0511 11:49:27.153832  4597 caffe.cpp:501] detection_eval = 11.256
-I0511 11:49:27.153836  4597 caffe.cpp:501] detection_eval = 0.0397309
-I0511 11:49:27.153841  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.153843  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.153847  4597 caffe.cpp:501] detection_eval = 3.37702
-I0511 11:49:27.153851  4597 caffe.cpp:501] detection_eval = 11.2863
-I0511 11:49:27.153856  4597 caffe.cpp:501] detection_eval = 0.0429492
-I0511 11:49:27.153858  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153862  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.153867  4597 caffe.cpp:501] detection_eval = 3.37702
-I0511 11:49:27.153873  4597 caffe.cpp:501] detection_eval = 11.3871
-I0511 11:49:27.153877  4597 caffe.cpp:501] detection_eval = 0.0470726
-I0511 11:49:27.153882  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153885  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153888  4597 caffe.cpp:501] detection_eval = 3.37903
-I0511 11:49:27.153892  4597 caffe.cpp:501] detection_eval = 11.4577
-I0511 11:49:27.153897  4597 caffe.cpp:501] detection_eval = 0.0455222
-I0511 11:49:27.153899  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.153903  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.153908  4597 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:49:27.153910  4597 caffe.cpp:501] detection_eval = 11.496
-I0511 11:49:27.153914  4597 caffe.cpp:501] detection_eval = 0.0377702
-I0511 11:49:27.153918  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.153923  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.153926  4597 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:49:27.153929  4597 caffe.cpp:501] detection_eval = 11.6129
-I0511 11:49:27.153934  4597 caffe.cpp:501] detection_eval = 0.0432228
-I0511 11:49:27.153937  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.153941  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153944  4597 caffe.cpp:501] detection_eval = 3.38508
-I0511 11:49:27.153949  4597 caffe.cpp:501] detection_eval = 11.6472
-I0511 11:49:27.153952  4597 caffe.cpp:501] detection_eval = 0.0457813
-I0511 11:49:27.153956  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.153960  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.153964  4597 caffe.cpp:501] detection_eval = 3.3871
-I0511 11:49:27.153967  4597 caffe.cpp:501] detection_eval = 11.6754
-I0511 11:49:27.153971  4597 caffe.cpp:501] detection_eval = 0.0452665
-I0511 11:49:27.153975  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.153978  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.153982  4597 caffe.cpp:501] detection_eval = 3.38911
-I0511 11:49:27.153986  4597 caffe.cpp:501] detection_eval = 11.7379
-I0511 11:49:27.153990  4597 caffe.cpp:501] detection_eval = 0.0458116
-I0511 11:49:27.153993  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.153997  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.154001  4597 caffe.cpp:501] detection_eval = 3.39315
-I0511 11:49:27.154004  4597 caffe.cpp:501] detection_eval = 11.7742
-I0511 11:49:27.154008  4597 caffe.cpp:501] detection_eval = 0.042421
-I0511 11:49:27.154012  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154016  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.154019  4597 caffe.cpp:501] detection_eval = 3.39919
-I0511 11:49:27.154023  4597 caffe.cpp:501] detection_eval = 11.8468
-I0511 11:49:27.154027  4597 caffe.cpp:501] detection_eval = 0.0538771
-I0511 11:49:27.154031  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.154034  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.154038  4597 caffe.cpp:501] detection_eval = 3.40323
-I0511 11:49:27.154042  4597 caffe.cpp:501] detection_eval = 11.8548
-I0511 11:49:27.154047  4597 caffe.cpp:501] detection_eval = 0.0412682
-I0511 11:49:27.154050  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154053  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154057  4597 caffe.cpp:501] detection_eval = 3.40726
-I0511 11:49:27.154062  4597 caffe.cpp:501] detection_eval = 11.8468
-I0511 11:49:27.154065  4597 caffe.cpp:501] detection_eval = 0.0429546
-I0511 11:49:27.154069  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154073  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154076  4597 caffe.cpp:501] detection_eval = 3.40726
-I0511 11:49:27.154080  4597 caffe.cpp:501] detection_eval = 11.8891
-I0511 11:49:27.154084  4597 caffe.cpp:501] detection_eval = 0.0432336
-I0511 11:49:27.154088  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154093  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154095  4597 caffe.cpp:501] detection_eval = 3.40927
-I0511 11:49:27.154103  4597 caffe.cpp:501] detection_eval = 11.9395
-I0511 11:49:27.154109  4597 caffe.cpp:501] detection_eval = 0.03952
-I0511 11:49:27.154111  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154115  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154119  4597 caffe.cpp:501] detection_eval = 3.40927
-I0511 11:49:27.154124  4597 caffe.cpp:501] detection_eval = 11.9819
-I0511 11:49:27.154127  4597 caffe.cpp:501] detection_eval = 0.0377363
-I0511 11:49:27.154131  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154135  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154139  4597 caffe.cpp:501] detection_eval = 3.40927
-I0511 11:49:27.154142  4597 caffe.cpp:501] detection_eval = 12.0444
-I0511 11:49:27.154146  4597 caffe.cpp:501] detection_eval = 0.040587
-I0511 11:49:27.154150  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154155  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154157  4597 caffe.cpp:501] detection_eval = 3.41734
-I0511 11:49:27.154161  4597 caffe.cpp:501] detection_eval = 11.9899
-I0511 11:49:27.154165  4597 caffe.cpp:501] detection_eval = 0.0405691
-I0511 11:49:27.154170  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154173  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154176  4597 caffe.cpp:501] detection_eval = 3.41935
-I0511 11:49:27.154181  4597 caffe.cpp:501] detection_eval = 12.0101
-I0511 11:49:27.154184  4597 caffe.cpp:501] detection_eval = 0.0373197
-I0511 11:49:27.154188  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154192  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154196  4597 caffe.cpp:501] detection_eval = 3.42137
-I0511 11:49:27.154199  4597 caffe.cpp:501] detection_eval = 12.0383
-I0511 11:49:27.154203  4597 caffe.cpp:501] detection_eval = 0.0420197
-I0511 11:49:27.154207  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154211  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154214  4597 caffe.cpp:501] detection_eval = 3.42742
-I0511 11:49:27.154218  4597 caffe.cpp:501] detection_eval = 11.9919
-I0511 11:49:27.154222  4597 caffe.cpp:501] detection_eval = 0.0407463
-I0511 11:49:27.154227  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154229  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154233  4597 caffe.cpp:501] detection_eval = 3.43145
-I0511 11:49:27.154237  4597 caffe.cpp:501] detection_eval = 12.0121
-I0511 11:49:27.154242  4597 caffe.cpp:501] detection_eval = 0.0429001
-I0511 11:49:27.154245  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.154248  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.154253  4597 caffe.cpp:501] detection_eval = 3.43347
-I0511 11:49:27.154256  4597 caffe.cpp:501] detection_eval = 12.0242
-I0511 11:49:27.154260  4597 caffe.cpp:501] detection_eval = 0.0425635
-I0511 11:49:27.154265  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154268  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154273  4597 caffe.cpp:501] detection_eval = 3.43548
-I0511 11:49:27.154276  4597 caffe.cpp:501] detection_eval = 12.0645
-I0511 11:49:27.154280  4597 caffe.cpp:501] detection_eval = 0.0406314
-I0511 11:49:27.154284  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154287  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154291  4597 caffe.cpp:501] detection_eval = 3.43952
-I0511 11:49:27.154295  4597 caffe.cpp:501] detection_eval = 12.0706
-I0511 11:49:27.154299  4597 caffe.cpp:501] detection_eval = 0.0404113
-I0511 11:49:27.154304  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154307  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154311  4597 caffe.cpp:501] detection_eval = 3.4496
-I0511 11:49:27.154315  4597 caffe.cpp:501] detection_eval = 11.998
-I0511 11:49:27.154320  4597 caffe.cpp:501] detection_eval = 0.0431162
-I0511 11:49:27.154323  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154327  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.154336  4597 caffe.cpp:501] detection_eval = 3.45161
-I0511 11:49:27.154340  4597 caffe.cpp:501] detection_eval = 12.0383
-I0511 11:49:27.154345  4597 caffe.cpp:501] detection_eval = 0.0391035
-I0511 11:49:27.154348  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154352  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154356  4597 caffe.cpp:501] detection_eval = 3.45766
-I0511 11:49:27.154359  4597 caffe.cpp:501] detection_eval = 12.0444
-I0511 11:49:27.154363  4597 caffe.cpp:501] detection_eval = 0.0427302
-I0511 11:49:27.154367  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.154371  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.154376  4597 caffe.cpp:501] detection_eval = 3.45968
-I0511 11:49:27.154378  4597 caffe.cpp:501] detection_eval = 12.0907
-I0511 11:49:27.154382  4597 caffe.cpp:501] detection_eval = 0.0453491
-I0511 11:49:27.154386  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154390  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154394  4597 caffe.cpp:501] detection_eval = 3.46169
-I0511 11:49:27.154397  4597 caffe.cpp:501] detection_eval = 12.123
-I0511 11:49:27.154402  4597 caffe.cpp:501] detection_eval = 0.0436261
-I0511 11:49:27.154405  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154409  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154413  4597 caffe.cpp:501] detection_eval = 3.46976
-I0511 11:49:27.154417  4597 caffe.cpp:501] detection_eval = 12.0403
-I0511 11:49:27.154420  4597 caffe.cpp:501] detection_eval = 0.041762
-I0511 11:49:27.154424  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154428  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.154431  4597 caffe.cpp:501] detection_eval = 3.47782
-I0511 11:49:27.154435  4597 caffe.cpp:501] detection_eval = 11.9496
-I0511 11:49:27.154439  4597 caffe.cpp:501] detection_eval = 0.0373443
-I0511 11:49:27.154443  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154446  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154450  4597 caffe.cpp:501] detection_eval = 3.47984
-I0511 11:49:27.154454  4597 caffe.cpp:501] detection_eval = 11.994
-I0511 11:49:27.154458  4597 caffe.cpp:501] detection_eval = 0.0407181
-I0511 11:49:27.154462  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154466  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154469  4597 caffe.cpp:501] detection_eval = 3.47984
-I0511 11:49:27.154474  4597 caffe.cpp:501] detection_eval = 12.0524
-I0511 11:49:27.154477  4597 caffe.cpp:501] detection_eval = 0.0409062
-I0511 11:49:27.154481  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154485  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.154489  4597 caffe.cpp:501] detection_eval = 3.48185
-I0511 11:49:27.154492  4597 caffe.cpp:501] detection_eval = 12.0726
-I0511 11:49:27.154497  4597 caffe.cpp:501] detection_eval = 0.0378516
-I0511 11:49:27.154500  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154505  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154508  4597 caffe.cpp:501] detection_eval = 3.48185
-I0511 11:49:27.154512  4597 caffe.cpp:501] detection_eval = 12.1815
-I0511 11:49:27.154516  4597 caffe.cpp:501] detection_eval = 0.0447198
-I0511 11:49:27.154520  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154525  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154527  4597 caffe.cpp:501] detection_eval = 3.48185
-I0511 11:49:27.154531  4597 caffe.cpp:501] detection_eval = 12.2056
-I0511 11:49:27.154536  4597 caffe.cpp:501] detection_eval = 0.0356161
-I0511 11:49:27.154539  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154543  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154546  4597 caffe.cpp:501] detection_eval = 3.48387
-I0511 11:49:27.154551  4597 caffe.cpp:501] detection_eval = 12.2621
-I0511 11:49:27.154554  4597 caffe.cpp:501] detection_eval = 0.0392694
-I0511 11:49:27.154558  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154561  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154569  4597 caffe.cpp:501] detection_eval = 3.48589
-I0511 11:49:27.154573  4597 caffe.cpp:501] detection_eval = 12.3206
-I0511 11:49:27.154577  4597 caffe.cpp:501] detection_eval = 0.0422359
-I0511 11:49:27.154580  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154584  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154588  4597 caffe.cpp:501] detection_eval = 3.49194
-I0511 11:49:27.154592  4597 caffe.cpp:501] detection_eval = 12.3024
-I0511 11:49:27.154597  4597 caffe.cpp:501] detection_eval = 0.0398411
-I0511 11:49:27.154599  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154603  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154608  4597 caffe.cpp:501] detection_eval = 3.49395
-I0511 11:49:27.154610  4597 caffe.cpp:501] detection_eval = 12.3508
-I0511 11:49:27.154614  4597 caffe.cpp:501] detection_eval = 0.0360825
-I0511 11:49:27.154618  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.154623  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154626  4597 caffe.cpp:501] detection_eval = 3.49395
-I0511 11:49:27.154629  4597 caffe.cpp:501] detection_eval = 12.4153
-I0511 11:49:27.154633  4597 caffe.cpp:501] detection_eval = 0.0379566
-I0511 11:49:27.154637  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154641  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154645  4597 caffe.cpp:501] detection_eval = 3.5
-I0511 11:49:27.154649  4597 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:49:27.154654  4597 caffe.cpp:501] detection_eval = 0.0408221
-I0511 11:49:27.154657  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154660  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154664  4597 caffe.cpp:501] detection_eval = 3.50806
-I0511 11:49:27.154669  4597 caffe.cpp:501] detection_eval = 12.3569
-I0511 11:49:27.154672  4597 caffe.cpp:501] detection_eval = 0.0385258
-I0511 11:49:27.154675  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154680  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154683  4597 caffe.cpp:501] detection_eval = 3.51008
-I0511 11:49:27.154687  4597 caffe.cpp:501] detection_eval = 12.371
-I0511 11:49:27.154691  4597 caffe.cpp:501] detection_eval = 0.0400125
-I0511 11:49:27.154695  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154698  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154702  4597 caffe.cpp:501] detection_eval = 3.5121
-I0511 11:49:27.154706  4597 caffe.cpp:501] detection_eval = 12.4173
-I0511 11:49:27.154711  4597 caffe.cpp:501] detection_eval = 0.0370765
-I0511 11:49:27.154713  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.154718  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154722  4597 caffe.cpp:501] detection_eval = 3.5121
-I0511 11:49:27.154726  4597 caffe.cpp:501] detection_eval = 12.4839
-I0511 11:49:27.154729  4597 caffe.cpp:501] detection_eval = 0.0374453
-I0511 11:49:27.154733  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154737  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.154742  4597 caffe.cpp:501] detection_eval = 3.5121
-I0511 11:49:27.154744  4597 caffe.cpp:501] detection_eval = 12.5645
-I0511 11:49:27.154748  4597 caffe.cpp:501] detection_eval = 0.0435159
-I0511 11:49:27.154752  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154757  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.154760  4597 caffe.cpp:501] detection_eval = 3.51613
-I0511 11:49:27.154764  4597 caffe.cpp:501] detection_eval = 12.6149
-I0511 11:49:27.154768  4597 caffe.cpp:501] detection_eval = 0.0416669
-I0511 11:49:27.154772  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154775  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.154779  4597 caffe.cpp:501] detection_eval = 3.52218
-I0511 11:49:27.154783  4597 caffe.cpp:501] detection_eval = 12.6089
-I0511 11:49:27.154786  4597 caffe.cpp:501] detection_eval = 0.0419004
-I0511 11:49:27.154790  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.154798  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154803  4597 caffe.cpp:501] detection_eval = 3.52621
-I0511 11:49:27.154806  4597 caffe.cpp:501] detection_eval = 12.5988
-I0511 11:49:27.154810  4597 caffe.cpp:501] detection_eval = 0.0393724
-I0511 11:49:27.154814  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154817  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.154821  4597 caffe.cpp:501] detection_eval = 3.53024
-I0511 11:49:27.154824  4597 caffe.cpp:501] detection_eval = 12.5665
-I0511 11:49:27.154829  4597 caffe.cpp:501] detection_eval = 0.0363939
-I0511 11:49:27.154832  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154836  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154840  4597 caffe.cpp:501] detection_eval = 3.53427
-I0511 11:49:27.154844  4597 caffe.cpp:501] detection_eval = 12.5665
-I0511 11:49:27.154847  4597 caffe.cpp:501] detection_eval = 0.0383389
-I0511 11:49:27.154851  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.154855  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154860  4597 caffe.cpp:501] detection_eval = 3.53831
-I0511 11:49:27.154862  4597 caffe.cpp:501] detection_eval = 12.5706
-I0511 11:49:27.154866  4597 caffe.cpp:501] detection_eval = 0.0337247
-I0511 11:49:27.154870  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.154875  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.154878  4597 caffe.cpp:501] detection_eval = 3.53831
-I0511 11:49:27.154881  4597 caffe.cpp:501] detection_eval = 12.6411
-I0511 11:49:27.154886  4597 caffe.cpp:501] detection_eval = 0.0380939
-I0511 11:49:27.154889  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154893  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.154897  4597 caffe.cpp:501] detection_eval = 3.54234
-I0511 11:49:27.154901  4597 caffe.cpp:501] detection_eval = 12.6331
-I0511 11:49:27.154904  4597 caffe.cpp:501] detection_eval = 0.037627
-I0511 11:49:27.154908  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.154912  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.154917  4597 caffe.cpp:501] detection_eval = 3.54234
-I0511 11:49:27.154919  4597 caffe.cpp:501] detection_eval = 12.6855
-I0511 11:49:27.154923  4597 caffe.cpp:501] detection_eval = 0.0369024
-I0511 11:49:27.154927  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154932  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.154934  4597 caffe.cpp:501] detection_eval = 3.54435
-I0511 11:49:27.154938  4597 caffe.cpp:501] detection_eval = 12.6996
-I0511 11:49:27.154942  4597 caffe.cpp:501] detection_eval = 0.0372405
-I0511 11:49:27.154947  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.154950  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.154953  4597 caffe.cpp:501] detection_eval = 3.54637
-I0511 11:49:27.154958  4597 caffe.cpp:501] detection_eval = 12.7319
-I0511 11:49:27.154961  4597 caffe.cpp:501] detection_eval = 0.0383912
-I0511 11:49:27.154964  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.154968  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.154973  4597 caffe.cpp:501] detection_eval = 3.5504
-I0511 11:49:27.154976  4597 caffe.cpp:501] detection_eval = 12.7298
-I0511 11:49:27.154980  4597 caffe.cpp:501] detection_eval = 0.0358585
-I0511 11:49:27.154984  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.154987  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.154991  4597 caffe.cpp:501] detection_eval = 3.55444
-I0511 11:49:27.154995  4597 caffe.cpp:501] detection_eval = 12.7419
-I0511 11:49:27.154999  4597 caffe.cpp:501] detection_eval = 0.034492
-I0511 11:49:27.155004  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155006  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155010  4597 caffe.cpp:501] detection_eval = 3.55645
-I0511 11:49:27.155014  4597 caffe.cpp:501] detection_eval = 12.7722
-I0511 11:49:27.155019  4597 caffe.cpp:501] detection_eval = 0.036101
-I0511 11:49:27.155026  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155030  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155035  4597 caffe.cpp:501] detection_eval = 3.56048
-I0511 11:49:27.155037  4597 caffe.cpp:501] detection_eval = 12.7823
-I0511 11:49:27.155041  4597 caffe.cpp:501] detection_eval = 0.0382512
-I0511 11:49:27.155045  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.155050  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155053  4597 caffe.cpp:501] detection_eval = 3.56653
-I0511 11:49:27.155056  4597 caffe.cpp:501] detection_eval = 12.7702
-I0511 11:49:27.155061  4597 caffe.cpp:501] detection_eval = 0.0426121
-I0511 11:49:27.155064  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155068  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.155071  4597 caffe.cpp:501] detection_eval = 3.56855
-I0511 11:49:27.155076  4597 caffe.cpp:501] detection_eval = 12.7762
-I0511 11:49:27.155079  4597 caffe.cpp:501] detection_eval = 0.0349352
-I0511 11:49:27.155083  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.155086  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155091  4597 caffe.cpp:501] detection_eval = 3.56855
-I0511 11:49:27.155094  4597 caffe.cpp:501] detection_eval = 12.8468
-I0511 11:49:27.155098  4597 caffe.cpp:501] detection_eval = 0.0353602
-I0511 11:49:27.155102  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.155105  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155109  4597 caffe.cpp:501] detection_eval = 3.57056
-I0511 11:49:27.155113  4597 caffe.cpp:501] detection_eval = 12.8649
-I0511 11:49:27.155117  4597 caffe.cpp:501] detection_eval = 0.0339189
-I0511 11:49:27.155120  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155124  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155128  4597 caffe.cpp:501] detection_eval = 3.5746
-I0511 11:49:27.155131  4597 caffe.cpp:501] detection_eval = 12.877
-I0511 11:49:27.155135  4597 caffe.cpp:501] detection_eval = 0.0349053
-I0511 11:49:27.155139  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155143  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155148  4597 caffe.cpp:501] detection_eval = 3.5746
-I0511 11:49:27.155150  4597 caffe.cpp:501] detection_eval = 12.9294
-I0511 11:49:27.155154  4597 caffe.cpp:501] detection_eval = 0.0316819
-I0511 11:49:27.155158  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155163  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155166  4597 caffe.cpp:501] detection_eval = 3.58669
-I0511 11:49:27.155170  4597 caffe.cpp:501] detection_eval = 12.8327
-I0511 11:49:27.155174  4597 caffe.cpp:501] detection_eval = 0.0345945
-I0511 11:49:27.155177  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155181  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155185  4597 caffe.cpp:501] detection_eval = 3.58669
-I0511 11:49:27.155189  4597 caffe.cpp:501] detection_eval = 12.9254
-I0511 11:49:27.155192  4597 caffe.cpp:501] detection_eval = 0.0364048
-I0511 11:49:27.155196  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155200  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155203  4597 caffe.cpp:501] detection_eval = 3.59476
-I0511 11:49:27.155207  4597 caffe.cpp:501] detection_eval = 12.871
-I0511 11:49:27.155211  4597 caffe.cpp:501] detection_eval = 0.0391323
-I0511 11:49:27.155215  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155218  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155222  4597 caffe.cpp:501] detection_eval = 3.59677
-I0511 11:49:27.155226  4597 caffe.cpp:501] detection_eval = 12.9194
-I0511 11:49:27.155230  4597 caffe.cpp:501] detection_eval = 0.0375311
-I0511 11:49:27.155233  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155237  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155241  4597 caffe.cpp:501] detection_eval = 3.60081
-I0511 11:49:27.155246  4597 caffe.cpp:501] detection_eval = 12.9294
-I0511 11:49:27.155249  4597 caffe.cpp:501] detection_eval = 0.0343586
-I0511 11:49:27.155256  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.155261  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155264  4597 caffe.cpp:501] detection_eval = 3.60685
-I0511 11:49:27.155268  4597 caffe.cpp:501] detection_eval = 12.9556
-I0511 11:49:27.155272  4597 caffe.cpp:501] detection_eval = 0.0430812
-I0511 11:49:27.155275  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155279  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155283  4597 caffe.cpp:501] detection_eval = 3.60685
-I0511 11:49:27.155287  4597 caffe.cpp:501] detection_eval = 13.0423
-I0511 11:49:27.155292  4597 caffe.cpp:501] detection_eval = 0.0405538
-I0511 11:49:27.155295  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155298  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155303  4597 caffe.cpp:501] detection_eval = 3.60887
-I0511 11:49:27.155306  4597 caffe.cpp:501] detection_eval = 13.0887
-I0511 11:49:27.155310  4597 caffe.cpp:501] detection_eval = 0.0370188
-I0511 11:49:27.155314  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155318  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155321  4597 caffe.cpp:501] detection_eval = 3.60887
-I0511 11:49:27.155325  4597 caffe.cpp:501] detection_eval = 13.1815
-I0511 11:49:27.155329  4597 caffe.cpp:501] detection_eval = 0.0410786
-I0511 11:49:27.155333  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155336  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155340  4597 caffe.cpp:501] detection_eval = 3.61089
-I0511 11:49:27.155344  4597 caffe.cpp:501] detection_eval = 13.2621
-I0511 11:49:27.155347  4597 caffe.cpp:501] detection_eval = 0.0463212
-I0511 11:49:27.155351  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155355  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155359  4597 caffe.cpp:501] detection_eval = 3.6129
-I0511 11:49:27.155364  4597 caffe.cpp:501] detection_eval = 13.3407
-I0511 11:49:27.155367  4597 caffe.cpp:501] detection_eval = 0.044323
-I0511 11:49:27.155371  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155375  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155378  4597 caffe.cpp:501] detection_eval = 3.625
-I0511 11:49:27.155382  4597 caffe.cpp:501] detection_eval = 13.2762
-I0511 11:49:27.155386  4597 caffe.cpp:501] detection_eval = 0.0458902
-I0511 11:49:27.155390  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155395  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.155398  4597 caffe.cpp:501] detection_eval = 3.625
-I0511 11:49:27.155402  4597 caffe.cpp:501] detection_eval = 13.4234
-I0511 11:49:27.155406  4597 caffe.cpp:501] detection_eval = 0.0362259
-I0511 11:49:27.155409  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155413  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155417  4597 caffe.cpp:501] detection_eval = 3.62702
-I0511 11:49:27.155421  4597 caffe.cpp:501] detection_eval = 13.5222
-I0511 11:49:27.155426  4597 caffe.cpp:501] detection_eval = 0.0388758
-I0511 11:49:27.155428  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155432  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155436  4597 caffe.cpp:501] detection_eval = 3.62903
-I0511 11:49:27.155441  4597 caffe.cpp:501] detection_eval = 13.6331
-I0511 11:49:27.155444  4597 caffe.cpp:501] detection_eval = 0.0345768
-I0511 11:49:27.155447  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155452  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155454  4597 caffe.cpp:501] detection_eval = 3.63508
-I0511 11:49:27.155458  4597 caffe.cpp:501] detection_eval = 13.7056
-I0511 11:49:27.155462  4597 caffe.cpp:501] detection_eval = 0.0406952
-I0511 11:49:27.155467  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155470  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155474  4597 caffe.cpp:501] detection_eval = 3.6371
-I0511 11:49:27.155478  4597 caffe.cpp:501] detection_eval = 13.8649
-I0511 11:49:27.155485  4597 caffe.cpp:501] detection_eval = 0.0384295
-I0511 11:49:27.155489  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155493  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155498  4597 caffe.cpp:501] detection_eval = 3.64315
-I0511 11:49:27.155501  4597 caffe.cpp:501] detection_eval = 14.0081
-I0511 11:49:27.155505  4597 caffe.cpp:501] detection_eval = 0.0350933
-I0511 11:49:27.155509  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155513  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155516  4597 caffe.cpp:501] detection_eval = 4.11694
-I0511 11:49:27.155520  4597 caffe.cpp:501] detection_eval = 7.05847
-I0511 11:49:27.155524  4597 caffe.cpp:501] detection_eval = 0.0858396
-I0511 11:49:27.155527  4597 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:49:27.155531  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.155535  4597 caffe.cpp:501] detection_eval = 4.11895
-I0511 11:49:27.155539  4597 caffe.cpp:501] detection_eval = 7.24395
-I0511 11:49:27.155544  4597 caffe.cpp:501] detection_eval = 0.0593276
-I0511 11:49:27.155547  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.155550  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.155555  4597 caffe.cpp:501] detection_eval = 4.12097
-I0511 11:49:27.155558  4597 caffe.cpp:501] detection_eval = 7.36895
-I0511 11:49:27.155562  4597 caffe.cpp:501] detection_eval = 0.0512497
-I0511 11:49:27.155565  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.155570  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.155573  4597 caffe.cpp:501] detection_eval = 4.12298
-I0511 11:49:27.155577  4597 caffe.cpp:501] detection_eval = 7.46976
-I0511 11:49:27.155581  4597 caffe.cpp:501] detection_eval = 0.0515406
-I0511 11:49:27.155584  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155588  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.155592  4597 caffe.cpp:501] detection_eval = 4.125
-I0511 11:49:27.155596  4597 caffe.cpp:501] detection_eval = 7.57661
-I0511 11:49:27.155599  4597 caffe.cpp:501] detection_eval = 0.0499778
-I0511 11:49:27.155603  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155607  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.155611  4597 caffe.cpp:501] detection_eval = 4.12702
-I0511 11:49:27.155614  4597 caffe.cpp:501] detection_eval = 7.63911
-I0511 11:49:27.155618  4597 caffe.cpp:501] detection_eval = 0.0468457
-I0511 11:49:27.155622  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.155625  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155629  4597 caffe.cpp:501] detection_eval = 4.12903
-I0511 11:49:27.155633  4597 caffe.cpp:501] detection_eval = 7.69758
-I0511 11:49:27.155637  4597 caffe.cpp:501] detection_eval = 0.0444881
-I0511 11:49:27.155640  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155644  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155648  4597 caffe.cpp:501] detection_eval = 4.13508
-I0511 11:49:27.155652  4597 caffe.cpp:501] detection_eval = 7.67137
-I0511 11:49:27.155655  4597 caffe.cpp:501] detection_eval = 0.0415724
-I0511 11:49:27.155659  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155663  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155668  4597 caffe.cpp:501] detection_eval = 4.13911
-I0511 11:49:27.155671  4597 caffe.cpp:501] detection_eval = 7.67944
-I0511 11:49:27.155675  4597 caffe.cpp:501] detection_eval = 0.0446926
-I0511 11:49:27.155678  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.155683  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.155686  4597 caffe.cpp:501] detection_eval = 4.14113
-I0511 11:49:27.155690  4597 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:49:27.155694  4597 caffe.cpp:501] detection_eval = 0.0431846
-I0511 11:49:27.155697  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.155701  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155705  4597 caffe.cpp:501] detection_eval = 4.14113
-I0511 11:49:27.155714  4597 caffe.cpp:501] detection_eval = 7.82863
-I0511 11:49:27.155717  4597 caffe.cpp:501] detection_eval = 0.041058
-I0511 11:49:27.155721  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155725  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155728  4597 caffe.cpp:501] detection_eval = 4.14718
-I0511 11:49:27.155732  4597 caffe.cpp:501] detection_eval = 7.83871
-I0511 11:49:27.155736  4597 caffe.cpp:501] detection_eval = 0.0447293
-I0511 11:49:27.155740  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155743  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155747  4597 caffe.cpp:501] detection_eval = 4.14718
-I0511 11:49:27.155751  4597 caffe.cpp:501] detection_eval = 7.92137
-I0511 11:49:27.155755  4597 caffe.cpp:501] detection_eval = 0.0416813
-I0511 11:49:27.155758  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.155762  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.155766  4597 caffe.cpp:501] detection_eval = 4.15323
-I0511 11:49:27.155771  4597 caffe.cpp:501] detection_eval = 7.92339
-I0511 11:49:27.155773  4597 caffe.cpp:501] detection_eval = 0.0464219
-I0511 11:49:27.155777  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155781  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.155786  4597 caffe.cpp:501] detection_eval = 4.15524
-I0511 11:49:27.155788  4597 caffe.cpp:501] detection_eval = 7.9496
-I0511 11:49:27.155792  4597 caffe.cpp:501] detection_eval = 0.0425792
-I0511 11:49:27.155797  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155800  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.155804  4597 caffe.cpp:501] detection_eval = 4.15726
-I0511 11:49:27.155807  4597 caffe.cpp:501] detection_eval = 7.98992
-I0511 11:49:27.155812  4597 caffe.cpp:501] detection_eval = 0.0450335
-I0511 11:49:27.155815  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155819  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155823  4597 caffe.cpp:501] detection_eval = 4.15927
-I0511 11:49:27.155827  4597 caffe.cpp:501] detection_eval = 8.0504
-I0511 11:49:27.155831  4597 caffe.cpp:501] detection_eval = 0.0480609
-I0511 11:49:27.155835  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155839  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155843  4597 caffe.cpp:501] detection_eval = 4.15927
-I0511 11:49:27.155846  4597 caffe.cpp:501] detection_eval = 8.11089
-I0511 11:49:27.155850  4597 caffe.cpp:501] detection_eval = 0.0410535
-I0511 11:49:27.155854  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.155858  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.155861  4597 caffe.cpp:501] detection_eval = 4.16129
-I0511 11:49:27.155865  4597 caffe.cpp:501] detection_eval = 8.14516
-I0511 11:49:27.155869  4597 caffe.cpp:501] detection_eval = 0.0408988
-I0511 11:49:27.155872  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.155876  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.155880  4597 caffe.cpp:501] detection_eval = 4.16129
-I0511 11:49:27.155884  4597 caffe.cpp:501] detection_eval = 8.19153
-I0511 11:49:27.155887  4597 caffe.cpp:501] detection_eval = 0.0385151
-I0511 11:49:27.155891  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.155895  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.155899  4597 caffe.cpp:501] detection_eval = 4.16331
-I0511 11:49:27.155902  4597 caffe.cpp:501] detection_eval = 8.21774
-I0511 11:49:27.155906  4597 caffe.cpp:501] detection_eval = 0.0343173
-I0511 11:49:27.155910  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155913  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.155917  4597 caffe.cpp:501] detection_eval = 4.16331
-I0511 11:49:27.155921  4597 caffe.cpp:501] detection_eval = 8.30242
-I0511 11:49:27.155925  4597 caffe.cpp:501] detection_eval = 0.0414283
-I0511 11:49:27.155930  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155933  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.155937  4597 caffe.cpp:501] detection_eval = 4.16935
-I0511 11:49:27.155944  4597 caffe.cpp:501] detection_eval = 8.32661
-I0511 11:49:27.155948  4597 caffe.cpp:501] detection_eval = 0.0370563
-I0511 11:49:27.155952  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.155956  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.155961  4597 caffe.cpp:501] detection_eval = 4.17944
-I0511 11:49:27.155963  4597 caffe.cpp:501] detection_eval = 8.22177
-I0511 11:49:27.155967  4597 caffe.cpp:501] detection_eval = 0.039177
-I0511 11:49:27.155972  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.155975  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.155979  4597 caffe.cpp:501] detection_eval = 4.18145
-I0511 11:49:27.155982  4597 caffe.cpp:501] detection_eval = 8.27823
-I0511 11:49:27.155987  4597 caffe.cpp:501] detection_eval = 0.0412711
-I0511 11:49:27.155992  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.155995  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.155999  4597 caffe.cpp:501] detection_eval = 4.18145
-I0511 11:49:27.156003  4597 caffe.cpp:501] detection_eval = 8.38105
-I0511 11:49:27.156008  4597 caffe.cpp:501] detection_eval = 0.0424748
-I0511 11:49:27.156010  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156014  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156018  4597 caffe.cpp:501] detection_eval = 4.18952
-I0511 11:49:27.156023  4597 caffe.cpp:501] detection_eval = 8.30444
-I0511 11:49:27.156026  4597 caffe.cpp:501] detection_eval = 0.0459202
-I0511 11:49:27.156030  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156034  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156038  4597 caffe.cpp:501] detection_eval = 4.19153
-I0511 11:49:27.156041  4597 caffe.cpp:501] detection_eval = 8.34073
-I0511 11:49:27.156045  4597 caffe.cpp:501] detection_eval = 0.0432066
-I0511 11:49:27.156049  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.156052  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.156056  4597 caffe.cpp:501] detection_eval = 4.19556
-I0511 11:49:27.156060  4597 caffe.cpp:501] detection_eval = 8.39315
-I0511 11:49:27.156064  4597 caffe.cpp:501] detection_eval = 0.0417494
-I0511 11:49:27.156067  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156071  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156075  4597 caffe.cpp:501] detection_eval = 4.19556
-I0511 11:49:27.156078  4597 caffe.cpp:501] detection_eval = 8.43952
-I0511 11:49:27.156082  4597 caffe.cpp:501] detection_eval = 0.0404347
-I0511 11:49:27.156086  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156090  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156093  4597 caffe.cpp:501] detection_eval = 4.19758
-I0511 11:49:27.156097  4597 caffe.cpp:501] detection_eval = 8.49798
-I0511 11:49:27.156101  4597 caffe.cpp:501] detection_eval = 0.0408992
-I0511 11:49:27.156105  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.156110  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156113  4597 caffe.cpp:501] detection_eval = 4.19758
-I0511 11:49:27.156116  4597 caffe.cpp:501] detection_eval = 8.54839
-I0511 11:49:27.156121  4597 caffe.cpp:501] detection_eval = 0.0413191
-I0511 11:49:27.156124  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156127  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156131  4597 caffe.cpp:501] detection_eval = 4.1996
-I0511 11:49:27.156136  4597 caffe.cpp:501] detection_eval = 8.60685
-I0511 11:49:27.156139  4597 caffe.cpp:501] detection_eval = 0.0435699
-I0511 11:49:27.156143  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156147  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156150  4597 caffe.cpp:501] detection_eval = 4.1996
-I0511 11:49:27.156154  4597 caffe.cpp:501] detection_eval = 8.66532
-I0511 11:49:27.156158  4597 caffe.cpp:501] detection_eval = 0.0383632
-I0511 11:49:27.156162  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156167  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156173  4597 caffe.cpp:501] detection_eval = 4.20363
-I0511 11:49:27.156178  4597 caffe.cpp:501] detection_eval = 8.6754
-I0511 11:49:27.156183  4597 caffe.cpp:501] detection_eval = 0.0404755
-I0511 11:49:27.156185  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156189  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156193  4597 caffe.cpp:501] detection_eval = 4.20565
-I0511 11:49:27.156198  4597 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:49:27.156200  4597 caffe.cpp:501] detection_eval = 0.0379169
-I0511 11:49:27.156204  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156208  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156213  4597 caffe.cpp:501] detection_eval = 4.20766
-I0511 11:49:27.156216  4597 caffe.cpp:501] detection_eval = 8.7379
-I0511 11:49:27.156219  4597 caffe.cpp:501] detection_eval = 0.0388246
-I0511 11:49:27.156224  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156227  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156231  4597 caffe.cpp:501] detection_eval = 4.21169
-I0511 11:49:27.156234  4597 caffe.cpp:501] detection_eval = 8.77419
-I0511 11:49:27.156239  4597 caffe.cpp:501] detection_eval = 0.0443882
-I0511 11:49:27.156242  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156246  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156250  4597 caffe.cpp:501] detection_eval = 4.21371
-I0511 11:49:27.156255  4597 caffe.cpp:501] detection_eval = 8.84677
-I0511 11:49:27.156257  4597 caffe.cpp:501] detection_eval = 0.0414387
-I0511 11:49:27.156261  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156265  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156270  4597 caffe.cpp:501] detection_eval = 4.21573
-I0511 11:49:27.156272  4597 caffe.cpp:501] detection_eval = 8.87702
-I0511 11:49:27.156276  4597 caffe.cpp:501] detection_eval = 0.0371307
-I0511 11:49:27.156280  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156285  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.156287  4597 caffe.cpp:501] detection_eval = 4.21573
-I0511 11:49:27.156291  4597 caffe.cpp:501] detection_eval = 8.97984
-I0511 11:49:27.156296  4597 caffe.cpp:501] detection_eval = 0.0383036
-I0511 11:49:27.156298  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156302  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156306  4597 caffe.cpp:501] detection_eval = 4.22177
-I0511 11:49:27.156311  4597 caffe.cpp:501] detection_eval = 8.94758
-I0511 11:49:27.156313  4597 caffe.cpp:501] detection_eval = 0.0437555
-I0511 11:49:27.156317  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156322  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156325  4597 caffe.cpp:501] detection_eval = 4.22379
-I0511 11:49:27.156328  4597 caffe.cpp:501] detection_eval = 9.00605
-I0511 11:49:27.156332  4597 caffe.cpp:501] detection_eval = 0.0451073
-I0511 11:49:27.156337  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156339  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156343  4597 caffe.cpp:501] detection_eval = 4.22984
-I0511 11:49:27.156347  4597 caffe.cpp:501] detection_eval = 9.02218
-I0511 11:49:27.156352  4597 caffe.cpp:501] detection_eval = 0.0392549
-I0511 11:49:27.156354  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156358  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.156363  4597 caffe.cpp:501] detection_eval = 4.23387
-I0511 11:49:27.156366  4597 caffe.cpp:501] detection_eval = 9.04234
-I0511 11:49:27.156370  4597 caffe.cpp:501] detection_eval = 0.0434554
-I0511 11:49:27.156374  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156378  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.156381  4597 caffe.cpp:501] detection_eval = 4.23387
-I0511 11:49:27.156385  4597 caffe.cpp:501] detection_eval = 9.12298
-I0511 11:49:27.156389  4597 caffe.cpp:501] detection_eval = 0.0380915
-I0511 11:49:27.156394  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156397  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156404  4597 caffe.cpp:501] detection_eval = 4.24194
-I0511 11:49:27.156409  4597 caffe.cpp:501] detection_eval = 9.08065
-I0511 11:49:27.156412  4597 caffe.cpp:501] detection_eval = 0.0377101
-I0511 11:49:27.156416  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156420  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.156424  4597 caffe.cpp:501] detection_eval = 4.24597
-I0511 11:49:27.156427  4597 caffe.cpp:501] detection_eval = 9.08065
-I0511 11:49:27.156431  4597 caffe.cpp:501] detection_eval = 0.040412
-I0511 11:49:27.156435  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156438  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.156442  4597 caffe.cpp:501] detection_eval = 4.25403
-I0511 11:49:27.156446  4597 caffe.cpp:501] detection_eval = 9.04032
-I0511 11:49:27.156450  4597 caffe.cpp:501] detection_eval = 0.0430151
-I0511 11:49:27.156453  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156457  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156461  4597 caffe.cpp:501] detection_eval = 4.25403
-I0511 11:49:27.156464  4597 caffe.cpp:501] detection_eval = 9.12097
-I0511 11:49:27.156468  4597 caffe.cpp:501] detection_eval = 0.0423637
-I0511 11:49:27.156472  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156476  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156481  4597 caffe.cpp:501] detection_eval = 4.25605
-I0511 11:49:27.156483  4597 caffe.cpp:501] detection_eval = 9.22581
-I0511 11:49:27.156487  4597 caffe.cpp:501] detection_eval = 0.0471794
-I0511 11:49:27.156491  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156496  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156498  4597 caffe.cpp:501] detection_eval = 4.25605
-I0511 11:49:27.156502  4597 caffe.cpp:501] detection_eval = 9.33871
-I0511 11:49:27.156507  4597 caffe.cpp:501] detection_eval = 0.0446415
-I0511 11:49:27.156510  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156513  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156517  4597 caffe.cpp:501] detection_eval = 4.2621
-I0511 11:49:27.156519  4597 caffe.cpp:501] detection_eval = 9.32863
-I0511 11:49:27.156522  4597 caffe.cpp:501] detection_eval = 0.0452137
-I0511 11:49:27.156533  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.156536  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.156540  4597 caffe.cpp:501] detection_eval = 4.2621
-I0511 11:49:27.156544  4597 caffe.cpp:501] detection_eval = 9.375
-I0511 11:49:27.156548  4597 caffe.cpp:501] detection_eval = 0.0429895
-I0511 11:49:27.156553  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156556  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156559  4597 caffe.cpp:501] detection_eval = 4.26613
-I0511 11:49:27.156563  4597 caffe.cpp:501] detection_eval = 9.40726
-I0511 11:49:27.156565  4597 caffe.cpp:501] detection_eval = 0.0457677
-I0511 11:49:27.156569  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156574  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156576  4597 caffe.cpp:501] detection_eval = 4.26613
-I0511 11:49:27.156580  4597 caffe.cpp:501] detection_eval = 9.48185
-I0511 11:49:27.156584  4597 caffe.cpp:501] detection_eval = 0.0435685
-I0511 11:49:27.156589  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156591  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156595  4597 caffe.cpp:501] detection_eval = 4.27016
-I0511 11:49:27.156599  4597 caffe.cpp:501] detection_eval = 9.48185
-I0511 11:49:27.156602  4597 caffe.cpp:501] detection_eval = 0.038904
-I0511 11:49:27.156606  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.156610  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.156615  4597 caffe.cpp:501] detection_eval = 4.27218
-I0511 11:49:27.156618  4597 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:49:27.156622  4597 caffe.cpp:501] detection_eval = 0.0382874
-I0511 11:49:27.156625  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156633  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.156638  4597 caffe.cpp:501] detection_eval = 4.27621
-I0511 11:49:27.156641  4597 caffe.cpp:501] detection_eval = 9.51411
-I0511 11:49:27.156646  4597 caffe.cpp:501] detection_eval = 0.0401356
-I0511 11:49:27.156649  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156653  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156656  4597 caffe.cpp:501] detection_eval = 4.27823
-I0511 11:49:27.156661  4597 caffe.cpp:501] detection_eval = 9.58669
-I0511 11:49:27.156664  4597 caffe.cpp:501] detection_eval = 0.0485891
-I0511 11:49:27.156668  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.156672  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.156677  4597 caffe.cpp:501] detection_eval = 4.28024
-I0511 11:49:27.156680  4597 caffe.cpp:501] detection_eval = 9.67339
-I0511 11:49:27.156683  4597 caffe.cpp:501] detection_eval = 0.0479873
-I0511 11:49:27.156687  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156692  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156695  4597 caffe.cpp:501] detection_eval = 4.28024
-I0511 11:49:27.156699  4597 caffe.cpp:501] detection_eval = 9.78226
-I0511 11:49:27.156702  4597 caffe.cpp:501] detection_eval = 0.0446545
-I0511 11:49:27.156707  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.156710  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156714  4597 caffe.cpp:501] detection_eval = 4.28226
-I0511 11:49:27.156718  4597 caffe.cpp:501] detection_eval = 9.8246
-I0511 11:49:27.156721  4597 caffe.cpp:501] detection_eval = 0.0395816
-I0511 11:49:27.156725  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156729  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156733  4597 caffe.cpp:501] detection_eval = 4.28629
-I0511 11:49:27.156736  4597 caffe.cpp:501] detection_eval = 9.85081
-I0511 11:49:27.156740  4597 caffe.cpp:501] detection_eval = 0.0462541
-I0511 11:49:27.156744  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156749  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156751  4597 caffe.cpp:501] detection_eval = 4.29234
-I0511 11:49:27.156755  4597 caffe.cpp:501] detection_eval = 9.88911
-I0511 11:49:27.156759  4597 caffe.cpp:501] detection_eval = 0.0437931
-I0511 11:49:27.156762  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156766  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.156770  4597 caffe.cpp:501] detection_eval = 4.29839
-I0511 11:49:27.156774  4597 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:49:27.156777  4597 caffe.cpp:501] detection_eval = 0.0497577
-I0511 11:49:27.156781  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156785  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156788  4597 caffe.cpp:501] detection_eval = 4.3004
-I0511 11:49:27.156792  4597 caffe.cpp:501] detection_eval = 9.97782
-I0511 11:49:27.156796  4597 caffe.cpp:501] detection_eval = 0.0463998
-I0511 11:49:27.156800  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.156805  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156807  4597 caffe.cpp:501] detection_eval = 4.30242
-I0511 11:49:27.156811  4597 caffe.cpp:501] detection_eval = 10.0242
-I0511 11:49:27.156816  4597 caffe.cpp:501] detection_eval = 0.050358
-I0511 11:49:27.156819  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156823  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156828  4597 caffe.cpp:501] detection_eval = 4.30242
-I0511 11:49:27.156832  4597 caffe.cpp:501] detection_eval = 10.1089
-I0511 11:49:27.156836  4597 caffe.cpp:501] detection_eval = 0.042978
-I0511 11:49:27.156841  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.156846  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.156852  4597 caffe.cpp:501] detection_eval = 4.30645
-I0511 11:49:27.156855  4597 caffe.cpp:501] detection_eval = 10.1069
-I0511 11:49:27.156859  4597 caffe.cpp:501] detection_eval = 0.0405982
-I0511 11:49:27.156867  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156872  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.156875  4597 caffe.cpp:501] detection_eval = 4.30847
-I0511 11:49:27.156879  4597 caffe.cpp:501] detection_eval = 10.127
-I0511 11:49:27.156883  4597 caffe.cpp:501] detection_eval = 0.0473988
-I0511 11:49:27.156888  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.156890  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.156894  4597 caffe.cpp:501] detection_eval = 4.30847
-I0511 11:49:27.156898  4597 caffe.cpp:501] detection_eval = 10.1895
-I0511 11:49:27.156903  4597 caffe.cpp:501] detection_eval = 0.039365
-I0511 11:49:27.156906  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.156909  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156913  4597 caffe.cpp:501] detection_eval = 4.3125
-I0511 11:49:27.156918  4597 caffe.cpp:501] detection_eval = 10.2016
-I0511 11:49:27.156921  4597 caffe.cpp:501] detection_eval = 0.0378485
-I0511 11:49:27.156924  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156929  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.156932  4597 caffe.cpp:501] detection_eval = 4.31653
-I0511 11:49:27.156936  4597 caffe.cpp:501] detection_eval = 10.25
-I0511 11:49:27.156940  4597 caffe.cpp:501] detection_eval = 0.0420936
-I0511 11:49:27.156944  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156947  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156951  4597 caffe.cpp:501] detection_eval = 4.3246
-I0511 11:49:27.156955  4597 caffe.cpp:501] detection_eval = 10.246
-I0511 11:49:27.156960  4597 caffe.cpp:501] detection_eval = 0.0418166
-I0511 11:49:27.156962  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.156966  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.156970  4597 caffe.cpp:501] detection_eval = 4.3246
-I0511 11:49:27.156975  4597 caffe.cpp:501] detection_eval = 10.3589
-I0511 11:49:27.156978  4597 caffe.cpp:501] detection_eval = 0.0415671
-I0511 11:49:27.156981  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.156985  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.156989  4597 caffe.cpp:501] detection_eval = 4.33065
-I0511 11:49:27.156993  4597 caffe.cpp:501] detection_eval = 10.4052
-I0511 11:49:27.156997  4597 caffe.cpp:501] detection_eval = 0.046085
-I0511 11:49:27.157001  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.157004  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.157008  4597 caffe.cpp:501] detection_eval = 4.33871
-I0511 11:49:27.157012  4597 caffe.cpp:501] detection_eval = 10.3569
-I0511 11:49:27.157016  4597 caffe.cpp:501] detection_eval = 0.0408102
-I0511 11:49:27.157021  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157023  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157027  4597 caffe.cpp:501] detection_eval = 4.34073
-I0511 11:49:27.157032  4597 caffe.cpp:501] detection_eval = 10.4133
-I0511 11:49:27.157035  4597 caffe.cpp:501] detection_eval = 0.0407476
-I0511 11:49:27.157038  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.157042  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.157047  4597 caffe.cpp:501] detection_eval = 4.34677
-I0511 11:49:27.157050  4597 caffe.cpp:501] detection_eval = 10.4073
-I0511 11:49:27.157054  4597 caffe.cpp:501] detection_eval = 0.0433495
-I0511 11:49:27.157058  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157061  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157065  4597 caffe.cpp:501] detection_eval = 4.35081
-I0511 11:49:27.157069  4597 caffe.cpp:501] detection_eval = 10.4476
-I0511 11:49:27.157073  4597 caffe.cpp:501] detection_eval = 0.0476197
-I0511 11:49:27.157076  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.157080  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.157084  4597 caffe.cpp:501] detection_eval = 4.35484
-I0511 11:49:27.157088  4597 caffe.cpp:501] detection_eval = 10.4637
-I0511 11:49:27.157091  4597 caffe.cpp:501] detection_eval = 0.037921
-I0511 11:49:27.157099  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.157104  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157106  4597 caffe.cpp:501] detection_eval = 4.35887
-I0511 11:49:27.157110  4597 caffe.cpp:501] detection_eval = 10.4435
-I0511 11:49:27.157114  4597 caffe.cpp:501] detection_eval = 0.0372124
-I0511 11:49:27.157119  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157122  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.157125  4597 caffe.cpp:501] detection_eval = 4.3629
-I0511 11:49:27.157130  4597 caffe.cpp:501] detection_eval = 10.4677
-I0511 11:49:27.157133  4597 caffe.cpp:501] detection_eval = 0.0391093
-I0511 11:49:27.157137  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157141  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.157145  4597 caffe.cpp:501] detection_eval = 4.36694
-I0511 11:49:27.157148  4597 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:49:27.157152  4597 caffe.cpp:501] detection_eval = 0.0444606
-I0511 11:49:27.157156  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157160  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157164  4597 caffe.cpp:501] detection_eval = 4.36694
-I0511 11:49:27.157167  4597 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:49:27.157171  4597 caffe.cpp:501] detection_eval = 0.0435741
-I0511 11:49:27.157176  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157179  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157183  4597 caffe.cpp:501] detection_eval = 4.37097
-I0511 11:49:27.157186  4597 caffe.cpp:501] detection_eval = 10.5565
-I0511 11:49:27.157191  4597 caffe.cpp:501] detection_eval = 0.0388593
-I0511 11:49:27.157194  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.157198  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157202  4597 caffe.cpp:501] detection_eval = 4.38105
-I0511 11:49:27.157207  4597 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:49:27.157210  4597 caffe.cpp:501] detection_eval = 0.0413194
-I0511 11:49:27.157213  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157217  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157222  4597 caffe.cpp:501] detection_eval = 4.38306
-I0511 11:49:27.157225  4597 caffe.cpp:501] detection_eval = 10.506
-I0511 11:49:27.157229  4597 caffe.cpp:501] detection_eval = 0.0445081
-I0511 11:49:27.157233  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157236  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157240  4597 caffe.cpp:501] detection_eval = 4.38508
-I0511 11:49:27.157244  4597 caffe.cpp:501] detection_eval = 10.5302
-I0511 11:49:27.157248  4597 caffe.cpp:501] detection_eval = 0.0367612
-I0511 11:49:27.157251  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157254  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157258  4597 caffe.cpp:501] detection_eval = 4.3871
-I0511 11:49:27.157260  4597 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:49:27.157264  4597 caffe.cpp:501] detection_eval = 0.0351988
-I0511 11:49:27.157268  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.157271  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.157275  4597 caffe.cpp:501] detection_eval = 4.39516
-I0511 11:49:27.157279  4597 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:49:27.157284  4597 caffe.cpp:501] detection_eval = 0.0404685
-I0511 11:49:27.157287  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157290  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157294  4597 caffe.cpp:501] detection_eval = 4.39718
-I0511 11:49:27.157299  4597 caffe.cpp:501] detection_eval = 10.623
-I0511 11:49:27.157302  4597 caffe.cpp:501] detection_eval = 0.0424681
-I0511 11:49:27.157306  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157310  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157315  4597 caffe.cpp:501] detection_eval = 4.40121
-I0511 11:49:27.157318  4597 caffe.cpp:501] detection_eval = 10.6815
-I0511 11:49:27.157326  4597 caffe.cpp:501] detection_eval = 0.0430303
-I0511 11:49:27.157330  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157335  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157338  4597 caffe.cpp:501] detection_eval = 4.40323
-I0511 11:49:27.157341  4597 caffe.cpp:501] detection_eval = 10.7298
-I0511 11:49:27.157346  4597 caffe.cpp:501] detection_eval = 0.0459157
-I0511 11:49:27.157349  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157353  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157357  4597 caffe.cpp:501] detection_eval = 4.40323
-I0511 11:49:27.157361  4597 caffe.cpp:501] detection_eval = 10.8004
-I0511 11:49:27.157366  4597 caffe.cpp:501] detection_eval = 0.0444377
-I0511 11:49:27.157368  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157372  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157377  4597 caffe.cpp:501] detection_eval = 4.40927
-I0511 11:49:27.157380  4597 caffe.cpp:501] detection_eval = 10.748
-I0511 11:49:27.157384  4597 caffe.cpp:501] detection_eval = 0.0443802
-I0511 11:49:27.157388  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157392  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157395  4597 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:49:27.157399  4597 caffe.cpp:501] detection_eval = 10.7782
-I0511 11:49:27.157403  4597 caffe.cpp:501] detection_eval = 0.0450336
-I0511 11:49:27.157407  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.157410  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157414  4597 caffe.cpp:501] detection_eval = 4.41331
-I0511 11:49:27.157418  4597 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:49:27.157423  4597 caffe.cpp:501] detection_eval = 0.0419207
-I0511 11:49:27.157426  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.157429  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.157433  4597 caffe.cpp:501] detection_eval = 4.41532
-I0511 11:49:27.157438  4597 caffe.cpp:501] detection_eval = 10.8589
-I0511 11:49:27.157441  4597 caffe.cpp:501] detection_eval = 0.0427965
-I0511 11:49:27.157444  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157449  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157452  4597 caffe.cpp:501] detection_eval = 4.41935
-I0511 11:49:27.157456  4597 caffe.cpp:501] detection_eval = 10.8589
-I0511 11:49:27.157460  4597 caffe.cpp:501] detection_eval = 0.03864
-I0511 11:49:27.157464  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157467  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.157471  4597 caffe.cpp:501] detection_eval = 4.42137
-I0511 11:49:27.157475  4597 caffe.cpp:501] detection_eval = 10.8831
-I0511 11:49:27.157479  4597 caffe.cpp:501] detection_eval = 0.0366291
-I0511 11:49:27.157482  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157486  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157490  4597 caffe.cpp:501] detection_eval = 4.4254
-I0511 11:49:27.157495  4597 caffe.cpp:501] detection_eval = 10.871
-I0511 11:49:27.157497  4597 caffe.cpp:501] detection_eval = 0.0374958
-I0511 11:49:27.157501  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157505  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157510  4597 caffe.cpp:501] detection_eval = 4.43347
-I0511 11:49:27.157512  4597 caffe.cpp:501] detection_eval = 10.8448
-I0511 11:49:27.157516  4597 caffe.cpp:501] detection_eval = 0.0414161
-I0511 11:49:27.157521  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157524  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157528  4597 caffe.cpp:501] detection_eval = 4.4375
-I0511 11:49:27.157532  4597 caffe.cpp:501] detection_eval = 10.879
-I0511 11:49:27.157536  4597 caffe.cpp:501] detection_eval = 0.041688
-I0511 11:49:27.157539  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157543  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.157547  4597 caffe.cpp:501] detection_eval = 4.43952
-I0511 11:49:27.157550  4597 caffe.cpp:501] detection_eval = 10.8911
-I0511 11:49:27.157558  4597 caffe.cpp:501] detection_eval = 0.0408087
-I0511 11:49:27.157562  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157565  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157569  4597 caffe.cpp:501] detection_eval = 4.44153
-I0511 11:49:27.157573  4597 caffe.cpp:501] detection_eval = 10.9335
-I0511 11:49:27.157577  4597 caffe.cpp:501] detection_eval = 0.0434129
-I0511 11:49:27.157582  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157584  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157588  4597 caffe.cpp:501] detection_eval = 4.44355
-I0511 11:49:27.157593  4597 caffe.cpp:501] detection_eval = 10.9637
-I0511 11:49:27.157596  4597 caffe.cpp:501] detection_eval = 0.0448603
-I0511 11:49:27.157600  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157603  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157608  4597 caffe.cpp:501] detection_eval = 4.4496
-I0511 11:49:27.157611  4597 caffe.cpp:501] detection_eval = 10.9819
-I0511 11:49:27.157615  4597 caffe.cpp:501] detection_eval = 0.0455613
-I0511 11:49:27.157619  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157622  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.157626  4597 caffe.cpp:501] detection_eval = 4.45161
-I0511 11:49:27.157631  4597 caffe.cpp:501] detection_eval = 11.0585
-I0511 11:49:27.157635  4597 caffe.cpp:501] detection_eval = 0.0437468
-I0511 11:49:27.157639  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157642  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157647  4597 caffe.cpp:501] detection_eval = 4.45565
-I0511 11:49:27.157650  4597 caffe.cpp:501] detection_eval = 11.0867
-I0511 11:49:27.157655  4597 caffe.cpp:501] detection_eval = 0.041675
-I0511 11:49:27.157658  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157662  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157666  4597 caffe.cpp:501] detection_eval = 4.45565
-I0511 11:49:27.157670  4597 caffe.cpp:501] detection_eval = 11.1613
-I0511 11:49:27.157675  4597 caffe.cpp:501] detection_eval = 0.046394
-I0511 11:49:27.157678  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157682  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.157685  4597 caffe.cpp:501] detection_eval = 4.45766
-I0511 11:49:27.157690  4597 caffe.cpp:501] detection_eval = 11.1956
-I0511 11:49:27.157693  4597 caffe.cpp:501] detection_eval = 0.0452438
-I0511 11:49:27.157697  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.157701  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157704  4597 caffe.cpp:501] detection_eval = 4.45968
-I0511 11:49:27.157708  4597 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:49:27.157712  4597 caffe.cpp:501] detection_eval = 0.0494338
-I0511 11:49:27.157716  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.157721  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.157723  4597 caffe.cpp:501] detection_eval = 4.46371
-I0511 11:49:27.157727  4597 caffe.cpp:501] detection_eval = 11.2944
-I0511 11:49:27.157732  4597 caffe.cpp:501] detection_eval = 0.0407226
-I0511 11:49:27.157735  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157738  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157742  4597 caffe.cpp:501] detection_eval = 4.46573
-I0511 11:49:27.157747  4597 caffe.cpp:501] detection_eval = 11.3266
-I0511 11:49:27.157750  4597 caffe.cpp:501] detection_eval = 0.0456388
-I0511 11:49:27.157754  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.157757  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.157761  4597 caffe.cpp:501] detection_eval = 4.46774
-I0511 11:49:27.157765  4597 caffe.cpp:501] detection_eval = 11.4032
-I0511 11:49:27.157769  4597 caffe.cpp:501] detection_eval = 0.048704
-I0511 11:49:27.157773  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157776  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157780  4597 caffe.cpp:501] detection_eval = 4.46774
-I0511 11:49:27.157788  4597 caffe.cpp:501] detection_eval = 11.4556
-I0511 11:49:27.157793  4597 caffe.cpp:501] detection_eval = 0.0452335
-I0511 11:49:27.157796  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157799  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.157804  4597 caffe.cpp:501] detection_eval = 4.46774
-I0511 11:49:27.157807  4597 caffe.cpp:501] detection_eval = 11.5101
-I0511 11:49:27.157811  4597 caffe.cpp:501] detection_eval = 0.0416035
-I0511 11:49:27.157814  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157819  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.157822  4597 caffe.cpp:501] detection_eval = 4.46976
-I0511 11:49:27.157826  4597 caffe.cpp:501] detection_eval = 11.5161
-I0511 11:49:27.157829  4597 caffe.cpp:501] detection_eval = 0.0392881
-I0511 11:49:27.157833  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157837  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157841  4597 caffe.cpp:501] detection_eval = 4.47177
-I0511 11:49:27.157845  4597 caffe.cpp:501] detection_eval = 11.5403
-I0511 11:49:27.157848  4597 caffe.cpp:501] detection_eval = 0.0396965
-I0511 11:49:27.157852  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.157856  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.157860  4597 caffe.cpp:501] detection_eval = 4.47177
-I0511 11:49:27.157863  4597 caffe.cpp:501] detection_eval = 11.5968
-I0511 11:49:27.157867  4597 caffe.cpp:501] detection_eval = 0.0395053
-I0511 11:49:27.157871  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.157876  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157879  4597 caffe.cpp:501] detection_eval = 4.47782
-I0511 11:49:27.157882  4597 caffe.cpp:501] detection_eval = 11.5766
-I0511 11:49:27.157886  4597 caffe.cpp:501] detection_eval = 0.0413298
-I0511 11:49:27.157891  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.157894  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157898  4597 caffe.cpp:501] detection_eval = 4.48185
-I0511 11:49:27.157902  4597 caffe.cpp:501] detection_eval = 11.6008
-I0511 11:49:27.157905  4597 caffe.cpp:501] detection_eval = 0.0437222
-I0511 11:49:27.157909  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157913  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157917  4597 caffe.cpp:501] detection_eval = 4.48589
-I0511 11:49:27.157920  4597 caffe.cpp:501] detection_eval = 11.6835
-I0511 11:49:27.157924  4597 caffe.cpp:501] detection_eval = 0.0432977
-I0511 11:49:27.157928  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.157932  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.157935  4597 caffe.cpp:501] detection_eval = 4.48992
-I0511 11:49:27.157939  4597 caffe.cpp:501] detection_eval = 11.6754
-I0511 11:49:27.157943  4597 caffe.cpp:501] detection_eval = 0.0463204
-I0511 11:49:27.157948  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.157951  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.157954  4597 caffe.cpp:501] detection_eval = 4.49597
-I0511 11:49:27.157958  4597 caffe.cpp:501] detection_eval = 11.7016
-I0511 11:49:27.157963  4597 caffe.cpp:501] detection_eval = 0.0482656
-I0511 11:49:27.157966  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.157969  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.157974  4597 caffe.cpp:501] detection_eval = 4.5
-I0511 11:49:27.157977  4597 caffe.cpp:501] detection_eval = 11.7238
-I0511 11:49:27.157981  4597 caffe.cpp:501] detection_eval = 0.041621
-I0511 11:49:27.157985  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.157989  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.157992  4597 caffe.cpp:501] detection_eval = 4.5
-I0511 11:49:27.157996  4597 caffe.cpp:501] detection_eval = 11.7702
-I0511 11:49:27.158000  4597 caffe.cpp:501] detection_eval = 0.0432754
-I0511 11:49:27.158004  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158007  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158015  4597 caffe.cpp:501] detection_eval = 4.50202
-I0511 11:49:27.158018  4597 caffe.cpp:501] detection_eval = 11.7964
-I0511 11:49:27.158022  4597 caffe.cpp:501] detection_eval = 0.0377137
-I0511 11:49:27.158026  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158030  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.158035  4597 caffe.cpp:501] detection_eval = 4.5121
-I0511 11:49:27.158038  4597 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:49:27.158042  4597 caffe.cpp:501] detection_eval = 0.0383119
-I0511 11:49:27.158046  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158049  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158053  4597 caffe.cpp:501] detection_eval = 4.51411
-I0511 11:49:27.158057  4597 caffe.cpp:501] detection_eval = 11.756
-I0511 11:49:27.158061  4597 caffe.cpp:501] detection_eval = 0.0418753
-I0511 11:49:27.158064  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158068  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158072  4597 caffe.cpp:501] detection_eval = 4.51613
-I0511 11:49:27.158077  4597 caffe.cpp:501] detection_eval = 11.7661
-I0511 11:49:27.158080  4597 caffe.cpp:501] detection_eval = 0.0371328
-I0511 11:49:27.158083  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158087  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158092  4597 caffe.cpp:501] detection_eval = 4.52419
-I0511 11:49:27.158094  4597 caffe.cpp:501] detection_eval = 11.7661
-I0511 11:49:27.158098  4597 caffe.cpp:501] detection_eval = 0.0369458
-I0511 11:49:27.158102  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158107  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158110  4597 caffe.cpp:501] detection_eval = 4.53024
-I0511 11:49:27.158113  4597 caffe.cpp:501] detection_eval = 11.7258
-I0511 11:49:27.158118  4597 caffe.cpp:501] detection_eval = 0.0408371
-I0511 11:49:27.158121  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158125  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158129  4597 caffe.cpp:501] detection_eval = 4.53427
-I0511 11:49:27.158133  4597 caffe.cpp:501] detection_eval = 11.7177
-I0511 11:49:27.158136  4597 caffe.cpp:501] detection_eval = 0.0414977
-I0511 11:49:27.158140  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158144  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158149  4597 caffe.cpp:501] detection_eval = 4.53831
-I0511 11:49:27.158151  4597 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:49:27.158155  4597 caffe.cpp:501] detection_eval = 0.0402817
-I0511 11:49:27.158159  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158164  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158167  4597 caffe.cpp:501] detection_eval = 4.54234
-I0511 11:49:27.158170  4597 caffe.cpp:501] detection_eval = 11.75
-I0511 11:49:27.158174  4597 caffe.cpp:501] detection_eval = 0.0401225
-I0511 11:49:27.158179  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158182  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158186  4597 caffe.cpp:501] detection_eval = 4.55242
-I0511 11:49:27.158190  4597 caffe.cpp:501] detection_eval = 11.6714
-I0511 11:49:27.158193  4597 caffe.cpp:501] detection_eval = 0.0438539
-I0511 11:49:27.158197  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.158201  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.158205  4597 caffe.cpp:501] detection_eval = 4.55242
-I0511 11:49:27.158208  4597 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:49:27.158212  4597 caffe.cpp:501] detection_eval = 0.0411232
-I0511 11:49:27.158216  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158221  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.158224  4597 caffe.cpp:501] detection_eval = 4.55847
-I0511 11:49:27.158228  4597 caffe.cpp:501] detection_eval = 11.6915
-I0511 11:49:27.158232  4597 caffe.cpp:501] detection_eval = 0.0390835
-I0511 11:49:27.158236  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158239  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158248  4597 caffe.cpp:501] detection_eval = 4.56048
-I0511 11:49:27.158252  4597 caffe.cpp:501] detection_eval = 11.7298
-I0511 11:49:27.158257  4597 caffe.cpp:501] detection_eval = 0.0414107
-I0511 11:49:27.158260  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158263  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.158267  4597 caffe.cpp:501] detection_eval = 4.5625
-I0511 11:49:27.158272  4597 caffe.cpp:501] detection_eval = 11.8266
-I0511 11:49:27.158275  4597 caffe.cpp:501] detection_eval = 0.0436668
-I0511 11:49:27.158278  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.158282  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.158287  4597 caffe.cpp:501] detection_eval = 4.57056
-I0511 11:49:27.158290  4597 caffe.cpp:501] detection_eval = 11.7681
-I0511 11:49:27.158293  4597 caffe.cpp:501] detection_eval = 0.0438924
-I0511 11:49:27.158298  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158301  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158305  4597 caffe.cpp:501] detection_eval = 4.57661
-I0511 11:49:27.158308  4597 caffe.cpp:501] detection_eval = 11.7661
-I0511 11:49:27.158313  4597 caffe.cpp:501] detection_eval = 0.0436783
-I0511 11:49:27.158316  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158320  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158324  4597 caffe.cpp:501] detection_eval = 4.57863
-I0511 11:49:27.158329  4597 caffe.cpp:501] detection_eval = 11.8286
-I0511 11:49:27.158331  4597 caffe.cpp:501] detection_eval = 0.0407017
-I0511 11:49:27.158335  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158339  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158344  4597 caffe.cpp:501] detection_eval = 4.57863
-I0511 11:49:27.158347  4597 caffe.cpp:501] detection_eval = 11.9113
-I0511 11:49:27.158351  4597 caffe.cpp:501] detection_eval = 0.0422112
-I0511 11:49:27.158355  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.158358  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.158362  4597 caffe.cpp:501] detection_eval = 4.58065
-I0511 11:49:27.158366  4597 caffe.cpp:501] detection_eval = 11.9435
-I0511 11:49:27.158370  4597 caffe.cpp:501] detection_eval = 0.0365646
-I0511 11:49:27.158375  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.158377  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.158381  4597 caffe.cpp:501] detection_eval = 4.58266
-I0511 11:49:27.158385  4597 caffe.cpp:501] detection_eval = 11.9657
-I0511 11:49:27.158390  4597 caffe.cpp:501] detection_eval = 0.0385419
-I0511 11:49:27.158392  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158396  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158401  4597 caffe.cpp:501] detection_eval = 4.58266
-I0511 11:49:27.158404  4597 caffe.cpp:501] detection_eval = 12.0262
-I0511 11:49:27.158408  4597 caffe.cpp:501] detection_eval = 0.0380468
-I0511 11:49:27.158411  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158416  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158419  4597 caffe.cpp:501] detection_eval = 4.58468
-I0511 11:49:27.158423  4597 caffe.cpp:501] detection_eval = 12.0383
-I0511 11:49:27.158427  4597 caffe.cpp:501] detection_eval = 0.0354415
-I0511 11:49:27.158430  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.158434  4597 caffe.cpp:501] detection_eval = 1
-I0511 11:49:27.158438  4597 caffe.cpp:501] detection_eval = 4.58871
-I0511 11:49:27.158442  4597 caffe.cpp:501] detection_eval = 12.0565
-I0511 11:49:27.158447  4597 caffe.cpp:501] detection_eval = 0.038643
-I0511 11:49:27.158450  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158454  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158458  4597 caffe.cpp:501] detection_eval = 4.59274
-I0511 11:49:27.158463  4597 caffe.cpp:501] detection_eval = 12.0484
-I0511 11:49:27.158466  4597 caffe.cpp:501] detection_eval = 0.0424511
-I0511 11:49:27.158469  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158478  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158483  4597 caffe.cpp:501] detection_eval = 4.59476
-I0511 11:49:27.158486  4597 caffe.cpp:501] detection_eval = 12.119
-I0511 11:49:27.158490  4597 caffe.cpp:501] detection_eval = 0.0386666
-I0511 11:49:27.158493  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158498  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158501  4597 caffe.cpp:501] detection_eval = 4.59476
-I0511 11:49:27.158505  4597 caffe.cpp:501] detection_eval = 12.1673
-I0511 11:49:27.158509  4597 caffe.cpp:501] detection_eval = 0.0433378
-I0511 11:49:27.158514  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158516  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158520  4597 caffe.cpp:501] detection_eval = 4.60081
-I0511 11:49:27.158524  4597 caffe.cpp:501] detection_eval = 12.1512
-I0511 11:49:27.158529  4597 caffe.cpp:501] detection_eval = 0.0410943
-I0511 11:49:27.158531  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158535  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158540  4597 caffe.cpp:501] detection_eval = 4.60685
-I0511 11:49:27.158543  4597 caffe.cpp:501] detection_eval = 12.127
-I0511 11:49:27.158547  4597 caffe.cpp:501] detection_eval = 0.0467994
-I0511 11:49:27.158550  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.158555  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.158558  4597 caffe.cpp:501] detection_eval = 4.61089
-I0511 11:49:27.158562  4597 caffe.cpp:501] detection_eval = 12.0948
-I0511 11:49:27.158566  4597 caffe.cpp:501] detection_eval = 0.043666
-I0511 11:49:27.158569  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158573  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158577  4597 caffe.cpp:501] detection_eval = 4.6129
-I0511 11:49:27.158581  4597 caffe.cpp:501] detection_eval = 12.1109
-I0511 11:49:27.158586  4597 caffe.cpp:501] detection_eval = 0.0420169
-I0511 11:49:27.158589  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158592  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.158596  4597 caffe.cpp:501] detection_eval = 4.6129
-I0511 11:49:27.158601  4597 caffe.cpp:501] detection_eval = 12.1613
-I0511 11:49:27.158604  4597 caffe.cpp:501] detection_eval = 0.036278
-I0511 11:49:27.158608  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158612  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158615  4597 caffe.cpp:501] detection_eval = 4.6129
-I0511 11:49:27.158619  4597 caffe.cpp:501] detection_eval = 12.2137
-I0511 11:49:27.158623  4597 caffe.cpp:501] detection_eval = 0.034748
-I0511 11:49:27.158627  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.158632  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.158634  4597 caffe.cpp:501] detection_eval = 4.61492
-I0511 11:49:27.158638  4597 caffe.cpp:501] detection_eval = 12.256
-I0511 11:49:27.158643  4597 caffe.cpp:501] detection_eval = 0.0388143
-I0511 11:49:27.158646  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158649  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.158653  4597 caffe.cpp:501] detection_eval = 4.62097
-I0511 11:49:27.158658  4597 caffe.cpp:501] detection_eval = 12.2016
-I0511 11:49:27.158661  4597 caffe.cpp:501] detection_eval = 0.0353157
-I0511 11:49:27.158665  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.158668  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.158673  4597 caffe.cpp:501] detection_eval = 4.62298
-I0511 11:49:27.158676  4597 caffe.cpp:501] detection_eval = 12.2137
-I0511 11:49:27.158680  4597 caffe.cpp:501] detection_eval = 0.0340815
-I0511 11:49:27.158684  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158687  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158691  4597 caffe.cpp:501] detection_eval = 4.625
-I0511 11:49:27.158695  4597 caffe.cpp:501] detection_eval = 12.2621
-I0511 11:49:27.158699  4597 caffe.cpp:501] detection_eval = 0.0360302
-I0511 11:49:27.158704  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158710  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158715  4597 caffe.cpp:501] detection_eval = 4.62903
-I0511 11:49:27.158718  4597 caffe.cpp:501] detection_eval = 12.2419
-I0511 11:49:27.158721  4597 caffe.cpp:501] detection_eval = 0.0383883
-I0511 11:49:27.158725  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158730  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158733  4597 caffe.cpp:501] detection_eval = 4.63508
-I0511 11:49:27.158736  4597 caffe.cpp:501] detection_eval = 12.1794
-I0511 11:49:27.158740  4597 caffe.cpp:501] detection_eval = 0.0369931
-I0511 11:49:27.158744  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158748  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158752  4597 caffe.cpp:501] detection_eval = 4.63508
-I0511 11:49:27.158756  4597 caffe.cpp:501] detection_eval = 12.2137
-I0511 11:49:27.158759  4597 caffe.cpp:501] detection_eval = 0.0361574
-I0511 11:49:27.158763  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.158767  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158771  4597 caffe.cpp:501] detection_eval = 4.64113
-I0511 11:49:27.158774  4597 caffe.cpp:501] detection_eval = 12.1915
-I0511 11:49:27.158778  4597 caffe.cpp:501] detection_eval = 0.0395487
-I0511 11:49:27.158782  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158787  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158790  4597 caffe.cpp:501] detection_eval = 4.64315
-I0511 11:49:27.158793  4597 caffe.cpp:501] detection_eval = 12.2379
-I0511 11:49:27.158797  4597 caffe.cpp:501] detection_eval = 0.0375797
-I0511 11:49:27.158802  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158805  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158809  4597 caffe.cpp:501] detection_eval = 4.64919
-I0511 11:49:27.158812  4597 caffe.cpp:501] detection_eval = 12.2056
-I0511 11:49:27.158816  4597 caffe.cpp:501] detection_eval = 0.0351078
-I0511 11:49:27.158820  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.158824  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.158828  4597 caffe.cpp:501] detection_eval = 4.64919
-I0511 11:49:27.158831  4597 caffe.cpp:501] detection_eval = 12.244
-I0511 11:49:27.158835  4597 caffe.cpp:501] detection_eval = 0.0342402
-I0511 11:49:27.158839  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158843  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.158848  4597 caffe.cpp:501] detection_eval = 4.65323
-I0511 11:49:27.158851  4597 caffe.cpp:501] detection_eval = 12.2379
-I0511 11:49:27.158855  4597 caffe.cpp:501] detection_eval = 0.033903
-I0511 11:49:27.158859  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158862  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.158866  4597 caffe.cpp:501] detection_eval = 4.65726
-I0511 11:49:27.158870  4597 caffe.cpp:501] detection_eval = 12.2177
-I0511 11:49:27.158874  4597 caffe.cpp:501] detection_eval = 0.0364475
-I0511 11:49:27.158879  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.158881  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158885  4597 caffe.cpp:501] detection_eval = 4.65927
-I0511 11:49:27.158890  4597 caffe.cpp:501] detection_eval = 12.252
-I0511 11:49:27.158893  4597 caffe.cpp:501] detection_eval = 0.0357001
-I0511 11:49:27.158896  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158900  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.158905  4597 caffe.cpp:501] detection_eval = 4.66532
-I0511 11:49:27.158908  4597 caffe.cpp:501] detection_eval = 12.2601
-I0511 11:49:27.158912  4597 caffe.cpp:501] detection_eval = 0.0393888
-I0511 11:49:27.158916  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.158921  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.158923  4597 caffe.cpp:501] detection_eval = 4.67137
-I0511 11:49:27.158927  4597 caffe.cpp:501] detection_eval = 12.2399
-I0511 11:49:27.158931  4597 caffe.cpp:501] detection_eval = 0.038015
-I0511 11:49:27.158938  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.158943  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.158946  4597 caffe.cpp:501] detection_eval = 4.67339
-I0511 11:49:27.158951  4597 caffe.cpp:501] detection_eval = 12.2883
-I0511 11:49:27.158954  4597 caffe.cpp:501] detection_eval = 0.0386486
-I0511 11:49:27.158958  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.158962  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.158965  4597 caffe.cpp:501] detection_eval = 4.67339
-I0511 11:49:27.158969  4597 caffe.cpp:501] detection_eval = 12.4335
-I0511 11:49:27.158973  4597 caffe.cpp:501] detection_eval = 0.0465097
-I0511 11:49:27.158977  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.158982  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.158984  4597 caffe.cpp:501] detection_eval = 4.67742
-I0511 11:49:27.158988  4597 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:49:27.158993  4597 caffe.cpp:501] detection_eval = 0.0369663
-I0511 11:49:27.158996  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.159000  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159004  4597 caffe.cpp:501] detection_eval = 4.68145
-I0511 11:49:27.159008  4597 caffe.cpp:501] detection_eval = 12.4032
-I0511 11:49:27.159011  4597 caffe.cpp:501] detection_eval = 0.042946
-I0511 11:49:27.159015  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159019  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.159024  4597 caffe.cpp:501] detection_eval = 4.68347
-I0511 11:49:27.159026  4597 caffe.cpp:501] detection_eval = 12.4113
-I0511 11:49:27.159030  4597 caffe.cpp:501] detection_eval = 0.0351064
-I0511 11:49:27.159034  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.159039  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.159042  4597 caffe.cpp:501] detection_eval = 4.69556
-I0511 11:49:27.159045  4597 caffe.cpp:501] detection_eval = 12.3105
-I0511 11:49:27.159049  4597 caffe.cpp:501] detection_eval = 0.0371418
-I0511 11:49:27.159054  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.159057  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159060  4597 caffe.cpp:501] detection_eval = 4.69556
-I0511 11:49:27.159065  4597 caffe.cpp:501] detection_eval = 12.3972
-I0511 11:49:27.159068  4597 caffe.cpp:501] detection_eval = 0.0421836
-I0511 11:49:27.159072  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159076  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159080  4597 caffe.cpp:501] detection_eval = 4.70161
-I0511 11:49:27.159083  4597 caffe.cpp:501] detection_eval = 12.3952
-I0511 11:49:27.159087  4597 caffe.cpp:501] detection_eval = 0.0421523
-I0511 11:49:27.159091  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159096  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.159098  4597 caffe.cpp:501] detection_eval = 4.70766
-I0511 11:49:27.159102  4597 caffe.cpp:501] detection_eval = 12.4012
-I0511 11:49:27.159106  4597 caffe.cpp:501] detection_eval = 0.0440006
-I0511 11:49:27.159111  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159114  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159117  4597 caffe.cpp:501] detection_eval = 4.70968
-I0511 11:49:27.159121  4597 caffe.cpp:501] detection_eval = 12.4375
-I0511 11:49:27.159126  4597 caffe.cpp:501] detection_eval = 0.0413539
-I0511 11:49:27.159129  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159133  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159137  4597 caffe.cpp:501] detection_eval = 4.71573
-I0511 11:49:27.159140  4597 caffe.cpp:501] detection_eval = 12.4214
-I0511 11:49:27.159144  4597 caffe.cpp:501] detection_eval = 0.0441704
-I0511 11:49:27.159148  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159152  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.159157  4597 caffe.cpp:501] detection_eval = 4.71573
-I0511 11:49:27.159159  4597 caffe.cpp:501] detection_eval = 12.5181
-I0511 11:49:27.159166  4597 caffe.cpp:501] detection_eval = 0.0440508
-I0511 11:49:27.159170  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.159174  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159178  4597 caffe.cpp:501] detection_eval = 4.71573
-I0511 11:49:27.159183  4597 caffe.cpp:501] detection_eval = 12.5887
-I0511 11:49:27.159186  4597 caffe.cpp:501] detection_eval = 0.0436599
-I0511 11:49:27.159189  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.159193  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159198  4597 caffe.cpp:501] detection_eval = 4.71573
-I0511 11:49:27.159201  4597 caffe.cpp:501] detection_eval = 12.6956
-I0511 11:49:27.159205  4597 caffe.cpp:501] detection_eval = 0.0428629
-I0511 11:49:27.159209  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159212  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159216  4597 caffe.cpp:501] detection_eval = 4.71976
-I0511 11:49:27.159219  4597 caffe.cpp:501] detection_eval = 12.7581
-I0511 11:49:27.159224  4597 caffe.cpp:501] detection_eval = 0.0448693
-I0511 11:49:27.159227  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.159231  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.159235  4597 caffe.cpp:501] detection_eval = 4.72177
-I0511 11:49:27.159238  4597 caffe.cpp:501] detection_eval = 12.8407
-I0511 11:49:27.159242  4597 caffe.cpp:501] detection_eval = 0.0433908
-I0511 11:49:27.159246  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.159250  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.159255  4597 caffe.cpp:501] detection_eval = 4.73589
-I0511 11:49:27.159257  4597 caffe.cpp:501] detection_eval = 12.7036
-I0511 11:49:27.159262  4597 caffe.cpp:501] detection_eval = 0.0435141
-I0511 11:49:27.159266  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159271  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.159273  4597 caffe.cpp:501] detection_eval = 4.7379
-I0511 11:49:27.159277  4597 caffe.cpp:501] detection_eval = 12.7964
-I0511 11:49:27.159281  4597 caffe.cpp:501] detection_eval = 0.0428964
-I0511 11:49:27.159286  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159288  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159292  4597 caffe.cpp:501] detection_eval = 4.73992
-I0511 11:49:27.159296  4597 caffe.cpp:501] detection_eval = 12.8569
-I0511 11:49:27.159301  4597 caffe.cpp:501] detection_eval = 0.0450329
-I0511 11:49:27.159303  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159307  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159312  4597 caffe.cpp:501] detection_eval = 4.74194
-I0511 11:49:27.159315  4597 caffe.cpp:501] detection_eval = 12.9657
-I0511 11:49:27.159319  4597 caffe.cpp:501] detection_eval = 0.0397115
-I0511 11:49:27.159322  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159327  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159330  4597 caffe.cpp:501] detection_eval = 4.75
-I0511 11:49:27.159333  4597 caffe.cpp:501] detection_eval = 12.996
-I0511 11:49:27.159337  4597 caffe.cpp:501] detection_eval = 0.0457237
-I0511 11:49:27.159341  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.159345  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.159349  4597 caffe.cpp:501] detection_eval = 4.75202
-I0511 11:49:27.159353  4597 caffe.cpp:501] detection_eval = 13.1593
-I0511 11:49:27.159356  4597 caffe.cpp:501] detection_eval = 0.0419493
-I0511 11:49:27.159360  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159364  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.159368  4597 caffe.cpp:501] detection_eval = 4.75605
-I0511 11:49:27.159371  4597 caffe.cpp:501] detection_eval = 13.3488
-I0511 11:49:27.159375  4597 caffe.cpp:501] detection_eval = 0.0408169
-I0511 11:49:27.159379  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.159384  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159386  4597 caffe.cpp:501] detection_eval = 5.14718
-I0511 11:49:27.159390  4597 caffe.cpp:501] detection_eval = 7.51411
-I0511 11:49:27.159397  4597 caffe.cpp:501] detection_eval = 0.0829268
-I0511 11:49:27.159401  4597 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:49:27.159405  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.159409  4597 caffe.cpp:501] detection_eval = 5.14919
-I0511 11:49:27.159413  4597 caffe.cpp:501] detection_eval = 7.66532
-I0511 11:49:27.159417  4597 caffe.cpp:501] detection_eval = 0.0581721
-I0511 11:49:27.159420  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.159425  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.159428  4597 caffe.cpp:501] detection_eval = 5.15323
-I0511 11:49:27.159432  4597 caffe.cpp:501] detection_eval = 7.77218
-I0511 11:49:27.159435  4597 caffe.cpp:501] detection_eval = 0.0568789
-I0511 11:49:27.159440  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.159443  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.159446  4597 caffe.cpp:501] detection_eval = 5.15726
-I0511 11:49:27.159451  4597 caffe.cpp:501] detection_eval = 7.85484
-I0511 11:49:27.159454  4597 caffe.cpp:501] detection_eval = 0.0504249
-I0511 11:49:27.159457  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159461  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159466  4597 caffe.cpp:501] detection_eval = 5.15927
-I0511 11:49:27.159469  4597 caffe.cpp:501] detection_eval = 7.95766
-I0511 11:49:27.159472  4597 caffe.cpp:501] detection_eval = 0.0588796
-I0511 11:49:27.159476  4597 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:49:27.159481  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.159484  4597 caffe.cpp:501] detection_eval = 5.16129
-I0511 11:49:27.159487  4597 caffe.cpp:501] detection_eval = 7.99597
-I0511 11:49:27.159492  4597 caffe.cpp:501] detection_eval = 0.046715
-I0511 11:49:27.159494  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.159498  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.159502  4597 caffe.cpp:501] detection_eval = 5.16331
-I0511 11:49:27.159507  4597 caffe.cpp:501] detection_eval = 8.06653
-I0511 11:49:27.159509  4597 caffe.cpp:501] detection_eval = 0.0474749
-I0511 11:49:27.159513  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.159518  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.159521  4597 caffe.cpp:501] detection_eval = 5.16935
-I0511 11:49:27.159524  4597 caffe.cpp:501] detection_eval = 8.06452
-I0511 11:49:27.159528  4597 caffe.cpp:501] detection_eval = 0.0424333
-I0511 11:49:27.159533  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159535  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159539  4597 caffe.cpp:501] detection_eval = 5.1754
-I0511 11:49:27.159543  4597 caffe.cpp:501] detection_eval = 8.04435
-I0511 11:49:27.159546  4597 caffe.cpp:501] detection_eval = 0.0414681
-I0511 11:49:27.159550  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.159554  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159559  4597 caffe.cpp:501] detection_eval = 5.17944
-I0511 11:49:27.159562  4597 caffe.cpp:501] detection_eval = 8.0504
-I0511 11:49:27.159566  4597 caffe.cpp:501] detection_eval = 0.0396226
-I0511 11:49:27.159569  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.159574  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159577  4597 caffe.cpp:501] detection_eval = 5.17944
-I0511 11:49:27.159581  4597 caffe.cpp:501] detection_eval = 8.16734
-I0511 11:49:27.159585  4597 caffe.cpp:501] detection_eval = 0.0495915
-I0511 11:49:27.159590  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.159593  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.159596  4597 caffe.cpp:501] detection_eval = 5.18548
-I0511 11:49:27.159600  4597 caffe.cpp:501] detection_eval = 8.11492
-I0511 11:49:27.159605  4597 caffe.cpp:501] detection_eval = 0.0419437
-I0511 11:49:27.159608  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159611  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.159615  4597 caffe.cpp:501] detection_eval = 5.18548
-I0511 11:49:27.159622  4597 caffe.cpp:501] detection_eval = 8.22782
-I0511 11:49:27.159626  4597 caffe.cpp:501] detection_eval = 0.0442945
-I0511 11:49:27.159631  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159634  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159638  4597 caffe.cpp:501] detection_eval = 5.18952
-I0511 11:49:27.159641  4597 caffe.cpp:501] detection_eval = 8.27419
-I0511 11:49:27.159646  4597 caffe.cpp:501] detection_eval = 0.0484873
-I0511 11:49:27.159649  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159653  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159657  4597 caffe.cpp:501] detection_eval = 5.19153
-I0511 11:49:27.159660  4597 caffe.cpp:501] detection_eval = 8.29234
-I0511 11:49:27.159664  4597 caffe.cpp:501] detection_eval = 0.0438324
-I0511 11:49:27.159668  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.159672  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159677  4597 caffe.cpp:501] detection_eval = 5.19355
-I0511 11:49:27.159680  4597 caffe.cpp:501] detection_eval = 8.34073
-I0511 11:49:27.159684  4597 caffe.cpp:501] detection_eval = 0.0407354
-I0511 11:49:27.159688  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.159692  4597 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:49:27.159695  4597 caffe.cpp:501] detection_eval = 5.19758
-I0511 11:49:27.159699  4597 caffe.cpp:501] detection_eval = 8.375
-I0511 11:49:27.159703  4597 caffe.cpp:501] detection_eval = 0.0435065
-I0511 11:49:27.159708  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159710  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159714  4597 caffe.cpp:501] detection_eval = 5.19758
-I0511 11:49:27.159718  4597 caffe.cpp:501] detection_eval = 8.46774
-I0511 11:49:27.159723  4597 caffe.cpp:501] detection_eval = 0.0432391
-I0511 11:49:27.159725  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159729  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.159734  4597 caffe.cpp:501] detection_eval = 5.20161
-I0511 11:49:27.159737  4597 caffe.cpp:501] detection_eval = 8.45968
-I0511 11:49:27.159741  4597 caffe.cpp:501] detection_eval = 0.042085
-I0511 11:49:27.159744  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159749  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159752  4597 caffe.cpp:501] detection_eval = 5.20161
-I0511 11:49:27.159756  4597 caffe.cpp:501] detection_eval = 8.50202
-I0511 11:49:27.159760  4597 caffe.cpp:501] detection_eval = 0.039412
-I0511 11:49:27.159763  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159767  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159771  4597 caffe.cpp:501] detection_eval = 5.20363
-I0511 11:49:27.159775  4597 caffe.cpp:501] detection_eval = 8.53226
-I0511 11:49:27.159778  4597 caffe.cpp:501] detection_eval = 0.0400512
-I0511 11:49:27.159782  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159786  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.159790  4597 caffe.cpp:501] detection_eval = 5.20363
-I0511 11:49:27.159795  4597 caffe.cpp:501] detection_eval = 8.66532
-I0511 11:49:27.159798  4597 caffe.cpp:501] detection_eval = 0.0454019
-I0511 11:49:27.159801  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159806  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159809  4597 caffe.cpp:501] detection_eval = 5.20968
-I0511 11:49:27.159813  4597 caffe.cpp:501] detection_eval = 8.67137
-I0511 11:49:27.159817  4597 caffe.cpp:501] detection_eval = 0.0426998
-I0511 11:49:27.159821  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.159826  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.159828  4597 caffe.cpp:501] detection_eval = 5.22177
-I0511 11:49:27.159832  4597 caffe.cpp:501] detection_eval = 8.5746
-I0511 11:49:27.159837  4597 caffe.cpp:501] detection_eval = 0.0408018
-I0511 11:49:27.159840  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.159844  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.159847  4597 caffe.cpp:501] detection_eval = 5.22379
-I0511 11:49:27.159855  4597 caffe.cpp:501] detection_eval = 8.6754
-I0511 11:49:27.159859  4597 caffe.cpp:501] detection_eval = 0.0395071
-I0511 11:49:27.159863  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.159868  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.159871  4597 caffe.cpp:501] detection_eval = 5.22379
-I0511 11:49:27.159875  4597 caffe.cpp:501] detection_eval = 8.78831
-I0511 11:49:27.159879  4597 caffe.cpp:501] detection_eval = 0.0442783
-I0511 11:49:27.159883  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.159886  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.159890  4597 caffe.cpp:501] detection_eval = 5.23185
-I0511 11:49:27.159894  4597 caffe.cpp:501] detection_eval = 8.75605
-I0511 11:49:27.159898  4597 caffe.cpp:501] detection_eval = 0.0487317
-I0511 11:49:27.159901  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.159905  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.159909  4597 caffe.cpp:501] detection_eval = 5.23589
-I0511 11:49:27.159912  4597 caffe.cpp:501] detection_eval = 8.76613
-I0511 11:49:27.159916  4597 caffe.cpp:501] detection_eval = 0.0466184
-I0511 11:49:27.159920  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159924  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.159927  4597 caffe.cpp:501] detection_eval = 5.2379
-I0511 11:49:27.159931  4597 caffe.cpp:501] detection_eval = 8.8246
-I0511 11:49:27.159935  4597 caffe.cpp:501] detection_eval = 0.0464592
-I0511 11:49:27.159940  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.159943  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159946  4597 caffe.cpp:501] detection_eval = 5.2379
-I0511 11:49:27.159950  4597 caffe.cpp:501] detection_eval = 8.875
-I0511 11:49:27.159955  4597 caffe.cpp:501] detection_eval = 0.0462804
-I0511 11:49:27.159958  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.159961  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.159965  4597 caffe.cpp:501] detection_eval = 5.23992
-I0511 11:49:27.159970  4597 caffe.cpp:501] detection_eval = 8.89516
-I0511 11:49:27.159973  4597 caffe.cpp:501] detection_eval = 0.0449413
-I0511 11:49:27.159976  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.159981  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.159984  4597 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:49:27.159988  4597 caffe.cpp:501] detection_eval = 8.91331
-I0511 11:49:27.159992  4597 caffe.cpp:501] detection_eval = 0.0456006
-I0511 11:49:27.159996  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.159999  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160004  4597 caffe.cpp:501] detection_eval = 5.24798
-I0511 11:49:27.160008  4597 caffe.cpp:501] detection_eval = 8.90927
-I0511 11:49:27.160012  4597 caffe.cpp:501] detection_eval = 0.0439038
-I0511 11:49:27.160015  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160019  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160023  4597 caffe.cpp:501] detection_eval = 5.25
-I0511 11:49:27.160027  4597 caffe.cpp:501] detection_eval = 8.9254
-I0511 11:49:27.160032  4597 caffe.cpp:501] detection_eval = 0.0369752
-I0511 11:49:27.160035  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160039  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160043  4597 caffe.cpp:501] detection_eval = 5.25202
-I0511 11:49:27.160048  4597 caffe.cpp:501] detection_eval = 8.95968
-I0511 11:49:27.160051  4597 caffe.cpp:501] detection_eval = 0.0460111
-I0511 11:49:27.160055  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160059  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160063  4597 caffe.cpp:501] detection_eval = 5.25403
-I0511 11:49:27.160068  4597 caffe.cpp:501] detection_eval = 9.00806
-I0511 11:49:27.160070  4597 caffe.cpp:501] detection_eval = 0.048944
-I0511 11:49:27.160074  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160079  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160087  4597 caffe.cpp:501] detection_eval = 5.25605
-I0511 11:49:27.160092  4597 caffe.cpp:501] detection_eval = 9.06452
-I0511 11:49:27.160096  4597 caffe.cpp:501] detection_eval = 0.0459543
-I0511 11:49:27.160099  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160104  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160107  4597 caffe.cpp:501] detection_eval = 5.25806
-I0511 11:49:27.160111  4597 caffe.cpp:501] detection_eval = 9.07863
-I0511 11:49:27.160115  4597 caffe.cpp:501] detection_eval = 0.041865
-I0511 11:49:27.160118  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160122  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160127  4597 caffe.cpp:501] detection_eval = 5.26008
-I0511 11:49:27.160131  4597 caffe.cpp:501] detection_eval = 9.09476
-I0511 11:49:27.160135  4597 caffe.cpp:501] detection_eval = 0.037409
-I0511 11:49:27.160140  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160143  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160146  4597 caffe.cpp:501] detection_eval = 5.26411
-I0511 11:49:27.160151  4597 caffe.cpp:501] detection_eval = 9.12298
-I0511 11:49:27.160154  4597 caffe.cpp:501] detection_eval = 0.03876
-I0511 11:49:27.160158  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160161  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160166  4597 caffe.cpp:501] detection_eval = 5.26411
-I0511 11:49:27.160169  4597 caffe.cpp:501] detection_eval = 9.21573
-I0511 11:49:27.160173  4597 caffe.cpp:501] detection_eval = 0.0465169
-I0511 11:49:27.160177  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160181  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160184  4597 caffe.cpp:501] detection_eval = 5.27016
-I0511 11:49:27.160188  4597 caffe.cpp:501] detection_eval = 9.21976
-I0511 11:49:27.160192  4597 caffe.cpp:501] detection_eval = 0.0382264
-I0511 11:49:27.160195  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160199  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160203  4597 caffe.cpp:501] detection_eval = 5.27218
-I0511 11:49:27.160207  4597 caffe.cpp:501] detection_eval = 9.27823
-I0511 11:49:27.160210  4597 caffe.cpp:501] detection_eval = 0.0434479
-I0511 11:49:27.160214  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160218  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160223  4597 caffe.cpp:501] detection_eval = 5.27621
-I0511 11:49:27.160225  4597 caffe.cpp:501] detection_eval = 9.30444
-I0511 11:49:27.160229  4597 caffe.cpp:501] detection_eval = 0.0445045
-I0511 11:49:27.160233  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160238  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160240  4597 caffe.cpp:501] detection_eval = 5.28024
-I0511 11:49:27.160244  4597 caffe.cpp:501] detection_eval = 9.31452
-I0511 11:49:27.160248  4597 caffe.cpp:501] detection_eval = 0.0463289
-I0511 11:49:27.160253  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160255  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160259  4597 caffe.cpp:501] detection_eval = 5.28024
-I0511 11:49:27.160264  4597 caffe.cpp:501] detection_eval = 9.39113
-I0511 11:49:27.160267  4597 caffe.cpp:501] detection_eval = 0.0468363
-I0511 11:49:27.160270  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.160274  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.160279  4597 caffe.cpp:501] detection_eval = 5.29032
-I0511 11:49:27.160282  4597 caffe.cpp:501] detection_eval = 9.29435
-I0511 11:49:27.160285  4597 caffe.cpp:501] detection_eval = 0.0425606
-I0511 11:49:27.160290  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160293  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160297  4597 caffe.cpp:501] detection_eval = 5.29435
-I0511 11:49:27.160301  4597 caffe.cpp:501] detection_eval = 9.34879
-I0511 11:49:27.160305  4597 caffe.cpp:501] detection_eval = 0.0420409
-I0511 11:49:27.160308  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160312  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.160320  4597 caffe.cpp:501] detection_eval = 5.30242
-I0511 11:49:27.160323  4597 caffe.cpp:501] detection_eval = 9.31653
-I0511 11:49:27.160327  4597 caffe.cpp:501] detection_eval = 0.0431198
-I0511 11:49:27.160331  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160336  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160338  4597 caffe.cpp:501] detection_eval = 5.30242
-I0511 11:49:27.160342  4597 caffe.cpp:501] detection_eval = 9.44355
-I0511 11:49:27.160346  4597 caffe.cpp:501] detection_eval = 0.0477149
-I0511 11:49:27.160349  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160353  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160357  4597 caffe.cpp:501] detection_eval = 5.30645
-I0511 11:49:27.160362  4597 caffe.cpp:501] detection_eval = 9.46169
-I0511 11:49:27.160365  4597 caffe.cpp:501] detection_eval = 0.0458819
-I0511 11:49:27.160369  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.160372  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.160377  4597 caffe.cpp:501] detection_eval = 5.30847
-I0511 11:49:27.160380  4597 caffe.cpp:501] detection_eval = 9.48992
-I0511 11:49:27.160384  4597 caffe.cpp:501] detection_eval = 0.0415921
-I0511 11:49:27.160387  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160392  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160395  4597 caffe.cpp:501] detection_eval = 5.31452
-I0511 11:49:27.160399  4597 caffe.cpp:501] detection_eval = 9.45565
-I0511 11:49:27.160403  4597 caffe.cpp:501] detection_eval = 0.0413678
-I0511 11:49:27.160406  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160410  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160414  4597 caffe.cpp:501] detection_eval = 5.31452
-I0511 11:49:27.160418  4597 caffe.cpp:501] detection_eval = 9.55847
-I0511 11:49:27.160421  4597 caffe.cpp:501] detection_eval = 0.0407364
-I0511 11:49:27.160425  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.160429  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.160434  4597 caffe.cpp:501] detection_eval = 5.31653
-I0511 11:49:27.160437  4597 caffe.cpp:501] detection_eval = 9.64919
-I0511 11:49:27.160440  4597 caffe.cpp:501] detection_eval = 0.0472103
-I0511 11:49:27.160444  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160449  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160452  4597 caffe.cpp:501] detection_eval = 5.31653
-I0511 11:49:27.160456  4597 caffe.cpp:501] detection_eval = 9.7379
-I0511 11:49:27.160459  4597 caffe.cpp:501] detection_eval = 0.0452346
-I0511 11:49:27.160464  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160467  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160471  4597 caffe.cpp:501] detection_eval = 5.32258
-I0511 11:49:27.160475  4597 caffe.cpp:501] detection_eval = 9.76008
-I0511 11:49:27.160478  4597 caffe.cpp:501] detection_eval = 0.0499323
-I0511 11:49:27.160482  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.160486  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.160490  4597 caffe.cpp:501] detection_eval = 5.3246
-I0511 11:49:27.160495  4597 caffe.cpp:501] detection_eval = 9.8004
-I0511 11:49:27.160498  4597 caffe.cpp:501] detection_eval = 0.0443093
-I0511 11:49:27.160503  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160506  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160511  4597 caffe.cpp:501] detection_eval = 5.32863
-I0511 11:49:27.160514  4597 caffe.cpp:501] detection_eval = 9.78831
-I0511 11:49:27.160518  4597 caffe.cpp:501] detection_eval = 0.0421533
-I0511 11:49:27.160522  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.160531  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.160535  4597 caffe.cpp:501] detection_eval = 5.33065
-I0511 11:49:27.160539  4597 caffe.cpp:501] detection_eval = 9.83266
-I0511 11:49:27.160543  4597 caffe.cpp:501] detection_eval = 0.0411291
-I0511 11:49:27.160547  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160557  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.160562  4597 caffe.cpp:501] detection_eval = 5.33266
-I0511 11:49:27.160564  4597 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:49:27.160568  4597 caffe.cpp:501] detection_eval = 0.0432754
-I0511 11:49:27.160573  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160576  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160580  4597 caffe.cpp:501] detection_eval = 5.33266
-I0511 11:49:27.160584  4597 caffe.cpp:501] detection_eval = 10
-I0511 11:49:27.160588  4597 caffe.cpp:501] detection_eval = 0.0427896
-I0511 11:49:27.160593  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160596  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160599  4597 caffe.cpp:501] detection_eval = 5.33871
-I0511 11:49:27.160604  4597 caffe.cpp:501] detection_eval = 9.97782
-I0511 11:49:27.160607  4597 caffe.cpp:501] detection_eval = 0.0417101
-I0511 11:49:27.160611  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160615  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160619  4597 caffe.cpp:501] detection_eval = 5.34274
-I0511 11:49:27.160622  4597 caffe.cpp:501] detection_eval = 9.97379
-I0511 11:49:27.160626  4597 caffe.cpp:501] detection_eval = 0.0400292
-I0511 11:49:27.160630  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160634  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160637  4597 caffe.cpp:501] detection_eval = 5.34879
-I0511 11:49:27.160641  4597 caffe.cpp:501] detection_eval = 9.97177
-I0511 11:49:27.160645  4597 caffe.cpp:501] detection_eval = 0.0437753
-I0511 11:49:27.160650  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160653  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160656  4597 caffe.cpp:501] detection_eval = 5.35484
-I0511 11:49:27.160660  4597 caffe.cpp:501] detection_eval = 10.004
-I0511 11:49:27.160662  4597 caffe.cpp:501] detection_eval = 0.0419356
-I0511 11:49:27.160665  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160668  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160672  4597 caffe.cpp:501] detection_eval = 5.35887
-I0511 11:49:27.160676  4597 caffe.cpp:501] detection_eval = 10.0423
-I0511 11:49:27.160678  4597 caffe.cpp:501] detection_eval = 0.0477488
-I0511 11:49:27.160682  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160686  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160688  4597 caffe.cpp:501] detection_eval = 5.36089
-I0511 11:49:27.160691  4597 caffe.cpp:501] detection_eval = 10.0524
-I0511 11:49:27.160696  4597 caffe.cpp:501] detection_eval = 0.0442932
-I0511 11:49:27.160698  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160701  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160704  4597 caffe.cpp:501] detection_eval = 5.3629
-I0511 11:49:27.160708  4597 caffe.cpp:501] detection_eval = 10.0927
-I0511 11:49:27.160712  4597 caffe.cpp:501] detection_eval = 0.0445454
-I0511 11:49:27.160714  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.160717  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160720  4597 caffe.cpp:501] detection_eval = 5.36492
-I0511 11:49:27.160724  4597 caffe.cpp:501] detection_eval = 10.1532
-I0511 11:49:27.160727  4597 caffe.cpp:501] detection_eval = 0.0486137
-I0511 11:49:27.160732  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160734  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160737  4597 caffe.cpp:501] detection_eval = 5.36694
-I0511 11:49:27.160740  4597 caffe.cpp:501] detection_eval = 10.1895
-I0511 11:49:27.160744  4597 caffe.cpp:501] detection_eval = 0.0405678
-I0511 11:49:27.160748  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160750  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.160754  4597 caffe.cpp:501] detection_eval = 5.37097
-I0511 11:49:27.160758  4597 caffe.cpp:501] detection_eval = 10.2077
-I0511 11:49:27.160761  4597 caffe.cpp:501] detection_eval = 0.0446628
-I0511 11:49:27.160768  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160771  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.160774  4597 caffe.cpp:501] detection_eval = 5.375
-I0511 11:49:27.160778  4597 caffe.cpp:501] detection_eval = 10.2198
-I0511 11:49:27.160781  4597 caffe.cpp:501] detection_eval = 0.0413298
-I0511 11:49:27.160784  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160787  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160791  4597 caffe.cpp:501] detection_eval = 5.38105
-I0511 11:49:27.160794  4597 caffe.cpp:501] detection_eval = 10.2419
-I0511 11:49:27.160797  4597 caffe.cpp:501] detection_eval = 0.0400922
-I0511 11:49:27.160800  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160804  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160807  4597 caffe.cpp:501] detection_eval = 5.38911
-I0511 11:49:27.160810  4597 caffe.cpp:501] detection_eval = 10.1875
-I0511 11:49:27.160815  4597 caffe.cpp:501] detection_eval = 0.0443394
-I0511 11:49:27.160817  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.160820  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160823  4597 caffe.cpp:501] detection_eval = 5.38911
-I0511 11:49:27.160826  4597 caffe.cpp:501] detection_eval = 10.252
-I0511 11:49:27.160830  4597 caffe.cpp:501] detection_eval = 0.0393483
-I0511 11:49:27.160833  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160836  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160840  4597 caffe.cpp:501] detection_eval = 5.39516
-I0511 11:49:27.160843  4597 caffe.cpp:501] detection_eval = 10.2419
-I0511 11:49:27.160846  4597 caffe.cpp:501] detection_eval = 0.0430957
-I0511 11:49:27.160850  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.160853  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.160856  4597 caffe.cpp:501] detection_eval = 5.40524
-I0511 11:49:27.160861  4597 caffe.cpp:501] detection_eval = 10.1815
-I0511 11:49:27.160863  4597 caffe.cpp:501] detection_eval = 0.0463508
-I0511 11:49:27.160866  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.160871  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.160873  4597 caffe.cpp:501] detection_eval = 5.40726
-I0511 11:49:27.160876  4597 caffe.cpp:501] detection_eval = 10.2359
-I0511 11:49:27.160879  4597 caffe.cpp:501] detection_eval = 0.0478428
-I0511 11:49:27.160883  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.160887  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.160889  4597 caffe.cpp:501] detection_eval = 5.41331
-I0511 11:49:27.160892  4597 caffe.cpp:501] detection_eval = 10.2117
-I0511 11:49:27.160897  4597 caffe.cpp:501] detection_eval = 0.0406707
-I0511 11:49:27.160899  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.160902  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.160907  4597 caffe.cpp:501] detection_eval = 5.41734
-I0511 11:49:27.160909  4597 caffe.cpp:501] detection_eval = 10.252
-I0511 11:49:27.160912  4597 caffe.cpp:501] detection_eval = 0.0420435
-I0511 11:49:27.160917  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.160921  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.160926  4597 caffe.cpp:501] detection_eval = 5.42137
-I0511 11:49:27.161113  4597 caffe.cpp:501] detection_eval = 10.2782
-I0511 11:49:27.161119  4597 caffe.cpp:501] detection_eval = 0.0423986
-I0511 11:49:27.161123  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161128  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.161131  4597 caffe.cpp:501] detection_eval = 5.4254
-I0511 11:49:27.161134  4597 caffe.cpp:501] detection_eval = 10.3125
-I0511 11:49:27.161139  4597 caffe.cpp:501] detection_eval = 0.0459558
-I0511 11:49:27.161142  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161146  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161150  4597 caffe.cpp:501] detection_eval = 5.42742
-I0511 11:49:27.161154  4597 caffe.cpp:501] detection_eval = 10.3972
-I0511 11:49:27.161159  4597 caffe.cpp:501] detection_eval = 0.0469398
-I0511 11:49:27.161167  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.161171  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.161175  4597 caffe.cpp:501] detection_eval = 5.42944
-I0511 11:49:27.161180  4597 caffe.cpp:501] detection_eval = 10.4476
-I0511 11:49:27.161183  4597 caffe.cpp:501] detection_eval = 0.0426102
-I0511 11:49:27.161187  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161191  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161195  4597 caffe.cpp:501] detection_eval = 5.42944
-I0511 11:49:27.161198  4597 caffe.cpp:501] detection_eval = 10.5444
-I0511 11:49:27.161202  4597 caffe.cpp:501] detection_eval = 0.0389233
-I0511 11:49:27.161206  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161209  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161213  4597 caffe.cpp:501] detection_eval = 5.43548
-I0511 11:49:27.161217  4597 caffe.cpp:501] detection_eval = 10.5444
-I0511 11:49:27.161221  4597 caffe.cpp:501] detection_eval = 0.0445941
-I0511 11:49:27.161224  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161228  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161232  4597 caffe.cpp:501] detection_eval = 5.44556
-I0511 11:49:27.161236  4597 caffe.cpp:501] detection_eval = 10.4415
-I0511 11:49:27.161239  4597 caffe.cpp:501] detection_eval = 0.0488672
-I0511 11:49:27.161243  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161247  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161252  4597 caffe.cpp:501] detection_eval = 5.45161
-I0511 11:49:27.161254  4597 caffe.cpp:501] detection_eval = 10.4415
-I0511 11:49:27.161259  4597 caffe.cpp:501] detection_eval = 0.0396903
-I0511 11:49:27.161262  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.161267  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.161270  4597 caffe.cpp:501] detection_eval = 5.45565
-I0511 11:49:27.161274  4597 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:49:27.161278  4597 caffe.cpp:501] detection_eval = 0.0415952
-I0511 11:49:27.161283  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.161286  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.161289  4597 caffe.cpp:501] detection_eval = 5.45766
-I0511 11:49:27.161293  4597 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:49:27.161298  4597 caffe.cpp:501] detection_eval = 0.0425015
-I0511 11:49:27.161301  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.161305  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.161309  4597 caffe.cpp:501] detection_eval = 5.46573
-I0511 11:49:27.161312  4597 caffe.cpp:501] detection_eval = 10.502
-I0511 11:49:27.161316  4597 caffe.cpp:501] detection_eval = 0.0476768
-I0511 11:49:27.161320  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161324  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161327  4597 caffe.cpp:501] detection_eval = 5.46774
-I0511 11:49:27.161331  4597 caffe.cpp:501] detection_eval = 10.5282
-I0511 11:49:27.161335  4597 caffe.cpp:501] detection_eval = 0.0461731
-I0511 11:49:27.161339  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161342  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161346  4597 caffe.cpp:501] detection_eval = 5.47177
-I0511 11:49:27.161350  4597 caffe.cpp:501] detection_eval = 10.5202
-I0511 11:49:27.161355  4597 caffe.cpp:501] detection_eval = 0.0412965
-I0511 11:49:27.161358  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.161362  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.161366  4597 caffe.cpp:501] detection_eval = 5.47379
-I0511 11:49:27.161370  4597 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:49:27.161373  4597 caffe.cpp:501] detection_eval = 0.0440154
-I0511 11:49:27.161377  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161381  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161384  4597 caffe.cpp:501] detection_eval = 5.47379
-I0511 11:49:27.161388  4597 caffe.cpp:501] detection_eval = 10.6008
-I0511 11:49:27.161396  4597 caffe.cpp:501] detection_eval = 0.0448397
-I0511 11:49:27.161401  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161404  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.161407  4597 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:49:27.161412  4597 caffe.cpp:501] detection_eval = 10.5665
-I0511 11:49:27.161417  4597 caffe.cpp:501] detection_eval = 0.0431499
-I0511 11:49:27.161420  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.161423  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161427  4597 caffe.cpp:501] detection_eval = 5.48387
-I0511 11:49:27.161432  4597 caffe.cpp:501] detection_eval = 10.5867
-I0511 11:49:27.161435  4597 caffe.cpp:501] detection_eval = 0.0461701
-I0511 11:49:27.161438  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161442  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161447  4597 caffe.cpp:501] detection_eval = 5.48589
-I0511 11:49:27.161450  4597 caffe.cpp:501] detection_eval = 10.6089
-I0511 11:49:27.161454  4597 caffe.cpp:501] detection_eval = 0.0417937
-I0511 11:49:27.161458  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161461  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161465  4597 caffe.cpp:501] detection_eval = 5.4879
-I0511 11:49:27.161468  4597 caffe.cpp:501] detection_eval = 10.6794
-I0511 11:49:27.161473  4597 caffe.cpp:501] detection_eval = 0.0506458
-I0511 11:49:27.161476  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161480  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161484  4597 caffe.cpp:501] detection_eval = 5.48992
-I0511 11:49:27.161487  4597 caffe.cpp:501] detection_eval = 10.7157
-I0511 11:49:27.161491  4597 caffe.cpp:501] detection_eval = 0.0439529
-I0511 11:49:27.161495  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.161499  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.161504  4597 caffe.cpp:501] detection_eval = 5.49194
-I0511 11:49:27.161506  4597 caffe.cpp:501] detection_eval = 10.7218
-I0511 11:49:27.161510  4597 caffe.cpp:501] detection_eval = 0.0437257
-I0511 11:49:27.161514  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161518  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161521  4597 caffe.cpp:501] detection_eval = 5.49597
-I0511 11:49:27.161525  4597 caffe.cpp:501] detection_eval = 10.7298
-I0511 11:49:27.161530  4597 caffe.cpp:501] detection_eval = 0.0456176
-I0511 11:49:27.161533  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161537  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161540  4597 caffe.cpp:501] detection_eval = 5.50403
-I0511 11:49:27.161545  4597 caffe.cpp:501] detection_eval = 10.6895
-I0511 11:49:27.161548  4597 caffe.cpp:501] detection_eval = 0.0444774
-I0511 11:49:27.161552  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161556  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161561  4597 caffe.cpp:501] detection_eval = 5.50806
-I0511 11:49:27.161563  4597 caffe.cpp:501] detection_eval = 10.7077
-I0511 11:49:27.161567  4597 caffe.cpp:501] detection_eval = 0.0459073
-I0511 11:49:27.161571  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161743  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161749  4597 caffe.cpp:501] detection_eval = 5.51008
-I0511 11:49:27.161753  4597 caffe.cpp:501] detection_eval = 10.7319
-I0511 11:49:27.161757  4597 caffe.cpp:501] detection_eval = 0.042579
-I0511 11:49:27.161761  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161765  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.161768  4597 caffe.cpp:501] detection_eval = 5.5121
-I0511 11:49:27.161772  4597 caffe.cpp:501] detection_eval = 10.7883
-I0511 11:49:27.161777  4597 caffe.cpp:501] detection_eval = 0.0499974
-I0511 11:49:27.161780  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161784  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161788  4597 caffe.cpp:501] detection_eval = 5.5121
-I0511 11:49:27.161797  4597 caffe.cpp:501] detection_eval = 10.8851
-I0511 11:49:27.161801  4597 caffe.cpp:501] detection_eval = 0.042366
-I0511 11:49:27.161804  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161808  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.161813  4597 caffe.cpp:501] detection_eval = 5.51815
-I0511 11:49:27.161815  4597 caffe.cpp:501] detection_eval = 10.8831
-I0511 11:49:27.161819  4597 caffe.cpp:501] detection_eval = 0.0477807
-I0511 11:49:27.161823  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.161828  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161831  4597 caffe.cpp:501] detection_eval = 5.52016
-I0511 11:49:27.161834  4597 caffe.cpp:501] detection_eval = 10.9819
-I0511 11:49:27.161839  4597 caffe.cpp:501] detection_eval = 0.0444135
-I0511 11:49:27.161842  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161846  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.161850  4597 caffe.cpp:501] detection_eval = 5.52621
-I0511 11:49:27.161854  4597 caffe.cpp:501] detection_eval = 10.9355
-I0511 11:49:27.161859  4597 caffe.cpp:501] detection_eval = 0.043241
-I0511 11:49:27.161861  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161865  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161870  4597 caffe.cpp:501] detection_eval = 5.52621
-I0511 11:49:27.161873  4597 caffe.cpp:501] detection_eval = 11.004
-I0511 11:49:27.161876  4597 caffe.cpp:501] detection_eval = 0.0428463
-I0511 11:49:27.161880  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.161885  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161888  4597 caffe.cpp:501] detection_eval = 5.52621
-I0511 11:49:27.161891  4597 caffe.cpp:501] detection_eval = 11.0927
-I0511 11:49:27.161895  4597 caffe.cpp:501] detection_eval = 0.0443812
-I0511 11:49:27.161900  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161903  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.161907  4597 caffe.cpp:501] detection_eval = 5.53024
-I0511 11:49:27.161911  4597 caffe.cpp:501] detection_eval = 11.119
-I0511 11:49:27.161914  4597 caffe.cpp:501] detection_eval = 0.0419728
-I0511 11:49:27.161918  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161922  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161926  4597 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:49:27.161929  4597 caffe.cpp:501] detection_eval = 11.1331
-I0511 11:49:27.161933  4597 caffe.cpp:501] detection_eval = 0.0406407
-I0511 11:49:27.161937  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.161940  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.161944  4597 caffe.cpp:501] detection_eval = 5.53831
-I0511 11:49:27.161948  4597 caffe.cpp:501] detection_eval = 11.1512
-I0511 11:49:27.161952  4597 caffe.cpp:501] detection_eval = 0.0448388
-I0511 11:49:27.161955  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.161959  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.161963  4597 caffe.cpp:501] detection_eval = 5.54234
-I0511 11:49:27.161967  4597 caffe.cpp:501] detection_eval = 11.1633
-I0511 11:49:27.161970  4597 caffe.cpp:501] detection_eval = 0.0418458
-I0511 11:49:27.161974  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.161978  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.161983  4597 caffe.cpp:501] detection_eval = 5.54234
-I0511 11:49:27.161986  4597 caffe.cpp:501] detection_eval = 11.2923
-I0511 11:49:27.161989  4597 caffe.cpp:501] detection_eval = 0.0507683
-I0511 11:49:27.161993  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.161998  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.162001  4597 caffe.cpp:501] detection_eval = 5.54234
-I0511 11:49:27.162004  4597 caffe.cpp:501] detection_eval = 11.3306
-I0511 11:49:27.162009  4597 caffe.cpp:501] detection_eval = 0.044087
-I0511 11:49:27.162012  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.162016  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.162020  4597 caffe.cpp:501] detection_eval = 5.54839
-I0511 11:49:27.162027  4597 caffe.cpp:501] detection_eval = 11.2964
-I0511 11:49:27.162031  4597 caffe.cpp:501] detection_eval = 0.0475861
-I0511 11:49:27.162035  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162039  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162042  4597 caffe.cpp:501] detection_eval = 5.5504
-I0511 11:49:27.162046  4597 caffe.cpp:501] detection_eval = 11.3508
-I0511 11:49:27.162050  4597 caffe.cpp:501] detection_eval = 0.0519199
-I0511 11:49:27.162055  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.162058  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162061  4597 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:49:27.162065  4597 caffe.cpp:501] detection_eval = 11.381
-I0511 11:49:27.162070  4597 caffe.cpp:501] detection_eval = 0.0452902
-I0511 11:49:27.162073  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.162077  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.162081  4597 caffe.cpp:501] detection_eval = 5.55847
-I0511 11:49:27.162084  4597 caffe.cpp:501] detection_eval = 11.3891
-I0511 11:49:27.162088  4597 caffe.cpp:501] detection_eval = 0.0478307
-I0511 11:49:27.162092  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.162096  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162099  4597 caffe.cpp:501] detection_eval = 5.5625
-I0511 11:49:27.162103  4597 caffe.cpp:501] detection_eval = 11.369
-I0511 11:49:27.162107  4597 caffe.cpp:501] detection_eval = 0.0431125
-I0511 11:49:27.162111  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.162114  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.162118  4597 caffe.cpp:501] detection_eval = 5.56653
-I0511 11:49:27.162122  4597 caffe.cpp:501] detection_eval = 11.4012
-I0511 11:49:27.162127  4597 caffe.cpp:501] detection_eval = 0.0432105
-I0511 11:49:27.162129  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.162133  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.162137  4597 caffe.cpp:501] detection_eval = 5.57056
-I0511 11:49:27.162140  4597 caffe.cpp:501] detection_eval = 11.4536
-I0511 11:49:27.162144  4597 caffe.cpp:501] detection_eval = 0.0533981
-I0511 11:49:27.162148  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.162153  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.162155  4597 caffe.cpp:501] detection_eval = 5.5746
-I0511 11:49:27.162159  4597 caffe.cpp:501] detection_eval = 11.4859
-I0511 11:49:27.162163  4597 caffe.cpp:501] detection_eval = 0.0472518
-I0511 11:49:27.162168  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.162170  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.162174  4597 caffe.cpp:501] detection_eval = 5.58065
-I0511 11:49:27.162178  4597 caffe.cpp:501] detection_eval = 11.5181
-I0511 11:49:27.162183  4597 caffe.cpp:501] detection_eval = 0.0493227
-I0511 11:49:27.162185  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.162189  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162192  4597 caffe.cpp:501] detection_eval = 5.58065
-I0511 11:49:27.162196  4597 caffe.cpp:501] detection_eval = 11.6048
-I0511 11:49:27.162374  4597 caffe.cpp:501] detection_eval = 0.0414111
-I0511 11:49:27.162380  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162384  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.162387  4597 caffe.cpp:501] detection_eval = 5.58266
-I0511 11:49:27.162391  4597 caffe.cpp:501] detection_eval = 11.6371
-I0511 11:49:27.162395  4597 caffe.cpp:501] detection_eval = 0.0464631
-I0511 11:49:27.162400  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162402  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162406  4597 caffe.cpp:501] detection_eval = 5.59073
-I0511 11:49:27.162410  4597 caffe.cpp:501] detection_eval = 11.5504
-I0511 11:49:27.162415  4597 caffe.cpp:501] detection_eval = 0.0493058
-I0511 11:49:27.162418  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162422  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162431  4597 caffe.cpp:501] detection_eval = 5.59274
-I0511 11:49:27.162434  4597 caffe.cpp:501] detection_eval = 11.625
-I0511 11:49:27.162438  4597 caffe.cpp:501] detection_eval = 0.0454611
-I0511 11:49:27.162442  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162446  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162451  4597 caffe.cpp:501] detection_eval = 5.59476
-I0511 11:49:27.162454  4597 caffe.cpp:501] detection_eval = 11.6835
-I0511 11:49:27.162458  4597 caffe.cpp:501] detection_eval = 0.0434493
-I0511 11:49:27.162461  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162466  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162469  4597 caffe.cpp:501] detection_eval = 5.60282
-I0511 11:49:27.162472  4597 caffe.cpp:501] detection_eval = 11.621
-I0511 11:49:27.162477  4597 caffe.cpp:501] detection_eval = 0.0392699
-I0511 11:49:27.162480  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.162484  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.162488  4597 caffe.cpp:501] detection_eval = 5.61089
-I0511 11:49:27.162492  4597 caffe.cpp:501] detection_eval = 11.5847
-I0511 11:49:27.162497  4597 caffe.cpp:501] detection_eval = 0.0437702
-I0511 11:49:27.162499  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.162503  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162508  4597 caffe.cpp:501] detection_eval = 5.61694
-I0511 11:49:27.162511  4597 caffe.cpp:501] detection_eval = 11.5282
-I0511 11:49:27.162515  4597 caffe.cpp:501] detection_eval = 0.0404295
-I0511 11:49:27.162518  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162523  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162526  4597 caffe.cpp:501] detection_eval = 5.62097
-I0511 11:49:27.162530  4597 caffe.cpp:501] detection_eval = 11.5585
-I0511 11:49:27.162534  4597 caffe.cpp:501] detection_eval = 0.0477996
-I0511 11:49:27.162537  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.162541  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162545  4597 caffe.cpp:501] detection_eval = 5.625
-I0511 11:49:27.162549  4597 caffe.cpp:501] detection_eval = 11.5726
-I0511 11:49:27.162552  4597 caffe.cpp:501] detection_eval = 0.0435699
-I0511 11:49:27.162556  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.162560  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.162564  4597 caffe.cpp:501] detection_eval = 5.6371
-I0511 11:49:27.162569  4597 caffe.cpp:501] detection_eval = 11.4617
-I0511 11:49:27.162572  4597 caffe.cpp:501] detection_eval = 0.0415749
-I0511 11:49:27.162575  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162580  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162583  4597 caffe.cpp:501] detection_eval = 5.6371
-I0511 11:49:27.162587  4597 caffe.cpp:501] detection_eval = 11.506
-I0511 11:49:27.162591  4597 caffe.cpp:501] detection_eval = 0.0371579
-I0511 11:49:27.162595  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.162598  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.162602  4597 caffe.cpp:501] detection_eval = 5.64315
-I0511 11:49:27.162606  4597 caffe.cpp:501] detection_eval = 11.5
-I0511 11:49:27.162611  4597 caffe.cpp:501] detection_eval = 0.0378634
-I0511 11:49:27.162614  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.162618  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.162621  4597 caffe.cpp:501] detection_eval = 5.64516
-I0511 11:49:27.162626  4597 caffe.cpp:501] detection_eval = 11.5887
-I0511 11:49:27.162629  4597 caffe.cpp:501] detection_eval = 0.0424586
-I0511 11:49:27.162633  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.162637  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.162641  4597 caffe.cpp:501] detection_eval = 5.64718
-I0511 11:49:27.162644  4597 caffe.cpp:501] detection_eval = 11.6593
-I0511 11:49:27.162648  4597 caffe.cpp:501] detection_eval = 0.0441311
-I0511 11:49:27.162652  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.162655  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.162663  4597 caffe.cpp:501] detection_eval = 5.65524
-I0511 11:49:27.162667  4597 caffe.cpp:501] detection_eval = 11.627
-I0511 11:49:27.162672  4597 caffe.cpp:501] detection_eval = 0.0482354
-I0511 11:49:27.162674  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.162678  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.162683  4597 caffe.cpp:501] detection_eval = 5.66129
-I0511 11:49:27.162686  4597 caffe.cpp:501] detection_eval = 11.5867
-I0511 11:49:27.162690  4597 caffe.cpp:501] detection_eval = 0.0463853
-I0511 11:49:27.162694  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.162698  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.162701  4597 caffe.cpp:501] detection_eval = 5.66331
-I0511 11:49:27.162705  4597 caffe.cpp:501] detection_eval = 11.5867
-I0511 11:49:27.162709  4597 caffe.cpp:501] detection_eval = 0.0423538
-I0511 11:49:27.162714  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162716  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.162720  4597 caffe.cpp:501] detection_eval = 5.66331
-I0511 11:49:27.162724  4597 caffe.cpp:501] detection_eval = 11.6794
-I0511 11:49:27.162729  4597 caffe.cpp:501] detection_eval = 0.0366064
-I0511 11:49:27.162732  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.162735  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.162739  4597 caffe.cpp:501] detection_eval = 5.66532
-I0511 11:49:27.162744  4597 caffe.cpp:501] detection_eval = 11.7137
-I0511 11:49:27.162747  4597 caffe.cpp:501] detection_eval = 0.0415668
-I0511 11:49:27.162750  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162755  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162758  4597 caffe.cpp:501] detection_eval = 5.66935
-I0511 11:49:27.162762  4597 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:49:27.162766  4597 caffe.cpp:501] detection_eval = 0.0378184
-I0511 11:49:27.162770  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.162773  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162777  4597 caffe.cpp:501] detection_eval = 5.67339
-I0511 11:49:27.162781  4597 caffe.cpp:501] detection_eval = 11.7238
-I0511 11:49:27.162784  4597 caffe.cpp:501] detection_eval = 0.0453912
-I0511 11:49:27.162788  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.162792  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.162796  4597 caffe.cpp:501] detection_eval = 5.67742
-I0511 11:49:27.162799  4597 caffe.cpp:501] detection_eval = 11.6976
-I0511 11:49:27.162803  4597 caffe.cpp:501] detection_eval = 0.0440392
-I0511 11:49:27.162807  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.162811  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.162814  4597 caffe.cpp:501] detection_eval = 5.68145
-I0511 11:49:27.162818  4597 caffe.cpp:501] detection_eval = 11.7177
-I0511 11:49:27.162822  4597 caffe.cpp:501] detection_eval = 0.0465293
-I0511 11:49:27.162827  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.162830  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163008  4597 caffe.cpp:501] detection_eval = 5.6875
-I0511 11:49:27.163014  4597 caffe.cpp:501] detection_eval = 11.6855
-I0511 11:49:27.163018  4597 caffe.cpp:501] detection_eval = 0.0466328
-I0511 11:49:27.163022  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.163025  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163029  4597 caffe.cpp:501] detection_eval = 5.68952
-I0511 11:49:27.163033  4597 caffe.cpp:501] detection_eval = 11.7056
-I0511 11:49:27.163038  4597 caffe.cpp:501] detection_eval = 0.0445552
-I0511 11:49:27.163041  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.163044  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.163048  4597 caffe.cpp:501] detection_eval = 5.68952
-I0511 11:49:27.163053  4597 caffe.cpp:501] detection_eval = 11.7722
-I0511 11:49:27.163056  4597 caffe.cpp:501] detection_eval = 0.0455712
-I0511 11:49:27.163059  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.163069  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.163072  4597 caffe.cpp:501] detection_eval = 5.6996
-I0511 11:49:27.163076  4597 caffe.cpp:501] detection_eval = 11.6794
-I0511 11:49:27.163080  4597 caffe.cpp:501] detection_eval = 0.0432129
-I0511 11:49:27.163084  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.163089  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.163091  4597 caffe.cpp:501] detection_eval = 5.70363
-I0511 11:49:27.163095  4597 caffe.cpp:501] detection_eval = 11.6472
-I0511 11:49:27.163100  4597 caffe.cpp:501] detection_eval = 0.044814
-I0511 11:49:27.163103  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163107  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163110  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163115  4597 caffe.cpp:501] detection_eval = 11.6452
-I0511 11:49:27.163118  4597 caffe.cpp:501] detection_eval = 0.0442991
-I0511 11:49:27.163122  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.163125  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163130  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163132  4597 caffe.cpp:501] detection_eval = 11.6915
-I0511 11:49:27.163136  4597 caffe.cpp:501] detection_eval = 0.0426855
-I0511 11:49:27.163141  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.163144  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163148  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163151  4597 caffe.cpp:501] detection_eval = 11.75
-I0511 11:49:27.163156  4597 caffe.cpp:501] detection_eval = 0.0402009
-I0511 11:49:27.163159  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163162  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163166  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163170  4597 caffe.cpp:501] detection_eval = 11.8266
-I0511 11:49:27.163174  4597 caffe.cpp:501] detection_eval = 0.0375853
-I0511 11:49:27.163178  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.163182  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163185  4597 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:49:27.163189  4597 caffe.cpp:501] detection_eval = 11.875
-I0511 11:49:27.163193  4597 caffe.cpp:501] detection_eval = 0.0399351
-I0511 11:49:27.163197  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.163200  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163204  4597 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:49:27.163208  4597 caffe.cpp:501] detection_eval = 11.8427
-I0511 11:49:27.163211  4597 caffe.cpp:501] detection_eval = 0.0388135
-I0511 11:49:27.163215  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163219  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163223  4597 caffe.cpp:501] detection_eval = 5.71774
-I0511 11:49:27.163226  4597 caffe.cpp:501] detection_eval = 11.8851
-I0511 11:49:27.163230  4597 caffe.cpp:501] detection_eval = 0.0457987
-I0511 11:49:27.163234  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.163240  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.163244  4597 caffe.cpp:501] detection_eval = 5.72177
-I0511 11:49:27.163249  4597 caffe.cpp:501] detection_eval = 11.9052
-I0511 11:49:27.163251  4597 caffe.cpp:501] detection_eval = 0.0446153
-I0511 11:49:27.163255  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.163259  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.163264  4597 caffe.cpp:501] detection_eval = 5.72782
-I0511 11:49:27.163266  4597 caffe.cpp:501] detection_eval = 11.8629
-I0511 11:49:27.163270  4597 caffe.cpp:501] detection_eval = 0.0366044
-I0511 11:49:27.163275  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.163278  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.163281  4597 caffe.cpp:501] detection_eval = 5.73185
-I0511 11:49:27.163285  4597 caffe.cpp:501] detection_eval = 11.8589
-I0511 11:49:27.163290  4597 caffe.cpp:501] detection_eval = 0.0373293
-I0511 11:49:27.163293  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163301  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163305  4597 caffe.cpp:501] detection_eval = 5.73185
-I0511 11:49:27.163309  4597 caffe.cpp:501] detection_eval = 11.9335
-I0511 11:49:27.163313  4597 caffe.cpp:501] detection_eval = 0.0344321
-I0511 11:49:27.163317  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.163321  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.163324  4597 caffe.cpp:501] detection_eval = 5.7379
-I0511 11:49:27.163327  4597 caffe.cpp:501] detection_eval = 11.9556
-I0511 11:49:27.163331  4597 caffe.cpp:501] detection_eval = 0.0369631
-I0511 11:49:27.163336  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163339  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163343  4597 caffe.cpp:501] detection_eval = 5.74194
-I0511 11:49:27.163347  4597 caffe.cpp:501] detection_eval = 11.9819
-I0511 11:49:27.163352  4597 caffe.cpp:501] detection_eval = 0.0419468
-I0511 11:49:27.163355  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163359  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163363  4597 caffe.cpp:501] detection_eval = 5.74798
-I0511 11:49:27.163367  4597 caffe.cpp:501] detection_eval = 12.0202
-I0511 11:49:27.163370  4597 caffe.cpp:501] detection_eval = 0.0448674
-I0511 11:49:27.163374  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.163378  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163383  4597 caffe.cpp:501] detection_eval = 5.75
-I0511 11:49:27.163385  4597 caffe.cpp:501] detection_eval = 12.0665
-I0511 11:49:27.163389  4597 caffe.cpp:501] detection_eval = 0.0403543
-I0511 11:49:27.163393  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163398  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.163400  4597 caffe.cpp:501] detection_eval = 5.75403
-I0511 11:49:27.163404  4597 caffe.cpp:501] detection_eval = 12.0544
-I0511 11:49:27.163408  4597 caffe.cpp:501] detection_eval = 0.0392934
-I0511 11:49:27.163413  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.163416  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163419  4597 caffe.cpp:501] detection_eval = 5.75806
-I0511 11:49:27.163424  4597 caffe.cpp:501] detection_eval = 12.0323
-I0511 11:49:27.163427  4597 caffe.cpp:501] detection_eval = 0.0426397
-I0511 11:49:27.163431  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163435  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163439  4597 caffe.cpp:501] detection_eval = 5.76008
-I0511 11:49:27.163442  4597 caffe.cpp:501] detection_eval = 12.1089
-I0511 11:49:27.163446  4597 caffe.cpp:501] detection_eval = 0.0402482
-I0511 11:49:27.163450  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163455  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163458  4597 caffe.cpp:501] detection_eval = 5.76411
-I0511 11:49:27.163461  4597 caffe.cpp:501] detection_eval = 12.0867
-I0511 11:49:27.163465  4597 caffe.cpp:501] detection_eval = 0.0386994
-I0511 11:49:27.163663  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163669  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163673  4597 caffe.cpp:501] detection_eval = 5.77218
-I0511 11:49:27.163677  4597 caffe.cpp:501] detection_eval = 12.0544
-I0511 11:49:27.163681  4597 caffe.cpp:501] detection_eval = 0.0352902
-I0511 11:49:27.163684  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.163688  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163692  4597 caffe.cpp:501] detection_eval = 5.77621
-I0511 11:49:27.163695  4597 caffe.cpp:501] detection_eval = 12.0403
-I0511 11:49:27.163699  4597 caffe.cpp:501] detection_eval = 0.036581
-I0511 11:49:27.163703  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163707  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163710  4597 caffe.cpp:501] detection_eval = 5.77621
-I0511 11:49:27.163714  4597 caffe.cpp:501] detection_eval = 12.1028
-I0511 11:49:27.163718  4597 caffe.cpp:501] detection_eval = 0.0353292
-I0511 11:49:27.163727  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.163731  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163734  4597 caffe.cpp:501] detection_eval = 5.78024
-I0511 11:49:27.163738  4597 caffe.cpp:501] detection_eval = 12.0948
-I0511 11:49:27.163743  4597 caffe.cpp:501] detection_eval = 0.0369279
-I0511 11:49:27.163746  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163750  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.163753  4597 caffe.cpp:501] detection_eval = 5.78629
-I0511 11:49:27.163758  4597 caffe.cpp:501] detection_eval = 12.0403
-I0511 11:49:27.163761  4597 caffe.cpp:501] detection_eval = 0.036216
-I0511 11:49:27.163765  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.163769  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.163772  4597 caffe.cpp:501] detection_eval = 5.78831
-I0511 11:49:27.163776  4597 caffe.cpp:501] detection_eval = 12.1149
-I0511 11:49:27.163780  4597 caffe.cpp:501] detection_eval = 0.0408232
-I0511 11:49:27.163784  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163787  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163791  4597 caffe.cpp:501] detection_eval = 5.8004
-I0511 11:49:27.163794  4597 caffe.cpp:501] detection_eval = 12.002
-I0511 11:49:27.163799  4597 caffe.cpp:501] detection_eval = 0.0424982
-I0511 11:49:27.163802  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163806  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163810  4597 caffe.cpp:501] detection_eval = 5.8004
-I0511 11:49:27.163813  4597 caffe.cpp:501] detection_eval = 12.0887
-I0511 11:49:27.163817  4597 caffe.cpp:501] detection_eval = 0.0353425
-I0511 11:49:27.163821  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163825  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.163828  4597 caffe.cpp:501] detection_eval = 5.80645
-I0511 11:49:27.163832  4597 caffe.cpp:501] detection_eval = 12.1129
-I0511 11:49:27.163836  4597 caffe.cpp:501] detection_eval = 0.0404876
-I0511 11:49:27.163841  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.163843  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163847  4597 caffe.cpp:501] detection_eval = 5.8125
-I0511 11:49:27.163851  4597 caffe.cpp:501] detection_eval = 12.0927
-I0511 11:49:27.163854  4597 caffe.cpp:501] detection_eval = 0.0459566
-I0511 11:49:27.163858  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.163862  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.163866  4597 caffe.cpp:501] detection_eval = 5.81452
-I0511 11:49:27.163869  4597 caffe.cpp:501] detection_eval = 12.121
-I0511 11:49:27.163873  4597 caffe.cpp:501] detection_eval = 0.039085
-I0511 11:49:27.163877  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163882  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.163885  4597 caffe.cpp:501] detection_eval = 5.81855
-I0511 11:49:27.163889  4597 caffe.cpp:501] detection_eval = 12.1048
-I0511 11:49:27.163893  4597 caffe.cpp:501] detection_eval = 0.0381383
-I0511 11:49:27.163897  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163902  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163904  4597 caffe.cpp:501] detection_eval = 5.81855
-I0511 11:49:27.163908  4597 caffe.cpp:501] detection_eval = 12.1774
-I0511 11:49:27.163913  4597 caffe.cpp:501] detection_eval = 0.0394167
-I0511 11:49:27.163916  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.163920  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163923  4597 caffe.cpp:501] detection_eval = 5.81855
-I0511 11:49:27.163928  4597 caffe.cpp:501] detection_eval = 12.2802
-I0511 11:49:27.163931  4597 caffe.cpp:501] detection_eval = 0.03695
-I0511 11:49:27.163935  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.163939  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.163944  4597 caffe.cpp:501] detection_eval = 5.82056
-I0511 11:49:27.163946  4597 caffe.cpp:501] detection_eval = 12.3226
-I0511 11:49:27.163954  4597 caffe.cpp:501] detection_eval = 0.0371963
-I0511 11:49:27.163959  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.163962  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.163966  4597 caffe.cpp:501] detection_eval = 5.8246
-I0511 11:49:27.163969  4597 caffe.cpp:501] detection_eval = 12.3024
-I0511 11:49:27.163975  4597 caffe.cpp:501] detection_eval = 0.0401487
-I0511 11:49:27.163978  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.163981  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.163985  4597 caffe.cpp:501] detection_eval = 5.82661
-I0511 11:49:27.163990  4597 caffe.cpp:501] detection_eval = 12.3629
-I0511 11:49:27.163993  4597 caffe.cpp:501] detection_eval = 0.0408615
-I0511 11:49:27.163997  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.164001  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.164005  4597 caffe.cpp:501] detection_eval = 5.83669
-I0511 11:49:27.164008  4597 caffe.cpp:501] detection_eval = 12.2681
-I0511 11:49:27.164012  4597 caffe.cpp:501] detection_eval = 0.0363798
-I0511 11:49:27.164016  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.164019  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.164023  4597 caffe.cpp:501] detection_eval = 5.83871
-I0511 11:49:27.164027  4597 caffe.cpp:501] detection_eval = 12.3427
-I0511 11:49:27.164031  4597 caffe.cpp:501] detection_eval = 0.0426772
-I0511 11:49:27.164034  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.164038  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.164042  4597 caffe.cpp:501] detection_eval = 5.84073
-I0511 11:49:27.164047  4597 caffe.cpp:501] detection_eval = 12.4093
-I0511 11:49:27.164049  4597 caffe.cpp:501] detection_eval = 0.0398318
-I0511 11:49:27.164053  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164057  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.164062  4597 caffe.cpp:501] detection_eval = 5.84073
-I0511 11:49:27.164065  4597 caffe.cpp:501] detection_eval = 12.5464
-I0511 11:49:27.164069  4597 caffe.cpp:501] detection_eval = 0.0405751
-I0511 11:49:27.164072  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.164077  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.164080  4597 caffe.cpp:501] detection_eval = 5.85081
-I0511 11:49:27.164083  4597 caffe.cpp:501] detection_eval = 12.6028
-I0511 11:49:27.164088  4597 caffe.cpp:501] detection_eval = 0.0437554
-I0511 11:49:27.164091  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164095  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.164099  4597 caffe.cpp:501] detection_eval = 5.85282
-I0511 11:49:27.164103  4597 caffe.cpp:501] detection_eval = 12.7702
-I0511 11:49:27.164108  4597 caffe.cpp:501] detection_eval = 0.0417783
-I0511 11:49:27.164111  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.164115  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.164120  4597 caffe.cpp:501] detection_eval = 5.85685
-I0511 11:49:27.164304  4597 caffe.cpp:501] detection_eval = 12.9194
-I0511 11:49:27.164311  4597 caffe.cpp:501] detection_eval = 0.0425652
-I0511 11:49:27.164314  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.164319  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164322  4597 caffe.cpp:501] detection_eval = 6.1875
-I0511 11:49:27.164326  4597 caffe.cpp:501] detection_eval = 7.95565
-I0511 11:49:27.164330  4597 caffe.cpp:501] detection_eval = 0.0710047
-I0511 11:49:27.164333  4597 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:49:27.164337  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.164341  4597 caffe.cpp:501] detection_eval = 6.18952
-I0511 11:49:27.164345  4597 caffe.cpp:501] detection_eval = 8.11694
-I0511 11:49:27.164348  4597 caffe.cpp:501] detection_eval = 0.0543399
-I0511 11:49:27.164352  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.164356  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164361  4597 caffe.cpp:501] detection_eval = 6.19355
-I0511 11:49:27.164363  4597 caffe.cpp:501] detection_eval = 8.16935
-I0511 11:49:27.164372  4597 caffe.cpp:501] detection_eval = 0.0498162
-I0511 11:49:27.164376  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.164381  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.164384  4597 caffe.cpp:501] detection_eval = 6.19758
-I0511 11:49:27.164387  4597 caffe.cpp:501] detection_eval = 8.20968
-I0511 11:49:27.164391  4597 caffe.cpp:501] detection_eval = 0.0504134
-I0511 11:49:27.164396  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.164399  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164403  4597 caffe.cpp:501] detection_eval = 6.20161
-I0511 11:49:27.164407  4597 caffe.cpp:501] detection_eval = 8.23992
-I0511 11:49:27.164410  4597 caffe.cpp:501] detection_eval = 0.0517857
-I0511 11:49:27.164414  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.164418  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.164422  4597 caffe.cpp:501] detection_eval = 6.20363
-I0511 11:49:27.164425  4597 caffe.cpp:501] detection_eval = 8.28024
-I0511 11:49:27.164429  4597 caffe.cpp:501] detection_eval = 0.0472596
-I0511 11:49:27.164433  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.164436  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.164440  4597 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:49:27.164444  4597 caffe.cpp:501] detection_eval = 8.33065
-I0511 11:49:27.164448  4597 caffe.cpp:501] detection_eval = 0.0494016
-I0511 11:49:27.164451  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.164455  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.164459  4597 caffe.cpp:501] detection_eval = 6.21573
-I0511 11:49:27.164463  4597 caffe.cpp:501] detection_eval = 8.26613
-I0511 11:49:27.164466  4597 caffe.cpp:501] detection_eval = 0.0445944
-I0511 11:49:27.164470  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.164474  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164477  4597 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:49:27.164481  4597 caffe.cpp:501] detection_eval = 8.22782
-I0511 11:49:27.164485  4597 caffe.cpp:501] detection_eval = 0.0461823
-I0511 11:49:27.164489  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.164494  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.164496  4597 caffe.cpp:501] detection_eval = 6.23185
-I0511 11:49:27.164500  4597 caffe.cpp:501] detection_eval = 8.18952
-I0511 11:49:27.164505  4597 caffe.cpp:501] detection_eval = 0.041241
-I0511 11:49:27.164507  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164511  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.164515  4597 caffe.cpp:501] detection_eval = 6.23185
-I0511 11:49:27.164520  4597 caffe.cpp:501] detection_eval = 8.26815
-I0511 11:49:27.164522  4597 caffe.cpp:501] detection_eval = 0.0411695
-I0511 11:49:27.164553  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.164557  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.164562  4597 caffe.cpp:501] detection_eval = 6.2379
-I0511 11:49:27.164566  4597 caffe.cpp:501] detection_eval = 8.29032
-I0511 11:49:27.164569  4597 caffe.cpp:501] detection_eval = 0.0415703
-I0511 11:49:27.164573  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164577  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.164582  4597 caffe.cpp:501] detection_eval = 6.2379
-I0511 11:49:27.164584  4597 caffe.cpp:501] detection_eval = 8.36089
-I0511 11:49:27.164588  4597 caffe.cpp:501] detection_eval = 0.0380232
-I0511 11:49:27.164592  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.164597  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.164599  4597 caffe.cpp:501] detection_eval = 6.24194
-I0511 11:49:27.164602  4597 caffe.cpp:501] detection_eval = 8.35081
-I0511 11:49:27.164607  4597 caffe.cpp:501] detection_eval = 0.0380361
-I0511 11:49:27.164610  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.164614  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.164618  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.164628  4597 caffe.cpp:501] detection_eval = 8.42137
-I0511 11:49:27.164633  4597 caffe.cpp:501] detection_eval = 0.0435461
-I0511 11:49:27.164636  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.164640  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.164644  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.164649  4597 caffe.cpp:501] detection_eval = 8.45363
-I0511 11:49:27.164651  4597 caffe.cpp:501] detection_eval = 0.038644
-I0511 11:49:27.164655  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.164659  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.164662  4597 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:49:27.164666  4597 caffe.cpp:501] detection_eval = 8.52621
-I0511 11:49:27.164670  4597 caffe.cpp:501] detection_eval = 0.0411444
-I0511 11:49:27.164674  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.164678  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.164682  4597 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:49:27.164686  4597 caffe.cpp:501] detection_eval = 8.59073
-I0511 11:49:27.164690  4597 caffe.cpp:501] detection_eval = 0.0423966
-I0511 11:49:27.164693  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.164697  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.164701  4597 caffe.cpp:501] detection_eval = 6.25
-I0511 11:49:27.164705  4597 caffe.cpp:501] detection_eval = 8.625
-I0511 11:49:27.164708  4597 caffe.cpp:501] detection_eval = 0.0414748
-I0511 11:49:27.164712  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.164716  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.164719  4597 caffe.cpp:501] detection_eval = 6.25
-I0511 11:49:27.164723  4597 caffe.cpp:501] detection_eval = 8.70565
-I0511 11:49:27.164727  4597 caffe.cpp:501] detection_eval = 0.047824
-I0511 11:49:27.164731  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.164734  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.164738  4597 caffe.cpp:501] detection_eval = 6.25403
-I0511 11:49:27.164742  4597 caffe.cpp:501] detection_eval = 8.7379
-I0511 11:49:27.164746  4597 caffe.cpp:501] detection_eval = 0.0440503
-I0511 11:49:27.164749  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.164753  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.164757  4597 caffe.cpp:501] detection_eval = 6.25403
-I0511 11:49:27.164760  4597 caffe.cpp:501] detection_eval = 8.84073
-I0511 11:49:27.164764  4597 caffe.cpp:501] detection_eval = 0.043202
-I0511 11:49:27.164768  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.164772  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.164777  4597 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:49:27.164780  4597 caffe.cpp:501] detection_eval = 8.78226
-I0511 11:49:27.164784  4597 caffe.cpp:501] detection_eval = 0.0408459
-I0511 11:49:27.164788  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.164976  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.164983  4597 caffe.cpp:501] detection_eval = 6.27218
-I0511 11:49:27.164988  4597 caffe.cpp:501] detection_eval = 8.66129
-I0511 11:49:27.164991  4597 caffe.cpp:501] detection_eval = 0.0375982
-I0511 11:49:27.164995  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.164999  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165002  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.165006  4597 caffe.cpp:501] detection_eval = 8.71371
-I0511 11:49:27.165010  4597 caffe.cpp:501] detection_eval = 0.0380173
-I0511 11:49:27.165014  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.165017  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165021  4597 caffe.cpp:501] detection_eval = 6.27621
-I0511 11:49:27.165025  4597 caffe.cpp:501] detection_eval = 8.75403
-I0511 11:49:27.165029  4597 caffe.cpp:501] detection_eval = 0.0410263
-I0511 11:49:27.165032  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165036  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165040  4597 caffe.cpp:501] detection_eval = 6.28629
-I0511 11:49:27.165048  4597 caffe.cpp:501] detection_eval = 8.66935
-I0511 11:49:27.165052  4597 caffe.cpp:501] detection_eval = 0.0394351
-I0511 11:49:27.165056  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165060  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.165065  4597 caffe.cpp:501] detection_eval = 6.29032
-I0511 11:49:27.165067  4597 caffe.cpp:501] detection_eval = 8.71169
-I0511 11:49:27.165071  4597 caffe.cpp:501] detection_eval = 0.0424281
-I0511 11:49:27.165076  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.165079  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165082  4597 caffe.cpp:501] detection_eval = 6.29234
-I0511 11:49:27.165086  4597 caffe.cpp:501] detection_eval = 8.75605
-I0511 11:49:27.165091  4597 caffe.cpp:501] detection_eval = 0.0393914
-I0511 11:49:27.165094  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165097  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165102  4597 caffe.cpp:501] detection_eval = 6.29234
-I0511 11:49:27.165105  4597 caffe.cpp:501] detection_eval = 8.82863
-I0511 11:49:27.165109  4597 caffe.cpp:501] detection_eval = 0.0390766
-I0511 11:49:27.165113  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165117  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165120  4597 caffe.cpp:501] detection_eval = 6.29435
-I0511 11:49:27.165124  4597 caffe.cpp:501] detection_eval = 8.89315
-I0511 11:49:27.165128  4597 caffe.cpp:501] detection_eval = 0.0416115
-I0511 11:49:27.165132  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165136  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165139  4597 caffe.cpp:501] detection_eval = 6.29839
-I0511 11:49:27.165143  4597 caffe.cpp:501] detection_eval = 8.875
-I0511 11:49:27.165148  4597 caffe.cpp:501] detection_eval = 0.0403249
-I0511 11:49:27.165151  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.165154  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165158  4597 caffe.cpp:501] detection_eval = 6.3004
-I0511 11:49:27.165161  4597 caffe.cpp:501] detection_eval = 8.90524
-I0511 11:49:27.165165  4597 caffe.cpp:501] detection_eval = 0.0396633
-I0511 11:49:27.165169  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165174  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.165177  4597 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:49:27.165180  4597 caffe.cpp:501] detection_eval = 8.9879
-I0511 11:49:27.165184  4597 caffe.cpp:501] detection_eval = 0.03926
-I0511 11:49:27.165189  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165192  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165195  4597 caffe.cpp:501] detection_eval = 6.30645
-I0511 11:49:27.165199  4597 caffe.cpp:501] detection_eval = 9.03629
-I0511 11:49:27.165204  4597 caffe.cpp:501] detection_eval = 0.0462224
-I0511 11:49:27.165207  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165211  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.165215  4597 caffe.cpp:501] detection_eval = 6.31048
-I0511 11:49:27.165218  4597 caffe.cpp:501] detection_eval = 9.04839
-I0511 11:49:27.165222  4597 caffe.cpp:501] detection_eval = 0.0469885
-I0511 11:49:27.165226  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.165230  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.165233  4597 caffe.cpp:501] detection_eval = 6.3125
-I0511 11:49:27.165237  4597 caffe.cpp:501] detection_eval = 9.05847
-I0511 11:49:27.165241  4597 caffe.cpp:501] detection_eval = 0.0391533
-I0511 11:49:27.165244  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165248  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165252  4597 caffe.cpp:501] detection_eval = 6.3125
-I0511 11:49:27.165256  4597 caffe.cpp:501] detection_eval = 9.13911
-I0511 11:49:27.165259  4597 caffe.cpp:501] detection_eval = 0.0391493
-I0511 11:49:27.165263  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165267  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165274  4597 caffe.cpp:501] detection_eval = 6.31452
-I0511 11:49:27.165278  4597 caffe.cpp:501] detection_eval = 9.18347
-I0511 11:49:27.165282  4597 caffe.cpp:501] detection_eval = 0.0419038
-I0511 11:49:27.165287  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165290  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165294  4597 caffe.cpp:501] detection_eval = 6.31855
-I0511 11:49:27.165298  4597 caffe.cpp:501] detection_eval = 9.24194
-I0511 11:49:27.165302  4597 caffe.cpp:501] detection_eval = 0.047811
-I0511 11:49:27.165305  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.165309  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.165313  4597 caffe.cpp:501] detection_eval = 6.31855
-I0511 11:49:27.165316  4597 caffe.cpp:501] detection_eval = 9.3004
-I0511 11:49:27.165321  4597 caffe.cpp:501] detection_eval = 0.0427403
-I0511 11:49:27.165325  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165328  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165333  4597 caffe.cpp:501] detection_eval = 6.32863
-I0511 11:49:27.165336  4597 caffe.cpp:501] detection_eval = 9.26613
-I0511 11:49:27.165339  4597 caffe.cpp:501] detection_eval = 0.0379645
-I0511 11:49:27.165343  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.165347  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165351  4597 caffe.cpp:501] detection_eval = 6.33065
-I0511 11:49:27.165354  4597 caffe.cpp:501] detection_eval = 9.29839
-I0511 11:49:27.165359  4597 caffe.cpp:501] detection_eval = 0.038076
-I0511 11:49:27.165362  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.165366  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165369  4597 caffe.cpp:501] detection_eval = 6.33871
-I0511 11:49:27.165374  4597 caffe.cpp:501] detection_eval = 9.26008
-I0511 11:49:27.165377  4597 caffe.cpp:501] detection_eval = 0.0373264
-I0511 11:49:27.165381  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165385  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.165388  4597 caffe.cpp:501] detection_eval = 6.34274
-I0511 11:49:27.165391  4597 caffe.cpp:501] detection_eval = 9.27419
-I0511 11:49:27.165395  4597 caffe.cpp:501] detection_eval = 0.0348104
-I0511 11:49:27.165400  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.165403  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.165406  4597 caffe.cpp:501] detection_eval = 6.34274
-I0511 11:49:27.165410  4597 caffe.cpp:501] detection_eval = 9.34073
-I0511 11:49:27.165415  4597 caffe.cpp:501] detection_eval = 0.0386115
-I0511 11:49:27.165418  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165422  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165426  4597 caffe.cpp:501] detection_eval = 6.35282
-I0511 11:49:27.165429  4597 caffe.cpp:501] detection_eval = 9.29032
-I0511 11:49:27.165616  4597 caffe.cpp:501] detection_eval = 0.0444557
-I0511 11:49:27.165621  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.165626  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.165629  4597 caffe.cpp:501] detection_eval = 6.35685
-I0511 11:49:27.165633  4597 caffe.cpp:501] detection_eval = 9.30645
-I0511 11:49:27.165637  4597 caffe.cpp:501] detection_eval = 0.037653
-I0511 11:49:27.165642  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165644  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165648  4597 caffe.cpp:501] detection_eval = 6.36492
-I0511 11:49:27.165652  4597 caffe.cpp:501] detection_eval = 9.26815
-I0511 11:49:27.165655  4597 caffe.cpp:501] detection_eval = 0.0390366
-I0511 11:49:27.165659  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165663  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165668  4597 caffe.cpp:501] detection_eval = 6.36492
-I0511 11:49:27.165670  4597 caffe.cpp:501] detection_eval = 9.35484
-I0511 11:49:27.165674  4597 caffe.cpp:501] detection_eval = 0.0425326
-I0511 11:49:27.165678  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165681  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165689  4597 caffe.cpp:501] detection_eval = 6.36895
-I0511 11:49:27.165694  4597 caffe.cpp:501] detection_eval = 9.37298
-I0511 11:49:27.165697  4597 caffe.cpp:501] detection_eval = 0.0398418
-I0511 11:49:27.165701  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165705  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165709  4597 caffe.cpp:501] detection_eval = 6.37097
-I0511 11:49:27.165712  4597 caffe.cpp:501] detection_eval = 9.42137
-I0511 11:49:27.165716  4597 caffe.cpp:501] detection_eval = 0.043694
-I0511 11:49:27.165720  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165724  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.165727  4597 caffe.cpp:501] detection_eval = 6.375
-I0511 11:49:27.165731  4597 caffe.cpp:501] detection_eval = 9.42742
-I0511 11:49:27.165735  4597 caffe.cpp:501] detection_eval = 0.0458208
-I0511 11:49:27.165738  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165742  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165746  4597 caffe.cpp:501] detection_eval = 6.37702
-I0511 11:49:27.165750  4597 caffe.cpp:501] detection_eval = 9.50403
-I0511 11:49:27.165753  4597 caffe.cpp:501] detection_eval = 0.0450507
-I0511 11:49:27.165757  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165761  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.165765  4597 caffe.cpp:501] detection_eval = 6.37702
-I0511 11:49:27.165768  4597 caffe.cpp:501] detection_eval = 9.57863
-I0511 11:49:27.165772  4597 caffe.cpp:501] detection_eval = 0.0409484
-I0511 11:49:27.165776  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165779  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.165783  4597 caffe.cpp:501] detection_eval = 6.37702
-I0511 11:49:27.165786  4597 caffe.cpp:501] detection_eval = 9.6875
-I0511 11:49:27.165791  4597 caffe.cpp:501] detection_eval = 0.0449141
-I0511 11:49:27.165794  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165797  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.165802  4597 caffe.cpp:501] detection_eval = 6.38508
-I0511 11:49:27.165805  4597 caffe.cpp:501] detection_eval = 9.69355
-I0511 11:49:27.165809  4597 caffe.cpp:501] detection_eval = 0.0414317
-I0511 11:49:27.165812  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.165817  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.165820  4597 caffe.cpp:501] detection_eval = 6.3871
-I0511 11:49:27.165823  4597 caffe.cpp:501] detection_eval = 9.80645
-I0511 11:49:27.165827  4597 caffe.cpp:501] detection_eval = 0.0417695
-I0511 11:49:27.165832  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.165834  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.165838  4597 caffe.cpp:501] detection_eval = 6.39113
-I0511 11:49:27.165843  4597 caffe.cpp:501] detection_eval = 9.8004
-I0511 11:49:27.165846  4597 caffe.cpp:501] detection_eval = 0.0433207
-I0511 11:49:27.165850  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165853  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.165858  4597 caffe.cpp:501] detection_eval = 6.39516
-I0511 11:49:27.165861  4597 caffe.cpp:501] detection_eval = 9.85282
-I0511 11:49:27.165864  4597 caffe.cpp:501] detection_eval = 0.0437603
-I0511 11:49:27.165868  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.165872  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165876  4597 caffe.cpp:501] detection_eval = 6.39718
-I0511 11:49:27.165879  4597 caffe.cpp:501] detection_eval = 9.92944
-I0511 11:49:27.165884  4597 caffe.cpp:501] detection_eval = 0.0469438
-I0511 11:49:27.165887  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165890  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.165894  4597 caffe.cpp:501] detection_eval = 6.39718
-I0511 11:49:27.165899  4597 caffe.cpp:501] detection_eval = 9.99798
-I0511 11:49:27.165902  4597 caffe.cpp:501] detection_eval = 0.0422279
-I0511 11:49:27.165905  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.165913  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.165917  4597 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:49:27.165920  4597 caffe.cpp:501] detection_eval = 9.99194
-I0511 11:49:27.165925  4597 caffe.cpp:501] detection_eval = 0.0505361
-I0511 11:49:27.165928  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.165931  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.165936  4597 caffe.cpp:501] detection_eval = 6.40726
-I0511 11:49:27.165940  4597 caffe.cpp:501] detection_eval = 10.0141
-I0511 11:49:27.165944  4597 caffe.cpp:501] detection_eval = 0.0402911
-I0511 11:49:27.165948  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.165951  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.165956  4597 caffe.cpp:501] detection_eval = 6.41331
-I0511 11:49:27.165959  4597 caffe.cpp:501] detection_eval = 10.0383
-I0511 11:49:27.165963  4597 caffe.cpp:501] detection_eval = 0.0467144
-I0511 11:49:27.165967  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.165971  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.165974  4597 caffe.cpp:501] detection_eval = 6.41935
-I0511 11:49:27.165978  4597 caffe.cpp:501] detection_eval = 10.0222
-I0511 11:49:27.165982  4597 caffe.cpp:501] detection_eval = 0.0429677
-I0511 11:49:27.165987  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.165989  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.165993  4597 caffe.cpp:501] detection_eval = 6.42742
-I0511 11:49:27.165997  4597 caffe.cpp:501] detection_eval = 9.97984
-I0511 11:49:27.166000  4597 caffe.cpp:501] detection_eval = 0.036843
-I0511 11:49:27.166004  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.166008  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.166012  4597 caffe.cpp:501] detection_eval = 6.42742
-I0511 11:49:27.166015  4597 caffe.cpp:501] detection_eval = 10.0786
-I0511 11:49:27.166019  4597 caffe.cpp:501] detection_eval = 0.0435872
-I0511 11:49:27.166023  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166028  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166030  4597 caffe.cpp:501] detection_eval = 6.43145
-I0511 11:49:27.166034  4597 caffe.cpp:501] detection_eval = 10.1028
-I0511 11:49:27.166038  4597 caffe.cpp:501] detection_eval = 0.0429136
-I0511 11:49:27.166043  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166045  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.166049  4597 caffe.cpp:501] detection_eval = 6.43145
-I0511 11:49:27.166054  4597 caffe.cpp:501] detection_eval = 10.1996
-I0511 11:49:27.166057  4597 caffe.cpp:501] detection_eval = 0.0437629
-I0511 11:49:27.166060  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166064  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166257  4597 caffe.cpp:501] detection_eval = 6.43347
-I0511 11:49:27.166263  4597 caffe.cpp:501] detection_eval = 10.244
-I0511 11:49:27.166267  4597 caffe.cpp:501] detection_eval = 0.03941
-I0511 11:49:27.166271  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166275  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.166278  4597 caffe.cpp:501] detection_eval = 6.4375
-I0511 11:49:27.166282  4597 caffe.cpp:501] detection_eval = 10.2762
-I0511 11:49:27.166286  4597 caffe.cpp:501] detection_eval = 0.0405624
-I0511 11:49:27.166290  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166293  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.166297  4597 caffe.cpp:501] detection_eval = 6.44355
-I0511 11:49:27.166301  4597 caffe.cpp:501] detection_eval = 10.2661
-I0511 11:49:27.166306  4597 caffe.cpp:501] detection_eval = 0.0467523
-I0511 11:49:27.166309  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166312  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.166316  4597 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:49:27.166321  4597 caffe.cpp:501] detection_eval = 10.2278
-I0511 11:49:27.166324  4597 caffe.cpp:501] detection_eval = 0.0424976
-I0511 11:49:27.166333  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166337  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166340  4597 caffe.cpp:501] detection_eval = 6.45565
-I0511 11:49:27.166344  4597 caffe.cpp:501] detection_eval = 10.2177
-I0511 11:49:27.166347  4597 caffe.cpp:501] detection_eval = 0.0425759
-I0511 11:49:27.166350  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166354  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.166357  4597 caffe.cpp:501] detection_eval = 6.45565
-I0511 11:49:27.166360  4597 caffe.cpp:501] detection_eval = 10.3206
-I0511 11:49:27.166363  4597 caffe.cpp:501] detection_eval = 0.0432726
-I0511 11:49:27.166366  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166370  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.166373  4597 caffe.cpp:501] detection_eval = 6.46169
-I0511 11:49:27.166376  4597 caffe.cpp:501] detection_eval = 10.3044
-I0511 11:49:27.166379  4597 caffe.cpp:501] detection_eval = 0.0396476
-I0511 11:49:27.166383  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166386  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.166389  4597 caffe.cpp:501] detection_eval = 6.47177
-I0511 11:49:27.166393  4597 caffe.cpp:501] detection_eval = 10.2177
-I0511 11:49:27.166395  4597 caffe.cpp:501] detection_eval = 0.0445121
-I0511 11:49:27.166399  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166402  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166405  4597 caffe.cpp:501] detection_eval = 6.47581
-I0511 11:49:27.166409  4597 caffe.cpp:501] detection_eval = 10.254
-I0511 11:49:27.166412  4597 caffe.cpp:501] detection_eval = 0.0411957
-I0511 11:49:27.166415  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166419  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.166421  4597 caffe.cpp:501] detection_eval = 6.48185
-I0511 11:49:27.166424  4597 caffe.cpp:501] detection_eval = 10.3044
-I0511 11:49:27.166429  4597 caffe.cpp:501] detection_eval = 0.0476864
-I0511 11:49:27.166431  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166435  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.166438  4597 caffe.cpp:501] detection_eval = 6.48387
-I0511 11:49:27.166441  4597 caffe.cpp:501] detection_eval = 10.3367
-I0511 11:49:27.166445  4597 caffe.cpp:501] detection_eval = 0.0436602
-I0511 11:49:27.166447  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166451  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166455  4597 caffe.cpp:501] detection_eval = 6.4879
-I0511 11:49:27.166457  4597 caffe.cpp:501] detection_eval = 10.3891
-I0511 11:49:27.166460  4597 caffe.cpp:501] detection_eval = 0.0480804
-I0511 11:49:27.166465  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166467  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.166471  4597 caffe.cpp:501] detection_eval = 6.49194
-I0511 11:49:27.166474  4597 caffe.cpp:501] detection_eval = 10.4093
-I0511 11:49:27.166477  4597 caffe.cpp:501] detection_eval = 0.0521192
-I0511 11:49:27.166481  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166484  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.166487  4597 caffe.cpp:501] detection_eval = 6.49597
-I0511 11:49:27.166491  4597 caffe.cpp:501] detection_eval = 10.4214
-I0511 11:49:27.166493  4597 caffe.cpp:501] detection_eval = 0.0463212
-I0511 11:49:27.166497  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166501  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.166503  4597 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:49:27.166507  4597 caffe.cpp:501] detection_eval = 10.4577
-I0511 11:49:27.166510  4597 caffe.cpp:501] detection_eval = 0.0438618
-I0511 11:49:27.166513  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166517  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.166519  4597 caffe.cpp:501] detection_eval = 6.5
-I0511 11:49:27.166523  4597 caffe.cpp:501] detection_eval = 10.5565
-I0511 11:49:27.166527  4597 caffe.cpp:501] detection_eval = 0.0417948
-I0511 11:49:27.166533  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166537  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.166540  4597 caffe.cpp:501] detection_eval = 6.50403
-I0511 11:49:27.166543  4597 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:49:27.166546  4597 caffe.cpp:501] detection_eval = 0.0370019
-I0511 11:49:27.166550  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.166553  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.166556  4597 caffe.cpp:501] detection_eval = 6.5121
-I0511 11:49:27.166559  4597 caffe.cpp:501] detection_eval = 10.5464
-I0511 11:49:27.166563  4597 caffe.cpp:501] detection_eval = 0.0423572
-I0511 11:49:27.166566  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.166569  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.166573  4597 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:49:27.166575  4597 caffe.cpp:501] detection_eval = 10.5101
-I0511 11:49:27.166579  4597 caffe.cpp:501] detection_eval = 0.0417664
-I0511 11:49:27.166582  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.166585  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.166589  4597 caffe.cpp:501] detection_eval = 6.52218
-I0511 11:49:27.166592  4597 caffe.cpp:501] detection_eval = 10.5181
-I0511 11:49:27.166595  4597 caffe.cpp:501] detection_eval = 0.0393381
-I0511 11:49:27.166600  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.166604  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.166609  4597 caffe.cpp:501] detection_eval = 6.52823
-I0511 11:49:27.166611  4597 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:49:27.166615  4597 caffe.cpp:501] detection_eval = 0.0440267
-I0511 11:49:27.166618  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.166622  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.166625  4597 caffe.cpp:501] detection_eval = 6.53629
-I0511 11:49:27.166630  4597 caffe.cpp:501] detection_eval = 10.4859
-I0511 11:49:27.166633  4597 caffe.cpp:501] detection_eval = 0.0369024
-I0511 11:49:27.166637  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.166640  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.166645  4597 caffe.cpp:501] detection_eval = 6.53831
-I0511 11:49:27.166648  4597 caffe.cpp:501] detection_eval = 10.5444
-I0511 11:49:27.166652  4597 caffe.cpp:501] detection_eval = 0.0401352
-I0511 11:49:27.166656  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.166661  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.166663  4597 caffe.cpp:501] detection_eval = 6.54234
-I0511 11:49:27.166667  4597 caffe.cpp:501] detection_eval = 10.5827
-I0511 11:49:27.166671  4597 caffe.cpp:501] detection_eval = 0.0389087
-I0511 11:49:27.167176  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167182  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.167186  4597 caffe.cpp:501] detection_eval = 6.54435
-I0511 11:49:27.167189  4597 caffe.cpp:501] detection_eval = 10.6573
-I0511 11:49:27.167193  4597 caffe.cpp:501] detection_eval = 0.0442123
-I0511 11:49:27.167197  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167201  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167206  4597 caffe.cpp:501] detection_eval = 6.54637
-I0511 11:49:27.167208  4597 caffe.cpp:501] detection_eval = 10.6875
-I0511 11:49:27.167212  4597 caffe.cpp:501] detection_eval = 0.0392356
-I0511 11:49:27.167217  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167220  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167224  4597 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:49:27.167227  4597 caffe.cpp:501] detection_eval = 10.6673
-I0511 11:49:27.167232  4597 caffe.cpp:501] detection_eval = 0.0412143
-I0511 11:49:27.167235  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167239  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167243  4597 caffe.cpp:501] detection_eval = 6.55645
-I0511 11:49:27.167246  4597 caffe.cpp:501] detection_eval = 10.6532
-I0511 11:49:27.167254  4597 caffe.cpp:501] detection_eval = 0.0370152
-I0511 11:49:27.167258  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167263  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167266  4597 caffe.cpp:501] detection_eval = 6.55847
-I0511 11:49:27.167269  4597 caffe.cpp:501] detection_eval = 10.7399
-I0511 11:49:27.167273  4597 caffe.cpp:501] detection_eval = 0.0377675
-I0511 11:49:27.167277  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167281  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167284  4597 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:49:27.167289  4597 caffe.cpp:501] detection_eval = 10.752
-I0511 11:49:27.167292  4597 caffe.cpp:501] detection_eval = 0.0435966
-I0511 11:49:27.167296  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167299  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167304  4597 caffe.cpp:501] detection_eval = 6.56653
-I0511 11:49:27.167307  4597 caffe.cpp:501] detection_eval = 10.8206
-I0511 11:49:27.167311  4597 caffe.cpp:501] detection_eval = 0.0392458
-I0511 11:49:27.167315  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167318  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167322  4597 caffe.cpp:501] detection_eval = 6.56855
-I0511 11:49:27.167325  4597 caffe.cpp:501] detection_eval = 10.8468
-I0511 11:49:27.167330  4597 caffe.cpp:501] detection_eval = 0.0400146
-I0511 11:49:27.167333  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167337  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.167341  4597 caffe.cpp:501] detection_eval = 6.5746
-I0511 11:49:27.167345  4597 caffe.cpp:501] detection_eval = 10.8488
-I0511 11:49:27.167348  4597 caffe.cpp:501] detection_eval = 0.0424466
-I0511 11:49:27.167352  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.167356  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.167361  4597 caffe.cpp:501] detection_eval = 6.58669
-I0511 11:49:27.167363  4597 caffe.cpp:501] detection_eval = 10.7399
-I0511 11:49:27.167367  4597 caffe.cpp:501] detection_eval = 0.0352173
-I0511 11:49:27.167371  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.167376  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.167378  4597 caffe.cpp:501] detection_eval = 6.59274
-I0511 11:49:27.167382  4597 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:49:27.167387  4597 caffe.cpp:501] detection_eval = 0.0463454
-I0511 11:49:27.167390  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.167393  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.167397  4597 caffe.cpp:501] detection_eval = 6.59476
-I0511 11:49:27.167402  4597 caffe.cpp:501] detection_eval = 10.8569
-I0511 11:49:27.167405  4597 caffe.cpp:501] detection_eval = 0.0412809
-I0511 11:49:27.167409  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167413  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167418  4597 caffe.cpp:501] detection_eval = 6.59677
-I0511 11:49:27.167420  4597 caffe.cpp:501] detection_eval = 10.8891
-I0511 11:49:27.167424  4597 caffe.cpp:501] detection_eval = 0.0431516
-I0511 11:49:27.167428  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167433  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.167435  4597 caffe.cpp:501] detection_eval = 6.59879
-I0511 11:49:27.167439  4597 caffe.cpp:501] detection_eval = 10.9395
-I0511 11:49:27.167443  4597 caffe.cpp:501] detection_eval = 0.0393903
-I0511 11:49:27.167448  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167450  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167454  4597 caffe.cpp:501] detection_eval = 6.60282
-I0511 11:49:27.167459  4597 caffe.cpp:501] detection_eval = 10.9698
-I0511 11:49:27.167462  4597 caffe.cpp:501] detection_eval = 0.0453448
-I0511 11:49:27.167465  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.167469  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.167474  4597 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:49:27.167476  4597 caffe.cpp:501] detection_eval = 11.0222
-I0511 11:49:27.167484  4597 caffe.cpp:501] detection_eval = 0.0449609
-I0511 11:49:27.167488  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.167492  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.167495  4597 caffe.cpp:501] detection_eval = 6.61089
-I0511 11:49:27.167500  4597 caffe.cpp:501] detection_eval = 10.994
-I0511 11:49:27.167503  4597 caffe.cpp:501] detection_eval = 0.0387491
-I0511 11:49:27.167507  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.167511  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167515  4597 caffe.cpp:501] detection_eval = 6.61089
-I0511 11:49:27.167520  4597 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:49:27.167523  4597 caffe.cpp:501] detection_eval = 0.0465081
-I0511 11:49:27.167527  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.167531  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.167534  4597 caffe.cpp:501] detection_eval = 6.6129
-I0511 11:49:27.167538  4597 caffe.cpp:501] detection_eval = 11.1573
-I0511 11:49:27.167542  4597 caffe.cpp:501] detection_eval = 0.0376537
-I0511 11:49:27.167546  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167549  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167553  4597 caffe.cpp:501] detection_eval = 6.61492
-I0511 11:49:27.167557  4597 caffe.cpp:501] detection_eval = 11.1794
-I0511 11:49:27.167562  4597 caffe.cpp:501] detection_eval = 0.0362195
-I0511 11:49:27.167564  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.167568  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.167572  4597 caffe.cpp:501] detection_eval = 6.61895
-I0511 11:49:27.167575  4597 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:49:27.167579  4597 caffe.cpp:501] detection_eval = 0.037401
-I0511 11:49:27.167583  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167587  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167590  4597 caffe.cpp:501] detection_eval = 6.62298
-I0511 11:49:27.167594  4597 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:49:27.167598  4597 caffe.cpp:501] detection_eval = 0.0384131
-I0511 11:49:27.167603  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167606  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.167609  4597 caffe.cpp:501] detection_eval = 6.62903
-I0511 11:49:27.167613  4597 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:49:27.167618  4597 caffe.cpp:501] detection_eval = 0.0406666
-I0511 11:49:27.167621  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167624  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167629  4597 caffe.cpp:501] detection_eval = 6.63105
-I0511 11:49:27.167801  4597 caffe.cpp:501] detection_eval = 11.244
-I0511 11:49:27.167806  4597 caffe.cpp:501] detection_eval = 0.0376225
-I0511 11:49:27.167810  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167814  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167819  4597 caffe.cpp:501] detection_eval = 6.63105
-I0511 11:49:27.167822  4597 caffe.cpp:501] detection_eval = 11.3327
-I0511 11:49:27.167826  4597 caffe.cpp:501] detection_eval = 0.0416811
-I0511 11:49:27.167830  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167834  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167837  4597 caffe.cpp:501] detection_eval = 6.63911
-I0511 11:49:27.167841  4597 caffe.cpp:501] detection_eval = 11.3065
-I0511 11:49:27.167845  4597 caffe.cpp:501] detection_eval = 0.0433205
-I0511 11:49:27.167848  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.167852  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.167856  4597 caffe.cpp:501] detection_eval = 6.64516
-I0511 11:49:27.167860  4597 caffe.cpp:501] detection_eval = 11.2681
-I0511 11:49:27.167865  4597 caffe.cpp:501] detection_eval = 0.0380282
-I0511 11:49:27.167867  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.167871  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167876  4597 caffe.cpp:501] detection_eval = 6.64718
-I0511 11:49:27.167883  4597 caffe.cpp:501] detection_eval = 11.256
-I0511 11:49:27.167887  4597 caffe.cpp:501] detection_eval = 0.0357891
-I0511 11:49:27.167891  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.167896  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167898  4597 caffe.cpp:501] detection_eval = 6.65524
-I0511 11:49:27.167902  4597 caffe.cpp:501] detection_eval = 11.2117
-I0511 11:49:27.167906  4597 caffe.cpp:501] detection_eval = 0.0388631
-I0511 11:49:27.167910  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167914  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167917  4597 caffe.cpp:501] detection_eval = 6.65927
-I0511 11:49:27.167922  4597 caffe.cpp:501] detection_eval = 11.2056
-I0511 11:49:27.167925  4597 caffe.cpp:501] detection_eval = 0.0361406
-I0511 11:49:27.167929  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167932  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167937  4597 caffe.cpp:501] detection_eval = 6.66331
-I0511 11:49:27.167940  4597 caffe.cpp:501] detection_eval = 11.2379
-I0511 11:49:27.167944  4597 caffe.cpp:501] detection_eval = 0.03999
-I0511 11:49:27.167948  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.167951  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.167955  4597 caffe.cpp:501] detection_eval = 6.66734
-I0511 11:49:27.167959  4597 caffe.cpp:501] detection_eval = 11.3024
-I0511 11:49:27.167963  4597 caffe.cpp:501] detection_eval = 0.0418456
-I0511 11:49:27.167968  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.167970  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.167974  4597 caffe.cpp:501] detection_eval = 6.67339
-I0511 11:49:27.167979  4597 caffe.cpp:501] detection_eval = 11.2883
-I0511 11:49:27.167982  4597 caffe.cpp:501] detection_eval = 0.0403524
-I0511 11:49:27.167986  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.167989  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.167994  4597 caffe.cpp:501] detection_eval = 6.67944
-I0511 11:49:27.167997  4597 caffe.cpp:501] detection_eval = 11.252
-I0511 11:49:27.168001  4597 caffe.cpp:501] detection_eval = 0.0454081
-I0511 11:49:27.168004  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.168009  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.168012  4597 caffe.cpp:501] detection_eval = 6.68145
-I0511 11:49:27.168015  4597 caffe.cpp:501] detection_eval = 11.3024
-I0511 11:49:27.168020  4597 caffe.cpp:501] detection_eval = 0.0455169
-I0511 11:49:27.168023  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.168027  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.168031  4597 caffe.cpp:501] detection_eval = 6.68347
-I0511 11:49:27.168035  4597 caffe.cpp:501] detection_eval = 11.3569
-I0511 11:49:27.168040  4597 caffe.cpp:501] detection_eval = 0.0395973
-I0511 11:49:27.168042  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168046  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168051  4597 caffe.cpp:501] detection_eval = 6.69153
-I0511 11:49:27.168053  4597 caffe.cpp:501] detection_eval = 11.2944
-I0511 11:49:27.168057  4597 caffe.cpp:501] detection_eval = 0.037244
-I0511 11:49:27.168061  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.168066  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.168069  4597 caffe.cpp:501] detection_eval = 6.69355
-I0511 11:49:27.168072  4597 caffe.cpp:501] detection_eval = 11.3548
-I0511 11:49:27.168076  4597 caffe.cpp:501] detection_eval = 0.0397247
-I0511 11:49:27.168081  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168084  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.168088  4597 caffe.cpp:501] detection_eval = 6.69758
-I0511 11:49:27.168092  4597 caffe.cpp:501] detection_eval = 11.3911
-I0511 11:49:27.168095  4597 caffe.cpp:501] detection_eval = 0.0389596
-I0511 11:49:27.168099  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168102  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.168109  4597 caffe.cpp:501] detection_eval = 6.70161
-I0511 11:49:27.168113  4597 caffe.cpp:501] detection_eval = 11.4173
-I0511 11:49:27.168118  4597 caffe.cpp:501] detection_eval = 0.0396886
-I0511 11:49:27.168121  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168125  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168129  4597 caffe.cpp:501] detection_eval = 6.70968
-I0511 11:49:27.168133  4597 caffe.cpp:501] detection_eval = 11.4012
-I0511 11:49:27.168136  4597 caffe.cpp:501] detection_eval = 0.0414539
-I0511 11:49:27.168140  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168144  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168148  4597 caffe.cpp:501] detection_eval = 6.71371
-I0511 11:49:27.168151  4597 caffe.cpp:501] detection_eval = 11.3931
-I0511 11:49:27.168156  4597 caffe.cpp:501] detection_eval = 0.0399272
-I0511 11:49:27.168159  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168164  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168167  4597 caffe.cpp:501] detection_eval = 6.71573
-I0511 11:49:27.168171  4597 caffe.cpp:501] detection_eval = 11.4173
-I0511 11:49:27.168174  4597 caffe.cpp:501] detection_eval = 0.0440318
-I0511 11:49:27.168179  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.168182  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.168186  4597 caffe.cpp:501] detection_eval = 6.71774
-I0511 11:49:27.168190  4597 caffe.cpp:501] detection_eval = 11.4335
-I0511 11:49:27.168193  4597 caffe.cpp:501] detection_eval = 0.0372345
-I0511 11:49:27.168197  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.168200  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168205  4597 caffe.cpp:501] detection_eval = 6.72782
-I0511 11:49:27.168208  4597 caffe.cpp:501] detection_eval = 11.3468
-I0511 11:49:27.168212  4597 caffe.cpp:501] detection_eval = 0.040946
-I0511 11:49:27.168216  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.168220  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168223  4597 caffe.cpp:501] detection_eval = 6.72782
-I0511 11:49:27.168227  4597 caffe.cpp:501] detection_eval = 11.4194
-I0511 11:49:27.168231  4597 caffe.cpp:501] detection_eval = 0.0395217
-I0511 11:49:27.168234  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168238  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168242  4597 caffe.cpp:501] detection_eval = 6.73185
-I0511 11:49:27.168246  4597 caffe.cpp:501] detection_eval = 11.4859
-I0511 11:49:27.168249  4597 caffe.cpp:501] detection_eval = 0.0395931
-I0511 11:49:27.168253  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.168439  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.168444  4597 caffe.cpp:501] detection_eval = 6.73387
-I0511 11:49:27.168448  4597 caffe.cpp:501] detection_eval = 11.5302
-I0511 11:49:27.168452  4597 caffe.cpp:501] detection_eval = 0.0451198
-I0511 11:49:27.168457  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.168460  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.168464  4597 caffe.cpp:501] detection_eval = 6.73589
-I0511 11:49:27.168467  4597 caffe.cpp:501] detection_eval = 11.5605
-I0511 11:49:27.168471  4597 caffe.cpp:501] detection_eval = 0.0444733
-I0511 11:49:27.168475  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.168479  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.168483  4597 caffe.cpp:501] detection_eval = 6.74395
-I0511 11:49:27.168486  4597 caffe.cpp:501] detection_eval = 11.5625
-I0511 11:49:27.168490  4597 caffe.cpp:501] detection_eval = 0.0427075
-I0511 11:49:27.168494  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168498  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168501  4597 caffe.cpp:501] detection_eval = 6.75202
-I0511 11:49:27.168505  4597 caffe.cpp:501] detection_eval = 11.5625
-I0511 11:49:27.168509  4597 caffe.cpp:501] detection_eval = 0.0470093
-I0511 11:49:27.168514  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168516  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168541  4597 caffe.cpp:501] detection_eval = 6.75403
-I0511 11:49:27.168545  4597 caffe.cpp:501] detection_eval = 11.6089
-I0511 11:49:27.168550  4597 caffe.cpp:501] detection_eval = 0.0426307
-I0511 11:49:27.168553  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168557  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.168561  4597 caffe.cpp:501] detection_eval = 6.75806
-I0511 11:49:27.168565  4597 caffe.cpp:501] detection_eval = 11.5847
-I0511 11:49:27.168570  4597 caffe.cpp:501] detection_eval = 0.0393675
-I0511 11:49:27.168572  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168576  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168581  4597 caffe.cpp:501] detection_eval = 6.76411
-I0511 11:49:27.168584  4597 caffe.cpp:501] detection_eval = 11.5746
-I0511 11:49:27.168588  4597 caffe.cpp:501] detection_eval = 0.0448684
-I0511 11:49:27.168591  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.168596  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.168599  4597 caffe.cpp:501] detection_eval = 6.77016
-I0511 11:49:27.168602  4597 caffe.cpp:501] detection_eval = 11.5403
-I0511 11:49:27.168606  4597 caffe.cpp:501] detection_eval = 0.0388882
-I0511 11:49:27.168611  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168614  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.168617  4597 caffe.cpp:501] detection_eval = 6.77016
-I0511 11:49:27.168622  4597 caffe.cpp:501] detection_eval = 11.625
-I0511 11:49:27.168625  4597 caffe.cpp:501] detection_eval = 0.0390283
-I0511 11:49:27.168629  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168633  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168637  4597 caffe.cpp:501] detection_eval = 6.77218
-I0511 11:49:27.168640  4597 caffe.cpp:501] detection_eval = 11.6431
-I0511 11:49:27.168644  4597 caffe.cpp:501] detection_eval = 0.0379601
-I0511 11:49:27.168648  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.168651  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.168655  4597 caffe.cpp:501] detection_eval = 6.77621
-I0511 11:49:27.168659  4597 caffe.cpp:501] detection_eval = 11.6633
-I0511 11:49:27.168663  4597 caffe.cpp:501] detection_eval = 0.0393689
-I0511 11:49:27.168666  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.168670  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168674  4597 caffe.cpp:501] detection_eval = 6.78427
-I0511 11:49:27.168678  4597 caffe.cpp:501] detection_eval = 11.629
-I0511 11:49:27.168682  4597 caffe.cpp:501] detection_eval = 0.0439522
-I0511 11:49:27.168686  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168690  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168694  4597 caffe.cpp:501] detection_eval = 6.78831
-I0511 11:49:27.168697  4597 caffe.cpp:501] detection_eval = 11.6391
-I0511 11:49:27.168701  4597 caffe.cpp:501] detection_eval = 0.0405236
-I0511 11:49:27.168705  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168709  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168712  4597 caffe.cpp:501] detection_eval = 6.78831
-I0511 11:49:27.168716  4597 caffe.cpp:501] detection_eval = 11.6996
-I0511 11:49:27.168720  4597 caffe.cpp:501] detection_eval = 0.0362257
-I0511 11:49:27.168723  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.168727  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.168731  4597 caffe.cpp:501] detection_eval = 6.79637
-I0511 11:49:27.168735  4597 caffe.cpp:501] detection_eval = 11.629
-I0511 11:49:27.168740  4597 caffe.cpp:501] detection_eval = 0.0355739
-I0511 11:49:27.168742  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.168746  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.168751  4597 caffe.cpp:501] detection_eval = 6.8004
-I0511 11:49:27.168753  4597 caffe.cpp:501] detection_eval = 11.6452
-I0511 11:49:27.168757  4597 caffe.cpp:501] detection_eval = 0.0378909
-I0511 11:49:27.168761  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.168769  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.168773  4597 caffe.cpp:501] detection_eval = 6.80444
-I0511 11:49:27.168777  4597 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:49:27.168781  4597 caffe.cpp:501] detection_eval = 0.0469753
-I0511 11:49:27.168784  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.168788  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168792  4597 caffe.cpp:501] detection_eval = 6.80847
-I0511 11:49:27.168795  4597 caffe.cpp:501] detection_eval = 11.6875
-I0511 11:49:27.168800  4597 caffe.cpp:501] detection_eval = 0.0398264
-I0511 11:49:27.168804  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.168807  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.168812  4597 caffe.cpp:501] detection_eval = 6.80847
-I0511 11:49:27.168815  4597 caffe.cpp:501] detection_eval = 11.7944
-I0511 11:49:27.168819  4597 caffe.cpp:501] detection_eval = 0.0426049
-I0511 11:49:27.168823  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.168826  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168830  4597 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:49:27.168834  4597 caffe.cpp:501] detection_eval = 11.8226
-I0511 11:49:27.168838  4597 caffe.cpp:501] detection_eval = 0.0409968
-I0511 11:49:27.168841  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168845  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168848  4597 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:49:27.168853  4597 caffe.cpp:501] detection_eval = 11.875
-I0511 11:49:27.168856  4597 caffe.cpp:501] detection_eval = 0.0380478
-I0511 11:49:27.168860  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168864  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.168867  4597 caffe.cpp:501] detection_eval = 6.82258
-I0511 11:49:27.168871  4597 caffe.cpp:501] detection_eval = 11.7802
-I0511 11:49:27.168875  4597 caffe.cpp:501] detection_eval = 0.043771
-I0511 11:49:27.168879  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.168884  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.168886  4597 caffe.cpp:501] detection_eval = 6.82863
-I0511 11:49:27.168890  4597 caffe.cpp:501] detection_eval = 11.7863
-I0511 11:49:27.168895  4597 caffe.cpp:501] detection_eval = 0.0417161
-I0511 11:49:27.168898  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.168901  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.168905  4597 caffe.cpp:501] detection_eval = 6.83266
-I0511 11:49:27.168910  4597 caffe.cpp:501] detection_eval = 11.7802
-I0511 11:49:27.169088  4597 caffe.cpp:501] detection_eval = 0.0366694
-I0511 11:49:27.169095  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169098  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.169101  4597 caffe.cpp:501] detection_eval = 6.83871
-I0511 11:49:27.169106  4597 caffe.cpp:501] detection_eval = 11.8024
-I0511 11:49:27.169109  4597 caffe.cpp:501] detection_eval = 0.0368604
-I0511 11:49:27.169113  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169117  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169121  4597 caffe.cpp:501] detection_eval = 6.84274
-I0511 11:49:27.169124  4597 caffe.cpp:501] detection_eval = 11.8185
-I0511 11:49:27.169128  4597 caffe.cpp:501] detection_eval = 0.037931
-I0511 11:49:27.169132  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169137  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.169139  4597 caffe.cpp:501] detection_eval = 6.84274
-I0511 11:49:27.169143  4597 caffe.cpp:501] detection_eval = 11.8609
-I0511 11:49:27.169147  4597 caffe.cpp:501] detection_eval = 0.0346255
-I0511 11:49:27.169152  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.169155  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.169158  4597 caffe.cpp:501] detection_eval = 6.85081
-I0511 11:49:27.169162  4597 caffe.cpp:501] detection_eval = 11.8065
-I0511 11:49:27.169167  4597 caffe.cpp:501] detection_eval = 0.0420333
-I0511 11:49:27.169174  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.169178  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169183  4597 caffe.cpp:501] detection_eval = 6.85887
-I0511 11:49:27.169185  4597 caffe.cpp:501] detection_eval = 11.7843
-I0511 11:49:27.169189  4597 caffe.cpp:501] detection_eval = 0.0397865
-I0511 11:49:27.169193  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169198  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.169200  4597 caffe.cpp:501] detection_eval = 6.86492
-I0511 11:49:27.169204  4597 caffe.cpp:501] detection_eval = 11.7802
-I0511 11:49:27.169209  4597 caffe.cpp:501] detection_eval = 0.0382312
-I0511 11:49:27.169212  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.169216  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.169219  4597 caffe.cpp:501] detection_eval = 6.87097
-I0511 11:49:27.169224  4597 caffe.cpp:501] detection_eval = 11.7923
-I0511 11:49:27.169227  4597 caffe.cpp:501] detection_eval = 0.0417241
-I0511 11:49:27.169230  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169234  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.169239  4597 caffe.cpp:501] detection_eval = 6.875
-I0511 11:49:27.169242  4597 caffe.cpp:501] detection_eval = 11.8669
-I0511 11:49:27.169245  4597 caffe.cpp:501] detection_eval = 0.0417634
-I0511 11:49:27.169250  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169253  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.169257  4597 caffe.cpp:501] detection_eval = 6.87702
-I0511 11:49:27.169260  4597 caffe.cpp:501] detection_eval = 11.9294
-I0511 11:49:27.169265  4597 caffe.cpp:501] detection_eval = 0.040084
-I0511 11:49:27.169268  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.169272  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169275  4597 caffe.cpp:501] detection_eval = 6.87903
-I0511 11:49:27.169279  4597 caffe.cpp:501] detection_eval = 11.9597
-I0511 11:49:27.169283  4597 caffe.cpp:501] detection_eval = 0.0393739
-I0511 11:49:27.169287  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169291  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169294  4597 caffe.cpp:501] detection_eval = 6.88105
-I0511 11:49:27.169298  4597 caffe.cpp:501] detection_eval = 12.0101
-I0511 11:49:27.169302  4597 caffe.cpp:501] detection_eval = 0.0377377
-I0511 11:49:27.169306  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169309  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.169313  4597 caffe.cpp:501] detection_eval = 6.89113
-I0511 11:49:27.169317  4597 caffe.cpp:501] detection_eval = 11.9657
-I0511 11:49:27.169322  4597 caffe.cpp:501] detection_eval = 0.039285
-I0511 11:49:27.169325  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.169329  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.169332  4597 caffe.cpp:501] detection_eval = 6.89315
-I0511 11:49:27.169337  4597 caffe.cpp:501] detection_eval = 12.0242
-I0511 11:49:27.169340  4597 caffe.cpp:501] detection_eval = 0.0362258
-I0511 11:49:27.169344  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.169348  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169351  4597 caffe.cpp:501] detection_eval = 6.89718
-I0511 11:49:27.169355  4597 caffe.cpp:501] detection_eval = 12.0464
-I0511 11:49:27.169359  4597 caffe.cpp:501] detection_eval = 0.040422
-I0511 11:49:27.169363  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.169366  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169370  4597 caffe.cpp:501] detection_eval = 6.89919
-I0511 11:49:27.169374  4597 caffe.cpp:501] detection_eval = 12.0806
-I0511 11:49:27.169378  4597 caffe.cpp:501] detection_eval = 0.0369308
-I0511 11:49:27.169381  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.169385  4597 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:49:27.169389  4597 caffe.cpp:501] detection_eval = 6.90726
-I0511 11:49:27.169392  4597 caffe.cpp:501] detection_eval = 12.0121
-I0511 11:49:27.169396  4597 caffe.cpp:501] detection_eval = 0.0395874
-I0511 11:49:27.169404  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.169407  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169411  4597 caffe.cpp:501] detection_eval = 6.91129
-I0511 11:49:27.169415  4597 caffe.cpp:501] detection_eval = 12.0121
-I0511 11:49:27.169420  4597 caffe.cpp:501] detection_eval = 0.041466
-I0511 11:49:27.169422  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169426  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169430  4597 caffe.cpp:501] detection_eval = 6.91734
-I0511 11:49:27.169435  4597 caffe.cpp:501] detection_eval = 11.9778
-I0511 11:49:27.169438  4597 caffe.cpp:501] detection_eval = 0.0398929
-I0511 11:49:27.169441  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169445  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.169450  4597 caffe.cpp:501] detection_eval = 6.91935
-I0511 11:49:27.169453  4597 caffe.cpp:501] detection_eval = 12.002
-I0511 11:49:27.169457  4597 caffe.cpp:501] detection_eval = 0.0376612
-I0511 11:49:27.169461  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.169464  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.169468  4597 caffe.cpp:501] detection_eval = 6.92944
-I0511 11:49:27.169472  4597 caffe.cpp:501] detection_eval = 11.9456
-I0511 11:49:27.169476  4597 caffe.cpp:501] detection_eval = 0.0462506
-I0511 11:49:27.169479  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.169483  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.169487  4597 caffe.cpp:501] detection_eval = 6.93548
-I0511 11:49:27.169492  4597 caffe.cpp:501] detection_eval = 11.9738
-I0511 11:49:27.169495  4597 caffe.cpp:501] detection_eval = 0.0432693
-I0511 11:49:27.169498  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.169502  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.169507  4597 caffe.cpp:501] detection_eval = 6.9375
-I0511 11:49:27.169509  4597 caffe.cpp:501] detection_eval = 12.0141
-I0511 11:49:27.169513  4597 caffe.cpp:501] detection_eval = 0.0364303
-I0511 11:49:27.169517  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.169522  4597 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:49:27.169525  4597 caffe.cpp:501] detection_eval = 6.94355
-I0511 11:49:27.169528  4597 caffe.cpp:501] detection_eval = 12.0141
-I0511 11:49:27.169533  4597 caffe.cpp:501] detection_eval = 0.0472611
-I0511 11:49:27.169536  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.169540  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.172562  4597 caffe.cpp:501] detection_eval = 6.94355
-I0511 11:49:27.172579  4597 caffe.cpp:501] detection_eval = 12.0625
-I0511 11:49:27.172582  4597 caffe.cpp:501] detection_eval = 0.0390168
-I0511 11:49:27.172585  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172587  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.172590  4597 caffe.cpp:501] detection_eval = 6.94556
-I0511 11:49:27.172591  4597 caffe.cpp:501] detection_eval = 12.1149
-I0511 11:49:27.172595  4597 caffe.cpp:501] detection_eval = 0.0399723
-I0511 11:49:27.172596  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172598  4597 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:49:27.172600  4597 caffe.cpp:501] detection_eval = 6.94758
-I0511 11:49:27.172602  4597 caffe.cpp:501] detection_eval = 12.1532
-I0511 11:49:27.172605  4597 caffe.cpp:501] detection_eval = 0.045016
-I0511 11:49:27.172607  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.172610  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.172611  4597 caffe.cpp:501] detection_eval = 6.95161
-I0511 11:49:27.172613  4597 caffe.cpp:501] detection_eval = 12.1573
-I0511 11:49:27.172616  4597 caffe.cpp:501] detection_eval = 0.0391619
-I0511 11:49:27.172621  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172623  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.172627  4597 caffe.cpp:501] detection_eval = 6.95363
-I0511 11:49:27.172631  4597 caffe.cpp:501] detection_eval = 12.2238
-I0511 11:49:27.172644  4597 caffe.cpp:501] detection_eval = 0.0420103
-I0511 11:49:27.172649  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.172652  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.172654  4597 caffe.cpp:501] detection_eval = 6.96169
-I0511 11:49:27.172657  4597 caffe.cpp:501] detection_eval = 12.2097
-I0511 11:49:27.172659  4597 caffe.cpp:501] detection_eval = 0.0436526
-I0511 11:49:27.172662  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172663  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.172665  4597 caffe.cpp:501] detection_eval = 6.96573
-I0511 11:49:27.172667  4597 caffe.cpp:501] detection_eval = 12.256
-I0511 11:49:27.172670  4597 caffe.cpp:501] detection_eval = 0.0421588
-I0511 11:49:27.172672  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172674  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.172677  4597 caffe.cpp:501] detection_eval = 6.95363
-I0511 11:49:27.172678  4597 caffe.cpp:501] detection_eval = 12.254
-I0511 11:49:27.172682  4597 caffe.cpp:501] detection_eval = 0.0394665
-I0511 11:49:27.172683  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172685  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.172688  4597 caffe.cpp:501] detection_eval = 6.93548
-I0511 11:49:27.172689  4597 caffe.cpp:501] detection_eval = 12.3609
-I0511 11:49:27.172691  4597 caffe.cpp:501] detection_eval = 0.0459468
-I0511 11:49:27.172693  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.172695  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.172698  4597 caffe.cpp:501] detection_eval = 6.94355
-I0511 11:49:27.172700  4597 caffe.cpp:501] detection_eval = 12.3407
-I0511 11:49:27.172703  4597 caffe.cpp:501] detection_eval = 0.0409542
-I0511 11:49:27.172704  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172706  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.172708  4597 caffe.cpp:501] detection_eval = 6.94758
-I0511 11:49:27.172710  4597 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:49:27.172713  4597 caffe.cpp:501] detection_eval = 0.0426733
-I0511 11:49:27.172715  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172718  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.172719  4597 caffe.cpp:501] detection_eval = 6.95565
-I0511 11:49:27.172722  4597 caffe.cpp:501] detection_eval = 12.4012
-I0511 11:49:27.172726  4597 caffe.cpp:501] detection_eval = 0.0403951
-I0511 11:49:27.172730  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172742  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.172747  4597 caffe.cpp:501] detection_eval = 7.23185
-I0511 11:49:27.172751  4597 caffe.cpp:501] detection_eval = 8.34879
-I0511 11:49:27.172755  4597 caffe.cpp:501] detection_eval = 0.0834918
-I0511 11:49:27.172758  4597 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:49:27.172762  4597 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:49:27.172765  4597 caffe.cpp:501] detection_eval = 7.23589
-I0511 11:49:27.172770  4597 caffe.cpp:501] detection_eval = 8.40323
-I0511 11:49:27.172772  4597 caffe.cpp:501] detection_eval = 0.0517371
-I0511 11:49:27.172777  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.172781  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.172785  4597 caffe.cpp:501] detection_eval = 7.2379
-I0511 11:49:27.172788  4597 caffe.cpp:501] detection_eval = 8.53024
-I0511 11:49:27.172791  4597 caffe.cpp:501] detection_eval = 0.0466181
-I0511 11:49:27.172796  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.172798  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.172801  4597 caffe.cpp:501] detection_eval = 7.24194
-I0511 11:49:27.172806  4597 caffe.cpp:501] detection_eval = 8.5625
-I0511 11:49:27.172809  4597 caffe.cpp:501] detection_eval = 0.043981
-I0511 11:49:27.172812  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.172816  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.172821  4597 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:49:27.172823  4597 caffe.cpp:501] detection_eval = 8.57661
-I0511 11:49:27.172832  4597 caffe.cpp:501] detection_eval = 0.0444849
-I0511 11:49:27.172837  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172847  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.172850  4597 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:49:27.172853  4597 caffe.cpp:501] detection_eval = 8.65121
-I0511 11:49:27.172857  4597 caffe.cpp:501] detection_eval = 0.0417519
-I0511 11:49:27.172861  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172864  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.172868  4597 caffe.cpp:501] detection_eval = 7.24798
-I0511 11:49:27.172873  4597 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:49:27.172875  4597 caffe.cpp:501] detection_eval = 0.042867
-I0511 11:49:27.172879  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172883  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.172885  4597 caffe.cpp:501] detection_eval = 7.25806
-I0511 11:49:27.172889  4597 caffe.cpp:501] detection_eval = 8.60282
-I0511 11:49:27.172893  4597 caffe.cpp:501] detection_eval = 0.0427657
-I0511 11:49:27.172896  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.172900  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.172904  4597 caffe.cpp:501] detection_eval = 7.26815
-I0511 11:49:27.172907  4597 caffe.cpp:501] detection_eval = 8.55847
-I0511 11:49:27.172911  4597 caffe.cpp:501] detection_eval = 0.0481058
-I0511 11:49:27.172914  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.172919  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.172922  4597 caffe.cpp:501] detection_eval = 7.27419
-I0511 11:49:27.172925  4597 caffe.cpp:501] detection_eval = 8.53024
-I0511 11:49:27.172930  4597 caffe.cpp:501] detection_eval = 0.0418924
-I0511 11:49:27.172933  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.172936  4597 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:49:27.172940  4597 caffe.cpp:501] detection_eval = 7.27419
-I0511 11:49:27.172945  4597 caffe.cpp:501] detection_eval = 8.63306
-I0511 11:49:27.172947  4597 caffe.cpp:501] detection_eval = 0.0396848
-I0511 11:49:27.172951  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.172955  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.172958  4597 caffe.cpp:501] detection_eval = 7.27621
-I0511 11:49:27.172962  4597 caffe.cpp:501] detection_eval = 8.69758
-I0511 11:49:27.172966  4597 caffe.cpp:501] detection_eval = 0.0444746
-I0511 11:49:27.172969  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.172972  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.172976  4597 caffe.cpp:501] detection_eval = 7.27823
-I0511 11:49:27.172979  4597 caffe.cpp:501] detection_eval = 8.75
-I0511 11:49:27.172983  4597 caffe.cpp:501] detection_eval = 0.0412421
-I0511 11:49:27.172986  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.172991  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.172994  4597 caffe.cpp:501] detection_eval = 7.28226
-I0511 11:49:27.172997  4597 caffe.cpp:501] detection_eval = 8.79234
-I0511 11:49:27.173002  4597 caffe.cpp:501] detection_eval = 0.0431306
-I0511 11:49:27.173005  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173009  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173012  4597 caffe.cpp:501] detection_eval = 7.28427
-I0511 11:49:27.173017  4597 caffe.cpp:501] detection_eval = 8.84677
-I0511 11:49:27.173019  4597 caffe.cpp:501] detection_eval = 0.0469652
-I0511 11:49:27.173023  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173027  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173030  4597 caffe.cpp:501] detection_eval = 7.28629
-I0511 11:49:27.173034  4597 caffe.cpp:501] detection_eval = 8.85685
-I0511 11:49:27.173038  4597 caffe.cpp:501] detection_eval = 0.0385625
-I0511 11:49:27.173041  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173045  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.173048  4597 caffe.cpp:501] detection_eval = 7.28831
-I0511 11:49:27.173056  4597 caffe.cpp:501] detection_eval = 8.90121
-I0511 11:49:27.173060  4597 caffe.cpp:501] detection_eval = 0.0392946
-I0511 11:49:27.173063  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173068  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173071  4597 caffe.cpp:501] detection_eval = 7.28831
-I0511 11:49:27.173075  4597 caffe.cpp:501] detection_eval = 8.97782
-I0511 11:49:27.173079  4597 caffe.cpp:501] detection_eval = 0.0418654
-I0511 11:49:27.173082  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173086  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.173089  4597 caffe.cpp:501] detection_eval = 7.29234
-I0511 11:49:27.173094  4597 caffe.cpp:501] detection_eval = 8.95565
-I0511 11:49:27.173097  4597 caffe.cpp:501] detection_eval = 0.0354717
-I0511 11:49:27.173100  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173105  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.173108  4597 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:49:27.173111  4597 caffe.cpp:501] detection_eval = 8.99395
-I0511 11:49:27.173115  4597 caffe.cpp:501] detection_eval = 0.0422992
-I0511 11:49:27.173120  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173122  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173126  4597 caffe.cpp:501] detection_eval = 7.29839
-I0511 11:49:27.173130  4597 caffe.cpp:501] detection_eval = 9
-I0511 11:49:27.173133  4597 caffe.cpp:501] detection_eval = 0.0390463
-I0511 11:49:27.173137  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.173141  4597 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:49:27.173144  4597 caffe.cpp:501] detection_eval = 7.29839
-I0511 11:49:27.173147  4597 caffe.cpp:501] detection_eval = 9.08871
-I0511 11:49:27.173151  4597 caffe.cpp:501] detection_eval = 0.0395434
-I0511 11:49:27.173154  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173158  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.173162  4597 caffe.cpp:501] detection_eval = 7.30444
-I0511 11:49:27.173166  4597 caffe.cpp:501] detection_eval = 9.0746
-I0511 11:49:27.173169  4597 caffe.cpp:501] detection_eval = 0.0334855
-I0511 11:49:27.173173  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.173177  4597 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:49:27.173180  4597 caffe.cpp:501] detection_eval = 7.31653
-I0511 11:49:27.173184  4597 caffe.cpp:501] detection_eval = 9.0121
-I0511 11:49:27.173188  4597 caffe.cpp:501] detection_eval = 0.0417966
-I0511 11:49:27.173192  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173195  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173199  4597 caffe.cpp:501] detection_eval = 7.31855
-I0511 11:49:27.173203  4597 caffe.cpp:501] detection_eval = 9.1129
-I0511 11:49:27.173207  4597 caffe.cpp:501] detection_eval = 0.0484479
-I0511 11:49:27.173210  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.173214  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173218  4597 caffe.cpp:501] detection_eval = 7.32056
-I0511 11:49:27.173221  4597 caffe.cpp:501] detection_eval = 9.18548
-I0511 11:49:27.173225  4597 caffe.cpp:501] detection_eval = 0.0456804
-I0511 11:49:27.173228  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173231  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173235  4597 caffe.cpp:501] detection_eval = 7.30847
-I0511 11:49:27.173238  4597 caffe.cpp:501] detection_eval = 9.11492
-I0511 11:49:27.173243  4597 caffe.cpp:501] detection_eval = 0.0449065
-I0511 11:49:27.173245  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173249  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173254  4597 caffe.cpp:501] detection_eval = 7.31048
-I0511 11:49:27.173256  4597 caffe.cpp:501] detection_eval = 9.19758
-I0511 11:49:27.173260  4597 caffe.cpp:501] detection_eval = 0.047664
-I0511 11:49:27.173264  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173267  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173276  4597 caffe.cpp:501] detection_eval = 7.31452
-I0511 11:49:27.173280  4597 caffe.cpp:501] detection_eval = 9.19153
-I0511 11:49:27.173283  4597 caffe.cpp:501] detection_eval = 0.0467778
-I0511 11:49:27.173287  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173291  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173295  4597 caffe.cpp:501] detection_eval = 7.31452
-I0511 11:49:27.173298  4597 caffe.cpp:501] detection_eval = 9.26613
-I0511 11:49:27.173302  4597 caffe.cpp:501] detection_eval = 0.0438267
-I0511 11:49:27.173305  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.173310  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173313  4597 caffe.cpp:501] detection_eval = 7.31653
-I0511 11:49:27.173316  4597 caffe.cpp:501] detection_eval = 9.31653
-I0511 11:49:27.173319  4597 caffe.cpp:501] detection_eval = 0.0454528
-I0511 11:49:27.173323  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173326  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173331  4597 caffe.cpp:501] detection_eval = 7.30242
-I0511 11:49:27.173334  4597 caffe.cpp:501] detection_eval = 9.25202
-I0511 11:49:27.173337  4597 caffe.cpp:501] detection_eval = 0.0390277
-I0511 11:49:27.173341  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173346  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173349  4597 caffe.cpp:501] detection_eval = 7.30645
-I0511 11:49:27.173352  4597 caffe.cpp:501] detection_eval = 9.24395
-I0511 11:49:27.173357  4597 caffe.cpp:501] detection_eval = 0.0396357
-I0511 11:49:27.173359  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173363  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173367  4597 caffe.cpp:501] detection_eval = 7.30847
-I0511 11:49:27.173372  4597 caffe.cpp:501] detection_eval = 9.30645
-I0511 11:49:27.173374  4597 caffe.cpp:501] detection_eval = 0.0380932
-I0511 11:49:27.173378  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173382  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173385  4597 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:49:27.173389  4597 caffe.cpp:501] detection_eval = 9.37298
-I0511 11:49:27.173393  4597 caffe.cpp:501] detection_eval = 0.0451464
-I0511 11:49:27.173396  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.173400  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.173403  4597 caffe.cpp:501] detection_eval = 7.31653
-I0511 11:49:27.173406  4597 caffe.cpp:501] detection_eval = 9.39718
-I0511 11:49:27.173410  4597 caffe.cpp:501] detection_eval = 0.0388492
-I0511 11:49:27.173413  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173416  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173419  4597 caffe.cpp:501] detection_eval = 7.32056
-I0511 11:49:27.173422  4597 caffe.cpp:501] detection_eval = 9.35887
-I0511 11:49:27.173425  4597 caffe.cpp:501] detection_eval = 0.0406518
-I0511 11:49:27.173429  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173431  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.173435  4597 caffe.cpp:501] detection_eval = 7.32056
-I0511 11:49:27.173439  4597 caffe.cpp:501] detection_eval = 9.43548
-I0511 11:49:27.173441  4597 caffe.cpp:501] detection_eval = 0.0383426
-I0511 11:49:27.173444  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.173447  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173451  4597 caffe.cpp:501] detection_eval = 7.3246
-I0511 11:49:27.173454  4597 caffe.cpp:501] detection_eval = 9.44355
-I0511 11:49:27.173457  4597 caffe.cpp:501] detection_eval = 0.0367932
-I0511 11:49:27.173460  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.173463  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173466  4597 caffe.cpp:501] detection_eval = 7.33266
-I0511 11:49:27.173470  4597 caffe.cpp:501] detection_eval = 9.38105
-I0511 11:49:27.173475  4597 caffe.cpp:501] detection_eval = 0.0361728
-I0511 11:49:27.173480  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.173485  4597 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:49:27.173493  4597 caffe.cpp:501] detection_eval = 7.33266
-I0511 11:49:27.173496  4597 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:49:27.173499  4597 caffe.cpp:501] detection_eval = 0.0407517
-I0511 11:49:27.173503  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173506  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173511  4597 caffe.cpp:501] detection_eval = 7.34073
-I0511 11:49:27.173513  4597 caffe.cpp:501] detection_eval = 9.43548
-I0511 11:49:27.173517  4597 caffe.cpp:501] detection_eval = 0.0421996
-I0511 11:49:27.173521  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.173524  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.173527  4597 caffe.cpp:501] detection_eval = 7.34274
-I0511 11:49:27.173532  4597 caffe.cpp:501] detection_eval = 9.50403
-I0511 11:49:27.173534  4597 caffe.cpp:501] detection_eval = 0.0435659
-I0511 11:49:27.173538  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173542  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173545  4597 caffe.cpp:501] detection_eval = 7.34677
-I0511 11:49:27.173548  4597 caffe.cpp:501] detection_eval = 9.53831
-I0511 11:49:27.173552  4597 caffe.cpp:501] detection_eval = 0.0458897
-I0511 11:49:27.173555  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173559  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173563  4597 caffe.cpp:501] detection_eval = 7.35282
-I0511 11:49:27.173565  4597 caffe.cpp:501] detection_eval = 9.53226
-I0511 11:49:27.173569  4597 caffe.cpp:501] detection_eval = 0.0465716
-I0511 11:49:27.173573  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.173576  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.173580  4597 caffe.cpp:501] detection_eval = 7.35282
-I0511 11:49:27.173583  4597 caffe.cpp:501] detection_eval = 9.64315
-I0511 11:49:27.173588  4597 caffe.cpp:501] detection_eval = 0.0427801
-I0511 11:49:27.173591  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173594  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173599  4597 caffe.cpp:501] detection_eval = 7.36089
-I0511 11:49:27.173602  4597 caffe.cpp:501] detection_eval = 9.59274
-I0511 11:49:27.173605  4597 caffe.cpp:501] detection_eval = 0.0423031
-I0511 11:49:27.173609  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173614  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173617  4597 caffe.cpp:501] detection_eval = 7.36089
-I0511 11:49:27.173621  4597 caffe.cpp:501] detection_eval = 9.65121
-I0511 11:49:27.173625  4597 caffe.cpp:501] detection_eval = 0.0383204
-I0511 11:49:27.173629  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173632  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173636  4597 caffe.cpp:501] detection_eval = 7.36694
-I0511 11:49:27.173640  4597 caffe.cpp:501] detection_eval = 9.62097
-I0511 11:49:27.173643  4597 caffe.cpp:501] detection_eval = 0.0369999
-I0511 11:49:27.173647  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173651  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173655  4597 caffe.cpp:501] detection_eval = 7.36895
-I0511 11:49:27.173658  4597 caffe.cpp:501] detection_eval = 9.67137
-I0511 11:49:27.173662  4597 caffe.cpp:501] detection_eval = 0.0430567
-I0511 11:49:27.173666  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173671  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173673  4597 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:49:27.173677  4597 caffe.cpp:501] detection_eval = 9.64113
-I0511 11:49:27.173681  4597 caffe.cpp:501] detection_eval = 0.0372989
-I0511 11:49:27.173684  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.173688  4597 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:49:27.173692  4597 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:49:27.173696  4597 caffe.cpp:501] detection_eval = 9.69355
-I0511 11:49:27.173699  4597 caffe.cpp:501] detection_eval = 0.0357105
-I0511 11:49:27.173703  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.173712  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173715  4597 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:49:27.173719  4597 caffe.cpp:501] detection_eval = 9.67944
-I0511 11:49:27.173723  4597 caffe.cpp:501] detection_eval = 0.0399388
-I0511 11:49:27.173727  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173732  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.173734  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.173738  4597 caffe.cpp:501] detection_eval = 9.70363
-I0511 11:49:27.173743  4597 caffe.cpp:501] detection_eval = 0.0429139
-I0511 11:49:27.173746  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173749  4597 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:49:27.173753  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.173758  4597 caffe.cpp:501] detection_eval = 9.78226
-I0511 11:49:27.173760  4597 caffe.cpp:501] detection_eval = 0.0461725
-I0511 11:49:27.173764  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.173768  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173771  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.173774  4597 caffe.cpp:501] detection_eval = 9.86694
-I0511 11:49:27.173779  4597 caffe.cpp:501] detection_eval = 0.0451524
-I0511 11:49:27.173781  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173784  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173787  4597 caffe.cpp:501] detection_eval = 7.36694
-I0511 11:49:27.173791  4597 caffe.cpp:501] detection_eval = 9.90323
-I0511 11:49:27.173794  4597 caffe.cpp:501] detection_eval = 0.0449568
-I0511 11:49:27.173797  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173801  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173804  4597 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:49:27.173807  4597 caffe.cpp:501] detection_eval = 9.92137
-I0511 11:49:27.173811  4597 caffe.cpp:501] detection_eval = 0.0478809
-I0511 11:49:27.173815  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173818  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.173822  4597 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:49:27.173826  4597 caffe.cpp:501] detection_eval = 9.86694
-I0511 11:49:27.173830  4597 caffe.cpp:501] detection_eval = 0.0393446
-I0511 11:49:27.173833  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173838  4597 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:49:27.173842  4597 caffe.cpp:501] detection_eval = 7.38306
-I0511 11:49:27.173846  4597 caffe.cpp:501] detection_eval = 9.94153
-I0511 11:49:27.173849  4597 caffe.cpp:501] detection_eval = 0.0461554
-I0511 11:49:27.173853  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173856  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173861  4597 caffe.cpp:501] detection_eval = 7.36492
-I0511 11:49:27.173864  4597 caffe.cpp:501] detection_eval = 10.0141
-I0511 11:49:27.173868  4597 caffe.cpp:501] detection_eval = 0.0447228
-I0511 11:49:27.173871  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173876  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173879  4597 caffe.cpp:501] detection_eval = 7.36895
-I0511 11:49:27.173882  4597 caffe.cpp:501] detection_eval = 10.0665
-I0511 11:49:27.173887  4597 caffe.cpp:501] detection_eval = 0.0444906
-I0511 11:49:27.173889  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.173892  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.173897  4597 caffe.cpp:501] detection_eval = 7.375
-I0511 11:49:27.173900  4597 caffe.cpp:501] detection_eval = 10.0706
-I0511 11:49:27.173904  4597 caffe.cpp:501] detection_eval = 0.0490498
-I0511 11:49:27.173908  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.173912  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.173915  4597 caffe.cpp:501] detection_eval = 7.37702
-I0511 11:49:27.173919  4597 caffe.cpp:501] detection_eval = 10.1694
-I0511 11:49:27.173923  4597 caffe.cpp:501] detection_eval = 0.0458965
-I0511 11:49:27.173926  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173934  4597 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:49:27.173938  4597 caffe.cpp:501] detection_eval = 7.3629
-I0511 11:49:27.173943  4597 caffe.cpp:501] detection_eval = 10.1371
-I0511 11:49:27.173946  4597 caffe.cpp:501] detection_eval = 0.0475492
-I0511 11:49:27.173950  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.173954  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.173957  4597 caffe.cpp:501] detection_eval = 7.37097
-I0511 11:49:27.173961  4597 caffe.cpp:501] detection_eval = 10.1089
-I0511 11:49:27.173965  4597 caffe.cpp:501] detection_eval = 0.0499534
-I0511 11:49:27.173969  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.173972  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173975  4597 caffe.cpp:501] detection_eval = 7.35685
-I0511 11:49:27.173979  4597 caffe.cpp:501] detection_eval = 10.1008
-I0511 11:49:27.173982  4597 caffe.cpp:501] detection_eval = 0.0470224
-I0511 11:49:27.173985  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.173990  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.173993  4597 caffe.cpp:501] detection_eval = 7.35887
-I0511 11:49:27.173996  4597 caffe.cpp:501] detection_eval = 10.1391
-I0511 11:49:27.174000  4597 caffe.cpp:501] detection_eval = 0.0408047
-I0511 11:49:27.174005  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174008  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174012  4597 caffe.cpp:501] detection_eval = 7.36089
-I0511 11:49:27.174015  4597 caffe.cpp:501] detection_eval = 10.2339
-I0511 11:49:27.174019  4597 caffe.cpp:501] detection_eval = 0.0501116
-I0511 11:49:27.174023  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.174026  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174031  4597 caffe.cpp:501] detection_eval = 7.34476
-I0511 11:49:27.174034  4597 caffe.cpp:501] detection_eval = 10.2238
-I0511 11:49:27.174038  4597 caffe.cpp:501] detection_eval = 0.0431928
-I0511 11:49:27.174041  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174046  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174049  4597 caffe.cpp:501] detection_eval = 7.34677
-I0511 11:49:27.174052  4597 caffe.cpp:501] detection_eval = 10.3065
-I0511 11:49:27.174057  4597 caffe.cpp:501] detection_eval = 0.0532231
-I0511 11:49:27.174060  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.174063  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.174067  4597 caffe.cpp:501] detection_eval = 7.35081
-I0511 11:49:27.174070  4597 caffe.cpp:501] detection_eval = 10.2903
-I0511 11:49:27.174074  4597 caffe.cpp:501] detection_eval = 0.0425843
-I0511 11:49:27.174077  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174082  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174085  4597 caffe.cpp:501] detection_eval = 7.33669
-I0511 11:49:27.174088  4597 caffe.cpp:501] detection_eval = 10.2621
-I0511 11:49:27.174093  4597 caffe.cpp:501] detection_eval = 0.0404038
-I0511 11:49:27.174096  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174100  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174103  4597 caffe.cpp:501] detection_eval = 7.34476
-I0511 11:49:27.174108  4597 caffe.cpp:501] detection_eval = 10.2137
-I0511 11:49:27.174111  4597 caffe.cpp:501] detection_eval = 0.0397234
-I0511 11:49:27.174115  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174118  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174123  4597 caffe.cpp:501] detection_eval = 7.35081
-I0511 11:49:27.174125  4597 caffe.cpp:501] detection_eval = 10.2077
-I0511 11:49:27.174129  4597 caffe.cpp:501] detection_eval = 0.0453921
-I0511 11:49:27.174134  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174136  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174140  4597 caffe.cpp:501] detection_eval = 7.35081
-I0511 11:49:27.174144  4597 caffe.cpp:501] detection_eval = 10.252
-I0511 11:49:27.174147  4597 caffe.cpp:501] detection_eval = 0.0410711
-I0511 11:49:27.174154  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174159  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174162  4597 caffe.cpp:501] detection_eval = 7.35685
-I0511 11:49:27.174166  4597 caffe.cpp:501] detection_eval = 10.2036
-I0511 11:49:27.174170  4597 caffe.cpp:501] detection_eval = 0.0424807
-I0511 11:49:27.174173  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174177  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174181  4597 caffe.cpp:501] detection_eval = 7.36694
-I0511 11:49:27.174185  4597 caffe.cpp:501] detection_eval = 10.1593
-I0511 11:49:27.174188  4597 caffe.cpp:501] detection_eval = 0.0441527
-I0511 11:49:27.174192  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174196  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174199  4597 caffe.cpp:501] detection_eval = 7.36895
-I0511 11:49:27.174203  4597 caffe.cpp:501] detection_eval = 10.2419
-I0511 11:49:27.174207  4597 caffe.cpp:501] detection_eval = 0.043085
-I0511 11:49:27.174211  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174214  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174217  4597 caffe.cpp:501] detection_eval = 7.37702
-I0511 11:49:27.174221  4597 caffe.cpp:501] detection_eval = 10.2177
-I0511 11:49:27.174226  4597 caffe.cpp:501] detection_eval = 0.0489284
-I0511 11:49:27.174229  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.174232  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.174237  4597 caffe.cpp:501] detection_eval = 7.37702
-I0511 11:49:27.174239  4597 caffe.cpp:501] detection_eval = 10.2843
-I0511 11:49:27.174242  4597 caffe.cpp:501] detection_eval = 0.0482222
-I0511 11:49:27.174247  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.174249  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.174253  4597 caffe.cpp:501] detection_eval = 7.38105
-I0511 11:49:27.174257  4597 caffe.cpp:501] detection_eval = 10.2722
-I0511 11:49:27.174260  4597 caffe.cpp:501] detection_eval = 0.0402078
-I0511 11:49:27.174264  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174268  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174271  4597 caffe.cpp:501] detection_eval = 7.38306
-I0511 11:49:27.174275  4597 caffe.cpp:501] detection_eval = 10.3024
-I0511 11:49:27.174279  4597 caffe.cpp:501] detection_eval = 0.0363361
-I0511 11:49:27.174283  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174286  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174290  4597 caffe.cpp:501] detection_eval = 7.3871
-I0511 11:49:27.174294  4597 caffe.cpp:501] detection_eval = 10.2944
-I0511 11:49:27.174298  4597 caffe.cpp:501] detection_eval = 0.0363834
-I0511 11:49:27.174301  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.174305  4597 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:49:27.174309  4597 caffe.cpp:501] detection_eval = 7.38911
-I0511 11:49:27.174312  4597 caffe.cpp:501] detection_eval = 10.3246
-I0511 11:49:27.174316  4597 caffe.cpp:501] detection_eval = 0.0420944
-I0511 11:49:27.174320  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174324  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174326  4597 caffe.cpp:501] detection_eval = 7.39113
-I0511 11:49:27.174330  4597 caffe.cpp:501] detection_eval = 10.3972
-I0511 11:49:27.174334  4597 caffe.cpp:501] detection_eval = 0.0490882
-I0511 11:49:27.174337  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.174340  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.174345  4597 caffe.cpp:501] detection_eval = 7.39516
-I0511 11:49:27.174348  4597 caffe.cpp:501] detection_eval = 10.4435
-I0511 11:49:27.174352  4597 caffe.cpp:501] detection_eval = 0.0413695
-I0511 11:49:27.174355  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174360  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174362  4597 caffe.cpp:501] detection_eval = 7.40524
-I0511 11:49:27.174366  4597 caffe.cpp:501] detection_eval = 10.3427
-I0511 11:49:27.174374  4597 caffe.cpp:501] detection_eval = 0.0429845
-I0511 11:49:27.174377  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174381  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174386  4597 caffe.cpp:501] detection_eval = 7.41129
-I0511 11:49:27.174388  4597 caffe.cpp:501] detection_eval = 10.3286
-I0511 11:49:27.174392  4597 caffe.cpp:501] detection_eval = 0.0392333
-I0511 11:49:27.174396  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174401  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174403  4597 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:49:27.174407  4597 caffe.cpp:501] detection_eval = 10.3649
-I0511 11:49:27.174410  4597 caffe.cpp:501] detection_eval = 0.0483903
-I0511 11:49:27.174414  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.174417  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174420  4597 caffe.cpp:501] detection_eval = 7.42339
-I0511 11:49:27.174424  4597 caffe.cpp:501] detection_eval = 10.3548
-I0511 11:49:27.174428  4597 caffe.cpp:501] detection_eval = 0.0470593
-I0511 11:49:27.174432  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.174435  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174439  4597 caffe.cpp:501] detection_eval = 7.43347
-I0511 11:49:27.174443  4597 caffe.cpp:501] detection_eval = 10.254
-I0511 11:49:27.174446  4597 caffe.cpp:501] detection_eval = 0.0456793
-I0511 11:49:27.174450  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174454  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174458  4597 caffe.cpp:501] detection_eval = 7.43548
-I0511 11:49:27.174461  4597 caffe.cpp:501] detection_eval = 10.2823
-I0511 11:49:27.174465  4597 caffe.cpp:501] detection_eval = 0.0433553
-I0511 11:49:27.174468  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174473  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174475  4597 caffe.cpp:501] detection_eval = 7.43952
-I0511 11:49:27.174479  4597 caffe.cpp:501] detection_eval = 10.2883
-I0511 11:49:27.174484  4597 caffe.cpp:501] detection_eval = 0.0454525
-I0511 11:49:27.174487  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174490  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174494  4597 caffe.cpp:501] detection_eval = 7.43952
-I0511 11:49:27.174497  4597 caffe.cpp:501] detection_eval = 10.3488
-I0511 11:49:27.174501  4597 caffe.cpp:501] detection_eval = 0.0430456
-I0511 11:49:27.174504  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174507  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174511  4597 caffe.cpp:501] detection_eval = 7.44355
-I0511 11:49:27.174515  4597 caffe.cpp:501] detection_eval = 10.3649
-I0511 11:49:27.174518  4597 caffe.cpp:501] detection_eval = 0.040618
-I0511 11:49:27.174522  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174526  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174530  4597 caffe.cpp:501] detection_eval = 7.4496
-I0511 11:49:27.174533  4597 caffe.cpp:501] detection_eval = 10.3609
-I0511 11:49:27.174537  4597 caffe.cpp:501] detection_eval = 0.0411297
-I0511 11:49:27.174540  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174545  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174548  4597 caffe.cpp:501] detection_eval = 7.45161
-I0511 11:49:27.174551  4597 caffe.cpp:501] detection_eval = 10.4093
-I0511 11:49:27.174556  4597 caffe.cpp:501] detection_eval = 0.0402608
-I0511 11:49:27.174559  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174562  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174566  4597 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:49:27.174571  4597 caffe.cpp:501] detection_eval = 10.496
-I0511 11:49:27.174573  4597 caffe.cpp:501] detection_eval = 0.0405892
-I0511 11:49:27.174577  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174582  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.174584  4597 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:49:27.174587  4597 caffe.cpp:501] detection_eval = 10.4415
-I0511 11:49:27.174595  4597 caffe.cpp:501] detection_eval = 0.0413932
-I0511 11:49:27.174599  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174603  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174607  4597 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:49:27.174610  4597 caffe.cpp:501] detection_eval = 10.5181
-I0511 11:49:27.174614  4597 caffe.cpp:501] detection_eval = 0.0432672
-I0511 11:49:27.174618  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174621  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174625  4597 caffe.cpp:501] detection_eval = 7.44355
-I0511 11:49:27.174629  4597 caffe.cpp:501] detection_eval = 10.5766
-I0511 11:49:27.174633  4597 caffe.cpp:501] detection_eval = 0.0451075
-I0511 11:49:27.174636  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.174640  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.174643  4597 caffe.cpp:501] detection_eval = 7.44556
-I0511 11:49:27.174648  4597 caffe.cpp:501] detection_eval = 10.6149
-I0511 11:49:27.174651  4597 caffe.cpp:501] detection_eval = 0.0448866
-I0511 11:49:27.174654  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174659  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174661  4597 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:49:27.174665  4597 caffe.cpp:501] detection_eval = 10.5645
-I0511 11:49:27.174669  4597 caffe.cpp:501] detection_eval = 0.0463545
-I0511 11:49:27.174672  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174675  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.174679  4597 caffe.cpp:501] detection_eval = 7.45565
-I0511 11:49:27.174682  4597 caffe.cpp:501] detection_eval = 10.5887
-I0511 11:49:27.174686  4597 caffe.cpp:501] detection_eval = 0.0414429
-I0511 11:49:27.174690  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174695  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174697  4597 caffe.cpp:501] detection_eval = 7.45565
-I0511 11:49:27.174701  4597 caffe.cpp:501] detection_eval = 10.6633
-I0511 11:49:27.174705  4597 caffe.cpp:501] detection_eval = 0.0390254
-I0511 11:49:27.174708  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.174712  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174716  4597 caffe.cpp:501] detection_eval = 7.45766
-I0511 11:49:27.174720  4597 caffe.cpp:501] detection_eval = 10.7258
-I0511 11:49:27.174723  4597 caffe.cpp:501] detection_eval = 0.0485399
-I0511 11:49:27.174727  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174731  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174734  4597 caffe.cpp:501] detection_eval = 7.45968
-I0511 11:49:27.174738  4597 caffe.cpp:501] detection_eval = 10.7601
-I0511 11:49:27.174741  4597 caffe.cpp:501] detection_eval = 0.0457567
-I0511 11:49:27.174746  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.174749  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.174752  4597 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:49:27.174756  4597 caffe.cpp:501] detection_eval = 10.7782
-I0511 11:49:27.174758  4597 caffe.cpp:501] detection_eval = 0.0452479
-I0511 11:49:27.174762  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174767  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.174769  4597 caffe.cpp:501] detection_eval = 7.46371
-I0511 11:49:27.174773  4597 caffe.cpp:501] detection_eval = 10.7903
-I0511 11:49:27.174777  4597 caffe.cpp:501] detection_eval = 0.0370989
-I0511 11:49:27.174782  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174784  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174788  4597 caffe.cpp:501] detection_eval = 7.46976
-I0511 11:49:27.174793  4597 caffe.cpp:501] detection_eval = 10.7762
-I0511 11:49:27.174796  4597 caffe.cpp:501] detection_eval = 0.0458781
-I0511 11:49:27.174799  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.174803  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.174806  4597 caffe.cpp:501] detection_eval = 7.46976
-I0511 11:49:27.174813  4597 caffe.cpp:501] detection_eval = 10.8226
-I0511 11:49:27.174818  4597 caffe.cpp:501] detection_eval = 0.0386743
-I0511 11:49:27.174821  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174825  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.174829  4597 caffe.cpp:501] detection_eval = 7.47379
-I0511 11:49:27.174832  4597 caffe.cpp:501] detection_eval = 10.7923
-I0511 11:49:27.174836  4597 caffe.cpp:501] detection_eval = 0.0367524
-I0511 11:49:27.174839  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.174842  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.174846  4597 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:49:27.174849  4597 caffe.cpp:501] detection_eval = 10.7903
-I0511 11:49:27.174854  4597 caffe.cpp:501] detection_eval = 0.0369325
-I0511 11:49:27.174857  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174860  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174865  4597 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:49:27.174868  4597 caffe.cpp:501] detection_eval = 10.8286
-I0511 11:49:27.174871  4597 caffe.cpp:501] detection_eval = 0.039236
-I0511 11:49:27.174875  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174880  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174882  4597 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:49:27.174886  4597 caffe.cpp:501] detection_eval = 10.75
-I0511 11:49:27.174890  4597 caffe.cpp:501] detection_eval = 0.0486638
-I0511 11:49:27.174893  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.174897  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.174901  4597 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:49:27.174904  4597 caffe.cpp:501] detection_eval = 10.7157
-I0511 11:49:27.174908  4597 caffe.cpp:501] detection_eval = 0.0394219
-I0511 11:49:27.174912  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.174916  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174919  4597 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:49:27.174922  4597 caffe.cpp:501] detection_eval = 10.8004
-I0511 11:49:27.174926  4597 caffe.cpp:501] detection_eval = 0.0437894
-I0511 11:49:27.174929  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174933  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.174937  4597 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:49:27.174940  4597 caffe.cpp:501] detection_eval = 10.8105
-I0511 11:49:27.174944  4597 caffe.cpp:501] detection_eval = 0.0412713
-I0511 11:49:27.174948  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.174952  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.174955  4597 caffe.cpp:501] detection_eval = 7.4879
-I0511 11:49:27.174959  4597 caffe.cpp:501] detection_eval = 10.8226
-I0511 11:49:27.174963  4597 caffe.cpp:501] detection_eval = 0.0410146
-I0511 11:49:27.174966  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.174970  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.174974  4597 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:49:27.174978  4597 caffe.cpp:501] detection_eval = 10.746
-I0511 11:49:27.174981  4597 caffe.cpp:501] detection_eval = 0.0432423
-I0511 11:49:27.174985  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.174988  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.174993  4597 caffe.cpp:501] detection_eval = 7.5
-I0511 11:49:27.174996  4597 caffe.cpp:501] detection_eval = 10.8185
-I0511 11:49:27.175000  4597 caffe.cpp:501] detection_eval = 0.0420377
-I0511 11:49:27.175004  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175007  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.175010  4597 caffe.cpp:501] detection_eval = 7.50605
-I0511 11:49:27.175014  4597 caffe.cpp:501] detection_eval = 10.7923
-I0511 11:49:27.175017  4597 caffe.cpp:501] detection_eval = 0.0398127
-I0511 11:49:27.175021  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.175024  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.175029  4597 caffe.cpp:501] detection_eval = 7.51008
-I0511 11:49:27.175035  4597 caffe.cpp:501] detection_eval = 10.8327
-I0511 11:49:27.175040  4597 caffe.cpp:501] detection_eval = 0.0384945
-I0511 11:49:27.175043  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.175047  4597 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:49:27.175050  4597 caffe.cpp:501] detection_eval = 7.52016
-I0511 11:49:27.175055  4597 caffe.cpp:501] detection_eval = 10.7621
-I0511 11:49:27.175058  4597 caffe.cpp:501] detection_eval = 0.0405141
-I0511 11:49:27.175062  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175065  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175070  4597 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:49:27.175072  4597 caffe.cpp:501] detection_eval = 10.7883
-I0511 11:49:27.175076  4597 caffe.cpp:501] detection_eval = 0.0368635
-I0511 11:49:27.175081  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.175084  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.175087  4597 caffe.cpp:501] detection_eval = 7.53024
-I0511 11:49:27.175091  4597 caffe.cpp:501] detection_eval = 10.7681
-I0511 11:49:27.175096  4597 caffe.cpp:501] detection_eval = 0.0424594
-I0511 11:49:27.175098  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175101  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175106  4597 caffe.cpp:501] detection_eval = 7.53629
-I0511 11:49:27.175108  4597 caffe.cpp:501] detection_eval = 10.7399
-I0511 11:49:27.175112  4597 caffe.cpp:501] detection_eval = 0.0415589
-I0511 11:49:27.175117  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.175119  4597 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:49:27.175123  4597 caffe.cpp:501] detection_eval = 7.52016
-I0511 11:49:27.175127  4597 caffe.cpp:501] detection_eval = 10.8145
-I0511 11:49:27.175130  4597 caffe.cpp:501] detection_eval = 0.0470319
-I0511 11:49:27.175134  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.175138  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.175143  4597 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:49:27.175145  4597 caffe.cpp:501] detection_eval = 10.8387
-I0511 11:49:27.175149  4597 caffe.cpp:501] detection_eval = 0.0430624
-I0511 11:49:27.175565  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.175572  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.175575  4597 caffe.cpp:501] detection_eval = 7.52823
-I0511 11:49:27.175580  4597 caffe.cpp:501] detection_eval = 10.8609
-I0511 11:49:27.175583  4597 caffe.cpp:501] detection_eval = 0.0490111
-I0511 11:49:27.175586  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175590  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175595  4597 caffe.cpp:501] detection_eval = 7.53024
-I0511 11:49:27.175598  4597 caffe.cpp:501] detection_eval = 10.9234
-I0511 11:49:27.175602  4597 caffe.cpp:501] detection_eval = 0.0421941
-I0511 11:49:27.175606  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175609  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175613  4597 caffe.cpp:501] detection_eval = 7.53427
-I0511 11:49:27.175616  4597 caffe.cpp:501] detection_eval = 10.9456
-I0511 11:49:27.175621  4597 caffe.cpp:501] detection_eval = 0.0405491
-I0511 11:49:27.175624  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175628  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.175631  4597 caffe.cpp:501] detection_eval = 7.53831
-I0511 11:49:27.175635  4597 caffe.cpp:501] detection_eval = 11
-I0511 11:49:27.175639  4597 caffe.cpp:501] detection_eval = 0.047071
-I0511 11:49:27.175642  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175645  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175648  4597 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:49:27.175653  4597 caffe.cpp:501] detection_eval = 10.9214
-I0511 11:49:27.175657  4597 caffe.cpp:501] detection_eval = 0.0439473
-I0511 11:49:27.175662  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.175668  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.175680  4597 caffe.cpp:501] detection_eval = 7.5504
-I0511 11:49:27.175686  4597 caffe.cpp:501] detection_eval = 10.9254
-I0511 11:49:27.175690  4597 caffe.cpp:501] detection_eval = 0.0403158
-I0511 11:49:27.175693  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175698  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.175701  4597 caffe.cpp:501] detection_eval = 7.55242
-I0511 11:49:27.175704  4597 caffe.cpp:501] detection_eval = 10.9556
-I0511 11:49:27.175707  4597 caffe.cpp:501] detection_eval = 0.0456277
-I0511 11:49:27.175711  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.175714  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175719  4597 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:49:27.175721  4597 caffe.cpp:501] detection_eval = 10.9476
-I0511 11:49:27.175725  4597 caffe.cpp:501] detection_eval = 0.0426379
-I0511 11:49:27.175729  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175734  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.175736  4597 caffe.cpp:501] detection_eval = 7.56452
-I0511 11:49:27.175740  4597 caffe.cpp:501] detection_eval = 10.9173
-I0511 11:49:27.175745  4597 caffe.cpp:501] detection_eval = 0.0448893
-I0511 11:49:27.175747  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.175751  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.175755  4597 caffe.cpp:501] detection_eval = 7.56653
-I0511 11:49:27.175758  4597 caffe.cpp:501] detection_eval = 10.9758
-I0511 11:49:27.175762  4597 caffe.cpp:501] detection_eval = 0.0458773
-I0511 11:49:27.175766  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.175770  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.175773  4597 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:49:27.175776  4597 caffe.cpp:501] detection_eval = 11.0121
-I0511 11:49:27.175781  4597 caffe.cpp:501] detection_eval = 0.0412877
-I0511 11:49:27.175784  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175788  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.175791  4597 caffe.cpp:501] detection_eval = 7.57258
-I0511 11:49:27.175794  4597 caffe.cpp:501] detection_eval = 11.002
-I0511 11:49:27.175798  4597 caffe.cpp:501] detection_eval = 0.0379916
-I0511 11:49:27.175802  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.175806  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175810  4597 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:49:27.175813  4597 caffe.cpp:501] detection_eval = 11.0847
-I0511 11:49:27.175817  4597 caffe.cpp:501] detection_eval = 0.0451914
-I0511 11:49:27.175822  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175824  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175828  4597 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:49:27.175832  4597 caffe.cpp:501] detection_eval = 11.0323
-I0511 11:49:27.175835  4597 caffe.cpp:501] detection_eval = 0.0439928
-I0511 11:49:27.175839  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175843  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.175846  4597 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:49:27.175850  4597 caffe.cpp:501] detection_eval = 10.9899
-I0511 11:49:27.175854  4597 caffe.cpp:501] detection_eval = 0.0409328
-I0511 11:49:27.175858  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.175861  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175865  4597 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:49:27.175868  4597 caffe.cpp:501] detection_eval = 10.9839
-I0511 11:49:27.175873  4597 caffe.cpp:501] detection_eval = 0.0389855
-I0511 11:49:27.175875  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.175879  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175882  4597 caffe.cpp:501] detection_eval = 7.57863
-I0511 11:49:27.175886  4597 caffe.cpp:501] detection_eval = 10.9859
-I0511 11:49:27.175890  4597 caffe.cpp:501] detection_eval = 0.0393829
-I0511 11:49:27.175894  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175901  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175905  4597 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:49:27.175909  4597 caffe.cpp:501] detection_eval = 11.0081
-I0511 11:49:27.175914  4597 caffe.cpp:501] detection_eval = 0.0406608
-I0511 11:49:27.175916  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175920  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175925  4597 caffe.cpp:501] detection_eval = 7.59073
-I0511 11:49:27.175928  4597 caffe.cpp:501] detection_eval = 10.9456
-I0511 11:49:27.175932  4597 caffe.cpp:501] detection_eval = 0.0404323
-I0511 11:49:27.175935  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.175940  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175943  4597 caffe.cpp:501] detection_eval = 7.59073
-I0511 11:49:27.175946  4597 caffe.cpp:501] detection_eval = 11.0282
-I0511 11:49:27.175951  4597 caffe.cpp:501] detection_eval = 0.043047
-I0511 11:49:27.175954  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.175957  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175961  4597 caffe.cpp:501] detection_eval = 7.59476
-I0511 11:49:27.175964  4597 caffe.cpp:501] detection_eval = 11.0524
-I0511 11:49:27.175967  4597 caffe.cpp:501] detection_eval = 0.0417951
-I0511 11:49:27.175971  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175976  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.175978  4597 caffe.cpp:501] detection_eval = 7.59677
-I0511 11:49:27.175982  4597 caffe.cpp:501] detection_eval = 11.0927
-I0511 11:49:27.175987  4597 caffe.cpp:501] detection_eval = 0.0371979
-I0511 11:49:27.175989  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.175993  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.175997  4597 caffe.cpp:501] detection_eval = 7.60282
-I0511 11:49:27.176000  4597 caffe.cpp:501] detection_eval = 11.0685
-I0511 11:49:27.176004  4597 caffe.cpp:501] detection_eval = 0.0440634
-I0511 11:49:27.176008  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.176012  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176015  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176309  4597 caffe.cpp:501] detection_eval = 11.0423
-I0511 11:49:27.176316  4597 caffe.cpp:501] detection_eval = 0.0465861
-I0511 11:49:27.176319  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.176323  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.176326  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176331  4597 caffe.cpp:501] detection_eval = 11.1351
-I0511 11:49:27.176334  4597 caffe.cpp:501] detection_eval = 0.0409808
-I0511 11:49:27.176338  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176342  4597 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:49:27.176345  4597 caffe.cpp:501] detection_eval = 7.59677
-I0511 11:49:27.176349  4597 caffe.cpp:501] detection_eval = 11.0786
-I0511 11:49:27.176352  4597 caffe.cpp:501] detection_eval = 0.0377656
-I0511 11:49:27.176357  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176360  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176363  4597 caffe.cpp:501] detection_eval = 7.60081
-I0511 11:49:27.176367  4597 caffe.cpp:501] detection_eval = 11.0585
-I0511 11:49:27.176370  4597 caffe.cpp:501] detection_eval = 0.0357857
-I0511 11:49:27.176374  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.176378  4597 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:49:27.176381  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.176385  4597 caffe.cpp:501] detection_eval = 11.0504
-I0511 11:49:27.176388  4597 caffe.cpp:501] detection_eval = 0.036233
-I0511 11:49:27.176393  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.176396  4597 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:49:27.176400  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176403  4597 caffe.cpp:501] detection_eval = 11.0484
-I0511 11:49:27.176407  4597 caffe.cpp:501] detection_eval = 0.0392681
-I0511 11:49:27.176411  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.176419  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176424  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176427  4597 caffe.cpp:501] detection_eval = 11.123
-I0511 11:49:27.176431  4597 caffe.cpp:501] detection_eval = 0.0397001
-I0511 11:49:27.176434  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.176439  4597 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:49:27.176441  4597 caffe.cpp:501] detection_eval = 7.61492
-I0511 11:49:27.176445  4597 caffe.cpp:501] detection_eval = 11.121
-I0511 11:49:27.176448  4597 caffe.cpp:501] detection_eval = 0.0381308
-I0511 11:49:27.176452  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.176456  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.176460  4597 caffe.cpp:501] detection_eval = 7.61492
-I0511 11:49:27.176463  4597 caffe.cpp:501] detection_eval = 11.1996
-I0511 11:49:27.176467  4597 caffe.cpp:501] detection_eval = 0.0407439
-I0511 11:49:27.176470  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176475  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.176478  4597 caffe.cpp:501] detection_eval = 7.62097
-I0511 11:49:27.176481  4597 caffe.cpp:501] detection_eval = 11.2056
-I0511 11:49:27.176486  4597 caffe.cpp:501] detection_eval = 0.0421225
-I0511 11:49:27.176489  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.176492  4597 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:49:27.176496  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176501  4597 caffe.cpp:501] detection_eval = 11.1492
-I0511 11:49:27.176503  4597 caffe.cpp:501] detection_eval = 0.0440622
-I0511 11:49:27.176507  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176512  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176514  4597 caffe.cpp:501] detection_eval = 7.59476
-I0511 11:49:27.176518  4597 caffe.cpp:501] detection_eval = 11.125
-I0511 11:49:27.176522  4597 caffe.cpp:501] detection_eval = 0.0411818
-I0511 11:49:27.176542  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.176545  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.176549  4597 caffe.cpp:501] detection_eval = 7.60081
-I0511 11:49:27.176553  4597 caffe.cpp:501] detection_eval = 11.0847
-I0511 11:49:27.176558  4597 caffe.cpp:501] detection_eval = 0.0365465
-I0511 11:49:27.176561  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.176564  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176568  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.176573  4597 caffe.cpp:501] detection_eval = 11.0746
-I0511 11:49:27.176575  4597 caffe.cpp:501] detection_eval = 0.0397285
-I0511 11:49:27.176579  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.176584  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176587  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.176590  4597 caffe.cpp:501] detection_eval = 11.1391
-I0511 11:49:27.176594  4597 caffe.cpp:501] detection_eval = 0.037983
-I0511 11:49:27.176599  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.176602  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.176605  4597 caffe.cpp:501] detection_eval = 7.61089
-I0511 11:49:27.176609  4597 caffe.cpp:501] detection_eval = 11.1028
-I0511 11:49:27.176614  4597 caffe.cpp:501] detection_eval = 0.0400337
-I0511 11:49:27.176617  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.176620  4597 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:49:27.176625  4597 caffe.cpp:501] detection_eval = 7.61895
-I0511 11:49:27.176627  4597 caffe.cpp:501] detection_eval = 11.0625
-I0511 11:49:27.176630  4597 caffe.cpp:501] detection_eval = 0.0397385
-I0511 11:49:27.176635  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.176638  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.176641  4597 caffe.cpp:501] detection_eval = 7.62097
-I0511 11:49:27.176645  4597 caffe.cpp:501] detection_eval = 11.1109
-I0511 11:49:27.176650  4597 caffe.cpp:501] detection_eval = 0.0427227
-I0511 11:49:27.176657  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.176661  4597 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:49:27.176666  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.176669  4597 caffe.cpp:501] detection_eval = 11.1069
-I0511 11:49:27.176673  4597 caffe.cpp:501] detection_eval = 0.0386111
-I0511 11:49:27.176676  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176681  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.176684  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176687  4597 caffe.cpp:501] detection_eval = 11.0907
-I0511 11:49:27.176692  4597 caffe.cpp:501] detection_eval = 0.036727
-I0511 11:49:27.176695  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.176699  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.176702  4597 caffe.cpp:501] detection_eval = 7.59476
-I0511 11:49:27.176707  4597 caffe.cpp:501] detection_eval = 11.0665
-I0511 11:49:27.176709  4597 caffe.cpp:501] detection_eval = 0.036776
-I0511 11:49:27.176713  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.176717  4597 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:49:27.176720  4597 caffe.cpp:501] detection_eval = 7.59677
-I0511 11:49:27.176723  4597 caffe.cpp:501] detection_eval = 11.0927
-I0511 11:49:27.176728  4597 caffe.cpp:501] detection_eval = 0.0361817
-I0511 11:49:27.176731  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.176735  4597 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:49:27.176738  4597 caffe.cpp:501] detection_eval = 7.59879
-I0511 11:49:27.176743  4597 caffe.cpp:501] detection_eval = 11.129
-I0511 11:49:27.176746  4597 caffe.cpp:501] detection_eval = 0.0378719
-I0511 11:49:27.176749  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.176753  4597 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:49:27.176757  4597 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:49:27.176760  4597 caffe.cpp:501] detection_eval = 11.0565
-I0511 11:49:27.176764  4597 caffe.cpp:501] detection_eval = 0.0374305
-I0511 11:49:27.176769  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.177091  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.177096  4597 caffe.cpp:501] detection_eval = 7.61089
-I0511 11:49:27.177100  4597 caffe.cpp:501] detection_eval = 11.123
-I0511 11:49:27.177104  4597 caffe.cpp:501] detection_eval = 0.0417044
-I0511 11:49:27.177109  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177111  4597 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:49:27.177115  4597 caffe.cpp:501] detection_eval = 7.61492
-I0511 11:49:27.177119  4597 caffe.cpp:501] detection_eval = 11.1048
-I0511 11:49:27.177122  4597 caffe.cpp:501] detection_eval = 0.0383507
-I0511 11:49:27.177125  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177140  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.177145  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.177148  4597 caffe.cpp:501] detection_eval = 11.1573
-I0511 11:49:27.177152  4597 caffe.cpp:501] detection_eval = 0.0405986
-I0511 11:49:27.177156  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177160  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.177163  4597 caffe.cpp:501] detection_eval = 7.60484
-I0511 11:49:27.177167  4597 caffe.cpp:501] detection_eval = 11.127
-I0511 11:49:27.177171  4597 caffe.cpp:501] detection_eval = 0.042147
-I0511 11:49:27.177175  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177178  4597 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:49:27.177182  4597 caffe.cpp:501] detection_eval = 7.58871
-I0511 11:49:27.177186  4597 caffe.cpp:501] detection_eval = 11.1512
-I0511 11:49:27.177189  4597 caffe.cpp:501] detection_eval = 0.0426079
-I0511 11:49:27.177193  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.177196  4597 caffe.cpp:501] detection_eval = 0.939516
-I0511 11:49:27.177201  4597 caffe.cpp:501] detection_eval = 7.59476
-I0511 11:49:27.177203  4597 caffe.cpp:501] detection_eval = 11.1331
-I0511 11:49:27.177206  4597 caffe.cpp:501] detection_eval = 0.0364144
-I0511 11:49:27.177215  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177219  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.177222  4597 caffe.cpp:501] detection_eval = 7.57863
-I0511 11:49:27.177227  4597 caffe.cpp:501] detection_eval = 11.1694
-I0511 11:49:27.177230  4597 caffe.cpp:501] detection_eval = 0.038096
-I0511 11:49:27.177234  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177237  4597 caffe.cpp:501] detection_eval = 0.941532
-I0511 11:49:27.177242  4597 caffe.cpp:501] detection_eval = 7.5625
-I0511 11:49:27.177245  4597 caffe.cpp:501] detection_eval = 11.1815
-I0511 11:49:27.177249  4597 caffe.cpp:501] detection_eval = 0.0357599
-I0511 11:49:27.177253  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.177256  4597 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:49:27.177260  4597 caffe.cpp:501] detection_eval = 7.56653
-I0511 11:49:27.177264  4597 caffe.cpp:501] detection_eval = 11.1996
-I0511 11:49:27.177268  4597 caffe.cpp:501] detection_eval = 0.0355026
-I0511 11:49:27.177271  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.177275  4597 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:49:27.177279  4597 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:49:27.177283  4597 caffe.cpp:501] detection_eval = 11.2238
-I0511 11:49:27.177286  4597 caffe.cpp:501] detection_eval = 0.0386533
-I0511 11:49:27.177289  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.177294  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.177297  4597 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:49:27.177301  4597 caffe.cpp:501] detection_eval = 11.2601
-I0511 11:49:27.177304  4597 caffe.cpp:501] detection_eval = 0.0463732
-I0511 11:49:27.177309  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177312  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.177316  4597 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:49:27.177320  4597 caffe.cpp:501] detection_eval = 11.3528
-I0511 11:49:27.177323  4597 caffe.cpp:501] detection_eval = 0.0391411
-I0511 11:49:27.177327  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.177331  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.177335  4597 caffe.cpp:501] detection_eval = 7.55847
-I0511 11:49:27.177338  4597 caffe.cpp:501] detection_eval = 11.3427
-I0511 11:49:27.177342  4597 caffe.cpp:501] detection_eval = 0.035949
-I0511 11:49:27.177346  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.177350  4597 caffe.cpp:501] detection_eval = 0.939516
-I0511 11:49:27.177353  4597 caffe.cpp:501] detection_eval = 7.56048
-I0511 11:49:27.177357  4597 caffe.cpp:501] detection_eval = 11.3891
-I0511 11:49:27.177361  4597 caffe.cpp:501] detection_eval = 0.0401412
-I0511 11:49:27.177364  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.177368  4597 caffe.cpp:501] detection_eval = 0.939516
-I0511 11:49:27.177371  4597 caffe.cpp:501] detection_eval = 7.56452
-I0511 11:49:27.177374  4597 caffe.cpp:501] detection_eval = 11.4093
-I0511 11:49:27.177378  4597 caffe.cpp:501] detection_eval = 0.0390099
-I0511 11:49:27.177381  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.177386  4597 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:49:27.177389  4597 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:49:27.177392  4597 caffe.cpp:501] detection_eval = 11.4435
-I0511 11:49:27.177397  4597 caffe.cpp:501] detection_eval = 0.040263
-I0511 11:49:27.177400  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.177404  4597 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:49:27.177407  4597 caffe.cpp:501] detection_eval = 7.53427
-I0511 11:49:27.177412  4597 caffe.cpp:501] detection_eval = 11.4032
-I0511 11:49:27.177415  4597 caffe.cpp:501] detection_eval = 0.0402077
-I0511 11:49:27.177418  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177423  4597 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:49:27.177426  4597 caffe.cpp:501] detection_eval = 7.51815
-I0511 11:49:27.177429  4597 caffe.cpp:501] detection_eval = 11.4355
-I0511 11:49:27.177438  4597 caffe.cpp:501] detection_eval = 0.0371625
-I0511 11:49:27.177441  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.177445  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.177449  4597 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:49:27.177453  4597 caffe.cpp:501] detection_eval = 11.4718
-I0511 11:49:27.177456  4597 caffe.cpp:501] detection_eval = 0.0411716
-I0511 11:49:27.177459  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177462  4597 caffe.cpp:501] detection_eval = 0.927419
-I0511 11:49:27.177466  4597 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:49:27.177469  4597 caffe.cpp:501] detection_eval = 11.5565
-I0511 11:49:27.177474  4597 caffe.cpp:501] detection_eval = 0.0383002
-I0511 11:49:27.177477  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.177481  4597 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:49:27.177485  4597 caffe.cpp:501] detection_eval = 7.53024
-I0511 11:49:27.177489  4597 caffe.cpp:501] detection_eval = 11.5988
-I0511 11:49:27.177492  4597 caffe.cpp:501] detection_eval = 0.0439466
-I0511 11:49:27.177496  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.177500  4597 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:49:27.177510  4597 caffe.cpp:501] detection_eval = 7.53427
-I0511 11:49:27.177513  4597 caffe.cpp:501] detection_eval = 11.6996
-I0511 11:49:27.177517  4597 caffe.cpp:501] detection_eval = 0.0420059
-I0511 11:49:27.177521  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.177525  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.177528  4597 caffe.cpp:501] detection_eval = 7.54234
-I0511 11:49:27.177532  4597 caffe.cpp:501] detection_eval = 11.7843
-I0511 11:49:27.177536  4597 caffe.cpp:501] detection_eval = 0.0382367
-I0511 11:49:27.177539  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.177542  4597 caffe.cpp:501] detection_eval = 0.935484
-I0511 11:49:27.177546  4597 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:49:27.177549  4597 caffe.cpp:501] detection_eval = 8.28024
-I0511 11:49:27.178318  4597 caffe.cpp:501] detection_eval = 0.058111
-I0511 11:49:27.178328  4597 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:49:27.178333  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178335  4597 caffe.cpp:501] detection_eval = 7.78226
-I0511 11:49:27.178339  4597 caffe.cpp:501] detection_eval = 8.29839
-I0511 11:49:27.178344  4597 caffe.cpp:501] detection_eval = 0.0464954
-I0511 11:49:27.178346  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178350  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178354  4597 caffe.cpp:501] detection_eval = 7.78427
-I0511 11:49:27.178357  4597 caffe.cpp:501] detection_eval = 8.37903
-I0511 11:49:27.178360  4597 caffe.cpp:501] detection_eval = 0.0468021
-I0511 11:49:27.178364  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178369  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178372  4597 caffe.cpp:501] detection_eval = 7.77016
-I0511 11:49:27.178375  4597 caffe.cpp:501] detection_eval = 8.39919
-I0511 11:49:27.178380  4597 caffe.cpp:501] detection_eval = 0.0519864
-I0511 11:49:27.178382  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.178386  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178390  4597 caffe.cpp:501] detection_eval = 7.77419
-I0511 11:49:27.178393  4597 caffe.cpp:501] detection_eval = 8.43347
-I0511 11:49:27.178396  4597 caffe.cpp:501] detection_eval = 0.0548872
-I0511 11:49:27.178400  4597 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:49:27.178403  4597 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:49:27.178406  4597 caffe.cpp:501] detection_eval = 7.77419
-I0511 11:49:27.178411  4597 caffe.cpp:501] detection_eval = 8.51411
-I0511 11:49:27.178413  4597 caffe.cpp:501] detection_eval = 0.0448702
-I0511 11:49:27.178417  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.178421  4597 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:49:27.178424  4597 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:49:27.178427  4597 caffe.cpp:501] detection_eval = 8.54234
-I0511 11:49:27.178436  4597 caffe.cpp:501] detection_eval = 0.0396127
-I0511 11:49:27.178442  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178444  4597 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:49:27.178447  4597 caffe.cpp:501] detection_eval = 7.76411
-I0511 11:49:27.178449  4597 caffe.cpp:501] detection_eval = 8.52016
-I0511 11:49:27.178452  4597 caffe.cpp:501] detection_eval = 0.0431888
-I0511 11:49:27.178453  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.178457  4597 caffe.cpp:501] detection_eval = 0.923387
-I0511 11:49:27.178458  4597 caffe.cpp:501] detection_eval = 7.75605
-I0511 11:49:27.178460  4597 caffe.cpp:501] detection_eval = 8.41129
-I0511 11:49:27.178462  4597 caffe.cpp:501] detection_eval = 0.0442477
-I0511 11:49:27.178464  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.178467  4597 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:49:27.178468  4597 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:49:27.178470  4597 caffe.cpp:501] detection_eval = 8.37702
-I0511 11:49:27.178473  4597 caffe.cpp:501] detection_eval = 0.0369189
-I0511 11:49:27.178475  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178478  4597 caffe.cpp:501] detection_eval = 0.927419
-I0511 11:49:27.178479  4597 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:49:27.178481  4597 caffe.cpp:501] detection_eval = 8.44758
-I0511 11:49:27.178483  4597 caffe.cpp:501] detection_eval = 0.0387095
-I0511 11:49:27.178485  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178488  4597 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:49:27.178489  4597 caffe.cpp:501] detection_eval = 7.74395
-I0511 11:49:27.178491  4597 caffe.cpp:501] detection_eval = 8.44758
-I0511 11:49:27.178494  4597 caffe.cpp:501] detection_eval = 0.0371474
-I0511 11:49:27.178496  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178498  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178500  4597 caffe.cpp:501] detection_eval = 7.74395
-I0511 11:49:27.178503  4597 caffe.cpp:501] detection_eval = 8.54637
-I0511 11:49:27.178504  4597 caffe.cpp:501] detection_eval = 0.0432443
-I0511 11:49:27.178508  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178509  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178511  4597 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:49:27.178514  4597 caffe.cpp:501] detection_eval = 8.57056
-I0511 11:49:27.178515  4597 caffe.cpp:501] detection_eval = 0.0418594
-I0511 11:49:27.178517  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178519  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178521  4597 caffe.cpp:501] detection_eval = 7.72782
-I0511 11:49:27.178524  4597 caffe.cpp:501] detection_eval = 8.60282
-I0511 11:49:27.178526  4597 caffe.cpp:501] detection_eval = 0.042764
-I0511 11:49:27.178529  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178530  4597 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:49:27.178532  4597 caffe.cpp:501] detection_eval = 7.72984
-I0511 11:49:27.178534  4597 caffe.cpp:501] detection_eval = 8.62298
-I0511 11:49:27.178536  4597 caffe.cpp:501] detection_eval = 0.0355886
-I0511 11:49:27.178539  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.178540  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178544  4597 caffe.cpp:501] detection_eval = 7.71169
-I0511 11:49:27.178545  4597 caffe.cpp:501] detection_eval = 8.65121
-I0511 11:49:27.178547  4597 caffe.cpp:501] detection_eval = 0.0369829
-I0511 11:49:27.178550  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.178551  4597 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:49:27.178553  4597 caffe.cpp:501] detection_eval = 7.71169
-I0511 11:49:27.178555  4597 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:49:27.178557  4597 caffe.cpp:501] detection_eval = 0.0373797
-I0511 11:49:27.178560  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.178562  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178565  4597 caffe.cpp:501] detection_eval = 7.71573
-I0511 11:49:27.178570  4597 caffe.cpp:501] detection_eval = 8.71169
-I0511 11:49:27.178571  4597 caffe.cpp:501] detection_eval = 0.0356923
-I0511 11:49:27.178573  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.178576  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178578  4597 caffe.cpp:501] detection_eval = 7.71976
-I0511 11:49:27.178581  4597 caffe.cpp:501] detection_eval = 8.71169
-I0511 11:49:27.178586  4597 caffe.cpp:501] detection_eval = 0.0388887
-I0511 11:49:27.178588  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.178592  4597 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:49:27.178596  4597 caffe.cpp:501] detection_eval = 7.6875
-I0511 11:49:27.178599  4597 caffe.cpp:501] detection_eval = 8.6371
-I0511 11:49:27.178603  4597 caffe.cpp:501] detection_eval = 0.0367226
-I0511 11:49:27.178607  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178611  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178614  4597 caffe.cpp:501] detection_eval = 7.6875
-I0511 11:49:27.178617  4597 caffe.cpp:501] detection_eval = 8.7379
-I0511 11:49:27.178620  4597 caffe.cpp:501] detection_eval = 0.0418173
-I0511 11:49:27.178624  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178627  4597 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:49:27.178632  4597 caffe.cpp:501] detection_eval = 7.69355
-I0511 11:49:27.178637  4597 caffe.cpp:501] detection_eval = 8.72984
-I0511 11:49:27.178639  4597 caffe.cpp:501] detection_eval = 0.0378575
-I0511 11:49:27.178642  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178643  4597 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:49:27.178647  4597 caffe.cpp:501] detection_eval = 7.70565
-I0511 11:49:27.178648  4597 caffe.cpp:501] detection_eval = 8.62097
-I0511 11:49:27.178650  4597 caffe.cpp:501] detection_eval = 0.0408286
-I0511 11:49:27.178653  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.178654  4597 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:49:27.178656  4597 caffe.cpp:501] detection_eval = 7.70766
-I0511 11:49:27.178658  4597 caffe.cpp:501] detection_eval = 8.65726
-I0511 11:49:27.178660  4597 caffe.cpp:501] detection_eval = 0.0408957
-I0511 11:49:27.178663  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.178665  4597 caffe.cpp:501] detection_eval = 0.903226
-I0511 11:49:27.178668  4597 caffe.cpp:501] detection_eval = 7.70968
-I0511 11:49:27.178669  4597 caffe.cpp:501] detection_eval = 8.74194
-I0511 11:49:27.178671  4597 caffe.cpp:501] detection_eval = 0.0408394
-I0511 11:49:27.178673  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178675  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178678  4597 caffe.cpp:501] detection_eval = 7.69556
-I0511 11:49:27.178679  4597 caffe.cpp:501] detection_eval = 8.71976
-I0511 11:49:27.178681  4597 caffe.cpp:501] detection_eval = 0.0373829
-I0511 11:49:27.178683  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178685  4597 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:49:27.178688  4597 caffe.cpp:501] detection_eval = 7.69758
-I0511 11:49:27.178690  4597 caffe.cpp:501] detection_eval = 8.7621
-I0511 11:49:27.178692  4597 caffe.cpp:501] detection_eval = 0.0379139
-I0511 11:49:27.178694  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178696  4597 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:49:27.178699  4597 caffe.cpp:501] detection_eval = 7.70161
-I0511 11:49:27.178700  4597 caffe.cpp:501] detection_eval = 8.77419
-I0511 11:49:27.178702  4597 caffe.cpp:501] detection_eval = 0.0377139
-I0511 11:49:27.178704  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178706  4597 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:49:27.178709  4597 caffe.cpp:501] detection_eval = 7.70161
-I0511 11:49:27.178710  4597 caffe.cpp:501] detection_eval = 8.81452
-I0511 11:49:27.178712  4597 caffe.cpp:501] detection_eval = 0.0355406
-I0511 11:49:27.178714  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178717  4597 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:49:27.178722  4597 caffe.cpp:501] detection_eval = 7.70565
-I0511 11:49:27.178725  4597 caffe.cpp:501] detection_eval = 8.8125
-I0511 11:49:27.178726  4597 caffe.cpp:501] detection_eval = 0.0367864
-I0511 11:49:27.178730  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178731  4597 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:49:27.178733  4597 caffe.cpp:501] detection_eval = 7.70968
-I0511 11:49:27.178735  4597 caffe.cpp:501] detection_eval = 8.82056
-I0511 11:49:27.178737  4597 caffe.cpp:501] detection_eval = 0.0366737
-I0511 11:49:27.178740  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.178741  4597 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:49:27.178743  4597 caffe.cpp:501] detection_eval = 7.71371
-I0511 11:49:27.178745  4597 caffe.cpp:501] detection_eval = 8.8246
-I0511 11:49:27.178748  4597 caffe.cpp:501] detection_eval = 0.0387977
-I0511 11:49:27.178750  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178752  4597 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:49:27.178755  4597 caffe.cpp:501] detection_eval = 7.71573
-I0511 11:49:27.178756  4597 caffe.cpp:501] detection_eval = 8.85685
-I0511 11:49:27.178758  4597 caffe.cpp:501] detection_eval = 0.0352025
-I0511 11:49:27.178761  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178762  4597 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:49:27.178764  4597 caffe.cpp:501] detection_eval = 7.70161
-I0511 11:49:27.178766  4597 caffe.cpp:501] detection_eval = 8.87903
-I0511 11:49:27.178768  4597 caffe.cpp:501] detection_eval = 0.0441723
-I0511 11:49:27.178771  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.178773  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178776  4597 caffe.cpp:501] detection_eval = 7.68548
-I0511 11:49:27.178777  4597 caffe.cpp:501] detection_eval = 8.89718
-I0511 11:49:27.178779  4597 caffe.cpp:501] detection_eval = 0.0351511
-I0511 11:49:27.178781  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178783  4597 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:49:27.178786  4597 caffe.cpp:501] detection_eval = 7.68952
-I0511 11:49:27.178788  4597 caffe.cpp:501] detection_eval = 8.8871
-I0511 11:49:27.178791  4597 caffe.cpp:501] detection_eval = 0.0427881
-I0511 11:49:27.178792  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178794  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178797  4597 caffe.cpp:501] detection_eval = 7.68952
-I0511 11:49:27.178798  4597 caffe.cpp:501] detection_eval = 8.97984
-I0511 11:49:27.178800  4597 caffe.cpp:501] detection_eval = 0.0378922
-I0511 11:49:27.178802  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178804  4597 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:49:27.178807  4597 caffe.cpp:501] detection_eval = 7.69153
-I0511 11:49:27.178809  4597 caffe.cpp:501] detection_eval = 9.00202
-I0511 11:49:27.178812  4597 caffe.cpp:501] detection_eval = 0.0416262
-I0511 11:49:27.178813  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178815  4597 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:49:27.178817  4597 caffe.cpp:501] detection_eval = 7.69556
-I0511 11:49:27.178819  4597 caffe.cpp:501] detection_eval = 9.03226
-I0511 11:49:27.178822  4597 caffe.cpp:501] detection_eval = 0.0384373
-I0511 11:49:27.178823  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178825  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178828  4597 caffe.cpp:501] detection_eval = 7.68145
-I0511 11:49:27.178830  4597 caffe.cpp:501] detection_eval = 9.02218
-I0511 11:49:27.178833  4597 caffe.cpp:501] detection_eval = 0.0400031
-I0511 11:49:27.178834  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178836  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178838  4597 caffe.cpp:501] detection_eval = 7.6875
-I0511 11:49:27.178840  4597 caffe.cpp:501] detection_eval = 9.00403
-I0511 11:49:27.178843  4597 caffe.cpp:501] detection_eval = 0.0396534
-I0511 11:49:27.178844  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178846  4597 caffe.cpp:501] detection_eval = 0.91129
-I0511 11:49:27.178851  4597 caffe.cpp:501] detection_eval = 7.69153
-I0511 11:49:27.178854  4597 caffe.cpp:501] detection_eval = 9.10081
-I0511 11:49:27.178856  4597 caffe.cpp:501] detection_eval = 0.0392174
-I0511 11:49:27.178858  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178860  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178863  4597 caffe.cpp:501] detection_eval = 7.67742
-I0511 11:49:27.178864  4597 caffe.cpp:501] detection_eval = 9.09476
-I0511 11:49:27.178866  4597 caffe.cpp:501] detection_eval = 0.0422733
-I0511 11:49:27.178869  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178870  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178874  4597 caffe.cpp:501] detection_eval = 7.68347
-I0511 11:49:27.178875  4597 caffe.cpp:501] detection_eval = 9.08266
-I0511 11:49:27.178877  4597 caffe.cpp:501] detection_eval = 0.0434857
-I0511 11:49:27.178879  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178881  4597 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:49:27.178884  4597 caffe.cpp:501] detection_eval = 7.66532
-I0511 11:49:27.178885  4597 caffe.cpp:501] detection_eval = 9.09677
-I0511 11:49:27.178887  4597 caffe.cpp:501] detection_eval = 0.0416815
-I0511 11:49:27.178889  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178891  4597 caffe.cpp:501] detection_eval = 0.903226
-I0511 11:49:27.178894  4597 caffe.cpp:501] detection_eval = 7.67339
-I0511 11:49:27.178896  4597 caffe.cpp:501] detection_eval = 9.02419
-I0511 11:49:27.178899  4597 caffe.cpp:501] detection_eval = 0.0396996
-I0511 11:49:27.178900  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.178902  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178905  4597 caffe.cpp:501] detection_eval = 7.6754
-I0511 11:49:27.178906  4597 caffe.cpp:501] detection_eval = 9.09476
-I0511 11:49:27.178908  4597 caffe.cpp:501] detection_eval = 0.0444098
-I0511 11:49:27.178911  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178913  4597 caffe.cpp:501] detection_eval = 0.895161
-I0511 11:49:27.178915  4597 caffe.cpp:501] detection_eval = 7.67944
-I0511 11:49:27.178917  4597 caffe.cpp:501] detection_eval = 9.125
-I0511 11:49:27.178920  4597 caffe.cpp:501] detection_eval = 0.0412734
-I0511 11:49:27.178921  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178923  4597 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:49:27.178925  4597 caffe.cpp:501] detection_eval = 7.68145
-I0511 11:49:27.178927  4597 caffe.cpp:501] detection_eval = 9.19355
-I0511 11:49:27.178930  4597 caffe.cpp:501] detection_eval = 0.0384269
-I0511 11:49:27.178931  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.178934  4597 caffe.cpp:501] detection_eval = 0.899194
-I0511 11:49:27.178936  4597 caffe.cpp:501] detection_eval = 7.66532
-I0511 11:49:27.178938  4597 caffe.cpp:501] detection_eval = 9.19355
-I0511 11:49:27.178941  4597 caffe.cpp:501] detection_eval = 0.0394395
-I0511 11:49:27.178942  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178944  4597 caffe.cpp:501] detection_eval = 0.891129
-I0511 11:49:27.178946  4597 caffe.cpp:501] detection_eval = 7.64919
-I0511 11:49:27.178948  4597 caffe.cpp:501] detection_eval = 9.24194
-I0511 11:49:27.178951  4597 caffe.cpp:501] detection_eval = 0.0448292
-I0511 11:49:27.178952  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.178954  4597 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:49:27.178957  4597 caffe.cpp:501] detection_eval = 7.63508
-I0511 11:49:27.178961  4597 caffe.cpp:501] detection_eval = 9.25403
-I0511 11:49:27.178964  4597 caffe.cpp:501] detection_eval = 0.0433481
-I0511 11:49:27.178967  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.178972  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178974  4597 caffe.cpp:501] detection_eval = 7.6371
-I0511 11:49:27.178978  4597 caffe.cpp:501] detection_eval = 9.27823
-I0511 11:49:27.178982  4597 caffe.cpp:501] detection_eval = 0.0414829
-I0511 11:49:27.178984  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.178992  4597 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:49:27.178997  4597 caffe.cpp:501] detection_eval = 7.6371
-I0511 11:49:27.178998  4597 caffe.cpp:501] detection_eval = 9.32863
-I0511 11:49:27.179000  4597 caffe.cpp:501] detection_eval = 0.0429957
-I0511 11:49:27.179003  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179005  4597 caffe.cpp:501] detection_eval = 0.899194
-I0511 11:49:27.179008  4597 caffe.cpp:501] detection_eval = 7.6371
-I0511 11:49:27.179009  4597 caffe.cpp:501] detection_eval = 9.37903
-I0511 11:49:27.179011  4597 caffe.cpp:501] detection_eval = 0.038854
-I0511 11:49:27.179013  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179015  4597 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:49:27.179018  4597 caffe.cpp:501] detection_eval = 7.62097
-I0511 11:49:27.179019  4597 caffe.cpp:501] detection_eval = 9.38911
-I0511 11:49:27.179021  4597 caffe.cpp:501] detection_eval = 0.0417525
-I0511 11:49:27.179023  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179026  4597 caffe.cpp:501] detection_eval = 0.899194
-I0511 11:49:27.179028  4597 caffe.cpp:501] detection_eval = 7.60685
-I0511 11:49:27.179030  4597 caffe.cpp:501] detection_eval = 9.33871
-I0511 11:49:27.179033  4597 caffe.cpp:501] detection_eval = 0.0358288
-I0511 11:49:27.179034  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.179036  4597 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:49:27.179039  4597 caffe.cpp:501] detection_eval = 7.61089
-I0511 11:49:27.179040  4597 caffe.cpp:501] detection_eval = 9.34879
-I0511 11:49:27.179042  4597 caffe.cpp:501] detection_eval = 0.0433477
-I0511 11:49:27.179045  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.179047  4597 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:49:27.179049  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.179051  4597 caffe.cpp:501] detection_eval = 9.34677
-I0511 11:49:27.179054  4597 caffe.cpp:501] detection_eval = 0.0463951
-I0511 11:49:27.179055  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.179057  4597 caffe.cpp:501] detection_eval = 0.891129
-I0511 11:49:27.179060  4597 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:49:27.179062  4597 caffe.cpp:501] detection_eval = 9.40524
-I0511 11:49:27.179064  4597 caffe.cpp:501] detection_eval = 0.038952
-I0511 11:49:27.179066  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.179069  4597 caffe.cpp:501] detection_eval = 0.887097
-I0511 11:49:27.179070  4597 caffe.cpp:501] detection_eval = 7.60282
-I0511 11:49:27.179072  4597 caffe.cpp:501] detection_eval = 9.41734
-I0511 11:49:27.179075  4597 caffe.cpp:501] detection_eval = 0.0382986
-I0511 11:49:27.179076  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179078  4597 caffe.cpp:501] detection_eval = 0.90121
-I0511 11:49:27.179080  4597 caffe.cpp:501] detection_eval = 7.58871
-I0511 11:49:27.179082  4597 caffe.cpp:501] detection_eval = 9.39516
-I0511 11:49:27.179085  4597 caffe.cpp:501] detection_eval = 0.039604
-I0511 11:49:27.179086  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.179088  4597 caffe.cpp:501] detection_eval = 0.885081
-I0511 11:49:27.179091  4597 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:49:27.179093  4597 caffe.cpp:501] detection_eval = 9.46774
-I0511 11:49:27.179095  4597 caffe.cpp:501] detection_eval = 0.0412622
-I0511 11:49:27.179097  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.179100  4597 caffe.cpp:501] detection_eval = 0.879032
-I0511 11:49:27.179101  4597 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:49:27.179103  4597 caffe.cpp:501] detection_eval = 9.47782
-I0511 11:49:27.179105  4597 caffe.cpp:501] detection_eval = 0.0412966
-I0511 11:49:27.179107  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.179109  4597 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:49:27.179111  4597 caffe.cpp:501] detection_eval = 7.5625
-I0511 11:49:27.179113  4597 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:49:27.179116  4597 caffe.cpp:501] detection_eval = 0.0367838
-I0511 11:49:27.179117  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179122  4597 caffe.cpp:501] detection_eval = 0.895161
-I0511 11:49:27.179124  4597 caffe.cpp:501] detection_eval = 7.5504
-I0511 11:49:27.179127  4597 caffe.cpp:501] detection_eval = 9.35685
-I0511 11:49:27.179129  4597 caffe.cpp:501] detection_eval = 0.035985
-I0511 11:49:27.179131  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179133  4597 caffe.cpp:501] detection_eval = 0.885081
-I0511 11:49:27.179136  4597 caffe.cpp:501] detection_eval = 7.53427
-I0511 11:49:27.179137  4597 caffe.cpp:501] detection_eval = 9.37097
-I0511 11:49:27.179139  4597 caffe.cpp:501] detection_eval = 0.0368773
-I0511 11:49:27.179141  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179143  4597 caffe.cpp:501] detection_eval = 0.885081
-I0511 11:49:27.179145  4597 caffe.cpp:501] detection_eval = 7.54032
-I0511 11:49:27.179147  4597 caffe.cpp:501] detection_eval = 9.36492
-I0511 11:49:27.179150  4597 caffe.cpp:501] detection_eval = 0.0505551
-I0511 11:49:27.179152  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.179154  4597 caffe.cpp:501] detection_eval = 0.875
-I0511 11:49:27.179157  4597 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:49:27.179158  4597 caffe.cpp:501] detection_eval = 9.34476
-I0511 11:49:27.179160  4597 caffe.cpp:501] detection_eval = 0.0519777
-I0511 11:49:27.179162  4597 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:49:27.179164  4597 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:49:27.179167  4597 caffe.cpp:501] detection_eval = 7.54839
-I0511 11:49:27.179168  4597 caffe.cpp:501] detection_eval = 9.42742
-I0511 11:49:27.179170  4597 caffe.cpp:501] detection_eval = 0.0499545
-I0511 11:49:27.179173  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.179175  4597 caffe.cpp:501] detection_eval = 0.872984
-I0511 11:49:27.179177  4597 caffe.cpp:501] detection_eval = 7.55242
-I0511 11:49:27.179517  4597 caffe.cpp:501] detection_eval = 9.42944
-I0511 11:49:27.179525  4597 caffe.cpp:501] detection_eval = 0.0417379
-I0511 11:49:27.179528  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.179530  4597 caffe.cpp:501] detection_eval = 0.875
-I0511 11:49:27.179533  4597 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:49:27.179535  4597 caffe.cpp:501] detection_eval = 9.45161
-I0511 11:49:27.179538  4597 caffe.cpp:501] detection_eval = 0.038692
-I0511 11:49:27.179539  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179543  4597 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:49:27.179544  4597 caffe.cpp:501] detection_eval = 7.50403
-I0511 11:49:27.179546  4597 caffe.cpp:501] detection_eval = 9.30847
-I0511 11:49:27.179548  4597 caffe.cpp:501] detection_eval = 0.0404907
-I0511 11:49:27.179550  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.179553  4597 caffe.cpp:501] detection_eval = 0.877016
-I0511 11:49:27.179555  4597 caffe.cpp:501] detection_eval = 7.48992
-I0511 11:49:27.179558  4597 caffe.cpp:501] detection_eval = 9.27419
-I0511 11:49:27.179559  4597 caffe.cpp:501] detection_eval = 0.0372388
-I0511 11:49:27.179561  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179563  4597 caffe.cpp:501] detection_eval = 0.877016
-I0511 11:49:27.179565  4597 caffe.cpp:501] detection_eval = 7.48992
-I0511 11:49:27.179567  4597 caffe.cpp:501] detection_eval = 9.3004
-I0511 11:49:27.179570  4597 caffe.cpp:501] detection_eval = 0.035991
-I0511 11:49:27.179572  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179574  4597 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:49:27.179576  4597 caffe.cpp:501] detection_eval = 7.47379
-I0511 11:49:27.179579  4597 caffe.cpp:501] detection_eval = 9.25605
-I0511 11:49:27.179580  4597 caffe.cpp:501] detection_eval = 0.0347708
-I0511 11:49:27.179584  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.179585  4597 caffe.cpp:501] detection_eval = 0.875
-I0511 11:49:27.179587  4597 caffe.cpp:501] detection_eval = 7.45968
-I0511 11:49:27.179589  4597 caffe.cpp:501] detection_eval = 9.24798
-I0511 11:49:27.179591  4597 caffe.cpp:501] detection_eval = 0.0382323
-I0511 11:49:27.179597  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179600  4597 caffe.cpp:501] detection_eval = 0.872984
-I0511 11:49:27.179602  4597 caffe.cpp:501] detection_eval = 7.45968
-I0511 11:49:27.179605  4597 caffe.cpp:501] detection_eval = 9.33669
-I0511 11:49:27.179606  4597 caffe.cpp:501] detection_eval = 0.0391961
-I0511 11:49:27.179608  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.179611  4597 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:49:27.179613  4597 caffe.cpp:501] detection_eval = 7.44556
-I0511 11:49:27.179615  4597 caffe.cpp:501] detection_eval = 9.33468
-I0511 11:49:27.179617  4597 caffe.cpp:501] detection_eval = 0.0406414
-I0511 11:49:27.179620  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179621  4597 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:49:27.179623  4597 caffe.cpp:501] detection_eval = 7.44556
-I0511 11:49:27.179625  4597 caffe.cpp:501] detection_eval = 9.39919
-I0511 11:49:27.179628  4597 caffe.cpp:501] detection_eval = 0.040219
-I0511 11:49:27.179630  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.179632  4597 caffe.cpp:501] detection_eval = 0.862903
-I0511 11:49:27.179635  4597 caffe.cpp:501] detection_eval = 7.4496
-I0511 11:49:27.179636  4597 caffe.cpp:501] detection_eval = 9.41129
-I0511 11:49:27.179638  4597 caffe.cpp:501] detection_eval = 0.0395767
-I0511 11:49:27.179641  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.179642  4597 caffe.cpp:501] detection_eval = 0.862903
-I0511 11:49:27.179644  4597 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:49:27.179647  4597 caffe.cpp:501] detection_eval = 9.41734
-I0511 11:49:27.179649  4597 caffe.cpp:501] detection_eval = 0.0368327
-I0511 11:49:27.179651  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179653  4597 caffe.cpp:501] detection_eval = 0.872984
-I0511 11:49:27.179656  4597 caffe.cpp:501] detection_eval = 7.45766
-I0511 11:49:27.179657  4597 caffe.cpp:501] detection_eval = 9.41935
-I0511 11:49:27.179659  4597 caffe.cpp:501] detection_eval = 0.0374821
-I0511 11:49:27.179662  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179664  4597 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:49:27.179666  4597 caffe.cpp:501] detection_eval = 7.43952
-I0511 11:49:27.179668  4597 caffe.cpp:501] detection_eval = 9.45766
-I0511 11:49:27.179671  4597 caffe.cpp:501] detection_eval = 0.0341754
-I0511 11:49:27.179672  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179674  4597 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:49:27.179677  4597 caffe.cpp:501] detection_eval = 7.42137
-I0511 11:49:27.179678  4597 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:49:27.179682  4597 caffe.cpp:501] detection_eval = 0.0359759
-I0511 11:49:27.179683  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179685  4597 caffe.cpp:501] detection_eval = 0.862903
-I0511 11:49:27.179687  4597 caffe.cpp:501] detection_eval = 7.4254
-I0511 11:49:27.179689  4597 caffe.cpp:501] detection_eval = 9.48992
-I0511 11:49:27.179692  4597 caffe.cpp:501] detection_eval = 0.0382348
-I0511 11:49:27.179693  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.179695  4597 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:49:27.179697  4597 caffe.cpp:501] detection_eval = 7.39315
-I0511 11:49:27.179700  4597 caffe.cpp:501] detection_eval = 9.41129
-I0511 11:49:27.179702  4597 caffe.cpp:501] detection_eval = 0.0360208
-I0511 11:49:27.179704  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.179706  4597 caffe.cpp:501] detection_eval = 0.856855
-I0511 11:49:27.179708  4597 caffe.cpp:501] detection_eval = 7.35685
-I0511 11:49:27.179710  4597 caffe.cpp:501] detection_eval = 9.41734
-I0511 11:49:27.179713  4597 caffe.cpp:501] detection_eval = 0.0350974
-I0511 11:49:27.179714  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.179716  4597 caffe.cpp:501] detection_eval = 0.860887
-I0511 11:49:27.179719  4597 caffe.cpp:501] detection_eval = 7.34073
-I0511 11:49:27.179721  4597 caffe.cpp:501] detection_eval = 9.43347
-I0511 11:49:27.179725  4597 caffe.cpp:501] detection_eval = 0.0383055
-I0511 11:49:27.179728  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.179730  4597 caffe.cpp:501] detection_eval = 0.852823
-I0511 11:49:27.179733  4597 caffe.cpp:501] detection_eval = 7.30645
-I0511 11:49:27.179734  4597 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:49:27.179736  4597 caffe.cpp:501] detection_eval = 0.0407837
-I0511 11:49:27.179738  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179741  4597 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:49:27.179744  4597 caffe.cpp:501] detection_eval = 7.31048
-I0511 11:49:27.179745  4597 caffe.cpp:501] detection_eval = 9.41532
-I0511 11:49:27.179747  4597 caffe.cpp:501] detection_eval = 0.0402762
-I0511 11:49:27.179749  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.179751  4597 caffe.cpp:501] detection_eval = 0.850806
-I0511 11:49:27.179754  4597 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:49:27.179755  4597 caffe.cpp:501] detection_eval = 9.42137
-I0511 11:49:27.179757  4597 caffe.cpp:501] detection_eval = 0.0335361
-I0511 11:49:27.179760  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.179762  4597 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:49:27.179764  4597 caffe.cpp:501] detection_eval = 7.29637
-I0511 11:49:27.179766  4597 caffe.cpp:501] detection_eval = 9.45161
-I0511 11:49:27.179769  4597 caffe.cpp:501] detection_eval = 0.037912
-I0511 11:49:27.179770  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.179772  4597 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:49:27.179774  4597 caffe.cpp:501] detection_eval = 7.29637
-I0511 11:49:27.179776  4597 caffe.cpp:501] detection_eval = 9.51613
-I0511 11:49:27.179780  4597 caffe.cpp:501] detection_eval = 0.0341082
-I0511 11:49:27.179781  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.180295  4597 caffe.cpp:501] detection_eval = 0.856855
-I0511 11:49:27.180303  4597 caffe.cpp:501] detection_eval = 7.27823
-I0511 11:49:27.180306  4597 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:49:27.180308  4597 caffe.cpp:501] detection_eval = 0.0324871
-I0511 11:49:27.180310  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.180313  4597 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:49:27.180315  4597 caffe.cpp:501] detection_eval = 7.26411
-I0511 11:49:27.180317  4597 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:49:27.180320  4597 caffe.cpp:501] detection_eval = 0.0307059
-I0511 11:49:27.180321  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.180323  4597 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:49:27.180326  4597 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:49:27.180328  4597 caffe.cpp:501] detection_eval = 9.47984
-I0511 11:49:27.180330  4597 caffe.cpp:501] detection_eval = 0.0358411
-I0511 11:49:27.180332  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.180335  4597 caffe.cpp:501] detection_eval = 0.842742
-I0511 11:49:27.180336  4597 caffe.cpp:501] detection_eval = 7.24798
-I0511 11:49:27.180338  4597 caffe.cpp:501] detection_eval = 9.48387
-I0511 11:49:27.180341  4597 caffe.cpp:501] detection_eval = 0.0337295
-I0511 11:49:27.180343  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.180346  4597 caffe.cpp:501] detection_eval = 0.852823
-I0511 11:49:27.180347  4597 caffe.cpp:501] detection_eval = 7.21774
-I0511 11:49:27.180349  4597 caffe.cpp:501] detection_eval = 9.38911
-I0511 11:49:27.180351  4597 caffe.cpp:501] detection_eval = 0.0364457
-I0511 11:49:27.180353  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180356  4597 caffe.cpp:501] detection_eval = 0.840726
-I0511 11:49:27.180357  4597 caffe.cpp:501] detection_eval = 7.21774
-I0511 11:49:27.180359  4597 caffe.cpp:501] detection_eval = 9.42944
-I0511 11:49:27.180362  4597 caffe.cpp:501] detection_eval = 0.0339522
-I0511 11:49:27.180364  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.180366  4597 caffe.cpp:501] detection_eval = 0.844758
-I0511 11:49:27.180368  4597 caffe.cpp:501] detection_eval = 7.21774
-I0511 11:49:27.180371  4597 caffe.cpp:501] detection_eval = 9.46573
-I0511 11:49:27.180377  4597 caffe.cpp:501] detection_eval = 0.0348179
-I0511 11:49:27.180378  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.180380  4597 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:49:27.180382  4597 caffe.cpp:501] detection_eval = 7.21976
-I0511 11:49:27.180385  4597 caffe.cpp:501] detection_eval = 9.48589
-I0511 11:49:27.180387  4597 caffe.cpp:501] detection_eval = 0.0332978
-I0511 11:49:27.180389  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.180392  4597 caffe.cpp:501] detection_eval = 0.842742
-I0511 11:49:27.180393  4597 caffe.cpp:501] detection_eval = 7.20766
-I0511 11:49:27.180395  4597 caffe.cpp:501] detection_eval = 9.41935
-I0511 11:49:27.180397  4597 caffe.cpp:501] detection_eval = 0.0338939
-I0511 11:49:27.180399  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180402  4597 caffe.cpp:501] detection_eval = 0.836694
-I0511 11:49:27.180404  4597 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:49:27.180407  4597 caffe.cpp:501] detection_eval = 9.45565
-I0511 11:49:27.180408  4597 caffe.cpp:501] detection_eval = 0.0335557
-I0511 11:49:27.180410  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.180413  4597 caffe.cpp:501] detection_eval = 0.836694
-I0511 11:49:27.180414  4597 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:49:27.180416  4597 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:49:27.180418  4597 caffe.cpp:501] detection_eval = 0.0340941
-I0511 11:49:27.180421  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.180423  4597 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:49:27.180425  4597 caffe.cpp:501] detection_eval = 7.21169
-I0511 11:49:27.180428  4597 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:49:27.180429  4597 caffe.cpp:501] detection_eval = 0.0310222
-I0511 11:49:27.180431  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180433  4597 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:49:27.180436  4597 caffe.cpp:501] detection_eval = 7.21371
-I0511 11:49:27.180438  4597 caffe.cpp:501] detection_eval = 9.57661
-I0511 11:49:27.180440  4597 caffe.cpp:501] detection_eval = 0.0336776
-I0511 11:49:27.180443  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.180444  4597 caffe.cpp:501] detection_eval = 0.836694
-I0511 11:49:27.180446  4597 caffe.cpp:501] detection_eval = 7.21371
-I0511 11:49:27.180449  4597 caffe.cpp:501] detection_eval = 9.64919
-I0511 11:49:27.180450  4597 caffe.cpp:501] detection_eval = 0.0354826
-I0511 11:49:27.180454  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180455  4597 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:49:27.180457  4597 caffe.cpp:501] detection_eval = 7.21573
-I0511 11:49:27.180459  4597 caffe.cpp:501] detection_eval = 9.68952
-I0511 11:49:27.180461  4597 caffe.cpp:501] detection_eval = 0.0353965
-I0511 11:49:27.180464  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.180465  4597 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:49:27.180467  4597 caffe.cpp:501] detection_eval = 7.20161
-I0511 11:49:27.180470  4597 caffe.cpp:501] detection_eval = 9.66734
-I0511 11:49:27.180472  4597 caffe.cpp:501] detection_eval = 0.0352699
-I0511 11:49:27.180474  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.180476  4597 caffe.cpp:501] detection_eval = 0.830645
-I0511 11:49:27.180479  4597 caffe.cpp:501] detection_eval = 7.20161
-I0511 11:49:27.180480  4597 caffe.cpp:501] detection_eval = 9.7621
-I0511 11:49:27.180482  4597 caffe.cpp:501] detection_eval = 0.0368593
-I0511 11:49:27.180485  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.180486  4597 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:49:27.180490  4597 caffe.cpp:501] detection_eval = 7.16734
-I0511 11:49:27.180491  4597 caffe.cpp:501] detection_eval = 9.71371
-I0511 11:49:27.180493  4597 caffe.cpp:501] detection_eval = 0.0397446
-I0511 11:49:27.180495  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.180497  4597 caffe.cpp:501] detection_eval = 0.826613
-I0511 11:49:27.180500  4597 caffe.cpp:501] detection_eval = 7.15121
-I0511 11:49:27.180505  4597 caffe.cpp:501] detection_eval = 9.70565
-I0511 11:49:27.180506  4597 caffe.cpp:501] detection_eval = 0.0369758
-I0511 11:49:27.180508  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.180511  4597 caffe.cpp:501] detection_eval = 0.828629
-I0511 11:49:27.180513  4597 caffe.cpp:501] detection_eval = 7.15121
-I0511 11:49:27.180516  4597 caffe.cpp:501] detection_eval = 9.78629
-I0511 11:49:27.180517  4597 caffe.cpp:501] detection_eval = 0.0347746
-I0511 11:49:27.180519  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.180521  4597 caffe.cpp:501] detection_eval = 0.830645
-I0511 11:49:27.180541  4597 caffe.cpp:501] detection_eval = 7.11895
-I0511 11:49:27.180544  4597 caffe.cpp:501] detection_eval = 9.73387
-I0511 11:49:27.180547  4597 caffe.cpp:501] detection_eval = 0.0392505
-I0511 11:49:27.180550  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.180552  4597 caffe.cpp:501] detection_eval = 0.814516
-I0511 11:49:27.180554  4597 caffe.cpp:501] detection_eval = 7.10282
-I0511 11:49:27.180557  4597 caffe.cpp:501] detection_eval = 9.72379
-I0511 11:49:27.180558  4597 caffe.cpp:501] detection_eval = 0.0338769
-I0511 11:49:27.180560  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.180562  4597 caffe.cpp:501] detection_eval = 0.828629
-I0511 11:49:27.180564  4597 caffe.cpp:501] detection_eval = 7.10484
-I0511 11:49:27.180567  4597 caffe.cpp:501] detection_eval = 9.7621
-I0511 11:49:27.180569  4597 caffe.cpp:501] detection_eval = 0.0340421
-I0511 11:49:27.180572  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.180573  4597 caffe.cpp:501] detection_eval = 0.826613
-I0511 11:49:27.180575  4597 caffe.cpp:501] detection_eval = 7.10685
-I0511 11:49:27.180577  4597 caffe.cpp:501] detection_eval = 9.82056
-I0511 11:49:27.181082  4597 caffe.cpp:501] detection_eval = 0.0402648
-I0511 11:49:27.181089  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181092  4597 caffe.cpp:501] detection_eval = 0.822581
-I0511 11:49:27.181094  4597 caffe.cpp:501] detection_eval = 7.1129
-I0511 11:49:27.181097  4597 caffe.cpp:501] detection_eval = 9.78226
-I0511 11:49:27.181099  4597 caffe.cpp:501] detection_eval = 0.0347552
-I0511 11:49:27.181102  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.181103  4597 caffe.cpp:501] detection_eval = 0.824597
-I0511 11:49:27.181105  4597 caffe.cpp:501] detection_eval = 7.06452
-I0511 11:49:27.181108  4597 caffe.cpp:501] detection_eval = 9.68145
-I0511 11:49:27.181110  4597 caffe.cpp:501] detection_eval = 0.0383627
-I0511 11:49:27.181113  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.181114  4597 caffe.cpp:501] detection_eval = 0.810484
-I0511 11:49:27.181116  4597 caffe.cpp:501] detection_eval = 7.06452
-I0511 11:49:27.181118  4597 caffe.cpp:501] detection_eval = 9.7621
-I0511 11:49:27.181120  4597 caffe.cpp:501] detection_eval = 0.035053
-I0511 11:49:27.181123  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181125  4597 caffe.cpp:501] detection_eval = 0.814516
-I0511 11:49:27.181128  4597 caffe.cpp:501] detection_eval = 7.03024
-I0511 11:49:27.181129  4597 caffe.cpp:501] detection_eval = 9.75
-I0511 11:49:27.181131  4597 caffe.cpp:501] detection_eval = 0.0352481
-I0511 11:49:27.181133  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.181135  4597 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:49:27.181138  4597 caffe.cpp:501] detection_eval = 7.03226
-I0511 11:49:27.181140  4597 caffe.cpp:501] detection_eval = 9.8004
-I0511 11:49:27.181143  4597 caffe.cpp:501] detection_eval = 0.0372214
-I0511 11:49:27.181144  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181146  4597 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:49:27.181149  4597 caffe.cpp:501] detection_eval = 7.02218
-I0511 11:49:27.181150  4597 caffe.cpp:501] detection_eval = 9.69758
-I0511 11:49:27.181154  4597 caffe.cpp:501] detection_eval = 0.03344
-I0511 11:49:27.181155  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181157  4597 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:49:27.181159  4597 caffe.cpp:501] detection_eval = 7.02419
-I0511 11:49:27.181165  4597 caffe.cpp:501] detection_eval = 9.70968
-I0511 11:49:27.181169  4597 caffe.cpp:501] detection_eval = 0.0327785
-I0511 11:49:27.181170  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181172  4597 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:49:27.181174  4597 caffe.cpp:501] detection_eval = 7.01008
-I0511 11:49:27.181176  4597 caffe.cpp:501] detection_eval = 9.68145
-I0511 11:49:27.181179  4597 caffe.cpp:501] detection_eval = 0.0364491
-I0511 11:49:27.181180  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181183  4597 caffe.cpp:501] detection_eval = 0.804435
-I0511 11:49:27.181185  4597 caffe.cpp:501] detection_eval = 6.99597
-I0511 11:49:27.181187  4597 caffe.cpp:501] detection_eval = 9.61694
-I0511 11:49:27.181190  4597 caffe.cpp:501] detection_eval = 0.0331811
-I0511 11:49:27.181191  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.181193  4597 caffe.cpp:501] detection_eval = 0.804435
-I0511 11:49:27.181195  4597 caffe.cpp:501] detection_eval = 6.97782
-I0511 11:49:27.181197  4597 caffe.cpp:501] detection_eval = 9.68548
-I0511 11:49:27.181200  4597 caffe.cpp:501] detection_eval = 0.0387094
-I0511 11:49:27.181202  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.181205  4597 caffe.cpp:501] detection_eval = 0.798387
-I0511 11:49:27.181206  4597 caffe.cpp:501] detection_eval = 6.97984
-I0511 11:49:27.181208  4597 caffe.cpp:501] detection_eval = 9.72177
-I0511 11:49:27.181210  4597 caffe.cpp:501] detection_eval = 0.0393089
-I0511 11:49:27.181212  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181215  4597 caffe.cpp:501] detection_eval = 0.800403
-I0511 11:49:27.181216  4597 caffe.cpp:501] detection_eval = 6.98589
-I0511 11:49:27.181219  4597 caffe.cpp:501] detection_eval = 9.6754
-I0511 11:49:27.181221  4597 caffe.cpp:501] detection_eval = 0.0372463
-I0511 11:49:27.181223  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.181226  4597 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:49:27.181227  4597 caffe.cpp:501] detection_eval = 6.96774
-I0511 11:49:27.181229  4597 caffe.cpp:501] detection_eval = 9.70363
-I0511 11:49:27.181231  4597 caffe.cpp:501] detection_eval = 0.0344107
-I0511 11:49:27.181234  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181236  4597 caffe.cpp:501] detection_eval = 0.806452
-I0511 11:49:27.181238  4597 caffe.cpp:501] detection_eval = 6.97379
-I0511 11:49:27.181241  4597 caffe.cpp:501] detection_eval = 9.65726
-I0511 11:49:27.181242  4597 caffe.cpp:501] detection_eval = 0.0359498
-I0511 11:49:27.181244  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181246  4597 caffe.cpp:501] detection_eval = 0.800403
-I0511 11:49:27.181249  4597 caffe.cpp:501] detection_eval = 6.95766
-I0511 11:49:27.181252  4597 caffe.cpp:501] detection_eval = 9.67137
-I0511 11:49:27.181253  4597 caffe.cpp:501] detection_eval = 0.0368076
-I0511 11:49:27.181255  4597 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:49:27.181257  4597 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:49:27.181259  4597 caffe.cpp:501] detection_eval = 6.92339
-I0511 11:49:27.181262  4597 caffe.cpp:501] detection_eval = 9.62097
-I0511 11:49:27.181263  4597 caffe.cpp:501] detection_eval = 0.0362358
-I0511 11:49:27.181267  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181268  4597 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:49:27.181270  4597 caffe.cpp:501] detection_eval = 6.92742
-I0511 11:49:27.181272  4597 caffe.cpp:501] detection_eval = 9.61895
-I0511 11:49:27.181274  4597 caffe.cpp:501] detection_eval = 0.0322296
-I0511 11:49:27.181277  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181278  4597 caffe.cpp:501] detection_eval = 0.798387
-I0511 11:49:27.181280  4597 caffe.cpp:501] detection_eval = 6.92742
-I0511 11:49:27.181282  4597 caffe.cpp:501] detection_eval = 9.71573
-I0511 11:49:27.181284  4597 caffe.cpp:501] detection_eval = 0.0376627
-I0511 11:49:27.181288  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.181289  4597 caffe.cpp:501] detection_eval = 0.78629
-I0511 11:49:27.181293  4597 caffe.cpp:501] detection_eval = 6.89315
-I0511 11:49:27.181296  4597 caffe.cpp:501] detection_eval = 9.68548
-I0511 11:49:27.181298  4597 caffe.cpp:501] detection_eval = 0.0382296
-I0511 11:49:27.181300  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181303  4597 caffe.cpp:501] detection_eval = 0.788306
-I0511 11:49:27.181304  4597 caffe.cpp:501] detection_eval = 6.87903
-I0511 11:49:27.181306  4597 caffe.cpp:501] detection_eval = 9.63306
-I0511 11:49:27.181308  4597 caffe.cpp:501] detection_eval = 0.0326784
-I0511 11:49:27.181311  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181313  4597 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:49:27.181315  4597 caffe.cpp:501] detection_eval = 6.87903
-I0511 11:49:27.181318  4597 caffe.cpp:501] detection_eval = 9.71169
-I0511 11:49:27.181319  4597 caffe.cpp:501] detection_eval = 0.0341897
-I0511 11:49:27.181321  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.181324  4597 caffe.cpp:501] detection_eval = 0.790323
-I0511 11:49:27.181325  4597 caffe.cpp:501] detection_eval = 6.88306
-I0511 11:49:27.181327  4597 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:49:27.181330  4597 caffe.cpp:501] detection_eval = 0.031211
-I0511 11:49:27.181332  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181334  4597 caffe.cpp:501] detection_eval = 0.794355
-I0511 11:49:27.181336  4597 caffe.cpp:501] detection_eval = 6.88508
-I0511 11:49:27.181339  4597 caffe.cpp:501] detection_eval = 9.75605
-I0511 11:49:27.181340  4597 caffe.cpp:501] detection_eval = 0.0357487
-I0511 11:49:27.181342  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181344  4597 caffe.cpp:501] detection_eval = 0.78629
-I0511 11:49:27.181859  4597 caffe.cpp:501] detection_eval = 6.84879
-I0511 11:49:27.181867  4597 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:49:27.181870  4597 caffe.cpp:501] detection_eval = 0.0373732
-I0511 11:49:27.181874  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.181875  4597 caffe.cpp:501] detection_eval = 0.782258
-I0511 11:49:27.181877  4597 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:49:27.181879  4597 caffe.cpp:501] detection_eval = 9.63105
-I0511 11:49:27.181882  4597 caffe.cpp:501] detection_eval = 0.0330568
-I0511 11:49:27.181885  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181886  4597 caffe.cpp:501] detection_eval = 0.782258
-I0511 11:49:27.181888  4597 caffe.cpp:501] detection_eval = 6.80242
-I0511 11:49:27.181890  4597 caffe.cpp:501] detection_eval = 9.66532
-I0511 11:49:27.181892  4597 caffe.cpp:501] detection_eval = 0.0361717
-I0511 11:49:27.181895  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.181897  4597 caffe.cpp:501] detection_eval = 0.774194
-I0511 11:49:27.181900  4597 caffe.cpp:501] detection_eval = 6.80444
-I0511 11:49:27.181901  4597 caffe.cpp:501] detection_eval = 9.67339
-I0511 11:49:27.181903  4597 caffe.cpp:501] detection_eval = 0.0313601
-I0511 11:49:27.181905  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181908  4597 caffe.cpp:501] detection_eval = 0.788306
-I0511 11:49:27.181910  4597 caffe.cpp:501] detection_eval = 6.75
-I0511 11:49:27.181912  4597 caffe.cpp:501] detection_eval = 9.59476
-I0511 11:49:27.181915  4597 caffe.cpp:501] detection_eval = 0.0277536
-I0511 11:49:27.181916  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181918  4597 caffe.cpp:501] detection_eval = 0.778226
-I0511 11:49:27.181921  4597 caffe.cpp:501] detection_eval = 6.73387
-I0511 11:49:27.181923  4597 caffe.cpp:501] detection_eval = 9.59677
-I0511 11:49:27.181926  4597 caffe.cpp:501] detection_eval = 0.0289066
-I0511 11:49:27.181927  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181929  4597 caffe.cpp:501] detection_eval = 0.778226
-I0511 11:49:27.181931  4597 caffe.cpp:501] detection_eval = 6.74194
-I0511 11:49:27.181933  4597 caffe.cpp:501] detection_eval = 9.51815
-I0511 11:49:27.181936  4597 caffe.cpp:501] detection_eval = 0.0267913
-I0511 11:49:27.181938  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181943  4597 caffe.cpp:501] detection_eval = 0.778226
-I0511 11:49:27.181946  4597 caffe.cpp:501] detection_eval = 6.74194
-I0511 11:49:27.181948  4597 caffe.cpp:501] detection_eval = 9.57056
-I0511 11:49:27.181951  4597 caffe.cpp:501] detection_eval = 0.0279466
-I0511 11:49:27.181952  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.181954  4597 caffe.cpp:501] detection_eval = 0.774194
-I0511 11:49:27.181957  4597 caffe.cpp:501] detection_eval = 6.72581
-I0511 11:49:27.181959  4597 caffe.cpp:501] detection_eval = 9.53831
-I0511 11:49:27.181962  4597 caffe.cpp:501] detection_eval = 0.0318604
-I0511 11:49:27.181963  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.181965  4597 caffe.cpp:501] detection_eval = 0.772177
-I0511 11:49:27.181967  4597 caffe.cpp:501] detection_eval = 6.72782
-I0511 11:49:27.181969  4597 caffe.cpp:501] detection_eval = 9.60081
-I0511 11:49:27.181972  4597 caffe.cpp:501] detection_eval = 0.0274806
-I0511 11:49:27.181973  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181977  4597 caffe.cpp:501] detection_eval = 0.778226
-I0511 11:49:27.181978  4597 caffe.cpp:501] detection_eval = 6.69556
-I0511 11:49:27.181980  4597 caffe.cpp:501] detection_eval = 9.50605
-I0511 11:49:27.181982  4597 caffe.cpp:501] detection_eval = 0.0277608
-I0511 11:49:27.181984  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181987  4597 caffe.cpp:501] detection_eval = 0.774194
-I0511 11:49:27.181988  4597 caffe.cpp:501] detection_eval = 6.70161
-I0511 11:49:27.181991  4597 caffe.cpp:501] detection_eval = 9.48589
-I0511 11:49:27.181993  4597 caffe.cpp:501] detection_eval = 0.0303468
-I0511 11:49:27.181995  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.181998  4597 caffe.cpp:501] detection_eval = 0.772177
-I0511 11:49:27.181999  4597 caffe.cpp:501] detection_eval = 6.70161
-I0511 11:49:27.182001  4597 caffe.cpp:501] detection_eval = 9.55444
-I0511 11:49:27.182004  4597 caffe.cpp:501] detection_eval = 0.0327595
-I0511 11:49:27.182006  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182008  4597 caffe.cpp:501] detection_eval = 0.768145
-I0511 11:49:27.182010  4597 caffe.cpp:501] detection_eval = 6.70766
-I0511 11:49:27.182013  4597 caffe.cpp:501] detection_eval = 9.51815
-I0511 11:49:27.182014  4597 caffe.cpp:501] detection_eval = 0.029785
-I0511 11:49:27.182016  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182018  4597 caffe.cpp:501] detection_eval = 0.774194
-I0511 11:49:27.182021  4597 caffe.cpp:501] detection_eval = 6.69556
-I0511 11:49:27.182024  4597 caffe.cpp:501] detection_eval = 9.44758
-I0511 11:49:27.182025  4597 caffe.cpp:501] detection_eval = 0.0328393
-I0511 11:49:27.182027  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182029  4597 caffe.cpp:501] detection_eval = 0.762097
-I0511 11:49:27.182031  4597 caffe.cpp:501] detection_eval = 6.67944
-I0511 11:49:27.182034  4597 caffe.cpp:501] detection_eval = 9.43347
-I0511 11:49:27.182035  4597 caffe.cpp:501] detection_eval = 0.0325699
-I0511 11:49:27.182037  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182040  4597 caffe.cpp:501] detection_eval = 0.764113
-I0511 11:49:27.182042  4597 caffe.cpp:501] detection_eval = 6.64315
-I0511 11:49:27.182044  4597 caffe.cpp:501] detection_eval = 9.40927
-I0511 11:49:27.182046  4597 caffe.cpp:501] detection_eval = 0.0298599
-I0511 11:49:27.182049  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182050  4597 caffe.cpp:501] detection_eval = 0.762097
-I0511 11:49:27.182052  4597 caffe.cpp:501] detection_eval = 6.64315
-I0511 11:49:27.182054  4597 caffe.cpp:501] detection_eval = 9.49597
-I0511 11:49:27.182057  4597 caffe.cpp:501] detection_eval = 0.0361235
-I0511 11:49:27.182060  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182061  4597 caffe.cpp:501] detection_eval = 0.756048
-I0511 11:49:27.182063  4597 caffe.cpp:501] detection_eval = 6.61089
-I0511 11:49:27.182065  4597 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:49:27.182067  4597 caffe.cpp:501] detection_eval = 0.034698
-I0511 11:49:27.182070  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182075  4597 caffe.cpp:501] detection_eval = 0.756048
-I0511 11:49:27.182077  4597 caffe.cpp:501] detection_eval = 6.61089
-I0511 11:49:27.182080  4597 caffe.cpp:501] detection_eval = 9.47984
-I0511 11:49:27.182081  4597 caffe.cpp:501] detection_eval = 0.0287569
-I0511 11:49:27.182083  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182085  4597 caffe.cpp:501] detection_eval = 0.762097
-I0511 11:49:27.182087  4597 caffe.cpp:501] detection_eval = 6.59476
-I0511 11:49:27.182090  4597 caffe.cpp:501] detection_eval = 9.47984
-I0511 11:49:27.182092  4597 caffe.cpp:501] detection_eval = 0.0304031
-I0511 11:49:27.182094  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182096  4597 caffe.cpp:501] detection_eval = 0.758065
-I0511 11:49:27.182098  4597 caffe.cpp:501] detection_eval = 6.58468
-I0511 11:49:27.182101  4597 caffe.cpp:501] detection_eval = 9.3629
-I0511 11:49:27.182102  4597 caffe.cpp:501] detection_eval = 0.0284584
-I0511 11:49:27.182104  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182107  4597 caffe.cpp:501] detection_eval = 0.754032
-I0511 11:49:27.182109  4597 caffe.cpp:501] detection_eval = 6.56855
-I0511 11:49:27.182111  4597 caffe.cpp:501] detection_eval = 9.33266
-I0511 11:49:27.182113  4597 caffe.cpp:501] detection_eval = 0.0278271
-I0511 11:49:27.182116  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.182117  4597 caffe.cpp:501] detection_eval = 0.756048
-I0511 11:49:27.182119  4597 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:49:27.182122  4597 caffe.cpp:501] detection_eval = 9.34677
-I0511 11:49:27.182124  4597 caffe.cpp:501] detection_eval = 0.0331575
-I0511 11:49:27.182631  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182638  4597 caffe.cpp:501] detection_eval = 0.745968
-I0511 11:49:27.182641  4597 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:49:27.182643  4597 caffe.cpp:501] detection_eval = 9.26613
-I0511 11:49:27.182646  4597 caffe.cpp:501] detection_eval = 0.0300592
-I0511 11:49:27.182648  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182651  4597 caffe.cpp:501] detection_eval = 0.741935
-I0511 11:49:27.182652  4597 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:49:27.182654  4597 caffe.cpp:501] detection_eval = 9.30242
-I0511 11:49:27.182657  4597 caffe.cpp:501] detection_eval = 0.0260824
-I0511 11:49:27.182659  4597 caffe.cpp:501] detection_eval = 0
-I0511 11:49:27.182662  4597 caffe.cpp:501] detection_eval = 0.752016
-I0511 11:49:27.182663  4597 caffe.cpp:501] detection_eval = 6.50202
-I0511 11:49:27.182665  4597 caffe.cpp:501] detection_eval = 9.31653
-I0511 11:49:27.182667  4597 caffe.cpp:501] detection_eval = 0.0286702
-I0511 11:49:27.182670  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182672  4597 caffe.cpp:501] detection_eval = 0.741935
-I0511 11:49:27.182674  4597 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:49:27.182677  4597 caffe.cpp:501] detection_eval = 9.21976
-I0511 11:49:27.182678  4597 caffe.cpp:501] detection_eval = 0.0263043
-I0511 11:49:27.182680  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.182683  4597 caffe.cpp:501] detection_eval = 0.741935
-I0511 11:49:27.182685  4597 caffe.cpp:501] detection_eval = 6.45161
-I0511 11:49:27.182687  4597 caffe.cpp:501] detection_eval = 9.24194
-I0511 11:49:27.182689  4597 caffe.cpp:501] detection_eval = 0.0275095
-I0511 11:49:27.182691  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182693  4597 caffe.cpp:501] detection_eval = 0.737903
-I0511 11:49:27.182695  4597 caffe.cpp:501] detection_eval = 6.43347
-I0511 11:49:27.182698  4597 caffe.cpp:501] detection_eval = 9.30847
-I0511 11:49:27.182700  4597 caffe.cpp:501] detection_eval = 0.03099
-I0511 11:49:27.182703  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182704  4597 caffe.cpp:501] detection_eval = 0.731855
-I0511 11:49:27.182706  4597 caffe.cpp:501] detection_eval = 6.4375
-I0511 11:49:27.182708  4597 caffe.cpp:501] detection_eval = 9.27419
-I0511 11:49:27.182710  4597 caffe.cpp:501] detection_eval = 0.0284238
-I0511 11:49:27.182716  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182719  4597 caffe.cpp:501] detection_eval = 0.737903
-I0511 11:49:27.182721  4597 caffe.cpp:501] detection_eval = 6.42339
-I0511 11:49:27.182723  4597 caffe.cpp:501] detection_eval = 9.20363
-I0511 11:49:27.182725  4597 caffe.cpp:501] detection_eval = 0.0305747
-I0511 11:49:27.182727  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182730  4597 caffe.cpp:501] detection_eval = 0.733871
-I0511 11:49:27.182732  4597 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:49:27.182734  4597 caffe.cpp:501] detection_eval = 9.18952
-I0511 11:49:27.182736  4597 caffe.cpp:501] detection_eval = 0.0271628
-I0511 11:49:27.182739  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182740  4597 caffe.cpp:501] detection_eval = 0.733871
-I0511 11:49:27.182742  4597 caffe.cpp:501] detection_eval = 6.36895
-I0511 11:49:27.182745  4597 caffe.cpp:501] detection_eval = 9.20968
-I0511 11:49:27.182747  4597 caffe.cpp:501] detection_eval = 0.0313459
-I0511 11:49:27.182749  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182751  4597 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:49:27.182754  4597 caffe.cpp:501] detection_eval = 6.35887
-I0511 11:49:27.182755  4597 caffe.cpp:501] detection_eval = 9.11089
-I0511 11:49:27.182757  4597 caffe.cpp:501] detection_eval = 0.0295643
-I0511 11:49:27.182760  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182761  4597 caffe.cpp:501] detection_eval = 0.725806
-I0511 11:49:27.182765  4597 caffe.cpp:501] detection_eval = 6.34073
-I0511 11:49:27.182766  4597 caffe.cpp:501] detection_eval = 9.14113
-I0511 11:49:27.182768  4597 caffe.cpp:501] detection_eval = 0.0305493
-I0511 11:49:27.182770  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182772  4597 caffe.cpp:501] detection_eval = 0.725806
-I0511 11:49:27.182775  4597 caffe.cpp:501] detection_eval = 6.34476
-I0511 11:49:27.182777  4597 caffe.cpp:501] detection_eval = 9.10484
-I0511 11:49:27.182780  4597 caffe.cpp:501] detection_eval = 0.0297302
-I0511 11:49:27.182781  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182783  4597 caffe.cpp:501] detection_eval = 0.725806
-I0511 11:49:27.182785  4597 caffe.cpp:501] detection_eval = 6.32863
-I0511 11:49:27.182787  4597 caffe.cpp:501] detection_eval = 9.08468
-I0511 11:49:27.182790  4597 caffe.cpp:501] detection_eval = 0.0293979
-I0511 11:49:27.182791  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182795  4597 caffe.cpp:501] detection_eval = 0.721774
-I0511 11:49:27.182796  4597 caffe.cpp:501] detection_eval = 6.31452
-I0511 11:49:27.182798  4597 caffe.cpp:501] detection_eval = 9.04435
-I0511 11:49:27.182801  4597 caffe.cpp:501] detection_eval = 0.0291608
-I0511 11:49:27.182802  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182804  4597 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:49:27.182806  4597 caffe.cpp:501] detection_eval = 6.31653
-I0511 11:49:27.182808  4597 caffe.cpp:501] detection_eval = 9.08669
-I0511 11:49:27.182811  4597 caffe.cpp:501] detection_eval = 0.0270491
-I0511 11:49:27.182813  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.182816  4597 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:49:27.182817  4597 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:49:27.182819  4597 caffe.cpp:501] detection_eval = 9.03831
-I0511 11:49:27.182821  4597 caffe.cpp:501] detection_eval = 0.0289935
-I0511 11:49:27.182823  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.182826  4597 caffe.cpp:501] detection_eval = 0.715726
-I0511 11:49:27.182828  4597 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:49:27.182831  4597 caffe.cpp:501] detection_eval = 9.09476
-I0511 11:49:27.182832  4597 caffe.cpp:501] detection_eval = 0.0290409
-I0511 11:49:27.182834  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182837  4597 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:49:27.182838  4597 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:49:27.182840  4597 caffe.cpp:501] detection_eval = 9.15524
-I0511 11:49:27.182845  4597 caffe.cpp:501] detection_eval = 0.030946
-I0511 11:49:27.182848  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.182850  4597 caffe.cpp:501] detection_eval = 0.71371
-I0511 11:49:27.182852  4597 caffe.cpp:501] detection_eval = 6.28629
-I0511 11:49:27.182854  4597 caffe.cpp:501] detection_eval = 9.14516
-I0511 11:49:27.182857  4597 caffe.cpp:501] detection_eval = 0.0287102
-I0511 11:49:27.182858  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182862  4597 caffe.cpp:501] detection_eval = 0.715726
-I0511 11:49:27.182863  4597 caffe.cpp:501] detection_eval = 6.29032
-I0511 11:49:27.182865  4597 caffe.cpp:501] detection_eval = 9.13911
-I0511 11:49:27.182868  4597 caffe.cpp:501] detection_eval = 0.0277487
-I0511 11:49:27.182869  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.182871  4597 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:49:27.182873  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.182875  4597 caffe.cpp:501] detection_eval = 9.1875
-I0511 11:49:27.182878  4597 caffe.cpp:501] detection_eval = 0.0340422
-I0511 11:49:27.182880  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.182883  4597 caffe.cpp:501] detection_eval = 0.705645
-I0511 11:49:27.182884  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.182886  4597 caffe.cpp:501] detection_eval = 9.24194
-I0511 11:49:27.182888  4597 caffe.cpp:501] detection_eval = 0.0291747
-I0511 11:49:27.182890  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.182893  4597 caffe.cpp:501] detection_eval = 0.715726
-I0511 11:49:27.182895  4597 caffe.cpp:501] detection_eval = 6.27621
-I0511 11:49:27.183416  4597 caffe.cpp:501] detection_eval = 9.26411
-I0511 11:49:27.183423  4597 caffe.cpp:501] detection_eval = 0.0270842
-I0511 11:49:27.183426  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183429  4597 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:49:27.183431  4597 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:49:27.183434  4597 caffe.cpp:501] detection_eval = 9.2621
-I0511 11:49:27.183435  4597 caffe.cpp:501] detection_eval = 0.0255036
-I0511 11:49:27.183439  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.183440  4597 caffe.cpp:501] detection_eval = 0.71371
-I0511 11:49:27.183442  4597 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:49:27.183444  4597 caffe.cpp:501] detection_eval = 9.24597
-I0511 11:49:27.183446  4597 caffe.cpp:501] detection_eval = 0.0281904
-I0511 11:49:27.183449  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183451  4597 caffe.cpp:501] detection_eval = 0.707661
-I0511 11:49:27.183454  4597 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:49:27.183455  4597 caffe.cpp:501] detection_eval = 9.28226
-I0511 11:49:27.183457  4597 caffe.cpp:501] detection_eval = 0.0245895
-I0511 11:49:27.183459  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183461  4597 caffe.cpp:501] detection_eval = 0.71371
-I0511 11:49:27.183465  4597 caffe.cpp:501] detection_eval = 6.19153
-I0511 11:49:27.183466  4597 caffe.cpp:501] detection_eval = 9.20766
-I0511 11:49:27.183468  4597 caffe.cpp:501] detection_eval = 0.0313816
-I0511 11:49:27.183470  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.183472  4597 caffe.cpp:501] detection_eval = 0.697581
-I0511 11:49:27.183475  4597 caffe.cpp:501] detection_eval = 6.1754
-I0511 11:49:27.183476  4597 caffe.cpp:501] detection_eval = 9.18145
-I0511 11:49:27.183480  4597 caffe.cpp:501] detection_eval = 0.0300773
-I0511 11:49:27.183481  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183483  4597 caffe.cpp:501] detection_eval = 0.701613
-I0511 11:49:27.183485  4597 caffe.cpp:501] detection_eval = 6.17944
-I0511 11:49:27.183487  4597 caffe.cpp:501] detection_eval = 9.19758
-I0511 11:49:27.183490  4597 caffe.cpp:501] detection_eval = 0.0237437
-I0511 11:49:27.183491  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183493  4597 caffe.cpp:501] detection_eval = 0.707661
-I0511 11:49:27.183496  4597 caffe.cpp:501] detection_eval = 6.17944
-I0511 11:49:27.183498  4597 caffe.cpp:501] detection_eval = 9.27823
-I0511 11:49:27.183503  4597 caffe.cpp:501] detection_eval = 0.0252186
-I0511 11:49:27.183506  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183508  4597 caffe.cpp:501] detection_eval = 0.707661
-I0511 11:49:27.183511  4597 caffe.cpp:501] detection_eval = 6.14516
-I0511 11:49:27.183512  4597 caffe.cpp:501] detection_eval = 9.30645
-I0511 11:49:27.183514  4597 caffe.cpp:501] detection_eval = 0.0272303
-I0511 11:49:27.183517  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183519  4597 caffe.cpp:501] detection_eval = 0.693548
-I0511 11:49:27.183521  4597 caffe.cpp:501] detection_eval = 6.12903
-I0511 11:49:27.183523  4597 caffe.cpp:501] detection_eval = 9.36895
-I0511 11:49:27.183526  4597 caffe.cpp:501] detection_eval = 0.0286934
-I0511 11:49:27.183527  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183531  4597 caffe.cpp:501] detection_eval = 0.691532
-I0511 11:49:27.183532  4597 caffe.cpp:501] detection_eval = 6.07661
-I0511 11:49:27.183534  4597 caffe.cpp:501] detection_eval = 9.36089
-I0511 11:49:27.183537  4597 caffe.cpp:501] detection_eval = 0.0270058
-I0511 11:49:27.183538  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.183540  4597 caffe.cpp:501] detection_eval = 0.683468
-I0511 11:49:27.183542  4597 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:49:27.183544  4597 caffe.cpp:501] detection_eval = 6.17944
-I0511 11:49:27.183547  4597 caffe.cpp:501] detection_eval = 0.0486907
-I0511 11:49:27.183549  4597 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:49:27.183552  4597 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:49:27.183553  4597 caffe.cpp:501] detection_eval = 6.16935
-I0511 11:49:27.183555  4597 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:49:27.183557  4597 caffe.cpp:501] detection_eval = 0.0444843
-I0511 11:49:27.183559  4597 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:49:27.183562  4597 caffe.cpp:501] detection_eval = 0.663306
-I0511 11:49:27.183564  4597 caffe.cpp:501] detection_eval = 6.15121
-I0511 11:49:27.183567  4597 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:49:27.183568  4597 caffe.cpp:501] detection_eval = 0.0409148
-I0511 11:49:27.183570  4597 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:49:27.183573  4597 caffe.cpp:501] detection_eval = 0.663306
-I0511 11:49:27.183574  4597 caffe.cpp:501] detection_eval = 6.11492
-I0511 11:49:27.183576  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.183579  4597 caffe.cpp:501] detection_eval = 0.0335623
-I0511 11:49:27.183581  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.183583  4597 caffe.cpp:501] detection_eval = 0.665323
-I0511 11:49:27.183585  4597 caffe.cpp:501] detection_eval = 6.07863
-I0511 11:49:27.183588  4597 caffe.cpp:501] detection_eval = 6.24194
-I0511 11:49:27.183589  4597 caffe.cpp:501] detection_eval = 0.0342348
-I0511 11:49:27.183591  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.183593  4597 caffe.cpp:501] detection_eval = 0.66129
-I0511 11:49:27.183596  4597 caffe.cpp:501] detection_eval = 6.07863
-I0511 11:49:27.183598  4597 caffe.cpp:501] detection_eval = 6.31048
-I0511 11:49:27.183600  4597 caffe.cpp:501] detection_eval = 0.0318322
-I0511 11:49:27.183603  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.183604  4597 caffe.cpp:501] detection_eval = 0.66129
-I0511 11:49:27.183606  4597 caffe.cpp:501] detection_eval = 6.06048
-I0511 11:49:27.183609  4597 caffe.cpp:501] detection_eval = 6.30444
-I0511 11:49:27.183610  4597 caffe.cpp:501] detection_eval = 0.0259541
-I0511 11:49:27.183612  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.183615  4597 caffe.cpp:501] detection_eval = 0.667339
-I0511 11:49:27.183617  4597 caffe.cpp:501] detection_eval = 6.00605
-I0511 11:49:27.183619  4597 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:49:27.183621  4597 caffe.cpp:501] detection_eval = 0.031006
-I0511 11:49:27.183624  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.183625  4597 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:49:27.183627  4597 caffe.cpp:501] detection_eval = 5.93347
-I0511 11:49:27.183632  4597 caffe.cpp:501] detection_eval = 6.19355
-I0511 11:49:27.183634  4597 caffe.cpp:501] detection_eval = 0.0311044
-I0511 11:49:27.183637  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.183640  4597 caffe.cpp:501] detection_eval = 0.643145
-I0511 11:49:27.183641  4597 caffe.cpp:501] detection_eval = 5.89718
-I0511 11:49:27.183643  4597 caffe.cpp:501] detection_eval = 6.14919
-I0511 11:49:27.183645  4597 caffe.cpp:501] detection_eval = 0.0279176
-I0511 11:49:27.183647  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.183650  4597 caffe.cpp:501] detection_eval = 0.647177
-I0511 11:49:27.183652  4597 caffe.cpp:501] detection_eval = 5.89718
-I0511 11:49:27.183655  4597 caffe.cpp:501] detection_eval = 6.19153
-I0511 11:49:27.183656  4597 caffe.cpp:501] detection_eval = 0.0303933
-I0511 11:49:27.183658  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.183660  4597 caffe.cpp:501] detection_eval = 0.641129
-I0511 11:49:27.183662  4597 caffe.cpp:501] detection_eval = 5.89718
-I0511 11:49:27.183665  4597 caffe.cpp:501] detection_eval = 6.21573
-I0511 11:49:27.183666  4597 caffe.cpp:501] detection_eval = 0.024151
-I0511 11:49:27.183668  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.183671  4597 caffe.cpp:501] detection_eval = 0.65121
-I0511 11:49:27.183673  4597 caffe.cpp:501] detection_eval = 5.87903
-I0511 11:49:27.183676  4597 caffe.cpp:501] detection_eval = 6.21169
-I0511 11:49:27.183677  4597 caffe.cpp:501] detection_eval = 0.0252697
-I0511 11:49:27.183679  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184206  4597 caffe.cpp:501] detection_eval = 0.647177
-I0511 11:49:27.184212  4597 caffe.cpp:501] detection_eval = 5.87903
-I0511 11:49:27.184216  4597 caffe.cpp:501] detection_eval = 6.26613
-I0511 11:49:27.184218  4597 caffe.cpp:501] detection_eval = 0.0259765
-I0511 11:49:27.184221  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184222  4597 caffe.cpp:501] detection_eval = 0.645161
-I0511 11:49:27.184224  4597 caffe.cpp:501] detection_eval = 5.87903
-I0511 11:49:27.184227  4597 caffe.cpp:501] detection_eval = 6.33065
-I0511 11:49:27.184229  4597 caffe.cpp:501] detection_eval = 0.0280103
-I0511 11:49:27.184231  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.184233  4597 caffe.cpp:501] detection_eval = 0.645161
-I0511 11:49:27.184236  4597 caffe.cpp:501] detection_eval = 5.86089
-I0511 11:49:27.184237  4597 caffe.cpp:501] detection_eval = 6.34677
-I0511 11:49:27.184240  4597 caffe.cpp:501] detection_eval = 0.0285469
-I0511 11:49:27.184242  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.184244  4597 caffe.cpp:501] detection_eval = 0.643145
-I0511 11:49:27.184247  4597 caffe.cpp:501] detection_eval = 5.84274
-I0511 11:49:27.184248  4597 caffe.cpp:501] detection_eval = 6.36089
-I0511 11:49:27.184250  4597 caffe.cpp:501] detection_eval = 0.02545
-I0511 11:49:27.184252  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184255  4597 caffe.cpp:501] detection_eval = 0.643145
-I0511 11:49:27.184257  4597 caffe.cpp:501] detection_eval = 5.84274
-I0511 11:49:27.184259  4597 caffe.cpp:501] detection_eval = 6.38911
-I0511 11:49:27.184262  4597 caffe.cpp:501] detection_eval = 0.0254611
-I0511 11:49:27.184263  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184265  4597 caffe.cpp:501] detection_eval = 0.645161
-I0511 11:49:27.184267  4597 caffe.cpp:501] detection_eval = 5.78831
-I0511 11:49:27.184270  4597 caffe.cpp:501] detection_eval = 6.32661
-I0511 11:49:27.184273  4597 caffe.cpp:501] detection_eval = 0.0267105
-I0511 11:49:27.184274  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184276  4597 caffe.cpp:501] detection_eval = 0.637097
-I0511 11:49:27.184278  4597 caffe.cpp:501] detection_eval = 5.75202
-I0511 11:49:27.184280  4597 caffe.cpp:501] detection_eval = 6.28831
-I0511 11:49:27.184283  4597 caffe.cpp:501] detection_eval = 0.0250424
-I0511 11:49:27.184284  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.184288  4597 caffe.cpp:501] detection_eval = 0.631048
-I0511 11:49:27.184294  4597 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:49:27.184296  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.184298  4597 caffe.cpp:501] detection_eval = 0.0268295
-I0511 11:49:27.184300  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184303  4597 caffe.cpp:501] detection_eval = 0.631048
-I0511 11:49:27.184305  4597 caffe.cpp:501] detection_eval = 5.69758
-I0511 11:49:27.184307  4597 caffe.cpp:501] detection_eval = 6.29435
-I0511 11:49:27.184309  4597 caffe.cpp:501] detection_eval = 0.0259999
-I0511 11:49:27.184311  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184314  4597 caffe.cpp:501] detection_eval = 0.627016
-I0511 11:49:27.184315  4597 caffe.cpp:501] detection_eval = 5.66129
-I0511 11:49:27.184317  4597 caffe.cpp:501] detection_eval = 6.28024
-I0511 11:49:27.184319  4597 caffe.cpp:501] detection_eval = 0.0225302
-I0511 11:49:27.184322  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.184324  4597 caffe.cpp:501] detection_eval = 0.627016
-I0511 11:49:27.184326  4597 caffe.cpp:501] detection_eval = 5.57056
-I0511 11:49:27.184329  4597 caffe.cpp:501] detection_eval = 6.12903
-I0511 11:49:27.184330  4597 caffe.cpp:501] detection_eval = 0.025236
-I0511 11:49:27.184334  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184335  4597 caffe.cpp:501] detection_eval = 0.606855
-I0511 11:49:27.184337  4597 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:49:27.184340  4597 caffe.cpp:501] detection_eval = 6.14919
-I0511 11:49:27.184341  4597 caffe.cpp:501] detection_eval = 0.0235622
-I0511 11:49:27.184345  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184346  4597 caffe.cpp:501] detection_eval = 0.612903
-I0511 11:49:27.184348  4597 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:49:27.184350  4597 caffe.cpp:501] detection_eval = 6.15323
-I0511 11:49:27.184352  4597 caffe.cpp:501] detection_eval = 0.0286466
-I0511 11:49:27.184355  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184356  4597 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:49:27.184360  4597 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:49:27.184361  4597 caffe.cpp:501] detection_eval = 6.20363
-I0511 11:49:27.184363  4597 caffe.cpp:501] detection_eval = 0.0239786
-I0511 11:49:27.184365  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184367  4597 caffe.cpp:501] detection_eval = 0.608871
-I0511 11:49:27.184370  4597 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:49:27.184371  4597 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:49:27.184373  4597 caffe.cpp:501] detection_eval = 0.021609
-I0511 11:49:27.184376  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.184378  4597 caffe.cpp:501] detection_eval = 0.610887
-I0511 11:49:27.184381  4597 caffe.cpp:501] detection_eval = 5.51613
-I0511 11:49:27.184382  4597 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:49:27.184384  4597 caffe.cpp:501] detection_eval = 0.0248316
-I0511 11:49:27.184386  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184388  4597 caffe.cpp:501] detection_eval = 0.596774
-I0511 11:49:27.184391  4597 caffe.cpp:501] detection_eval = 5.49798
-I0511 11:49:27.184392  4597 caffe.cpp:501] detection_eval = 6.29234
-I0511 11:49:27.184394  4597 caffe.cpp:501] detection_eval = 0.0259911
-I0511 11:49:27.184397  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184399  4597 caffe.cpp:501] detection_eval = 0.600806
-I0511 11:49:27.184401  4597 caffe.cpp:501] detection_eval = 5.46169
-I0511 11:49:27.184403  4597 caffe.cpp:501] detection_eval = 6.23992
-I0511 11:49:27.184406  4597 caffe.cpp:501] detection_eval = 0.0234384
-I0511 11:49:27.184407  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184409  4597 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:49:27.184412  4597 caffe.cpp:501] detection_eval = 5.4254
-I0511 11:49:27.184414  4597 caffe.cpp:501] detection_eval = 6.27823
-I0511 11:49:27.184417  4597 caffe.cpp:501] detection_eval = 0.0310337
-I0511 11:49:27.184418  4597 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:49:27.184423  4597 caffe.cpp:501] detection_eval = 0.58871
-I0511 11:49:27.184427  4597 caffe.cpp:501] detection_eval = 5.37097
-I0511 11:49:27.184428  4597 caffe.cpp:501] detection_eval = 6.24395
-I0511 11:49:27.184430  4597 caffe.cpp:501] detection_eval = 0.0281657
-I0511 11:49:27.184432  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.184434  4597 caffe.cpp:501] detection_eval = 0.582661
-I0511 11:49:27.184437  4597 caffe.cpp:501] detection_eval = 5.35282
-I0511 11:49:27.184438  4597 caffe.cpp:501] detection_eval = 6.2379
-I0511 11:49:27.184440  4597 caffe.cpp:501] detection_eval = 0.0223501
-I0511 11:49:27.184443  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.184445  4597 caffe.cpp:501] detection_eval = 0.58871
-I0511 11:49:27.184448  4597 caffe.cpp:501] detection_eval = 5.29839
-I0511 11:49:27.184449  4597 caffe.cpp:501] detection_eval = 6.1996
-I0511 11:49:27.184451  4597 caffe.cpp:501] detection_eval = 0.0255929
-I0511 11:49:27.184453  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.184455  4597 caffe.cpp:501] detection_eval = 0.584677
-I0511 11:49:27.184458  4597 caffe.cpp:501] detection_eval = 5.28024
-I0511 11:49:27.184460  4597 caffe.cpp:501] detection_eval = 6.22581
-I0511 11:49:27.184463  4597 caffe.cpp:501] detection_eval = 0.0251907
-I0511 11:49:27.184464  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.184466  4597 caffe.cpp:501] detection_eval = 0.576613
-I0511 11:49:27.184468  4597 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:49:27.184470  4597 caffe.cpp:501] detection_eval = 6.16129
-I0511 11:49:27.184978  4597 caffe.cpp:501] detection_eval = 0.0210612
-I0511 11:49:27.184985  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.184988  4597 caffe.cpp:501] detection_eval = 0.578629
-I0511 11:49:27.184990  4597 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:49:27.184993  4597 caffe.cpp:501] detection_eval = 6.20161
-I0511 11:49:27.184994  4597 caffe.cpp:501] detection_eval = 0.0208977
-I0511 11:49:27.184996  4597 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:49:27.184999  4597 caffe.cpp:501] detection_eval = 0.572581
-I0511 11:49:27.185001  4597 caffe.cpp:501] detection_eval = 5.18952
-I0511 11:49:27.185003  4597 caffe.cpp:501] detection_eval = 6.13508
-I0511 11:49:27.185005  4597 caffe.cpp:501] detection_eval = 0.0219971
-I0511 11:49:27.185008  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.185009  4597 caffe.cpp:501] detection_eval = 0.570565
-I0511 11:49:27.185012  4597 caffe.cpp:501] detection_eval = 5.15323
-I0511 11:49:27.185014  4597 caffe.cpp:501] detection_eval = 6.08871
-I0511 11:49:27.185016  4597 caffe.cpp:501] detection_eval = 0.0227967
-I0511 11:49:27.185019  4597 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:49:27.185020  4597 caffe.cpp:501] detection_eval = 0.568548
-I0511 11:49:27.185022  4597 caffe.cpp:501] detection_eval = 5.11694
-I0511 11:49:27.185024  4597 caffe.cpp:501] detection_eval = 6.10484
-I0511 11:49:27.185027  4597 caffe.cpp:501] detection_eval = 0.023998
-I0511 11:49:27.185029  4597 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:49:27.185031  4597 caffe.cpp:501] detection_eval = 0.556452
-I0511 11:49:27.185034  4597 caffe.cpp:501] detection_eval = 5.08065
-I0511 11:49:27.185035  4597 caffe.cpp:501] detection_eval = 6.06452
-I0511 11:49:27.185037  4597 caffe.cpp:501] detection_eval = 0.0238617
-I0511 11:49:27.185040  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.185042  4597 caffe.cpp:501] detection_eval = 0.558468
-I0511 11:49:27.185045  4597 caffe.cpp:501] detection_eval = 5.04435
-I0511 11:49:27.185046  4597 caffe.cpp:501] detection_eval = 6.04839
-I0511 11:49:27.185048  4597 caffe.cpp:501] detection_eval = 0.0233311
-I0511 11:49:27.185050  4597 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:49:27.185052  4597 caffe.cpp:501] detection_eval = 0.554435
-I0511 11:49:27.185055  4597 caffe.cpp:501] detection_eval = 5.00806
-I0511 11:49:27.185057  4597 caffe.cpp:501] detection_eval = 6.0121
-I0511 11:49:27.185060  4597 caffe.cpp:501] detection_eval = 0.0228293
-I0511 11:49:27.185061  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.185068  4597 caffe.cpp:501] detection_eval = 0.546371
-I0511 11:49:27.185070  4597 caffe.cpp:501] detection_eval = 4.97177
-I0511 11:49:27.185073  4597 caffe.cpp:501] detection_eval = 5.98185
-I0511 11:49:27.185075  4597 caffe.cpp:501] detection_eval = 0.0257397
-I0511 11:49:27.185077  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.185079  4597 caffe.cpp:501] detection_eval = 0.542339
-I0511 11:49:27.185081  4597 caffe.cpp:501] detection_eval = 4.97177
-I0511 11:49:27.185083  4597 caffe.cpp:501] detection_eval = 6.05847
-I0511 11:49:27.185086  4597 caffe.cpp:501] detection_eval = 0.0266467
-I0511 11:49:27.185087  4597 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:49:27.185091  4597 caffe.cpp:501] detection_eval = 0.532258
-I0511 11:49:27.185092  4597 caffe.cpp:501] detection_eval = 4.93548
-I0511 11:49:27.185094  4597 caffe.cpp:501] detection_eval = 6.03831
-I0511 11:49:27.185096  4597 caffe.cpp:501] detection_eval = 0.0265504
-I0511 11:49:27.185098  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.185101  4597 caffe.cpp:501] detection_eval = 0.53629
-I0511 11:49:27.185102  4597 caffe.cpp:501] detection_eval = 4.91734
-I0511 11:49:27.185104  4597 caffe.cpp:501] detection_eval = 6.03024
-I0511 11:49:27.185106  4597 caffe.cpp:501] detection_eval = 0.0236068
-I0511 11:49:27.185109  4597 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:49:27.185111  4597 caffe.cpp:501] detection_eval = 0.53629
-I0511 11:49:27.185113  4597 caffe.cpp:501] detection_eval = 4.88105
-I0511 11:49:27.185115  4597 caffe.cpp:501] detection_eval = 6.01008
-I0511 11:49:27.185117  4597 caffe.cpp:501] detection_eval = 0.0230098
-I0511 11:49:27.185120  4597 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:49:27.185122  4597 caffe.cpp:501] detection_eval = 0.53629
-I0511 11:49:27.186365  4597 caffe.cpp:546] class AP 1: 0.651434
-I0511 11:49:27.186940  4597 caffe.cpp:546] class AP 2: 0.730767
-I0511 11:49:27.195986  4597 caffe.cpp:546] class AP 3: 0.555641
-I0511 11:49:27.201273  4597 caffe.cpp:546] class AP 4: 0.5085
-I0511 11:49:27.221433  4597 caffe.cpp:546] class AP 5: 0.337752
-I0511 11:49:27.221793  4597 caffe.cpp:546] class AP 6: 0.737833
-I0511 11:49:27.230624  4597 caffe.cpp:546] class AP 7: 0.70404
-I0511 11:49:27.231215  4597 caffe.cpp:546] class AP 8: 0.815221
-I0511 11:49:27.250205  4597 caffe.cpp:546] class AP 9: 0.431295
-I0511 11:49:27.250967  4597 caffe.cpp:546] class AP 10: 0.638275
-I0511 11:49:27.251662  4597 caffe.cpp:546] class AP 11: 0.596563
-I0511 11:49:27.252665  4597 caffe.cpp:546] class AP 12: 0.724503
-I0511 11:49:27.253118  4597 caffe.cpp:546] class AP 13: 0.799232
-I0511 11:49:27.253480  4597 caffe.cpp:546] class AP 14: 0.746535
-I0511 11:49:27.301280  4597 caffe.cpp:546] class AP 15: 0.727107
-I0511 11:49:27.307509  4597 caffe.cpp:546] class AP 16: 0.366775
-I0511 11:49:27.309844  4597 caffe.cpp:546] class AP 17: 0.600392
-I0511 11:49:27.310420  4597 caffe.cpp:546] class AP 18: 0.60817
-I0511 11:49:27.311082  4597 caffe.cpp:546] class AP 19: 0.75051
-I0511 11:49:27.312469  4597 caffe.cpp:546] class AP 20: 0.6172
-I0511 11:49:27.312475  4597 caffe.cpp:552] Test net output mAP #0: detection_eval = 0.632387
-I0511 11:49:27.312480  4597 caffe.cpp:556] =========================
-I0511 11:49:27.312484  4597 caffe.cpp:557] Sparsity of the test net:
-I0511 11:49:27.314363  4597 net.cpp:2452] Num Params(47), Sparsity (zero_weights/count): 
-I0511 11:49:27.314370  4597 net.cpp:2463] conv1_param_0(0) 
-I0511 11:49:27.314380  4597 net.cpp:2463] conv2_1/dw_param_0(0) 
-I0511 11:49:27.314394  4597 net.cpp:2463] conv2_1/sep_param_0(0) 
-I0511 11:49:27.314400  4597 net.cpp:2463] conv2_2/dw_param_0(0) 
-I0511 11:49:27.314409  4597 net.cpp:2463] conv2_2/sep_param_0(0) 
-I0511 11:49:27.314414  4597 net.cpp:2463] conv3_1/dw_param_0(0) 
-I0511 11:49:27.314417  4597 net.cpp:2463] conv3_1/sep_param_0(0) 
-I0511 11:49:27.314426  4597 net.cpp:2463] conv3_2/dw_param_0(0) 
-I0511 11:49:27.314431  4597 net.cpp:2463] conv3_2/sep_param_0(0) 
-I0511 11:49:27.314435  4597 net.cpp:2463] conv4_1/dw_param_0(0) 
-I0511 11:49:27.314442  4597 net.cpp:2463] conv4_1/sep_param_0(0) 
-I0511 11:49:27.314458  4597 net.cpp:2463] conv4_2/dw_param_0(0) 
-I0511 11:49:27.314462  4597 net.cpp:2463] conv4_2/sep_param_0(0) 
-I0511 11:49:27.314471  4597 net.cpp:2463] conv5_1/dw_param_0(0) 
-I0511 11:49:27.314481  4597 net.cpp:2463] conv5_1/sep_param_0(0) 
-I0511 11:49:27.314486  4597 net.cpp:2463] conv5_2/dw_param_0(0) 
-I0511 11:49:27.314489  4597 net.cpp:2463] conv5_2/sep_param_0(0) 
-I0511 11:49:27.314497  4597 net.cpp:2463] conv5_3/dw_param_0(0) 
-I0511 11:49:27.314502  4597 net.cpp:2463] conv5_3/sep_param_0(0) 
-I0511 11:49:27.314505  4597 net.cpp:2463] conv5_4/dw_param_0(0) 
-I0511 11:49:27.314513  4597 net.cpp:2463] conv5_4/sep_param_0(0) 
-I0511 11:49:27.314517  4597 net.cpp:2463] conv5_5/dw_param_0(0) 
-I0511 11:49:27.314525  4597 net.cpp:2463] conv5_5/sep_param_0(0) 
-I0511 11:49:27.314530  4597 net.cpp:2463] conv5_6/dw_param_0(0) 
-I0511 11:49:27.314538  4597 net.cpp:2463] conv5_6/sep_param_0(0) 
-I0511 11:49:27.314543  4597 net.cpp:2463] conv6/dw_param_0(0) 
-I0511 11:49:27.314550  4597 net.cpp:2463] conv6/sep_param_0(0) 
-I0511 11:49:27.314558  4597 net.cpp:2463] ctx_output1/1x1_param_0(0) 
-I0511 11:49:27.314563  4597 net.cpp:2463] ctx_output1/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314571  4597 net.cpp:2463] ctx_output1/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314575  4597 net.cpp:2463] ctx_output1_param_0(0) 
-I0511 11:49:27.314584  4597 net.cpp:2463] ctx_output2/1x1_param_0(0) 
-I0511 11:49:27.314587  4597 net.cpp:2463] ctx_output2/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314595  4597 net.cpp:2463] ctx_output2/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314600  4597 net.cpp:2463] ctx_output2_param_0(0) 
-I0511 11:49:27.314607  4597 net.cpp:2463] ctx_output3/1x1_param_0(0) 
-I0511 11:49:27.314616  4597 net.cpp:2463] ctx_output3/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314621  4597 net.cpp:2463] ctx_output3/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314630  4597 net.cpp:2463] ctx_output3_param_0(0) 
-I0511 11:49:27.314633  4597 net.cpp:2463] ctx_output4/1x1_param_0(0) 
-I0511 11:49:27.314641  4597 net.cpp:2463] ctx_output4/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314646  4597 net.cpp:2463] ctx_output4/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314653  4597 net.cpp:2463] ctx_output4_param_0(0) 
-I0511 11:49:27.314657  4597 net.cpp:2463] ctx_output5/1x1_param_0(0) 
-I0511 11:49:27.314666  4597 net.cpp:2463] ctx_output5/relu_mbox_conf_param_0(0) 
-I0511 11:49:27.314669  4597 net.cpp:2463] ctx_output5/relu_mbox_loc_param_0(0) 
-I0511 11:49:27.314677  4597 net.cpp:2463] ctx_output5_param_0(0) 
-I0511 11:49:27.314682  4597 net.cpp:2467] Total Sparsity (zero_weights/count) =  (0/2.31754e+06) 0
-I0511 11:49:27.314703  4597 caffe.cpp:559] =========================
-I0511 11:49:27.915685  5581 caffe.cpp:902] This is NVCaffe 0.17.0 started at Fri May 11 11:49:27 2018
-I0511 11:49:27.915874  5581 caffe.cpp:904] CuDNN version: 7003
-I0511 11:49:27.915879  5581 caffe.cpp:905] CuBLAS version: 9000
-I0511 11:49:27.915882  5581 caffe.cpp:906] CUDA version: 9000
-I0511 11:49:27.915885  5581 caffe.cpp:907] CUDA driver version: 9000
-I0511 11:49:27.915890  5581 caffe.cpp:908] Arguments: 
-[0]: /user/a0393608/files/work/code/vision/ti/bitbucket/algoref/caffe-jacinto/build/tools/caffe.bin
-[1]: test_detection
-[2]: --model=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/test_quantize/test.prototxt
-[3]: --iterations=496
-[4]: --weights=training/voc0712/mobiledetnet-0.5/20180510_14-48_ds_PSP_dsFac_32_hdDS8_1/initial/voc0712_mobiledetnet-0.5_iter_120000.caffemodel
-[5]: --gpu
-[6]: 0
-I0511 11:49:27.944636  5581 gpu_memory.cpp:105] GPUMemory::Manager initialized
-I0511 11:49:27.945523  5581 gpu_memory.cpp:107] Total memory: 11713708032, Free: 11223957504, dev_info[0]: total=11713708032 free=11223957504
-I0511 11:49:27.945531  5581 caffe.cpp:406] Use GPU with device ID 0
-I0511 11:49:27.946121  5581 caffe.cpp:409] GPU device name: GeForce GTX 1080 Ti
-I0511 11:49:27.962272  5581 net.cpp:80] Initializing net from parameters: 
-name: "mobiledetnet-0.5_test"
-state {
-  phase: TEST
-  level: 0
-}
-layer {
-  name: "data"
-  type: "AnnotatedData"
-  top: "data"
-  top: "label"
-  include {
-    phase: TEST
-  }
-  transform_param {
-    mean_value: 0
-    mean_value: 0
-    mean_value: 0
-    force_color: false
-    resize_param {
-      prob: 1
-      resize_mode: WARP
-      height: 256
-      width: 512
-      interp_mode: LINEAR
-    }
-    crop_h: 256
-    crop_w: 512
-  }
-  data_param {
-    source: "../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb"
-    batch_size: 10
-    backend: LMDB
-    threads: 4
-    parser_threads: 4
-  }
-  annotated_data_param {
-    batch_sampler {
-    }
-    label_map_file: "../../caffe-jacinto/data/VOC0712/labelmap_voc.prototxt"
-  }
-}
-layer {
-  name: "data/bias"
-  type: "Bias"
-  bottom: "data"
-  top: "data/bias"
-  param {
-    lr_mult: 0
-    decay_mult: 0
-  }
-  bias_param {
-    filler {
-      type: "constant"
-      value: -128
-    }
-  }
-}
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data/bias"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 1
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1/bn"
-  type: "BatchNorm"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv1/scale"
-  type: "Scale"
-  bottom: "conv1"
-  top: "conv1"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "conv2_1/dw"
-  type: "Convolution"
-  bottom: "conv1"
-  top: "conv2_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 16
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/dw/scale"
-  type: "Scale"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/dw"
-  type: "ReLU"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/dw"
-}
-layer {
-  name: "conv2_1/sep"
-  type: "Convolution"
-  bottom: "conv2_1/dw"
-  top: "conv2_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_1/sep/scale"
-  type: "Scale"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1/sep"
-  type: "ReLU"
-  bottom: "conv2_1/sep"
-  top: "conv2_1/sep"
-}
-layer {
-  name: "conv2_2/dw"
-  type: "Convolution"
-  bottom: "conv2_1/sep"
-  top: "conv2_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 32
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 32
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/dw/scale"
-  type: "Scale"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-  scale_param {
-    bias_term: true
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-}
-layer {
-  name: "relu2_2/dw"
-  type: "ReLU"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/dw"
-}
-layer {
-  name: "conv2_2/sep"
-  type: "Convolution"
-  bottom: "conv2_2/dw"
-  top: "conv2_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv2_2/sep/scale"
-  type: "Scale"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-  scale_param {
-    bias_term: true
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-}
-layer {
-  name: "relu2_2/sep"
-  type: "ReLU"
-  bottom: "conv2_2/sep"
-  top: "conv2_2/sep"
-}
-layer {
-  name: "conv3_1/dw"
-  type: "Convolution"
-  bottom: "conv2_2/sep"
-  top: "conv3_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
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-}
-layer {
-  name: "conv3_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/dw/scale"
-  type: "Scale"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-  scale_param {
-    bias_term: true
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-}
-layer {
-  name: "relu3_1/dw"
-  type: "ReLU"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/dw"
-}
-layer {
-  name: "conv3_1/sep"
-  type: "Convolution"
-  bottom: "conv3_1/dw"
-  top: "conv3_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_1/sep/scale"
-  type: "Scale"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-  scale_param {
-    bias_term: true
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-}
-layer {
-  name: "relu3_1/sep"
-  type: "ReLU"
-  bottom: "conv3_1/sep"
-  top: "conv3_1/sep"
-}
-layer {
-  name: "conv3_2/dw"
-  type: "Convolution"
-  bottom: "conv3_1/sep"
-  top: "conv3_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 64
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 64
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/dw/scale"
-  type: "Scale"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2/dw"
-  type: "ReLU"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/dw"
-}
-layer {
-  name: "conv3_2/sep"
-  type: "Convolution"
-  bottom: "conv3_2/dw"
-  top: "conv3_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv3_2/sep/scale"
-  type: "Scale"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-  scale_param {
-    bias_term: true
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-}
-layer {
-  name: "relu3_2/sep"
-  type: "ReLU"
-  bottom: "conv3_2/sep"
-  top: "conv3_2/sep"
-}
-layer {
-  name: "conv4_1/dw"
-  type: "Convolution"
-  bottom: "conv3_2/sep"
-  top: "conv4_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/dw/scale"
-  type: "Scale"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/dw"
-  type: "ReLU"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/dw"
-}
-layer {
-  name: "conv4_1/sep"
-  type: "Convolution"
-  bottom: "conv4_1/dw"
-  top: "conv4_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_1/sep/scale"
-  type: "Scale"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1/sep"
-  type: "ReLU"
-  bottom: "conv4_1/sep"
-  top: "conv4_1/sep"
-}
-layer {
-  name: "conv4_2/dw"
-  type: "Convolution"
-  bottom: "conv4_1/sep"
-  top: "conv4_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 128
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 128
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/dw/scale"
-  type: "Scale"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-  scale_param {
-    bias_term: true
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-}
-layer {
-  name: "relu4_2/dw"
-  type: "ReLU"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/dw"
-}
-layer {
-  name: "conv4_2/sep"
-  type: "Convolution"
-  bottom: "conv4_2/dw"
-  top: "conv4_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv4_2/sep/scale"
-  type: "Scale"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2/sep"
-  type: "ReLU"
-  bottom: "conv4_2/sep"
-  top: "conv4_2/sep"
-}
-layer {
-  name: "conv5_1/dw"
-  type: "Convolution"
-  bottom: "conv4_2/sep"
-  top: "conv5_1/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/dw/scale"
-  type: "Scale"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/dw"
-  type: "ReLU"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/dw"
-}
-layer {
-  name: "conv5_1/sep"
-  type: "Convolution"
-  bottom: "conv5_1/dw"
-  top: "conv5_1/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_1/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_1/sep/scale"
-  type: "Scale"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1/sep"
-  type: "ReLU"
-  bottom: "conv5_1/sep"
-  top: "conv5_1/sep"
-}
-layer {
-  name: "conv5_2/dw"
-  type: "Convolution"
-  bottom: "conv5_1/sep"
-  top: "conv5_2/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/dw/scale"
-  type: "Scale"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/dw"
-  type: "ReLU"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/dw"
-}
-layer {
-  name: "conv5_2/sep"
-  type: "Convolution"
-  bottom: "conv5_2/dw"
-  top: "conv5_2/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_2/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_2/sep/scale"
-  type: "Scale"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2/sep"
-  type: "ReLU"
-  bottom: "conv5_2/sep"
-  top: "conv5_2/sep"
-}
-layer {
-  name: "conv5_3/dw"
-  type: "Convolution"
-  bottom: "conv5_2/sep"
-  top: "conv5_3/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/dw/scale"
-  type: "Scale"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/dw"
-  type: "ReLU"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/dw"
-}
-layer {
-  name: "conv5_3/sep"
-  type: "Convolution"
-  bottom: "conv5_3/dw"
-  top: "conv5_3/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_3/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_3/sep/scale"
-  type: "Scale"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3/sep"
-  type: "ReLU"
-  bottom: "conv5_3/sep"
-  top: "conv5_3/sep"
-}
-layer {
-  name: "conv5_4/dw"
-  type: "Convolution"
-  bottom: "conv5_3/sep"
-  top: "conv5_4/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/dw/scale"
-  type: "Scale"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/dw"
-  type: "ReLU"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/dw"
-}
-layer {
-  name: "conv5_4/sep"
-  type: "Convolution"
-  bottom: "conv5_4/dw"
-  top: "conv5_4/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_4/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_4/sep/scale"
-  type: "Scale"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4/sep"
-  type: "ReLU"
-  bottom: "conv5_4/sep"
-  top: "conv5_4/sep"
-}
-layer {
-  name: "conv5_5/dw"
-  type: "Convolution"
-  bottom: "conv5_4/sep"
-  top: "conv5_5/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/dw/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/dw/scale"
-  type: "Scale"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/dw"
-  type: "ReLU"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/dw"
-}
-layer {
-  name: "conv5_5/sep"
-  type: "Convolution"
-  bottom: "conv5_5/dw"
-  top: "conv5_5/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 256
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_5/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_5/sep/scale"
-  type: "Scale"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_5/sep"
-  type: "ReLU"
-  bottom: "conv5_5/sep"
-  top: "conv5_5/sep"
-}
-layer {
-  name: "conv5_6/dw"
-  type: "Convolution"
-  bottom: "conv5_5/sep"
-  top: "conv5_6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 256
-    stride: 2
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/dw"
-  type: "ReLU"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/dw"
-}
-layer {
-  name: "conv5_6/sep"
-  type: "Convolution"
-  bottom: "conv5_6/dw"
-  top: "conv5_6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv5_6/sep/bn"
-  type: "BatchNorm"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv5_6/sep/scale"
-  type: "Scale"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_6/sep"
-  type: "ReLU"
-  bottom: "conv5_6/sep"
-  top: "conv5_6/sep"
-}
-layer {
-  name: "conv6/dw"
-  type: "Convolution"
-  bottom: "conv5_6/sep"
-  top: "conv6/dw"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
-  name: "conv6/dw/scale"
-  type: "Scale"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/dw"
-  top: "conv6/dw"
-}
-layer {
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-  type: "Convolution"
-  bottom: "conv6/dw"
-  top: "conv6/sep"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  convolution_param {
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-    bias_term: false
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
-  }
-}
-layer {
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-  type: "BatchNorm"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
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-  type: "Scale"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-  scale_param {
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-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "conv6/sep"
-  top: "conv6/sep"
-}
-layer {
-  name: "pool6"
-  type: "Pooling"
-  bottom: "conv6/sep"
-  top: "pool6"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
-  name: "pool7"
-  type: "Pooling"
-  bottom: "pool6"
-  top: "pool7"
-  pooling_param {
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-    kernel_size: 3
-    stride: 2
-    pad: 1
-  }
-}
-layer {
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-  type: "Pooling"
-  bottom: "pool7"
-  top: "pool8"
-  pooling_param {
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-    kernel_size: 3
-    stride: 1
-    pad: 1
-  }
-}
-layer {
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-  bottom: "conv5_5/sep"
-  top: "ctx_output1/1x1"
-  param {
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-    decay_mult: 0
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-layer {
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-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  top: "ctx_output1/1x1"
-}
-layer {
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-  bottom: "ctx_output1/1x1"
-  top: "ctx_output1"
-  param {
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-  param {
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-    decay_mult: 0
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-  convolution_param {
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-    kernel_size: 3
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-    }
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-layer {
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-layer {
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-  top: "ctx_output1"
-}
-layer {
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-  bottom: "conv6/sep"
-  top: "ctx_output2/1x1"
-  param {
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-  param {
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-    decay_mult: 0
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-      value: 0
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-layer {
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-  top: "ctx_output2/1x1"
-  batch_norm_param {
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-    eps: 0.0001
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-  }
-}
-layer {
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-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2/1x1"
-}
-layer {
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-  bottom: "ctx_output2/1x1"
-  top: "ctx_output2"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    pad: 1
-    kernel_size: 3
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-    }
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-layer {
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-layer {
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-  top: "ctx_output2"
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-layer {
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-  bottom: "pool6"
-  top: "ctx_output3/1x1"
-  param {
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-    decay_mult: 1
-  }
-  param {
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-    decay_mult: 0
-  }
-  convolution_param {
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-    kernel_size: 1
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-    }
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-    dilation: 1
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-layer {
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-  top: "ctx_output3/1x1"
-  batch_norm_param {
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-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
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-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3/1x1"
-}
-layer {
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-  type: "Convolution"
-  bottom: "ctx_output3/1x1"
-  top: "ctx_output3"
-  param {
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-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
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-    }
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-layer {
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-  bottom: "ctx_output3"
-  top: "ctx_output3"
-  batch_norm_param {
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-    scale_bias: true
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "ctx_output3"
-  top: "ctx_output3"
-}
-layer {
-  name: "ctx_output4/1x1"
-  type: "Convolution"
-  bottom: "pool7"
-  top: "ctx_output4/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
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-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
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-    }
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-      value: 0
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-    dilation: 1
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-}
-layer {
-  name: "ctx_output4/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4/1x1"
-}
-layer {
-  name: "ctx_output4"
-  type: "Convolution"
-  bottom: "ctx_output4/1x1"
-  top: "ctx_output4"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output4/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output4/relu"
-  type: "ReLU"
-  bottom: "ctx_output4"
-  top: "ctx_output4"
-}
-layer {
-  name: "ctx_output5/1x1"
-  type: "Convolution"
-  bottom: "pool8"
-  top: "ctx_output5/1x1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/1x1/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/1x1/relu"
-  type: "ReLU"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5/1x1"
-}
-layer {
-  name: "ctx_output5"
-  type: "Convolution"
-  bottom: "ctx_output5/1x1"
-  top: "ctx_output5"
-  param {
-    lr_mult: 1
-    decay_mult: 0.01
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 1
-    kernel_size: 3
-    group: 512
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output5/bn"
-  type: "BatchNorm"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-  batch_norm_param {
-    moving_average_fraction: 0.99
-    eps: 0.0001
-    scale_bias: true
-  }
-}
-layer {
-  name: "ctx_output5/relu"
-  type: "ReLU"
-  bottom: "ctx_output5"
-  top: "ctx_output5"
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 16
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_loc"
-  top: "ctx_output1/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_loc_perm"
-  top: "ctx_output1/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output1"
-  top: "ctx_output1/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 84
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output1/relu_mbox_conf"
-  top: "ctx_output1/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output1/relu_mbox_conf_perm"
-  top: "ctx_output1/relu_mbox_conf_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output1/relu_mbox_priorbox"
-  type: "PriorBox"
-  bottom: "ctx_output1"
-  bottom: "data"
-  top: "ctx_output1/relu_mbox_priorbox"
-  prior_box_param {
-    min_size: 19
-    max_size: 88
-    aspect_ratio: 2
-    flip: true
-    clip: false
-    variance: 0.1
-    variance: 0.1
-    variance: 0.2
-    variance: 0.2
-    offset: 0.5
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_loc"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 24
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_loc"
-  top: "ctx_output2/relu_mbox_loc_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_loc_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_loc_perm"
-  top: "ctx_output2/relu_mbox_loc_flat"
-  flatten_param {
-    axis: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf"
-  type: "Convolution"
-  bottom: "ctx_output2"
-  top: "ctx_output2/relu_mbox_conf"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 126
-    bias_term: true
-    pad: 0
-    kernel_size: 1
-    group: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0
-    }
-    dilation: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_perm"
-  type: "Permute"
-  bottom: "ctx_output2/relu_mbox_conf"
-  top: "ctx_output2/relu_mbox_conf_perm"
-  permute_param {
-    order: 0
-    order: 2
-    order: 3
-    order: 1
-  }
-}
-layer {
-  name: "ctx_output2/relu_mbox_conf_flat"
-  type: "Flatten"
-  bottom: "ctx_output2/relu_mbox_conf_perm"
-  top: "ctx
-I0511 11:49:27.962703  5581 net.cpp:110] Using FLOAT as default forward math type
-I0511 11:49:27.962710  5581 net.cpp:116] Using FLOAT as default backward math type
-I0511 11:49:27.962715  5581 layer_factory.hpp:172] Creating layer 'data' of type 'AnnotatedData'
-I0511 11:49:27.962719  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:27.963043  5581 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:49:27.963100  5581 net.cpp:200] Created Layer data (0)
-I0511 11:49:27.963106  5581 net.cpp:542] data -> data
-I0511 11:49:27.963117  5581 net.cpp:542] data -> label
-I0511 11:49:27.963129  5581 data_reader.cpp:58] Data Reader threads: 1, out queues: 1, depth: 10
-I0511 11:49:27.963138  5581 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:49:27.965538  5599 blocking_queue.cpp:40] Data layer prefetch queue empty
-I0511 11:49:27.966433  5600 db_lmdb.cpp:36] Opened lmdb ../../caffe-jacinto/examples/VOC0712/VOC0712_test_lmdb
-I0511 11:49:27.968072  5581 annotated_data_layer.cpp:105] output data size: 10,3,256,512
-I0511 11:49:27.968124  5581 annotated_data_layer.cpp:150] (0) Output data size: 10, 3, 256, 512
-I0511 11:49:27.968178  5581 internal_thread.cpp:19] Starting 1 internal thread(s) on device 0
-I0511 11:49:27.968207  5581 net.cpp:260] Setting up data
-I0511 11:49:27.969072  5601 data_layer.cpp:105] (0) Parser threads: 1
-I0511 11:49:27.969077  5581 net.cpp:267] TEST Top shape for layer 0 'data' 10 3 256 512 (3932160)
-I0511 11:49:27.969082  5601 data_layer.cpp:107] (0) Transformer threads: 1
-I0511 11:49:27.969090  5581 net.cpp:267] TEST Top shape for layer 0 'data' 1 1 2 8 (16)
-I0511 11:49:27.969120  5581 layer_factory.hpp:172] Creating layer 'data_data_0_split' of type 'Split'
-I0511 11:49:27.969127  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:27.969143  5581 net.cpp:200] Created Layer data_data_0_split (1)
-I0511 11:49:27.969152  5581 net.cpp:572] data_data_0_split <- data
-I0511 11:49:27.969171  5581 net.cpp:542] data_data_0_split -> data_data_0_split_0
-I0511 11:49:27.969178  5581 net.cpp:542] data_data_0_split -> data_data_0_split_1
-I0511 11:49:27.969185  5581 net.cpp:542] data_data_0_split -> data_data_0_split_2
-I0511 11:49:27.969194  5581 net.cpp:542] data_data_0_split -> data_data_0_split_3
-I0511 11:49:27.969200  5581 net.cpp:542] data_data_0_split -> data_data_0_split_4
-I0511 11:49:27.969207  5581 net.cpp:542] data_data_0_split -> data_data_0_split_5
-I0511 11:49:27.969292  5581 net.cpp:260] Setting up data_data_0_split
-I0511 11:49:27.969300  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969305  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969310  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969314  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969318  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969322  5581 net.cpp:267] TEST Top shape for layer 1 'data_data_0_split' 10 3 256 512 (3932160)
-I0511 11:49:27.969326  5581 layer_factory.hpp:172] Creating layer 'data/bias' of type 'Bias'
-I0511 11:49:27.969332  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:27.969341  5581 net.cpp:200] Created Layer data/bias (2)
-I0511 11:49:27.969346  5581 net.cpp:572] data/bias <- data_data_0_split_0
-I0511 11:49:27.969350  5581 net.cpp:542] data/bias -> data/bias
-I0511 11:49:27.970402  5581 net.cpp:260] Setting up data/bias
-I0511 11:49:27.970420  5581 net.cpp:267] TEST Top shape for layer 2 'data/bias' 10 3 256 512 (3932160)
-I0511 11:49:27.970438  5581 layer_factory.hpp:172] Creating layer 'conv1' of type 'Convolution'
-I0511 11:49:27.970444  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:27.970474  5581 net.cpp:200] Created Layer conv1 (3)
-I0511 11:49:27.970479  5581 net.cpp:572] conv1 <- data/bias
-I0511 11:49:27.970485  5581 net.cpp:542] conv1 -> conv1
-I0511 11:49:28.457382  5581 net.cpp:260] Setting up conv1
-I0511 11:49:28.457409  5581 net.cpp:267] TEST Top shape for layer 3 'conv1' 10 16 128 256 (5242880)
-I0511 11:49:28.457423  5581 layer_factory.hpp:172] Creating layer 'conv1/bn' of type 'BatchNorm'
-I0511 11:49:28.457432  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.457450  5581 net.cpp:200] Created Layer conv1/bn (4)
-I0511 11:49:28.457458  5581 net.cpp:572] conv1/bn <- conv1
-I0511 11:49:28.457474  5581 net.cpp:527] conv1/bn -> conv1 (in-place)
-I0511 11:49:28.458456  5581 net.cpp:260] Setting up conv1/bn
-I0511 11:49:28.458472  5581 net.cpp:267] TEST Top shape for layer 4 'conv1/bn' 10 16 128 256 (5242880)
-I0511 11:49:28.458489  5581 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Scale'
-I0511 11:49:28.458511  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.458524  5581 net.cpp:200] Created Layer conv1/scale (5)
-I0511 11:49:28.458535  5581 net.cpp:572] conv1/scale <- conv1
-I0511 11:49:28.458544  5581 net.cpp:527] conv1/scale -> conv1 (in-place)
-I0511 11:49:28.458587  5581 layer_factory.hpp:172] Creating layer 'conv1/scale' of type 'Bias'
-I0511 11:49:28.458595  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.458706  5581 net.cpp:260] Setting up conv1/scale
-I0511 11:49:28.458714  5581 net.cpp:267] TEST Top shape for layer 5 'conv1/scale' 10 16 128 256 (5242880)
-I0511 11:49:28.458745  5581 layer_factory.hpp:172] Creating layer 'relu1' of type 'ReLU'
-I0511 11:49:28.458750  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.458756  5581 net.cpp:200] Created Layer relu1 (6)
-I0511 11:49:28.458762  5581 net.cpp:572] relu1 <- conv1
-I0511 11:49:28.458767  5581 net.cpp:527] relu1 -> conv1 (in-place)
-I0511 11:49:28.458786  5581 net.cpp:260] Setting up relu1
-I0511 11:49:28.458792  5581 net.cpp:267] TEST Top shape for layer 6 'relu1' 10 16 128 256 (5242880)
-I0511 11:49:28.458797  5581 layer_factory.hpp:172] Creating layer 'conv2_1/dw' of type 'Convolution'
-I0511 11:49:28.458802  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.458815  5581 net.cpp:200] Created Layer conv2_1/dw (7)
-I0511 11:49:28.458822  5581 net.cpp:572] conv2_1/dw <- conv1
-I0511 11:49:28.458827  5581 net.cpp:542] conv2_1/dw -> conv2_1/dw
-I0511 11:49:28.459959  5581 net.cpp:260] Setting up conv2_1/dw
-I0511 11:49:28.459969  5581 net.cpp:267] TEST Top shape for layer 7 'conv2_1/dw' 10 16 128 256 (5242880)
-I0511 11:49:28.459975  5581 layer_factory.hpp:172] Creating layer 'conv2_1/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.459987  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.459997  5581 net.cpp:200] Created Layer conv2_1/dw/bn (8)
-I0511 11:49:28.460002  5581 net.cpp:572] conv2_1/dw/bn <- conv2_1/dw
-I0511 11:49:28.460012  5581 net.cpp:527] conv2_1/dw/bn -> conv2_1/dw (in-place)
-I0511 11:49:28.460278  5581 net.cpp:260] Setting up conv2_1/dw/bn
-I0511 11:49:28.460285  5581 net.cpp:267] TEST Top shape for layer 8 'conv2_1/dw/bn' 10 16 128 256 (5242880)
-I0511 11:49:28.460301  5581 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Scale'
-I0511 11:49:28.460306  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460314  5581 net.cpp:200] Created Layer conv2_1/dw/scale (9)
-I0511 11:49:28.460322  5581 net.cpp:572] conv2_1/dw/scale <- conv2_1/dw
-I0511 11:49:28.460330  5581 net.cpp:527] conv2_1/dw/scale -> conv2_1/dw (in-place)
-I0511 11:49:28.460362  5581 layer_factory.hpp:172] Creating layer 'conv2_1/dw/scale' of type 'Bias'
-I0511 11:49:28.460368  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460477  5581 net.cpp:260] Setting up conv2_1/dw/scale
-I0511 11:49:28.460484  5581 net.cpp:267] TEST Top shape for layer 9 'conv2_1/dw/scale' 10 16 128 256 (5242880)
-I0511 11:49:28.460496  5581 layer_factory.hpp:172] Creating layer 'relu2_1/dw' of type 'ReLU'
-I0511 11:49:28.460502  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460507  5581 net.cpp:200] Created Layer relu2_1/dw (10)
-I0511 11:49:28.460516  5581 net.cpp:572] relu2_1/dw <- conv2_1/dw
-I0511 11:49:28.460535  5581 net.cpp:527] relu2_1/dw -> conv2_1/dw (in-place)
-I0511 11:49:28.460547  5581 net.cpp:260] Setting up relu2_1/dw
-I0511 11:49:28.460554  5581 net.cpp:267] TEST Top shape for layer 10 'relu2_1/dw' 10 16 128 256 (5242880)
-I0511 11:49:28.460564  5581 layer_factory.hpp:172] Creating layer 'conv2_1/sep' of type 'Convolution'
-I0511 11:49:28.460569  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460583  5581 net.cpp:200] Created Layer conv2_1/sep (11)
-I0511 11:49:28.460587  5581 net.cpp:572] conv2_1/sep <- conv2_1/dw
-I0511 11:49:28.460592  5581 net.cpp:542] conv2_1/sep -> conv2_1/sep
-I0511 11:49:28.460750  5581 net.cpp:260] Setting up conv2_1/sep
-I0511 11:49:28.460758  5581 net.cpp:267] TEST Top shape for layer 11 'conv2_1/sep' 10 32 128 256 (10485760)
-I0511 11:49:28.460770  5581 layer_factory.hpp:172] Creating layer 'conv2_1/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.460775  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.460781  5581 net.cpp:200] Created Layer conv2_1/sep/bn (12)
-I0511 11:49:28.460799  5581 net.cpp:572] conv2_1/sep/bn <- conv2_1/sep
-I0511 11:49:28.460805  5581 net.cpp:527] conv2_1/sep/bn -> conv2_1/sep (in-place)
-I0511 11:49:28.461089  5581 net.cpp:260] Setting up conv2_1/sep/bn
-I0511 11:49:28.461097  5581 net.cpp:267] TEST Top shape for layer 12 'conv2_1/sep/bn' 10 32 128 256 (10485760)
-I0511 11:49:28.461117  5581 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Scale'
-I0511 11:49:28.461122  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461134  5581 net.cpp:200] Created Layer conv2_1/sep/scale (13)
-I0511 11:49:28.461139  5581 net.cpp:572] conv2_1/sep/scale <- conv2_1/sep
-I0511 11:49:28.461144  5581 net.cpp:527] conv2_1/sep/scale -> conv2_1/sep (in-place)
-I0511 11:49:28.461177  5581 layer_factory.hpp:172] Creating layer 'conv2_1/sep/scale' of type 'Bias'
-I0511 11:49:28.461182  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461292  5581 net.cpp:260] Setting up conv2_1/sep/scale
-I0511 11:49:28.461299  5581 net.cpp:267] TEST Top shape for layer 13 'conv2_1/sep/scale' 10 32 128 256 (10485760)
-I0511 11:49:28.461311  5581 layer_factory.hpp:172] Creating layer 'relu2_1/sep' of type 'ReLU'
-I0511 11:49:28.461318  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461323  5581 net.cpp:200] Created Layer relu2_1/sep (14)
-I0511 11:49:28.461333  5581 net.cpp:572] relu2_1/sep <- conv2_1/sep
-I0511 11:49:28.461343  5581 net.cpp:527] relu2_1/sep -> conv2_1/sep (in-place)
-I0511 11:49:28.461349  5581 net.cpp:260] Setting up relu2_1/sep
-I0511 11:49:28.461359  5581 net.cpp:267] TEST Top shape for layer 14 'relu2_1/sep' 10 32 128 256 (10485760)
-I0511 11:49:28.461364  5581 layer_factory.hpp:172] Creating layer 'conv2_2/dw' of type 'Convolution'
-I0511 11:49:28.461374  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461383  5581 net.cpp:200] Created Layer conv2_2/dw (15)
-I0511 11:49:28.461390  5581 net.cpp:572] conv2_2/dw <- conv2_1/sep
-I0511 11:49:28.461398  5581 net.cpp:542] conv2_2/dw -> conv2_2/dw
-I0511 11:49:28.461545  5581 net.cpp:260] Setting up conv2_2/dw
-I0511 11:49:28.461553  5581 net.cpp:267] TEST Top shape for layer 15 'conv2_2/dw' 10 32 64 128 (2621440)
-I0511 11:49:28.461565  5581 layer_factory.hpp:172] Creating layer 'conv2_2/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.461571  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.461582  5581 net.cpp:200] Created Layer conv2_2/dw/bn (16)
-I0511 11:49:28.461587  5581 net.cpp:572] conv2_2/dw/bn <- conv2_2/dw
-I0511 11:49:28.461596  5581 net.cpp:527] conv2_2/dw/bn -> conv2_2/dw (in-place)
-I0511 11:49:28.462540  5581 net.cpp:260] Setting up conv2_2/dw/bn
-I0511 11:49:28.462553  5581 net.cpp:267] TEST Top shape for layer 16 'conv2_2/dw/bn' 10 32 64 128 (2621440)
-I0511 11:49:28.462561  5581 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Scale'
-I0511 11:49:28.462574  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.462584  5581 net.cpp:200] Created Layer conv2_2/dw/scale (17)
-I0511 11:49:28.462594  5581 net.cpp:572] conv2_2/dw/scale <- conv2_2/dw
-I0511 11:49:28.462600  5581 net.cpp:527] conv2_2/dw/scale -> conv2_2/dw (in-place)
-I0511 11:49:28.462636  5581 layer_factory.hpp:172] Creating layer 'conv2_2/dw/scale' of type 'Bias'
-I0511 11:49:28.462641  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.462726  5581 net.cpp:260] Setting up conv2_2/dw/scale
-I0511 11:49:28.462733  5581 net.cpp:267] TEST Top shape for layer 17 'conv2_2/dw/scale' 10 32 64 128 (2621440)
-I0511 11:49:28.462746  5581 layer_factory.hpp:172] Creating layer 'relu2_2/dw' of type 'ReLU'
-I0511 11:49:28.462752  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.462766  5581 net.cpp:200] Created Layer relu2_2/dw (18)
-I0511 11:49:28.462775  5581 net.cpp:572] relu2_2/dw <- conv2_2/dw
-I0511 11:49:28.462785  5581 net.cpp:527] relu2_2/dw -> conv2_2/dw (in-place)
-I0511 11:49:28.462795  5581 net.cpp:260] Setting up relu2_2/dw
-I0511 11:49:28.462806  5581 net.cpp:267] TEST Top shape for layer 18 'relu2_2/dw' 10 32 64 128 (2621440)
-I0511 11:49:28.462811  5581 layer_factory.hpp:172] Creating layer 'conv2_2/sep' of type 'Convolution'
-I0511 11:49:28.462821  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.462831  5581 net.cpp:200] Created Layer conv2_2/sep (19)
-I0511 11:49:28.462836  5581 net.cpp:572] conv2_2/sep <- conv2_2/dw
-I0511 11:49:28.462844  5581 net.cpp:542] conv2_2/sep -> conv2_2/sep
-I0511 11:49:28.463678  5581 net.cpp:260] Setting up conv2_2/sep
-I0511 11:49:28.463695  5581 net.cpp:267] TEST Top shape for layer 19 'conv2_2/sep' 10 64 64 128 (5242880)
-I0511 11:49:28.463708  5581 layer_factory.hpp:172] Creating layer 'conv2_2/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.463716  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.463727  5581 net.cpp:200] Created Layer conv2_2/sep/bn (20)
-I0511 11:49:28.463732  5581 net.cpp:572] conv2_2/sep/bn <- conv2_2/sep
-I0511 11:49:28.463742  5581 net.cpp:527] conv2_2/sep/bn -> conv2_2/sep (in-place)
-I0511 11:49:28.464006  5581 net.cpp:260] Setting up conv2_2/sep/bn
-I0511 11:49:28.464015  5581 net.cpp:267] TEST Top shape for layer 20 'conv2_2/sep/bn' 10 64 64 128 (5242880)
-I0511 11:49:28.464028  5581 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Scale'
-I0511 11:49:28.464035  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.464046  5581 net.cpp:200] Created Layer conv2_2/sep/scale (21)
-I0511 11:49:28.464051  5581 net.cpp:572] conv2_2/sep/scale <- conv2_2/sep
-I0511 11:49:28.464061  5581 net.cpp:527] conv2_2/sep/scale -> conv2_2/sep (in-place)
-I0511 11:49:28.464095  5581 layer_factory.hpp:172] Creating layer 'conv2_2/sep/scale' of type 'Bias'
-I0511 11:49:28.464100  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.464193  5581 net.cpp:260] Setting up conv2_2/sep/scale
-I0511 11:49:28.464200  5581 net.cpp:267] TEST Top shape for layer 21 'conv2_2/sep/scale' 10 64 64 128 (5242880)
-I0511 11:49:28.464213  5581 layer_factory.hpp:172] Creating layer 'relu2_2/sep' of type 'ReLU'
-I0511 11:49:28.464220  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.464229  5581 net.cpp:200] Created Layer relu2_2/sep (22)
-I0511 11:49:28.464236  5581 net.cpp:572] relu2_2/sep <- conv2_2/sep
-I0511 11:49:28.464244  5581 net.cpp:527] relu2_2/sep -> conv2_2/sep (in-place)
-I0511 11:49:28.464252  5581 net.cpp:260] Setting up relu2_2/sep
-I0511 11:49:28.464262  5581 net.cpp:267] TEST Top shape for layer 22 'relu2_2/sep' 10 64 64 128 (5242880)
-I0511 11:49:28.464268  5581 layer_factory.hpp:172] Creating layer 'conv3_1/dw' of type 'Convolution'
-I0511 11:49:28.464277  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.464292  5581 net.cpp:200] Created Layer conv3_1/dw (23)
-I0511 11:49:28.464296  5581 net.cpp:572] conv3_1/dw <- conv2_2/sep
-I0511 11:49:28.464305  5581 net.cpp:542] conv3_1/dw -> conv3_1/dw
-I0511 11:49:28.465170  5581 net.cpp:260] Setting up conv3_1/dw
-I0511 11:49:28.465180  5581 net.cpp:267] TEST Top shape for layer 23 'conv3_1/dw' 10 64 64 128 (5242880)
-I0511 11:49:28.465186  5581 layer_factory.hpp:172] Creating layer 'conv3_1/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.465198  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465211  5581 net.cpp:200] Created Layer conv3_1/dw/bn (24)
-I0511 11:49:28.465217  5581 net.cpp:572] conv3_1/dw/bn <- conv3_1/dw
-I0511 11:49:28.465226  5581 net.cpp:527] conv3_1/dw/bn -> conv3_1/dw (in-place)
-I0511 11:49:28.465489  5581 net.cpp:260] Setting up conv3_1/dw/bn
-I0511 11:49:28.465505  5581 net.cpp:267] TEST Top shape for layer 24 'conv3_1/dw/bn' 10 64 64 128 (5242880)
-I0511 11:49:28.465523  5581 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Scale'
-I0511 11:49:28.465528  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465540  5581 net.cpp:200] Created Layer conv3_1/dw/scale (25)
-I0511 11:49:28.465545  5581 net.cpp:572] conv3_1/dw/scale <- conv3_1/dw
-I0511 11:49:28.465554  5581 net.cpp:527] conv3_1/dw/scale -> conv3_1/dw (in-place)
-I0511 11:49:28.465587  5581 layer_factory.hpp:172] Creating layer 'conv3_1/dw/scale' of type 'Bias'
-I0511 11:49:28.465592  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465680  5581 net.cpp:260] Setting up conv3_1/dw/scale
-I0511 11:49:28.465687  5581 net.cpp:267] TEST Top shape for layer 25 'conv3_1/dw/scale' 10 64 64 128 (5242880)
-I0511 11:49:28.465700  5581 layer_factory.hpp:172] Creating layer 'relu3_1/dw' of type 'ReLU'
-I0511 11:49:28.465706  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465716  5581 net.cpp:200] Created Layer relu3_1/dw (26)
-I0511 11:49:28.465721  5581 net.cpp:572] relu3_1/dw <- conv3_1/dw
-I0511 11:49:28.465730  5581 net.cpp:527] relu3_1/dw -> conv3_1/dw (in-place)
-I0511 11:49:28.465739  5581 net.cpp:260] Setting up relu3_1/dw
-I0511 11:49:28.465749  5581 net.cpp:267] TEST Top shape for layer 26 'relu3_1/dw' 10 64 64 128 (5242880)
-I0511 11:49:28.465754  5581 layer_factory.hpp:172] Creating layer 'conv3_1/sep' of type 'Convolution'
-I0511 11:49:28.465762  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.465777  5581 net.cpp:200] Created Layer conv3_1/sep (27)
-I0511 11:49:28.465781  5581 net.cpp:572] conv3_1/sep <- conv3_1/dw
-I0511 11:49:28.465791  5581 net.cpp:542] conv3_1/sep -> conv3_1/sep
-I0511 11:49:28.466006  5581 net.cpp:260] Setting up conv3_1/sep
-I0511 11:49:28.466013  5581 net.cpp:267] TEST Top shape for layer 27 'conv3_1/sep' 10 64 64 128 (5242880)
-I0511 11:49:28.466025  5581 layer_factory.hpp:172] Creating layer 'conv3_1/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.466030  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466042  5581 net.cpp:200] Created Layer conv3_1/sep/bn (28)
-I0511 11:49:28.466048  5581 net.cpp:572] conv3_1/sep/bn <- conv3_1/sep
-I0511 11:49:28.466056  5581 net.cpp:527] conv3_1/sep/bn -> conv3_1/sep (in-place)
-I0511 11:49:28.466300  5581 net.cpp:260] Setting up conv3_1/sep/bn
-I0511 11:49:28.466307  5581 net.cpp:267] TEST Top shape for layer 28 'conv3_1/sep/bn' 10 64 64 128 (5242880)
-I0511 11:49:28.466320  5581 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Scale'
-I0511 11:49:28.466327  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466338  5581 net.cpp:200] Created Layer conv3_1/sep/scale (29)
-I0511 11:49:28.466343  5581 net.cpp:572] conv3_1/sep/scale <- conv3_1/sep
-I0511 11:49:28.466352  5581 net.cpp:527] conv3_1/sep/scale -> conv3_1/sep (in-place)
-I0511 11:49:28.466385  5581 layer_factory.hpp:172] Creating layer 'conv3_1/sep/scale' of type 'Bias'
-I0511 11:49:28.466390  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466478  5581 net.cpp:260] Setting up conv3_1/sep/scale
-I0511 11:49:28.466485  5581 net.cpp:267] TEST Top shape for layer 29 'conv3_1/sep/scale' 10 64 64 128 (5242880)
-I0511 11:49:28.466497  5581 layer_factory.hpp:172] Creating layer 'relu3_1/sep' of type 'ReLU'
-I0511 11:49:28.466503  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466508  5581 net.cpp:200] Created Layer relu3_1/sep (30)
-I0511 11:49:28.466517  5581 net.cpp:572] relu3_1/sep <- conv3_1/sep
-I0511 11:49:28.466529  5581 net.cpp:527] relu3_1/sep -> conv3_1/sep (in-place)
-I0511 11:49:28.466540  5581 net.cpp:260] Setting up relu3_1/sep
-I0511 11:49:28.466552  5581 net.cpp:267] TEST Top shape for layer 30 'relu3_1/sep' 10 64 64 128 (5242880)
-I0511 11:49:28.466557  5581 layer_factory.hpp:172] Creating layer 'conv3_2/dw' of type 'Convolution'
-I0511 11:49:28.466565  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466574  5581 net.cpp:200] Created Layer conv3_2/dw (31)
-I0511 11:49:28.466579  5581 net.cpp:572] conv3_2/dw <- conv3_1/sep
-I0511 11:49:28.466589  5581 net.cpp:542] conv3_2/dw -> conv3_2/dw
-I0511 11:49:28.466734  5581 net.cpp:260] Setting up conv3_2/dw
-I0511 11:49:28.466743  5581 net.cpp:267] TEST Top shape for layer 31 'conv3_2/dw' 10 64 32 64 (1310720)
-I0511 11:49:28.466755  5581 layer_factory.hpp:172] Creating layer 'conv3_2/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.466760  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.466773  5581 net.cpp:200] Created Layer conv3_2/dw/bn (32)
-I0511 11:49:28.466778  5581 net.cpp:572] conv3_2/dw/bn <- conv3_2/dw
-I0511 11:49:28.466786  5581 net.cpp:527] conv3_2/dw/bn -> conv3_2/dw (in-place)
-I0511 11:49:28.467030  5581 net.cpp:260] Setting up conv3_2/dw/bn
-I0511 11:49:28.467036  5581 net.cpp:267] TEST Top shape for layer 32 'conv3_2/dw/bn' 10 64 32 64 (1310720)
-I0511 11:49:28.467049  5581 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Scale'
-I0511 11:49:28.467056  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467067  5581 net.cpp:200] Created Layer conv3_2/dw/scale (33)
-I0511 11:49:28.467072  5581 net.cpp:572] conv3_2/dw/scale <- conv3_2/dw
-I0511 11:49:28.467080  5581 net.cpp:527] conv3_2/dw/scale -> conv3_2/dw (in-place)
-I0511 11:49:28.467116  5581 layer_factory.hpp:172] Creating layer 'conv3_2/dw/scale' of type 'Bias'
-I0511 11:49:28.467121  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467201  5581 net.cpp:260] Setting up conv3_2/dw/scale
-I0511 11:49:28.467208  5581 net.cpp:267] TEST Top shape for layer 33 'conv3_2/dw/scale' 10 64 32 64 (1310720)
-I0511 11:49:28.467221  5581 layer_factory.hpp:172] Creating layer 'relu3_2/dw' of type 'ReLU'
-I0511 11:49:28.467226  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467236  5581 net.cpp:200] Created Layer relu3_2/dw (34)
-I0511 11:49:28.467242  5581 net.cpp:572] relu3_2/dw <- conv3_2/dw
-I0511 11:49:28.467250  5581 net.cpp:527] relu3_2/dw -> conv3_2/dw (in-place)
-I0511 11:49:28.467257  5581 net.cpp:260] Setting up relu3_2/dw
-I0511 11:49:28.467267  5581 net.cpp:267] TEST Top shape for layer 34 'relu3_2/dw' 10 64 32 64 (1310720)
-I0511 11:49:28.467272  5581 layer_factory.hpp:172] Creating layer 'conv3_2/sep' of type 'Convolution'
-I0511 11:49:28.467281  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467294  5581 net.cpp:200] Created Layer conv3_2/sep (35)
-I0511 11:49:28.467298  5581 net.cpp:572] conv3_2/sep <- conv3_2/dw
-I0511 11:49:28.467308  5581 net.cpp:542] conv3_2/sep -> conv3_2/sep
-I0511 11:49:28.467595  5581 net.cpp:260] Setting up conv3_2/sep
-I0511 11:49:28.467602  5581 net.cpp:267] TEST Top shape for layer 35 'conv3_2/sep' 10 128 32 64 (2621440)
-I0511 11:49:28.467614  5581 layer_factory.hpp:172] Creating layer 'conv3_2/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.467620  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467631  5581 net.cpp:200] Created Layer conv3_2/sep/bn (36)
-I0511 11:49:28.467636  5581 net.cpp:572] conv3_2/sep/bn <- conv3_2/sep
-I0511 11:49:28.467645  5581 net.cpp:527] conv3_2/sep/bn -> conv3_2/sep (in-place)
-I0511 11:49:28.467877  5581 net.cpp:260] Setting up conv3_2/sep/bn
-I0511 11:49:28.467885  5581 net.cpp:267] TEST Top shape for layer 36 'conv3_2/sep/bn' 10 128 32 64 (2621440)
-I0511 11:49:28.467901  5581 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Scale'
-I0511 11:49:28.467913  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.467933  5581 net.cpp:200] Created Layer conv3_2/sep/scale (37)
-I0511 11:49:28.467938  5581 net.cpp:572] conv3_2/sep/scale <- conv3_2/sep
-I0511 11:49:28.467948  5581 net.cpp:527] conv3_2/sep/scale -> conv3_2/sep (in-place)
-I0511 11:49:28.467980  5581 layer_factory.hpp:172] Creating layer 'conv3_2/sep/scale' of type 'Bias'
-I0511 11:49:28.467985  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468057  5581 net.cpp:260] Setting up conv3_2/sep/scale
-I0511 11:49:28.468065  5581 net.cpp:267] TEST Top shape for layer 37 'conv3_2/sep/scale' 10 128 32 64 (2621440)
-I0511 11:49:28.468072  5581 layer_factory.hpp:172] Creating layer 'relu3_2/sep' of type 'ReLU'
-I0511 11:49:28.468077  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468083  5581 net.cpp:200] Created Layer relu3_2/sep (38)
-I0511 11:49:28.468088  5581 net.cpp:572] relu3_2/sep <- conv3_2/sep
-I0511 11:49:28.468092  5581 net.cpp:527] relu3_2/sep -> conv3_2/sep (in-place)
-I0511 11:49:28.468099  5581 net.cpp:260] Setting up relu3_2/sep
-I0511 11:49:28.468106  5581 net.cpp:267] TEST Top shape for layer 38 'relu3_2/sep' 10 128 32 64 (2621440)
-I0511 11:49:28.468111  5581 layer_factory.hpp:172] Creating layer 'conv4_1/dw' of type 'Convolution'
-I0511 11:49:28.468116  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468128  5581 net.cpp:200] Created Layer conv4_1/dw (39)
-I0511 11:49:28.468132  5581 net.cpp:572] conv4_1/dw <- conv3_2/sep
-I0511 11:49:28.468137  5581 net.cpp:542] conv4_1/dw -> conv4_1/dw
-I0511 11:49:28.468284  5581 net.cpp:260] Setting up conv4_1/dw
-I0511 11:49:28.468291  5581 net.cpp:267] TEST Top shape for layer 39 'conv4_1/dw' 10 128 32 64 (2621440)
-I0511 11:49:28.468297  5581 layer_factory.hpp:172] Creating layer 'conv4_1/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.468299  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468305  5581 net.cpp:200] Created Layer conv4_1/dw/bn (40)
-I0511 11:49:28.468310  5581 net.cpp:572] conv4_1/dw/bn <- conv4_1/dw
-I0511 11:49:28.468315  5581 net.cpp:527] conv4_1/dw/bn -> conv4_1/dw (in-place)
-I0511 11:49:28.468911  5581 net.cpp:260] Setting up conv4_1/dw/bn
-I0511 11:49:28.468920  5581 net.cpp:267] TEST Top shape for layer 40 'conv4_1/dw/bn' 10 128 32 64 (2621440)
-I0511 11:49:28.468927  5581 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Scale'
-I0511 11:49:28.468933  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.468940  5581 net.cpp:200] Created Layer conv4_1/dw/scale (41)
-I0511 11:49:28.468945  5581 net.cpp:572] conv4_1/dw/scale <- conv4_1/dw
-I0511 11:49:28.468947  5581 net.cpp:527] conv4_1/dw/scale -> conv4_1/dw (in-place)
-I0511 11:49:28.468979  5581 layer_factory.hpp:172] Creating layer 'conv4_1/dw/scale' of type 'Bias'
-I0511 11:49:28.468986  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469060  5581 net.cpp:260] Setting up conv4_1/dw/scale
-I0511 11:49:28.469066  5581 net.cpp:267] TEST Top shape for layer 41 'conv4_1/dw/scale' 10 128 32 64 (2621440)
-I0511 11:49:28.469071  5581 layer_factory.hpp:172] Creating layer 'relu4_1/dw' of type 'ReLU'
-I0511 11:49:28.469074  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469079  5581 net.cpp:200] Created Layer relu4_1/dw (42)
-I0511 11:49:28.469084  5581 net.cpp:572] relu4_1/dw <- conv4_1/dw
-I0511 11:49:28.469087  5581 net.cpp:527] relu4_1/dw -> conv4_1/dw (in-place)
-I0511 11:49:28.469094  5581 net.cpp:260] Setting up relu4_1/dw
-I0511 11:49:28.469099  5581 net.cpp:267] TEST Top shape for layer 42 'relu4_1/dw' 10 128 32 64 (2621440)
-I0511 11:49:28.469100  5581 layer_factory.hpp:172] Creating layer 'conv4_1/sep' of type 'Convolution'
-I0511 11:49:28.469108  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469115  5581 net.cpp:200] Created Layer conv4_1/sep (43)
-I0511 11:49:28.469117  5581 net.cpp:572] conv4_1/sep <- conv4_1/dw
-I0511 11:49:28.469120  5581 net.cpp:542] conv4_1/sep -> conv4_1/sep
-I0511 11:49:28.469573  5581 net.cpp:260] Setting up conv4_1/sep
-I0511 11:49:28.469579  5581 net.cpp:267] TEST Top shape for layer 43 'conv4_1/sep' 10 128 32 64 (2621440)
-I0511 11:49:28.469584  5581 layer_factory.hpp:172] Creating layer 'conv4_1/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.469589  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469596  5581 net.cpp:200] Created Layer conv4_1/sep/bn (44)
-I0511 11:49:28.469600  5581 net.cpp:572] conv4_1/sep/bn <- conv4_1/sep
-I0511 11:49:28.469604  5581 net.cpp:527] conv4_1/sep/bn -> conv4_1/sep (in-place)
-I0511 11:49:28.469838  5581 net.cpp:260] Setting up conv4_1/sep/bn
-I0511 11:49:28.469844  5581 net.cpp:267] TEST Top shape for layer 44 'conv4_1/sep/bn' 10 128 32 64 (2621440)
-I0511 11:49:28.469856  5581 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Scale'
-I0511 11:49:28.469862  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469869  5581 net.cpp:200] Created Layer conv4_1/sep/scale (45)
-I0511 11:49:28.469872  5581 net.cpp:572] conv4_1/sep/scale <- conv4_1/sep
-I0511 11:49:28.469875  5581 net.cpp:527] conv4_1/sep/scale -> conv4_1/sep (in-place)
-I0511 11:49:28.469916  5581 layer_factory.hpp:172] Creating layer 'conv4_1/sep/scale' of type 'Bias'
-I0511 11:49:28.469923  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.469997  5581 net.cpp:260] Setting up conv4_1/sep/scale
-I0511 11:49:28.470003  5581 net.cpp:267] TEST Top shape for layer 45 'conv4_1/sep/scale' 10 128 32 64 (2621440)
-I0511 11:49:28.470010  5581 layer_factory.hpp:172] Creating layer 'relu4_1/sep' of type 'ReLU'
-I0511 11:49:28.470015  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470021  5581 net.cpp:200] Created Layer relu4_1/sep (46)
-I0511 11:49:28.470023  5581 net.cpp:572] relu4_1/sep <- conv4_1/sep
-I0511 11:49:28.470026  5581 net.cpp:527] relu4_1/sep -> conv4_1/sep (in-place)
-I0511 11:49:28.470029  5581 net.cpp:260] Setting up relu4_1/sep
-I0511 11:49:28.470032  5581 net.cpp:267] TEST Top shape for layer 46 'relu4_1/sep' 10 128 32 64 (2621440)
-I0511 11:49:28.470034  5581 layer_factory.hpp:172] Creating layer 'conv4_2/dw' of type 'Convolution'
-I0511 11:49:28.470037  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470048  5581 net.cpp:200] Created Layer conv4_2/dw (47)
-I0511 11:49:28.470054  5581 net.cpp:572] conv4_2/dw <- conv4_1/sep
-I0511 11:49:28.470058  5581 net.cpp:542] conv4_2/dw -> conv4_2/dw
-I0511 11:49:28.470216  5581 net.cpp:260] Setting up conv4_2/dw
-I0511 11:49:28.470223  5581 net.cpp:267] TEST Top shape for layer 47 'conv4_2/dw' 10 128 16 32 (655360)
-I0511 11:49:28.470228  5581 layer_factory.hpp:172] Creating layer 'conv4_2/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.470233  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470239  5581 net.cpp:200] Created Layer conv4_2/dw/bn (48)
-I0511 11:49:28.470243  5581 net.cpp:572] conv4_2/dw/bn <- conv4_2/dw
-I0511 11:49:28.470247  5581 net.cpp:527] conv4_2/dw/bn -> conv4_2/dw (in-place)
-I0511 11:49:28.470497  5581 net.cpp:260] Setting up conv4_2/dw/bn
-I0511 11:49:28.470504  5581 net.cpp:267] TEST Top shape for layer 48 'conv4_2/dw/bn' 10 128 16 32 (655360)
-I0511 11:49:28.470510  5581 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Scale'
-I0511 11:49:28.470515  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470522  5581 net.cpp:200] Created Layer conv4_2/dw/scale (49)
-I0511 11:49:28.470530  5581 net.cpp:572] conv4_2/dw/scale <- conv4_2/dw
-I0511 11:49:28.470533  5581 net.cpp:527] conv4_2/dw/scale -> conv4_2/dw (in-place)
-I0511 11:49:28.470569  5581 layer_factory.hpp:172] Creating layer 'conv4_2/dw/scale' of type 'Bias'
-I0511 11:49:28.470574  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470649  5581 net.cpp:260] Setting up conv4_2/dw/scale
-I0511 11:49:28.470655  5581 net.cpp:267] TEST Top shape for layer 49 'conv4_2/dw/scale' 10 128 16 32 (655360)
-I0511 11:49:28.470662  5581 layer_factory.hpp:172] Creating layer 'relu4_2/dw' of type 'ReLU'
-I0511 11:49:28.470667  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470674  5581 net.cpp:200] Created Layer relu4_2/dw (50)
-I0511 11:49:28.470679  5581 net.cpp:572] relu4_2/dw <- conv4_2/dw
-I0511 11:49:28.470682  5581 net.cpp:527] relu4_2/dw -> conv4_2/dw (in-place)
-I0511 11:49:28.470690  5581 net.cpp:260] Setting up relu4_2/dw
-I0511 11:49:28.470696  5581 net.cpp:267] TEST Top shape for layer 50 'relu4_2/dw' 10 128 16 32 (655360)
-I0511 11:49:28.470701  5581 layer_factory.hpp:172] Creating layer 'conv4_2/sep' of type 'Convolution'
-I0511 11:49:28.470706  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.470715  5581 net.cpp:200] Created Layer conv4_2/sep (51)
-I0511 11:49:28.470718  5581 net.cpp:572] conv4_2/sep <- conv4_2/dw
-I0511 11:49:28.470722  5581 net.cpp:542] conv4_2/sep -> conv4_2/sep
-I0511 11:49:28.471474  5581 net.cpp:260] Setting up conv4_2/sep
-I0511 11:49:28.471482  5581 net.cpp:267] TEST Top shape for layer 51 'conv4_2/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.471487  5581 layer_factory.hpp:172] Creating layer 'conv4_2/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.471491  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471498  5581 net.cpp:200] Created Layer conv4_2/sep/bn (52)
-I0511 11:49:28.471503  5581 net.cpp:572] conv4_2/sep/bn <- conv4_2/sep
-I0511 11:49:28.471508  5581 net.cpp:527] conv4_2/sep/bn -> conv4_2/sep (in-place)
-I0511 11:49:28.471745  5581 net.cpp:260] Setting up conv4_2/sep/bn
-I0511 11:49:28.471751  5581 net.cpp:267] TEST Top shape for layer 52 'conv4_2/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.471757  5581 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Scale'
-I0511 11:49:28.471763  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471771  5581 net.cpp:200] Created Layer conv4_2/sep/scale (53)
-I0511 11:49:28.471776  5581 net.cpp:572] conv4_2/sep/scale <- conv4_2/sep
-I0511 11:49:28.471781  5581 net.cpp:527] conv4_2/sep/scale -> conv4_2/sep (in-place)
-I0511 11:49:28.471813  5581 layer_factory.hpp:172] Creating layer 'conv4_2/sep/scale' of type 'Bias'
-I0511 11:49:28.471818  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471889  5581 net.cpp:260] Setting up conv4_2/sep/scale
-I0511 11:49:28.471895  5581 net.cpp:267] TEST Top shape for layer 53 'conv4_2/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.471902  5581 layer_factory.hpp:172] Creating layer 'relu4_2/sep' of type 'ReLU'
-I0511 11:49:28.471907  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471913  5581 net.cpp:200] Created Layer relu4_2/sep (54)
-I0511 11:49:28.471920  5581 net.cpp:572] relu4_2/sep <- conv4_2/sep
-I0511 11:49:28.471925  5581 net.cpp:527] relu4_2/sep -> conv4_2/sep (in-place)
-I0511 11:49:28.471931  5581 net.cpp:260] Setting up relu4_2/sep
-I0511 11:49:28.471936  5581 net.cpp:267] TEST Top shape for layer 54 'relu4_2/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.471941  5581 layer_factory.hpp:172] Creating layer 'conv5_1/dw' of type 'Convolution'
-I0511 11:49:28.471946  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.471962  5581 net.cpp:200] Created Layer conv5_1/dw (55)
-I0511 11:49:28.471971  5581 net.cpp:572] conv5_1/dw <- conv4_2/sep
-I0511 11:49:28.471976  5581 net.cpp:542] conv5_1/dw -> conv5_1/dw
-I0511 11:49:28.472154  5581 net.cpp:260] Setting up conv5_1/dw
-I0511 11:49:28.472162  5581 net.cpp:267] TEST Top shape for layer 55 'conv5_1/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.472167  5581 layer_factory.hpp:172] Creating layer 'conv5_1/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.472173  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472180  5581 net.cpp:200] Created Layer conv5_1/dw/bn (56)
-I0511 11:49:28.472185  5581 net.cpp:572] conv5_1/dw/bn <- conv5_1/dw
-I0511 11:49:28.472190  5581 net.cpp:527] conv5_1/dw/bn -> conv5_1/dw (in-place)
-I0511 11:49:28.472412  5581 net.cpp:260] Setting up conv5_1/dw/bn
-I0511 11:49:28.472419  5581 net.cpp:267] TEST Top shape for layer 56 'conv5_1/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.472426  5581 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Scale'
-I0511 11:49:28.472432  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472440  5581 net.cpp:200] Created Layer conv5_1/dw/scale (57)
-I0511 11:49:28.472445  5581 net.cpp:572] conv5_1/dw/scale <- conv5_1/dw
-I0511 11:49:28.472450  5581 net.cpp:527] conv5_1/dw/scale -> conv5_1/dw (in-place)
-I0511 11:49:28.472481  5581 layer_factory.hpp:172] Creating layer 'conv5_1/dw/scale' of type 'Bias'
-I0511 11:49:28.472484  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472581  5581 net.cpp:260] Setting up conv5_1/dw/scale
-I0511 11:49:28.472589  5581 net.cpp:267] TEST Top shape for layer 57 'conv5_1/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.472595  5581 layer_factory.hpp:172] Creating layer 'relu5_1/dw' of type 'ReLU'
-I0511 11:49:28.472600  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472604  5581 net.cpp:200] Created Layer relu5_1/dw (58)
-I0511 11:49:28.472607  5581 net.cpp:572] relu5_1/dw <- conv5_1/dw
-I0511 11:49:28.472609  5581 net.cpp:527] relu5_1/dw -> conv5_1/dw (in-place)
-I0511 11:49:28.472614  5581 net.cpp:260] Setting up relu5_1/dw
-I0511 11:49:28.472616  5581 net.cpp:267] TEST Top shape for layer 58 'relu5_1/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.472620  5581 layer_factory.hpp:172] Creating layer 'conv5_1/sep' of type 'Convolution'
-I0511 11:49:28.472625  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.472632  5581 net.cpp:200] Created Layer conv5_1/sep (59)
-I0511 11:49:28.472637  5581 net.cpp:572] conv5_1/sep <- conv5_1/dw
-I0511 11:49:28.472641  5581 net.cpp:542] conv5_1/sep -> conv5_1/sep
-I0511 11:49:28.474005  5581 net.cpp:260] Setting up conv5_1/sep
-I0511 11:49:28.474012  5581 net.cpp:267] TEST Top shape for layer 59 'conv5_1/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.474017  5581 layer_factory.hpp:172] Creating layer 'conv5_1/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.474022  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474028  5581 net.cpp:200] Created Layer conv5_1/sep/bn (60)
-I0511 11:49:28.474032  5581 net.cpp:572] conv5_1/sep/bn <- conv5_1/sep
-I0511 11:49:28.474035  5581 net.cpp:527] conv5_1/sep/bn -> conv5_1/sep (in-place)
-I0511 11:49:28.474267  5581 net.cpp:260] Setting up conv5_1/sep/bn
-I0511 11:49:28.474273  5581 net.cpp:267] TEST Top shape for layer 60 'conv5_1/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.474280  5581 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Scale'
-I0511 11:49:28.474287  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474298  5581 net.cpp:200] Created Layer conv5_1/sep/scale (61)
-I0511 11:49:28.474303  5581 net.cpp:572] conv5_1/sep/scale <- conv5_1/sep
-I0511 11:49:28.474308  5581 net.cpp:527] conv5_1/sep/scale -> conv5_1/sep (in-place)
-I0511 11:49:28.474347  5581 layer_factory.hpp:172] Creating layer 'conv5_1/sep/scale' of type 'Bias'
-I0511 11:49:28.474362  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474467  5581 net.cpp:260] Setting up conv5_1/sep/scale
-I0511 11:49:28.474475  5581 net.cpp:267] TEST Top shape for layer 61 'conv5_1/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.474483  5581 layer_factory.hpp:172] Creating layer 'relu5_1/sep' of type 'ReLU'
-I0511 11:49:28.474488  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474493  5581 net.cpp:200] Created Layer relu5_1/sep (62)
-I0511 11:49:28.474498  5581 net.cpp:572] relu5_1/sep <- conv5_1/sep
-I0511 11:49:28.474503  5581 net.cpp:527] relu5_1/sep -> conv5_1/sep (in-place)
-I0511 11:49:28.474510  5581 net.cpp:260] Setting up relu5_1/sep
-I0511 11:49:28.474517  5581 net.cpp:267] TEST Top shape for layer 62 'relu5_1/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.474522  5581 layer_factory.hpp:172] Creating layer 'conv5_2/dw' of type 'Convolution'
-I0511 11:49:28.474526  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474541  5581 net.cpp:200] Created Layer conv5_2/dw (63)
-I0511 11:49:28.474546  5581 net.cpp:572] conv5_2/dw <- conv5_1/sep
-I0511 11:49:28.474551  5581 net.cpp:542] conv5_2/dw -> conv5_2/dw
-I0511 11:49:28.474815  5581 net.cpp:260] Setting up conv5_2/dw
-I0511 11:49:28.474825  5581 net.cpp:267] TEST Top shape for layer 63 'conv5_2/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.474833  5581 layer_factory.hpp:172] Creating layer 'conv5_2/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.474836  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.474845  5581 net.cpp:200] Created Layer conv5_2/dw/bn (64)
-I0511 11:49:28.474850  5581 net.cpp:572] conv5_2/dw/bn <- conv5_2/dw
-I0511 11:49:28.474856  5581 net.cpp:527] conv5_2/dw/bn -> conv5_2/dw (in-place)
-I0511 11:49:28.475193  5581 net.cpp:260] Setting up conv5_2/dw/bn
-I0511 11:49:28.475201  5581 net.cpp:267] TEST Top shape for layer 64 'conv5_2/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.475210  5581 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Scale'
-I0511 11:49:28.475215  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.475222  5581 net.cpp:200] Created Layer conv5_2/dw/scale (65)
-I0511 11:49:28.475227  5581 net.cpp:572] conv5_2/dw/scale <- conv5_2/dw
-I0511 11:49:28.475234  5581 net.cpp:527] conv5_2/dw/scale -> conv5_2/dw (in-place)
-I0511 11:49:28.475276  5581 layer_factory.hpp:172] Creating layer 'conv5_2/dw/scale' of type 'Bias'
-I0511 11:49:28.475282  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.475384  5581 net.cpp:260] Setting up conv5_2/dw/scale
-I0511 11:49:28.475394  5581 net.cpp:267] TEST Top shape for layer 65 'conv5_2/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.475401  5581 layer_factory.hpp:172] Creating layer 'relu5_2/dw' of type 'ReLU'
-I0511 11:49:28.475406  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.475415  5581 net.cpp:200] Created Layer relu5_2/dw (66)
-I0511 11:49:28.475421  5581 net.cpp:572] relu5_2/dw <- conv5_2/dw
-I0511 11:49:28.475426  5581 net.cpp:527] relu5_2/dw -> conv5_2/dw (in-place)
-I0511 11:49:28.475433  5581 net.cpp:260] Setting up relu5_2/dw
-I0511 11:49:28.475440  5581 net.cpp:267] TEST Top shape for layer 66 'relu5_2/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.475445  5581 layer_factory.hpp:172] Creating layer 'conv5_2/sep' of type 'Convolution'
-I0511 11:49:28.475450  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.475458  5581 net.cpp:200] Created Layer conv5_2/sep (67)
-I0511 11:49:28.475463  5581 net.cpp:572] conv5_2/sep <- conv5_2/dw
-I0511 11:49:28.475468  5581 net.cpp:542] conv5_2/sep -> conv5_2/sep
-I0511 11:49:28.477046  5581 net.cpp:260] Setting up conv5_2/sep
-I0511 11:49:28.477087  5581 net.cpp:267] TEST Top shape for layer 67 'conv5_2/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.477098  5581 layer_factory.hpp:172] Creating layer 'conv5_2/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.477108  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477123  5581 net.cpp:200] Created Layer conv5_2/sep/bn (68)
-I0511 11:49:28.477130  5581 net.cpp:572] conv5_2/sep/bn <- conv5_2/sep
-I0511 11:49:28.477138  5581 net.cpp:527] conv5_2/sep/bn -> conv5_2/sep (in-place)
-I0511 11:49:28.477432  5581 net.cpp:260] Setting up conv5_2/sep/bn
-I0511 11:49:28.477438  5581 net.cpp:267] TEST Top shape for layer 68 'conv5_2/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.477447  5581 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Scale'
-I0511 11:49:28.477452  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477466  5581 net.cpp:200] Created Layer conv5_2/sep/scale (69)
-I0511 11:49:28.477470  5581 net.cpp:572] conv5_2/sep/scale <- conv5_2/sep
-I0511 11:49:28.477474  5581 net.cpp:527] conv5_2/sep/scale -> conv5_2/sep (in-place)
-I0511 11:49:28.477512  5581 layer_factory.hpp:172] Creating layer 'conv5_2/sep/scale' of type 'Bias'
-I0511 11:49:28.477519  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477600  5581 net.cpp:260] Setting up conv5_2/sep/scale
-I0511 11:49:28.477607  5581 net.cpp:267] TEST Top shape for layer 69 'conv5_2/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.477613  5581 layer_factory.hpp:172] Creating layer 'relu5_2/sep' of type 'ReLU'
-I0511 11:49:28.477618  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477624  5581 net.cpp:200] Created Layer relu5_2/sep (70)
-I0511 11:49:28.477629  5581 net.cpp:572] relu5_2/sep <- conv5_2/sep
-I0511 11:49:28.477634  5581 net.cpp:527] relu5_2/sep -> conv5_2/sep (in-place)
-I0511 11:49:28.477641  5581 net.cpp:260] Setting up relu5_2/sep
-I0511 11:49:28.477648  5581 net.cpp:267] TEST Top shape for layer 70 'relu5_2/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.477651  5581 layer_factory.hpp:172] Creating layer 'conv5_3/dw' of type 'Convolution'
-I0511 11:49:28.477656  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477669  5581 net.cpp:200] Created Layer conv5_3/dw (71)
-I0511 11:49:28.477674  5581 net.cpp:572] conv5_3/dw <- conv5_2/sep
-I0511 11:49:28.477676  5581 net.cpp:542] conv5_3/dw -> conv5_3/dw
-I0511 11:49:28.477857  5581 net.cpp:260] Setting up conv5_3/dw
-I0511 11:49:28.477864  5581 net.cpp:267] TEST Top shape for layer 71 'conv5_3/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.477870  5581 layer_factory.hpp:172] Creating layer 'conv5_3/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.477876  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.477882  5581 net.cpp:200] Created Layer conv5_3/dw/bn (72)
-I0511 11:49:28.477887  5581 net.cpp:572] conv5_3/dw/bn <- conv5_3/dw
-I0511 11:49:28.477893  5581 net.cpp:527] conv5_3/dw/bn -> conv5_3/dw (in-place)
-I0511 11:49:28.478126  5581 net.cpp:260] Setting up conv5_3/dw/bn
-I0511 11:49:28.478132  5581 net.cpp:267] TEST Top shape for layer 72 'conv5_3/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.478139  5581 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Scale'
-I0511 11:49:28.478145  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.478153  5581 net.cpp:200] Created Layer conv5_3/dw/scale (73)
-I0511 11:49:28.478157  5581 net.cpp:572] conv5_3/dw/scale <- conv5_3/dw
-I0511 11:49:28.478161  5581 net.cpp:527] conv5_3/dw/scale -> conv5_3/dw (in-place)
-I0511 11:49:28.478193  5581 layer_factory.hpp:172] Creating layer 'conv5_3/dw/scale' of type 'Bias'
-I0511 11:49:28.478196  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.478271  5581 net.cpp:260] Setting up conv5_3/dw/scale
-I0511 11:49:28.478281  5581 net.cpp:267] TEST Top shape for layer 73 'conv5_3/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.478288  5581 layer_factory.hpp:172] Creating layer 'relu5_3/dw' of type 'ReLU'
-I0511 11:49:28.478294  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.478298  5581 net.cpp:200] Created Layer relu5_3/dw (74)
-I0511 11:49:28.478302  5581 net.cpp:572] relu5_3/dw <- conv5_3/dw
-I0511 11:49:28.478307  5581 net.cpp:527] relu5_3/dw -> conv5_3/dw (in-place)
-I0511 11:49:28.478319  5581 net.cpp:260] Setting up relu5_3/dw
-I0511 11:49:28.478323  5581 net.cpp:267] TEST Top shape for layer 74 'relu5_3/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.478327  5581 layer_factory.hpp:172] Creating layer 'conv5_3/sep' of type 'Convolution'
-I0511 11:49:28.478332  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.478340  5581 net.cpp:200] Created Layer conv5_3/sep (75)
-I0511 11:49:28.478344  5581 net.cpp:572] conv5_3/sep <- conv5_3/dw
-I0511 11:49:28.478348  5581 net.cpp:542] conv5_3/sep -> conv5_3/sep
-I0511 11:49:28.479776  5581 net.cpp:260] Setting up conv5_3/sep
-I0511 11:49:28.479785  5581 net.cpp:267] TEST Top shape for layer 75 'conv5_3/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.479792  5581 layer_factory.hpp:172] Creating layer 'conv5_3/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.479797  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.479802  5581 net.cpp:200] Created Layer conv5_3/sep/bn (76)
-I0511 11:49:28.479805  5581 net.cpp:572] conv5_3/sep/bn <- conv5_3/sep
-I0511 11:49:28.479809  5581 net.cpp:527] conv5_3/sep/bn -> conv5_3/sep (in-place)
-I0511 11:49:28.480049  5581 net.cpp:260] Setting up conv5_3/sep/bn
-I0511 11:49:28.480057  5581 net.cpp:267] TEST Top shape for layer 76 'conv5_3/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.480064  5581 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Scale'
-I0511 11:49:28.480069  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480074  5581 net.cpp:200] Created Layer conv5_3/sep/scale (77)
-I0511 11:49:28.480079  5581 net.cpp:572] conv5_3/sep/scale <- conv5_3/sep
-I0511 11:49:28.480085  5581 net.cpp:527] conv5_3/sep/scale -> conv5_3/sep (in-place)
-I0511 11:49:28.480114  5581 layer_factory.hpp:172] Creating layer 'conv5_3/sep/scale' of type 'Bias'
-I0511 11:49:28.480119  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480186  5581 net.cpp:260] Setting up conv5_3/sep/scale
-I0511 11:49:28.480191  5581 net.cpp:267] TEST Top shape for layer 77 'conv5_3/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.480198  5581 layer_factory.hpp:172] Creating layer 'relu5_3/sep' of type 'ReLU'
-I0511 11:49:28.480203  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480211  5581 net.cpp:200] Created Layer relu5_3/sep (78)
-I0511 11:49:28.480216  5581 net.cpp:572] relu5_3/sep <- conv5_3/sep
-I0511 11:49:28.480221  5581 net.cpp:527] relu5_3/sep -> conv5_3/sep (in-place)
-I0511 11:49:28.480227  5581 net.cpp:260] Setting up relu5_3/sep
-I0511 11:49:28.480232  5581 net.cpp:267] TEST Top shape for layer 78 'relu5_3/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.480238  5581 layer_factory.hpp:172] Creating layer 'conv5_4/dw' of type 'Convolution'
-I0511 11:49:28.480243  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480252  5581 net.cpp:200] Created Layer conv5_4/dw (79)
-I0511 11:49:28.480257  5581 net.cpp:572] conv5_4/dw <- conv5_3/sep
-I0511 11:49:28.480260  5581 net.cpp:542] conv5_4/dw -> conv5_4/dw
-I0511 11:49:28.480432  5581 net.cpp:260] Setting up conv5_4/dw
-I0511 11:49:28.480439  5581 net.cpp:267] TEST Top shape for layer 79 'conv5_4/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.480445  5581 layer_factory.hpp:172] Creating layer 'conv5_4/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.480458  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480463  5581 net.cpp:200] Created Layer conv5_4/dw/bn (80)
-I0511 11:49:28.480469  5581 net.cpp:572] conv5_4/dw/bn <- conv5_4/dw
-I0511 11:49:28.480474  5581 net.cpp:527] conv5_4/dw/bn -> conv5_4/dw (in-place)
-I0511 11:49:28.480720  5581 net.cpp:260] Setting up conv5_4/dw/bn
-I0511 11:49:28.480726  5581 net.cpp:267] TEST Top shape for layer 80 'conv5_4/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.480734  5581 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Scale'
-I0511 11:49:28.480739  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480746  5581 net.cpp:200] Created Layer conv5_4/dw/scale (81)
-I0511 11:49:28.480751  5581 net.cpp:572] conv5_4/dw/scale <- conv5_4/dw
-I0511 11:49:28.480756  5581 net.cpp:527] conv5_4/dw/scale -> conv5_4/dw (in-place)
-I0511 11:49:28.480792  5581 layer_factory.hpp:172] Creating layer 'conv5_4/dw/scale' of type 'Bias'
-I0511 11:49:28.480796  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480865  5581 net.cpp:260] Setting up conv5_4/dw/scale
-I0511 11:49:28.480870  5581 net.cpp:267] TEST Top shape for layer 81 'conv5_4/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.480877  5581 layer_factory.hpp:172] Creating layer 'relu5_4/dw' of type 'ReLU'
-I0511 11:49:28.480882  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480888  5581 net.cpp:200] Created Layer relu5_4/dw (82)
-I0511 11:49:28.480893  5581 net.cpp:572] relu5_4/dw <- conv5_4/dw
-I0511 11:49:28.480898  5581 net.cpp:527] relu5_4/dw -> conv5_4/dw (in-place)
-I0511 11:49:28.480904  5581 net.cpp:260] Setting up relu5_4/dw
-I0511 11:49:28.480911  5581 net.cpp:267] TEST Top shape for layer 82 'relu5_4/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.480916  5581 layer_factory.hpp:172] Creating layer 'conv5_4/sep' of type 'Convolution'
-I0511 11:49:28.480919  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.480933  5581 net.cpp:200] Created Layer conv5_4/sep (83)
-I0511 11:49:28.480937  5581 net.cpp:572] conv5_4/sep <- conv5_4/dw
-I0511 11:49:28.480940  5581 net.cpp:542] conv5_4/sep -> conv5_4/sep
-I0511 11:49:28.482995  5581 net.cpp:260] Setting up conv5_4/sep
-I0511 11:49:28.483008  5581 net.cpp:267] TEST Top shape for layer 83 'conv5_4/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.483016  5581 layer_factory.hpp:172] Creating layer 'conv5_4/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.483022  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483032  5581 net.cpp:200] Created Layer conv5_4/sep/bn (84)
-I0511 11:49:28.483036  5581 net.cpp:572] conv5_4/sep/bn <- conv5_4/sep
-I0511 11:49:28.483042  5581 net.cpp:527] conv5_4/sep/bn -> conv5_4/sep (in-place)
-I0511 11:49:28.483292  5581 net.cpp:260] Setting up conv5_4/sep/bn
-I0511 11:49:28.483299  5581 net.cpp:267] TEST Top shape for layer 84 'conv5_4/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.483309  5581 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Scale'
-I0511 11:49:28.483314  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483325  5581 net.cpp:200] Created Layer conv5_4/sep/scale (85)
-I0511 11:49:28.483330  5581 net.cpp:572] conv5_4/sep/scale <- conv5_4/sep
-I0511 11:49:28.483333  5581 net.cpp:527] conv5_4/sep/scale -> conv5_4/sep (in-place)
-I0511 11:49:28.483366  5581 layer_factory.hpp:172] Creating layer 'conv5_4/sep/scale' of type 'Bias'
-I0511 11:49:28.483369  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483444  5581 net.cpp:260] Setting up conv5_4/sep/scale
-I0511 11:49:28.483450  5581 net.cpp:267] TEST Top shape for layer 85 'conv5_4/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.483458  5581 layer_factory.hpp:172] Creating layer 'relu5_4/sep' of type 'ReLU'
-I0511 11:49:28.483470  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483477  5581 net.cpp:200] Created Layer relu5_4/sep (86)
-I0511 11:49:28.483482  5581 net.cpp:572] relu5_4/sep <- conv5_4/sep
-I0511 11:49:28.483487  5581 net.cpp:527] relu5_4/sep -> conv5_4/sep (in-place)
-I0511 11:49:28.483494  5581 net.cpp:260] Setting up relu5_4/sep
-I0511 11:49:28.483500  5581 net.cpp:267] TEST Top shape for layer 86 'relu5_4/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.483506  5581 layer_factory.hpp:172] Creating layer 'conv5_5/dw' of type 'Convolution'
-I0511 11:49:28.483511  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483520  5581 net.cpp:200] Created Layer conv5_5/dw (87)
-I0511 11:49:28.483525  5581 net.cpp:572] conv5_5/dw <- conv5_4/sep
-I0511 11:49:28.483528  5581 net.cpp:542] conv5_5/dw -> conv5_5/dw
-I0511 11:49:28.483711  5581 net.cpp:260] Setting up conv5_5/dw
-I0511 11:49:28.483718  5581 net.cpp:267] TEST Top shape for layer 87 'conv5_5/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.483726  5581 layer_factory.hpp:172] Creating layer 'conv5_5/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.483731  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.483736  5581 net.cpp:200] Created Layer conv5_5/dw/bn (88)
-I0511 11:49:28.483738  5581 net.cpp:572] conv5_5/dw/bn <- conv5_5/dw
-I0511 11:49:28.483741  5581 net.cpp:527] conv5_5/dw/bn -> conv5_5/dw (in-place)
-I0511 11:49:28.483975  5581 net.cpp:260] Setting up conv5_5/dw/bn
-I0511 11:49:28.483981  5581 net.cpp:267] TEST Top shape for layer 88 'conv5_5/dw/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.483999  5581 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Scale'
-I0511 11:49:28.484004  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.484014  5581 net.cpp:200] Created Layer conv5_5/dw/scale (89)
-I0511 11:49:28.484019  5581 net.cpp:572] conv5_5/dw/scale <- conv5_5/dw
-I0511 11:49:28.484021  5581 net.cpp:527] conv5_5/dw/scale -> conv5_5/dw (in-place)
-I0511 11:49:28.484050  5581 layer_factory.hpp:172] Creating layer 'conv5_5/dw/scale' of type 'Bias'
-I0511 11:49:28.484055  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.484128  5581 net.cpp:260] Setting up conv5_5/dw/scale
-I0511 11:49:28.484134  5581 net.cpp:267] TEST Top shape for layer 89 'conv5_5/dw/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.484141  5581 layer_factory.hpp:172] Creating layer 'relu5_5/dw' of type 'ReLU'
-I0511 11:49:28.484146  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.484150  5581 net.cpp:200] Created Layer relu5_5/dw (90)
-I0511 11:49:28.484155  5581 net.cpp:572] relu5_5/dw <- conv5_5/dw
-I0511 11:49:28.484161  5581 net.cpp:527] relu5_5/dw -> conv5_5/dw (in-place)
-I0511 11:49:28.484169  5581 net.cpp:260] Setting up relu5_5/dw
-I0511 11:49:28.484174  5581 net.cpp:267] TEST Top shape for layer 90 'relu5_5/dw' 10 256 16 32 (1310720)
-I0511 11:49:28.484179  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep' of type 'Convolution'
-I0511 11:49:28.484184  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.484192  5581 net.cpp:200] Created Layer conv5_5/sep (91)
-I0511 11:49:28.484197  5581 net.cpp:572] conv5_5/sep <- conv5_5/dw
-I0511 11:49:28.484201  5581 net.cpp:542] conv5_5/sep -> conv5_5/sep
-I0511 11:49:28.485569  5581 net.cpp:260] Setting up conv5_5/sep
-I0511 11:49:28.485576  5581 net.cpp:267] TEST Top shape for layer 91 'conv5_5/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.485584  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.485589  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.485596  5581 net.cpp:200] Created Layer conv5_5/sep/bn (92)
-I0511 11:49:28.485610  5581 net.cpp:572] conv5_5/sep/bn <- conv5_5/sep
-I0511 11:49:28.485615  5581 net.cpp:527] conv5_5/sep/bn -> conv5_5/sep (in-place)
-I0511 11:49:28.485862  5581 net.cpp:260] Setting up conv5_5/sep/bn
-I0511 11:49:28.485868  5581 net.cpp:267] TEST Top shape for layer 92 'conv5_5/sep/bn' 10 256 16 32 (1310720)
-I0511 11:49:28.485877  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Scale'
-I0511 11:49:28.485882  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.485889  5581 net.cpp:200] Created Layer conv5_5/sep/scale (93)
-I0511 11:49:28.485894  5581 net.cpp:572] conv5_5/sep/scale <- conv5_5/sep
-I0511 11:49:28.485899  5581 net.cpp:527] conv5_5/sep/scale -> conv5_5/sep (in-place)
-I0511 11:49:28.485930  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep/scale' of type 'Bias'
-I0511 11:49:28.485935  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486006  5581 net.cpp:260] Setting up conv5_5/sep/scale
-I0511 11:49:28.486011  5581 net.cpp:267] TEST Top shape for layer 93 'conv5_5/sep/scale' 10 256 16 32 (1310720)
-I0511 11:49:28.486018  5581 layer_factory.hpp:172] Creating layer 'relu5_5/sep' of type 'ReLU'
-I0511 11:49:28.486023  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486029  5581 net.cpp:200] Created Layer relu5_5/sep (94)
-I0511 11:49:28.486034  5581 net.cpp:572] relu5_5/sep <- conv5_5/sep
-I0511 11:49:28.486038  5581 net.cpp:527] relu5_5/sep -> conv5_5/sep (in-place)
-I0511 11:49:28.486047  5581 net.cpp:260] Setting up relu5_5/sep
-I0511 11:49:28.486052  5581 net.cpp:267] TEST Top shape for layer 94 'relu5_5/sep' 10 256 16 32 (1310720)
-I0511 11:49:28.486054  5581 layer_factory.hpp:172] Creating layer 'conv5_5/sep_relu5_5/sep_0_split' of type 'Split'
-I0511 11:49:28.486060  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486068  5581 net.cpp:200] Created Layer conv5_5/sep_relu5_5/sep_0_split (95)
-I0511 11:49:28.486073  5581 net.cpp:572] conv5_5/sep_relu5_5/sep_0_split <- conv5_5/sep
-I0511 11:49:28.486076  5581 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_0
-I0511 11:49:28.486084  5581 net.cpp:542] conv5_5/sep_relu5_5/sep_0_split -> conv5_5/sep_relu5_5/sep_0_split_1
-I0511 11:49:28.486119  5581 net.cpp:260] Setting up conv5_5/sep_relu5_5/sep_0_split
-I0511 11:49:28.486125  5581 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 10 256 16 32 (1310720)
-I0511 11:49:28.486131  5581 net.cpp:267] TEST Top shape for layer 95 'conv5_5/sep_relu5_5/sep_0_split' 10 256 16 32 (1310720)
-I0511 11:49:28.486136  5581 layer_factory.hpp:172] Creating layer 'conv5_6/dw' of type 'Convolution'
-I0511 11:49:28.486141  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486155  5581 net.cpp:200] Created Layer conv5_6/dw (96)
-I0511 11:49:28.486160  5581 net.cpp:572] conv5_6/dw <- conv5_5/sep_relu5_5/sep_0_split_0
-I0511 11:49:28.486163  5581 net.cpp:542] conv5_6/dw -> conv5_6/dw
-I0511 11:49:28.486348  5581 net.cpp:260] Setting up conv5_6/dw
-I0511 11:49:28.486354  5581 net.cpp:267] TEST Top shape for layer 96 'conv5_6/dw' 10 256 8 16 (327680)
-I0511 11:49:28.486361  5581 layer_factory.hpp:172] Creating layer 'conv5_6/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.486367  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486372  5581 net.cpp:200] Created Layer conv5_6/dw/bn (97)
-I0511 11:49:28.486377  5581 net.cpp:572] conv5_6/dw/bn <- conv5_6/dw
-I0511 11:49:28.486382  5581 net.cpp:527] conv5_6/dw/bn -> conv5_6/dw (in-place)
-I0511 11:49:28.486614  5581 net.cpp:260] Setting up conv5_6/dw/bn
-I0511 11:49:28.486621  5581 net.cpp:267] TEST Top shape for layer 97 'conv5_6/dw/bn' 10 256 8 16 (327680)
-I0511 11:49:28.486629  5581 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Scale'
-I0511 11:49:28.486634  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486646  5581 net.cpp:200] Created Layer conv5_6/dw/scale (98)
-I0511 11:49:28.486651  5581 net.cpp:572] conv5_6/dw/scale <- conv5_6/dw
-I0511 11:49:28.486656  5581 net.cpp:527] conv5_6/dw/scale -> conv5_6/dw (in-place)
-I0511 11:49:28.486686  5581 layer_factory.hpp:172] Creating layer 'conv5_6/dw/scale' of type 'Bias'
-I0511 11:49:28.486691  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486759  5581 net.cpp:260] Setting up conv5_6/dw/scale
-I0511 11:49:28.486765  5581 net.cpp:267] TEST Top shape for layer 98 'conv5_6/dw/scale' 10 256 8 16 (327680)
-I0511 11:49:28.486783  5581 layer_factory.hpp:172] Creating layer 'relu5_6/dw' of type 'ReLU'
-I0511 11:49:28.486788  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486793  5581 net.cpp:200] Created Layer relu5_6/dw (99)
-I0511 11:49:28.486804  5581 net.cpp:572] relu5_6/dw <- conv5_6/dw
-I0511 11:49:28.486809  5581 net.cpp:527] relu5_6/dw -> conv5_6/dw (in-place)
-I0511 11:49:28.486819  5581 net.cpp:260] Setting up relu5_6/dw
-I0511 11:49:28.486824  5581 net.cpp:267] TEST Top shape for layer 99 'relu5_6/dw' 10 256 8 16 (327680)
-I0511 11:49:28.486834  5581 layer_factory.hpp:172] Creating layer 'conv5_6/sep' of type 'Convolution'
-I0511 11:49:28.486837  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.486855  5581 net.cpp:200] Created Layer conv5_6/sep (100)
-I0511 11:49:28.486860  5581 net.cpp:572] conv5_6/sep <- conv5_6/dw
-I0511 11:49:28.486868  5581 net.cpp:542] conv5_6/sep -> conv5_6/sep
-I0511 11:49:28.489506  5581 net.cpp:260] Setting up conv5_6/sep
-I0511 11:49:28.489519  5581 net.cpp:267] TEST Top shape for layer 100 'conv5_6/sep' 10 512 8 16 (655360)
-I0511 11:49:28.489526  5581 layer_factory.hpp:172] Creating layer 'conv5_6/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.489532  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.489542  5581 net.cpp:200] Created Layer conv5_6/sep/bn (101)
-I0511 11:49:28.489545  5581 net.cpp:572] conv5_6/sep/bn <- conv5_6/sep
-I0511 11:49:28.489550  5581 net.cpp:527] conv5_6/sep/bn -> conv5_6/sep (in-place)
-I0511 11:49:28.489810  5581 net.cpp:260] Setting up conv5_6/sep/bn
-I0511 11:49:28.489819  5581 net.cpp:267] TEST Top shape for layer 101 'conv5_6/sep/bn' 10 512 8 16 (655360)
-I0511 11:49:28.489828  5581 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Scale'
-I0511 11:49:28.489832  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.489840  5581 net.cpp:200] Created Layer conv5_6/sep/scale (102)
-I0511 11:49:28.489843  5581 net.cpp:572] conv5_6/sep/scale <- conv5_6/sep
-I0511 11:49:28.489848  5581 net.cpp:527] conv5_6/sep/scale -> conv5_6/sep (in-place)
-I0511 11:49:28.489881  5581 layer_factory.hpp:172] Creating layer 'conv5_6/sep/scale' of type 'Bias'
-I0511 11:49:28.489886  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.489965  5581 net.cpp:260] Setting up conv5_6/sep/scale
-I0511 11:49:28.489971  5581 net.cpp:267] TEST Top shape for layer 102 'conv5_6/sep/scale' 10 512 8 16 (655360)
-I0511 11:49:28.489979  5581 layer_factory.hpp:172] Creating layer 'relu5_6/sep' of type 'ReLU'
-I0511 11:49:28.489982  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.489989  5581 net.cpp:200] Created Layer relu5_6/sep (103)
-I0511 11:49:28.489992  5581 net.cpp:572] relu5_6/sep <- conv5_6/sep
-I0511 11:49:28.489996  5581 net.cpp:527] relu5_6/sep -> conv5_6/sep (in-place)
-I0511 11:49:28.490003  5581 net.cpp:260] Setting up relu5_6/sep
-I0511 11:49:28.490008  5581 net.cpp:267] TEST Top shape for layer 103 'relu5_6/sep' 10 512 8 16 (655360)
-I0511 11:49:28.490013  5581 layer_factory.hpp:172] Creating layer 'conv6/dw' of type 'Convolution'
-I0511 11:49:28.490017  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490032  5581 net.cpp:200] Created Layer conv6/dw (104)
-I0511 11:49:28.490036  5581 net.cpp:572] conv6/dw <- conv5_6/sep
-I0511 11:49:28.490042  5581 net.cpp:542] conv6/dw -> conv6/dw
-I0511 11:49:28.490264  5581 net.cpp:260] Setting up conv6/dw
-I0511 11:49:28.490272  5581 net.cpp:267] TEST Top shape for layer 104 'conv6/dw' 10 512 8 16 (655360)
-I0511 11:49:28.490278  5581 layer_factory.hpp:172] Creating layer 'conv6/dw/bn' of type 'BatchNorm'
-I0511 11:49:28.490283  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490289  5581 net.cpp:200] Created Layer conv6/dw/bn (105)
-I0511 11:49:28.490293  5581 net.cpp:572] conv6/dw/bn <- conv6/dw
-I0511 11:49:28.490298  5581 net.cpp:527] conv6/dw/bn -> conv6/dw (in-place)
-I0511 11:49:28.490540  5581 net.cpp:260] Setting up conv6/dw/bn
-I0511 11:49:28.490547  5581 net.cpp:267] TEST Top shape for layer 105 'conv6/dw/bn' 10 512 8 16 (655360)
-I0511 11:49:28.490556  5581 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Scale'
-I0511 11:49:28.490559  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490569  5581 net.cpp:200] Created Layer conv6/dw/scale (106)
-I0511 11:49:28.490573  5581 net.cpp:572] conv6/dw/scale <- conv6/dw
-I0511 11:49:28.490578  5581 net.cpp:527] conv6/dw/scale -> conv6/dw (in-place)
-I0511 11:49:28.490607  5581 layer_factory.hpp:172] Creating layer 'conv6/dw/scale' of type 'Bias'
-I0511 11:49:28.490612  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490687  5581 net.cpp:260] Setting up conv6/dw/scale
-I0511 11:49:28.490694  5581 net.cpp:267] TEST Top shape for layer 106 'conv6/dw/scale' 10 512 8 16 (655360)
-I0511 11:49:28.490701  5581 layer_factory.hpp:172] Creating layer 'relu6/dw' of type 'ReLU'
-I0511 11:49:28.490705  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490711  5581 net.cpp:200] Created Layer relu6/dw (107)
-I0511 11:49:28.490715  5581 net.cpp:572] relu6/dw <- conv6/dw
-I0511 11:49:28.490720  5581 net.cpp:527] relu6/dw -> conv6/dw (in-place)
-I0511 11:49:28.490725  5581 net.cpp:260] Setting up relu6/dw
-I0511 11:49:28.490731  5581 net.cpp:267] TEST Top shape for layer 107 'relu6/dw' 10 512 8 16 (655360)
-I0511 11:49:28.490736  5581 layer_factory.hpp:172] Creating layer 'conv6/sep' of type 'Convolution'
-I0511 11:49:28.490741  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.490748  5581 net.cpp:200] Created Layer conv6/sep (108)
-I0511 11:49:28.490752  5581 net.cpp:572] conv6/sep <- conv6/dw
-I0511 11:49:28.490757  5581 net.cpp:542] conv6/sep -> conv6/sep
-I0511 11:49:28.495813  5581 net.cpp:260] Setting up conv6/sep
-I0511 11:49:28.495831  5581 net.cpp:267] TEST Top shape for layer 108 'conv6/sep' 10 512 8 16 (655360)
-I0511 11:49:28.495841  5581 layer_factory.hpp:172] Creating layer 'conv6/sep/bn' of type 'BatchNorm'
-I0511 11:49:28.495862  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.495872  5581 net.cpp:200] Created Layer conv6/sep/bn (109)
-I0511 11:49:28.495878  5581 net.cpp:572] conv6/sep/bn <- conv6/sep
-I0511 11:49:28.495884  5581 net.cpp:527] conv6/sep/bn -> conv6/sep (in-place)
-I0511 11:49:28.496156  5581 net.cpp:260] Setting up conv6/sep/bn
-I0511 11:49:28.496163  5581 net.cpp:267] TEST Top shape for layer 109 'conv6/sep/bn' 10 512 8 16 (655360)
-I0511 11:49:28.496171  5581 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Scale'
-I0511 11:49:28.496176  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496187  5581 net.cpp:200] Created Layer conv6/sep/scale (110)
-I0511 11:49:28.496191  5581 net.cpp:572] conv6/sep/scale <- conv6/sep
-I0511 11:49:28.496196  5581 net.cpp:527] conv6/sep/scale -> conv6/sep (in-place)
-I0511 11:49:28.496235  5581 layer_factory.hpp:172] Creating layer 'conv6/sep/scale' of type 'Bias'
-I0511 11:49:28.496240  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496492  5581 net.cpp:260] Setting up conv6/sep/scale
-I0511 11:49:28.496501  5581 net.cpp:267] TEST Top shape for layer 110 'conv6/sep/scale' 10 512 8 16 (655360)
-I0511 11:49:28.496510  5581 layer_factory.hpp:172] Creating layer 'relu6/sep' of type 'ReLU'
-I0511 11:49:28.496513  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496520  5581 net.cpp:200] Created Layer relu6/sep (111)
-I0511 11:49:28.496529  5581 net.cpp:572] relu6/sep <- conv6/sep
-I0511 11:49:28.496534  5581 net.cpp:527] relu6/sep -> conv6/sep (in-place)
-I0511 11:49:28.496541  5581 net.cpp:260] Setting up relu6/sep
-I0511 11:49:28.496546  5581 net.cpp:267] TEST Top shape for layer 111 'relu6/sep' 10 512 8 16 (655360)
-I0511 11:49:28.496551  5581 layer_factory.hpp:172] Creating layer 'conv6/sep_relu6/sep_0_split' of type 'Split'
-I0511 11:49:28.496556  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496564  5581 net.cpp:200] Created Layer conv6/sep_relu6/sep_0_split (112)
-I0511 11:49:28.496567  5581 net.cpp:572] conv6/sep_relu6/sep_0_split <- conv6/sep
-I0511 11:49:28.496572  5581 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_0
-I0511 11:49:28.496579  5581 net.cpp:542] conv6/sep_relu6/sep_0_split -> conv6/sep_relu6/sep_0_split_1
-I0511 11:49:28.496610  5581 net.cpp:260] Setting up conv6/sep_relu6/sep_0_split
-I0511 11:49:28.496616  5581 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.496623  5581 net.cpp:267] TEST Top shape for layer 112 'conv6/sep_relu6/sep_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.496628  5581 layer_factory.hpp:172] Creating layer 'pool6' of type 'Pooling'
-I0511 11:49:28.496631  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496641  5581 net.cpp:200] Created Layer pool6 (113)
-I0511 11:49:28.496645  5581 net.cpp:572] pool6 <- conv6/sep_relu6/sep_0_split_0
-I0511 11:49:28.496651  5581 net.cpp:542] pool6 -> pool6
-I0511 11:49:28.496702  5581 net.cpp:260] Setting up pool6
-I0511 11:49:28.496708  5581 net.cpp:267] TEST Top shape for layer 113 'pool6' 10 512 5 9 (230400)
-I0511 11:49:28.496713  5581 layer_factory.hpp:172] Creating layer 'pool6_pool6_0_split' of type 'Split'
-I0511 11:49:28.496718  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496723  5581 net.cpp:200] Created Layer pool6_pool6_0_split (114)
-I0511 11:49:28.496728  5581 net.cpp:572] pool6_pool6_0_split <- pool6
-I0511 11:49:28.496733  5581 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_0
-I0511 11:49:28.496738  5581 net.cpp:542] pool6_pool6_0_split -> pool6_pool6_0_split_1
-I0511 11:49:28.496763  5581 net.cpp:260] Setting up pool6_pool6_0_split
-I0511 11:49:28.496768  5581 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.496774  5581 net.cpp:267] TEST Top shape for layer 114 'pool6_pool6_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.496779  5581 layer_factory.hpp:172] Creating layer 'pool7' of type 'Pooling'
-I0511 11:49:28.496784  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496790  5581 net.cpp:200] Created Layer pool7 (115)
-I0511 11:49:28.496794  5581 net.cpp:572] pool7 <- pool6_pool6_0_split_0
-I0511 11:49:28.496799  5581 net.cpp:542] pool7 -> pool7
-I0511 11:49:28.496832  5581 net.cpp:260] Setting up pool7
-I0511 11:49:28.496839  5581 net.cpp:267] TEST Top shape for layer 115 'pool7' 10 512 3 5 (76800)
-I0511 11:49:28.496842  5581 layer_factory.hpp:172] Creating layer 'pool7_pool7_0_split' of type 'Split'
-I0511 11:49:28.496847  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496860  5581 net.cpp:200] Created Layer pool7_pool7_0_split (116)
-I0511 11:49:28.496863  5581 net.cpp:572] pool7_pool7_0_split <- pool7
-I0511 11:49:28.496868  5581 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_0
-I0511 11:49:28.496875  5581 net.cpp:542] pool7_pool7_0_split -> pool7_pool7_0_split_1
-I0511 11:49:28.496903  5581 net.cpp:260] Setting up pool7_pool7_0_split
-I0511 11:49:28.496909  5581 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.496915  5581 net.cpp:267] TEST Top shape for layer 116 'pool7_pool7_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.496919  5581 layer_factory.hpp:172] Creating layer 'pool8' of type 'Pooling'
-I0511 11:49:28.496924  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.496930  5581 net.cpp:200] Created Layer pool8 (117)
-I0511 11:49:28.496935  5581 net.cpp:572] pool8 <- pool7_pool7_0_split_0
-I0511 11:49:28.496939  5581 net.cpp:542] pool8 -> pool8
-I0511 11:49:28.496978  5581 net.cpp:260] Setting up pool8
-I0511 11:49:28.496984  5581 net.cpp:267] TEST Top shape for layer 117 'pool8' 10 512 3 5 (76800)
-I0511 11:49:28.496989  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1' of type 'Convolution'
-I0511 11:49:28.496994  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.497009  5581 net.cpp:200] Created Layer ctx_output1/1x1 (118)
-I0511 11:49:28.497012  5581 net.cpp:572] ctx_output1/1x1 <- conv5_5/sep_relu5_5/sep_0_split_1
-I0511 11:49:28.497018  5581 net.cpp:542] ctx_output1/1x1 -> ctx_output1/1x1
-I0511 11:49:28.500376  5581 net.cpp:260] Setting up ctx_output1/1x1
-I0511 11:49:28.500396  5581 net.cpp:267] TEST Top shape for layer 118 'ctx_output1/1x1' 10 512 16 32 (2621440)
-I0511 11:49:28.500404  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.500411  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.500422  5581 net.cpp:200] Created Layer ctx_output1/1x1/bn (119)
-I0511 11:49:28.500427  5581 net.cpp:572] ctx_output1/1x1/bn <- ctx_output1/1x1
-I0511 11:49:28.500433  5581 net.cpp:527] ctx_output1/1x1/bn -> ctx_output1/1x1 (in-place)
-I0511 11:49:28.500695  5581 net.cpp:260] Setting up ctx_output1/1x1/bn
-I0511 11:49:28.500704  5581 net.cpp:267] TEST Top shape for layer 119 'ctx_output1/1x1/bn' 10 512 16 32 (2621440)
-I0511 11:49:28.500713  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/1x1/relu' of type 'ReLU'
-I0511 11:49:28.500717  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.500725  5581 net.cpp:200] Created Layer ctx_output1/1x1/relu (120)
-I0511 11:49:28.500728  5581 net.cpp:572] ctx_output1/1x1/relu <- ctx_output1/1x1
-I0511 11:49:28.500733  5581 net.cpp:527] ctx_output1/1x1/relu -> ctx_output1/1x1 (in-place)
-I0511 11:49:28.500739  5581 net.cpp:260] Setting up ctx_output1/1x1/relu
-I0511 11:49:28.500744  5581 net.cpp:267] TEST Top shape for layer 120 'ctx_output1/1x1/relu' 10 512 16 32 (2621440)
-I0511 11:49:28.500749  5581 layer_factory.hpp:172] Creating layer 'ctx_output1' of type 'Convolution'
-I0511 11:49:28.500754  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.500763  5581 net.cpp:200] Created Layer ctx_output1 (121)
-I0511 11:49:28.500767  5581 net.cpp:572] ctx_output1 <- ctx_output1/1x1
-I0511 11:49:28.500772  5581 net.cpp:542] ctx_output1 -> ctx_output1
-I0511 11:49:28.501034  5581 net.cpp:260] Setting up ctx_output1
-I0511 11:49:28.501040  5581 net.cpp:267] TEST Top shape for layer 121 'ctx_output1' 10 512 16 32 (2621440)
-I0511 11:49:28.501049  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/bn' of type 'BatchNorm'
-I0511 11:49:28.501052  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.501060  5581 net.cpp:200] Created Layer ctx_output1/bn (122)
-I0511 11:49:28.501063  5581 net.cpp:572] ctx_output1/bn <- ctx_output1
-I0511 11:49:28.501076  5581 net.cpp:527] ctx_output1/bn -> ctx_output1 (in-place)
-I0511 11:49:28.501315  5581 net.cpp:260] Setting up ctx_output1/bn
-I0511 11:49:28.501322  5581 net.cpp:267] TEST Top shape for layer 122 'ctx_output1/bn' 10 512 16 32 (2621440)
-I0511 11:49:28.501332  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu' of type 'ReLU'
-I0511 11:49:28.501336  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.501343  5581 net.cpp:200] Created Layer ctx_output1/relu (123)
-I0511 11:49:28.501346  5581 net.cpp:572] ctx_output1/relu <- ctx_output1
-I0511 11:49:28.501351  5581 net.cpp:527] ctx_output1/relu -> ctx_output1 (in-place)
-I0511 11:49:28.501358  5581 net.cpp:260] Setting up ctx_output1/relu
-I0511 11:49:28.501363  5581 net.cpp:267] TEST Top shape for layer 123 'ctx_output1/relu' 10 512 16 32 (2621440)
-I0511 11:49:28.501366  5581 layer_factory.hpp:172] Creating layer 'ctx_output1_ctx_output1/relu_0_split' of type 'Split'
-I0511 11:49:28.501371  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.501377  5581 net.cpp:200] Created Layer ctx_output1_ctx_output1/relu_0_split (124)
-I0511 11:49:28.501381  5581 net.cpp:572] ctx_output1_ctx_output1/relu_0_split <- ctx_output1
-I0511 11:49:28.501386  5581 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_0
-I0511 11:49:28.501392  5581 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_1
-I0511 11:49:28.501399  5581 net.cpp:542] ctx_output1_ctx_output1/relu_0_split -> ctx_output1_ctx_output1/relu_0_split_2
-I0511 11:49:28.501437  5581 net.cpp:260] Setting up ctx_output1_ctx_output1/relu_0_split
-I0511 11:49:28.501443  5581 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:49:28.501449  5581 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:49:28.501454  5581 net.cpp:267] TEST Top shape for layer 124 'ctx_output1_ctx_output1/relu_0_split' 10 512 16 32 (2621440)
-I0511 11:49:28.501459  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1' of type 'Convolution'
-I0511 11:49:28.501464  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.501477  5581 net.cpp:200] Created Layer ctx_output2/1x1 (125)
-I0511 11:49:28.501482  5581 net.cpp:572] ctx_output2/1x1 <- conv6/sep_relu6/sep_0_split_1
-I0511 11:49:28.501487  5581 net.cpp:542] ctx_output2/1x1 -> ctx_output2/1x1
-I0511 11:49:28.506613  5581 net.cpp:260] Setting up ctx_output2/1x1
-I0511 11:49:28.506633  5581 net.cpp:267] TEST Top shape for layer 125 'ctx_output2/1x1' 10 512 8 16 (655360)
-I0511 11:49:28.506640  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.506654  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.506664  5581 net.cpp:200] Created Layer ctx_output2/1x1/bn (126)
-I0511 11:49:28.506670  5581 net.cpp:572] ctx_output2/1x1/bn <- ctx_output2/1x1
-I0511 11:49:28.506676  5581 net.cpp:527] ctx_output2/1x1/bn -> ctx_output2/1x1 (in-place)
-I0511 11:49:28.506932  5581 net.cpp:260] Setting up ctx_output2/1x1/bn
-I0511 11:49:28.506938  5581 net.cpp:267] TEST Top shape for layer 126 'ctx_output2/1x1/bn' 10 512 8 16 (655360)
-I0511 11:49:28.506948  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/1x1/relu' of type 'ReLU'
-I0511 11:49:28.506953  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.506958  5581 net.cpp:200] Created Layer ctx_output2/1x1/relu (127)
-I0511 11:49:28.506963  5581 net.cpp:572] ctx_output2/1x1/relu <- ctx_output2/1x1
-I0511 11:49:28.506966  5581 net.cpp:527] ctx_output2/1x1/relu -> ctx_output2/1x1 (in-place)
-I0511 11:49:28.506973  5581 net.cpp:260] Setting up ctx_output2/1x1/relu
-I0511 11:49:28.506978  5581 net.cpp:267] TEST Top shape for layer 127 'ctx_output2/1x1/relu' 10 512 8 16 (655360)
-I0511 11:49:28.506991  5581 layer_factory.hpp:172] Creating layer 'ctx_output2' of type 'Convolution'
-I0511 11:49:28.506996  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507007  5581 net.cpp:200] Created Layer ctx_output2 (128)
-I0511 11:49:28.507011  5581 net.cpp:572] ctx_output2 <- ctx_output2/1x1
-I0511 11:49:28.507016  5581 net.cpp:542] ctx_output2 -> ctx_output2
-I0511 11:49:28.507282  5581 net.cpp:260] Setting up ctx_output2
-I0511 11:49:28.507288  5581 net.cpp:267] TEST Top shape for layer 128 'ctx_output2' 10 512 8 16 (655360)
-I0511 11:49:28.507297  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/bn' of type 'BatchNorm'
-I0511 11:49:28.507300  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507308  5581 net.cpp:200] Created Layer ctx_output2/bn (129)
-I0511 11:49:28.507311  5581 net.cpp:572] ctx_output2/bn <- ctx_output2
-I0511 11:49:28.507316  5581 net.cpp:527] ctx_output2/bn -> ctx_output2 (in-place)
-I0511 11:49:28.507547  5581 net.cpp:260] Setting up ctx_output2/bn
-I0511 11:49:28.507555  5581 net.cpp:267] TEST Top shape for layer 129 'ctx_output2/bn' 10 512 8 16 (655360)
-I0511 11:49:28.507565  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu' of type 'ReLU'
-I0511 11:49:28.507568  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507573  5581 net.cpp:200] Created Layer ctx_output2/relu (130)
-I0511 11:49:28.507577  5581 net.cpp:572] ctx_output2/relu <- ctx_output2
-I0511 11:49:28.507582  5581 net.cpp:527] ctx_output2/relu -> ctx_output2 (in-place)
-I0511 11:49:28.507588  5581 net.cpp:260] Setting up ctx_output2/relu
-I0511 11:49:28.507593  5581 net.cpp:267] TEST Top shape for layer 130 'ctx_output2/relu' 10 512 8 16 (655360)
-I0511 11:49:28.507598  5581 layer_factory.hpp:172] Creating layer 'ctx_output2_ctx_output2/relu_0_split' of type 'Split'
-I0511 11:49:28.507603  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507609  5581 net.cpp:200] Created Layer ctx_output2_ctx_output2/relu_0_split (131)
-I0511 11:49:28.507613  5581 net.cpp:572] ctx_output2_ctx_output2/relu_0_split <- ctx_output2
-I0511 11:49:28.507618  5581 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_0
-I0511 11:49:28.507623  5581 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_1
-I0511 11:49:28.507629  5581 net.cpp:542] ctx_output2_ctx_output2/relu_0_split -> ctx_output2_ctx_output2/relu_0_split_2
-I0511 11:49:28.507668  5581 net.cpp:260] Setting up ctx_output2_ctx_output2/relu_0_split
-I0511 11:49:28.507673  5581 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.507679  5581 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.507684  5581 net.cpp:267] TEST Top shape for layer 131 'ctx_output2_ctx_output2/relu_0_split' 10 512 8 16 (655360)
-I0511 11:49:28.507689  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1' of type 'Convolution'
-I0511 11:49:28.507694  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.507705  5581 net.cpp:200] Created Layer ctx_output3/1x1 (132)
-I0511 11:49:28.507710  5581 net.cpp:572] ctx_output3/1x1 <- pool6_pool6_0_split_1
-I0511 11:49:28.507716  5581 net.cpp:542] ctx_output3/1x1 -> ctx_output3/1x1
-I0511 11:49:28.513507  5581 net.cpp:260] Setting up ctx_output3/1x1
-I0511 11:49:28.513531  5581 net.cpp:267] TEST Top shape for layer 132 'ctx_output3/1x1' 10 512 5 9 (230400)
-I0511 11:49:28.513540  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.513566  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.513588  5581 net.cpp:200] Created Layer ctx_output3/1x1/bn (133)
-I0511 11:49:28.513608  5581 net.cpp:572] ctx_output3/1x1/bn <- ctx_output3/1x1
-I0511 11:49:28.513620  5581 net.cpp:527] ctx_output3/1x1/bn -> ctx_output3/1x1 (in-place)
-I0511 11:49:28.514001  5581 net.cpp:260] Setting up ctx_output3/1x1/bn
-I0511 11:49:28.514010  5581 net.cpp:267] TEST Top shape for layer 133 'ctx_output3/1x1/bn' 10 512 5 9 (230400)
-I0511 11:49:28.514020  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/1x1/relu' of type 'ReLU'
-I0511 11:49:28.514025  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.514031  5581 net.cpp:200] Created Layer ctx_output3/1x1/relu (134)
-I0511 11:49:28.514035  5581 net.cpp:572] ctx_output3/1x1/relu <- ctx_output3/1x1
-I0511 11:49:28.514048  5581 net.cpp:527] ctx_output3/1x1/relu -> ctx_output3/1x1 (in-place)
-I0511 11:49:28.514061  5581 net.cpp:260] Setting up ctx_output3/1x1/relu
-I0511 11:49:28.514071  5581 net.cpp:267] TEST Top shape for layer 134 'ctx_output3/1x1/relu' 10 512 5 9 (230400)
-I0511 11:49:28.514081  5581 layer_factory.hpp:172] Creating layer 'ctx_output3' of type 'Convolution'
-I0511 11:49:28.514091  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.514107  5581 net.cpp:200] Created Layer ctx_output3 (135)
-I0511 11:49:28.514117  5581 net.cpp:572] ctx_output3 <- ctx_output3/1x1
-I0511 11:49:28.514127  5581 net.cpp:542] ctx_output3 -> ctx_output3
-I0511 11:49:28.514535  5581 net.cpp:260] Setting up ctx_output3
-I0511 11:49:28.514545  5581 net.cpp:267] TEST Top shape for layer 135 'ctx_output3' 10 512 5 9 (230400)
-I0511 11:49:28.514552  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/bn' of type 'BatchNorm'
-I0511 11:49:28.514565  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.514577  5581 net.cpp:200] Created Layer ctx_output3/bn (136)
-I0511 11:49:28.514587  5581 net.cpp:572] ctx_output3/bn <- ctx_output3
-I0511 11:49:28.514597  5581 net.cpp:527] ctx_output3/bn -> ctx_output3 (in-place)
-I0511 11:49:28.514950  5581 net.cpp:260] Setting up ctx_output3/bn
-I0511 11:49:28.514957  5581 net.cpp:267] TEST Top shape for layer 136 'ctx_output3/bn' 10 512 5 9 (230400)
-I0511 11:49:28.514967  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu' of type 'ReLU'
-I0511 11:49:28.514972  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.514989  5581 net.cpp:200] Created Layer ctx_output3/relu (137)
-I0511 11:49:28.514999  5581 net.cpp:572] ctx_output3/relu <- ctx_output3
-I0511 11:49:28.515009  5581 net.cpp:527] ctx_output3/relu -> ctx_output3 (in-place)
-I0511 11:49:28.515020  5581 net.cpp:260] Setting up ctx_output3/relu
-I0511 11:49:28.515031  5581 net.cpp:267] TEST Top shape for layer 137 'ctx_output3/relu' 10 512 5 9 (230400)
-I0511 11:49:28.515041  5581 layer_factory.hpp:172] Creating layer 'ctx_output3_ctx_output3/relu_0_split' of type 'Split'
-I0511 11:49:28.515051  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.515061  5581 net.cpp:200] Created Layer ctx_output3_ctx_output3/relu_0_split (138)
-I0511 11:49:28.515071  5581 net.cpp:572] ctx_output3_ctx_output3/relu_0_split <- ctx_output3
-I0511 11:49:28.515081  5581 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_0
-I0511 11:49:28.515092  5581 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_1
-I0511 11:49:28.515102  5581 net.cpp:542] ctx_output3_ctx_output3/relu_0_split -> ctx_output3_ctx_output3/relu_0_split_2
-I0511 11:49:28.515156  5581 net.cpp:260] Setting up ctx_output3_ctx_output3/relu_0_split
-I0511 11:49:28.515163  5581 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.515169  5581 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.515184  5581 net.cpp:267] TEST Top shape for layer 138 'ctx_output3_ctx_output3/relu_0_split' 10 512 5 9 (230400)
-I0511 11:49:28.515199  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1' of type 'Convolution'
-I0511 11:49:28.515209  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.515228  5581 net.cpp:200] Created Layer ctx_output4/1x1 (139)
-I0511 11:49:28.515239  5581 net.cpp:572] ctx_output4/1x1 <- pool7_pool7_0_split_1
-I0511 11:49:28.515249  5581 net.cpp:542] ctx_output4/1x1 -> ctx_output4/1x1
-I0511 11:49:28.523124  5581 net.cpp:260] Setting up ctx_output4/1x1
-I0511 11:49:28.523154  5581 net.cpp:267] TEST Top shape for layer 139 'ctx_output4/1x1' 10 512 3 5 (76800)
-I0511 11:49:28.523164  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.523170  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.523181  5581 net.cpp:200] Created Layer ctx_output4/1x1/bn (140)
-I0511 11:49:28.523187  5581 net.cpp:572] ctx_output4/1x1/bn <- ctx_output4/1x1
-I0511 11:49:28.523193  5581 net.cpp:527] ctx_output4/1x1/bn -> ctx_output4/1x1 (in-place)
-I0511 11:49:28.523564  5581 net.cpp:260] Setting up ctx_output4/1x1/bn
-I0511 11:49:28.523573  5581 net.cpp:267] TEST Top shape for layer 140 'ctx_output4/1x1/bn' 10 512 3 5 (76800)
-I0511 11:49:28.523582  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/1x1/relu' of type 'ReLU'
-I0511 11:49:28.523587  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.523592  5581 net.cpp:200] Created Layer ctx_output4/1x1/relu (141)
-I0511 11:49:28.523597  5581 net.cpp:572] ctx_output4/1x1/relu <- ctx_output4/1x1
-I0511 11:49:28.523600  5581 net.cpp:527] ctx_output4/1x1/relu -> ctx_output4/1x1 (in-place)
-I0511 11:49:28.523605  5581 net.cpp:260] Setting up ctx_output4/1x1/relu
-I0511 11:49:28.523617  5581 net.cpp:267] TEST Top shape for layer 141 'ctx_output4/1x1/relu' 10 512 3 5 (76800)
-I0511 11:49:28.523635  5581 layer_factory.hpp:172] Creating layer 'ctx_output4' of type 'Convolution'
-I0511 11:49:28.523646  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.523663  5581 net.cpp:200] Created Layer ctx_output4 (142)
-I0511 11:49:28.523672  5581 net.cpp:572] ctx_output4 <- ctx_output4/1x1
-I0511 11:49:28.523682  5581 net.cpp:542] ctx_output4 -> ctx_output4
-I0511 11:49:28.524089  5581 net.cpp:260] Setting up ctx_output4
-I0511 11:49:28.524098  5581 net.cpp:267] TEST Top shape for layer 142 'ctx_output4' 10 512 3 5 (76800)
-I0511 11:49:28.524106  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/bn' of type 'BatchNorm'
-I0511 11:49:28.524109  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.524116  5581 net.cpp:200] Created Layer ctx_output4/bn (143)
-I0511 11:49:28.524121  5581 net.cpp:572] ctx_output4/bn <- ctx_output4
-I0511 11:49:28.524125  5581 net.cpp:527] ctx_output4/bn -> ctx_output4 (in-place)
-I0511 11:49:28.524469  5581 net.cpp:260] Setting up ctx_output4/bn
-I0511 11:49:28.524477  5581 net.cpp:267] TEST Top shape for layer 143 'ctx_output4/bn' 10 512 3 5 (76800)
-I0511 11:49:28.524487  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu' of type 'ReLU'
-I0511 11:49:28.524492  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.524508  5581 net.cpp:200] Created Layer ctx_output4/relu (144)
-I0511 11:49:28.524519  5581 net.cpp:572] ctx_output4/relu <- ctx_output4
-I0511 11:49:28.524538  5581 net.cpp:527] ctx_output4/relu -> ctx_output4 (in-place)
-I0511 11:49:28.524552  5581 net.cpp:260] Setting up ctx_output4/relu
-I0511 11:49:28.524565  5581 net.cpp:267] TEST Top shape for layer 144 'ctx_output4/relu' 10 512 3 5 (76800)
-I0511 11:49:28.524577  5581 layer_factory.hpp:172] Creating layer 'ctx_output4_ctx_output4/relu_0_split' of type 'Split'
-I0511 11:49:28.524590  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.524610  5581 net.cpp:200] Created Layer ctx_output4_ctx_output4/relu_0_split (145)
-I0511 11:49:28.524616  5581 net.cpp:572] ctx_output4_ctx_output4/relu_0_split <- ctx_output4
-I0511 11:49:28.524621  5581 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_0
-I0511 11:49:28.524628  5581 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_1
-I0511 11:49:28.524634  5581 net.cpp:542] ctx_output4_ctx_output4/relu_0_split -> ctx_output4_ctx_output4/relu_0_split_2
-I0511 11:49:28.524685  5581 net.cpp:260] Setting up ctx_output4_ctx_output4/relu_0_split
-I0511 11:49:28.524694  5581 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.524701  5581 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.524716  5581 net.cpp:267] TEST Top shape for layer 145 'ctx_output4_ctx_output4/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.524729  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1' of type 'Convolution'
-I0511 11:49:28.524740  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.524761  5581 net.cpp:200] Created Layer ctx_output5/1x1 (146)
-I0511 11:49:28.524773  5581 net.cpp:572] ctx_output5/1x1 <- pool8
-I0511 11:49:28.524785  5581 net.cpp:542] ctx_output5/1x1 -> ctx_output5/1x1
-I0511 11:49:28.533604  5581 net.cpp:260] Setting up ctx_output5/1x1
-I0511 11:49:28.533640  5581 net.cpp:267] TEST Top shape for layer 146 'ctx_output5/1x1' 10 512 3 5 (76800)
-I0511 11:49:28.533653  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/bn' of type 'BatchNorm'
-I0511 11:49:28.533661  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.533675  5581 net.cpp:200] Created Layer ctx_output5/1x1/bn (147)
-I0511 11:49:28.533682  5581 net.cpp:572] ctx_output5/1x1/bn <- ctx_output5/1x1
-I0511 11:49:28.533689  5581 net.cpp:527] ctx_output5/1x1/bn -> ctx_output5/1x1 (in-place)
-I0511 11:49:28.534118  5581 net.cpp:260] Setting up ctx_output5/1x1/bn
-I0511 11:49:28.534127  5581 net.cpp:267] TEST Top shape for layer 147 'ctx_output5/1x1/bn' 10 512 3 5 (76800)
-I0511 11:49:28.534138  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/1x1/relu' of type 'ReLU'
-I0511 11:49:28.534144  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.534152  5581 net.cpp:200] Created Layer ctx_output5/1x1/relu (148)
-I0511 11:49:28.534171  5581 net.cpp:572] ctx_output5/1x1/relu <- ctx_output5/1x1
-I0511 11:49:28.534184  5581 net.cpp:527] ctx_output5/1x1/relu -> ctx_output5/1x1 (in-place)
-I0511 11:49:28.534205  5581 net.cpp:260] Setting up ctx_output5/1x1/relu
-I0511 11:49:28.534217  5581 net.cpp:267] TEST Top shape for layer 148 'ctx_output5/1x1/relu' 10 512 3 5 (76800)
-I0511 11:49:28.534229  5581 layer_factory.hpp:172] Creating layer 'ctx_output5' of type 'Convolution'
-I0511 11:49:28.534240  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.534258  5581 net.cpp:200] Created Layer ctx_output5 (149)
-I0511 11:49:28.534268  5581 net.cpp:572] ctx_output5 <- ctx_output5/1x1
-I0511 11:49:28.534279  5581 net.cpp:542] ctx_output5 -> ctx_output5
-I0511 11:49:28.534817  5581 net.cpp:260] Setting up ctx_output5
-I0511 11:49:28.534828  5581 net.cpp:267] TEST Top shape for layer 149 'ctx_output5' 10 512 3 5 (76800)
-I0511 11:49:28.534837  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/bn' of type 'BatchNorm'
-I0511 11:49:28.534842  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.534858  5581 net.cpp:200] Created Layer ctx_output5/bn (150)
-I0511 11:49:28.534869  5581 net.cpp:572] ctx_output5/bn <- ctx_output5
-I0511 11:49:28.534880  5581 net.cpp:527] ctx_output5/bn -> ctx_output5 (in-place)
-I0511 11:49:28.535284  5581 net.cpp:260] Setting up ctx_output5/bn
-I0511 11:49:28.535295  5581 net.cpp:267] TEST Top shape for layer 150 'ctx_output5/bn' 10 512 3 5 (76800)
-I0511 11:49:28.535315  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu' of type 'ReLU'
-I0511 11:49:28.535320  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.535334  5581 net.cpp:200] Created Layer ctx_output5/relu (151)
-I0511 11:49:28.535346  5581 net.cpp:572] ctx_output5/relu <- ctx_output5
-I0511 11:49:28.535357  5581 net.cpp:527] ctx_output5/relu -> ctx_output5 (in-place)
-I0511 11:49:28.535370  5581 net.cpp:260] Setting up ctx_output5/relu
-I0511 11:49:28.535382  5581 net.cpp:267] TEST Top shape for layer 151 'ctx_output5/relu' 10 512 3 5 (76800)
-I0511 11:49:28.535392  5581 layer_factory.hpp:172] Creating layer 'ctx_output5_ctx_output5/relu_0_split' of type 'Split'
-I0511 11:49:28.535403  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.535420  5581 net.cpp:200] Created Layer ctx_output5_ctx_output5/relu_0_split (152)
-I0511 11:49:28.535431  5581 net.cpp:572] ctx_output5_ctx_output5/relu_0_split <- ctx_output5
-I0511 11:49:28.535442  5581 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_0
-I0511 11:49:28.535454  5581 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_1
-I0511 11:49:28.535466  5581 net.cpp:542] ctx_output5_ctx_output5/relu_0_split -> ctx_output5_ctx_output5/relu_0_split_2
-I0511 11:49:28.535522  5581 net.cpp:260] Setting up ctx_output5_ctx_output5/relu_0_split
-I0511 11:49:28.535531  5581 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.535537  5581 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.535549  5581 net.cpp:267] TEST Top shape for layer 152 'ctx_output5_ctx_output5/relu_0_split' 10 512 3 5 (76800)
-I0511 11:49:28.535560  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.535570  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.535585  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc (153)
-I0511 11:49:28.535598  5581 net.cpp:572] ctx_output1/relu_mbox_loc <- ctx_output1_ctx_output1/relu_0_split_0
-I0511 11:49:28.535609  5581 net.cpp:542] ctx_output1/relu_mbox_loc -> ctx_output1/relu_mbox_loc
-I0511 11:49:28.536129  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_loc
-I0511 11:49:28.536139  5581 net.cpp:267] TEST Top shape for layer 153 'ctx_output1/relu_mbox_loc' 10 16 16 32 (81920)
-I0511 11:49:28.536147  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.536154  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.536178  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_perm (154)
-I0511 11:49:28.536190  5581 net.cpp:572] ctx_output1/relu_mbox_loc_perm <- ctx_output1/relu_mbox_loc
-I0511 11:49:28.536201  5581 net.cpp:542] ctx_output1/relu_mbox_loc_perm -> ctx_output1/relu_mbox_loc_perm
-I0511 11:49:28.536312  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_perm
-I0511 11:49:28.536321  5581 net.cpp:267] TEST Top shape for layer 154 'ctx_output1/relu_mbox_loc_perm' 10 16 32 16 (81920)
-I0511 11:49:28.536334  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.536345  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.536358  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_loc_flat (155)
-I0511 11:49:28.536370  5581 net.cpp:572] ctx_output1/relu_mbox_loc_flat <- ctx_output1/relu_mbox_loc_perm
-I0511 11:49:28.536381  5581 net.cpp:542] ctx_output1/relu_mbox_loc_flat -> ctx_output1/relu_mbox_loc_flat
-I0511 11:49:28.536516  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_loc_flat
-I0511 11:49:28.536536  5581 net.cpp:267] TEST Top shape for layer 155 'ctx_output1/relu_mbox_loc_flat' 10 8192 (81920)
-I0511 11:49:28.536554  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.536567  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.536584  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf (156)
-I0511 11:49:28.536595  5581 net.cpp:572] ctx_output1/relu_mbox_conf <- ctx_output1_ctx_output1/relu_0_split_1
-I0511 11:49:28.536607  5581 net.cpp:542] ctx_output1/relu_mbox_conf -> ctx_output1/relu_mbox_conf
-I0511 11:49:28.538188  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_conf
-I0511 11:49:28.538213  5581 net.cpp:267] TEST Top shape for layer 156 'ctx_output1/relu_mbox_conf' 10 84 16 32 (430080)
-I0511 11:49:28.538221  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.538239  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.538259  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_perm (157)
-I0511 11:49:28.538271  5581 net.cpp:572] ctx_output1/relu_mbox_conf_perm <- ctx_output1/relu_mbox_conf
-I0511 11:49:28.538283  5581 net.cpp:542] ctx_output1/relu_mbox_conf_perm -> ctx_output1/relu_mbox_conf_perm
-I0511 11:49:28.538386  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_perm
-I0511 11:49:28.538395  5581 net.cpp:267] TEST Top shape for layer 157 'ctx_output1/relu_mbox_conf_perm' 10 16 32 84 (430080)
-I0511 11:49:28.538408  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.538419  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.538430  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_conf_flat (158)
-I0511 11:49:28.538441  5581 net.cpp:572] ctx_output1/relu_mbox_conf_flat <- ctx_output1/relu_mbox_conf_perm
-I0511 11:49:28.538452  5581 net.cpp:542] ctx_output1/relu_mbox_conf_flat -> ctx_output1/relu_mbox_conf_flat
-I0511 11:49:28.541393  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_conf_flat
-I0511 11:49:28.541440  5581 net.cpp:267] TEST Top shape for layer 158 'ctx_output1/relu_mbox_conf_flat' 10 43008 (430080)
-I0511 11:49:28.541450  5581 layer_factory.hpp:172] Creating layer 'ctx_output1/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.541458  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.541483  5581 net.cpp:200] Created Layer ctx_output1/relu_mbox_priorbox (159)
-I0511 11:49:28.541492  5581 net.cpp:572] ctx_output1/relu_mbox_priorbox <- ctx_output1_ctx_output1/relu_0_split_2
-I0511 11:49:28.541508  5581 net.cpp:572] ctx_output1/relu_mbox_priorbox <- data_data_0_split_1
-I0511 11:49:28.541517  5581 net.cpp:542] ctx_output1/relu_mbox_priorbox -> ctx_output1/relu_mbox_priorbox
-I0511 11:49:28.541589  5581 net.cpp:260] Setting up ctx_output1/relu_mbox_priorbox
-I0511 11:49:28.541599  5581 net.cpp:267] TEST Top shape for layer 159 'ctx_output1/relu_mbox_priorbox' 1 2 8192 (16384)
-I0511 11:49:28.541610  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.541615  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.541645  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc (160)
-I0511 11:49:28.541651  5581 net.cpp:572] ctx_output2/relu_mbox_loc <- ctx_output2_ctx_output2/relu_0_split_0
-I0511 11:49:28.541656  5581 net.cpp:542] ctx_output2/relu_mbox_loc -> ctx_output2/relu_mbox_loc
-I0511 11:49:28.542155  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_loc
-I0511 11:49:28.542165  5581 net.cpp:267] TEST Top shape for layer 160 'ctx_output2/relu_mbox_loc' 10 24 8 16 (30720)
-I0511 11:49:28.542181  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.542186  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.542207  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_perm (161)
-I0511 11:49:28.542212  5581 net.cpp:572] ctx_output2/relu_mbox_loc_perm <- ctx_output2/relu_mbox_loc
-I0511 11:49:28.542218  5581 net.cpp:542] ctx_output2/relu_mbox_loc_perm -> ctx_output2/relu_mbox_loc_perm
-I0511 11:49:28.542297  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_perm
-I0511 11:49:28.542305  5581 net.cpp:267] TEST Top shape for layer 161 'ctx_output2/relu_mbox_loc_perm' 10 8 16 24 (30720)
-I0511 11:49:28.542315  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.542321  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.542332  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_loc_flat (162)
-I0511 11:49:28.542337  5581 net.cpp:572] ctx_output2/relu_mbox_loc_flat <- ctx_output2/relu_mbox_loc_perm
-I0511 11:49:28.542346  5581 net.cpp:542] ctx_output2/relu_mbox_loc_flat -> ctx_output2/relu_mbox_loc_flat
-I0511 11:49:28.542423  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_loc_flat
-I0511 11:49:28.542430  5581 net.cpp:267] TEST Top shape for layer 162 'ctx_output2/relu_mbox_loc_flat' 10 3072 (30720)
-I0511 11:49:28.542440  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.542445  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.542459  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf (163)
-I0511 11:49:28.542464  5581 net.cpp:572] ctx_output2/relu_mbox_conf <- ctx_output2_ctx_output2/relu_0_split_1
-I0511 11:49:28.542474  5581 net.cpp:542] ctx_output2/relu_mbox_conf -> ctx_output2/relu_mbox_conf
-I0511 11:49:28.543903  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_conf
-I0511 11:49:28.543917  5581 net.cpp:267] TEST Top shape for layer 163 'ctx_output2/relu_mbox_conf' 10 126 8 16 (161280)
-I0511 11:49:28.543934  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.543941  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.543952  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_perm (164)
-I0511 11:49:28.543958  5581 net.cpp:572] ctx_output2/relu_mbox_conf_perm <- ctx_output2/relu_mbox_conf
-I0511 11:49:28.543968  5581 net.cpp:542] ctx_output2/relu_mbox_conf_perm -> ctx_output2/relu_mbox_conf_perm
-I0511 11:49:28.544045  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_perm
-I0511 11:49:28.544052  5581 net.cpp:267] TEST Top shape for layer 164 'ctx_output2/relu_mbox_conf_perm' 10 8 16 126 (161280)
-I0511 11:49:28.544062  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.544067  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.544078  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_conf_flat (165)
-I0511 11:49:28.544085  5581 net.cpp:572] ctx_output2/relu_mbox_conf_flat <- ctx_output2/relu_mbox_conf_perm
-I0511 11:49:28.544095  5581 net.cpp:542] ctx_output2/relu_mbox_conf_flat -> ctx_output2/relu_mbox_conf_flat
-I0511 11:49:28.545334  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_conf_flat
-I0511 11:49:28.545356  5581 net.cpp:267] TEST Top shape for layer 165 'ctx_output2/relu_mbox_conf_flat' 10 16128 (161280)
-I0511 11:49:28.545362  5581 layer_factory.hpp:172] Creating layer 'ctx_output2/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.545377  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.545393  5581 net.cpp:200] Created Layer ctx_output2/relu_mbox_priorbox (166)
-I0511 11:49:28.545399  5581 net.cpp:572] ctx_output2/relu_mbox_priorbox <- ctx_output2_ctx_output2/relu_0_split_2
-I0511 11:49:28.545411  5581 net.cpp:572] ctx_output2/relu_mbox_priorbox <- data_data_0_split_2
-I0511 11:49:28.545418  5581 net.cpp:542] ctx_output2/relu_mbox_priorbox -> ctx_output2/relu_mbox_priorbox
-I0511 11:49:28.545473  5581 net.cpp:260] Setting up ctx_output2/relu_mbox_priorbox
-I0511 11:49:28.545481  5581 net.cpp:267] TEST Top shape for layer 166 'ctx_output2/relu_mbox_priorbox' 1 2 3072 (6144)
-I0511 11:49:28.545492  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.545497  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.545521  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc (167)
-I0511 11:49:28.545527  5581 net.cpp:572] ctx_output3/relu_mbox_loc <- ctx_output3_ctx_output3/relu_0_split_0
-I0511 11:49:28.545537  5581 net.cpp:542] ctx_output3/relu_mbox_loc -> ctx_output3/relu_mbox_loc
-I0511 11:49:28.546008  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_loc
-I0511 11:49:28.546016  5581 net.cpp:267] TEST Top shape for layer 167 'ctx_output3/relu_mbox_loc' 10 24 5 9 (10800)
-I0511 11:49:28.546030  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.546036  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.546047  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_perm (168)
-I0511 11:49:28.546052  5581 net.cpp:572] ctx_output3/relu_mbox_loc_perm <- ctx_output3/relu_mbox_loc
-I0511 11:49:28.546061  5581 net.cpp:542] ctx_output3/relu_mbox_loc_perm -> ctx_output3/relu_mbox_loc_perm
-I0511 11:49:28.546142  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_perm
-I0511 11:49:28.546149  5581 net.cpp:267] TEST Top shape for layer 168 'ctx_output3/relu_mbox_loc_perm' 10 5 9 24 (10800)
-I0511 11:49:28.546159  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.546164  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.546176  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_loc_flat (169)
-I0511 11:49:28.546180  5581 net.cpp:572] ctx_output3/relu_mbox_loc_flat <- ctx_output3/relu_mbox_loc_perm
-I0511 11:49:28.546190  5581 net.cpp:542] ctx_output3/relu_mbox_loc_flat -> ctx_output3/relu_mbox_loc_flat
-I0511 11:49:28.546272  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_loc_flat
-I0511 11:49:28.546278  5581 net.cpp:267] TEST Top shape for layer 169 'ctx_output3/relu_mbox_loc_flat' 10 1080 (10800)
-I0511 11:49:28.546288  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.546293  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.546313  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf (170)
-I0511 11:49:28.546319  5581 net.cpp:572] ctx_output3/relu_mbox_conf <- ctx_output3_ctx_output3/relu_0_split_1
-I0511 11:49:28.546329  5581 net.cpp:542] ctx_output3/relu_mbox_conf -> ctx_output3/relu_mbox_conf
-I0511 11:49:28.547796  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_conf
-I0511 11:49:28.547819  5581 net.cpp:267] TEST Top shape for layer 170 'ctx_output3/relu_mbox_conf' 10 126 5 9 (56700)
-I0511 11:49:28.547828  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.547842  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.547854  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_perm (171)
-I0511 11:49:28.547860  5581 net.cpp:572] ctx_output3/relu_mbox_conf_perm <- ctx_output3/relu_mbox_conf
-I0511 11:49:28.547873  5581 net.cpp:542] ctx_output3/relu_mbox_conf_perm -> ctx_output3/relu_mbox_conf_perm
-I0511 11:49:28.547966  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_perm
-I0511 11:49:28.547972  5581 net.cpp:267] TEST Top shape for layer 171 'ctx_output3/relu_mbox_conf_perm' 10 5 9 126 (56700)
-I0511 11:49:28.547984  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.547989  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548012  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_conf_flat (172)
-I0511 11:49:28.548018  5581 net.cpp:572] ctx_output3/relu_mbox_conf_flat <- ctx_output3/relu_mbox_conf_perm
-I0511 11:49:28.548029  5581 net.cpp:542] ctx_output3/relu_mbox_conf_flat -> ctx_output3/relu_mbox_conf_flat
-I0511 11:49:28.548180  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_conf_flat
-I0511 11:49:28.548187  5581 net.cpp:267] TEST Top shape for layer 172 'ctx_output3/relu_mbox_conf_flat' 10 5670 (56700)
-I0511 11:49:28.548197  5581 layer_factory.hpp:172] Creating layer 'ctx_output3/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.548203  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548215  5581 net.cpp:200] Created Layer ctx_output3/relu_mbox_priorbox (173)
-I0511 11:49:28.548219  5581 net.cpp:572] ctx_output3/relu_mbox_priorbox <- ctx_output3_ctx_output3/relu_0_split_2
-I0511 11:49:28.548230  5581 net.cpp:572] ctx_output3/relu_mbox_priorbox <- data_data_0_split_3
-I0511 11:49:28.548238  5581 net.cpp:542] ctx_output3/relu_mbox_priorbox -> ctx_output3/relu_mbox_priorbox
-I0511 11:49:28.548266  5581 net.cpp:260] Setting up ctx_output3/relu_mbox_priorbox
-I0511 11:49:28.548272  5581 net.cpp:267] TEST Top shape for layer 173 'ctx_output3/relu_mbox_priorbox' 1 2 1080 (2160)
-I0511 11:49:28.548282  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.548288  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548312  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc (174)
-I0511 11:49:28.548317  5581 net.cpp:572] ctx_output4/relu_mbox_loc <- ctx_output4_ctx_output4/relu_0_split_0
-I0511 11:49:28.548328  5581 net.cpp:542] ctx_output4/relu_mbox_loc -> ctx_output4/relu_mbox_loc
-I0511 11:49:28.548722  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_loc
-I0511 11:49:28.548732  5581 net.cpp:267] TEST Top shape for layer 174 'ctx_output4/relu_mbox_loc' 10 16 3 5 (2400)
-I0511 11:49:28.548738  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.548750  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548758  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_perm (175)
-I0511 11:49:28.548764  5581 net.cpp:572] ctx_output4/relu_mbox_loc_perm <- ctx_output4/relu_mbox_loc
-I0511 11:49:28.548774  5581 net.cpp:542] ctx_output4/relu_mbox_loc_perm -> ctx_output4/relu_mbox_loc_perm
-I0511 11:49:28.548852  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_perm
-I0511 11:49:28.548859  5581 net.cpp:267] TEST Top shape for layer 175 'ctx_output4/relu_mbox_loc_perm' 10 3 5 16 (2400)
-I0511 11:49:28.548869  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.548876  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548880  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_loc_flat (176)
-I0511 11:49:28.548890  5581 net.cpp:572] ctx_output4/relu_mbox_loc_flat <- ctx_output4/relu_mbox_loc_perm
-I0511 11:49:28.548895  5581 net.cpp:542] ctx_output4/relu_mbox_loc_flat -> ctx_output4/relu_mbox_loc_flat
-I0511 11:49:28.548956  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_loc_flat
-I0511 11:49:28.548964  5581 net.cpp:267] TEST Top shape for layer 176 'ctx_output4/relu_mbox_loc_flat' 10 240 (2400)
-I0511 11:49:28.548974  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.548979  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.548992  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf (177)
-I0511 11:49:28.548997  5581 net.cpp:572] ctx_output4/relu_mbox_conf <- ctx_output4_ctx_output4/relu_0_split_1
-I0511 11:49:28.549010  5581 net.cpp:542] ctx_output4/relu_mbox_conf -> ctx_output4/relu_mbox_conf
-I0511 11:49:28.550056  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_conf
-I0511 11:49:28.550068  5581 net.cpp:267] TEST Top shape for layer 177 'ctx_output4/relu_mbox_conf' 10 84 3 5 (12600)
-I0511 11:49:28.550076  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.550089  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550099  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_perm (178)
-I0511 11:49:28.550106  5581 net.cpp:572] ctx_output4/relu_mbox_conf_perm <- ctx_output4/relu_mbox_conf
-I0511 11:49:28.550117  5581 net.cpp:542] ctx_output4/relu_mbox_conf_perm -> ctx_output4/relu_mbox_conf_perm
-I0511 11:49:28.550205  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_perm
-I0511 11:49:28.550212  5581 net.cpp:267] TEST Top shape for layer 178 'ctx_output4/relu_mbox_conf_perm' 10 3 5 84 (12600)
-I0511 11:49:28.550222  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.550227  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550237  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_conf_flat (179)
-I0511 11:49:28.550242  5581 net.cpp:572] ctx_output4/relu_mbox_conf_flat <- ctx_output4/relu_mbox_conf_perm
-I0511 11:49:28.550252  5581 net.cpp:542] ctx_output4/relu_mbox_conf_flat -> ctx_output4/relu_mbox_conf_flat
-I0511 11:49:28.550349  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_conf_flat
-I0511 11:49:28.550356  5581 net.cpp:267] TEST Top shape for layer 179 'ctx_output4/relu_mbox_conf_flat' 10 1260 (12600)
-I0511 11:49:28.550367  5581 layer_factory.hpp:172] Creating layer 'ctx_output4/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.550372  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550384  5581 net.cpp:200] Created Layer ctx_output4/relu_mbox_priorbox (180)
-I0511 11:49:28.550388  5581 net.cpp:572] ctx_output4/relu_mbox_priorbox <- ctx_output4_ctx_output4/relu_0_split_2
-I0511 11:49:28.550400  5581 net.cpp:572] ctx_output4/relu_mbox_priorbox <- data_data_0_split_4
-I0511 11:49:28.550405  5581 net.cpp:542] ctx_output4/relu_mbox_priorbox -> ctx_output4/relu_mbox_priorbox
-I0511 11:49:28.550434  5581 net.cpp:260] Setting up ctx_output4/relu_mbox_priorbox
-I0511 11:49:28.550441  5581 net.cpp:267] TEST Top shape for layer 180 'ctx_output4/relu_mbox_priorbox' 1 2 240 (480)
-I0511 11:49:28.550451  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc' of type 'Convolution'
-I0511 11:49:28.550456  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550469  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc (181)
-I0511 11:49:28.550474  5581 net.cpp:572] ctx_output5/relu_mbox_loc <- ctx_output5_ctx_output5/relu_0_split_0
-I0511 11:49:28.550484  5581 net.cpp:542] ctx_output5/relu_mbox_loc -> ctx_output5/relu_mbox_loc
-I0511 11:49:28.550839  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_loc
-I0511 11:49:28.550848  5581 net.cpp:267] TEST Top shape for layer 181 'ctx_output5/relu_mbox_loc' 10 16 3 5 (2400)
-I0511 11:49:28.550860  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_perm' of type 'Permute'
-I0511 11:49:28.550865  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.550876  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_perm (182)
-I0511 11:49:28.550881  5581 net.cpp:572] ctx_output5/relu_mbox_loc_perm <- ctx_output5/relu_mbox_loc
-I0511 11:49:28.550891  5581 net.cpp:542] ctx_output5/relu_mbox_loc_perm -> ctx_output5/relu_mbox_loc_perm
-I0511 11:49:28.550966  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_perm
-I0511 11:49:28.550972  5581 net.cpp:267] TEST Top shape for layer 182 'ctx_output5/relu_mbox_loc_perm' 10 3 5 16 (2400)
-I0511 11:49:28.550987  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_loc_flat' of type 'Flatten'
-I0511 11:49:28.550997  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.551007  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_loc_flat (183)
-I0511 11:49:28.551012  5581 net.cpp:572] ctx_output5/relu_mbox_loc_flat <- ctx_output5/relu_mbox_loc_perm
-I0511 11:49:28.551020  5581 net.cpp:542] ctx_output5/relu_mbox_loc_flat -> ctx_output5/relu_mbox_loc_flat
-I0511 11:49:28.551079  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_loc_flat
-I0511 11:49:28.551085  5581 net.cpp:267] TEST Top shape for layer 183 'ctx_output5/relu_mbox_loc_flat' 10 240 (2400)
-I0511 11:49:28.551095  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf' of type 'Convolution'
-I0511 11:49:28.551100  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.551118  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf (184)
-I0511 11:49:28.551123  5581 net.cpp:572] ctx_output5/relu_mbox_conf <- ctx_output5_ctx_output5/relu_0_split_1
-I0511 11:49:28.551133  5581 net.cpp:542] ctx_output5/relu_mbox_conf -> ctx_output5/relu_mbox_conf
-I0511 11:49:28.552150  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_conf
-I0511 11:49:28.552160  5581 net.cpp:267] TEST Top shape for layer 184 'ctx_output5/relu_mbox_conf' 10 84 3 5 (12600)
-I0511 11:49:28.552175  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_perm' of type 'Permute'
-I0511 11:49:28.552181  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552191  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_perm (185)
-I0511 11:49:28.552196  5581 net.cpp:572] ctx_output5/relu_mbox_conf_perm <- ctx_output5/relu_mbox_conf
-I0511 11:49:28.552206  5581 net.cpp:542] ctx_output5/relu_mbox_conf_perm -> ctx_output5/relu_mbox_conf_perm
-I0511 11:49:28.552289  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_perm
-I0511 11:49:28.552295  5581 net.cpp:267] TEST Top shape for layer 185 'ctx_output5/relu_mbox_conf_perm' 10 3 5 84 (12600)
-I0511 11:49:28.552305  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_conf_flat' of type 'Flatten'
-I0511 11:49:28.552310  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552321  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_conf_flat (186)
-I0511 11:49:28.552325  5581 net.cpp:572] ctx_output5/relu_mbox_conf_flat <- ctx_output5/relu_mbox_conf_perm
-I0511 11:49:28.552335  5581 net.cpp:542] ctx_output5/relu_mbox_conf_flat -> ctx_output5/relu_mbox_conf_flat
-I0511 11:49:28.552394  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_conf_flat
-I0511 11:49:28.552400  5581 net.cpp:267] TEST Top shape for layer 186 'ctx_output5/relu_mbox_conf_flat' 10 1260 (12600)
-I0511 11:49:28.552410  5581 layer_factory.hpp:172] Creating layer 'ctx_output5/relu_mbox_priorbox' of type 'PriorBox'
-I0511 11:49:28.552422  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552433  5581 net.cpp:200] Created Layer ctx_output5/relu_mbox_priorbox (187)
-I0511 11:49:28.552438  5581 net.cpp:572] ctx_output5/relu_mbox_priorbox <- ctx_output5_ctx_output5/relu_0_split_2
-I0511 11:49:28.552448  5581 net.cpp:572] ctx_output5/relu_mbox_priorbox <- data_data_0_split_5
-I0511 11:49:28.552453  5581 net.cpp:542] ctx_output5/relu_mbox_priorbox -> ctx_output5/relu_mbox_priorbox
-I0511 11:49:28.552481  5581 net.cpp:260] Setting up ctx_output5/relu_mbox_priorbox
-I0511 11:49:28.552489  5581 net.cpp:267] TEST Top shape for layer 187 'ctx_output5/relu_mbox_priorbox' 1 2 240 (480)
-I0511 11:49:28.552498  5581 layer_factory.hpp:172] Creating layer 'mbox_loc' of type 'Concat'
-I0511 11:49:28.552502  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552515  5581 net.cpp:200] Created Layer mbox_loc (188)
-I0511 11:49:28.552520  5581 net.cpp:572] mbox_loc <- ctx_output1/relu_mbox_loc_flat
-I0511 11:49:28.552533  5581 net.cpp:572] mbox_loc <- ctx_output2/relu_mbox_loc_flat
-I0511 11:49:28.552552  5581 net.cpp:572] mbox_loc <- ctx_output3/relu_mbox_loc_flat
-I0511 11:49:28.552557  5581 net.cpp:572] mbox_loc <- ctx_output4/relu_mbox_loc_flat
-I0511 11:49:28.552562  5581 net.cpp:572] mbox_loc <- ctx_output5/relu_mbox_loc_flat
-I0511 11:49:28.552568  5581 net.cpp:542] mbox_loc -> mbox_loc
-I0511 11:49:28.552592  5581 net.cpp:260] Setting up mbox_loc
-I0511 11:49:28.552598  5581 net.cpp:267] TEST Top shape for layer 188 'mbox_loc' 10 12824 (128240)
-I0511 11:49:28.552603  5581 layer_factory.hpp:172] Creating layer 'mbox_conf' of type 'Concat'
-I0511 11:49:28.552608  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552614  5581 net.cpp:200] Created Layer mbox_conf (189)
-I0511 11:49:28.552618  5581 net.cpp:572] mbox_conf <- ctx_output1/relu_mbox_conf_flat
-I0511 11:49:28.552624  5581 net.cpp:572] mbox_conf <- ctx_output2/relu_mbox_conf_flat
-I0511 11:49:28.552630  5581 net.cpp:572] mbox_conf <- ctx_output3/relu_mbox_conf_flat
-I0511 11:49:28.552635  5581 net.cpp:572] mbox_conf <- ctx_output4/relu_mbox_conf_flat
-I0511 11:49:28.552640  5581 net.cpp:572] mbox_conf <- ctx_output5/relu_mbox_conf_flat
-I0511 11:49:28.552645  5581 net.cpp:542] mbox_conf -> mbox_conf
-I0511 11:49:28.552670  5581 net.cpp:260] Setting up mbox_conf
-I0511 11:49:28.552676  5581 net.cpp:267] TEST Top shape for layer 189 'mbox_conf' 10 67326 (673260)
-I0511 11:49:28.552681  5581 layer_factory.hpp:172] Creating layer 'mbox_priorbox' of type 'Concat'
-I0511 11:49:28.552685  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552691  5581 net.cpp:200] Created Layer mbox_priorbox (190)
-I0511 11:49:28.552695  5581 net.cpp:572] mbox_priorbox <- ctx_output1/relu_mbox_priorbox
-I0511 11:49:28.552700  5581 net.cpp:572] mbox_priorbox <- ctx_output2/relu_mbox_priorbox
-I0511 11:49:28.552706  5581 net.cpp:572] mbox_priorbox <- ctx_output3/relu_mbox_priorbox
-I0511 11:49:28.552711  5581 net.cpp:572] mbox_priorbox <- ctx_output4/relu_mbox_priorbox
-I0511 11:49:28.552716  5581 net.cpp:572] mbox_priorbox <- ctx_output5/relu_mbox_priorbox
-I0511 11:49:28.552721  5581 net.cpp:542] mbox_priorbox -> mbox_priorbox
-I0511 11:49:28.552738  5581 net.cpp:260] Setting up mbox_priorbox
-I0511 11:49:28.552744  5581 net.cpp:267] TEST Top shape for layer 190 'mbox_priorbox' 1 2 12824 (25648)
-I0511 11:49:28.552749  5581 layer_factory.hpp:172] Creating layer 'mbox_conf_reshape' of type 'Reshape'
-I0511 11:49:28.552754  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552763  5581 net.cpp:200] Created Layer mbox_conf_reshape (191)
-I0511 11:49:28.552767  5581 net.cpp:572] mbox_conf_reshape <- mbox_conf
-I0511 11:49:28.552772  5581 net.cpp:542] mbox_conf_reshape -> mbox_conf_reshape
-I0511 11:49:28.552793  5581 net.cpp:260] Setting up mbox_conf_reshape
-I0511 11:49:28.552798  5581 net.cpp:267] TEST Top shape for layer 191 'mbox_conf_reshape' 10 3206 21 (673260)
-I0511 11:49:28.552803  5581 layer_factory.hpp:172] Creating layer 'mbox_conf_softmax' of type 'Softmax'
-I0511 11:49:28.552808  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552822  5581 net.cpp:200] Created Layer mbox_conf_softmax (192)
-I0511 11:49:28.552826  5581 net.cpp:572] mbox_conf_softmax <- mbox_conf_reshape
-I0511 11:49:28.552831  5581 net.cpp:542] mbox_conf_softmax -> mbox_conf_softmax
-I0511 11:49:28.552882  5581 net.cpp:260] Setting up mbox_conf_softmax
-I0511 11:49:28.552888  5581 net.cpp:267] TEST Top shape for layer 192 'mbox_conf_softmax' 10 3206 21 (673260)
-I0511 11:49:28.552893  5581 layer_factory.hpp:172] Creating layer 'mbox_conf_flatten' of type 'Flatten'
-I0511 11:49:28.552897  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.552903  5581 net.cpp:200] Created Layer mbox_conf_flatten (193)
-I0511 11:49:28.552908  5581 net.cpp:572] mbox_conf_flatten <- mbox_conf_softmax
-I0511 11:49:28.552918  5581 net.cpp:542] mbox_conf_flatten -> mbox_conf_flatten
-I0511 11:49:28.565068  5581 net.cpp:260] Setting up mbox_conf_flatten
-I0511 11:49:28.565095  5581 net.cpp:267] TEST Top shape for layer 193 'mbox_conf_flatten' 10 67326 (673260)
-I0511 11:49:28.565104  5581 layer_factory.hpp:172] Creating layer 'detection_out' of type 'DetectionOutput'
-I0511 11:49:28.565111  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.565136  5581 net.cpp:200] Created Layer detection_out (194)
-I0511 11:49:28.565143  5581 net.cpp:572] detection_out <- mbox_loc
-I0511 11:49:28.565151  5581 net.cpp:572] detection_out <- mbox_conf_flatten
-I0511 11:49:28.565156  5581 net.cpp:572] detection_out <- mbox_priorbox
-I0511 11:49:28.565161  5581 net.cpp:542] detection_out -> detection_out
-I0511 11:49:28.566352  5581 net.cpp:260] Setting up detection_out
-I0511 11:49:28.566362  5581 net.cpp:267] TEST Top shape for layer 194 'detection_out' 1 1 1 7 (7)
-I0511 11:49:28.566367  5581 layer_factory.hpp:172] Creating layer 'detection_eval' of type 'DetectionEvaluate'
-I0511 11:49:28.566373  5581 layer_factory.hpp:184] Layer's types are Ftype:FLOAT Btype:FLOAT Fmath:FLOAT Bmath:FLOAT
-I0511 11:49:28.566382  5581 net.cpp:200] Created Layer detection_eval (195)
-I0511 11:49:28.566387  5581 net.cpp:572] detection_eval <- detection_out
-I0511 11:49:28.566392  5581 net.cpp:572] detection_eval <- label
-I0511 11:49:28.566399  5581 net.cpp:542] detection_eval -> detection_eval
-I0511 11:49:28.567126  5581 net.cpp:260] Setting up detection_eval
-I0511 11:49:28.567133  5581 net.cpp:267] TEST Top shape for layer 195 'detection_eval' 1 1 21 5 (105)
-I0511 11:49:28.567139  5581 net.cpp:338] detection_eval does not need backward computation.
-I0511 11:49:28.567143  5581 net.cpp:338] detection_out does not need backward computation.
-I0511 11:49:28.567149  5581 net.cpp:338] mbox_conf_flatten does not need backward computation.
-I0511 11:49:28.567153  5581 net.cpp:338] mbox_conf_softmax does not need backward computation.
-I0511 11:49:28.567157  5581 net.cpp:338] mbox_conf_reshape does not need backward computation.
-I0511 11:49:28.567162  5581 net.cpp:338] mbox_priorbox does not need backward computation.
-I0511 11:49:28.567168  5581 net.cpp:338] mbox_conf does not need backward computation.
-I0511 11:49:28.567173  5581 net.cpp:338] mbox_loc does not need backward computation.
-I0511 11:49:28.567178  5581 net.cpp:338] ctx_output5/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567183  5581 net.cpp:338] ctx_output5/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567188  5581 net.cpp:338] ctx_output5/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567191  5581 net.cpp:338] ctx_output5/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567196  5581 net.cpp:338] ctx_output5/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567200  5581 net.cpp:338] ctx_output5/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567204  5581 net.cpp:338] ctx_output5/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567209  5581 net.cpp:338] ctx_output4/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567214  5581 net.cpp:338] ctx_output4/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567219  5581 net.cpp:338] ctx_output4/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567222  5581 net.cpp:338] ctx_output4/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567226  5581 net.cpp:338] ctx_output4/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567231  5581 net.cpp:338] ctx_output4/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567236  5581 net.cpp:338] ctx_output4/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567240  5581 net.cpp:338] ctx_output3/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567245  5581 net.cpp:338] ctx_output3/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567261  5581 net.cpp:338] ctx_output3/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567266  5581 net.cpp:338] ctx_output3/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567271  5581 net.cpp:338] ctx_output3/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567276  5581 net.cpp:338] ctx_output3/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567279  5581 net.cpp:338] ctx_output3/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567283  5581 net.cpp:338] ctx_output2/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567288  5581 net.cpp:338] ctx_output2/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567292  5581 net.cpp:338] ctx_output2/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567296  5581 net.cpp:338] ctx_output2/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567301  5581 net.cpp:338] ctx_output2/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567304  5581 net.cpp:338] ctx_output2/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567309  5581 net.cpp:338] ctx_output2/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567313  5581 net.cpp:338] ctx_output1/relu_mbox_priorbox does not need backward computation.
-I0511 11:49:28.567318  5581 net.cpp:338] ctx_output1/relu_mbox_conf_flat does not need backward computation.
-I0511 11:49:28.567322  5581 net.cpp:338] ctx_output1/relu_mbox_conf_perm does not need backward computation.
-I0511 11:49:28.567327  5581 net.cpp:338] ctx_output1/relu_mbox_conf does not need backward computation.
-I0511 11:49:28.567330  5581 net.cpp:338] ctx_output1/relu_mbox_loc_flat does not need backward computation.
-I0511 11:49:28.567335  5581 net.cpp:338] ctx_output1/relu_mbox_loc_perm does not need backward computation.
-I0511 11:49:28.567339  5581 net.cpp:338] ctx_output1/relu_mbox_loc does not need backward computation.
-I0511 11:49:28.567344  5581 net.cpp:338] ctx_output5_ctx_output5/relu_0_split does not need backward computation.
-I0511 11:49:28.567348  5581 net.cpp:338] ctx_output5/relu does not need backward computation.
-I0511 11:49:28.567353  5581 net.cpp:338] ctx_output5/bn does not need backward computation.
-I0511 11:49:28.567358  5581 net.cpp:338] ctx_output5 does not need backward computation.
-I0511 11:49:28.567363  5581 net.cpp:338] ctx_output5/1x1/relu does not need backward computation.
-I0511 11:49:28.567366  5581 net.cpp:338] ctx_output5/1x1/bn does not need backward computation.
-I0511 11:49:28.567370  5581 net.cpp:338] ctx_output5/1x1 does not need backward computation.
-I0511 11:49:28.567375  5581 net.cpp:338] ctx_output4_ctx_output4/relu_0_split does not need backward computation.
-I0511 11:49:28.567379  5581 net.cpp:338] ctx_output4/relu does not need backward computation.
-I0511 11:49:28.567384  5581 net.cpp:338] ctx_output4/bn does not need backward computation.
-I0511 11:49:28.567389  5581 net.cpp:338] ctx_output4 does not need backward computation.
-I0511 11:49:28.567392  5581 net.cpp:338] ctx_output4/1x1/relu does not need backward computation.
-I0511 11:49:28.567397  5581 net.cpp:338] ctx_output4/1x1/bn does not need backward computation.
-I0511 11:49:28.567401  5581 net.cpp:338] ctx_output4/1x1 does not need backward computation.
-I0511 11:49:28.567405  5581 net.cpp:338] ctx_output3_ctx_output3/relu_0_split does not need backward computation.
-I0511 11:49:28.567410  5581 net.cpp:338] ctx_output3/relu does not need backward computation.
-I0511 11:49:28.567414  5581 net.cpp:338] ctx_output3/bn does not need backward computation.
-I0511 11:49:28.567418  5581 net.cpp:338] ctx_output3 does not need backward computation.
-I0511 11:49:28.567423  5581 net.cpp:338] ctx_output3/1x1/relu does not need backward computation.
-I0511 11:49:28.567427  5581 net.cpp:338] ctx_output3/1x1/bn does not need backward computation.
-I0511 11:49:28.567431  5581 net.cpp:338] ctx_output3/1x1 does not need backward computation.
-I0511 11:49:28.567440  5581 net.cpp:338] ctx_output2_ctx_output2/relu_0_split does not need backward computation.
-I0511 11:49:28.567445  5581 net.cpp:338] ctx_output2/relu does not need backward computation.
-I0511 11:49:28.567448  5581 net.cpp:338] ctx_output2/bn does not need backward computation.
-I0511 11:49:28.567453  5581 net.cpp:338] ctx_output2 does not need backward computation.
-I0511 11:49:28.567457  5581 net.cpp:338] ctx_output2/1x1/relu does not need backward computation.
-I0511 11:49:28.567461  5581 net.cpp:338] ctx_output2/1x1/bn does not need backward computation.
-I0511 11:49:28.567466  5581 net.cpp:338] ctx_output2/1x1 does not need backward computation.
-I0511 11:49:28.567471  5581 net.cpp:338] ctx_output1_ctx_output1/relu_0_split does not need backward computation.
-I0511 11:49:28.567474  5581 net.cpp:338] ctx_output1/relu does not need backward computation.
-I0511 11:49:28.567479  5581 net.cpp:338] ctx_output1/bn does not need backward computation.
-I0511 11:49:28.567483  5581 net.cpp:338] ctx_output1 does not need backward computation.
-I0511 11:49:28.567488  5581 net.cpp:338] ctx_output1/1x1/relu does not need backward computation.
-I0511 11:49:28.567492  5581 net.cpp:338] ctx_output1/1x1/bn does not need backward computation.
-I0511 11:49:28.567497  5581 net.cpp:338] ctx_output1/1x1 does not need backward computation.
-I0511 11:49:28.567500  5581 net.cpp:338] pool8 does not need backward computation.
-I0511 11:49:28.567505  5581 net.cpp:338] pool7_pool7_0_split does not need backward computation.
-I0511 11:49:28.567509  5581 net.cpp:338] pool7 does not need backward computation.
-I0511 11:49:28.567514  5581 net.cpp:338] pool6_pool6_0_split does not need backward computation.
-I0511 11:49:28.567518  5581 net.cpp:338] pool6 does not need backward computation.
-I0511 11:49:28.567523  5581 net.cpp:338] conv6/sep_relu6/sep_0_split does not need backward computation.
-I0511 11:49:28.567528  5581 net.cpp:338] relu6/sep does not need backward computation.
-I0511 11:49:28.567533  5581 net.cpp:338] conv6/sep/scale does not need backward computation.
-I0511 11:49:28.567536  5581 net.cpp:338] conv6/sep/bn does not need backward computation.
-I0511 11:49:28.567540  5581 net.cpp:338] conv6/sep does not need backward computation.
-I0511 11:49:28.567545  5581 net.cpp:338] relu6/dw does not need backward computation.
-I0511 11:49:28.567549  5581 net.cpp:338] conv6/dw/scale does not need backward computation.
-I0511 11:49:28.567554  5581 net.cpp:338] conv6/dw/bn does not need backward computation.
-I0511 11:49:28.567557  5581 net.cpp:338] conv6/dw does not need backward computation.
-I0511 11:49:28.567562  5581 net.cpp:338] relu5_6/sep does not need backward computation.
-I0511 11:49:28.567566  5581 net.cpp:338] conv5_6/sep/scale does not need backward computation.
-I0511 11:49:28.567570  5581 net.cpp:338] conv5_6/sep/bn does not need backward computation.
-I0511 11:49:28.567575  5581 net.cpp:338] conv5_6/sep does not need backward computation.
-I0511 11:49:28.567579  5581 net.cpp:338] relu5_6/dw does not need backward computation.
-I0511 11:49:28.567584  5581 net.cpp:338] conv5_6/dw/scale does not need backward computation.
-I0511 11:49:28.567587  5581 net.cpp:338] conv5_6/dw/bn does not need backward computation.
-I0511 11:49:28.567591  5581 net.cpp:338] conv5_6/dw does not need backward computation.
-I0511 11:49:28.567597  5581 net.cpp:338] conv5_5/sep_relu5_5/sep_0_split does not need backward computation.
-I0511 11:49:28.567601  5581 net.cpp:338] relu5_5/sep does not need backward computation.
-I0511 11:49:28.567605  5581 net.cpp:338] conv5_5/sep/scale does not need backward computation.
-I0511 11:49:28.567610  5581 net.cpp:338] conv5_5/sep/bn does not need backward computation.
-I0511 11:49:28.567613  5581 net.cpp:338] conv5_5/sep does not need backward computation.
-I0511 11:49:28.567617  5581 net.cpp:338] relu5_5/dw does not need backward computation.
-I0511 11:49:28.567622  5581 net.cpp:338] conv5_5/dw/scale does not need backward computation.
-I0511 11:49:28.567626  5581 net.cpp:338] conv5_5/dw/bn does not need backward computation.
-I0511 11:49:28.567633  5581 net.cpp:338] conv5_5/dw does not need backward computation.
-I0511 11:49:28.567638  5581 net.cpp:338] relu5_4/sep does not need backward computation.
-I0511 11:49:28.567643  5581 net.cpp:338] conv5_4/sep/scale does not need backward computation.
-I0511 11:49:28.567647  5581 net.cpp:338] conv5_4/sep/bn does not need backward computation.
-I0511 11:49:28.567651  5581 net.cpp:338] conv5_4/sep does not need backward computation.
-I0511 11:49:28.567656  5581 net.cpp:338] relu5_4/dw does not need backward computation.
-I0511 11:49:28.567659  5581 net.cpp:338] conv5_4/dw/scale does not need backward computation.
-I0511 11:49:28.567663  5581 net.cpp:338] conv5_4/dw/bn does not need backward computation.
-I0511 11:49:28.567668  5581 net.cpp:338] conv5_4/dw does not need backward computation.
-I0511 11:49:28.567672  5581 net.cpp:338] relu5_3/sep does not need backward computation.
-I0511 11:49:28.567677  5581 net.cpp:338] conv5_3/sep/scale does not need backward computation.
-I0511 11:49:28.567680  5581 net.cpp:338] conv5_3/sep/bn does not need backward computation.
-I0511 11:49:28.567684  5581 net.cpp:338] conv5_3/sep does not need backward computation.
-I0511 11:49:28.567689  5581 net.cpp:338] relu5_3/dw does not need backward computation.
-I0511 11:49:28.567693  5581 net.cpp:338] conv5_3/dw/scale does not need backward computation.
-I0511 11:49:28.567698  5581 net.cpp:338] conv5_3/dw/bn does not need backward computation.
-I0511 11:49:28.567701  5581 net.cpp:338] conv5_3/dw does not need backward computation.
-I0511 11:49:28.567706  5581 net.cpp:338] relu5_2/sep does not need backward computation.
-I0511 11:49:28.567710  5581 net.cpp:338] conv5_2/sep/scale does not need backward computation.
-I0511 11:49:28.567714  5581 net.cpp:338] conv5_2/sep/bn does not need backward computation.
-I0511 11:49:28.567718  5581 net.cpp:338] conv5_2/sep does not need backward computation.
-I0511 11:49:28.567723  5581 net.cpp:338] relu5_2/dw does not need backward computation.
-I0511 11:49:28.567726  5581 net.cpp:338] conv5_2/dw/scale does not need backward computation.
-I0511 11:49:28.567730  5581 net.cpp:338] conv5_2/dw/bn does not need backward computation.
-I0511 11:49:28.567735  5581 net.cpp:338] conv5_2/dw does not need backward computation.
-I0511 11:49:28.567739  5581 net.cpp:338] relu5_1/sep does not need backward computation.
-I0511 11:49:28.567744  5581 net.cpp:338] conv5_1/sep/scale does not need backward computation.
-I0511 11:49:28.567747  5581 net.cpp:338] conv5_1/sep/bn does not need backward computation.
-I0511 11:49:28.567751  5581 net.cpp:338] conv5_1/sep does not need backward computation.
-I0511 11:49:28.567756  5581 net.cpp:338] relu5_1/dw does not need backward computation.
-I0511 11:49:28.567760  5581 net.cpp:338] conv5_1/dw/scale does not need backward computation.
-I0511 11:49:28.567764  5581 net.cpp:338] conv5_1/dw/bn does not need backward computation.
-I0511 11:49:28.567768  5581 net.cpp:338] conv5_1/dw does not need backward computation.
-I0511 11:49:28.567772  5581 net.cpp:338] relu4_2/sep does not need backward computation.
-I0511 11:49:28.567777  5581 net.cpp:338] conv4_2/sep/scale does not need backward computation.
-I0511 11:49:28.567781  5581 net.cpp:338] conv4_2/sep/bn does not need backward computation.
-I0511 11:49:28.567785  5581 net.cpp:338] conv4_2/sep does not need backward computation.
-I0511 11:49:28.567790  5581 net.cpp:338] relu4_2/dw does not need backward computation.
-I0511 11:49:28.567793  5581 net.cpp:338] conv4_2/dw/scale does not need backward computation.
-I0511 11:49:28.567798  5581 net.cpp:338] conv4_2/dw/bn does not need backward computation.
-I0511 11:49:28.567802  5581 net.cpp:338] conv4_2/dw does not need backward computation.
-I0511 11:49:28.567806  5581 net.cpp:338] relu4_1/sep does not need backward computation.
-I0511 11:49:28.567811  5581 net.cpp:338] conv4_1/sep/scale does not need backward computation.
-I0511 11:49:28.567814  5581 net.cpp:338] conv4_1/sep/bn does not need backward computation.
-I0511 11:49:28.567818  5581 net.cpp:338] conv4_1/sep does not need backward computation.
-I0511 11:49:28.567823  5581 net.cpp:338] relu4_1/dw does not need backward computation.
-I0511 11:49:28.567831  5581 net.cpp:338] conv4_1/dw/scale does not need backward computation.
-I0511 11:49:28.567834  5581 net.cpp:338] conv4_1/dw/bn does not need backward computation.
-I0511 11:49:28.567838  5581 net.cpp:338] conv4_1/dw does not need backward computation.
-I0511 11:49:28.567843  5581 net.cpp:338] relu3_2/sep does not need backward computation.
-I0511 11:49:28.567847  5581 net.cpp:338] conv3_2/sep/scale does not need backward computation.
-I0511 11:49:28.567852  5581 net.cpp:338] conv3_2/sep/bn does not need backward computation.
-I0511 11:49:28.567857  5581 net.cpp:338] conv3_2/sep does not need backward computation.
-I0511 11:49:28.567860  5581 net.cpp:338] relu3_2/dw does not need backward computation.
-I0511 11:49:28.567865  5581 net.cpp:338] conv3_2/dw/scale does not need backward computation.
-I0511 11:49:28.567869  5581 net.cpp:338] conv3_2/dw/bn does not need backward computation.
-I0511 11:49:28.567874  5581 net.cpp:338] conv3_2/dw does not need backward computation.
-I0511 11:49:28.567879  5581 net.cpp:338] relu3_1/sep does not need backward computation.
-I0511 11:49:28.567883  5581 net.cpp:338] conv3_1/sep/scale does not need backward computation.
-I0511 11:49:28.567888  5581 net.cpp:338] conv3_1/sep/bn does not need backward computation.
-I0511 11:49:28.567891  5581 net.cpp:338] conv3_1/sep does not need backward computation.
-I0511 11:49:28.567896  5581 net.cpp:338] relu3_1/dw does not need backward computation.
-I0511 11:49:28.567900  5581 net.cpp:338] conv3_1/dw/scale does not need backward computation.
-I0511 11:49:28.567904  5581 net.cpp:338] conv3_1/dw/bn does not need backward computation.
-I0511 11:49:28.567909  5581 net.cpp:338] conv3_1/dw does not need backward computation.
-I0511 11:49:28.567914  5581 net.cpp:338] relu2_2/sep does not need backward computation.
-I0511 11:49:28.567917  5581 net.cpp:338] conv2_2/sep/scale does not need backward computation.
-I0511 11:49:28.567922  5581 net.cpp:338] conv2_2/sep/bn does not need backward computation.
-I0511 11:49:28.567927  5581 net.cpp:338] conv2_2/sep does not need backward computation.
-I0511 11:49:28.567931  5581 net.cpp:338] relu2_2/dw does not need backward computation.
-I0511 11:49:28.567935  5581 net.cpp:338] conv2_2/dw/scale does not need backward computation.
-I0511 11:49:28.567939  5581 net.cpp:338] conv2_2/dw/bn does not need backward computation.
-I0511 11:49:28.567945  5581 net.cpp:338] conv2_2/dw does not need backward computation.
-I0511 11:49:28.567950  5581 net.cpp:338] relu2_1/sep does not need backward computation.
-I0511 11:49:28.567953  5581 net.cpp:338] conv2_1/sep/scale does not need backward computation.
-I0511 11:49:28.567957  5581 net.cpp:338] conv2_1/sep/bn does not need backward computation.
-I0511 11:49:28.567961  5581 net.cpp:338] conv2_1/sep does not need backward computation.
-I0511 11:49:28.567966  5581 net.cpp:338] relu2_1/dw does not need backward computation.
-I0511 11:49:28.567971  5581 net.cpp:338] conv2_1/dw/scale does not need backward computation.
-I0511 11:49:28.567975  5581 net.cpp:338] conv2_1/dw/bn does not need backward computation.
-I0511 11:49:28.567979  5581 net.cpp:338] conv2_1/dw does not need backward computation.
-I0511 11:49:28.567984  5581 net.cpp:338] relu1 does not need backward computation.
-I0511 11:49:28.567988  5581 net.cpp:338] conv1/scale does not need backward computation.
-I0511 11:49:28.567992  5581 net.cpp:338] conv1/bn does not need backward computation.
-I0511 11:49:28.567997  5581 net.cpp:338] conv1 does not need backward computation.
-I0511 11:49:28.568002  5581 net.cpp:338] data/bias does not need backward computation.
-I0511 11:49:28.568007  5581 net.cpp:338] data_data_0_split does not need backward computation.
-I0511 11:49:28.568012  5581 net.cpp:338] data does not need backward computation.
-I0511 11:49:28.568017  5581 net.cpp:380] This network produces output detection_eval
-I0511 11:49:28.568183  5581 net.cpp:403] Top memory (TEST) required for data: 1352267864 diff: 1352267864
-I0511 11:49:28.568188  5581 net.cpp:406] Bottom memory (TEST) required for data: 1352267440 diff: 1352267440
-I0511 11:49:28.568198  5581 net.cpp:409] Shared (in-place) memory (TEST) by data: 848936960 diff: 848936960
-I0511 11:49:28.568203  5581 net.cpp:412] Parameters memory (TEST) required for data: 9462808 diff: 9462808
-I0511 11:49:28.568207  5581 net.cpp:415] Parameters shared memory (TEST) by data: 0 diff: 0
-I0511 11:49:28.568212  5581 net.cpp:421] Network initialization done.
-I0511 11:49:28.574254  5581 net.cpp:1144] Copying source layer data Type:AnnotatedData #blobs=0
-I0511 11:49:28.574291  5581 net.cpp:1144] Copying source layer data_data_0_split Type:Split #blobs=0
-I0511 11:49:28.574295  5581 net.cpp:1144] Copying source layer data/bias Type:Bias #blobs=1
-I0511 11:49:28.574371  5581 net.cpp:1144] Copying source layer conv1 Type:Convolution #blobs=1
-I0511 11:49:28.574388  5581 net.cpp:1144] Copying source layer conv1/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574414  5581 net.cpp:1144] Copying source layer conv1/scale Type:Scale #blobs=2
-I0511 11:49:28.574429  5581 net.cpp:1144] Copying source layer relu1 Type:ReLU #blobs=0
-I0511 11:49:28.574432  5581 net.cpp:1144] Copying source layer conv2_1/dw Type:Convolution #blobs=1
-I0511 11:49:28.574441  5581 net.cpp:1144] Copying source layer conv2_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574456  5581 net.cpp:1144] Copying source layer conv2_1/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574470  5581 net.cpp:1144] Copying source layer relu2_1/dw Type:ReLU #blobs=0
-I0511 11:49:28.574473  5581 net.cpp:1144] Copying source layer conv2_1/sep Type:Convolution #blobs=1
-I0511 11:49:28.574481  5581 net.cpp:1144] Copying source layer conv2_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574496  5581 net.cpp:1144] Copying source layer conv2_1/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574507  5581 net.cpp:1144] Copying source layer relu2_1/sep Type:ReLU #blobs=0
-I0511 11:49:28.574512  5581 net.cpp:1144] Copying source layer conv2_2/dw Type:Convolution #blobs=1
-I0511 11:49:28.574520  5581 net.cpp:1144] Copying source layer conv2_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574534  5581 net.cpp:1144] Copying source layer conv2_2/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574548  5581 net.cpp:1144] Copying source layer relu2_2/dw Type:ReLU #blobs=0
-I0511 11:49:28.574551  5581 net.cpp:1144] Copying source layer conv2_2/sep Type:Convolution #blobs=1
-I0511 11:49:28.574561  5581 net.cpp:1144] Copying source layer conv2_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574576  5581 net.cpp:1144] Copying source layer conv2_2/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574589  5581 net.cpp:1144] Copying source layer relu2_2/sep Type:ReLU #blobs=0
-I0511 11:49:28.574592  5581 net.cpp:1144] Copying source layer conv3_1/dw Type:Convolution #blobs=1
-I0511 11:49:28.574601  5581 net.cpp:1144] Copying source layer conv3_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574616  5581 net.cpp:1144] Copying source layer conv3_1/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574627  5581 net.cpp:1144] Copying source layer relu3_1/dw Type:ReLU #blobs=0
-I0511 11:49:28.574632  5581 net.cpp:1144] Copying source layer conv3_1/sep Type:Convolution #blobs=1
-I0511 11:49:28.574642  5581 net.cpp:1144] Copying source layer conv3_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574656  5581 net.cpp:1144] Copying source layer conv3_1/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574667  5581 net.cpp:1144] Copying source layer relu3_1/sep Type:ReLU #blobs=0
-I0511 11:49:28.574671  5581 net.cpp:1144] Copying source layer conv3_2/dw Type:Convolution #blobs=1
-I0511 11:49:28.574681  5581 net.cpp:1144] Copying source layer conv3_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574697  5581 net.cpp:1144] Copying source layer conv3_2/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574708  5581 net.cpp:1144] Copying source layer relu3_2/dw Type:ReLU #blobs=0
-I0511 11:49:28.574712  5581 net.cpp:1144] Copying source layer conv3_2/sep Type:Convolution #blobs=1
-I0511 11:49:28.574726  5581 net.cpp:1144] Copying source layer conv3_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574743  5581 net.cpp:1144] Copying source layer conv3_2/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574766  5581 net.cpp:1144] Copying source layer relu3_2/sep Type:ReLU #blobs=0
-I0511 11:49:28.574771  5581 net.cpp:1144] Copying source layer conv4_1/dw Type:Convolution #blobs=1
-I0511 11:49:28.574780  5581 net.cpp:1144] Copying source layer conv4_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574795  5581 net.cpp:1144] Copying source layer conv4_1/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574807  5581 net.cpp:1144] Copying source layer relu4_1/dw Type:ReLU #blobs=0
-I0511 11:49:28.574811  5581 net.cpp:1144] Copying source layer conv4_1/sep Type:Convolution #blobs=1
-I0511 11:49:28.574828  5581 net.cpp:1144] Copying source layer conv4_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574844  5581 net.cpp:1144] Copying source layer conv4_1/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574856  5581 net.cpp:1144] Copying source layer relu4_1/sep Type:ReLU #blobs=0
-I0511 11:49:28.574859  5581 net.cpp:1144] Copying source layer conv4_2/dw Type:Convolution #blobs=1
-I0511 11:49:28.574869  5581 net.cpp:1144] Copying source layer conv4_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574883  5581 net.cpp:1144] Copying source layer conv4_2/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574896  5581 net.cpp:1144] Copying source layer relu4_2/dw Type:ReLU #blobs=0
-I0511 11:49:28.574899  5581 net.cpp:1144] Copying source layer conv4_2/sep Type:Convolution #blobs=1
-I0511 11:49:28.574925  5581 net.cpp:1144] Copying source layer conv4_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574941  5581 net.cpp:1144] Copying source layer conv4_2/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.574954  5581 net.cpp:1144] Copying source layer relu4_2/sep Type:ReLU #blobs=0
-I0511 11:49:28.574957  5581 net.cpp:1144] Copying source layer conv5_1/dw Type:Convolution #blobs=1
-I0511 11:49:28.574967  5581 net.cpp:1144] Copying source layer conv5_1/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.574981  5581 net.cpp:1144] Copying source layer conv5_1/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.574993  5581 net.cpp:1144] Copying source layer relu5_1/dw Type:ReLU #blobs=0
-I0511 11:49:28.574997  5581 net.cpp:1144] Copying source layer conv5_1/sep Type:Convolution #blobs=1
-I0511 11:49:28.575040  5581 net.cpp:1144] Copying source layer conv5_1/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575055  5581 net.cpp:1144] Copying source layer conv5_1/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575068  5581 net.cpp:1144] Copying source layer relu5_1/sep Type:ReLU #blobs=0
-I0511 11:49:28.575073  5581 net.cpp:1144] Copying source layer conv5_2/dw Type:Convolution #blobs=1
-I0511 11:49:28.575081  5581 net.cpp:1144] Copying source layer conv5_2/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575095  5581 net.cpp:1144] Copying source layer conv5_2/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575109  5581 net.cpp:1144] Copying source layer relu5_2/dw Type:ReLU #blobs=0
-I0511 11:49:28.575112  5581 net.cpp:1144] Copying source layer conv5_2/sep Type:Convolution #blobs=1
-I0511 11:49:28.575153  5581 net.cpp:1144] Copying source layer conv5_2/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575168  5581 net.cpp:1144] Copying source layer conv5_2/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575181  5581 net.cpp:1144] Copying source layer relu5_2/sep Type:ReLU #blobs=0
-I0511 11:49:28.575184  5581 net.cpp:1144] Copying source layer conv5_3/dw Type:Convolution #blobs=1
-I0511 11:49:28.575194  5581 net.cpp:1144] Copying source layer conv5_3/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575209  5581 net.cpp:1144] Copying source layer conv5_3/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575222  5581 net.cpp:1144] Copying source layer relu5_3/dw Type:ReLU #blobs=0
-I0511 11:49:28.575225  5581 net.cpp:1144] Copying source layer conv5_3/sep Type:Convolution #blobs=1
-I0511 11:49:28.575268  5581 net.cpp:1144] Copying source layer conv5_3/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575284  5581 net.cpp:1144] Copying source layer conv5_3/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575296  5581 net.cpp:1144] Copying source layer relu5_3/sep Type:ReLU #blobs=0
-I0511 11:49:28.575306  5581 net.cpp:1144] Copying source layer conv5_4/dw Type:Convolution #blobs=1
-I0511 11:49:28.575317  5581 net.cpp:1144] Copying source layer conv5_4/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575332  5581 net.cpp:1144] Copying source layer conv5_4/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575345  5581 net.cpp:1144] Copying source layer relu5_4/dw Type:ReLU #blobs=0
-I0511 11:49:28.575348  5581 net.cpp:1144] Copying source layer conv5_4/sep Type:Convolution #blobs=1
-I0511 11:49:28.575393  5581 net.cpp:1144] Copying source layer conv5_4/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575409  5581 net.cpp:1144] Copying source layer conv5_4/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575422  5581 net.cpp:1144] Copying source layer relu5_4/sep Type:ReLU #blobs=0
-I0511 11:49:28.575426  5581 net.cpp:1144] Copying source layer conv5_5/dw Type:Convolution #blobs=1
-I0511 11:49:28.575435  5581 net.cpp:1144] Copying source layer conv5_5/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575450  5581 net.cpp:1144] Copying source layer conv5_5/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575462  5581 net.cpp:1144] Copying source layer relu5_5/dw Type:ReLU #blobs=0
-I0511 11:49:28.575466  5581 net.cpp:1144] Copying source layer conv5_5/sep Type:Convolution #blobs=1
-I0511 11:49:28.575508  5581 net.cpp:1144] Copying source layer conv5_5/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575525  5581 net.cpp:1144] Copying source layer conv5_5/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575536  5581 net.cpp:1144] Copying source layer relu5_5/sep Type:ReLU #blobs=0
-I0511 11:49:28.575541  5581 net.cpp:1144] Copying source layer conv5_5/sep_relu5_5/sep_0_split Type:Split #blobs=0
-I0511 11:49:28.575546  5581 net.cpp:1144] Copying source layer conv5_6/dw Type:Convolution #blobs=1
-I0511 11:49:28.575556  5581 net.cpp:1144] Copying source layer conv5_6/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575570  5581 net.cpp:1144] Copying source layer conv5_6/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575582  5581 net.cpp:1144] Copying source layer relu5_6/dw Type:ReLU #blobs=0
-I0511 11:49:28.575587  5581 net.cpp:1144] Copying source layer conv5_6/sep Type:Convolution #blobs=1
-I0511 11:49:28.575659  5581 net.cpp:1144] Copying source layer conv5_6/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575675  5581 net.cpp:1144] Copying source layer conv5_6/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575688  5581 net.cpp:1144] Copying source layer relu5_6/sep Type:ReLU #blobs=0
-I0511 11:49:28.575692  5581 net.cpp:1144] Copying source layer conv6/dw Type:Convolution #blobs=1
-I0511 11:49:28.575703  5581 net.cpp:1144] Copying source layer conv6/dw/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575717  5581 net.cpp:1144] Copying source layer conv6/dw/scale Type:Scale #blobs=2
-I0511 11:49:28.575731  5581 net.cpp:1144] Copying source layer relu6/dw Type:ReLU #blobs=0
-I0511 11:49:28.575734  5581 net.cpp:1144] Copying source layer conv6/sep Type:Convolution #blobs=1
-I0511 11:49:28.575876  5581 net.cpp:1144] Copying source layer conv6/sep/bn Type:BatchNorm #blobs=3
-I0511 11:49:28.575892  5581 net.cpp:1144] Copying source layer conv6/sep/scale Type:Scale #blobs=2
-I0511 11:49:28.575904  5581 net.cpp:1144] Copying source layer relu6/sep Type:ReLU #blobs=0
-I0511 11:49:28.575909  5581 net.cpp:1144] Copying source layer conv6/sep_relu6/sep_0_split Type:Split #blobs=0
-I0511 11:49:28.575913  5581 net.cpp:1144] Copying source layer pool6 Type:Pooling #blobs=0
-I0511 11:49:28.575917  5581 net.cpp:1144] Copying source layer pool6_pool6_0_split Type:Split #blobs=0
-I0511 11:49:28.575922  5581 net.cpp:1144] Copying source layer pool7 Type:Pooling #blobs=0
-I0511 11:49:28.575927  5581 net.cpp:1144] Copying source layer pool7_pool7_0_split Type:Split #blobs=0
-I0511 11:49:28.575930  5581 net.cpp:1144] Copying source layer pool8 Type:Pooling #blobs=0
-I0511 11:49:28.575934  5581 net.cpp:1144] Copying source layer ctx_output1/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576009  5581 net.cpp:1144] Copying source layer ctx_output1/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576037  5581 net.cpp:1144] Copying source layer ctx_output1/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576042  5581 net.cpp:1144] Copying source layer ctx_output1 Type:Convolution #blobs=2
-I0511 11:49:28.576057  5581 net.cpp:1144] Copying source layer ctx_output1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576077  5581 net.cpp:1144] Copying source layer ctx_output1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576081  5581 net.cpp:1144] Copying source layer ctx_output1_ctx_output1/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576086  5581 net.cpp:1144] Copying source layer ctx_output2/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576217  5581 net.cpp:1144] Copying source layer ctx_output2/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576239  5581 net.cpp:1144] Copying source layer ctx_output2/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576243  5581 net.cpp:1144] Copying source layer ctx_output2 Type:Convolution #blobs=2
-I0511 11:49:28.576257  5581 net.cpp:1144] Copying source layer ctx_output2/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576280  5581 net.cpp:1144] Copying source layer ctx_output2/relu Type:ReLU #blobs=0
-I0511 11:49:28.576284  5581 net.cpp:1144] Copying source layer ctx_output2_ctx_output2/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576288  5581 net.cpp:1144] Copying source layer ctx_output3/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576441  5581 net.cpp:1144] Copying source layer ctx_output3/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576462  5581 net.cpp:1144] Copying source layer ctx_output3/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576467  5581 net.cpp:1144] Copying source layer ctx_output3 Type:Convolution #blobs=2
-I0511 11:49:28.576480  5581 net.cpp:1144] Copying source layer ctx_output3/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576500  5581 net.cpp:1144] Copying source layer ctx_output3/relu Type:ReLU #blobs=0
-I0511 11:49:28.576504  5581 net.cpp:1144] Copying source layer ctx_output3_ctx_output3/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576508  5581 net.cpp:1144] Copying source layer ctx_output4/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576669  5581 net.cpp:1144] Copying source layer ctx_output4/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576692  5581 net.cpp:1144] Copying source layer ctx_output4/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576697  5581 net.cpp:1144] Copying source layer ctx_output4 Type:Convolution #blobs=2
-I0511 11:49:28.576711  5581 net.cpp:1144] Copying source layer ctx_output4/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576732  5581 net.cpp:1144] Copying source layer ctx_output4/relu Type:ReLU #blobs=0
-I0511 11:49:28.576736  5581 net.cpp:1144] Copying source layer ctx_output4_ctx_output4/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576741  5581 net.cpp:1144] Copying source layer ctx_output5/1x1 Type:Convolution #blobs=2
-I0511 11:49:28.576867  5581 net.cpp:1144] Copying source layer ctx_output5/1x1/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576889  5581 net.cpp:1144] Copying source layer ctx_output5/1x1/relu Type:ReLU #blobs=0
-I0511 11:49:28.576894  5581 net.cpp:1144] Copying source layer ctx_output5 Type:Convolution #blobs=2
-I0511 11:49:28.576910  5581 net.cpp:1144] Copying source layer ctx_output5/bn Type:BatchNorm #blobs=5
-I0511 11:49:28.576931  5581 net.cpp:1144] Copying source layer ctx_output5/relu Type:ReLU #blobs=0
-I0511 11:49:28.576936  5581 net.cpp:1144] Copying source layer ctx_output5_ctx_output5/relu_0_split Type:Split #blobs=0
-I0511 11:49:28.576941  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.576957  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.576962  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.576967  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577008  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577013  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577024  5581 net.cpp:1144] Copying source layer ctx_output1/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577029  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.577047  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.577051  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.577056  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577100  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577105  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577111  5581 net.cpp:1144] Copying source layer ctx_output2/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577114  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.577131  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.577136  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.577141  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577185  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577190  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577194  5581 net.cpp:1144] Copying source layer ctx_output3/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577199  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.577217  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.577221  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.577225  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577258  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577263  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577267  5581 net.cpp:1144] Copying source layer ctx_output4/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577272  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_loc Type:Convolution #blobs=2
-I0511 11:49:28.577286  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_loc_perm Type:Permute #blobs=0
-I0511 11:49:28.577291  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_loc_flat Type:Flatten #blobs=0
-I0511 11:49:28.577296  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_conf Type:Convolution #blobs=2
-I0511 11:49:28.577332  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_conf_perm Type:Permute #blobs=0
-I0511 11:49:28.577337  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_conf_flat Type:Flatten #blobs=0
-I0511 11:49:28.577340  5581 net.cpp:1144] Copying source layer ctx_output5/relu_mbox_priorbox Type:PriorBox #blobs=0
-I0511 11:49:28.577344  5581 net.cpp:1144] Copying source layer mbox_loc Type:Concat #blobs=0
-I0511 11:49:28.577348  5581 net.cpp:1144] Copying source layer mbox_conf Type:Concat #blobs=0
-I0511 11:49:28.577353  5581 net.cpp:1144] Copying source layer mbox_priorbox Type:Concat #blobs=0
-I0511 11:49:28.577358  5581 net.cpp:1136] Ignoring source layer mbox_loss
-I0511 11:49:28.577541  5581 caffe.cpp:419] Running for 496 iterations.
-I0511 11:49:28.821983  5581 caffe.cpp:449] Batch 0
-I0511 11:49:28.822185  5581 net.cpp:1765] Enabling quantization flag in quantization_param at infer/iter index: 1
-I0511 11:49:28.822203  5581 net.cpp:1998] Enabling quantization at output of: AnnotatedData data
-I0511 11:49:28.822218  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu1
-I0511 11:49:28.822222  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu2_1/dw
-I0511 11:49:28.822226  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu2_1/sep
-I0511 11:49:28.822228  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu2_2/dw
-I0511 11:49:28.822232  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu2_2/sep
-I0511 11:49:28.822233  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu3_1/dw
-I0511 11:49:28.822237  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu3_1/sep
-I0511 11:49:28.822239  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu3_2/dw
-I0511 11:49:28.822242  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu3_2/sep
-I0511 11:49:28.822245  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu4_1/dw
-I0511 11:49:28.822248  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu4_1/sep
-I0511 11:49:28.822250  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu4_2/dw
-I0511 11:49:28.822253  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu4_2/sep
-I0511 11:49:28.822257  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_1/dw
-I0511 11:49:28.822258  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_1/sep
-I0511 11:49:28.822262  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_2/dw
-I0511 11:49:28.822264  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_2/sep
-I0511 11:49:28.822268  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_3/dw
-I0511 11:49:28.822270  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_3/sep
-I0511 11:49:28.822273  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_4/dw
-I0511 11:49:28.822275  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_4/sep
-I0511 11:49:28.822278  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_5/dw
-I0511 11:49:28.822281  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_5/sep
-I0511 11:49:28.822284  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_6/dw
-I0511 11:49:28.822288  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu5_6/sep
-I0511 11:49:28.822290  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu6/dw
-I0511 11:49:28.822293  5581 net.cpp:1998] Enabling quantization at output of: ReLU relu6/sep
-I0511 11:49:28.822298  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output1/1x1/relu
-I0511 11:49:28.822300  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output1/relu
-I0511 11:49:28.822304  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output2/1x1/relu
-I0511 11:49:28.822305  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output2/relu
-I0511 11:49:28.822309  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output3/1x1/relu
-I0511 11:49:28.822311  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output3/relu
-I0511 11:49:28.822314  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output4/1x1/relu
-I0511 11:49:28.822316  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output4/relu
-I0511 11:49:28.822319  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output5/1x1/relu
-I0511 11:49:28.822322  5581 net.cpp:1998] Enabling quantization at output of: ReLU ctx_output5/relu
-I0511 11:49:28.822324  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output1/relu_mbox_loc
-I0511 11:49:28.822327  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output1/relu_mbox_conf
-I0511 11:49:28.822330  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output2/relu_mbox_loc
-I0511 11:49:28.822332  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output2/relu_mbox_conf
-I0511 11:49:28.822336  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output3/relu_mbox_loc
-I0511 11:49:28.822343  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output3/relu_mbox_conf
-I0511 11:49:28.822346  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output4/relu_mbox_loc
-I0511 11:49:28.822350  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output4/relu_mbox_conf
-I0511 11:49:28.822352  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output5/relu_mbox_loc
-I0511 11:49:28.822355  5581 net.cpp:1998] Enabling quantization at output of: Convolution ctx_output5/relu_mbox_conf
-I0511 11:49:28.822358  5581 net.cpp:1998] Enabling quantization at output of: Concat mbox_loc
-I0511 11:49:28.822360  5581 net.cpp:1998] Enabling quantization at output of: Concat mbox_conf
-I0511 11:49:28.822362  5581 net.cpp:1998] Enabling quantization at output of: Concat mbox_priorbox
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-I0511 11:50:51.801546  5581 caffe.cpp:449] Batch 472
-I0511 11:50:51.989671  5581 caffe.cpp:449] Batch 473
-I0511 11:50:52.141434  5581 caffe.cpp:449] Batch 474
-I0511 11:50:52.310739  5581 caffe.cpp:449] Batch 475
-I0511 11:50:52.480485  5581 caffe.cpp:449] Batch 476
-I0511 11:50:52.649008  5581 caffe.cpp:449] Batch 477
-I0511 11:50:52.808902  5581 caffe.cpp:449] Batch 478
-I0511 11:50:52.975853  5581 caffe.cpp:449] Batch 479
-I0511 11:50:53.148497  5581 caffe.cpp:449] Batch 480
-I0511 11:50:53.305781  5581 caffe.cpp:449] Batch 481
-I0511 11:50:53.459128  5581 caffe.cpp:449] Batch 482
-I0511 11:50:53.606559  5581 caffe.cpp:449] Batch 483
-I0511 11:50:53.778055  5581 caffe.cpp:449] Batch 484
-I0511 11:50:53.947490  5581 caffe.cpp:449] Batch 485
-I0511 11:50:54.106217  5581 caffe.cpp:449] Batch 486
-I0511 11:50:54.279709  5581 caffe.cpp:449] Batch 487
-I0511 11:50:54.444160  5581 caffe.cpp:449] Batch 488
-I0511 11:50:54.618955  5581 caffe.cpp:449] Batch 489
-I0511 11:50:54.778282  5581 caffe.cpp:449] Batch 490
-I0511 11:50:54.946440  5581 caffe.cpp:449] Batch 491
-I0511 11:50:54.957875  5600 data_reader.cpp:320] Restarting data pre-fetching
-I0511 11:50:55.121860  5581 caffe.cpp:449] Batch 492
-I0511 11:50:55.303601  5581 caffe.cpp:449] Batch 493
-I0511 11:50:55.474619  5581 caffe.cpp:449] Batch 494
-I0511 11:50:55.638821  5581 caffe.cpp:449] Batch 495
-I0511 11:50:55.638908  5581 caffe.cpp:483] Loss: 0
-I0511 11:50:55.638947  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638953  5581 caffe.cpp:501] detection_eval = 1
-I0511 11:50:55.638958  5581 caffe.cpp:501] detection_eval = 0.574597
-I0511 11:50:55.638964  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638968  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638972  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638978  5581 caffe.cpp:501] detection_eval = 2
-I0511 11:50:55.638981  5581 caffe.cpp:501] detection_eval = 0.679435
-I0511 11:50:55.638985  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638990  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638993  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.638996  5581 caffe.cpp:501] detection_eval = 3
-I0511 11:50:55.639000  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.639004  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639010  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639014  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639019  5581 caffe.cpp:501] detection_eval = 4
-I0511 11:50:55.639024  5581 caffe.cpp:501] detection_eval = 0.530242
-I0511 11:50:55.639027  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639031  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639036  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639040  5581 caffe.cpp:501] detection_eval = 5
-I0511 11:50:55.639045  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.639050  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639053  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639057  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639065  5581 caffe.cpp:501] detection_eval = 6
-I0511 11:50:55.639070  5581 caffe.cpp:501] detection_eval = 0.429435
-I0511 11:50:55.639073  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639077  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639082  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639087  5581 caffe.cpp:501] detection_eval = 7
-I0511 11:50:55.639093  5581 caffe.cpp:501] detection_eval = 2.43548
-I0511 11:50:55.639097  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639102  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639106  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639111  5581 caffe.cpp:501] detection_eval = 8
-I0511 11:50:55.639117  5581 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:50:55.639122  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639127  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639130  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639135  5581 caffe.cpp:501] detection_eval = 9
-I0511 11:50:55.639139  5581 caffe.cpp:501] detection_eval = 1.53226
-I0511 11:50:55.639144  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639148  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639153  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639158  5581 caffe.cpp:501] detection_eval = 10
-I0511 11:50:55.639163  5581 caffe.cpp:501] detection_eval = 0.491935
-I0511 11:50:55.639168  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639171  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639175  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639179  5581 caffe.cpp:501] detection_eval = 11
-I0511 11:50:55.639184  5581 caffe.cpp:501] detection_eval = 0.417339
-I0511 11:50:55.639189  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639194  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639197  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639202  5581 caffe.cpp:501] detection_eval = 12
-I0511 11:50:55.639206  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.639211  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639215  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639219  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639225  5581 caffe.cpp:501] detection_eval = 13
-I0511 11:50:55.639230  5581 caffe.cpp:501] detection_eval = 0.703629
-I0511 11:50:55.639236  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639258  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639267  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639272  5581 caffe.cpp:501] detection_eval = 14
-I0511 11:50:55.639277  5581 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:50:55.639282  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639287  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639292  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639297  5581 caffe.cpp:501] detection_eval = 15
-I0511 11:50:55.639302  5581 caffe.cpp:501] detection_eval = 9.13306
-I0511 11:50:55.639305  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639310  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639314  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639319  5581 caffe.cpp:501] detection_eval = 16
-I0511 11:50:55.639324  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.639329  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639334  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639339  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639343  5581 caffe.cpp:501] detection_eval = 17
-I0511 11:50:55.639348  5581 caffe.cpp:501] detection_eval = 0.487903
-I0511 11:50:55.639353  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639358  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639364  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639367  5581 caffe.cpp:501] detection_eval = 18
-I0511 11:50:55.639372  5581 caffe.cpp:501] detection_eval = 0.483871
-I0511 11:50:55.639377  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639381  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639386  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639390  5581 caffe.cpp:501] detection_eval = 19
-I0511 11:50:55.639394  5581 caffe.cpp:501] detection_eval = 0.570565
-I0511 11:50:55.639400  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639403  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639407  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639412  5581 caffe.cpp:501] detection_eval = 20
-I0511 11:50:55.639416  5581 caffe.cpp:501] detection_eval = 0.620968
-I0511 11:50:55.639421  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639426  5581 caffe.cpp:501] detection_eval = -1
-I0511 11:50:55.639430  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639434  5581 caffe.cpp:501] detection_eval = 3.25202
-I0511 11:50:55.639438  5581 caffe.cpp:501] detection_eval = 0.164725
-I0511 11:50:55.639442  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.639447  5581 caffe.cpp:501] detection_eval = 0.872984
-I0511 11:50:55.639451  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639456  5581 caffe.cpp:501] detection_eval = 3.65323
-I0511 11:50:55.639461  5581 caffe.cpp:501] detection_eval = 0.104809
-I0511 11:50:55.639466  5581 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:50:55.639470  5581 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:50:55.639474  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639479  5581 caffe.cpp:501] detection_eval = 3.84677
-I0511 11:50:55.639483  5581 caffe.cpp:501] detection_eval = 0.0762525
-I0511 11:50:55.639488  5581 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:50:55.639492  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.639497  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639503  5581 caffe.cpp:501] detection_eval = 4
-I0511 11:50:55.639508  5581 caffe.cpp:501] detection_eval = 0.0660003
-I0511 11:50:55.639511  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.639516  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.639520  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639525  5581 caffe.cpp:501] detection_eval = 4.14718
-I0511 11:50:55.639529  5581 caffe.cpp:501] detection_eval = 0.0605915
-I0511 11:50:55.639534  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.639539  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.639544  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.639551  5581 caffe.cpp:501] detection_eval = 4.23589
-I0511 11:50:55.639556  5581 caffe.cpp:501] detection_eval = 0.0589541
-I0511 11:50:55.639561  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.639565  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.639569  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639575  5581 caffe.cpp:501] detection_eval = 4.34677
-I0511 11:50:55.639578  5581 caffe.cpp:501] detection_eval = 0.0533733
-I0511 11:50:55.639583  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.639588  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.639592  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639597  5581 caffe.cpp:501] detection_eval = 4.43347
-I0511 11:50:55.639602  5581 caffe.cpp:501] detection_eval = 0.0445817
-I0511 11:50:55.639606  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639611  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.639616  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639621  5581 caffe.cpp:501] detection_eval = 4.5121
-I0511 11:50:55.639624  5581 caffe.cpp:501] detection_eval = 0.0445154
-I0511 11:50:55.639629  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.639634  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.639639  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639644  5581 caffe.cpp:501] detection_eval = 4.59073
-I0511 11:50:55.639648  5581 caffe.cpp:501] detection_eval = 0.0476314
-I0511 11:50:55.639653  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639658  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.639662  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639667  5581 caffe.cpp:501] detection_eval = 4.65323
-I0511 11:50:55.639672  5581 caffe.cpp:501] detection_eval = 0.0438739
-I0511 11:50:55.639677  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.639680  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.639685  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639689  5581 caffe.cpp:501] detection_eval = 4.70968
-I0511 11:50:55.639694  5581 caffe.cpp:501] detection_eval = 0.0465306
-I0511 11:50:55.639698  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.639703  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.639708  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.639713  5581 caffe.cpp:501] detection_eval = 4.79435
-I0511 11:50:55.639717  5581 caffe.cpp:501] detection_eval = 0.041596
-I0511 11:50:55.639721  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639726  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.639730  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639735  5581 caffe.cpp:501] detection_eval = 4.85484
-I0511 11:50:55.639740  5581 caffe.cpp:501] detection_eval = 0.0488618
-I0511 11:50:55.639744  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639750  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.639753  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639757  5581 caffe.cpp:501] detection_eval = 4.89315
-I0511 11:50:55.639762  5581 caffe.cpp:501] detection_eval = 0.043171
-I0511 11:50:55.639767  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639771  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.639776  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639781  5581 caffe.cpp:501] detection_eval = 4.98185
-I0511 11:50:55.639786  5581 caffe.cpp:501] detection_eval = 0.0431476
-I0511 11:50:55.639791  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639794  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.639799  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639804  5581 caffe.cpp:501] detection_eval = 5.08871
-I0511 11:50:55.639811  5581 caffe.cpp:501] detection_eval = 0.0481148
-I0511 11:50:55.639814  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.639819  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.639828  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639834  5581 caffe.cpp:501] detection_eval = 5.14718
-I0511 11:50:55.639839  5581 caffe.cpp:501] detection_eval = 0.0433028
-I0511 11:50:55.639844  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.639849  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.639854  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639859  5581 caffe.cpp:501] detection_eval = 5.22984
-I0511 11:50:55.639863  5581 caffe.cpp:501] detection_eval = 0.0444779
-I0511 11:50:55.639868  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639873  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.639878  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.639883  5581 caffe.cpp:501] detection_eval = 5.27823
-I0511 11:50:55.639886  5581 caffe.cpp:501] detection_eval = 0.0408055
-I0511 11:50:55.639891  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.639896  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.639900  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.639905  5581 caffe.cpp:501] detection_eval = 5.33065
-I0511 11:50:55.639909  5581 caffe.cpp:501] detection_eval = 0.045186
-I0511 11:50:55.639914  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.639919  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.639924  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.639927  5581 caffe.cpp:501] detection_eval = 5.39919
-I0511 11:50:55.639933  5581 caffe.cpp:501] detection_eval = 0.0447129
-I0511 11:50:55.639937  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.639942  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.639946  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.639951  5581 caffe.cpp:501] detection_eval = 5.47379
-I0511 11:50:55.639955  5581 caffe.cpp:501] detection_eval = 0.0434004
-I0511 11:50:55.639961  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.639964  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.639969  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.639974  5581 caffe.cpp:501] detection_eval = 5.53024
-I0511 11:50:55.639979  5581 caffe.cpp:501] detection_eval = 0.0489237
-I0511 11:50:55.639983  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.639988  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.639992  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.639997  5581 caffe.cpp:501] detection_eval = 5.57258
-I0511 11:50:55.640002  5581 caffe.cpp:501] detection_eval = 0.0410275
-I0511 11:50:55.640007  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640010  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.640015  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640019  5581 caffe.cpp:501] detection_eval = 5.61895
-I0511 11:50:55.640024  5581 caffe.cpp:501] detection_eval = 0.0423506
-I0511 11:50:55.640028  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.640033  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640038  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640043  5581 caffe.cpp:501] detection_eval = 5.69355
-I0511 11:50:55.640046  5581 caffe.cpp:501] detection_eval = 0.0451725
-I0511 11:50:55.640051  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640055  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.640060  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640064  5581 caffe.cpp:501] detection_eval = 5.73185
-I0511 11:50:55.640069  5581 caffe.cpp:501] detection_eval = 0.0393402
-I0511 11:50:55.640074  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640079  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640084  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640087  5581 caffe.cpp:501] detection_eval = 5.86694
-I0511 11:50:55.640091  5581 caffe.cpp:501] detection_eval = 0.0424488
-I0511 11:50:55.640096  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640106  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640111  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640116  5581 caffe.cpp:501] detection_eval = 5.91734
-I0511 11:50:55.640121  5581 caffe.cpp:501] detection_eval = 0.0435992
-I0511 11:50:55.640125  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.640130  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.640135  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640138  5581 caffe.cpp:501] detection_eval = 6.01008
-I0511 11:50:55.640143  5581 caffe.cpp:501] detection_eval = 0.0480477
-I0511 11:50:55.640148  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640153  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640157  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640162  5581 caffe.cpp:501] detection_eval = 6.08871
-I0511 11:50:55.640167  5581 caffe.cpp:501] detection_eval = 0.0412229
-I0511 11:50:55.640172  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640177  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640180  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640185  5581 caffe.cpp:501] detection_eval = 6.11694
-I0511 11:50:55.640190  5581 caffe.cpp:501] detection_eval = 0.0411029
-I0511 11:50:55.640195  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640200  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.640204  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640209  5581 caffe.cpp:501] detection_eval = 6.26815
-I0511 11:50:55.640213  5581 caffe.cpp:501] detection_eval = 0.0398907
-I0511 11:50:55.640218  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640223  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640226  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640230  5581 caffe.cpp:501] detection_eval = 6.33468
-I0511 11:50:55.640235  5581 caffe.cpp:501] detection_eval = 0.0437772
-I0511 11:50:55.640240  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640245  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640250  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640254  5581 caffe.cpp:501] detection_eval = 6.42339
-I0511 11:50:55.640259  5581 caffe.cpp:501] detection_eval = 0.039532
-I0511 11:50:55.640264  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.640269  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640274  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640277  5581 caffe.cpp:501] detection_eval = 6.49597
-I0511 11:50:55.640281  5581 caffe.cpp:501] detection_eval = 0.0400402
-I0511 11:50:55.640286  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.640290  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640295  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640300  5581 caffe.cpp:501] detection_eval = 6.6371
-I0511 11:50:55.640305  5581 caffe.cpp:501] detection_eval = 0.048498
-I0511 11:50:55.640310  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640313  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.640318  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640323  5581 caffe.cpp:501] detection_eval = 6.65121
-I0511 11:50:55.640328  5581 caffe.cpp:501] detection_eval = 0.0427957
-I0511 11:50:55.640332  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640337  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.640341  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640347  5581 caffe.cpp:501] detection_eval = 6.75806
-I0511 11:50:55.640352  5581 caffe.cpp:501] detection_eval = 0.0484034
-I0511 11:50:55.640357  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640360  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.640365  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640369  5581 caffe.cpp:501] detection_eval = 6.83065
-I0511 11:50:55.640373  5581 caffe.cpp:501] detection_eval = 0.0446842
-I0511 11:50:55.640383  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640388  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640393  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640398  5581 caffe.cpp:501] detection_eval = 6.90323
-I0511 11:50:55.640403  5581 caffe.cpp:501] detection_eval = 0.0414079
-I0511 11:50:55.640408  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640413  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640416  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640421  5581 caffe.cpp:501] detection_eval = 6.95161
-I0511 11:50:55.640425  5581 caffe.cpp:501] detection_eval = 0.0429655
-I0511 11:50:55.640430  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640434  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640439  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640449  5581 caffe.cpp:501] detection_eval = 6.9879
-I0511 11:50:55.640453  5581 caffe.cpp:501] detection_eval = 0.0390551
-I0511 11:50:55.640457  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640462  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640467  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640472  5581 caffe.cpp:501] detection_eval = 7.08468
-I0511 11:50:55.640477  5581 caffe.cpp:501] detection_eval = 0.0442344
-I0511 11:50:55.640482  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640486  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640491  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640496  5581 caffe.cpp:501] detection_eval = 7.15121
-I0511 11:50:55.640499  5581 caffe.cpp:501] detection_eval = 0.0426983
-I0511 11:50:55.640504  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640509  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.640514  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640518  5581 caffe.cpp:501] detection_eval = 7.24798
-I0511 11:50:55.640522  5581 caffe.cpp:501] detection_eval = 0.0426494
-I0511 11:50:55.640533  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.640537  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640544  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.640565  5581 caffe.cpp:501] detection_eval = 7.35484
-I0511 11:50:55.640583  5581 caffe.cpp:501] detection_eval = 0.0417271
-I0511 11:50:55.640594  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640602  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.640607  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640612  5581 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:50:55.640616  5581 caffe.cpp:501] detection_eval = 0.0406579
-I0511 11:50:55.640621  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640625  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.640630  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640640  5581 caffe.cpp:501] detection_eval = 7.49597
-I0511 11:50:55.640650  5581 caffe.cpp:501] detection_eval = 0.0428491
-I0511 11:50:55.640662  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.640673  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.640686  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640697  5581 caffe.cpp:501] detection_eval = 7.58669
-I0511 11:50:55.640708  5581 caffe.cpp:501] detection_eval = 0.0414093
-I0511 11:50:55.640714  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640719  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640724  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640729  5581 caffe.cpp:501] detection_eval = 7.63508
-I0511 11:50:55.640734  5581 caffe.cpp:501] detection_eval = 0.037889
-I0511 11:50:55.640739  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.640744  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.640749  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640754  5581 caffe.cpp:501] detection_eval = 7.75806
-I0511 11:50:55.640765  5581 caffe.cpp:501] detection_eval = 0.0415663
-I0511 11:50:55.640777  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.640789  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640799  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640810  5581 caffe.cpp:501] detection_eval = 7.86895
-I0511 11:50:55.640818  5581 caffe.cpp:501] detection_eval = 0.0495166
-I0511 11:50:55.640823  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640828  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.640832  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640837  5581 caffe.cpp:501] detection_eval = 7.97782
-I0511 11:50:55.640842  5581 caffe.cpp:501] detection_eval = 0.0460135
-I0511 11:50:55.640847  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640852  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.640857  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640862  5581 caffe.cpp:501] detection_eval = 8.05444
-I0511 11:50:55.640867  5581 caffe.cpp:501] detection_eval = 0.0421181
-I0511 11:50:55.640872  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640877  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.640882  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640887  5581 caffe.cpp:501] detection_eval = 8.14919
-I0511 11:50:55.640892  5581 caffe.cpp:501] detection_eval = 0.0403573
-I0511 11:50:55.640897  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.640902  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.640907  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640915  5581 caffe.cpp:501] detection_eval = 8.24597
-I0511 11:50:55.640924  5581 caffe.cpp:501] detection_eval = 0.0420401
-I0511 11:50:55.640933  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.640942  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.640949  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.640956  5581 caffe.cpp:501] detection_eval = 8.34476
-I0511 11:50:55.640961  5581 caffe.cpp:501] detection_eval = 0.0467141
-I0511 11:50:55.640970  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.640976  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.640981  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.640990  5581 caffe.cpp:501] detection_eval = 8.39315
-I0511 11:50:55.640998  5581 caffe.cpp:501] detection_eval = 0.0470415
-I0511 11:50:55.641005  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.641012  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.641018  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.641026  5581 caffe.cpp:501] detection_eval = 8.44758
-I0511 11:50:55.641032  5581 caffe.cpp:501] detection_eval = 0.0435731
-I0511 11:50:55.641041  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.641047  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641054  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.641060  5581 caffe.cpp:501] detection_eval = 8.52218
-I0511 11:50:55.641068  5581 caffe.cpp:501] detection_eval = 0.0439346
-I0511 11:50:55.641074  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.641083  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.641088  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.641093  5581 caffe.cpp:501] detection_eval = 8.65323
-I0511 11:50:55.641098  5581 caffe.cpp:501] detection_eval = 0.045293
-I0511 11:50:55.641103  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.641108  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.641113  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.641119  5581 caffe.cpp:501] detection_eval = 8.72379
-I0511 11:50:55.641124  5581 caffe.cpp:501] detection_eval = 0.0451606
-I0511 11:50:55.641129  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.641134  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.641139  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641149  5581 caffe.cpp:501] detection_eval = 8.76411
-I0511 11:50:55.641155  5581 caffe.cpp:501] detection_eval = 0.0453022
-I0511 11:50:55.641158  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.641163  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.641168  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641173  5581 caffe.cpp:501] detection_eval = 8.79839
-I0511 11:50:55.641178  5581 caffe.cpp:501] detection_eval = 0.0459531
-I0511 11:50:55.641183  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.641187  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.641191  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641196  5581 caffe.cpp:501] detection_eval = 8.84879
-I0511 11:50:55.641201  5581 caffe.cpp:501] detection_eval = 0.0440237
-I0511 11:50:55.641206  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.641211  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.641216  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641219  5581 caffe.cpp:501] detection_eval = 8.91129
-I0511 11:50:55.641224  5581 caffe.cpp:501] detection_eval = 0.0421023
-I0511 11:50:55.641229  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641234  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.641238  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641243  5581 caffe.cpp:501] detection_eval = 8.97782
-I0511 11:50:55.641247  5581 caffe.cpp:501] detection_eval = 0.0424941
-I0511 11:50:55.641252  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641257  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641261  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641266  5581 caffe.cpp:501] detection_eval = 9.06048
-I0511 11:50:55.641271  5581 caffe.cpp:501] detection_eval = 0.0413233
-I0511 11:50:55.641275  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641280  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641285  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641290  5581 caffe.cpp:501] detection_eval = 9.14113
-I0511 11:50:55.641294  5581 caffe.cpp:501] detection_eval = 0.0394532
-I0511 11:50:55.641299  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.641304  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641314  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641319  5581 caffe.cpp:501] detection_eval = 9.28427
-I0511 11:50:55.641324  5581 caffe.cpp:501] detection_eval = 0.0466154
-I0511 11:50:55.641329  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641333  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641340  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641345  5581 caffe.cpp:501] detection_eval = 9.33065
-I0511 11:50:55.641355  5581 caffe.cpp:501] detection_eval = 0.0391784
-I0511 11:50:55.641366  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.641376  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641386  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.641397  5581 caffe.cpp:501] detection_eval = 9.41935
-I0511 11:50:55.641407  5581 caffe.cpp:501] detection_eval = 0.0399461
-I0511 11:50:55.641412  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.641417  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.641422  5581 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:50:55.641427  5581 caffe.cpp:501] detection_eval = 9.45363
-I0511 11:50:55.641433  5581 caffe.cpp:501] detection_eval = 0.0418448
-I0511 11:50:55.641438  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.641441  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641446  5581 caffe.cpp:501] detection_eval = 0.0342742
-I0511 11:50:55.641451  5581 caffe.cpp:501] detection_eval = 9.53629
-I0511 11:50:55.641456  5581 caffe.cpp:501] detection_eval = 0.0411611
-I0511 11:50:55.641461  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641466  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.641475  5581 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:50:55.641481  5581 caffe.cpp:501] detection_eval = 9.56855
-I0511 11:50:55.641487  5581 caffe.cpp:501] detection_eval = 0.0487977
-I0511 11:50:55.641492  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641501  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.641506  5581 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:50:55.641511  5581 caffe.cpp:501] detection_eval = 9.64516
-I0511 11:50:55.641515  5581 caffe.cpp:501] detection_eval = 0.0457145
-I0511 11:50:55.641520  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641525  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641530  5581 caffe.cpp:501] detection_eval = 0.0403226
-I0511 11:50:55.641535  5581 caffe.cpp:501] detection_eval = 9.66935
-I0511 11:50:55.641541  5581 caffe.cpp:501] detection_eval = 0.043002
-I0511 11:50:55.641546  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.641551  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641554  5581 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:50:55.641559  5581 caffe.cpp:501] detection_eval = 9.71371
-I0511 11:50:55.641564  5581 caffe.cpp:501] detection_eval = 0.0434862
-I0511 11:50:55.641571  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641580  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641592  5581 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:50:55.641602  5581 caffe.cpp:501] detection_eval = 9.76815
-I0511 11:50:55.641613  5581 caffe.cpp:501] detection_eval = 0.0448317
-I0511 11:50:55.641623  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.641634  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641644  5581 caffe.cpp:501] detection_eval = 0.0423387
-I0511 11:50:55.641651  5581 caffe.cpp:501] detection_eval = 9.84274
-I0511 11:50:55.641656  5581 caffe.cpp:501] detection_eval = 0.0405645
-I0511 11:50:55.641661  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641665  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641670  5581 caffe.cpp:501] detection_eval = 0.0443548
-I0511 11:50:55.641675  5581 caffe.cpp:501] detection_eval = 9.86492
-I0511 11:50:55.641680  5581 caffe.cpp:501] detection_eval = 0.0451478
-I0511 11:50:55.641685  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.641690  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641695  5581 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:50:55.641700  5581 caffe.cpp:501] detection_eval = 9.86492
-I0511 11:50:55.641705  5581 caffe.cpp:501] detection_eval = 0.0396386
-I0511 11:50:55.641710  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641715  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641724  5581 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:50:55.641736  5581 caffe.cpp:501] detection_eval = 9.93952
-I0511 11:50:55.641746  5581 caffe.cpp:501] detection_eval = 0.0448263
-I0511 11:50:55.641757  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641767  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641772  5581 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:50:55.641777  5581 caffe.cpp:501] detection_eval = 10.0323
-I0511 11:50:55.641783  5581 caffe.cpp:501] detection_eval = 0.0429454
-I0511 11:50:55.641790  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641798  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.641803  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641808  5581 caffe.cpp:501] detection_eval = 10.0464
-I0511 11:50:55.641813  5581 caffe.cpp:501] detection_eval = 0.0451522
-I0511 11:50:55.641819  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641830  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.641840  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641851  5581 caffe.cpp:501] detection_eval = 10.121
-I0511 11:50:55.641862  5581 caffe.cpp:501] detection_eval = 0.0435291
-I0511 11:50:55.641873  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.641890  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.641894  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641899  5581 caffe.cpp:501] detection_eval = 10.2218
-I0511 11:50:55.641904  5581 caffe.cpp:501] detection_eval = 0.0490495
-I0511 11:50:55.641909  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.641916  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.641921  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641924  5581 caffe.cpp:501] detection_eval = 10.2702
-I0511 11:50:55.641929  5581 caffe.cpp:501] detection_eval = 0.0389256
-I0511 11:50:55.641934  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.641939  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641944  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.641949  5581 caffe.cpp:501] detection_eval = 10.3589
-I0511 11:50:55.641954  5581 caffe.cpp:501] detection_eval = 0.0411403
-I0511 11:50:55.641958  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.641963  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.641968  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.641973  5581 caffe.cpp:501] detection_eval = 10.4476
-I0511 11:50:55.641983  5581 caffe.cpp:501] detection_eval = 0.0496988
-I0511 11:50:55.641991  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642001  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.642012  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642021  5581 caffe.cpp:501] detection_eval = 10.5161
-I0511 11:50:55.642030  5581 caffe.cpp:501] detection_eval = 0.0399565
-I0511 11:50:55.642035  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.642040  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642045  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642050  5581 caffe.cpp:501] detection_eval = 10.5948
-I0511 11:50:55.642055  5581 caffe.cpp:501] detection_eval = 0.0397837
-I0511 11:50:55.642060  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.642063  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.642068  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642073  5581 caffe.cpp:501] detection_eval = 10.6895
-I0511 11:50:55.642077  5581 caffe.cpp:501] detection_eval = 0.0466224
-I0511 11:50:55.642082  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.642088  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.642097  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642107  5581 caffe.cpp:501] detection_eval = 10.7742
-I0511 11:50:55.642117  5581 caffe.cpp:501] detection_eval = 0.0444724
-I0511 11:50:55.642127  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642138  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642146  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.642155  5581 caffe.cpp:501] detection_eval = 10.8851
-I0511 11:50:55.642165  5581 caffe.cpp:501] detection_eval = 0.0498522
-I0511 11:50:55.642175  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.642184  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.642190  5581 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:50:55.642195  5581 caffe.cpp:501] detection_eval = 10.9012
-I0511 11:50:55.642200  5581 caffe.cpp:501] detection_eval = 0.0456841
-I0511 11:50:55.642204  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642210  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.642213  5581 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:50:55.642218  5581 caffe.cpp:501] detection_eval = 10.996
-I0511 11:50:55.642223  5581 caffe.cpp:501] detection_eval = 0.0469158
-I0511 11:50:55.642227  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.642232  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.642237  5581 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:50:55.642247  5581 caffe.cpp:501] detection_eval = 11.0847
-I0511 11:50:55.642252  5581 caffe.cpp:501] detection_eval = 0.0454253
-I0511 11:50:55.642261  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.642271  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.642278  5581 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:50:55.642288  5581 caffe.cpp:501] detection_eval = 11.121
-I0511 11:50:55.642300  5581 caffe.cpp:501] detection_eval = 0.0476964
-I0511 11:50:55.642310  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642318  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.642328  5581 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:50:55.642331  5581 caffe.cpp:501] detection_eval = 11.2056
-I0511 11:50:55.642340  5581 caffe.cpp:501] detection_eval = 0.0415643
-I0511 11:50:55.642344  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642352  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.642356  5581 caffe.cpp:501] detection_eval = 0.0564516
-I0511 11:50:55.642364  5581 caffe.cpp:501] detection_eval = 11.25
-I0511 11:50:55.642369  5581 caffe.cpp:501] detection_eval = 0.0445424
-I0511 11:50:55.642377  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642381  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642390  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642395  5581 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:50:55.642403  5581 caffe.cpp:501] detection_eval = 0.0435517
-I0511 11:50:55.642408  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.642412  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.642416  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642424  5581 caffe.cpp:501] detection_eval = 11.3367
-I0511 11:50:55.642428  5581 caffe.cpp:501] detection_eval = 0.0463047
-I0511 11:50:55.642437  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.642441  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.642449  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642453  5581 caffe.cpp:501] detection_eval = 11.4052
-I0511 11:50:55.642462  5581 caffe.cpp:501] detection_eval = 0.0468383
-I0511 11:50:55.642467  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.642474  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.642478  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642487  5581 caffe.cpp:501] detection_eval = 11.4677
-I0511 11:50:55.642491  5581 caffe.cpp:501] detection_eval = 0.0410226
-I0511 11:50:55.642499  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.642506  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642514  5581 caffe.cpp:501] detection_eval = 0.0584677
-I0511 11:50:55.642518  5581 caffe.cpp:501] detection_eval = 11.502
-I0511 11:50:55.642526  5581 caffe.cpp:501] detection_eval = 0.0382867
-I0511 11:50:55.642531  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642540  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642549  5581 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:50:55.642558  5581 caffe.cpp:501] detection_eval = 11.5484
-I0511 11:50:55.642568  5581 caffe.cpp:501] detection_eval = 0.0419781
-I0511 11:50:55.642577  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642587  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642597  5581 caffe.cpp:501] detection_eval = 0.0604839
-I0511 11:50:55.642606  5581 caffe.cpp:501] detection_eval = 11.5948
-I0511 11:50:55.642616  5581 caffe.cpp:501] detection_eval = 0.0414562
-I0511 11:50:55.642626  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642634  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642643  5581 caffe.cpp:501] detection_eval = 0.0625
-I0511 11:50:55.642653  5581 caffe.cpp:501] detection_eval = 11.6331
-I0511 11:50:55.642663  5581 caffe.cpp:501] detection_eval = 0.0410472
-I0511 11:50:55.642673  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642683  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642693  5581 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:50:55.642702  5581 caffe.cpp:501] detection_eval = 11.6855
-I0511 11:50:55.642714  5581 caffe.cpp:501] detection_eval = 0.0405388
-I0511 11:50:55.642724  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.642729  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.642736  5581 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:50:55.642742  5581 caffe.cpp:501] detection_eval = 11.754
-I0511 11:50:55.642751  5581 caffe.cpp:501] detection_eval = 0.0414713
-I0511 11:50:55.642756  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.642765  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.642768  5581 caffe.cpp:501] detection_eval = 0.0645161
-I0511 11:50:55.642776  5581 caffe.cpp:501] detection_eval = 11.8347
-I0511 11:50:55.642782  5581 caffe.cpp:501] detection_eval = 0.0419868
-I0511 11:50:55.642791  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.642802  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.642812  5581 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:50:55.642820  5581 caffe.cpp:501] detection_eval = 11.8952
-I0511 11:50:55.642830  5581 caffe.cpp:501] detection_eval = 0.0380018
-I0511 11:50:55.642840  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.642850  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.642860  5581 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:50:55.642869  5581 caffe.cpp:501] detection_eval = 12.0161
-I0511 11:50:55.642879  5581 caffe.cpp:501] detection_eval = 0.0432168
-I0511 11:50:55.642890  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.642895  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.642904  5581 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:50:55.642909  5581 caffe.cpp:501] detection_eval = 12.0565
-I0511 11:50:55.642916  5581 caffe.cpp:501] detection_eval = 0.0387167
-I0511 11:50:55.642921  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642930  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.642933  5581 caffe.cpp:501] detection_eval = 0.0665323
-I0511 11:50:55.642941  5581 caffe.cpp:501] detection_eval = 12.1149
-I0511 11:50:55.642946  5581 caffe.cpp:501] detection_eval = 0.0401728
-I0511 11:50:55.642954  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.642958  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.642967  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.642972  5581 caffe.cpp:501] detection_eval = 12.131
-I0511 11:50:55.642980  5581 caffe.cpp:501] detection_eval = 0.0417049
-I0511 11:50:55.642984  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.642992  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.642997  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.643005  5581 caffe.cpp:501] detection_eval = 12.1855
-I0511 11:50:55.643009  5581 caffe.cpp:501] detection_eval = 0.0408608
-I0511 11:50:55.643018  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.643021  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643029  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.643034  5581 caffe.cpp:501] detection_eval = 12.244
-I0511 11:50:55.643043  5581 caffe.cpp:501] detection_eval = 0.0384291
-I0511 11:50:55.643048  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.643057  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.643065  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.643074  5581 caffe.cpp:501] detection_eval = 12.3125
-I0511 11:50:55.643079  5581 caffe.cpp:501] detection_eval = 0.0450185
-I0511 11:50:55.643087  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.643091  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.643100  5581 caffe.cpp:501] detection_eval = 0.0705645
-I0511 11:50:55.643103  5581 caffe.cpp:501] detection_eval = 12.3609
-I0511 11:50:55.643111  5581 caffe.cpp:501] detection_eval = 0.0436057
-I0511 11:50:55.643116  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643124  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.643128  5581 caffe.cpp:501] detection_eval = 0.0745968
-I0511 11:50:55.643137  5581 caffe.cpp:501] detection_eval = 12.3528
-I0511 11:50:55.643147  5581 caffe.cpp:501] detection_eval = 0.0433886
-I0511 11:50:55.643152  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.643160  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643165  5581 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:50:55.643174  5581 caffe.cpp:501] detection_eval = 12.381
-I0511 11:50:55.643179  5581 caffe.cpp:501] detection_eval = 0.04524
-I0511 11:50:55.643187  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643191  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.643200  5581 caffe.cpp:501] detection_eval = 0.0766129
-I0511 11:50:55.643205  5581 caffe.cpp:501] detection_eval = 12.4335
-I0511 11:50:55.643213  5581 caffe.cpp:501] detection_eval = 0.0384115
-I0511 11:50:55.643218  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643226  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643230  5581 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:50:55.643239  5581 caffe.cpp:501] detection_eval = 12.4677
-I0511 11:50:55.643242  5581 caffe.cpp:501] detection_eval = 0.0406575
-I0511 11:50:55.643247  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643251  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643256  5581 caffe.cpp:501] detection_eval = 0.078629
-I0511 11:50:55.643261  5581 caffe.cpp:501] detection_eval = 12.5302
-I0511 11:50:55.643265  5581 caffe.cpp:501] detection_eval = 0.0391606
-I0511 11:50:55.643270  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.643275  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.643281  5581 caffe.cpp:501] detection_eval = 0.0806452
-I0511 11:50:55.643285  5581 caffe.cpp:501] detection_eval = 12.6129
-I0511 11:50:55.643291  5581 caffe.cpp:501] detection_eval = 0.0460983
-I0511 11:50:55.643297  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.643304  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643309  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643314  5581 caffe.cpp:501] detection_eval = 12.7198
-I0511 11:50:55.643319  5581 caffe.cpp:501] detection_eval = 0.0505505
-I0511 11:50:55.643323  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.643328  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.643333  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643337  5581 caffe.cpp:501] detection_eval = 12.8266
-I0511 11:50:55.643343  5581 caffe.cpp:501] detection_eval = 0.0519473
-I0511 11:50:55.643348  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643352  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643358  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643363  5581 caffe.cpp:501] detection_eval = 12.8992
-I0511 11:50:55.643368  5581 caffe.cpp:501] detection_eval = 0.0499161
-I0511 11:50:55.643373  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.643378  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.643384  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643394  5581 caffe.cpp:501] detection_eval = 12.9415
-I0511 11:50:55.643405  5581 caffe.cpp:501] detection_eval = 0.0458294
-I0511 11:50:55.643416  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643427  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.643437  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643448  5581 caffe.cpp:501] detection_eval = 13.0242
-I0511 11:50:55.643456  5581 caffe.cpp:501] detection_eval = 0.0417185
-I0511 11:50:55.643461  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643466  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.643471  5581 caffe.cpp:501] detection_eval = 0.0826613
-I0511 11:50:55.643476  5581 caffe.cpp:501] detection_eval = 13.0645
-I0511 11:50:55.643481  5581 caffe.cpp:501] detection_eval = 0.0405417
-I0511 11:50:55.643486  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643491  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643501  5581 caffe.cpp:501] detection_eval = 0.0866935
-I0511 11:50:55.643518  5581 caffe.cpp:501] detection_eval = 13.0423
-I0511 11:50:55.643530  5581 caffe.cpp:501] detection_eval = 0.0371573
-I0511 11:50:55.643540  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.643553  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.643563  5581 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:50:55.643571  5581 caffe.cpp:501] detection_eval = 13.0827
-I0511 11:50:55.643576  5581 caffe.cpp:501] detection_eval = 0.0410347
-I0511 11:50:55.643585  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.643590  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.643601  5581 caffe.cpp:501] detection_eval = 0.0887097
-I0511 11:50:55.643610  5581 caffe.cpp:501] detection_eval = 13.1431
-I0511 11:50:55.643621  5581 caffe.cpp:501] detection_eval = 0.0439197
-I0511 11:50:55.643633  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.643645  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.643654  5581 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:50:55.643663  5581 caffe.cpp:501] detection_eval = 13.1794
-I0511 11:50:55.643668  5581 caffe.cpp:501] detection_eval = 0.0455159
-I0511 11:50:55.643676  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643682  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643694  5581 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:50:55.643699  5581 caffe.cpp:501] detection_eval = 13.2339
-I0511 11:50:55.643703  5581 caffe.cpp:501] detection_eval = 0.0469671
-I0511 11:50:55.643712  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.643724  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.643733  5581 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:50:55.643744  5581 caffe.cpp:501] detection_eval = 13.3044
-I0511 11:50:55.643755  5581 caffe.cpp:501] detection_eval = 0.0425159
-I0511 11:50:55.643766  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643777  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643788  5581 caffe.cpp:501] detection_eval = 0.0927419
-I0511 11:50:55.643800  5581 caffe.cpp:501] detection_eval = 13.3327
-I0511 11:50:55.643810  5581 caffe.cpp:501] detection_eval = 0.0395842
-I0511 11:50:55.643821  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.643832  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.643843  5581 caffe.cpp:501] detection_eval = 0.0927419
-I0511 11:50:55.643853  5581 caffe.cpp:501] detection_eval = 13.3992
-I0511 11:50:55.643862  5581 caffe.cpp:501] detection_eval = 0.0415257
-I0511 11:50:55.643867  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643877  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.643882  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.643890  5581 caffe.cpp:501] detection_eval = 13.4395
-I0511 11:50:55.643895  5581 caffe.cpp:501] detection_eval = 0.0437205
-I0511 11:50:55.643904  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.643909  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.643918  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.643924  5581 caffe.cpp:501] detection_eval = 13.4758
-I0511 11:50:55.643934  5581 caffe.cpp:501] detection_eval = 0.037161
-I0511 11:50:55.643939  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.643946  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.643952  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.643960  5581 caffe.cpp:501] detection_eval = 13.5282
-I0511 11:50:55.643966  5581 caffe.cpp:501] detection_eval = 0.0394226
-I0511 11:50:55.643975  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.643985  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.643995  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.644006  5581 caffe.cpp:501] detection_eval = 13.5706
-I0511 11:50:55.644017  5581 caffe.cpp:501] detection_eval = 0.0361466
-I0511 11:50:55.644027  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644038  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.644049  5581 caffe.cpp:501] detection_eval = 0.0947581
-I0511 11:50:55.644059  5581 caffe.cpp:501] detection_eval = 13.625
-I0511 11:50:55.644064  5581 caffe.cpp:501] detection_eval = 0.0402962
-I0511 11:50:55.644073  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.644083  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.644088  5581 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:50:55.644098  5581 caffe.cpp:501] detection_eval = 13.6532
-I0511 11:50:55.644102  5581 caffe.cpp:501] detection_eval = 0.0436865
-I0511 11:50:55.644111  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.644117  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.644125  5581 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:50:55.644131  5581 caffe.cpp:501] detection_eval = 13.6835
-I0511 11:50:55.644140  5581 caffe.cpp:501] detection_eval = 0.0398312
-I0511 11:50:55.644148  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644158  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.644170  5581 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:50:55.644181  5581 caffe.cpp:501] detection_eval = 13.7258
-I0511 11:50:55.644191  5581 caffe.cpp:501] detection_eval = 0.0427413
-I0511 11:50:55.644202  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.644215  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.644232  5581 caffe.cpp:501] detection_eval = 0.0967742
-I0511 11:50:55.644240  5581 caffe.cpp:501] detection_eval = 13.7944
-I0511 11:50:55.644253  5581 caffe.cpp:501] detection_eval = 0.038353
-I0511 11:50:55.644263  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.644273  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.644279  5581 caffe.cpp:501] detection_eval = 0.0987903
-I0511 11:50:55.644289  5581 caffe.cpp:501] detection_eval = 13.7964
-I0511 11:50:55.644294  5581 caffe.cpp:501] detection_eval = 0.0400739
-I0511 11:50:55.644302  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644309  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.644317  5581 caffe.cpp:501] detection_eval = 0.0987903
-I0511 11:50:55.644322  5581 caffe.cpp:501] detection_eval = 13.8649
-I0511 11:50:55.644332  5581 caffe.cpp:501] detection_eval = 0.0441469
-I0511 11:50:55.644337  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.644345  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.644351  5581 caffe.cpp:501] detection_eval = 0.100806
-I0511 11:50:55.644361  5581 caffe.cpp:501] detection_eval = 13.9173
-I0511 11:50:55.644366  5581 caffe.cpp:501] detection_eval = 0.0413464
-I0511 11:50:55.644374  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.644381  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.644389  5581 caffe.cpp:501] detection_eval = 0.100806
-I0511 11:50:55.644394  5581 caffe.cpp:501] detection_eval = 13.9556
-I0511 11:50:55.644403  5581 caffe.cpp:501] detection_eval = 0.0382349
-I0511 11:50:55.644409  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.644418  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.644423  5581 caffe.cpp:501] detection_eval = 0.100806
-I0511 11:50:55.644433  5581 caffe.cpp:501] detection_eval = 14.002
-I0511 11:50:55.644438  5581 caffe.cpp:501] detection_eval = 0.0338957
-I0511 11:50:55.644446  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644453  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644460  5581 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:50:55.644466  5581 caffe.cpp:501] detection_eval = 13.996
-I0511 11:50:55.644475  5581 caffe.cpp:501] detection_eval = 0.0405347
-I0511 11:50:55.644480  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.644490  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.644495  5581 caffe.cpp:501] detection_eval = 0.104839
-I0511 11:50:55.644503  5581 caffe.cpp:501] detection_eval = 14.0383
-I0511 11:50:55.644510  5581 caffe.cpp:501] detection_eval = 0.0392191
-I0511 11:50:55.644517  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.644546  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.644556  5581 caffe.cpp:501] detection_eval = 0.106855
-I0511 11:50:55.644562  5581 caffe.cpp:501] detection_eval = 14.0464
-I0511 11:50:55.644570  5581 caffe.cpp:501] detection_eval = 0.0358572
-I0511 11:50:55.644580  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644585  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644594  5581 caffe.cpp:501] detection_eval = 0.106855
-I0511 11:50:55.644603  5581 caffe.cpp:501] detection_eval = 14.1028
-I0511 11:50:55.644611  5581 caffe.cpp:501] detection_eval = 0.0331913
-I0511 11:50:55.644616  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.644625  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644630  5581 caffe.cpp:501] detection_eval = 0.106855
-I0511 11:50:55.644639  5581 caffe.cpp:501] detection_eval = 14.125
-I0511 11:50:55.644644  5581 caffe.cpp:501] detection_eval = 0.0355084
-I0511 11:50:55.644659  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644668  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644680  5581 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:50:55.644690  5581 caffe.cpp:501] detection_eval = 14.1391
-I0511 11:50:55.644701  5581 caffe.cpp:501] detection_eval = 0.043656
-I0511 11:50:55.644709  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.644724  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.644728  5581 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:50:55.644732  5581 caffe.cpp:501] detection_eval = 14.1694
-I0511 11:50:55.644742  5581 caffe.cpp:501] detection_eval = 0.0400982
-I0511 11:50:55.644747  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.644757  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.644765  5581 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:50:55.644770  5581 caffe.cpp:501] detection_eval = 14.2157
-I0511 11:50:55.644779  5581 caffe.cpp:501] detection_eval = 0.0381633
-I0511 11:50:55.644784  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644793  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644800  5581 caffe.cpp:501] detection_eval = 0.108871
-I0511 11:50:55.644809  5581 caffe.cpp:501] detection_eval = 14.2641
-I0511 11:50:55.644817  5581 caffe.cpp:501] detection_eval = 0.0326405
-I0511 11:50:55.644824  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.644835  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644845  5581 caffe.cpp:501] detection_eval = 0.112903
-I0511 11:50:55.644856  5581 caffe.cpp:501] detection_eval = 14.2399
-I0511 11:50:55.644867  5581 caffe.cpp:501] detection_eval = 0.0350096
-I0511 11:50:55.644878  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644886  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644896  5581 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:50:55.644901  5581 caffe.cpp:501] detection_eval = 14.2661
-I0511 11:50:55.644909  5581 caffe.cpp:501] detection_eval = 0.0319027
-I0511 11:50:55.644915  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.644923  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.644929  5581 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:50:55.644937  5581 caffe.cpp:501] detection_eval = 14.3085
-I0511 11:50:55.644943  5581 caffe.cpp:501] detection_eval = 0.0341428
-I0511 11:50:55.644953  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.644958  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.644965  5581 caffe.cpp:501] detection_eval = 0.114919
-I0511 11:50:55.644974  5581 caffe.cpp:501] detection_eval = 14.3327
-I0511 11:50:55.644980  5581 caffe.cpp:501] detection_eval = 0.0308989
-I0511 11:50:55.644994  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.644999  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.645007  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645014  5581 caffe.cpp:501] detection_eval = 14.3387
-I0511 11:50:55.645022  5581 caffe.cpp:501] detection_eval = 0.034269
-I0511 11:50:55.645032  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645041  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645051  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645062  5581 caffe.cpp:501] detection_eval = 14.377
-I0511 11:50:55.645078  5581 caffe.cpp:501] detection_eval = 0.0313198
-I0511 11:50:55.645093  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.645104  5581 caffe.cpp:501] detection_eval = 1
-I0511 11:50:55.645115  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645126  5581 caffe.cpp:501] detection_eval = 14.4274
-I0511 11:50:55.645138  5581 caffe.cpp:501] detection_eval = 0.0345124
-I0511 11:50:55.645148  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.645157  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.645164  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645170  5581 caffe.cpp:501] detection_eval = 14.4597
-I0511 11:50:55.645179  5581 caffe.cpp:501] detection_eval = 0.0330961
-I0511 11:50:55.645184  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645191  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645196  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645205  5581 caffe.cpp:501] detection_eval = 14.506
-I0511 11:50:55.645210  5581 caffe.cpp:501] detection_eval = 0.0319597
-I0511 11:50:55.645220  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645236  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645242  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.645253  5581 caffe.cpp:501] detection_eval = 14.5585
-I0511 11:50:55.645258  5581 caffe.cpp:501] detection_eval = 0.0339037
-I0511 11:50:55.645267  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645272  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645282  5581 caffe.cpp:501] detection_eval = 0.120968
-I0511 11:50:55.645287  5581 caffe.cpp:501] detection_eval = 14.5827
-I0511 11:50:55.645295  5581 caffe.cpp:501] detection_eval = 0.0324709
-I0511 11:50:55.645305  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645316  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645326  5581 caffe.cpp:501] detection_eval = 0.120968
-I0511 11:50:55.645337  5581 caffe.cpp:501] detection_eval = 14.619
-I0511 11:50:55.645349  5581 caffe.cpp:501] detection_eval = 0.034883
-I0511 11:50:55.645359  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.645370  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645380  5581 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:50:55.645387  5581 caffe.cpp:501] detection_eval = 14.6089
-I0511 11:50:55.645396  5581 caffe.cpp:501] detection_eval = 0.0312104
-I0511 11:50:55.645406  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.645411  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645421  5581 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:50:55.645426  5581 caffe.cpp:501] detection_eval = 14.6573
-I0511 11:50:55.645434  5581 caffe.cpp:501] detection_eval = 0.0334001
-I0511 11:50:55.645440  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645449  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.645454  5581 caffe.cpp:501] detection_eval = 0.122984
-I0511 11:50:55.645465  5581 caffe.cpp:501] detection_eval = 14.7117
-I0511 11:50:55.645474  5581 caffe.cpp:501] detection_eval = 0.0315325
-I0511 11:50:55.645485  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.645495  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.645506  5581 caffe.cpp:501] detection_eval = 0.125
-I0511 11:50:55.645516  5581 caffe.cpp:501] detection_eval = 14.7097
-I0511 11:50:55.645529  5581 caffe.cpp:501] detection_eval = 0.0336649
-I0511 11:50:55.645539  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645548  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645553  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645562  5581 caffe.cpp:501] detection_eval = 14.7117
-I0511 11:50:55.645571  5581 caffe.cpp:501] detection_eval = 0.0368732
-I0511 11:50:55.645581  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.645586  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645594  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645603  5581 caffe.cpp:501] detection_eval = 14.7641
-I0511 11:50:55.645609  5581 caffe.cpp:501] detection_eval = 0.0349081
-I0511 11:50:55.645617  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.645623  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.645632  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645637  5581 caffe.cpp:501] detection_eval = 14.8427
-I0511 11:50:55.645645  5581 caffe.cpp:501] detection_eval = 0.0354973
-I0511 11:50:55.645650  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645659  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.645664  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645673  5581 caffe.cpp:501] detection_eval = 14.9052
-I0511 11:50:55.645679  5581 caffe.cpp:501] detection_eval = 0.0350628
-I0511 11:50:55.645687  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645694  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.645701  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645706  5581 caffe.cpp:501] detection_eval = 14.9819
-I0511 11:50:55.645718  5581 caffe.cpp:501] detection_eval = 0.0350495
-I0511 11:50:55.645723  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.645727  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.645735  5581 caffe.cpp:501] detection_eval = 0.127016
-I0511 11:50:55.645745  5581 caffe.cpp:501] detection_eval = 15.0827
-I0511 11:50:55.645750  5581 caffe.cpp:501] detection_eval = 0.0356054
-I0511 11:50:55.645757  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645763  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.645771  5581 caffe.cpp:501] detection_eval = 0.131048
-I0511 11:50:55.645776  5581 caffe.cpp:501] detection_eval = 15.1109
-I0511 11:50:55.645786  5581 caffe.cpp:501] detection_eval = 0.0375291
-I0511 11:50:55.645790  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.645799  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.645804  5581 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:50:55.645813  5581 caffe.cpp:501] detection_eval = 15.0867
-I0511 11:50:55.645820  5581 caffe.cpp:501] detection_eval = 0.0346692
-I0511 11:50:55.645829  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.645834  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.645843  5581 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:50:55.645848  5581 caffe.cpp:501] detection_eval = 15.1774
-I0511 11:50:55.645856  5581 caffe.cpp:501] detection_eval = 0.0387023
-I0511 11:50:55.645862  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.645870  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.645876  5581 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:50:55.645884  5581 caffe.cpp:501] detection_eval = 15.2782
-I0511 11:50:55.645890  5581 caffe.cpp:501] detection_eval = 0.0381264
-I0511 11:50:55.645901  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.645910  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.645921  5581 caffe.cpp:501] detection_eval = 0.139113
-I0511 11:50:55.645928  5581 caffe.cpp:501] detection_eval = 15.3145
-I0511 11:50:55.645936  5581 caffe.cpp:501] detection_eval = 0.0370335
-I0511 11:50:55.645942  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645951  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.645956  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.645967  5581 caffe.cpp:501] detection_eval = 15.4133
-I0511 11:50:55.645977  5581 caffe.cpp:501] detection_eval = 0.0354428
-I0511 11:50:55.645987  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.645998  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.646008  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.646028  5581 caffe.cpp:501] detection_eval = 15.5927
-I0511 11:50:55.646040  5581 caffe.cpp:501] detection_eval = 0.0402357
-I0511 11:50:55.646050  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.646062  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.646071  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.646077  5581 caffe.cpp:501] detection_eval = 15.7621
-I0511 11:50:55.646086  5581 caffe.cpp:501] detection_eval = 0.0409724
-I0511 11:50:55.646091  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.646100  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.646109  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.646118  5581 caffe.cpp:501] detection_eval = 15.9133
-I0511 11:50:55.646131  5581 caffe.cpp:501] detection_eval = 0.0364343
-I0511 11:50:55.646138  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.646149  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.646160  5581 caffe.cpp:501] detection_eval = 0.141129
-I0511 11:50:55.646170  5581 caffe.cpp:501] detection_eval = 16.1734
-I0511 11:50:55.646181  5581 caffe.cpp:501] detection_eval = 0.0399021
-I0511 11:50:55.646193  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.646203  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.646214  5581 caffe.cpp:501] detection_eval = 0.145161
-I0511 11:50:55.646224  5581 caffe.cpp:501] detection_eval = 16.4274
-I0511 11:50:55.646236  5581 caffe.cpp:501] detection_eval = 0.0425502
-I0511 11:50:55.646246  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.646257  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.646268  5581 caffe.cpp:501] detection_eval = 0.149194
-I0511 11:50:55.646279  5581 caffe.cpp:501] detection_eval = 16.9194
-I0511 11:50:55.646289  5581 caffe.cpp:501] detection_eval = 0.0322777
-I0511 11:50:55.646299  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.646304  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.646312  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646322  5581 caffe.cpp:501] detection_eval = 4.15323
-I0511 11:50:55.646330  5581 caffe.cpp:501] detection_eval = 0.162295
-I0511 11:50:55.646340  5581 caffe.cpp:501] detection_eval = 0.135081
-I0511 11:50:55.646351  5581 caffe.cpp:501] detection_eval = 0.862903
-I0511 11:50:55.646363  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646373  5581 caffe.cpp:501] detection_eval = 4.44355
-I0511 11:50:55.646385  5581 caffe.cpp:501] detection_eval = 0.0833618
-I0511 11:50:55.646397  5581 caffe.cpp:501] detection_eval = 0.0544355
-I0511 11:50:55.646409  5581 caffe.cpp:501] detection_eval = 0.941532
-I0511 11:50:55.646420  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646428  5581 caffe.cpp:501] detection_eval = 4.62903
-I0511 11:50:55.646437  5581 caffe.cpp:501] detection_eval = 0.0740181
-I0511 11:50:55.646442  5581 caffe.cpp:501] detection_eval = 0.0383065
-I0511 11:50:55.646453  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.646458  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646466  5581 caffe.cpp:501] detection_eval = 4.82863
-I0511 11:50:55.646471  5581 caffe.cpp:501] detection_eval = 0.0657454
-I0511 11:50:55.646481  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.646486  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.646494  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646503  5581 caffe.cpp:501] detection_eval = 4.97177
-I0511 11:50:55.646514  5581 caffe.cpp:501] detection_eval = 0.0525329
-I0511 11:50:55.646525  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.646538  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.646548  5581 caffe.cpp:501] detection_eval = 1.00806
-I0511 11:50:55.646558  5581 caffe.cpp:501] detection_eval = 5.08266
-I0511 11:50:55.646569  5581 caffe.cpp:501] detection_eval = 0.0577359
-I0511 11:50:55.646579  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.646589  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.646600  5581 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:50:55.646613  5581 caffe.cpp:501] detection_eval = 5.16129
-I0511 11:50:55.646622  5581 caffe.cpp:501] detection_eval = 0.0573572
-I0511 11:50:55.646631  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.646641  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.646649  5581 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:50:55.646659  5581 caffe.cpp:501] detection_eval = 5.2621
-I0511 11:50:55.646670  5581 caffe.cpp:501] detection_eval = 0.0510652
-I0511 11:50:55.646680  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.646690  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.646701  5581 caffe.cpp:501] detection_eval = 1.0121
-I0511 11:50:55.646713  5581 caffe.cpp:501] detection_eval = 5.34879
-I0511 11:50:55.646723  5581 caffe.cpp:501] detection_eval = 0.0441459
-I0511 11:50:55.646733  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.646744  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.646754  5581 caffe.cpp:501] detection_eval = 1.01411
-I0511 11:50:55.646764  5581 caffe.cpp:501] detection_eval = 5.4254
-I0511 11:50:55.646775  5581 caffe.cpp:501] detection_eval = 0.047929
-I0511 11:50:55.646785  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.646795  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.646802  5581 caffe.cpp:501] detection_eval = 1.01613
-I0511 11:50:55.646816  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.646826  5581 caffe.cpp:501] detection_eval = 0.0461593
-I0511 11:50:55.646836  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.646845  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.646850  5581 caffe.cpp:501] detection_eval = 1.01613
-I0511 11:50:55.646858  5581 caffe.cpp:501] detection_eval = 5.53024
-I0511 11:50:55.646863  5581 caffe.cpp:501] detection_eval = 0.0461314
-I0511 11:50:55.646872  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.646878  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.646888  5581 caffe.cpp:501] detection_eval = 1.01815
-I0511 11:50:55.646893  5581 caffe.cpp:501] detection_eval = 5.57056
-I0511 11:50:55.646900  5581 caffe.cpp:501] detection_eval = 0.0440755
-I0511 11:50:55.646906  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.646914  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.646920  5581 caffe.cpp:501] detection_eval = 1.02218
-I0511 11:50:55.646929  5581 caffe.cpp:501] detection_eval = 5.59274
-I0511 11:50:55.646937  5581 caffe.cpp:501] detection_eval = 0.0506842
-I0511 11:50:55.646942  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.646951  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.646956  5581 caffe.cpp:501] detection_eval = 1.02218
-I0511 11:50:55.646965  5581 caffe.cpp:501] detection_eval = 5.67944
-I0511 11:50:55.646970  5581 caffe.cpp:501] detection_eval = 0.0473503
-I0511 11:50:55.646978  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.646984  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.646992  5581 caffe.cpp:501] detection_eval = 1.02218
-I0511 11:50:55.646997  5581 caffe.cpp:501] detection_eval = 5.75605
-I0511 11:50:55.647006  5581 caffe.cpp:501] detection_eval = 0.0442622
-I0511 11:50:55.647011  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.647020  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.647025  5581 caffe.cpp:501] detection_eval = 1.02419
-I0511 11:50:55.647033  5581 caffe.cpp:501] detection_eval = 5.81653
-I0511 11:50:55.647039  5581 caffe.cpp:501] detection_eval = 0.0437179
-I0511 11:50:55.647047  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647053  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.647061  5581 caffe.cpp:501] detection_eval = 1.02419
-I0511 11:50:55.647066  5581 caffe.cpp:501] detection_eval = 5.89919
-I0511 11:50:55.647075  5581 caffe.cpp:501] detection_eval = 0.0422151
-I0511 11:50:55.647080  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647089  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.647099  5581 caffe.cpp:501] detection_eval = 1.02419
-I0511 11:50:55.647107  5581 caffe.cpp:501] detection_eval = 5.97379
-I0511 11:50:55.647116  5581 caffe.cpp:501] detection_eval = 0.0397156
-I0511 11:50:55.647125  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.647135  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.647141  5581 caffe.cpp:501] detection_eval = 1.02621
-I0511 11:50:55.647152  5581 caffe.cpp:501] detection_eval = 6.03831
-I0511 11:50:55.647162  5581 caffe.cpp:501] detection_eval = 0.0410696
-I0511 11:50:55.647173  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647184  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647194  5581 caffe.cpp:501] detection_eval = 1.02823
-I0511 11:50:55.647203  5581 caffe.cpp:501] detection_eval = 6.05242
-I0511 11:50:55.647213  5581 caffe.cpp:501] detection_eval = 0.0445519
-I0511 11:50:55.647218  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.647227  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.647235  5581 caffe.cpp:501] detection_eval = 1.02823
-I0511 11:50:55.647240  5581 caffe.cpp:501] detection_eval = 6.11492
-I0511 11:50:55.647249  5581 caffe.cpp:501] detection_eval = 0.041272
-I0511 11:50:55.647255  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647267  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.647276  5581 caffe.cpp:501] detection_eval = 1.03024
-I0511 11:50:55.647292  5581 caffe.cpp:501] detection_eval = 6.18145
-I0511 11:50:55.647301  5581 caffe.cpp:501] detection_eval = 0.0424877
-I0511 11:50:55.647311  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647322  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.647327  5581 caffe.cpp:501] detection_eval = 1.03226
-I0511 11:50:55.647336  5581 caffe.cpp:501] detection_eval = 6.24194
-I0511 11:50:55.647341  5581 caffe.cpp:501] detection_eval = 0.0409147
-I0511 11:50:55.647349  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647356  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.647367  5581 caffe.cpp:501] detection_eval = 1.03427
-I0511 11:50:55.647377  5581 caffe.cpp:501] detection_eval = 6.31048
-I0511 11:50:55.647387  5581 caffe.cpp:501] detection_eval = 0.043412
-I0511 11:50:55.647397  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.647408  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.647418  5581 caffe.cpp:501] detection_eval = 1.03629
-I0511 11:50:55.647426  5581 caffe.cpp:501] detection_eval = 6.41935
-I0511 11:50:55.647431  5581 caffe.cpp:501] detection_eval = 0.0427416
-I0511 11:50:55.647439  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.647445  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.647454  5581 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:50:55.647459  5581 caffe.cpp:501] detection_eval = 6.41935
-I0511 11:50:55.647467  5581 caffe.cpp:501] detection_eval = 0.0435719
-I0511 11:50:55.647473  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.647481  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.647487  5581 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:50:55.647495  5581 caffe.cpp:501] detection_eval = 6.50605
-I0511 11:50:55.647500  5581 caffe.cpp:501] detection_eval = 0.0387101
-I0511 11:50:55.647508  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647514  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.647524  5581 caffe.cpp:501] detection_eval = 1.04032
-I0511 11:50:55.647534  5581 caffe.cpp:501] detection_eval = 6.5746
-I0511 11:50:55.647544  5581 caffe.cpp:501] detection_eval = 0.0392613
-I0511 11:50:55.647555  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647565  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.647577  5581 caffe.cpp:501] detection_eval = 1.04435
-I0511 11:50:55.647586  5581 caffe.cpp:501] detection_eval = 6.57863
-I0511 11:50:55.647596  5581 caffe.cpp:501] detection_eval = 0.0379121
-I0511 11:50:55.647603  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647615  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647620  5581 caffe.cpp:501] detection_eval = 1.04435
-I0511 11:50:55.647629  5581 caffe.cpp:501] detection_eval = 6.625
-I0511 11:50:55.647634  5581 caffe.cpp:501] detection_eval = 0.0442701
-I0511 11:50:55.647650  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647658  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.647668  5581 caffe.cpp:501] detection_eval = 1.04637
-I0511 11:50:55.647680  5581 caffe.cpp:501] detection_eval = 6.70565
-I0511 11:50:55.647689  5581 caffe.cpp:501] detection_eval = 0.0376735
-I0511 11:50:55.647699  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647711  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647722  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647729  5581 caffe.cpp:501] detection_eval = 6.73185
-I0511 11:50:55.647734  5581 caffe.cpp:501] detection_eval = 0.0395867
-I0511 11:50:55.647743  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647748  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647756  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647763  5581 caffe.cpp:501] detection_eval = 6.83669
-I0511 11:50:55.647770  5581 caffe.cpp:501] detection_eval = 0.040853
-I0511 11:50:55.647776  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.647789  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647797  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647809  5581 caffe.cpp:501] detection_eval = 6.93347
-I0511 11:50:55.647819  5581 caffe.cpp:501] detection_eval = 0.0420755
-I0511 11:50:55.647830  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.647838  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.647843  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647852  5581 caffe.cpp:501] detection_eval = 6.98589
-I0511 11:50:55.647857  5581 caffe.cpp:501] detection_eval = 0.0422012
-I0511 11:50:55.647866  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.647871  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.647879  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647888  5581 caffe.cpp:501] detection_eval = 7.06855
-I0511 11:50:55.647893  5581 caffe.cpp:501] detection_eval = 0.0381115
-I0511 11:50:55.647902  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.647907  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.647917  5581 caffe.cpp:501] detection_eval = 1.0504
-I0511 11:50:55.647922  5581 caffe.cpp:501] detection_eval = 7.15323
-I0511 11:50:55.647933  5581 caffe.cpp:501] detection_eval = 0.048996
-I0511 11:50:55.647943  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.647953  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.647963  5581 caffe.cpp:501] detection_eval = 1.05242
-I0511 11:50:55.647971  5581 caffe.cpp:501] detection_eval = 7.20161
-I0511 11:50:55.647979  5581 caffe.cpp:501] detection_eval = 0.0458926
-I0511 11:50:55.647989  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.648000  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.648010  5581 caffe.cpp:501] detection_eval = 1.05444
-I0511 11:50:55.648020  5581 caffe.cpp:501] detection_eval = 7.26815
-I0511 11:50:55.648030  5581 caffe.cpp:501] detection_eval = 0.0430835
-I0511 11:50:55.648041  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648051  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648062  5581 caffe.cpp:501] detection_eval = 1.05444
-I0511 11:50:55.648072  5581 caffe.cpp:501] detection_eval = 7.42137
-I0511 11:50:55.648083  5581 caffe.cpp:501] detection_eval = 0.0464151
-I0511 11:50:55.648093  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.648103  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.648111  5581 caffe.cpp:501] detection_eval = 1.05444
-I0511 11:50:55.648118  5581 caffe.cpp:501] detection_eval = 7.47581
-I0511 11:50:55.648125  5581 caffe.cpp:501] detection_eval = 0.0399444
-I0511 11:50:55.648130  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.648140  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.648149  5581 caffe.cpp:501] detection_eval = 1.05645
-I0511 11:50:55.648154  5581 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:50:55.648164  5581 caffe.cpp:501] detection_eval = 0.0454342
-I0511 11:50:55.648175  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.648185  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.648196  5581 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:50:55.648206  5581 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:50:55.648217  5581 caffe.cpp:501] detection_eval = 0.0434764
-I0511 11:50:55.648227  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.648238  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.648248  5581 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:50:55.648259  5581 caffe.cpp:501] detection_eval = 7.61895
-I0511 11:50:55.648269  5581 caffe.cpp:501] detection_eval = 0.0371605
-I0511 11:50:55.648280  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.648291  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.648300  5581 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:50:55.648309  5581 caffe.cpp:501] detection_eval = 7.6875
-I0511 11:50:55.648314  5581 caffe.cpp:501] detection_eval = 0.0416036
-I0511 11:50:55.648324  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648331  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648335  5581 caffe.cpp:501] detection_eval = 1.06048
-I0511 11:50:55.648344  5581 caffe.cpp:501] detection_eval = 7.78024
-I0511 11:50:55.648355  5581 caffe.cpp:501] detection_eval = 0.0401231
-I0511 11:50:55.648365  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.648376  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.648387  5581 caffe.cpp:501] detection_eval = 1.0625
-I0511 11:50:55.648398  5581 caffe.cpp:501] detection_eval = 7.83669
-I0511 11:50:55.648407  5581 caffe.cpp:501] detection_eval = 0.0427721
-I0511 11:50:55.648416  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648422  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.648432  5581 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:50:55.648437  5581 caffe.cpp:501] detection_eval = 7.87097
-I0511 11:50:55.648444  5581 caffe.cpp:501] detection_eval = 0.0395211
-I0511 11:50:55.648454  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.648459  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.648468  5581 caffe.cpp:501] detection_eval = 1.06452
-I0511 11:50:55.648478  5581 caffe.cpp:501] detection_eval = 7.94758
-I0511 11:50:55.648488  5581 caffe.cpp:501] detection_eval = 0.0378073
-I0511 11:50:55.648499  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.648509  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.648520  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648538  5581 caffe.cpp:501] detection_eval = 7.99597
-I0511 11:50:55.648555  5581 caffe.cpp:501] detection_eval = 0.0381689
-I0511 11:50:55.648563  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648573  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648582  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648588  5581 caffe.cpp:501] detection_eval = 8.06855
-I0511 11:50:55.648597  5581 caffe.cpp:501] detection_eval = 0.0425882
-I0511 11:50:55.648602  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.648610  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.648615  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648624  5581 caffe.cpp:501] detection_eval = 8.11492
-I0511 11:50:55.648630  5581 caffe.cpp:501] detection_eval = 0.0383515
-I0511 11:50:55.648638  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.648644  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.648653  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648658  5581 caffe.cpp:501] detection_eval = 8.16331
-I0511 11:50:55.648667  5581 caffe.cpp:501] detection_eval = 0.0415489
-I0511 11:50:55.648679  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.648687  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.648696  5581 caffe.cpp:501] detection_eval = 1.06653
-I0511 11:50:55.648705  5581 caffe.cpp:501] detection_eval = 8.25806
-I0511 11:50:55.648715  5581 caffe.cpp:501] detection_eval = 0.0427888
-I0511 11:50:55.648720  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648728  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.648735  5581 caffe.cpp:501] detection_eval = 1.07056
-I0511 11:50:55.648742  5581 caffe.cpp:501] detection_eval = 8.31048
-I0511 11:50:55.648748  5581 caffe.cpp:501] detection_eval = 0.0417843
-I0511 11:50:55.648759  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648768  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648779  5581 caffe.cpp:501] detection_eval = 1.07258
-I0511 11:50:55.648789  5581 caffe.cpp:501] detection_eval = 8.38306
-I0511 11:50:55.648799  5581 caffe.cpp:501] detection_eval = 0.0434073
-I0511 11:50:55.648810  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648820  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.648825  5581 caffe.cpp:501] detection_eval = 1.07258
-I0511 11:50:55.648834  5581 caffe.cpp:501] detection_eval = 8.4879
-I0511 11:50:55.648839  5581 caffe.cpp:501] detection_eval = 0.0444408
-I0511 11:50:55.648850  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648855  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648864  5581 caffe.cpp:501] detection_eval = 1.0746
-I0511 11:50:55.648869  5581 caffe.cpp:501] detection_eval = 8.54234
-I0511 11:50:55.648877  5581 caffe.cpp:501] detection_eval = 0.0404407
-I0511 11:50:55.648882  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.648891  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.648896  5581 caffe.cpp:501] detection_eval = 1.07661
-I0511 11:50:55.648905  5581 caffe.cpp:501] detection_eval = 8.57258
-I0511 11:50:55.648910  5581 caffe.cpp:501] detection_eval = 0.0421837
-I0511 11:50:55.648919  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.648924  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.648933  5581 caffe.cpp:501] detection_eval = 1.07863
-I0511 11:50:55.648938  5581 caffe.cpp:501] detection_eval = 8.6371
-I0511 11:50:55.648947  5581 caffe.cpp:501] detection_eval = 0.0382398
-I0511 11:50:55.648952  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.648962  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.648967  5581 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:50:55.648974  5581 caffe.cpp:501] detection_eval = 8.71976
-I0511 11:50:55.648980  5581 caffe.cpp:501] detection_eval = 0.0412205
-I0511 11:50:55.648989  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.648994  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649003  5581 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:50:55.649008  5581 caffe.cpp:501] detection_eval = 8.83669
-I0511 11:50:55.649016  5581 caffe.cpp:501] detection_eval = 0.0449207
-I0511 11:50:55.649022  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.649030  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.649039  5581 caffe.cpp:501] detection_eval = 1.08065
-I0511 11:50:55.649044  5581 caffe.cpp:501] detection_eval = 8.9254
-I0511 11:50:55.649053  5581 caffe.cpp:501] detection_eval = 0.0446503
-I0511 11:50:55.649060  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.649068  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.649073  5581 caffe.cpp:501] detection_eval = 1.08468
-I0511 11:50:55.649081  5581 caffe.cpp:501] detection_eval = 8.98589
-I0511 11:50:55.649086  5581 caffe.cpp:501] detection_eval = 0.0438332
-I0511 11:50:55.649096  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649101  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.649109  5581 caffe.cpp:501] detection_eval = 1.08468
-I0511 11:50:55.649114  5581 caffe.cpp:501] detection_eval = 9.09879
-I0511 11:50:55.649122  5581 caffe.cpp:501] detection_eval = 0.0409492
-I0511 11:50:55.649132  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.649144  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649154  5581 caffe.cpp:501] detection_eval = 1.08669
-I0511 11:50:55.649170  5581 caffe.cpp:501] detection_eval = 9.16532
-I0511 11:50:55.649179  5581 caffe.cpp:501] detection_eval = 0.0465822
-I0511 11:50:55.649190  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.649201  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649211  5581 caffe.cpp:501] detection_eval = 1.08871
-I0511 11:50:55.649221  5581 caffe.cpp:501] detection_eval = 9.22379
-I0511 11:50:55.649227  5581 caffe.cpp:501] detection_eval = 0.0373351
-I0511 11:50:55.649235  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.649240  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649250  5581 caffe.cpp:501] detection_eval = 1.09073
-I0511 11:50:55.649255  5581 caffe.cpp:501] detection_eval = 9.30847
-I0511 11:50:55.649262  5581 caffe.cpp:501] detection_eval = 0.0483995
-I0511 11:50:55.649267  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.649276  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.649284  5581 caffe.cpp:501] detection_eval = 1.09274
-I0511 11:50:55.649294  5581 caffe.cpp:501] detection_eval = 9.36694
-I0511 11:50:55.649305  5581 caffe.cpp:501] detection_eval = 0.045512
-I0511 11:50:55.649315  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.649327  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649334  5581 caffe.cpp:501] detection_eval = 1.09476
-I0511 11:50:55.649344  5581 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:50:55.649351  5581 caffe.cpp:501] detection_eval = 0.0479182
-I0511 11:50:55.649359  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.649365  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.649374  5581 caffe.cpp:501] detection_eval = 1.09677
-I0511 11:50:55.649379  5581 caffe.cpp:501] detection_eval = 9.50403
-I0511 11:50:55.649387  5581 caffe.cpp:501] detection_eval = 0.0436144
-I0511 11:50:55.649394  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649401  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.649407  5581 caffe.cpp:501] detection_eval = 1.09879
-I0511 11:50:55.649417  5581 caffe.cpp:501] detection_eval = 9.54637
-I0511 11:50:55.649426  5581 caffe.cpp:501] detection_eval = 0.0455071
-I0511 11:50:55.649437  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.649449  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649459  5581 caffe.cpp:501] detection_eval = 1.09879
-I0511 11:50:55.649471  5581 caffe.cpp:501] detection_eval = 9.66129
-I0511 11:50:55.649479  5581 caffe.cpp:501] detection_eval = 0.0471619
-I0511 11:50:55.649484  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.649492  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649498  5581 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:50:55.649507  5581 caffe.cpp:501] detection_eval = 9.71976
-I0511 11:50:55.649515  5581 caffe.cpp:501] detection_eval = 0.0502448
-I0511 11:50:55.649524  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.649534  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.649545  5581 caffe.cpp:501] detection_eval = 1.10081
-I0511 11:50:55.649555  5581 caffe.cpp:501] detection_eval = 9.84879
-I0511 11:50:55.649566  5581 caffe.cpp:501] detection_eval = 0.054421
-I0511 11:50:55.649577  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.649587  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.649592  5581 caffe.cpp:501] detection_eval = 1.10484
-I0511 11:50:55.649600  5581 caffe.cpp:501] detection_eval = 9.89315
-I0511 11:50:55.649606  5581 caffe.cpp:501] detection_eval = 0.0514542
-I0511 11:50:55.649615  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649621  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649628  5581 caffe.cpp:501] detection_eval = 1.10685
-I0511 11:50:55.649634  5581 caffe.cpp:501] detection_eval = 9.92137
-I0511 11:50:55.649647  5581 caffe.cpp:501] detection_eval = 0.0478509
-I0511 11:50:55.649652  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.649662  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.649670  5581 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:50:55.649682  5581 caffe.cpp:501] detection_eval = 9.94355
-I0511 11:50:55.649693  5581 caffe.cpp:501] detection_eval = 0.0418964
-I0511 11:50:55.649703  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649713  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649724  5581 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:50:55.649734  5581 caffe.cpp:501] detection_eval = 10.0202
-I0511 11:50:55.649739  5581 caffe.cpp:501] detection_eval = 0.0441931
-I0511 11:50:55.649747  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.649754  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.649761  5581 caffe.cpp:501] detection_eval = 1.10887
-I0511 11:50:55.649767  5581 caffe.cpp:501] detection_eval = 10.0806
-I0511 11:50:55.649776  5581 caffe.cpp:501] detection_eval = 0.0413312
-I0511 11:50:55.649781  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.649791  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.649799  5581 caffe.cpp:501] detection_eval = 1.11089
-I0511 11:50:55.649804  5581 caffe.cpp:501] detection_eval = 10.1512
-I0511 11:50:55.649822  5581 caffe.cpp:501] detection_eval = 0.0473174
-I0511 11:50:55.649832  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.649842  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.649853  5581 caffe.cpp:501] detection_eval = 1.1129
-I0511 11:50:55.649861  5581 caffe.cpp:501] detection_eval = 10.2077
-I0511 11:50:55.649870  5581 caffe.cpp:501] detection_eval = 0.041972
-I0511 11:50:55.649875  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.649884  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.649890  5581 caffe.cpp:501] detection_eval = 1.11694
-I0511 11:50:55.649899  5581 caffe.cpp:501] detection_eval = 10.2581
-I0511 11:50:55.649904  5581 caffe.cpp:501] detection_eval = 0.0428795
-I0511 11:50:55.649912  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.649919  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.649926  5581 caffe.cpp:501] detection_eval = 1.11895
-I0511 11:50:55.649931  5581 caffe.cpp:501] detection_eval = 10.2964
-I0511 11:50:55.649942  5581 caffe.cpp:501] detection_eval = 0.0449703
-I0511 11:50:55.649950  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.649961  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.649971  5581 caffe.cpp:501] detection_eval = 1.11895
-I0511 11:50:55.649981  5581 caffe.cpp:501] detection_eval = 10.3891
-I0511 11:50:55.649993  5581 caffe.cpp:501] detection_eval = 0.0461663
-I0511 11:50:55.650003  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650012  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.650020  5581 caffe.cpp:501] detection_eval = 1.12097
-I0511 11:50:55.650025  5581 caffe.cpp:501] detection_eval = 10.4496
-I0511 11:50:55.650034  5581 caffe.cpp:501] detection_eval = 0.0472882
-I0511 11:50:55.650039  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650048  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.650053  5581 caffe.cpp:501] detection_eval = 1.12298
-I0511 11:50:55.650063  5581 caffe.cpp:501] detection_eval = 10.4839
-I0511 11:50:55.650068  5581 caffe.cpp:501] detection_eval = 0.0490379
-I0511 11:50:55.650076  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.650082  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650090  5581 caffe.cpp:501] detection_eval = 1.125
-I0511 11:50:55.650095  5581 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:50:55.650104  5581 caffe.cpp:501] detection_eval = 0.0433475
-I0511 11:50:55.650110  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.650118  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.650123  5581 caffe.cpp:501] detection_eval = 1.125
-I0511 11:50:55.650140  5581 caffe.cpp:501] detection_eval = 10.6411
-I0511 11:50:55.650149  5581 caffe.cpp:501] detection_eval = 0.0465548
-I0511 11:50:55.650161  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.650171  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.650182  5581 caffe.cpp:501] detection_eval = 1.125
-I0511 11:50:55.650192  5581 caffe.cpp:501] detection_eval = 10.6996
-I0511 11:50:55.650200  5581 caffe.cpp:501] detection_eval = 0.0447184
-I0511 11:50:55.650205  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.650214  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.650219  5581 caffe.cpp:501] detection_eval = 1.12903
-I0511 11:50:55.650228  5581 caffe.cpp:501] detection_eval = 10.7319
-I0511 11:50:55.650233  5581 caffe.cpp:501] detection_eval = 0.0495963
-I0511 11:50:55.650241  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.650247  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.650255  5581 caffe.cpp:501] detection_eval = 1.12903
-I0511 11:50:55.650260  5581 caffe.cpp:501] detection_eval = 10.8407
-I0511 11:50:55.650269  5581 caffe.cpp:501] detection_eval = 0.041825
-I0511 11:50:55.650279  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.650287  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650295  5581 caffe.cpp:501] detection_eval = 1.13306
-I0511 11:50:55.650301  5581 caffe.cpp:501] detection_eval = 10.8448
-I0511 11:50:55.650305  5581 caffe.cpp:501] detection_eval = 0.0408316
-I0511 11:50:55.650315  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.650322  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.650327  5581 caffe.cpp:501] detection_eval = 1.13508
-I0511 11:50:55.650336  5581 caffe.cpp:501] detection_eval = 10.9738
-I0511 11:50:55.650341  5581 caffe.cpp:501] detection_eval = 0.0480057
-I0511 11:50:55.650354  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.650362  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.650373  5581 caffe.cpp:501] detection_eval = 1.13508
-I0511 11:50:55.650383  5581 caffe.cpp:501] detection_eval = 11.0746
-I0511 11:50:55.650394  5581 caffe.cpp:501] detection_eval = 0.0489584
-I0511 11:50:55.650405  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.650416  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.650426  5581 caffe.cpp:501] detection_eval = 1.13508
-I0511 11:50:55.650436  5581 caffe.cpp:501] detection_eval = 11.1794
-I0511 11:50:55.650447  5581 caffe.cpp:501] detection_eval = 0.0542728
-I0511 11:50:55.650458  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.650467  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.650475  5581 caffe.cpp:501] detection_eval = 1.1371
-I0511 11:50:55.650480  5581 caffe.cpp:501] detection_eval = 11.2218
-I0511 11:50:55.650490  5581 caffe.cpp:501] detection_eval = 0.0456568
-I0511 11:50:55.650496  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650503  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.650509  5581 caffe.cpp:501] detection_eval = 1.13911
-I0511 11:50:55.650517  5581 caffe.cpp:501] detection_eval = 11.2581
-I0511 11:50:55.650523  5581 caffe.cpp:501] detection_eval = 0.0453398
-I0511 11:50:55.650532  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650537  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650547  5581 caffe.cpp:501] detection_eval = 1.14113
-I0511 11:50:55.650552  5581 caffe.cpp:501] detection_eval = 11.2661
-I0511 11:50:55.650560  5581 caffe.cpp:501] detection_eval = 0.0411792
-I0511 11:50:55.650569  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.650578  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.650583  5581 caffe.cpp:501] detection_eval = 1.14516
-I0511 11:50:55.650590  5581 caffe.cpp:501] detection_eval = 11.2944
-I0511 11:50:55.650596  5581 caffe.cpp:501] detection_eval = 0.0449004
-I0511 11:50:55.650605  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.650610  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650619  5581 caffe.cpp:501] detection_eval = 1.14919
-I0511 11:50:55.650629  5581 caffe.cpp:501] detection_eval = 11.3004
-I0511 11:50:55.650637  5581 caffe.cpp:501] detection_eval = 0.0497927
-I0511 11:50:55.650642  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.650651  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.650661  5581 caffe.cpp:501] detection_eval = 1.14919
-I0511 11:50:55.650666  5581 caffe.cpp:501] detection_eval = 11.3589
-I0511 11:50:55.650677  5581 caffe.cpp:501] detection_eval = 0.043157
-I0511 11:50:55.650687  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.650698  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.650708  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650719  5581 caffe.cpp:501] detection_eval = 11.3891
-I0511 11:50:55.650730  5581 caffe.cpp:501] detection_eval = 0.0432482
-I0511 11:50:55.650738  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.650748  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.650753  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650761  5581 caffe.cpp:501] detection_eval = 11.4617
-I0511 11:50:55.650768  5581 caffe.cpp:501] detection_eval = 0.0400496
-I0511 11:50:55.650775  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.650781  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.650789  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650794  5581 caffe.cpp:501] detection_eval = 11.5544
-I0511 11:50:55.650799  5581 caffe.cpp:501] detection_eval = 0.0485405
-I0511 11:50:55.650809  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.650817  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.650823  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650831  5581 caffe.cpp:501] detection_eval = 11.623
-I0511 11:50:55.650837  5581 caffe.cpp:501] detection_eval = 0.044955
-I0511 11:50:55.650846  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.650851  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.650859  5581 caffe.cpp:501] detection_eval = 1.15323
-I0511 11:50:55.650866  5581 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:50:55.650873  5581 caffe.cpp:501] detection_eval = 0.0465296
-I0511 11:50:55.650879  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.650887  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.650893  5581 caffe.cpp:501] detection_eval = 1.15524
-I0511 11:50:55.650902  5581 caffe.cpp:501] detection_eval = 11.744
-I0511 11:50:55.650907  5581 caffe.cpp:501] detection_eval = 0.0429926
-I0511 11:50:55.650915  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.650921  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.650929  5581 caffe.cpp:501] detection_eval = 1.15726
-I0511 11:50:55.650934  5581 caffe.cpp:501] detection_eval = 11.7823
-I0511 11:50:55.650943  5581 caffe.cpp:501] detection_eval = 0.0445645
-I0511 11:50:55.650949  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650957  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.650966  5581 caffe.cpp:501] detection_eval = 1.15927
-I0511 11:50:55.650971  5581 caffe.cpp:501] detection_eval = 11.8125
-I0511 11:50:55.650980  5581 caffe.cpp:501] detection_eval = 0.0394349
-I0511 11:50:55.650985  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.650996  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.651001  5581 caffe.cpp:501] detection_eval = 1.16331
-I0511 11:50:55.651010  5581 caffe.cpp:501] detection_eval = 11.8286
-I0511 11:50:55.651015  5581 caffe.cpp:501] detection_eval = 0.0394802
-I0511 11:50:55.651023  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.651028  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.651037  5581 caffe.cpp:501] detection_eval = 1.16331
-I0511 11:50:55.651042  5581 caffe.cpp:501] detection_eval = 11.8891
-I0511 11:50:55.651057  5581 caffe.cpp:501] detection_eval = 0.0437617
-I0511 11:50:55.651064  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.651075  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651093  5581 caffe.cpp:501] detection_eval = 1.16331
-I0511 11:50:55.651103  5581 caffe.cpp:501] detection_eval = 11.9395
-I0511 11:50:55.651113  5581 caffe.cpp:501] detection_eval = 0.0452932
-I0511 11:50:55.651118  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651125  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651134  5581 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:50:55.651141  5581 caffe.cpp:501] detection_eval = 11.9859
-I0511 11:50:55.651150  5581 caffe.cpp:501] detection_eval = 0.0494409
-I0511 11:50:55.651156  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651165  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651170  5581 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:50:55.651181  5581 caffe.cpp:501] detection_eval = 12.0726
-I0511 11:50:55.651190  5581 caffe.cpp:501] detection_eval = 0.0507496
-I0511 11:50:55.651201  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651212  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.651219  5581 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:50:55.651232  5581 caffe.cpp:501] detection_eval = 12.1331
-I0511 11:50:55.651237  5581 caffe.cpp:501] detection_eval = 0.046769
-I0511 11:50:55.651247  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651252  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.651262  5581 caffe.cpp:501] detection_eval = 1.16532
-I0511 11:50:55.651268  5581 caffe.cpp:501] detection_eval = 12.2016
-I0511 11:50:55.651279  5581 caffe.cpp:501] detection_eval = 0.0454815
-I0511 11:50:55.651290  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.651301  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.651311  5581 caffe.cpp:501] detection_eval = 1.16935
-I0511 11:50:55.651322  5581 caffe.cpp:501] detection_eval = 12.1774
-I0511 11:50:55.651331  5581 caffe.cpp:501] detection_eval = 0.0420104
-I0511 11:50:55.651345  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651350  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.651358  5581 caffe.cpp:501] detection_eval = 1.17137
-I0511 11:50:55.651367  5581 caffe.cpp:501] detection_eval = 12.2077
-I0511 11:50:55.651372  5581 caffe.cpp:501] detection_eval = 0.0409585
-I0511 11:50:55.651381  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.651387  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.651396  5581 caffe.cpp:501] detection_eval = 1.17339
-I0511 11:50:55.651403  5581 caffe.cpp:501] detection_eval = 12.2641
-I0511 11:50:55.651413  5581 caffe.cpp:501] detection_eval = 0.0436587
-I0511 11:50:55.651424  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.651435  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.651445  5581 caffe.cpp:501] detection_eval = 1.17339
-I0511 11:50:55.651455  5581 caffe.cpp:501] detection_eval = 12.2903
-I0511 11:50:55.651468  5581 caffe.cpp:501] detection_eval = 0.0377398
-I0511 11:50:55.651477  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.651489  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.651499  5581 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:50:55.651510  5581 caffe.cpp:501] detection_eval = 12.3347
-I0511 11:50:55.651520  5581 caffe.cpp:501] detection_eval = 0.0434924
-I0511 11:50:55.651531  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651545  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.651553  5581 caffe.cpp:501] detection_eval = 1.1754
-I0511 11:50:55.651567  5581 caffe.cpp:501] detection_eval = 12.4093
-I0511 11:50:55.651576  5581 caffe.cpp:501] detection_eval = 0.0381849
-I0511 11:50:55.651587  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651598  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.651615  5581 caffe.cpp:501] detection_eval = 1.17742
-I0511 11:50:55.651624  5581 caffe.cpp:501] detection_eval = 12.4637
-I0511 11:50:55.651635  5581 caffe.cpp:501] detection_eval = 0.0420042
-I0511 11:50:55.651645  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.651665  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.651676  5581 caffe.cpp:501] detection_eval = 1.17742
-I0511 11:50:55.651687  5581 caffe.cpp:501] detection_eval = 12.5444
-I0511 11:50:55.651700  5581 caffe.cpp:501] detection_eval = 0.0419976
-I0511 11:50:55.651718  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.651723  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.651733  5581 caffe.cpp:501] detection_eval = 1.17944
-I0511 11:50:55.651738  5581 caffe.cpp:501] detection_eval = 12.5766
-I0511 11:50:55.651749  5581 caffe.cpp:501] detection_eval = 0.0431548
-I0511 11:50:55.651760  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651772  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.651782  5581 caffe.cpp:501] detection_eval = 1.18145
-I0511 11:50:55.651799  5581 caffe.cpp:501] detection_eval = 12.6048
-I0511 11:50:55.651809  5581 caffe.cpp:501] detection_eval = 0.0490637
-I0511 11:50:55.651821  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.651834  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651844  5581 caffe.cpp:501] detection_eval = 1.18347
-I0511 11:50:55.651856  5581 caffe.cpp:501] detection_eval = 12.6532
-I0511 11:50:55.651868  5581 caffe.cpp:501] detection_eval = 0.0482764
-I0511 11:50:55.651880  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651892  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.651912  5581 caffe.cpp:501] detection_eval = 1.18347
-I0511 11:50:55.651921  5581 caffe.cpp:501] detection_eval = 12.7319
-I0511 11:50:55.651933  5581 caffe.cpp:501] detection_eval = 0.0433545
-I0511 11:50:55.651945  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.651955  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.651967  5581 caffe.cpp:501] detection_eval = 1.1875
-I0511 11:50:55.651974  5581 caffe.cpp:501] detection_eval = 12.7298
-I0511 11:50:55.651983  5581 caffe.cpp:501] detection_eval = 0.047096
-I0511 11:50:55.651988  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.651998  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.652007  5581 caffe.cpp:501] detection_eval = 1.1875
-I0511 11:50:55.652019  5581 caffe.cpp:501] detection_eval = 12.7944
-I0511 11:50:55.652029  5581 caffe.cpp:501] detection_eval = 0.0487267
-I0511 11:50:55.652040  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.652051  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.652062  5581 caffe.cpp:501] detection_eval = 1.1875
-I0511 11:50:55.652073  5581 caffe.cpp:501] detection_eval = 12.8387
-I0511 11:50:55.652084  5581 caffe.cpp:501] detection_eval = 0.0468088
-I0511 11:50:55.652096  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.652112  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.652122  5581 caffe.cpp:501] detection_eval = 1.18952
-I0511 11:50:55.652137  5581 caffe.cpp:501] detection_eval = 12.8528
-I0511 11:50:55.652146  5581 caffe.cpp:501] detection_eval = 0.0444437
-I0511 11:50:55.652156  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652161  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652170  5581 caffe.cpp:501] detection_eval = 1.19355
-I0511 11:50:55.652175  5581 caffe.cpp:501] detection_eval = 12.8226
-I0511 11:50:55.652184  5581 caffe.cpp:501] detection_eval = 0.0398538
-I0511 11:50:55.652191  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652200  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652206  5581 caffe.cpp:501] detection_eval = 1.1996
-I0511 11:50:55.652215  5581 caffe.cpp:501] detection_eval = 12.8185
-I0511 11:50:55.652225  5581 caffe.cpp:501] detection_eval = 0.0389354
-I0511 11:50:55.652235  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652245  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652254  5581 caffe.cpp:501] detection_eval = 1.20161
-I0511 11:50:55.652266  5581 caffe.cpp:501] detection_eval = 12.877
-I0511 11:50:55.652277  5581 caffe.cpp:501] detection_eval = 0.0419467
-I0511 11:50:55.652288  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652307  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652318  5581 caffe.cpp:501] detection_eval = 1.20363
-I0511 11:50:55.652329  5581 caffe.cpp:501] detection_eval = 12.9173
-I0511 11:50:55.652340  5581 caffe.cpp:501] detection_eval = 0.0398573
-I0511 11:50:55.652359  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652369  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652380  5581 caffe.cpp:501] detection_eval = 1.20565
-I0511 11:50:55.652391  5581 caffe.cpp:501] detection_eval = 12.9476
-I0511 11:50:55.652402  5581 caffe.cpp:501] detection_eval = 0.0379745
-I0511 11:50:55.652413  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652426  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.652436  5581 caffe.cpp:501] detection_eval = 1.20766
-I0511 11:50:55.652446  5581 caffe.cpp:501] detection_eval = 12.996
-I0511 11:50:55.652452  5581 caffe.cpp:501] detection_eval = 0.0404742
-I0511 11:50:55.652462  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.652467  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.652474  5581 caffe.cpp:501] detection_eval = 1.20766
-I0511 11:50:55.652483  5581 caffe.cpp:501] detection_eval = 13.0887
-I0511 11:50:55.652489  5581 caffe.cpp:501] detection_eval = 0.0445697
-I0511 11:50:55.652498  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652509  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.652514  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652523  5581 caffe.cpp:501] detection_eval = 13.0282
-I0511 11:50:55.652539  5581 caffe.cpp:501] detection_eval = 0.0402824
-I0511 11:50:55.652549  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652557  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652564  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652571  5581 caffe.cpp:501] detection_eval = 13.0927
-I0511 11:50:55.652577  5581 caffe.cpp:501] detection_eval = 0.0440938
-I0511 11:50:55.652585  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652591  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.652600  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652606  5581 caffe.cpp:501] detection_eval = 13.1734
-I0511 11:50:55.652614  5581 caffe.cpp:501] detection_eval = 0.0431589
-I0511 11:50:55.652621  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.652628  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.652634  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652642  5581 caffe.cpp:501] detection_eval = 13.2379
-I0511 11:50:55.652652  5581 caffe.cpp:501] detection_eval = 0.0415992
-I0511 11:50:55.652657  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652667  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652671  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652679  5581 caffe.cpp:501] detection_eval = 13.2681
-I0511 11:50:55.652685  5581 caffe.cpp:501] detection_eval = 0.0385722
-I0511 11:50:55.652694  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652699  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652707  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652716  5581 caffe.cpp:501] detection_eval = 13.3226
-I0511 11:50:55.652722  5581 caffe.cpp:501] detection_eval = 0.0384585
-I0511 11:50:55.652730  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.652736  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652745  5581 caffe.cpp:501] detection_eval = 1.21371
-I0511 11:50:55.652750  5581 caffe.cpp:501] detection_eval = 13.4516
-I0511 11:50:55.652760  5581 caffe.cpp:501] detection_eval = 0.0401032
-I0511 11:50:55.652765  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652773  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.652779  5581 caffe.cpp:501] detection_eval = 1.21976
-I0511 11:50:55.652787  5581 caffe.cpp:501] detection_eval = 13.4133
-I0511 11:50:55.652793  5581 caffe.cpp:501] detection_eval = 0.03765
-I0511 11:50:55.652803  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.652813  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.652818  5581 caffe.cpp:501] detection_eval = 1.21976
-I0511 11:50:55.652827  5581 caffe.cpp:501] detection_eval = 13.4778
-I0511 11:50:55.652837  5581 caffe.cpp:501] detection_eval = 0.0384597
-I0511 11:50:55.652842  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652850  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652859  5581 caffe.cpp:501] detection_eval = 1.22379
-I0511 11:50:55.652865  5581 caffe.cpp:501] detection_eval = 13.4879
-I0511 11:50:55.652873  5581 caffe.cpp:501] detection_eval = 0.042613
-I0511 11:50:55.652879  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652889  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652894  5581 caffe.cpp:501] detection_eval = 1.22379
-I0511 11:50:55.652902  5581 caffe.cpp:501] detection_eval = 13.5323
-I0511 11:50:55.652909  5581 caffe.cpp:501] detection_eval = 0.040689
-I0511 11:50:55.652916  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.652922  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.652930  5581 caffe.cpp:501] detection_eval = 1.22581
-I0511 11:50:55.652937  5581 caffe.cpp:501] detection_eval = 13.5423
-I0511 11:50:55.652946  5581 caffe.cpp:501] detection_eval = 0.0396034
-I0511 11:50:55.652952  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.652956  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.652966  5581 caffe.cpp:501] detection_eval = 1.22984
-I0511 11:50:55.652973  5581 caffe.cpp:501] detection_eval = 13.504
-I0511 11:50:55.652979  5581 caffe.cpp:501] detection_eval = 0.039439
-I0511 11:50:55.652987  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.652997  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653005  5581 caffe.cpp:501] detection_eval = 1.23387
-I0511 11:50:55.653010  5581 caffe.cpp:501] detection_eval = 13.506
-I0511 11:50:55.653020  5581 caffe.cpp:501] detection_eval = 0.0414768
-I0511 11:50:55.653025  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.653034  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653039  5581 caffe.cpp:501] detection_eval = 1.23387
-I0511 11:50:55.653048  5581 caffe.cpp:501] detection_eval = 13.5544
-I0511 11:50:55.653055  5581 caffe.cpp:501] detection_eval = 0.0392363
-I0511 11:50:55.653066  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653077  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653087  5581 caffe.cpp:501] detection_eval = 1.23387
-I0511 11:50:55.653095  5581 caffe.cpp:501] detection_eval = 13.5786
-I0511 11:50:55.653106  5581 caffe.cpp:501] detection_eval = 0.034826
-I0511 11:50:55.653116  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653126  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653141  5581 caffe.cpp:501] detection_eval = 1.23992
-I0511 11:50:55.653149  5581 caffe.cpp:501] detection_eval = 13.5202
-I0511 11:50:55.653161  5581 caffe.cpp:501] detection_eval = 0.0353811
-I0511 11:50:55.653172  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653182  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653192  5581 caffe.cpp:501] detection_eval = 1.23992
-I0511 11:50:55.653197  5581 caffe.cpp:501] detection_eval = 13.5464
-I0511 11:50:55.653205  5581 caffe.cpp:501] detection_eval = 0.0334824
-I0511 11:50:55.653211  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.653219  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.653225  5581 caffe.cpp:501] detection_eval = 1.24194
-I0511 11:50:55.653234  5581 caffe.cpp:501] detection_eval = 13.5383
-I0511 11:50:55.653239  5581 caffe.cpp:501] detection_eval = 0.0353618
-I0511 11:50:55.653247  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653254  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653261  5581 caffe.cpp:501] detection_eval = 1.24194
-I0511 11:50:55.653266  5581 caffe.cpp:501] detection_eval = 13.5907
-I0511 11:50:55.653275  5581 caffe.cpp:501] detection_eval = 0.0379702
-I0511 11:50:55.653293  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653304  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.653314  5581 caffe.cpp:501] detection_eval = 1.24194
-I0511 11:50:55.653323  5581 caffe.cpp:501] detection_eval = 13.6169
-I0511 11:50:55.653328  5581 caffe.cpp:501] detection_eval = 0.0366723
-I0511 11:50:55.653337  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653342  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653349  5581 caffe.cpp:501] detection_eval = 1.24395
-I0511 11:50:55.653354  5581 caffe.cpp:501] detection_eval = 13.625
-I0511 11:50:55.653363  5581 caffe.cpp:501] detection_eval = 0.0349927
-I0511 11:50:55.653368  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.653378  5581 caffe.cpp:501] detection_eval = 1
-I0511 11:50:55.653383  5581 caffe.cpp:501] detection_eval = 1.24597
-I0511 11:50:55.653391  5581 caffe.cpp:501] detection_eval = 13.621
-I0511 11:50:55.653400  5581 caffe.cpp:501] detection_eval = 0.0325302
-I0511 11:50:55.653405  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653416  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.653421  5581 caffe.cpp:501] detection_eval = 1.24798
-I0511 11:50:55.653434  5581 caffe.cpp:501] detection_eval = 13.6532
-I0511 11:50:55.653443  5581 caffe.cpp:501] detection_eval = 0.0358958
-I0511 11:50:55.653455  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653471  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653481  5581 caffe.cpp:501] detection_eval = 1.24798
-I0511 11:50:55.653491  5581 caffe.cpp:501] detection_eval = 13.6915
-I0511 11:50:55.653503  5581 caffe.cpp:501] detection_eval = 0.0352341
-I0511 11:50:55.653513  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653518  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653527  5581 caffe.cpp:501] detection_eval = 1.25605
-I0511 11:50:55.653532  5581 caffe.cpp:501] detection_eval = 13.6593
-I0511 11:50:55.653545  5581 caffe.cpp:501] detection_eval = 0.0399494
-I0511 11:50:55.653555  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.653565  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653576  5581 caffe.cpp:501] detection_eval = 1.26613
-I0511 11:50:55.653586  5581 caffe.cpp:501] detection_eval = 13.5544
-I0511 11:50:55.653597  5581 caffe.cpp:501] detection_eval = 0.0439208
-I0511 11:50:55.653609  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.653620  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653630  5581 caffe.cpp:501] detection_eval = 1.26815
-I0511 11:50:55.653641  5581 caffe.cpp:501] detection_eval = 13.5524
-I0511 11:50:55.653652  5581 caffe.cpp:501] detection_eval = 0.0342003
-I0511 11:50:55.653663  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.653672  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.653682  5581 caffe.cpp:501] detection_eval = 1.26815
-I0511 11:50:55.653692  5581 caffe.cpp:501] detection_eval = 13.6069
-I0511 11:50:55.653702  5581 caffe.cpp:501] detection_eval = 0.0357598
-I0511 11:50:55.653712  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653722  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653730  5581 caffe.cpp:501] detection_eval = 1.27419
-I0511 11:50:55.653740  5581 caffe.cpp:501] detection_eval = 13.5847
-I0511 11:50:55.653750  5581 caffe.cpp:501] detection_eval = 0.0395496
-I0511 11:50:55.653760  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.653770  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.653779  5581 caffe.cpp:501] detection_eval = 1.27823
-I0511 11:50:55.653789  5581 caffe.cpp:501] detection_eval = 13.5827
-I0511 11:50:55.653800  5581 caffe.cpp:501] detection_eval = 0.0364555
-I0511 11:50:55.653810  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.653820  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.653831  5581 caffe.cpp:501] detection_eval = 1.28024
-I0511 11:50:55.653841  5581 caffe.cpp:501] detection_eval = 13.6008
-I0511 11:50:55.653857  5581 caffe.cpp:501] detection_eval = 0.0366828
-I0511 11:50:55.653867  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.653874  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.653883  5581 caffe.cpp:501] detection_eval = 1.28024
-I0511 11:50:55.653890  5581 caffe.cpp:501] detection_eval = 13.621
-I0511 11:50:55.653899  5581 caffe.cpp:501] detection_eval = 0.0368157
-I0511 11:50:55.653908  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.653915  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653923  5581 caffe.cpp:501] detection_eval = 1.28024
-I0511 11:50:55.653931  5581 caffe.cpp:501] detection_eval = 13.6714
-I0511 11:50:55.653939  5581 caffe.cpp:501] detection_eval = 0.0372316
-I0511 11:50:55.653944  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.653950  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.653959  5581 caffe.cpp:501] detection_eval = 1.28226
-I0511 11:50:55.653965  5581 caffe.cpp:501] detection_eval = 13.6815
-I0511 11:50:55.653973  5581 caffe.cpp:501] detection_eval = 0.0366134
-I0511 11:50:55.653981  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.653988  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.653996  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654003  5581 caffe.cpp:501] detection_eval = 13.6815
-I0511 11:50:55.654011  5581 caffe.cpp:501] detection_eval = 0.0336653
-I0511 11:50:55.654021  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654029  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654037  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654044  5581 caffe.cpp:501] detection_eval = 13.7157
-I0511 11:50:55.654052  5581 caffe.cpp:501] detection_eval = 0.0369443
-I0511 11:50:55.654060  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654068  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654076  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654083  5581 caffe.cpp:501] detection_eval = 13.7681
-I0511 11:50:55.654091  5581 caffe.cpp:501] detection_eval = 0.0362468
-I0511 11:50:55.654098  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.654108  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.654114  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654121  5581 caffe.cpp:501] detection_eval = 13.8185
-I0511 11:50:55.654130  5581 caffe.cpp:501] detection_eval = 0.0366433
-I0511 11:50:55.654137  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654145  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654151  5581 caffe.cpp:501] detection_eval = 1.28427
-I0511 11:50:55.654158  5581 caffe.cpp:501] detection_eval = 13.8972
-I0511 11:50:55.654165  5581 caffe.cpp:501] detection_eval = 0.0377793
-I0511 11:50:55.654172  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.654181  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654187  5581 caffe.cpp:501] detection_eval = 1.28629
-I0511 11:50:55.654196  5581 caffe.cpp:501] detection_eval = 13.9556
-I0511 11:50:55.654203  5581 caffe.cpp:501] detection_eval = 0.037428
-I0511 11:50:55.654211  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654219  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654227  5581 caffe.cpp:501] detection_eval = 1.28831
-I0511 11:50:55.654235  5581 caffe.cpp:501] detection_eval = 14.006
-I0511 11:50:55.654243  5581 caffe.cpp:501] detection_eval = 0.0395422
-I0511 11:50:55.654251  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654258  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654265  5581 caffe.cpp:501] detection_eval = 1.29234
-I0511 11:50:55.654273  5581 caffe.cpp:501] detection_eval = 14
-I0511 11:50:55.654281  5581 caffe.cpp:501] detection_eval = 0.0390295
-I0511 11:50:55.654289  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654297  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654304  5581 caffe.cpp:501] detection_eval = 1.29637
-I0511 11:50:55.654320  5581 caffe.cpp:501] detection_eval = 14
-I0511 11:50:55.654328  5581 caffe.cpp:501] detection_eval = 0.0362773
-I0511 11:50:55.654335  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654343  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654350  5581 caffe.cpp:501] detection_eval = 1.29637
-I0511 11:50:55.654358  5581 caffe.cpp:501] detection_eval = 14.1008
-I0511 11:50:55.654366  5581 caffe.cpp:501] detection_eval = 0.0387912
-I0511 11:50:55.654374  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654382  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654389  5581 caffe.cpp:501] detection_eval = 1.29839
-I0511 11:50:55.654397  5581 caffe.cpp:501] detection_eval = 14.1331
-I0511 11:50:55.654405  5581 caffe.cpp:501] detection_eval = 0.0373136
-I0511 11:50:55.654413  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.654420  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.654428  5581 caffe.cpp:501] detection_eval = 1.3004
-I0511 11:50:55.654433  5581 caffe.cpp:501] detection_eval = 14.1815
-I0511 11:50:55.654439  5581 caffe.cpp:501] detection_eval = 0.0376101
-I0511 11:50:55.654446  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654453  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654460  5581 caffe.cpp:501] detection_eval = 1.30645
-I0511 11:50:55.654465  5581 caffe.cpp:501] detection_eval = 14.1976
-I0511 11:50:55.654474  5581 caffe.cpp:501] detection_eval = 0.0438003
-I0511 11:50:55.654484  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.654491  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.654498  5581 caffe.cpp:501] detection_eval = 1.31048
-I0511 11:50:55.654506  5581 caffe.cpp:501] detection_eval = 14.2238
-I0511 11:50:55.654515  5581 caffe.cpp:501] detection_eval = 0.041372
-I0511 11:50:55.654521  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.654530  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.654537  5581 caffe.cpp:501] detection_eval = 1.3125
-I0511 11:50:55.654546  5581 caffe.cpp:501] detection_eval = 14.2702
-I0511 11:50:55.654552  5581 caffe.cpp:501] detection_eval = 0.0381121
-I0511 11:50:55.654561  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654568  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.654575  5581 caffe.cpp:501] detection_eval = 1.3125
-I0511 11:50:55.654583  5581 caffe.cpp:501] detection_eval = 14.3427
-I0511 11:50:55.654592  5581 caffe.cpp:501] detection_eval = 0.0411211
-I0511 11:50:55.654599  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654606  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.654614  5581 caffe.cpp:501] detection_eval = 1.3125
-I0511 11:50:55.654623  5581 caffe.cpp:501] detection_eval = 14.4194
-I0511 11:50:55.654630  5581 caffe.cpp:501] detection_eval = 0.0381935
-I0511 11:50:55.654637  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.654645  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.654652  5581 caffe.cpp:501] detection_eval = 1.31452
-I0511 11:50:55.654661  5581 caffe.cpp:501] detection_eval = 14.496
-I0511 11:50:55.654667  5581 caffe.cpp:501] detection_eval = 0.0416936
-I0511 11:50:55.654672  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.654680  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.654685  5581 caffe.cpp:501] detection_eval = 1.32056
-I0511 11:50:55.654690  5581 caffe.cpp:501] detection_eval = 14.5141
-I0511 11:50:55.654695  5581 caffe.cpp:501] detection_eval = 0.0391074
-I0511 11:50:55.654700  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654703  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654708  5581 caffe.cpp:501] detection_eval = 1.32056
-I0511 11:50:55.654712  5581 caffe.cpp:501] detection_eval = 14.5665
-I0511 11:50:55.654717  5581 caffe.cpp:501] detection_eval = 0.0356851
-I0511 11:50:55.654724  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.654731  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654739  5581 caffe.cpp:501] detection_eval = 1.32056
-I0511 11:50:55.654752  5581 caffe.cpp:501] detection_eval = 14.7419
-I0511 11:50:55.654762  5581 caffe.cpp:501] detection_eval = 0.0367648
-I0511 11:50:55.654769  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.654778  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654785  5581 caffe.cpp:501] detection_eval = 1.32056
-I0511 11:50:55.654793  5581 caffe.cpp:501] detection_eval = 14.9657
-I0511 11:50:55.654800  5581 caffe.cpp:501] detection_eval = 0.0389562
-I0511 11:50:55.654808  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.654815  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654824  5581 caffe.cpp:501] detection_eval = 1.3246
-I0511 11:50:55.654831  5581 caffe.cpp:501] detection_eval = 15.1835
-I0511 11:50:55.654839  5581 caffe.cpp:501] detection_eval = 0.0328463
-I0511 11:50:55.654847  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.654855  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.654862  5581 caffe.cpp:501] detection_eval = 1.32661
-I0511 11:50:55.654870  5581 caffe.cpp:501] detection_eval = 15.5343
-I0511 11:50:55.654878  5581 caffe.cpp:501] detection_eval = 0.0305074
-I0511 11:50:55.654886  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.654893  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.654901  5581 caffe.cpp:501] detection_eval = 2.03226
-I0511 11:50:55.654909  5581 caffe.cpp:501] detection_eval = 5.1129
-I0511 11:50:55.654917  5581 caffe.cpp:501] detection_eval = 0.132968
-I0511 11:50:55.654925  5581 caffe.cpp:501] detection_eval = 0.118952
-I0511 11:50:55.654933  5581 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:50:55.654940  5581 caffe.cpp:501] detection_eval = 2.03226
-I0511 11:50:55.654948  5581 caffe.cpp:501] detection_eval = 5.41532
-I0511 11:50:55.654958  5581 caffe.cpp:501] detection_eval = 0.0767423
-I0511 11:50:55.654970  5581 caffe.cpp:501] detection_eval = 0.0483871
-I0511 11:50:55.654974  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.654979  5581 caffe.cpp:501] detection_eval = 2.03226
-I0511 11:50:55.654983  5581 caffe.cpp:501] detection_eval = 5.6371
-I0511 11:50:55.654989  5581 caffe.cpp:501] detection_eval = 0.0650996
-I0511 11:50:55.654992  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.654997  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.655001  5581 caffe.cpp:501] detection_eval = 2.03629
-I0511 11:50:55.655006  5581 caffe.cpp:501] detection_eval = 5.74194
-I0511 11:50:55.655010  5581 caffe.cpp:501] detection_eval = 0.046285
-I0511 11:50:55.655014  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655019  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655023  5581 caffe.cpp:501] detection_eval = 2.03831
-I0511 11:50:55.655028  5581 caffe.cpp:501] detection_eval = 5.83468
-I0511 11:50:55.655032  5581 caffe.cpp:501] detection_eval = 0.0510127
-I0511 11:50:55.655036  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.655041  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.655045  5581 caffe.cpp:501] detection_eval = 2.03831
-I0511 11:50:55.655050  5581 caffe.cpp:501] detection_eval = 6.02621
-I0511 11:50:55.655055  5581 caffe.cpp:501] detection_eval = 0.0508325
-I0511 11:50:55.655059  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.655063  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.655067  5581 caffe.cpp:501] detection_eval = 2.04032
-I0511 11:50:55.655072  5581 caffe.cpp:501] detection_eval = 6.06653
-I0511 11:50:55.655076  5581 caffe.cpp:501] detection_eval = 0.0428764
-I0511 11:50:55.655081  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655086  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655091  5581 caffe.cpp:501] detection_eval = 2.04032
-I0511 11:50:55.655094  5581 caffe.cpp:501] detection_eval = 6.14718
-I0511 11:50:55.655098  5581 caffe.cpp:501] detection_eval = 0.0447347
-I0511 11:50:55.655103  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.655107  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655117  5581 caffe.cpp:501] detection_eval = 2.04234
-I0511 11:50:55.655120  5581 caffe.cpp:501] detection_eval = 6.25
-I0511 11:50:55.655125  5581 caffe.cpp:501] detection_eval = 0.0436314
-I0511 11:50:55.655129  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655134  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.655138  5581 caffe.cpp:501] detection_eval = 2.04839
-I0511 11:50:55.655143  5581 caffe.cpp:501] detection_eval = 6.2621
-I0511 11:50:55.655148  5581 caffe.cpp:501] detection_eval = 0.0444333
-I0511 11:50:55.655153  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655156  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655161  5581 caffe.cpp:501] detection_eval = 2.0504
-I0511 11:50:55.655165  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.655169  5581 caffe.cpp:501] detection_eval = 0.0379169
-I0511 11:50:55.655174  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655179  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655184  5581 caffe.cpp:501] detection_eval = 2.0504
-I0511 11:50:55.655187  5581 caffe.cpp:501] detection_eval = 6.42137
-I0511 11:50:55.655192  5581 caffe.cpp:501] detection_eval = 0.0442222
-I0511 11:50:55.655196  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.655200  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655205  5581 caffe.cpp:501] detection_eval = 2.05444
-I0511 11:50:55.655210  5581 caffe.cpp:501] detection_eval = 6.46371
-I0511 11:50:55.655213  5581 caffe.cpp:501] detection_eval = 0.0433093
-I0511 11:50:55.655218  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.655222  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655227  5581 caffe.cpp:501] detection_eval = 2.05847
-I0511 11:50:55.655231  5581 caffe.cpp:501] detection_eval = 6.52419
-I0511 11:50:55.655236  5581 caffe.cpp:501] detection_eval = 0.0444015
-I0511 11:50:55.655241  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655244  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.655249  5581 caffe.cpp:501] detection_eval = 2.05847
-I0511 11:50:55.655253  5581 caffe.cpp:501] detection_eval = 6.60887
-I0511 11:50:55.655258  5581 caffe.cpp:501] detection_eval = 0.0375061
-I0511 11:50:55.655262  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655267  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.655272  5581 caffe.cpp:501] detection_eval = 2.05847
-I0511 11:50:55.655275  5581 caffe.cpp:501] detection_eval = 6.68347
-I0511 11:50:55.655280  5581 caffe.cpp:501] detection_eval = 0.0366371
-I0511 11:50:55.655284  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.655289  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655293  5581 caffe.cpp:501] detection_eval = 2.06452
-I0511 11:50:55.655297  5581 caffe.cpp:501] detection_eval = 6.6754
-I0511 11:50:55.655303  5581 caffe.cpp:501] detection_eval = 0.0425301
-I0511 11:50:55.655306  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.655311  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655315  5581 caffe.cpp:501] detection_eval = 2.06855
-I0511 11:50:55.655319  5581 caffe.cpp:501] detection_eval = 6.71774
-I0511 11:50:55.655324  5581 caffe.cpp:501] detection_eval = 0.0502925
-I0511 11:50:55.655328  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.655333  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.655338  5581 caffe.cpp:501] detection_eval = 2.07056
-I0511 11:50:55.655341  5581 caffe.cpp:501] detection_eval = 6.74194
-I0511 11:50:55.655346  5581 caffe.cpp:501] detection_eval = 0.0441572
-I0511 11:50:55.655350  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.655355  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.655359  5581 caffe.cpp:501] detection_eval = 2.07258
-I0511 11:50:55.655364  5581 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:50:55.655369  5581 caffe.cpp:501] detection_eval = 0.0410851
-I0511 11:50:55.655372  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655377  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655385  5581 caffe.cpp:501] detection_eval = 2.0746
-I0511 11:50:55.655390  5581 caffe.cpp:501] detection_eval = 6.89315
-I0511 11:50:55.655393  5581 caffe.cpp:501] detection_eval = 0.0467197
-I0511 11:50:55.655398  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.655402  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.655407  5581 caffe.cpp:501] detection_eval = 2.0746
-I0511 11:50:55.655411  5581 caffe.cpp:501] detection_eval = 6.98589
-I0511 11:50:55.655416  5581 caffe.cpp:501] detection_eval = 0.0467414
-I0511 11:50:55.655421  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.655424  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.655429  5581 caffe.cpp:501] detection_eval = 2.07661
-I0511 11:50:55.655433  5581 caffe.cpp:501] detection_eval = 7.03427
-I0511 11:50:55.655437  5581 caffe.cpp:501] detection_eval = 0.0414753
-I0511 11:50:55.655442  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655447  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655452  5581 caffe.cpp:501] detection_eval = 2.08065
-I0511 11:50:55.655455  5581 caffe.cpp:501] detection_eval = 7.05444
-I0511 11:50:55.655460  5581 caffe.cpp:501] detection_eval = 0.0484892
-I0511 11:50:55.655464  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.655468  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.655473  5581 caffe.cpp:501] detection_eval = 2.08468
-I0511 11:50:55.655478  5581 caffe.cpp:501] detection_eval = 7.09677
-I0511 11:50:55.655481  5581 caffe.cpp:501] detection_eval = 0.0469197
-I0511 11:50:55.655486  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.655490  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.655495  5581 caffe.cpp:501] detection_eval = 2.08468
-I0511 11:50:55.655499  5581 caffe.cpp:501] detection_eval = 7.17742
-I0511 11:50:55.655503  5581 caffe.cpp:501] detection_eval = 0.0450967
-I0511 11:50:55.655508  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655513  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.655517  5581 caffe.cpp:501] detection_eval = 2.08871
-I0511 11:50:55.655521  5581 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:50:55.655525  5581 caffe.cpp:501] detection_eval = 0.0410055
-I0511 11:50:55.655530  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.655534  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.655539  5581 caffe.cpp:501] detection_eval = 2.08871
-I0511 11:50:55.655544  5581 caffe.cpp:501] detection_eval = 7.32056
-I0511 11:50:55.655547  5581 caffe.cpp:501] detection_eval = 0.0405258
-I0511 11:50:55.655552  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655556  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655561  5581 caffe.cpp:501] detection_eval = 2.09274
-I0511 11:50:55.655565  5581 caffe.cpp:501] detection_eval = 7.32863
-I0511 11:50:55.655570  5581 caffe.cpp:501] detection_eval = 0.0397538
-I0511 11:50:55.655575  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655578  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655583  5581 caffe.cpp:501] detection_eval = 2.09476
-I0511 11:50:55.655587  5581 caffe.cpp:501] detection_eval = 7.38306
-I0511 11:50:55.655591  5581 caffe.cpp:501] detection_eval = 0.0413817
-I0511 11:50:55.655596  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.655601  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655606  5581 caffe.cpp:501] detection_eval = 2.09879
-I0511 11:50:55.655609  5581 caffe.cpp:501] detection_eval = 7.375
-I0511 11:50:55.655613  5581 caffe.cpp:501] detection_eval = 0.0433942
-I0511 11:50:55.655618  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655622  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.655627  5581 caffe.cpp:501] detection_eval = 2.10081
-I0511 11:50:55.655632  5581 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:50:55.655637  5581 caffe.cpp:501] detection_eval = 0.0413281
-I0511 11:50:55.655640  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655647  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.655652  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655656  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.655661  5581 caffe.cpp:501] detection_eval = 0.0418032
-I0511 11:50:55.655665  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655670  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.655674  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655678  5581 caffe.cpp:501] detection_eval = 7.49597
-I0511 11:50:55.655683  5581 caffe.cpp:501] detection_eval = 0.0442379
-I0511 11:50:55.655688  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.655692  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.655696  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655701  5581 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:50:55.655705  5581 caffe.cpp:501] detection_eval = 0.0417567
-I0511 11:50:55.655710  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655714  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655719  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655724  5581 caffe.cpp:501] detection_eval = 7.62903
-I0511 11:50:55.655727  5581 caffe.cpp:501] detection_eval = 0.0417958
-I0511 11:50:55.655732  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655736  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655741  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655745  5581 caffe.cpp:501] detection_eval = 7.67944
-I0511 11:50:55.655750  5581 caffe.cpp:501] detection_eval = 0.0386043
-I0511 11:50:55.655753  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.655758  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.655762  5581 caffe.cpp:501] detection_eval = 2.10484
-I0511 11:50:55.655767  5581 caffe.cpp:501] detection_eval = 7.75806
-I0511 11:50:55.655771  5581 caffe.cpp:501] detection_eval = 0.0407014
-I0511 11:50:55.655776  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655781  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655784  5581 caffe.cpp:501] detection_eval = 2.10887
-I0511 11:50:55.655789  5581 caffe.cpp:501] detection_eval = 7.73589
-I0511 11:50:55.655793  5581 caffe.cpp:501] detection_eval = 0.0427375
-I0511 11:50:55.655797  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655802  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.655807  5581 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:50:55.655810  5581 caffe.cpp:501] detection_eval = 7.79435
-I0511 11:50:55.655815  5581 caffe.cpp:501] detection_eval = 0.0348502
-I0511 11:50:55.655819  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.655824  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.655828  5581 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:50:55.655833  5581 caffe.cpp:501] detection_eval = 7.89718
-I0511 11:50:55.655838  5581 caffe.cpp:501] detection_eval = 0.0354301
-I0511 11:50:55.655841  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.655846  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.655850  5581 caffe.cpp:501] detection_eval = 2.11089
-I0511 11:50:55.655855  5581 caffe.cpp:501] detection_eval = 7.96169
-I0511 11:50:55.655859  5581 caffe.cpp:501] detection_eval = 0.0419408
-I0511 11:50:55.655864  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655869  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.655874  5581 caffe.cpp:501] detection_eval = 2.1129
-I0511 11:50:55.655877  5581 caffe.cpp:501] detection_eval = 8.02823
-I0511 11:50:55.655882  5581 caffe.cpp:501] detection_eval = 0.0383237
-I0511 11:50:55.655886  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.655890  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.655895  5581 caffe.cpp:501] detection_eval = 2.11694
-I0511 11:50:55.655900  5581 caffe.cpp:501] detection_eval = 8.05847
-I0511 11:50:55.655905  5581 caffe.cpp:501] detection_eval = 0.0404135
-I0511 11:50:55.655911  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.655916  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.655920  5581 caffe.cpp:501] detection_eval = 2.11895
-I0511 11:50:55.655925  5581 caffe.cpp:501] detection_eval = 8.10484
-I0511 11:50:55.655930  5581 caffe.cpp:501] detection_eval = 0.0386075
-I0511 11:50:55.655933  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655938  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.655942  5581 caffe.cpp:501] detection_eval = 2.12097
-I0511 11:50:55.655947  5581 caffe.cpp:501] detection_eval = 8.15726
-I0511 11:50:55.655951  5581 caffe.cpp:501] detection_eval = 0.0353515
-I0511 11:50:55.655956  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.655961  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.655966  5581 caffe.cpp:501] detection_eval = 2.12097
-I0511 11:50:55.655969  5581 caffe.cpp:501] detection_eval = 8.28427
-I0511 11:50:55.655974  5581 caffe.cpp:501] detection_eval = 0.0456017
-I0511 11:50:55.655978  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.655982  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.655987  5581 caffe.cpp:501] detection_eval = 2.12298
-I0511 11:50:55.655992  5581 caffe.cpp:501] detection_eval = 8.35685
-I0511 11:50:55.655997  5581 caffe.cpp:501] detection_eval = 0.0364799
-I0511 11:50:55.656000  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.656004  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.656009  5581 caffe.cpp:501] detection_eval = 2.12903
-I0511 11:50:55.656013  5581 caffe.cpp:501] detection_eval = 8.36895
-I0511 11:50:55.656018  5581 caffe.cpp:501] detection_eval = 0.0499687
-I0511 11:50:55.656023  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.656026  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656031  5581 caffe.cpp:501] detection_eval = 2.13306
-I0511 11:50:55.656035  5581 caffe.cpp:501] detection_eval = 8.42339
-I0511 11:50:55.656040  5581 caffe.cpp:501] detection_eval = 0.0447311
-I0511 11:50:55.656044  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656049  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656054  5581 caffe.cpp:501] detection_eval = 2.13508
-I0511 11:50:55.656057  5581 caffe.cpp:501] detection_eval = 8.43952
-I0511 11:50:55.656062  5581 caffe.cpp:501] detection_eval = 0.0376752
-I0511 11:50:55.656066  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656071  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.656075  5581 caffe.cpp:501] detection_eval = 2.1371
-I0511 11:50:55.656080  5581 caffe.cpp:501] detection_eval = 8.48185
-I0511 11:50:55.656085  5581 caffe.cpp:501] detection_eval = 0.0475302
-I0511 11:50:55.656090  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.656093  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.656098  5581 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:50:55.656102  5581 caffe.cpp:501] detection_eval = 8.52823
-I0511 11:50:55.656107  5581 caffe.cpp:501] detection_eval = 0.0420878
-I0511 11:50:55.656111  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656116  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656121  5581 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:50:55.656126  5581 caffe.cpp:501] detection_eval = 8.64718
-I0511 11:50:55.656129  5581 caffe.cpp:501] detection_eval = 0.0512985
-I0511 11:50:55.656134  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.656138  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.656143  5581 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:50:55.656147  5581 caffe.cpp:501] detection_eval = 8.7621
-I0511 11:50:55.656152  5581 caffe.cpp:501] detection_eval = 0.0481503
-I0511 11:50:55.656157  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.656162  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656165  5581 caffe.cpp:501] detection_eval = 2.13911
-I0511 11:50:55.656169  5581 caffe.cpp:501] detection_eval = 8.83871
-I0511 11:50:55.656174  5581 caffe.cpp:501] detection_eval = 0.0419182
-I0511 11:50:55.656181  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656186  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656190  5581 caffe.cpp:501] detection_eval = 2.14315
-I0511 11:50:55.656195  5581 caffe.cpp:501] detection_eval = 8.83266
-I0511 11:50:55.656199  5581 caffe.cpp:501] detection_eval = 0.0370229
-I0511 11:50:55.656204  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656208  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.656213  5581 caffe.cpp:501] detection_eval = 2.14315
-I0511 11:50:55.656217  5581 caffe.cpp:501] detection_eval = 8.90726
-I0511 11:50:55.656221  5581 caffe.cpp:501] detection_eval = 0.0399283
-I0511 11:50:55.656226  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656230  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656235  5581 caffe.cpp:501] detection_eval = 2.14516
-I0511 11:50:55.656239  5581 caffe.cpp:501] detection_eval = 8.96371
-I0511 11:50:55.656244  5581 caffe.cpp:501] detection_eval = 0.0429597
-I0511 11:50:55.656249  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656253  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.656257  5581 caffe.cpp:501] detection_eval = 2.14718
-I0511 11:50:55.656261  5581 caffe.cpp:501] detection_eval = 8.99798
-I0511 11:50:55.656266  5581 caffe.cpp:501] detection_eval = 0.0425507
-I0511 11:50:55.656270  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656275  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.656280  5581 caffe.cpp:501] detection_eval = 2.14919
-I0511 11:50:55.656283  5581 caffe.cpp:501] detection_eval = 9.04637
-I0511 11:50:55.656288  5581 caffe.cpp:501] detection_eval = 0.0384549
-I0511 11:50:55.656292  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656297  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656301  5581 caffe.cpp:501] detection_eval = 2.15323
-I0511 11:50:55.656306  5581 caffe.cpp:501] detection_eval = 9.11694
-I0511 11:50:55.656311  5581 caffe.cpp:501] detection_eval = 0.0420552
-I0511 11:50:55.656316  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656319  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656323  5581 caffe.cpp:501] detection_eval = 2.15323
-I0511 11:50:55.656328  5581 caffe.cpp:501] detection_eval = 9.25202
-I0511 11:50:55.656332  5581 caffe.cpp:501] detection_eval = 0.0472095
-I0511 11:50:55.656337  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.656342  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.656345  5581 caffe.cpp:501] detection_eval = 2.15524
-I0511 11:50:55.656350  5581 caffe.cpp:501] detection_eval = 9.32661
-I0511 11:50:55.656354  5581 caffe.cpp:501] detection_eval = 0.0473926
-I0511 11:50:55.656359  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656363  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.656368  5581 caffe.cpp:501] detection_eval = 2.15726
-I0511 11:50:55.656373  5581 caffe.cpp:501] detection_eval = 9.41129
-I0511 11:50:55.656378  5581 caffe.cpp:501] detection_eval = 0.0481998
-I0511 11:50:55.656381  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.656386  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656390  5581 caffe.cpp:501] detection_eval = 2.15927
-I0511 11:50:55.656394  5581 caffe.cpp:501] detection_eval = 9.4496
-I0511 11:50:55.656399  5581 caffe.cpp:501] detection_eval = 0.0434614
-I0511 11:50:55.656404  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.656409  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656412  5581 caffe.cpp:501] detection_eval = 2.15927
-I0511 11:50:55.656417  5581 caffe.cpp:501] detection_eval = 9.5
-I0511 11:50:55.656421  5581 caffe.cpp:501] detection_eval = 0.044086
-I0511 11:50:55.656426  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656430  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656435  5581 caffe.cpp:501] detection_eval = 2.15927
-I0511 11:50:55.656440  5581 caffe.cpp:501] detection_eval = 9.60081
-I0511 11:50:55.656446  5581 caffe.cpp:501] detection_eval = 0.0431457
-I0511 11:50:55.656451  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.656456  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.656461  5581 caffe.cpp:501] detection_eval = 2.15927
-I0511 11:50:55.656464  5581 caffe.cpp:501] detection_eval = 9.6875
-I0511 11:50:55.656469  5581 caffe.cpp:501] detection_eval = 0.0463762
-I0511 11:50:55.656473  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656478  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656483  5581 caffe.cpp:501] detection_eval = 2.16331
-I0511 11:50:55.656487  5581 caffe.cpp:501] detection_eval = 9.72177
-I0511 11:50:55.656491  5581 caffe.cpp:501] detection_eval = 0.0428794
-I0511 11:50:55.656497  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656500  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656505  5581 caffe.cpp:501] detection_eval = 2.16532
-I0511 11:50:55.656509  5581 caffe.cpp:501] detection_eval = 9.79234
-I0511 11:50:55.656514  5581 caffe.cpp:501] detection_eval = 0.0423227
-I0511 11:50:55.656518  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.656523  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656533  5581 caffe.cpp:501] detection_eval = 2.16734
-I0511 11:50:55.656536  5581 caffe.cpp:501] detection_eval = 9.82863
-I0511 11:50:55.656539  5581 caffe.cpp:501] detection_eval = 0.0416507
-I0511 11:50:55.656543  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.656548  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656551  5581 caffe.cpp:501] detection_eval = 2.17137
-I0511 11:50:55.656556  5581 caffe.cpp:501] detection_eval = 9.85484
-I0511 11:50:55.656560  5581 caffe.cpp:501] detection_eval = 0.0412244
-I0511 11:50:55.656565  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656569  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.656574  5581 caffe.cpp:501] detection_eval = 2.17137
-I0511 11:50:55.656579  5581 caffe.cpp:501] detection_eval = 9.92944
-I0511 11:50:55.656584  5581 caffe.cpp:501] detection_eval = 0.0419297
-I0511 11:50:55.656587  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.656592  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656596  5581 caffe.cpp:501] detection_eval = 2.17339
-I0511 11:50:55.656601  5581 caffe.cpp:501] detection_eval = 10.0101
-I0511 11:50:55.656605  5581 caffe.cpp:501] detection_eval = 0.0429888
-I0511 11:50:55.656610  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656615  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656620  5581 caffe.cpp:501] detection_eval = 2.17339
-I0511 11:50:55.656623  5581 caffe.cpp:501] detection_eval = 10.0706
-I0511 11:50:55.656628  5581 caffe.cpp:501] detection_eval = 0.0388895
-I0511 11:50:55.656632  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.656637  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656641  5581 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:50:55.656646  5581 caffe.cpp:501] detection_eval = 10.1411
-I0511 11:50:55.656651  5581 caffe.cpp:501] detection_eval = 0.0401069
-I0511 11:50:55.656656  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.656661  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656664  5581 caffe.cpp:501] detection_eval = 2.17742
-I0511 11:50:55.656668  5581 caffe.cpp:501] detection_eval = 10.2177
-I0511 11:50:55.656673  5581 caffe.cpp:501] detection_eval = 0.0438226
-I0511 11:50:55.656678  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.656682  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.656687  5581 caffe.cpp:501] detection_eval = 2.17944
-I0511 11:50:55.656692  5581 caffe.cpp:501] detection_eval = 10.3024
-I0511 11:50:55.656695  5581 caffe.cpp:501] detection_eval = 0.0466152
-I0511 11:50:55.656700  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.656704  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656709  5581 caffe.cpp:501] detection_eval = 2.18145
-I0511 11:50:55.656713  5581 caffe.cpp:501] detection_eval = 10.3488
-I0511 11:50:55.656723  5581 caffe.cpp:501] detection_eval = 0.0422544
-I0511 11:50:55.656726  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.656731  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.656736  5581 caffe.cpp:501] detection_eval = 2.18347
-I0511 11:50:55.656740  5581 caffe.cpp:501] detection_eval = 10.377
-I0511 11:50:55.656745  5581 caffe.cpp:501] detection_eval = 0.0389843
-I0511 11:50:55.656749  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656754  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.656759  5581 caffe.cpp:501] detection_eval = 2.18548
-I0511 11:50:55.656764  5581 caffe.cpp:501] detection_eval = 10.4536
-I0511 11:50:55.656767  5581 caffe.cpp:501] detection_eval = 0.0482508
-I0511 11:50:55.656772  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.656776  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.656781  5581 caffe.cpp:501] detection_eval = 2.18952
-I0511 11:50:55.656785  5581 caffe.cpp:501] detection_eval = 10.4819
-I0511 11:50:55.656790  5581 caffe.cpp:501] detection_eval = 0.0443439
-I0511 11:50:55.656795  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656800  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656803  5581 caffe.cpp:501] detection_eval = 2.19355
-I0511 11:50:55.656807  5581 caffe.cpp:501] detection_eval = 10.4879
-I0511 11:50:55.656812  5581 caffe.cpp:501] detection_eval = 0.0382944
-I0511 11:50:55.656816  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.656821  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.656826  5581 caffe.cpp:501] detection_eval = 2.19556
-I0511 11:50:55.656831  5581 caffe.cpp:501] detection_eval = 10.5141
-I0511 11:50:55.656834  5581 caffe.cpp:501] detection_eval = 0.0436659
-I0511 11:50:55.656839  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.656843  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.656848  5581 caffe.cpp:501] detection_eval = 2.19556
-I0511 11:50:55.656852  5581 caffe.cpp:501] detection_eval = 10.5585
-I0511 11:50:55.656857  5581 caffe.cpp:501] detection_eval = 0.0429225
-I0511 11:50:55.656862  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.656867  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.656870  5581 caffe.cpp:501] detection_eval = 2.20161
-I0511 11:50:55.656875  5581 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:50:55.656879  5581 caffe.cpp:501] detection_eval = 0.043948
-I0511 11:50:55.656884  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.656888  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.656893  5581 caffe.cpp:501] detection_eval = 2.20161
-I0511 11:50:55.656898  5581 caffe.cpp:501] detection_eval = 10.627
-I0511 11:50:55.656903  5581 caffe.cpp:501] detection_eval = 0.0418339
-I0511 11:50:55.656908  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.656911  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.656915  5581 caffe.cpp:501] detection_eval = 2.20363
-I0511 11:50:55.656920  5581 caffe.cpp:501] detection_eval = 10.6331
-I0511 11:50:55.656925  5581 caffe.cpp:501] detection_eval = 0.0455964
-I0511 11:50:55.656929  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.656934  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.656939  5581 caffe.cpp:501] detection_eval = 2.20363
-I0511 11:50:55.656942  5581 caffe.cpp:501] detection_eval = 10.6875
-I0511 11:50:55.656947  5581 caffe.cpp:501] detection_eval = 0.0433667
-I0511 11:50:55.656952  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.656956  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.656961  5581 caffe.cpp:501] detection_eval = 2.20363
-I0511 11:50:55.656965  5581 caffe.cpp:501] detection_eval = 10.7722
-I0511 11:50:55.656970  5581 caffe.cpp:501] detection_eval = 0.0418561
-I0511 11:50:55.656975  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.656980  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.656985  5581 caffe.cpp:501] detection_eval = 2.20968
-I0511 11:50:55.656991  5581 caffe.cpp:501] detection_eval = 10.8004
-I0511 11:50:55.656996  5581 caffe.cpp:501] detection_eval = 0.0499823
-I0511 11:50:55.657001  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.657006  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657011  5581 caffe.cpp:501] detection_eval = 2.21169
-I0511 11:50:55.657014  5581 caffe.cpp:501] detection_eval = 10.8387
-I0511 11:50:55.657019  5581 caffe.cpp:501] detection_eval = 0.0439527
-I0511 11:50:55.657023  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657028  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657032  5581 caffe.cpp:501] detection_eval = 2.21573
-I0511 11:50:55.657037  5581 caffe.cpp:501] detection_eval = 10.8448
-I0511 11:50:55.657042  5581 caffe.cpp:501] detection_eval = 0.0450626
-I0511 11:50:55.657047  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.657050  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.657055  5581 caffe.cpp:501] detection_eval = 2.21976
-I0511 11:50:55.657059  5581 caffe.cpp:501] detection_eval = 10.871
-I0511 11:50:55.657064  5581 caffe.cpp:501] detection_eval = 0.0397917
-I0511 11:50:55.657068  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657073  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.657078  5581 caffe.cpp:501] detection_eval = 2.22177
-I0511 11:50:55.657083  5581 caffe.cpp:501] detection_eval = 10.9173
-I0511 11:50:55.657088  5581 caffe.cpp:501] detection_eval = 0.0396326
-I0511 11:50:55.657093  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657096  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657101  5581 caffe.cpp:501] detection_eval = 2.22177
-I0511 11:50:55.657105  5581 caffe.cpp:501] detection_eval = 10.9798
-I0511 11:50:55.657110  5581 caffe.cpp:501] detection_eval = 0.0403599
-I0511 11:50:55.657115  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.657119  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657124  5581 caffe.cpp:501] detection_eval = 2.22984
-I0511 11:50:55.657129  5581 caffe.cpp:501] detection_eval = 10.9617
-I0511 11:50:55.657133  5581 caffe.cpp:501] detection_eval = 0.0476307
-I0511 11:50:55.657137  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657142  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657147  5581 caffe.cpp:501] detection_eval = 2.23185
-I0511 11:50:55.657151  5581 caffe.cpp:501] detection_eval = 10.9819
-I0511 11:50:55.657156  5581 caffe.cpp:501] detection_eval = 0.0392576
-I0511 11:50:55.657160  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657166  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657171  5581 caffe.cpp:501] detection_eval = 2.23992
-I0511 11:50:55.657174  5581 caffe.cpp:501] detection_eval = 11.006
-I0511 11:50:55.657179  5581 caffe.cpp:501] detection_eval = 0.0496554
-I0511 11:50:55.657183  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.657188  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.657192  5581 caffe.cpp:501] detection_eval = 2.24597
-I0511 11:50:55.657197  5581 caffe.cpp:501] detection_eval = 10.9476
-I0511 11:50:55.657202  5581 caffe.cpp:501] detection_eval = 0.0398903
-I0511 11:50:55.657207  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657210  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657215  5581 caffe.cpp:501] detection_eval = 2.25
-I0511 11:50:55.657220  5581 caffe.cpp:501] detection_eval = 10.9617
-I0511 11:50:55.657225  5581 caffe.cpp:501] detection_eval = 0.0407143
-I0511 11:50:55.657230  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657234  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657239  5581 caffe.cpp:501] detection_eval = 2.25202
-I0511 11:50:55.657243  5581 caffe.cpp:501] detection_eval = 11.0262
-I0511 11:50:55.657248  5581 caffe.cpp:501] detection_eval = 0.0404579
-I0511 11:50:55.657253  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657258  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.657268  5581 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:50:55.657272  5581 caffe.cpp:501] detection_eval = 11.0585
-I0511 11:50:55.657277  5581 caffe.cpp:501] detection_eval = 0.0486328
-I0511 11:50:55.657282  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.657286  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657291  5581 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:50:55.657296  5581 caffe.cpp:501] detection_eval = 11.1452
-I0511 11:50:55.657301  5581 caffe.cpp:501] detection_eval = 0.0444327
-I0511 11:50:55.657305  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657311  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657315  5581 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:50:55.657320  5581 caffe.cpp:501] detection_eval = 11.1976
-I0511 11:50:55.657325  5581 caffe.cpp:501] detection_eval = 0.0420833
-I0511 11:50:55.657331  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657336  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657341  5581 caffe.cpp:501] detection_eval = 2.25605
-I0511 11:50:55.657344  5581 caffe.cpp:501] detection_eval = 11.2581
-I0511 11:50:55.657349  5581 caffe.cpp:501] detection_eval = 0.0406848
-I0511 11:50:55.657354  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.657359  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657362  5581 caffe.cpp:501] detection_eval = 2.25806
-I0511 11:50:55.657366  5581 caffe.cpp:501] detection_eval = 11.2964
-I0511 11:50:55.657372  5581 caffe.cpp:501] detection_eval = 0.0420972
-I0511 11:50:55.657377  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657382  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657387  5581 caffe.cpp:501] detection_eval = 2.26008
-I0511 11:50:55.657390  5581 caffe.cpp:501] detection_eval = 11.3589
-I0511 11:50:55.657395  5581 caffe.cpp:501] detection_eval = 0.0446766
-I0511 11:50:55.657399  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657404  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657408  5581 caffe.cpp:501] detection_eval = 2.2621
-I0511 11:50:55.657413  5581 caffe.cpp:501] detection_eval = 11.4093
-I0511 11:50:55.657418  5581 caffe.cpp:501] detection_eval = 0.0477488
-I0511 11:50:55.657423  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.657428  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.657433  5581 caffe.cpp:501] detection_eval = 2.26613
-I0511 11:50:55.657436  5581 caffe.cpp:501] detection_eval = 11.4254
-I0511 11:50:55.657441  5581 caffe.cpp:501] detection_eval = 0.0441837
-I0511 11:50:55.657446  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.657450  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657455  5581 caffe.cpp:501] detection_eval = 2.27016
-I0511 11:50:55.657459  5581 caffe.cpp:501] detection_eval = 11.4073
-I0511 11:50:55.657464  5581 caffe.cpp:501] detection_eval = 0.0433764
-I0511 11:50:55.657469  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657474  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657479  5581 caffe.cpp:501] detection_eval = 2.27016
-I0511 11:50:55.657482  5581 caffe.cpp:501] detection_eval = 11.4919
-I0511 11:50:55.657487  5581 caffe.cpp:501] detection_eval = 0.0418392
-I0511 11:50:55.657491  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.657496  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657500  5581 caffe.cpp:501] detection_eval = 2.27016
-I0511 11:50:55.657505  5581 caffe.cpp:501] detection_eval = 11.5464
-I0511 11:50:55.657510  5581 caffe.cpp:501] detection_eval = 0.0392405
-I0511 11:50:55.657515  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.657519  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.657524  5581 caffe.cpp:501] detection_eval = 2.27218
-I0511 11:50:55.657528  5581 caffe.cpp:501] detection_eval = 11.5867
-I0511 11:50:55.657533  5581 caffe.cpp:501] detection_eval = 0.0387267
-I0511 11:50:55.657537  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.657542  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657550  5581 caffe.cpp:501] detection_eval = 2.27218
-I0511 11:50:55.657555  5581 caffe.cpp:501] detection_eval = 11.6351
-I0511 11:50:55.657560  5581 caffe.cpp:501] detection_eval = 0.0385455
-I0511 11:50:55.657564  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.657569  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.657574  5581 caffe.cpp:501] detection_eval = 2.27419
-I0511 11:50:55.657579  5581 caffe.cpp:501] detection_eval = 11.6593
-I0511 11:50:55.657584  5581 caffe.cpp:501] detection_eval = 0.0409101
-I0511 11:50:55.657588  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657593  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.657598  5581 caffe.cpp:501] detection_eval = 2.27419
-I0511 11:50:55.657601  5581 caffe.cpp:501] detection_eval = 11.7036
-I0511 11:50:55.657606  5581 caffe.cpp:501] detection_eval = 0.0402169
-I0511 11:50:55.657611  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657615  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.657620  5581 caffe.cpp:501] detection_eval = 2.27823
-I0511 11:50:55.657624  5581 caffe.cpp:501] detection_eval = 11.6875
-I0511 11:50:55.657629  5581 caffe.cpp:501] detection_eval = 0.0424572
-I0511 11:50:55.657634  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657639  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657644  5581 caffe.cpp:501] detection_eval = 2.28024
-I0511 11:50:55.657647  5581 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:50:55.657652  5581 caffe.cpp:501] detection_eval = 0.036214
-I0511 11:50:55.657656  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657661  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657665  5581 caffe.cpp:501] detection_eval = 2.28226
-I0511 11:50:55.657670  5581 caffe.cpp:501] detection_eval = 11.756
-I0511 11:50:55.657675  5581 caffe.cpp:501] detection_eval = 0.0399918
-I0511 11:50:55.657680  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657685  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.657688  5581 caffe.cpp:501] detection_eval = 2.28427
-I0511 11:50:55.657693  5581 caffe.cpp:501] detection_eval = 11.7782
-I0511 11:50:55.657697  5581 caffe.cpp:501] detection_eval = 0.0351907
-I0511 11:50:55.657702  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.657706  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.657711  5581 caffe.cpp:501] detection_eval = 2.28831
-I0511 11:50:55.657716  5581 caffe.cpp:501] detection_eval = 11.8246
-I0511 11:50:55.657721  5581 caffe.cpp:501] detection_eval = 0.0411504
-I0511 11:50:55.657724  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.657729  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.657733  5581 caffe.cpp:501] detection_eval = 2.28831
-I0511 11:50:55.657738  5581 caffe.cpp:501] detection_eval = 11.9435
-I0511 11:50:55.657742  5581 caffe.cpp:501] detection_eval = 0.0389682
-I0511 11:50:55.657747  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.657752  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657757  5581 caffe.cpp:501] detection_eval = 2.29234
-I0511 11:50:55.657760  5581 caffe.cpp:501] detection_eval = 11.9274
-I0511 11:50:55.657765  5581 caffe.cpp:501] detection_eval = 0.0338678
-I0511 11:50:55.657769  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.657774  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.657778  5581 caffe.cpp:501] detection_eval = 2.29234
-I0511 11:50:55.657783  5581 caffe.cpp:501] detection_eval = 12.002
-I0511 11:50:55.657788  5581 caffe.cpp:501] detection_eval = 0.035592
-I0511 11:50:55.657793  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.657796  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.657801  5581 caffe.cpp:501] detection_eval = 2.29435
-I0511 11:50:55.657805  5581 caffe.cpp:501] detection_eval = 12.0464
-I0511 11:50:55.657810  5581 caffe.cpp:501] detection_eval = 0.0399416
-I0511 11:50:55.657815  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657822  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657827  5581 caffe.cpp:501] detection_eval = 2.29839
-I0511 11:50:55.657831  5581 caffe.cpp:501] detection_eval = 12.0484
-I0511 11:50:55.657836  5581 caffe.cpp:501] detection_eval = 0.0391435
-I0511 11:50:55.657840  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657845  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.657850  5581 caffe.cpp:501] detection_eval = 2.30242
-I0511 11:50:55.657855  5581 caffe.cpp:501] detection_eval = 12.0625
-I0511 11:50:55.657860  5581 caffe.cpp:501] detection_eval = 0.0390239
-I0511 11:50:55.657863  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657867  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657872  5581 caffe.cpp:501] detection_eval = 2.30242
-I0511 11:50:55.657876  5581 caffe.cpp:501] detection_eval = 12.2036
-I0511 11:50:55.657881  5581 caffe.cpp:501] detection_eval = 0.0462124
-I0511 11:50:55.657886  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657891  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657894  5581 caffe.cpp:501] detection_eval = 2.30645
-I0511 11:50:55.657899  5581 caffe.cpp:501] detection_eval = 12.2077
-I0511 11:50:55.657904  5581 caffe.cpp:501] detection_eval = 0.046275
-I0511 11:50:55.657908  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.657913  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657917  5581 caffe.cpp:501] detection_eval = 2.30645
-I0511 11:50:55.657922  5581 caffe.cpp:501] detection_eval = 12.2722
-I0511 11:50:55.657927  5581 caffe.cpp:501] detection_eval = 0.0449226
-I0511 11:50:55.657932  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.657935  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.657940  5581 caffe.cpp:501] detection_eval = 2.30847
-I0511 11:50:55.657944  5581 caffe.cpp:501] detection_eval = 12.3125
-I0511 11:50:55.657949  5581 caffe.cpp:501] detection_eval = 0.0419957
-I0511 11:50:55.657953  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.657958  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.657963  5581 caffe.cpp:501] detection_eval = 2.3125
-I0511 11:50:55.657966  5581 caffe.cpp:501] detection_eval = 12.3367
-I0511 11:50:55.657971  5581 caffe.cpp:501] detection_eval = 0.0450801
-I0511 11:50:55.657976  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.657980  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.657985  5581 caffe.cpp:501] detection_eval = 2.31653
-I0511 11:50:55.657989  5581 caffe.cpp:501] detection_eval = 12.3306
-I0511 11:50:55.657994  5581 caffe.cpp:501] detection_eval = 0.0447295
-I0511 11:50:55.657999  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658002  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658007  5581 caffe.cpp:501] detection_eval = 2.32258
-I0511 11:50:55.658011  5581 caffe.cpp:501] detection_eval = 12.3629
-I0511 11:50:55.658016  5581 caffe.cpp:501] detection_eval = 0.0393389
-I0511 11:50:55.658021  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658025  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658030  5581 caffe.cpp:501] detection_eval = 2.32661
-I0511 11:50:55.658035  5581 caffe.cpp:501] detection_eval = 12.4032
-I0511 11:50:55.658040  5581 caffe.cpp:501] detection_eval = 0.0446266
-I0511 11:50:55.658043  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.658048  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.658053  5581 caffe.cpp:501] detection_eval = 2.32863
-I0511 11:50:55.658057  5581 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:50:55.658062  5581 caffe.cpp:501] detection_eval = 0.0412649
-I0511 11:50:55.658066  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658071  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658076  5581 caffe.cpp:501] detection_eval = 2.33065
-I0511 11:50:55.658080  5581 caffe.cpp:501] detection_eval = 12.4355
-I0511 11:50:55.658084  5581 caffe.cpp:501] detection_eval = 0.0417905
-I0511 11:50:55.658092  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658097  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658102  5581 caffe.cpp:501] detection_eval = 2.33266
-I0511 11:50:55.658105  5581 caffe.cpp:501] detection_eval = 12.4415
-I0511 11:50:55.658110  5581 caffe.cpp:501] detection_eval = 0.0390862
-I0511 11:50:55.658115  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658119  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658124  5581 caffe.cpp:501] detection_eval = 2.33468
-I0511 11:50:55.658128  5581 caffe.cpp:501] detection_eval = 12.4859
-I0511 11:50:55.658133  5581 caffe.cpp:501] detection_eval = 0.0435713
-I0511 11:50:55.658138  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658143  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658146  5581 caffe.cpp:501] detection_eval = 2.34274
-I0511 11:50:55.658151  5581 caffe.cpp:501] detection_eval = 12.4516
-I0511 11:50:55.658155  5581 caffe.cpp:501] detection_eval = 0.0425151
-I0511 11:50:55.658160  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658164  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658169  5581 caffe.cpp:501] detection_eval = 2.34274
-I0511 11:50:55.658174  5581 caffe.cpp:501] detection_eval = 12.5444
-I0511 11:50:55.658179  5581 caffe.cpp:501] detection_eval = 0.0444467
-I0511 11:50:55.658182  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658186  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658191  5581 caffe.cpp:501] detection_eval = 2.34274
-I0511 11:50:55.658195  5581 caffe.cpp:501] detection_eval = 12.5927
-I0511 11:50:55.658200  5581 caffe.cpp:501] detection_eval = 0.0420531
-I0511 11:50:55.658205  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658210  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658213  5581 caffe.cpp:501] detection_eval = 2.34274
-I0511 11:50:55.658218  5581 caffe.cpp:501] detection_eval = 12.6976
-I0511 11:50:55.658222  5581 caffe.cpp:501] detection_eval = 0.0379126
-I0511 11:50:55.658227  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658231  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658236  5581 caffe.cpp:501] detection_eval = 2.34476
-I0511 11:50:55.658241  5581 caffe.cpp:501] detection_eval = 12.6855
-I0511 11:50:55.658246  5581 caffe.cpp:501] detection_eval = 0.0379459
-I0511 11:50:55.658249  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.658254  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658258  5581 caffe.cpp:501] detection_eval = 2.34476
-I0511 11:50:55.658263  5581 caffe.cpp:501] detection_eval = 12.7359
-I0511 11:50:55.658267  5581 caffe.cpp:501] detection_eval = 0.039052
-I0511 11:50:55.658272  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658277  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658282  5581 caffe.cpp:501] detection_eval = 2.34677
-I0511 11:50:55.658285  5581 caffe.cpp:501] detection_eval = 12.7359
-I0511 11:50:55.658290  5581 caffe.cpp:501] detection_eval = 0.0387269
-I0511 11:50:55.658294  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658299  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658303  5581 caffe.cpp:501] detection_eval = 2.35282
-I0511 11:50:55.658308  5581 caffe.cpp:501] detection_eval = 12.6976
-I0511 11:50:55.658313  5581 caffe.cpp:501] detection_eval = 0.0426419
-I0511 11:50:55.658318  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.658321  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.658325  5581 caffe.cpp:501] detection_eval = 2.35282
-I0511 11:50:55.658330  5581 caffe.cpp:501] detection_eval = 12.7601
-I0511 11:50:55.658335  5581 caffe.cpp:501] detection_eval = 0.0395139
-I0511 11:50:55.658339  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658344  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658349  5581 caffe.cpp:501] detection_eval = 2.35685
-I0511 11:50:55.658352  5581 caffe.cpp:501] detection_eval = 12.7742
-I0511 11:50:55.658357  5581 caffe.cpp:501] detection_eval = 0.0397158
-I0511 11:50:55.658365  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658370  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658373  5581 caffe.cpp:501] detection_eval = 2.36089
-I0511 11:50:55.658378  5581 caffe.cpp:501] detection_eval = 12.8044
-I0511 11:50:55.658383  5581 caffe.cpp:501] detection_eval = 0.04272
-I0511 11:50:55.658387  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658392  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658396  5581 caffe.cpp:501] detection_eval = 2.3629
-I0511 11:50:55.658401  5581 caffe.cpp:501] detection_eval = 12.8992
-I0511 11:50:55.658406  5581 caffe.cpp:501] detection_eval = 0.0471257
-I0511 11:50:55.658411  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.658414  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658419  5581 caffe.cpp:501] detection_eval = 2.36694
-I0511 11:50:55.658423  5581 caffe.cpp:501] detection_eval = 12.8952
-I0511 11:50:55.658428  5581 caffe.cpp:501] detection_eval = 0.0426985
-I0511 11:50:55.658432  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658437  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658442  5581 caffe.cpp:501] detection_eval = 2.37702
-I0511 11:50:55.658447  5581 caffe.cpp:501] detection_eval = 12.8185
-I0511 11:50:55.658450  5581 caffe.cpp:501] detection_eval = 0.0428066
-I0511 11:50:55.658455  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.658459  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.658463  5581 caffe.cpp:501] detection_eval = 2.38508
-I0511 11:50:55.658468  5581 caffe.cpp:501] detection_eval = 12.744
-I0511 11:50:55.658473  5581 caffe.cpp:501] detection_eval = 0.0429672
-I0511 11:50:55.658478  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658481  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658486  5581 caffe.cpp:501] detection_eval = 2.38508
-I0511 11:50:55.658490  5581 caffe.cpp:501] detection_eval = 12.7964
-I0511 11:50:55.658495  5581 caffe.cpp:501] detection_eval = 0.0365405
-I0511 11:50:55.658499  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.658504  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.658509  5581 caffe.cpp:501] detection_eval = 2.38911
-I0511 11:50:55.658514  5581 caffe.cpp:501] detection_eval = 12.7641
-I0511 11:50:55.658519  5581 caffe.cpp:501] detection_eval = 0.0361698
-I0511 11:50:55.658522  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.658527  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.658531  5581 caffe.cpp:501] detection_eval = 2.38911
-I0511 11:50:55.658536  5581 caffe.cpp:501] detection_eval = 12.8044
-I0511 11:50:55.658540  5581 caffe.cpp:501] detection_eval = 0.0351099
-I0511 11:50:55.658545  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.658550  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.658555  5581 caffe.cpp:501] detection_eval = 2.39113
-I0511 11:50:55.658558  5581 caffe.cpp:501] detection_eval = 12.8468
-I0511 11:50:55.658563  5581 caffe.cpp:501] detection_eval = 0.0407372
-I0511 11:50:55.658567  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658572  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658577  5581 caffe.cpp:501] detection_eval = 2.39315
-I0511 11:50:55.658581  5581 caffe.cpp:501] detection_eval = 12.881
-I0511 11:50:55.658587  5581 caffe.cpp:501] detection_eval = 0.038156
-I0511 11:50:55.658591  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658597  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658602  5581 caffe.cpp:501] detection_eval = 2.39315
-I0511 11:50:55.658607  5581 caffe.cpp:501] detection_eval = 12.9516
-I0511 11:50:55.658612  5581 caffe.cpp:501] detection_eval = 0.0393703
-I0511 11:50:55.658617  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658620  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658625  5581 caffe.cpp:501] detection_eval = 2.39516
-I0511 11:50:55.658629  5581 caffe.cpp:501] detection_eval = 12.9597
-I0511 11:50:55.658639  5581 caffe.cpp:501] detection_eval = 0.0410465
-I0511 11:50:55.658645  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.658649  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.658654  5581 caffe.cpp:501] detection_eval = 2.39718
-I0511 11:50:55.658658  5581 caffe.cpp:501] detection_eval = 12.9657
-I0511 11:50:55.658663  5581 caffe.cpp:501] detection_eval = 0.0372105
-I0511 11:50:55.658668  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658671  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658676  5581 caffe.cpp:501] detection_eval = 2.39718
-I0511 11:50:55.658680  5581 caffe.cpp:501] detection_eval = 13.0605
-I0511 11:50:55.658685  5581 caffe.cpp:501] detection_eval = 0.0395689
-I0511 11:50:55.658690  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658695  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658699  5581 caffe.cpp:501] detection_eval = 2.40121
-I0511 11:50:55.658704  5581 caffe.cpp:501] detection_eval = 13.0847
-I0511 11:50:55.658710  5581 caffe.cpp:501] detection_eval = 0.0402218
-I0511 11:50:55.658713  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658718  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.658722  5581 caffe.cpp:501] detection_eval = 2.40927
-I0511 11:50:55.658727  5581 caffe.cpp:501] detection_eval = 13.0565
-I0511 11:50:55.658732  5581 caffe.cpp:501] detection_eval = 0.0486767
-I0511 11:50:55.658736  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.658740  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.658746  5581 caffe.cpp:501] detection_eval = 2.41532
-I0511 11:50:55.658749  5581 caffe.cpp:501] detection_eval = 13.0403
-I0511 11:50:55.658754  5581 caffe.cpp:501] detection_eval = 0.0441381
-I0511 11:50:55.658758  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658763  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658767  5581 caffe.cpp:501] detection_eval = 2.41532
-I0511 11:50:55.658772  5581 caffe.cpp:501] detection_eval = 13.0685
-I0511 11:50:55.658777  5581 caffe.cpp:501] detection_eval = 0.0379605
-I0511 11:50:55.658782  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658787  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658790  5581 caffe.cpp:501] detection_eval = 2.41532
-I0511 11:50:55.658795  5581 caffe.cpp:501] detection_eval = 13.119
-I0511 11:50:55.658799  5581 caffe.cpp:501] detection_eval = 0.0366211
-I0511 11:50:55.658804  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658809  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658813  5581 caffe.cpp:501] detection_eval = 2.42137
-I0511 11:50:55.658818  5581 caffe.cpp:501] detection_eval = 13.1169
-I0511 11:50:55.658823  5581 caffe.cpp:501] detection_eval = 0.0412391
-I0511 11:50:55.658828  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658831  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.658836  5581 caffe.cpp:501] detection_eval = 2.42742
-I0511 11:50:55.658840  5581 caffe.cpp:501] detection_eval = 13.0766
-I0511 11:50:55.658845  5581 caffe.cpp:501] detection_eval = 0.0404661
-I0511 11:50:55.658849  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658854  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.658859  5581 caffe.cpp:501] detection_eval = 2.42944
-I0511 11:50:55.658862  5581 caffe.cpp:501] detection_eval = 13.0948
-I0511 11:50:55.658867  5581 caffe.cpp:501] detection_eval = 0.0379305
-I0511 11:50:55.658871  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658876  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.658880  5581 caffe.cpp:501] detection_eval = 2.43145
-I0511 11:50:55.658885  5581 caffe.cpp:501] detection_eval = 13.1069
-I0511 11:50:55.658890  5581 caffe.cpp:501] detection_eval = 0.033756
-I0511 11:50:55.658895  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.658898  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.658903  5581 caffe.cpp:501] detection_eval = 2.43145
-I0511 11:50:55.658911  5581 caffe.cpp:501] detection_eval = 13.2097
-I0511 11:50:55.658916  5581 caffe.cpp:501] detection_eval = 0.0418653
-I0511 11:50:55.658921  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.658926  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.658929  5581 caffe.cpp:501] detection_eval = 2.43347
-I0511 11:50:55.658934  5581 caffe.cpp:501] detection_eval = 13.2258
-I0511 11:50:55.658939  5581 caffe.cpp:501] detection_eval = 0.0382543
-I0511 11:50:55.658943  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658948  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.658952  5581 caffe.cpp:501] detection_eval = 2.43548
-I0511 11:50:55.658957  5581 caffe.cpp:501] detection_eval = 13.2601
-I0511 11:50:55.658962  5581 caffe.cpp:501] detection_eval = 0.0409673
-I0511 11:50:55.658967  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.658972  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.658977  5581 caffe.cpp:501] detection_eval = 2.43548
-I0511 11:50:55.658980  5581 caffe.cpp:501] detection_eval = 13.3125
-I0511 11:50:55.658985  5581 caffe.cpp:501] detection_eval = 0.0370747
-I0511 11:50:55.658989  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.658994  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.658998  5581 caffe.cpp:501] detection_eval = 2.4375
-I0511 11:50:55.659003  5581 caffe.cpp:501] detection_eval = 13.3468
-I0511 11:50:55.659008  5581 caffe.cpp:501] detection_eval = 0.0370443
-I0511 11:50:55.659011  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659016  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.659020  5581 caffe.cpp:501] detection_eval = 2.43952
-I0511 11:50:55.659025  5581 caffe.cpp:501] detection_eval = 13.3589
-I0511 11:50:55.659029  5581 caffe.cpp:501] detection_eval = 0.0330922
-I0511 11:50:55.659034  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.659039  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.659044  5581 caffe.cpp:501] detection_eval = 2.43952
-I0511 11:50:55.659047  5581 caffe.cpp:501] detection_eval = 13.3992
-I0511 11:50:55.659052  5581 caffe.cpp:501] detection_eval = 0.0354148
-I0511 11:50:55.659056  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659061  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659065  5581 caffe.cpp:501] detection_eval = 2.44153
-I0511 11:50:55.659070  5581 caffe.cpp:501] detection_eval = 13.4274
-I0511 11:50:55.659075  5581 caffe.cpp:501] detection_eval = 0.0369373
-I0511 11:50:55.659080  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659085  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.659088  5581 caffe.cpp:501] detection_eval = 2.44355
-I0511 11:50:55.659093  5581 caffe.cpp:501] detection_eval = 13.4315
-I0511 11:50:55.659097  5581 caffe.cpp:501] detection_eval = 0.0333409
-I0511 11:50:55.659102  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.659107  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.659111  5581 caffe.cpp:501] detection_eval = 2.44758
-I0511 11:50:55.659116  5581 caffe.cpp:501] detection_eval = 13.4355
-I0511 11:50:55.659121  5581 caffe.cpp:501] detection_eval = 0.0351842
-I0511 11:50:55.659126  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.659129  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.659134  5581 caffe.cpp:501] detection_eval = 2.4496
-I0511 11:50:55.659138  5581 caffe.cpp:501] detection_eval = 13.4597
-I0511 11:50:55.659143  5581 caffe.cpp:501] detection_eval = 0.033905
-I0511 11:50:55.659148  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659152  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659157  5581 caffe.cpp:501] detection_eval = 2.45161
-I0511 11:50:55.659162  5581 caffe.cpp:501] detection_eval = 13.5302
-I0511 11:50:55.659166  5581 caffe.cpp:501] detection_eval = 0.0374625
-I0511 11:50:55.659171  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659175  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.659180  5581 caffe.cpp:501] detection_eval = 2.45363
-I0511 11:50:55.659188  5581 caffe.cpp:501] detection_eval = 13.5645
-I0511 11:50:55.659193  5581 caffe.cpp:501] detection_eval = 0.0368777
-I0511 11:50:55.659198  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.659202  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.659207  5581 caffe.cpp:501] detection_eval = 2.45363
-I0511 11:50:55.659211  5581 caffe.cpp:501] detection_eval = 13.629
-I0511 11:50:55.659217  5581 caffe.cpp:501] detection_eval = 0.0410905
-I0511 11:50:55.659221  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659226  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.659230  5581 caffe.cpp:501] detection_eval = 2.45968
-I0511 11:50:55.659235  5581 caffe.cpp:501] detection_eval = 13.6411
-I0511 11:50:55.659240  5581 caffe.cpp:501] detection_eval = 0.0418434
-I0511 11:50:55.659245  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.659248  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.659253  5581 caffe.cpp:501] detection_eval = 2.46573
-I0511 11:50:55.659257  5581 caffe.cpp:501] detection_eval = 13.6532
-I0511 11:50:55.659262  5581 caffe.cpp:501] detection_eval = 0.0353083
-I0511 11:50:55.659266  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659271  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.659276  5581 caffe.cpp:501] detection_eval = 2.46976
-I0511 11:50:55.659281  5581 caffe.cpp:501] detection_eval = 13.7077
-I0511 11:50:55.659284  5581 caffe.cpp:501] detection_eval = 0.0469151
-I0511 11:50:55.659288  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.659293  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.659298  5581 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:50:55.659302  5581 caffe.cpp:501] detection_eval = 13.7742
-I0511 11:50:55.659307  5581 caffe.cpp:501] detection_eval = 0.0435944
-I0511 11:50:55.659312  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659317  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.659320  5581 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:50:55.659324  5581 caffe.cpp:501] detection_eval = 13.881
-I0511 11:50:55.659329  5581 caffe.cpp:501] detection_eval = 0.0363762
-I0511 11:50:55.659334  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.659338  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659343  5581 caffe.cpp:501] detection_eval = 2.47177
-I0511 11:50:55.659348  5581 caffe.cpp:501] detection_eval = 13.9738
-I0511 11:50:55.659353  5581 caffe.cpp:501] detection_eval = 0.0417812
-I0511 11:50:55.659356  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659361  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659365  5581 caffe.cpp:501] detection_eval = 2.47581
-I0511 11:50:55.659370  5581 caffe.cpp:501] detection_eval = 14.0081
-I0511 11:50:55.659375  5581 caffe.cpp:501] detection_eval = 0.0403118
-I0511 11:50:55.659379  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659384  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.659389  5581 caffe.cpp:501] detection_eval = 2.47581
-I0511 11:50:55.659394  5581 caffe.cpp:501] detection_eval = 14.1331
-I0511 11:50:55.659397  5581 caffe.cpp:501] detection_eval = 0.0433493
-I0511 11:50:55.659402  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.659406  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.659411  5581 caffe.cpp:501] detection_eval = 2.47782
-I0511 11:50:55.659415  5581 caffe.cpp:501] detection_eval = 14.3024
-I0511 11:50:55.659420  5581 caffe.cpp:501] detection_eval = 0.0381602
-I0511 11:50:55.659425  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.659430  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.659435  5581 caffe.cpp:501] detection_eval = 2.47984
-I0511 11:50:55.659438  5581 caffe.cpp:501] detection_eval = 14.4335
-I0511 11:50:55.659443  5581 caffe.cpp:501] detection_eval = 0.0360524
-I0511 11:50:55.659448  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.659453  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.659461  5581 caffe.cpp:501] detection_eval = 2.48387
-I0511 11:50:55.659466  5581 caffe.cpp:501] detection_eval = 14.6069
-I0511 11:50:55.659471  5581 caffe.cpp:501] detection_eval = 0.040243
-I0511 11:50:55.659474  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.659479  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659483  5581 caffe.cpp:501] detection_eval = 2.48589
-I0511 11:50:55.659488  5581 caffe.cpp:501] detection_eval = 14.9657
-I0511 11:50:55.659492  5581 caffe.cpp:501] detection_eval = 0.0352473
-I0511 11:50:55.659497  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.659502  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659507  5581 caffe.cpp:501] detection_eval = 3.07056
-I0511 11:50:55.659510  5581 caffe.cpp:501] detection_eval = 6.3004
-I0511 11:50:55.659515  5581 caffe.cpp:501] detection_eval = 0.123152
-I0511 11:50:55.659519  5581 caffe.cpp:501] detection_eval = 0.0907258
-I0511 11:50:55.659524  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.659528  5581 caffe.cpp:501] detection_eval = 3.07258
-I0511 11:50:55.659533  5581 caffe.cpp:501] detection_eval = 6.53024
-I0511 11:50:55.659538  5581 caffe.cpp:501] detection_eval = 0.0802531
-I0511 11:50:55.659543  5581 caffe.cpp:501] detection_eval = 0.0524194
-I0511 11:50:55.659546  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.659550  5581 caffe.cpp:501] detection_eval = 3.07258
-I0511 11:50:55.659555  5581 caffe.cpp:501] detection_eval = 6.67944
-I0511 11:50:55.659559  5581 caffe.cpp:501] detection_eval = 0.0610168
-I0511 11:50:55.659564  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.659569  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.659574  5581 caffe.cpp:501] detection_eval = 3.07661
-I0511 11:50:55.659577  5581 caffe.cpp:501] detection_eval = 6.79032
-I0511 11:50:55.659581  5581 caffe.cpp:501] detection_eval = 0.0696688
-I0511 11:50:55.659586  5581 caffe.cpp:501] detection_eval = 0.0302419
-I0511 11:50:55.659590  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.659595  5581 caffe.cpp:501] detection_eval = 3.08065
-I0511 11:50:55.659600  5581 caffe.cpp:501] detection_eval = 6.82661
-I0511 11:50:55.659605  5581 caffe.cpp:501] detection_eval = 0.0640188
-I0511 11:50:55.659608  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.659612  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.659617  5581 caffe.cpp:501] detection_eval = 3.08065
-I0511 11:50:55.659621  5581 caffe.cpp:501] detection_eval = 6.93145
-I0511 11:50:55.659626  5581 caffe.cpp:501] detection_eval = 0.054402
-I0511 11:50:55.659631  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.659636  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.659639  5581 caffe.cpp:501] detection_eval = 3.08266
-I0511 11:50:55.659644  5581 caffe.cpp:501] detection_eval = 6.98992
-I0511 11:50:55.659648  5581 caffe.cpp:501] detection_eval = 0.0485258
-I0511 11:50:55.659652  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.659657  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.659662  5581 caffe.cpp:501] detection_eval = 3.08468
-I0511 11:50:55.659667  5581 caffe.cpp:501] detection_eval = 7.09274
-I0511 11:50:55.659670  5581 caffe.cpp:501] detection_eval = 0.047552
-I0511 11:50:55.659675  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.659679  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.659684  5581 caffe.cpp:501] detection_eval = 3.08468
-I0511 11:50:55.659688  5581 caffe.cpp:501] detection_eval = 7.18952
-I0511 11:50:55.659693  5581 caffe.cpp:501] detection_eval = 0.0483895
-I0511 11:50:55.659698  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.659701  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.659706  5581 caffe.cpp:501] detection_eval = 3.09274
-I0511 11:50:55.659710  5581 caffe.cpp:501] detection_eval = 7.16935
-I0511 11:50:55.659715  5581 caffe.cpp:501] detection_eval = 0.0472736
-I0511 11:50:55.659719  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.659727  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.659732  5581 caffe.cpp:501] detection_eval = 3.09476
-I0511 11:50:55.659736  5581 caffe.cpp:501] detection_eval = 7.1875
-I0511 11:50:55.659741  5581 caffe.cpp:501] detection_eval = 0.0440118
-I0511 11:50:55.659745  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.659750  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659754  5581 caffe.cpp:501] detection_eval = 3.09476
-I0511 11:50:55.659759  5581 caffe.cpp:501] detection_eval = 7.2379
-I0511 11:50:55.659763  5581 caffe.cpp:501] detection_eval = 0.0420377
-I0511 11:50:55.659768  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659772  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659777  5581 caffe.cpp:501] detection_eval = 3.09879
-I0511 11:50:55.659781  5581 caffe.cpp:501] detection_eval = 7.26411
-I0511 11:50:55.659785  5581 caffe.cpp:501] detection_eval = 0.0442456
-I0511 11:50:55.659790  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659795  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659799  5581 caffe.cpp:501] detection_eval = 3.10081
-I0511 11:50:55.659803  5581 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:50:55.659808  5581 caffe.cpp:501] detection_eval = 0.0434348
-I0511 11:50:55.659812  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.659817  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.659821  5581 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:50:55.659826  5581 caffe.cpp:501] detection_eval = 7.32258
-I0511 11:50:55.659831  5581 caffe.cpp:501] detection_eval = 0.0425304
-I0511 11:50:55.659835  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659839  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659844  5581 caffe.cpp:501] detection_eval = 3.10282
-I0511 11:50:55.659848  5581 caffe.cpp:501] detection_eval = 7.42944
-I0511 11:50:55.659853  5581 caffe.cpp:501] detection_eval = 0.0481387
-I0511 11:50:55.659857  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.659862  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.659867  5581 caffe.cpp:501] detection_eval = 3.10887
-I0511 11:50:55.659871  5581 caffe.cpp:501] detection_eval = 7.39718
-I0511 11:50:55.659875  5581 caffe.cpp:501] detection_eval = 0.0475778
-I0511 11:50:55.659880  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.659884  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.659889  5581 caffe.cpp:501] detection_eval = 3.11089
-I0511 11:50:55.659893  5581 caffe.cpp:501] detection_eval = 7.44153
-I0511 11:50:55.659898  5581 caffe.cpp:501] detection_eval = 0.0461505
-I0511 11:50:55.659903  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.659906  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.659911  5581 caffe.cpp:501] detection_eval = 3.1129
-I0511 11:50:55.659915  5581 caffe.cpp:501] detection_eval = 7.50605
-I0511 11:50:55.659919  5581 caffe.cpp:501] detection_eval = 0.0481217
-I0511 11:50:55.659924  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.659929  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.659934  5581 caffe.cpp:501] detection_eval = 3.11492
-I0511 11:50:55.659937  5581 caffe.cpp:501] detection_eval = 7.56855
-I0511 11:50:55.659942  5581 caffe.cpp:501] detection_eval = 0.0483339
-I0511 11:50:55.659946  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.659951  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.659956  5581 caffe.cpp:501] detection_eval = 3.11694
-I0511 11:50:55.659960  5581 caffe.cpp:501] detection_eval = 7.63105
-I0511 11:50:55.659965  5581 caffe.cpp:501] detection_eval = 0.0495814
-I0511 11:50:55.659970  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.659973  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.659978  5581 caffe.cpp:501] detection_eval = 3.11694
-I0511 11:50:55.659982  5581 caffe.cpp:501] detection_eval = 7.70565
-I0511 11:50:55.659986  5581 caffe.cpp:501] detection_eval = 0.0476704
-I0511 11:50:55.659991  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.659998  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.660003  5581 caffe.cpp:501] detection_eval = 3.11895
-I0511 11:50:55.660008  5581 caffe.cpp:501] detection_eval = 7.73185
-I0511 11:50:55.660012  5581 caffe.cpp:501] detection_eval = 0.0407552
-I0511 11:50:55.660017  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.660022  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.660027  5581 caffe.cpp:501] detection_eval = 3.12298
-I0511 11:50:55.660030  5581 caffe.cpp:501] detection_eval = 7.76815
-I0511 11:50:55.660035  5581 caffe.cpp:501] detection_eval = 0.0423516
-I0511 11:50:55.660039  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660044  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660048  5581 caffe.cpp:501] detection_eval = 3.12702
-I0511 11:50:55.660053  5581 caffe.cpp:501] detection_eval = 7.78024
-I0511 11:50:55.660058  5581 caffe.cpp:501] detection_eval = 0.0395827
-I0511 11:50:55.660061  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.660066  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.660070  5581 caffe.cpp:501] detection_eval = 3.12903
-I0511 11:50:55.660075  5581 caffe.cpp:501] detection_eval = 7.82056
-I0511 11:50:55.660079  5581 caffe.cpp:501] detection_eval = 0.0398919
-I0511 11:50:55.660084  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660089  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660092  5581 caffe.cpp:501] detection_eval = 3.13105
-I0511 11:50:55.660097  5581 caffe.cpp:501] detection_eval = 7.86895
-I0511 11:50:55.660101  5581 caffe.cpp:501] detection_eval = 0.0429695
-I0511 11:50:55.660106  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660110  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660115  5581 caffe.cpp:501] detection_eval = 3.13105
-I0511 11:50:55.660120  5581 caffe.cpp:501] detection_eval = 7.9375
-I0511 11:50:55.660125  5581 caffe.cpp:501] detection_eval = 0.039879
-I0511 11:50:55.660128  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660133  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660137  5581 caffe.cpp:501] detection_eval = 3.1371
-I0511 11:50:55.660142  5581 caffe.cpp:501] detection_eval = 7.92339
-I0511 11:50:55.660146  5581 caffe.cpp:501] detection_eval = 0.0446489
-I0511 11:50:55.660151  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660156  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660161  5581 caffe.cpp:501] detection_eval = 3.13911
-I0511 11:50:55.660164  5581 caffe.cpp:501] detection_eval = 7.98387
-I0511 11:50:55.660169  5581 caffe.cpp:501] detection_eval = 0.0406522
-I0511 11:50:55.660173  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660178  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660182  5581 caffe.cpp:501] detection_eval = 3.14113
-I0511 11:50:55.660187  5581 caffe.cpp:501] detection_eval = 8.0504
-I0511 11:50:55.660192  5581 caffe.cpp:501] detection_eval = 0.0431023
-I0511 11:50:55.660195  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.660200  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660204  5581 caffe.cpp:501] detection_eval = 3.14315
-I0511 11:50:55.660209  5581 caffe.cpp:501] detection_eval = 8.11089
-I0511 11:50:55.660213  5581 caffe.cpp:501] detection_eval = 0.0458252
-I0511 11:50:55.660218  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660223  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.660226  5581 caffe.cpp:501] detection_eval = 3.14718
-I0511 11:50:55.660231  5581 caffe.cpp:501] detection_eval = 8.14516
-I0511 11:50:55.660235  5581 caffe.cpp:501] detection_eval = 0.0506663
-I0511 11:50:55.660240  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660244  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.660249  5581 caffe.cpp:501] detection_eval = 3.14919
-I0511 11:50:55.660254  5581 caffe.cpp:501] detection_eval = 8.16129
-I0511 11:50:55.660259  5581 caffe.cpp:501] detection_eval = 0.0450997
-I0511 11:50:55.660266  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.660270  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.660275  5581 caffe.cpp:501] detection_eval = 3.14919
-I0511 11:50:55.660279  5581 caffe.cpp:501] detection_eval = 8.24395
-I0511 11:50:55.660284  5581 caffe.cpp:501] detection_eval = 0.0406565
-I0511 11:50:55.660289  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660293  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660297  5581 caffe.cpp:501] detection_eval = 3.15121
-I0511 11:50:55.660302  5581 caffe.cpp:501] detection_eval = 8.27016
-I0511 11:50:55.660306  5581 caffe.cpp:501] detection_eval = 0.0396103
-I0511 11:50:55.660310  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660315  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660320  5581 caffe.cpp:501] detection_eval = 3.15323
-I0511 11:50:55.660324  5581 caffe.cpp:501] detection_eval = 8.27016
-I0511 11:50:55.660328  5581 caffe.cpp:501] detection_eval = 0.0415813
-I0511 11:50:55.660333  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660337  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660342  5581 caffe.cpp:501] detection_eval = 3.15323
-I0511 11:50:55.660346  5581 caffe.cpp:501] detection_eval = 8.34879
-I0511 11:50:55.660351  5581 caffe.cpp:501] detection_eval = 0.040227
-I0511 11:50:55.660356  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660359  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660363  5581 caffe.cpp:501] detection_eval = 3.15524
-I0511 11:50:55.660368  5581 caffe.cpp:501] detection_eval = 8.40524
-I0511 11:50:55.660372  5581 caffe.cpp:501] detection_eval = 0.043475
-I0511 11:50:55.660377  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.660382  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.660387  5581 caffe.cpp:501] detection_eval = 3.15927
-I0511 11:50:55.660392  5581 caffe.cpp:501] detection_eval = 8.41331
-I0511 11:50:55.660395  5581 caffe.cpp:501] detection_eval = 0.0437719
-I0511 11:50:55.660400  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660404  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.660409  5581 caffe.cpp:501] detection_eval = 3.15927
-I0511 11:50:55.660413  5581 caffe.cpp:501] detection_eval = 8.46169
-I0511 11:50:55.660418  5581 caffe.cpp:501] detection_eval = 0.0393098
-I0511 11:50:55.660423  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660426  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660431  5581 caffe.cpp:501] detection_eval = 3.15927
-I0511 11:50:55.660435  5581 caffe.cpp:501] detection_eval = 8.54637
-I0511 11:50:55.660440  5581 caffe.cpp:501] detection_eval = 0.0413076
-I0511 11:50:55.660444  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.660449  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.660454  5581 caffe.cpp:501] detection_eval = 3.16532
-I0511 11:50:55.660459  5581 caffe.cpp:501] detection_eval = 8.56048
-I0511 11:50:55.660462  5581 caffe.cpp:501] detection_eval = 0.0432862
-I0511 11:50:55.660466  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.660471  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.660475  5581 caffe.cpp:501] detection_eval = 3.16935
-I0511 11:50:55.660480  5581 caffe.cpp:501] detection_eval = 8.56452
-I0511 11:50:55.660485  5581 caffe.cpp:501] detection_eval = 0.0434875
-I0511 11:50:55.660490  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660493  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660498  5581 caffe.cpp:501] detection_eval = 3.17137
-I0511 11:50:55.660502  5581 caffe.cpp:501] detection_eval = 8.63911
-I0511 11:50:55.660507  5581 caffe.cpp:501] detection_eval = 0.0415305
-I0511 11:50:55.660511  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660516  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.660521  5581 caffe.cpp:501] detection_eval = 3.17339
-I0511 11:50:55.660544  5581 caffe.cpp:501] detection_eval = 8.65927
-I0511 11:50:55.660548  5581 caffe.cpp:501] detection_eval = 0.0445828
-I0511 11:50:55.660558  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660563  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660567  5581 caffe.cpp:501] detection_eval = 3.17339
-I0511 11:50:55.660573  5581 caffe.cpp:501] detection_eval = 8.76008
-I0511 11:50:55.660576  5581 caffe.cpp:501] detection_eval = 0.0437319
-I0511 11:50:55.660581  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.660585  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660590  5581 caffe.cpp:501] detection_eval = 3.17742
-I0511 11:50:55.660594  5581 caffe.cpp:501] detection_eval = 8.8125
-I0511 11:50:55.660599  5581 caffe.cpp:501] detection_eval = 0.0456554
-I0511 11:50:55.660604  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.660609  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.660612  5581 caffe.cpp:501] detection_eval = 3.18347
-I0511 11:50:55.660616  5581 caffe.cpp:501] detection_eval = 8.79435
-I0511 11:50:55.660620  5581 caffe.cpp:501] detection_eval = 0.0465603
-I0511 11:50:55.660625  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660629  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.660634  5581 caffe.cpp:501] detection_eval = 3.1875
-I0511 11:50:55.660639  5581 caffe.cpp:501] detection_eval = 8.86089
-I0511 11:50:55.660643  5581 caffe.cpp:501] detection_eval = 0.0500802
-I0511 11:50:55.660647  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.660652  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.660656  5581 caffe.cpp:501] detection_eval = 3.18952
-I0511 11:50:55.660660  5581 caffe.cpp:501] detection_eval = 8.86694
-I0511 11:50:55.660665  5581 caffe.cpp:501] detection_eval = 0.0397763
-I0511 11:50:55.660668  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.660673  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660677  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660682  5581 caffe.cpp:501] detection_eval = 8.93145
-I0511 11:50:55.660687  5581 caffe.cpp:501] detection_eval = 0.0455478
-I0511 11:50:55.660691  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.660696  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660701  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660706  5581 caffe.cpp:501] detection_eval = 9.02823
-I0511 11:50:55.660709  5581 caffe.cpp:501] detection_eval = 0.0453798
-I0511 11:50:55.660714  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660718  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.660723  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660727  5581 caffe.cpp:501] detection_eval = 9.10685
-I0511 11:50:55.660732  5581 caffe.cpp:501] detection_eval = 0.0421948
-I0511 11:50:55.660737  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.660742  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.660745  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660749  5581 caffe.cpp:501] detection_eval = 9.17137
-I0511 11:50:55.660754  5581 caffe.cpp:501] detection_eval = 0.0399903
-I0511 11:50:55.660759  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660763  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660768  5581 caffe.cpp:501] detection_eval = 3.19153
-I0511 11:50:55.660773  5581 caffe.cpp:501] detection_eval = 9.23992
-I0511 11:50:55.660778  5581 caffe.cpp:501] detection_eval = 0.0410463
-I0511 11:50:55.660781  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660786  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660790  5581 caffe.cpp:501] detection_eval = 3.19556
-I0511 11:50:55.660794  5581 caffe.cpp:501] detection_eval = 9.28629
-I0511 11:50:55.660799  5581 caffe.cpp:501] detection_eval = 0.0421853
-I0511 11:50:55.660804  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660809  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660814  5581 caffe.cpp:501] detection_eval = 3.1996
-I0511 11:50:55.660817  5581 caffe.cpp:501] detection_eval = 9.33468
-I0511 11:50:55.660826  5581 caffe.cpp:501] detection_eval = 0.0469477
-I0511 11:50:55.660831  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.660836  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.660840  5581 caffe.cpp:501] detection_eval = 3.20161
-I0511 11:50:55.660845  5581 caffe.cpp:501] detection_eval = 9.39113
-I0511 11:50:55.660851  5581 caffe.cpp:501] detection_eval = 0.0419991
-I0511 11:50:55.660854  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.660859  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.660863  5581 caffe.cpp:501] detection_eval = 3.20565
-I0511 11:50:55.660868  5581 caffe.cpp:501] detection_eval = 9.41129
-I0511 11:50:55.660872  5581 caffe.cpp:501] detection_eval = 0.0423253
-I0511 11:50:55.660877  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660881  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660887  5581 caffe.cpp:501] detection_eval = 3.20766
-I0511 11:50:55.660892  5581 caffe.cpp:501] detection_eval = 9.46371
-I0511 11:50:55.660895  5581 caffe.cpp:501] detection_eval = 0.0410735
-I0511 11:50:55.660900  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.660904  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.660909  5581 caffe.cpp:501] detection_eval = 3.21169
-I0511 11:50:55.660913  5581 caffe.cpp:501] detection_eval = 9.51411
-I0511 11:50:55.660918  5581 caffe.cpp:501] detection_eval = 0.0425367
-I0511 11:50:55.660923  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.660926  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.660931  5581 caffe.cpp:501] detection_eval = 3.21371
-I0511 11:50:55.660935  5581 caffe.cpp:501] detection_eval = 9.58266
-I0511 11:50:55.660940  5581 caffe.cpp:501] detection_eval = 0.0459977
-I0511 11:50:55.660945  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.660949  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.660953  5581 caffe.cpp:501] detection_eval = 3.21774
-I0511 11:50:55.660959  5581 caffe.cpp:501] detection_eval = 9.63508
-I0511 11:50:55.660962  5581 caffe.cpp:501] detection_eval = 0.039977
-I0511 11:50:55.660967  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.660972  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.660976  5581 caffe.cpp:501] detection_eval = 3.21774
-I0511 11:50:55.660981  5581 caffe.cpp:501] detection_eval = 9.71573
-I0511 11:50:55.660985  5581 caffe.cpp:501] detection_eval = 0.0402232
-I0511 11:50:55.660990  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.660995  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.661000  5581 caffe.cpp:501] detection_eval = 3.21976
-I0511 11:50:55.661005  5581 caffe.cpp:501] detection_eval = 9.75
-I0511 11:50:55.661008  5581 caffe.cpp:501] detection_eval = 0.0414932
-I0511 11:50:55.661013  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.661017  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661022  5581 caffe.cpp:501] detection_eval = 3.21976
-I0511 11:50:55.661026  5581 caffe.cpp:501] detection_eval = 9.82056
-I0511 11:50:55.661031  5581 caffe.cpp:501] detection_eval = 0.0441414
-I0511 11:50:55.661036  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661041  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661044  5581 caffe.cpp:501] detection_eval = 3.21976
-I0511 11:50:55.661049  5581 caffe.cpp:501] detection_eval = 9.90524
-I0511 11:50:55.661053  5581 caffe.cpp:501] detection_eval = 0.0406413
-I0511 11:50:55.661058  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661062  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661067  5581 caffe.cpp:501] detection_eval = 3.22177
-I0511 11:50:55.661072  5581 caffe.cpp:501] detection_eval = 9.97782
-I0511 11:50:55.661077  5581 caffe.cpp:501] detection_eval = 0.0446964
-I0511 11:50:55.661080  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661085  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661089  5581 caffe.cpp:501] detection_eval = 3.22984
-I0511 11:50:55.661098  5581 caffe.cpp:501] detection_eval = 9.95766
-I0511 11:50:55.661103  5581 caffe.cpp:501] detection_eval = 0.0467316
-I0511 11:50:55.661108  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661113  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.661118  5581 caffe.cpp:501] detection_eval = 3.23185
-I0511 11:50:55.661121  5581 caffe.cpp:501] detection_eval = 9.97581
-I0511 11:50:55.661125  5581 caffe.cpp:501] detection_eval = 0.0449375
-I0511 11:50:55.661130  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661134  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661139  5581 caffe.cpp:501] detection_eval = 3.23387
-I0511 11:50:55.661144  5581 caffe.cpp:501] detection_eval = 10.0202
-I0511 11:50:55.661149  5581 caffe.cpp:501] detection_eval = 0.0404493
-I0511 11:50:55.661154  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661157  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661162  5581 caffe.cpp:501] detection_eval = 3.23992
-I0511 11:50:55.661166  5581 caffe.cpp:501] detection_eval = 10.006
-I0511 11:50:55.661171  5581 caffe.cpp:501] detection_eval = 0.0474648
-I0511 11:50:55.661175  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661180  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.661185  5581 caffe.cpp:501] detection_eval = 3.23992
-I0511 11:50:55.661190  5581 caffe.cpp:501] detection_eval = 10.0766
-I0511 11:50:55.661193  5581 caffe.cpp:501] detection_eval = 0.0429031
-I0511 11:50:55.661198  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661202  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661207  5581 caffe.cpp:501] detection_eval = 3.24395
-I0511 11:50:55.661212  5581 caffe.cpp:501] detection_eval = 10.0746
-I0511 11:50:55.661216  5581 caffe.cpp:501] detection_eval = 0.0419923
-I0511 11:50:55.661221  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661226  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661231  5581 caffe.cpp:501] detection_eval = 3.24597
-I0511 11:50:55.661236  5581 caffe.cpp:501] detection_eval = 10.0948
-I0511 11:50:55.661239  5581 caffe.cpp:501] detection_eval = 0.0425072
-I0511 11:50:55.661244  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661248  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.661253  5581 caffe.cpp:501] detection_eval = 3.25
-I0511 11:50:55.661257  5581 caffe.cpp:501] detection_eval = 10.1532
-I0511 11:50:55.661262  5581 caffe.cpp:501] detection_eval = 0.044023
-I0511 11:50:55.661267  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.661272  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.661276  5581 caffe.cpp:501] detection_eval = 3.25202
-I0511 11:50:55.661280  5581 caffe.cpp:501] detection_eval = 10.2258
-I0511 11:50:55.661285  5581 caffe.cpp:501] detection_eval = 0.0487238
-I0511 11:50:55.661290  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661294  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661299  5581 caffe.cpp:501] detection_eval = 3.25403
-I0511 11:50:55.661303  5581 caffe.cpp:501] detection_eval = 10.2661
-I0511 11:50:55.661309  5581 caffe.cpp:501] detection_eval = 0.0422363
-I0511 11:50:55.661312  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661317  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661321  5581 caffe.cpp:501] detection_eval = 3.25605
-I0511 11:50:55.661326  5581 caffe.cpp:501] detection_eval = 10.2984
-I0511 11:50:55.661330  5581 caffe.cpp:501] detection_eval = 0.0439842
-I0511 11:50:55.661335  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661339  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661345  5581 caffe.cpp:501] detection_eval = 3.25605
-I0511 11:50:55.661348  5581 caffe.cpp:501] detection_eval = 10.3488
-I0511 11:50:55.661353  5581 caffe.cpp:501] detection_eval = 0.0402993
-I0511 11:50:55.661357  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.661362  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661366  5581 caffe.cpp:501] detection_eval = 3.26008
-I0511 11:50:55.661375  5581 caffe.cpp:501] detection_eval = 10.373
-I0511 11:50:55.661379  5581 caffe.cpp:501] detection_eval = 0.0436663
-I0511 11:50:55.661383  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661388  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661392  5581 caffe.cpp:501] detection_eval = 3.26411
-I0511 11:50:55.661397  5581 caffe.cpp:501] detection_eval = 10.3609
-I0511 11:50:55.661401  5581 caffe.cpp:501] detection_eval = 0.0465564
-I0511 11:50:55.661406  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661411  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661415  5581 caffe.cpp:501] detection_eval = 3.26815
-I0511 11:50:55.661420  5581 caffe.cpp:501] detection_eval = 10.3851
-I0511 11:50:55.661424  5581 caffe.cpp:501] detection_eval = 0.0454225
-I0511 11:50:55.661429  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661433  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661438  5581 caffe.cpp:501] detection_eval = 3.27419
-I0511 11:50:55.661442  5581 caffe.cpp:501] detection_eval = 10.3629
-I0511 11:50:55.661448  5581 caffe.cpp:501] detection_eval = 0.040721
-I0511 11:50:55.661451  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.661456  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661461  5581 caffe.cpp:501] detection_eval = 3.27419
-I0511 11:50:55.661465  5581 caffe.cpp:501] detection_eval = 10.4355
-I0511 11:50:55.661469  5581 caffe.cpp:501] detection_eval = 0.0432446
-I0511 11:50:55.661474  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661478  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661484  5581 caffe.cpp:501] detection_eval = 3.28226
-I0511 11:50:55.661487  5581 caffe.cpp:501] detection_eval = 10.3629
-I0511 11:50:55.661492  5581 caffe.cpp:501] detection_eval = 0.0393292
-I0511 11:50:55.661496  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661501  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.661505  5581 caffe.cpp:501] detection_eval = 3.28427
-I0511 11:50:55.661509  5581 caffe.cpp:501] detection_eval = 10.4274
-I0511 11:50:55.661514  5581 caffe.cpp:501] detection_eval = 0.0394937
-I0511 11:50:55.661518  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.661523  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661527  5581 caffe.cpp:501] detection_eval = 3.28629
-I0511 11:50:55.661532  5581 caffe.cpp:501] detection_eval = 10.4577
-I0511 11:50:55.661536  5581 caffe.cpp:501] detection_eval = 0.0450987
-I0511 11:50:55.661541  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661545  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661550  5581 caffe.cpp:501] detection_eval = 3.28629
-I0511 11:50:55.661554  5581 caffe.cpp:501] detection_eval = 10.5423
-I0511 11:50:55.661559  5581 caffe.cpp:501] detection_eval = 0.0466144
-I0511 11:50:55.661563  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.661568  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.661573  5581 caffe.cpp:501] detection_eval = 3.28831
-I0511 11:50:55.661577  5581 caffe.cpp:501] detection_eval = 10.5968
-I0511 11:50:55.661582  5581 caffe.cpp:501] detection_eval = 0.0461445
-I0511 11:50:55.661587  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.661592  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.661595  5581 caffe.cpp:501] detection_eval = 3.29234
-I0511 11:50:55.661600  5581 caffe.cpp:501] detection_eval = 10.6069
-I0511 11:50:55.661604  5581 caffe.cpp:501] detection_eval = 0.0418586
-I0511 11:50:55.661609  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.661613  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661618  5581 caffe.cpp:501] detection_eval = 3.29435
-I0511 11:50:55.661623  5581 caffe.cpp:501] detection_eval = 10.6452
-I0511 11:50:55.661628  5581 caffe.cpp:501] detection_eval = 0.0422106
-I0511 11:50:55.661631  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.661636  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.661643  5581 caffe.cpp:501] detection_eval = 3.29839
-I0511 11:50:55.661648  5581 caffe.cpp:501] detection_eval = 10.621
-I0511 11:50:55.661653  5581 caffe.cpp:501] detection_eval = 0.0417796
-I0511 11:50:55.661658  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661662  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661666  5581 caffe.cpp:501] detection_eval = 3.30242
-I0511 11:50:55.661671  5581 caffe.cpp:501] detection_eval = 10.6391
-I0511 11:50:55.661675  5581 caffe.cpp:501] detection_eval = 0.0372237
-I0511 11:50:55.661680  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.661685  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661689  5581 caffe.cpp:501] detection_eval = 3.30444
-I0511 11:50:55.661695  5581 caffe.cpp:501] detection_eval = 10.7016
-I0511 11:50:55.661698  5581 caffe.cpp:501] detection_eval = 0.0478853
-I0511 11:50:55.661703  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.661707  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.661712  5581 caffe.cpp:501] detection_eval = 3.30645
-I0511 11:50:55.661716  5581 caffe.cpp:501] detection_eval = 10.744
-I0511 11:50:55.661721  5581 caffe.cpp:501] detection_eval = 0.0507787
-I0511 11:50:55.661725  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.661731  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.661734  5581 caffe.cpp:501] detection_eval = 3.31452
-I0511 11:50:55.661739  5581 caffe.cpp:501] detection_eval = 10.6875
-I0511 11:50:55.661743  5581 caffe.cpp:501] detection_eval = 0.0448198
-I0511 11:50:55.661748  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661752  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.661756  5581 caffe.cpp:501] detection_eval = 3.31653
-I0511 11:50:55.661761  5581 caffe.cpp:501] detection_eval = 10.7762
-I0511 11:50:55.661767  5581 caffe.cpp:501] detection_eval = 0.0447045
-I0511 11:50:55.661770  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661775  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661779  5581 caffe.cpp:501] detection_eval = 3.3246
-I0511 11:50:55.661784  5581 caffe.cpp:501] detection_eval = 10.7218
-I0511 11:50:55.661788  5581 caffe.cpp:501] detection_eval = 0.0442786
-I0511 11:50:55.661793  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.661798  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661803  5581 caffe.cpp:501] detection_eval = 3.33266
-I0511 11:50:55.661806  5581 caffe.cpp:501] detection_eval = 10.6835
-I0511 11:50:55.661811  5581 caffe.cpp:501] detection_eval = 0.0508508
-I0511 11:50:55.661815  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.661820  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.661824  5581 caffe.cpp:501] detection_eval = 3.33669
-I0511 11:50:55.661828  5581 caffe.cpp:501] detection_eval = 10.7278
-I0511 11:50:55.661834  5581 caffe.cpp:501] detection_eval = 0.0502371
-I0511 11:50:55.661839  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.661842  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.661847  5581 caffe.cpp:501] detection_eval = 3.34073
-I0511 11:50:55.661851  5581 caffe.cpp:501] detection_eval = 10.7298
-I0511 11:50:55.661856  5581 caffe.cpp:501] detection_eval = 0.0473864
-I0511 11:50:55.661860  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661865  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661870  5581 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:50:55.661875  5581 caffe.cpp:501] detection_eval = 10.7419
-I0511 11:50:55.661878  5581 caffe.cpp:501] detection_eval = 0.0492456
-I0511 11:50:55.661883  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.661887  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.661892  5581 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:50:55.661896  5581 caffe.cpp:501] detection_eval = 10.7782
-I0511 11:50:55.661901  5581 caffe.cpp:501] detection_eval = 0.0470619
-I0511 11:50:55.661906  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.661912  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.661917  5581 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:50:55.661922  5581 caffe.cpp:501] detection_eval = 10.8327
-I0511 11:50:55.661927  5581 caffe.cpp:501] detection_eval = 0.0473917
-I0511 11:50:55.661931  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.661936  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.661940  5581 caffe.cpp:501] detection_eval = 3.34476
-I0511 11:50:55.661944  5581 caffe.cpp:501] detection_eval = 10.881
-I0511 11:50:55.661949  5581 caffe.cpp:501] detection_eval = 0.0412994
-I0511 11:50:55.661954  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.661958  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661963  5581 caffe.cpp:501] detection_eval = 3.34677
-I0511 11:50:55.661967  5581 caffe.cpp:501] detection_eval = 10.9073
-I0511 11:50:55.661972  5581 caffe.cpp:501] detection_eval = 0.0389469
-I0511 11:50:55.661976  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.661981  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.661985  5581 caffe.cpp:501] detection_eval = 3.34677
-I0511 11:50:55.661990  5581 caffe.cpp:501] detection_eval = 10.9718
-I0511 11:50:55.661994  5581 caffe.cpp:501] detection_eval = 0.0423717
-I0511 11:50:55.661999  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662003  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662009  5581 caffe.cpp:501] detection_eval = 3.34879
-I0511 11:50:55.662012  5581 caffe.cpp:501] detection_eval = 11.0161
-I0511 11:50:55.662017  5581 caffe.cpp:501] detection_eval = 0.0474591
-I0511 11:50:55.662021  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.662026  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.662030  5581 caffe.cpp:501] detection_eval = 3.35282
-I0511 11:50:55.662035  5581 caffe.cpp:501] detection_eval = 10.9899
-I0511 11:50:55.662039  5581 caffe.cpp:501] detection_eval = 0.0420343
-I0511 11:50:55.662045  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.662048  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662053  5581 caffe.cpp:501] detection_eval = 3.35685
-I0511 11:50:55.662057  5581 caffe.cpp:501] detection_eval = 10.9859
-I0511 11:50:55.662062  5581 caffe.cpp:501] detection_eval = 0.0453503
-I0511 11:50:55.662066  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662071  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662075  5581 caffe.cpp:501] detection_eval = 3.35685
-I0511 11:50:55.662081  5581 caffe.cpp:501] detection_eval = 11.0464
-I0511 11:50:55.662084  5581 caffe.cpp:501] detection_eval = 0.0403172
-I0511 11:50:55.662089  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662093  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662098  5581 caffe.cpp:501] detection_eval = 3.35685
-I0511 11:50:55.662102  5581 caffe.cpp:501] detection_eval = 11.1129
-I0511 11:50:55.662107  5581 caffe.cpp:501] detection_eval = 0.0402488
-I0511 11:50:55.662111  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.662117  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.662120  5581 caffe.cpp:501] detection_eval = 3.35887
-I0511 11:50:55.662125  5581 caffe.cpp:501] detection_eval = 11.1855
-I0511 11:50:55.662130  5581 caffe.cpp:501] detection_eval = 0.0435009
-I0511 11:50:55.662134  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.662139  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.662143  5581 caffe.cpp:501] detection_eval = 3.36089
-I0511 11:50:55.662148  5581 caffe.cpp:501] detection_eval = 11.246
-I0511 11:50:55.662153  5581 caffe.cpp:501] detection_eval = 0.0444329
-I0511 11:50:55.662158  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662163  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662168  5581 caffe.cpp:501] detection_eval = 3.3629
-I0511 11:50:55.662171  5581 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:50:55.662176  5581 caffe.cpp:501] detection_eval = 0.0411983
-I0511 11:50:55.662180  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662190  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662195  5581 caffe.cpp:501] detection_eval = 3.3629
-I0511 11:50:55.662199  5581 caffe.cpp:501] detection_eval = 11.3669
-I0511 11:50:55.662204  5581 caffe.cpp:501] detection_eval = 0.0414894
-I0511 11:50:55.662209  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662214  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662217  5581 caffe.cpp:501] detection_eval = 3.36492
-I0511 11:50:55.662222  5581 caffe.cpp:501] detection_eval = 11.4435
-I0511 11:50:55.662226  5581 caffe.cpp:501] detection_eval = 0.04472
-I0511 11:50:55.662231  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662235  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662240  5581 caffe.cpp:501] detection_eval = 3.36492
-I0511 11:50:55.662245  5581 caffe.cpp:501] detection_eval = 11.504
-I0511 11:50:55.662250  5581 caffe.cpp:501] detection_eval = 0.0420281
-I0511 11:50:55.662255  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662258  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662263  5581 caffe.cpp:501] detection_eval = 3.36895
-I0511 11:50:55.662267  5581 caffe.cpp:501] detection_eval = 11.5544
-I0511 11:50:55.662272  5581 caffe.cpp:501] detection_eval = 0.0472357
-I0511 11:50:55.662276  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.662281  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.662286  5581 caffe.cpp:501] detection_eval = 3.37097
-I0511 11:50:55.662289  5581 caffe.cpp:501] detection_eval = 11.6048
-I0511 11:50:55.662294  5581 caffe.cpp:501] detection_eval = 0.0450204
-I0511 11:50:55.662298  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.662303  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.662307  5581 caffe.cpp:501] detection_eval = 3.375
-I0511 11:50:55.662312  5581 caffe.cpp:501] detection_eval = 11.6048
-I0511 11:50:55.662317  5581 caffe.cpp:501] detection_eval = 0.0401472
-I0511 11:50:55.662322  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662326  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662331  5581 caffe.cpp:501] detection_eval = 3.37702
-I0511 11:50:55.662335  5581 caffe.cpp:501] detection_eval = 11.6855
-I0511 11:50:55.662340  5581 caffe.cpp:501] detection_eval = 0.0452125
-I0511 11:50:55.662344  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662349  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662354  5581 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:50:55.662358  5581 caffe.cpp:501] detection_eval = 11.7137
-I0511 11:50:55.662364  5581 caffe.cpp:501] detection_eval = 0.0457496
-I0511 11:50:55.662367  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662372  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662376  5581 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:50:55.662381  5581 caffe.cpp:501] detection_eval = 11.8145
-I0511 11:50:55.662385  5581 caffe.cpp:501] detection_eval = 0.0522002
-I0511 11:50:55.662390  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.662395  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.662400  5581 caffe.cpp:501] detection_eval = 3.38105
-I0511 11:50:55.662403  5581 caffe.cpp:501] detection_eval = 11.9173
-I0511 11:50:55.662408  5581 caffe.cpp:501] detection_eval = 0.0508763
-I0511 11:50:55.662413  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.662417  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.662422  5581 caffe.cpp:501] detection_eval = 3.38306
-I0511 11:50:55.662426  5581 caffe.cpp:501] detection_eval = 11.9819
-I0511 11:50:55.662431  5581 caffe.cpp:501] detection_eval = 0.0544258
-I0511 11:50:55.662436  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.662441  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.662444  5581 caffe.cpp:501] detection_eval = 3.3871
-I0511 11:50:55.662449  5581 caffe.cpp:501] detection_eval = 11.9798
-I0511 11:50:55.662454  5581 caffe.cpp:501] detection_eval = 0.0399811
-I0511 11:50:55.662464  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662470  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662474  5581 caffe.cpp:501] detection_eval = 3.3871
-I0511 11:50:55.662479  5581 caffe.cpp:501] detection_eval = 12.0625
-I0511 11:50:55.662483  5581 caffe.cpp:501] detection_eval = 0.0451576
-I0511 11:50:55.662488  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662493  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662497  5581 caffe.cpp:501] detection_eval = 3.39113
-I0511 11:50:55.662501  5581 caffe.cpp:501] detection_eval = 12.0847
-I0511 11:50:55.662506  5581 caffe.cpp:501] detection_eval = 0.0407882
-I0511 11:50:55.662510  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.662515  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662520  5581 caffe.cpp:501] detection_eval = 3.39113
-I0511 11:50:55.662524  5581 caffe.cpp:501] detection_eval = 12.125
-I0511 11:50:55.662529  5581 caffe.cpp:501] detection_eval = 0.0444575
-I0511 11:50:55.662533  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662539  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662544  5581 caffe.cpp:501] detection_eval = 3.39315
-I0511 11:50:55.662547  5581 caffe.cpp:501] detection_eval = 12.1411
-I0511 11:50:55.662552  5581 caffe.cpp:501] detection_eval = 0.038277
-I0511 11:50:55.662557  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662561  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662565  5581 caffe.cpp:501] detection_eval = 3.39718
-I0511 11:50:55.662570  5581 caffe.cpp:501] detection_eval = 12.1331
-I0511 11:50:55.662575  5581 caffe.cpp:501] detection_eval = 0.0387226
-I0511 11:50:55.662580  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.662583  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.662588  5581 caffe.cpp:501] detection_eval = 3.40323
-I0511 11:50:55.662592  5581 caffe.cpp:501] detection_eval = 12.1048
-I0511 11:50:55.662597  5581 caffe.cpp:501] detection_eval = 0.039161
-I0511 11:50:55.662601  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662606  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.662611  5581 caffe.cpp:501] detection_eval = 3.40524
-I0511 11:50:55.662616  5581 caffe.cpp:501] detection_eval = 12.1573
-I0511 11:50:55.662619  5581 caffe.cpp:501] detection_eval = 0.0400443
-I0511 11:50:55.662624  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662628  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662633  5581 caffe.cpp:501] detection_eval = 3.40726
-I0511 11:50:55.662637  5581 caffe.cpp:501] detection_eval = 12.1956
-I0511 11:50:55.662642  5581 caffe.cpp:501] detection_eval = 0.0410004
-I0511 11:50:55.662647  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662652  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662657  5581 caffe.cpp:501] detection_eval = 3.40927
-I0511 11:50:55.662660  5581 caffe.cpp:501] detection_eval = 12.2077
-I0511 11:50:55.662665  5581 caffe.cpp:501] detection_eval = 0.0385639
-I0511 11:50:55.662670  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.662674  5581 caffe.cpp:501] detection_eval = 1
-I0511 11:50:55.662679  5581 caffe.cpp:501] detection_eval = 3.41129
-I0511 11:50:55.662684  5581 caffe.cpp:501] detection_eval = 12.2339
-I0511 11:50:55.662688  5581 caffe.cpp:501] detection_eval = 0.0432004
-I0511 11:50:55.662693  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662698  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662703  5581 caffe.cpp:501] detection_eval = 3.41331
-I0511 11:50:55.662706  5581 caffe.cpp:501] detection_eval = 12.2944
-I0511 11:50:55.662711  5581 caffe.cpp:501] detection_eval = 0.0436488
-I0511 11:50:55.662715  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662720  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.662724  5581 caffe.cpp:501] detection_eval = 3.41734
-I0511 11:50:55.662729  5581 caffe.cpp:501] detection_eval = 12.3226
-I0511 11:50:55.662734  5581 caffe.cpp:501] detection_eval = 0.0417765
-I0511 11:50:55.662741  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662746  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662751  5581 caffe.cpp:501] detection_eval = 3.4254
-I0511 11:50:55.662755  5581 caffe.cpp:501] detection_eval = 12.2258
-I0511 11:50:55.662760  5581 caffe.cpp:501] detection_eval = 0.0403891
-I0511 11:50:55.662765  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662770  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662773  5581 caffe.cpp:501] detection_eval = 3.4254
-I0511 11:50:55.662777  5581 caffe.cpp:501] detection_eval = 12.2681
-I0511 11:50:55.662782  5581 caffe.cpp:501] detection_eval = 0.0386823
-I0511 11:50:55.662787  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662791  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662796  5581 caffe.cpp:501] detection_eval = 3.4254
-I0511 11:50:55.662801  5581 caffe.cpp:501] detection_eval = 12.2964
-I0511 11:50:55.662806  5581 caffe.cpp:501] detection_eval = 0.0396935
-I0511 11:50:55.662809  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662814  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.662819  5581 caffe.cpp:501] detection_eval = 3.4254
-I0511 11:50:55.662823  5581 caffe.cpp:501] detection_eval = 12.3649
-I0511 11:50:55.662828  5581 caffe.cpp:501] detection_eval = 0.0426829
-I0511 11:50:55.662832  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662837  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.662842  5581 caffe.cpp:501] detection_eval = 3.42742
-I0511 11:50:55.662845  5581 caffe.cpp:501] detection_eval = 12.4294
-I0511 11:50:55.662850  5581 caffe.cpp:501] detection_eval = 0.0410268
-I0511 11:50:55.662855  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.662860  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.662864  5581 caffe.cpp:501] detection_eval = 3.42742
-I0511 11:50:55.662868  5581 caffe.cpp:501] detection_eval = 12.502
-I0511 11:50:55.662873  5581 caffe.cpp:501] detection_eval = 0.041119
-I0511 11:50:55.662878  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.662883  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662888  5581 caffe.cpp:501] detection_eval = 3.43145
-I0511 11:50:55.662891  5581 caffe.cpp:501] detection_eval = 12.5645
-I0511 11:50:55.662896  5581 caffe.cpp:501] detection_eval = 0.0471057
-I0511 11:50:55.662901  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662905  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.662911  5581 caffe.cpp:501] detection_eval = 3.43548
-I0511 11:50:55.662915  5581 caffe.cpp:501] detection_eval = 12.5948
-I0511 11:50:55.662920  5581 caffe.cpp:501] detection_eval = 0.0487928
-I0511 11:50:55.662925  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.662930  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.662933  5581 caffe.cpp:501] detection_eval = 3.4375
-I0511 11:50:55.662938  5581 caffe.cpp:501] detection_eval = 12.6331
-I0511 11:50:55.662943  5581 caffe.cpp:501] detection_eval = 0.0462303
-I0511 11:50:55.662948  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662952  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.662957  5581 caffe.cpp:501] detection_eval = 3.43952
-I0511 11:50:55.662961  5581 caffe.cpp:501] detection_eval = 12.6593
-I0511 11:50:55.662966  5581 caffe.cpp:501] detection_eval = 0.0423336
-I0511 11:50:55.662971  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.662976  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.662979  5581 caffe.cpp:501] detection_eval = 3.44556
-I0511 11:50:55.662983  5581 caffe.cpp:501] detection_eval = 12.631
-I0511 11:50:55.662988  5581 caffe.cpp:501] detection_eval = 0.0434904
-I0511 11:50:55.662993  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.662997  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.663002  5581 caffe.cpp:501] detection_eval = 3.4496
-I0511 11:50:55.663007  5581 caffe.cpp:501] detection_eval = 12.6331
-I0511 11:50:55.663014  5581 caffe.cpp:501] detection_eval = 0.0369244
-I0511 11:50:55.663018  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663023  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663028  5581 caffe.cpp:501] detection_eval = 3.45363
-I0511 11:50:55.663033  5581 caffe.cpp:501] detection_eval = 12.6411
-I0511 11:50:55.663038  5581 caffe.cpp:501] detection_eval = 0.0398743
-I0511 11:50:55.663041  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663046  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.663050  5581 caffe.cpp:501] detection_eval = 3.46169
-I0511 11:50:55.663054  5581 caffe.cpp:501] detection_eval = 12.5726
-I0511 11:50:55.663059  5581 caffe.cpp:501] detection_eval = 0.0438739
-I0511 11:50:55.663064  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.663069  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.663072  5581 caffe.cpp:501] detection_eval = 3.46976
-I0511 11:50:55.663077  5581 caffe.cpp:501] detection_eval = 12.5161
-I0511 11:50:55.663082  5581 caffe.cpp:501] detection_eval = 0.0385053
-I0511 11:50:55.663086  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663091  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.663095  5581 caffe.cpp:501] detection_eval = 3.46976
-I0511 11:50:55.663100  5581 caffe.cpp:501] detection_eval = 12.5706
-I0511 11:50:55.663105  5581 caffe.cpp:501] detection_eval = 0.0371973
-I0511 11:50:55.663108  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663113  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663117  5581 caffe.cpp:501] detection_eval = 3.47177
-I0511 11:50:55.663121  5581 caffe.cpp:501] detection_eval = 12.5786
-I0511 11:50:55.663126  5581 caffe.cpp:501] detection_eval = 0.037234
-I0511 11:50:55.663130  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663136  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.663139  5581 caffe.cpp:501] detection_eval = 3.47177
-I0511 11:50:55.663144  5581 caffe.cpp:501] detection_eval = 12.6129
-I0511 11:50:55.663148  5581 caffe.cpp:501] detection_eval = 0.0371231
-I0511 11:50:55.663153  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663157  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663162  5581 caffe.cpp:501] detection_eval = 3.47581
-I0511 11:50:55.663166  5581 caffe.cpp:501] detection_eval = 12.5867
-I0511 11:50:55.663172  5581 caffe.cpp:501] detection_eval = 0.0363783
-I0511 11:50:55.663175  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663180  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663184  5581 caffe.cpp:501] detection_eval = 3.47581
-I0511 11:50:55.663189  5581 caffe.cpp:501] detection_eval = 12.6411
-I0511 11:50:55.663193  5581 caffe.cpp:501] detection_eval = 0.0411364
-I0511 11:50:55.663198  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663203  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.663208  5581 caffe.cpp:501] detection_eval = 3.47782
-I0511 11:50:55.663211  5581 caffe.cpp:501] detection_eval = 12.7056
-I0511 11:50:55.663216  5581 caffe.cpp:501] detection_eval = 0.0376425
-I0511 11:50:55.663221  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663225  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663230  5581 caffe.cpp:501] detection_eval = 3.47984
-I0511 11:50:55.663235  5581 caffe.cpp:501] detection_eval = 12.7177
-I0511 11:50:55.663239  5581 caffe.cpp:501] detection_eval = 0.0359646
-I0511 11:50:55.663244  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663249  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663254  5581 caffe.cpp:501] detection_eval = 3.48589
-I0511 11:50:55.663259  5581 caffe.cpp:501] detection_eval = 12.6754
-I0511 11:50:55.663262  5581 caffe.cpp:501] detection_eval = 0.0359471
-I0511 11:50:55.663267  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.663271  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.663276  5581 caffe.cpp:501] detection_eval = 3.48589
-I0511 11:50:55.663280  5581 caffe.cpp:501] detection_eval = 12.7238
-I0511 11:50:55.663288  5581 caffe.cpp:501] detection_eval = 0.0384166
-I0511 11:50:55.663293  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663298  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663303  5581 caffe.cpp:501] detection_eval = 3.48992
-I0511 11:50:55.663307  5581 caffe.cpp:501] detection_eval = 12.7157
-I0511 11:50:55.663312  5581 caffe.cpp:501] detection_eval = 0.0378033
-I0511 11:50:55.663316  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663321  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663326  5581 caffe.cpp:501] detection_eval = 3.49597
-I0511 11:50:55.663331  5581 caffe.cpp:501] detection_eval = 12.6472
-I0511 11:50:55.663336  5581 caffe.cpp:501] detection_eval = 0.0381147
-I0511 11:50:55.663339  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.663344  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.663348  5581 caffe.cpp:501] detection_eval = 3.5
-I0511 11:50:55.663353  5581 caffe.cpp:501] detection_eval = 12.6593
-I0511 11:50:55.663358  5581 caffe.cpp:501] detection_eval = 0.033748
-I0511 11:50:55.663362  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663367  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663372  5581 caffe.cpp:501] detection_eval = 3.5
-I0511 11:50:55.663377  5581 caffe.cpp:501] detection_eval = 12.6895
-I0511 11:50:55.663380  5581 caffe.cpp:501] detection_eval = 0.0337718
-I0511 11:50:55.663385  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663389  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663393  5581 caffe.cpp:501] detection_eval = 3.5
-I0511 11:50:55.663398  5581 caffe.cpp:501] detection_eval = 12.746
-I0511 11:50:55.663403  5581 caffe.cpp:501] detection_eval = 0.0341012
-I0511 11:50:55.663408  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663413  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663416  5581 caffe.cpp:501] detection_eval = 3.50605
-I0511 11:50:55.663421  5581 caffe.cpp:501] detection_eval = 12.7782
-I0511 11:50:55.663425  5581 caffe.cpp:501] detection_eval = 0.0367891
-I0511 11:50:55.663430  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663434  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663439  5581 caffe.cpp:501] detection_eval = 3.51008
-I0511 11:50:55.663444  5581 caffe.cpp:501] detection_eval = 12.7601
-I0511 11:50:55.663450  5581 caffe.cpp:501] detection_eval = 0.0369924
-I0511 11:50:55.663453  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.663458  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663462  5581 caffe.cpp:501] detection_eval = 3.51411
-I0511 11:50:55.663468  5581 caffe.cpp:501] detection_eval = 12.752
-I0511 11:50:55.663473  5581 caffe.cpp:501] detection_eval = 0.0390217
-I0511 11:50:55.663477  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.663481  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.663486  5581 caffe.cpp:501] detection_eval = 3.51613
-I0511 11:50:55.663491  5581 caffe.cpp:501] detection_eval = 12.8407
-I0511 11:50:55.663496  5581 caffe.cpp:501] detection_eval = 0.0383866
-I0511 11:50:55.663501  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663506  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663509  5581 caffe.cpp:501] detection_eval = 3.51815
-I0511 11:50:55.663514  5581 caffe.cpp:501] detection_eval = 12.8548
-I0511 11:50:55.663518  5581 caffe.cpp:501] detection_eval = 0.042047
-I0511 11:50:55.663523  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663527  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.663532  5581 caffe.cpp:501] detection_eval = 3.52016
-I0511 11:50:55.663537  5581 caffe.cpp:501] detection_eval = 12.881
-I0511 11:50:55.663542  5581 caffe.cpp:501] detection_eval = 0.0372107
-I0511 11:50:55.663545  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663550  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663555  5581 caffe.cpp:501] detection_eval = 3.52218
-I0511 11:50:55.663563  5581 caffe.cpp:501] detection_eval = 12.8931
-I0511 11:50:55.663568  5581 caffe.cpp:501] detection_eval = 0.0364517
-I0511 11:50:55.663573  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663576  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663581  5581 caffe.cpp:501] detection_eval = 3.52218
-I0511 11:50:55.663585  5581 caffe.cpp:501] detection_eval = 12.9657
-I0511 11:50:55.663590  5581 caffe.cpp:501] detection_eval = 0.0351007
-I0511 11:50:55.663594  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.663599  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.663604  5581 caffe.cpp:501] detection_eval = 3.52621
-I0511 11:50:55.663609  5581 caffe.cpp:501] detection_eval = 12.9556
-I0511 11:50:55.663614  5581 caffe.cpp:501] detection_eval = 0.0346564
-I0511 11:50:55.663619  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663622  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663627  5581 caffe.cpp:501] detection_eval = 3.52823
-I0511 11:50:55.663631  5581 caffe.cpp:501] detection_eval = 12.9899
-I0511 11:50:55.663636  5581 caffe.cpp:501] detection_eval = 0.0356952
-I0511 11:50:55.663640  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663645  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663650  5581 caffe.cpp:501] detection_eval = 3.52823
-I0511 11:50:55.663655  5581 caffe.cpp:501] detection_eval = 13.0565
-I0511 11:50:55.663658  5581 caffe.cpp:501] detection_eval = 0.0364956
-I0511 11:50:55.663663  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663667  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663672  5581 caffe.cpp:501] detection_eval = 3.53226
-I0511 11:50:55.663676  5581 caffe.cpp:501] detection_eval = 13.0343
-I0511 11:50:55.663681  5581 caffe.cpp:501] detection_eval = 0.0377902
-I0511 11:50:55.663686  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663691  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.663694  5581 caffe.cpp:501] detection_eval = 3.53427
-I0511 11:50:55.663698  5581 caffe.cpp:501] detection_eval = 13.0444
-I0511 11:50:55.663703  5581 caffe.cpp:501] detection_eval = 0.0378157
-I0511 11:50:55.663707  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663712  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663717  5581 caffe.cpp:501] detection_eval = 3.53831
-I0511 11:50:55.663722  5581 caffe.cpp:501] detection_eval = 13.0827
-I0511 11:50:55.663725  5581 caffe.cpp:501] detection_eval = 0.0363094
-I0511 11:50:55.663730  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663734  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.663739  5581 caffe.cpp:501] detection_eval = 3.53831
-I0511 11:50:55.663743  5581 caffe.cpp:501] detection_eval = 13.1532
-I0511 11:50:55.663748  5581 caffe.cpp:501] detection_eval = 0.0387398
-I0511 11:50:55.663753  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663756  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663761  5581 caffe.cpp:501] detection_eval = 3.54032
-I0511 11:50:55.663765  5581 caffe.cpp:501] detection_eval = 13.2298
-I0511 11:50:55.663770  5581 caffe.cpp:501] detection_eval = 0.0371919
-I0511 11:50:55.663774  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663779  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.663784  5581 caffe.cpp:501] detection_eval = 3.54435
-I0511 11:50:55.663789  5581 caffe.cpp:501] detection_eval = 13.25
-I0511 11:50:55.663794  5581 caffe.cpp:501] detection_eval = 0.0400435
-I0511 11:50:55.663797  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663802  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663806  5581 caffe.cpp:501] detection_eval = 3.54435
-I0511 11:50:55.663810  5581 caffe.cpp:501] detection_eval = 13.3387
-I0511 11:50:55.663815  5581 caffe.cpp:501] detection_eval = 0.0379552
-I0511 11:50:55.663820  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.663825  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663833  5581 caffe.cpp:501] detection_eval = 3.5504
-I0511 11:50:55.663838  5581 caffe.cpp:501] detection_eval = 13.3125
-I0511 11:50:55.663842  5581 caffe.cpp:501] detection_eval = 0.0364762
-I0511 11:50:55.663847  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.663851  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663856  5581 caffe.cpp:501] detection_eval = 3.55645
-I0511 11:50:55.663861  5581 caffe.cpp:501] detection_eval = 13.2581
-I0511 11:50:55.663866  5581 caffe.cpp:501] detection_eval = 0.0388246
-I0511 11:50:55.663869  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663874  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663878  5581 caffe.cpp:501] detection_eval = 3.56048
-I0511 11:50:55.663883  5581 caffe.cpp:501] detection_eval = 13.3145
-I0511 11:50:55.663887  5581 caffe.cpp:501] detection_eval = 0.0419986
-I0511 11:50:55.663892  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663897  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.663902  5581 caffe.cpp:501] detection_eval = 3.56048
-I0511 11:50:55.663905  5581 caffe.cpp:501] detection_eval = 13.3891
-I0511 11:50:55.663910  5581 caffe.cpp:501] detection_eval = 0.03772
-I0511 11:50:55.663914  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.663919  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.663923  5581 caffe.cpp:501] detection_eval = 3.5625
-I0511 11:50:55.663928  5581 caffe.cpp:501] detection_eval = 13.4597
-I0511 11:50:55.663933  5581 caffe.cpp:501] detection_eval = 0.0409735
-I0511 11:50:55.663938  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663942  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.663947  5581 caffe.cpp:501] detection_eval = 3.5625
-I0511 11:50:55.663951  5581 caffe.cpp:501] detection_eval = 13.6008
-I0511 11:50:55.663956  5581 caffe.cpp:501] detection_eval = 0.0356702
-I0511 11:50:55.663960  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.663965  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.663969  5581 caffe.cpp:501] detection_eval = 3.56855
-I0511 11:50:55.663975  5581 caffe.cpp:501] detection_eval = 13.6613
-I0511 11:50:55.663980  5581 caffe.cpp:501] detection_eval = 0.0413387
-I0511 11:50:55.663983  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.663988  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.663992  5581 caffe.cpp:501] detection_eval = 3.56855
-I0511 11:50:55.663996  5581 caffe.cpp:501] detection_eval = 13.7762
-I0511 11:50:55.664001  5581 caffe.cpp:501] detection_eval = 0.0366315
-I0511 11:50:55.664006  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664011  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.664014  5581 caffe.cpp:501] detection_eval = 3.57056
-I0511 11:50:55.664019  5581 caffe.cpp:501] detection_eval = 13.9234
-I0511 11:50:55.664024  5581 caffe.cpp:501] detection_eval = 0.0361069
-I0511 11:50:55.664028  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664033  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664037  5581 caffe.cpp:501] detection_eval = 3.5746
-I0511 11:50:55.664041  5581 caffe.cpp:501] detection_eval = 14.004
-I0511 11:50:55.664047  5581 caffe.cpp:501] detection_eval = 0.034146
-I0511 11:50:55.664052  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664055  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664059  5581 caffe.cpp:501] detection_eval = 3.57863
-I0511 11:50:55.664064  5581 caffe.cpp:501] detection_eval = 14.1331
-I0511 11:50:55.664068  5581 caffe.cpp:501] detection_eval = 0.0357709
-I0511 11:50:55.664073  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.664077  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.664083  5581 caffe.cpp:501] detection_eval = 3.58468
-I0511 11:50:55.664086  5581 caffe.cpp:501] detection_eval = 14.2923
-I0511 11:50:55.664091  5581 caffe.cpp:501] detection_eval = 0.0329436
-I0511 11:50:55.664095  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.664100  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.664108  5581 caffe.cpp:501] detection_eval = 4.10282
-I0511 11:50:55.664113  5581 caffe.cpp:501] detection_eval = 6.76815
-I0511 11:50:55.664116  5581 caffe.cpp:501] detection_eval = 0.0905092
-I0511 11:50:55.664121  5581 caffe.cpp:501] detection_eval = 0.0685484
-I0511 11:50:55.664125  5581 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:50:55.664130  5581 caffe.cpp:501] detection_eval = 4.10484
-I0511 11:50:55.664134  5581 caffe.cpp:501] detection_eval = 6.96976
-I0511 11:50:55.664139  5581 caffe.cpp:501] detection_eval = 0.0644852
-I0511 11:50:55.664144  5581 caffe.cpp:501] detection_eval = 0.0342742
-I0511 11:50:55.664149  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.664152  5581 caffe.cpp:501] detection_eval = 4.10484
-I0511 11:50:55.664157  5581 caffe.cpp:501] detection_eval = 7.11694
-I0511 11:50:55.664161  5581 caffe.cpp:501] detection_eval = 0.0627071
-I0511 11:50:55.664166  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.664170  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.664175  5581 caffe.cpp:501] detection_eval = 4.10887
-I0511 11:50:55.664180  5581 caffe.cpp:501] detection_eval = 7.22581
-I0511 11:50:55.664183  5581 caffe.cpp:501] detection_eval = 0.0579806
-I0511 11:50:55.664188  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.664192  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.664197  5581 caffe.cpp:501] detection_eval = 4.1129
-I0511 11:50:55.664201  5581 caffe.cpp:501] detection_eval = 7.32863
-I0511 11:50:55.664206  5581 caffe.cpp:501] detection_eval = 0.0572587
-I0511 11:50:55.664211  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.664214  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.664219  5581 caffe.cpp:501] detection_eval = 4.11492
-I0511 11:50:55.664223  5581 caffe.cpp:501] detection_eval = 7.41935
-I0511 11:50:55.664227  5581 caffe.cpp:501] detection_eval = 0.0513708
-I0511 11:50:55.664232  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664237  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.664242  5581 caffe.cpp:501] detection_eval = 4.11694
-I0511 11:50:55.664245  5581 caffe.cpp:501] detection_eval = 7.44153
-I0511 11:50:55.664249  5581 caffe.cpp:501] detection_eval = 0.0486991
-I0511 11:50:55.664254  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.664258  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.664263  5581 caffe.cpp:501] detection_eval = 4.11895
-I0511 11:50:55.664268  5581 caffe.cpp:501] detection_eval = 7.51008
-I0511 11:50:55.664271  5581 caffe.cpp:501] detection_eval = 0.0435088
-I0511 11:50:55.664276  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.664280  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.664285  5581 caffe.cpp:501] detection_eval = 4.11895
-I0511 11:50:55.664289  5581 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:50:55.664294  5581 caffe.cpp:501] detection_eval = 0.0472525
-I0511 11:50:55.664299  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664304  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.664307  5581 caffe.cpp:501] detection_eval = 4.125
-I0511 11:50:55.664312  5581 caffe.cpp:501] detection_eval = 7.62903
-I0511 11:50:55.664316  5581 caffe.cpp:501] detection_eval = 0.0532138
-I0511 11:50:55.664321  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.664325  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.664330  5581 caffe.cpp:501] detection_eval = 4.12702
-I0511 11:50:55.664335  5581 caffe.cpp:501] detection_eval = 7.71774
-I0511 11:50:55.664338  5581 caffe.cpp:501] detection_eval = 0.0483561
-I0511 11:50:55.664343  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.664347  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.664352  5581 caffe.cpp:501] detection_eval = 4.12702
-I0511 11:50:55.664356  5581 caffe.cpp:501] detection_eval = 7.80444
-I0511 11:50:55.664361  5581 caffe.cpp:501] detection_eval = 0.0546764
-I0511 11:50:55.664366  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.664372  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.664377  5581 caffe.cpp:501] detection_eval = 4.12903
-I0511 11:50:55.664382  5581 caffe.cpp:501] detection_eval = 7.8629
-I0511 11:50:55.664386  5581 caffe.cpp:501] detection_eval = 0.0472698
-I0511 11:50:55.664391  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664396  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664400  5581 caffe.cpp:501] detection_eval = 4.13306
-I0511 11:50:55.664404  5581 caffe.cpp:501] detection_eval = 7.89919
-I0511 11:50:55.664408  5581 caffe.cpp:501] detection_eval = 0.0498237
-I0511 11:50:55.664413  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.664417  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.664422  5581 caffe.cpp:501] detection_eval = 4.1371
-I0511 11:50:55.664427  5581 caffe.cpp:501] detection_eval = 7.92742
-I0511 11:50:55.664432  5581 caffe.cpp:501] detection_eval = 0.0475132
-I0511 11:50:55.664435  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.664440  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.664444  5581 caffe.cpp:501] detection_eval = 4.13911
-I0511 11:50:55.664448  5581 caffe.cpp:501] detection_eval = 7.94758
-I0511 11:50:55.664453  5581 caffe.cpp:501] detection_eval = 0.0415651
-I0511 11:50:55.664458  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664463  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664466  5581 caffe.cpp:501] detection_eval = 4.14315
-I0511 11:50:55.664470  5581 caffe.cpp:501] detection_eval = 7.97379
-I0511 11:50:55.664475  5581 caffe.cpp:501] detection_eval = 0.0415416
-I0511 11:50:55.664479  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664484  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664489  5581 caffe.cpp:501] detection_eval = 4.14516
-I0511 11:50:55.664494  5581 caffe.cpp:501] detection_eval = 8.00605
-I0511 11:50:55.664497  5581 caffe.cpp:501] detection_eval = 0.0378814
-I0511 11:50:55.664502  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664506  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.664510  5581 caffe.cpp:501] detection_eval = 4.14919
-I0511 11:50:55.664515  5581 caffe.cpp:501] detection_eval = 8.03024
-I0511 11:50:55.664520  5581 caffe.cpp:501] detection_eval = 0.0385318
-I0511 11:50:55.664530  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664535  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664541  5581 caffe.cpp:501] detection_eval = 4.15121
-I0511 11:50:55.664544  5581 caffe.cpp:501] detection_eval = 8.05242
-I0511 11:50:55.664548  5581 caffe.cpp:501] detection_eval = 0.0426493
-I0511 11:50:55.664553  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664557  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664562  5581 caffe.cpp:501] detection_eval = 4.15323
-I0511 11:50:55.664566  5581 caffe.cpp:501] detection_eval = 8.08468
-I0511 11:50:55.664572  5581 caffe.cpp:501] detection_eval = 0.0418494
-I0511 11:50:55.664575  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664580  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664584  5581 caffe.cpp:501] detection_eval = 4.15323
-I0511 11:50:55.664589  5581 caffe.cpp:501] detection_eval = 8.15524
-I0511 11:50:55.664593  5581 caffe.cpp:501] detection_eval = 0.0368556
-I0511 11:50:55.664597  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.664602  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664607  5581 caffe.cpp:501] detection_eval = 4.15726
-I0511 11:50:55.664611  5581 caffe.cpp:501] detection_eval = 8.16734
-I0511 11:50:55.664615  5581 caffe.cpp:501] detection_eval = 0.0369818
-I0511 11:50:55.664620  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664624  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664629  5581 caffe.cpp:501] detection_eval = 4.16532
-I0511 11:50:55.664633  5581 caffe.cpp:501] detection_eval = 8.14516
-I0511 11:50:55.664638  5581 caffe.cpp:501] detection_eval = 0.0413868
-I0511 11:50:55.664643  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664650  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664655  5581 caffe.cpp:501] detection_eval = 4.17137
-I0511 11:50:55.664659  5581 caffe.cpp:501] detection_eval = 8.14919
-I0511 11:50:55.664664  5581 caffe.cpp:501] detection_eval = 0.0452327
-I0511 11:50:55.664669  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.664672  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.664677  5581 caffe.cpp:501] detection_eval = 4.17339
-I0511 11:50:55.664681  5581 caffe.cpp:501] detection_eval = 8.21169
-I0511 11:50:55.664686  5581 caffe.cpp:501] detection_eval = 0.0418572
-I0511 11:50:55.664690  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664695  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664700  5581 caffe.cpp:501] detection_eval = 4.17742
-I0511 11:50:55.664703  5581 caffe.cpp:501] detection_eval = 8.23387
-I0511 11:50:55.664708  5581 caffe.cpp:501] detection_eval = 0.0442426
-I0511 11:50:55.664712  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664717  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664721  5581 caffe.cpp:501] detection_eval = 4.17742
-I0511 11:50:55.664726  5581 caffe.cpp:501] detection_eval = 8.30645
-I0511 11:50:55.664731  5581 caffe.cpp:501] detection_eval = 0.0407148
-I0511 11:50:55.664736  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.664739  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.664743  5581 caffe.cpp:501] detection_eval = 4.18145
-I0511 11:50:55.664747  5581 caffe.cpp:501] detection_eval = 8.30242
-I0511 11:50:55.664752  5581 caffe.cpp:501] detection_eval = 0.0422106
-I0511 11:50:55.664757  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664762  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664765  5581 caffe.cpp:501] detection_eval = 4.18347
-I0511 11:50:55.664770  5581 caffe.cpp:501] detection_eval = 8.34879
-I0511 11:50:55.664774  5581 caffe.cpp:501] detection_eval = 0.0429992
-I0511 11:50:55.664779  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664783  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.664788  5581 caffe.cpp:501] detection_eval = 4.18548
-I0511 11:50:55.664793  5581 caffe.cpp:501] detection_eval = 8.47177
-I0511 11:50:55.664796  5581 caffe.cpp:501] detection_eval = 0.0445516
-I0511 11:50:55.664801  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.664805  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.664810  5581 caffe.cpp:501] detection_eval = 4.1875
-I0511 11:50:55.664814  5581 caffe.cpp:501] detection_eval = 8.50202
-I0511 11:50:55.664819  5581 caffe.cpp:501] detection_eval = 0.0383899
-I0511 11:50:55.664824  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664829  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.664832  5581 caffe.cpp:501] detection_eval = 4.19153
-I0511 11:50:55.664837  5581 caffe.cpp:501] detection_eval = 8.52823
-I0511 11:50:55.664841  5581 caffe.cpp:501] detection_eval = 0.0370178
-I0511 11:50:55.664846  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664850  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.664855  5581 caffe.cpp:501] detection_eval = 4.19355
-I0511 11:50:55.664860  5581 caffe.cpp:501] detection_eval = 8.56855
-I0511 11:50:55.664865  5581 caffe.cpp:501] detection_eval = 0.0433073
-I0511 11:50:55.664868  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664873  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664877  5581 caffe.cpp:501] detection_eval = 4.19355
-I0511 11:50:55.664881  5581 caffe.cpp:501] detection_eval = 8.65927
-I0511 11:50:55.664886  5581 caffe.cpp:501] detection_eval = 0.0473801
-I0511 11:50:55.664891  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664896  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664899  5581 caffe.cpp:501] detection_eval = 4.19556
-I0511 11:50:55.664904  5581 caffe.cpp:501] detection_eval = 8.66734
-I0511 11:50:55.664908  5581 caffe.cpp:501] detection_eval = 0.0405125
-I0511 11:50:55.664916  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.664921  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.664925  5581 caffe.cpp:501] detection_eval = 4.19758
-I0511 11:50:55.664929  5581 caffe.cpp:501] detection_eval = 8.72177
-I0511 11:50:55.664934  5581 caffe.cpp:501] detection_eval = 0.0375741
-I0511 11:50:55.664938  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664943  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664947  5581 caffe.cpp:501] detection_eval = 4.19758
-I0511 11:50:55.664952  5581 caffe.cpp:501] detection_eval = 8.77218
-I0511 11:50:55.664957  5581 caffe.cpp:501] detection_eval = 0.041395
-I0511 11:50:55.664961  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.664965  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.664970  5581 caffe.cpp:501] detection_eval = 4.1996
-I0511 11:50:55.664974  5581 caffe.cpp:501] detection_eval = 8.80847
-I0511 11:50:55.664978  5581 caffe.cpp:501] detection_eval = 0.043218
-I0511 11:50:55.664983  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.664988  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.664993  5581 caffe.cpp:501] detection_eval = 4.20363
-I0511 11:50:55.664996  5581 caffe.cpp:501] detection_eval = 8.80847
-I0511 11:50:55.665001  5581 caffe.cpp:501] detection_eval = 0.0418496
-I0511 11:50:55.665005  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665009  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.665014  5581 caffe.cpp:501] detection_eval = 4.20363
-I0511 11:50:55.665019  5581 caffe.cpp:501] detection_eval = 8.88508
-I0511 11:50:55.665022  5581 caffe.cpp:501] detection_eval = 0.0375474
-I0511 11:50:55.665027  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.665031  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665036  5581 caffe.cpp:501] detection_eval = 4.20363
-I0511 11:50:55.665040  5581 caffe.cpp:501] detection_eval = 8.94758
-I0511 11:50:55.665045  5581 caffe.cpp:501] detection_eval = 0.0381792
-I0511 11:50:55.665050  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665053  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665058  5581 caffe.cpp:501] detection_eval = 4.20766
-I0511 11:50:55.665062  5581 caffe.cpp:501] detection_eval = 8.9879
-I0511 11:50:55.665067  5581 caffe.cpp:501] detection_eval = 0.0396819
-I0511 11:50:55.665071  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.665076  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665081  5581 caffe.cpp:501] detection_eval = 4.21371
-I0511 11:50:55.665086  5581 caffe.cpp:501] detection_eval = 8.93952
-I0511 11:50:55.665089  5581 caffe.cpp:501] detection_eval = 0.0350682
-I0511 11:50:55.665093  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665098  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665102  5581 caffe.cpp:501] detection_eval = 4.21573
-I0511 11:50:55.665107  5581 caffe.cpp:501] detection_eval = 8.98589
-I0511 11:50:55.665112  5581 caffe.cpp:501] detection_eval = 0.0396747
-I0511 11:50:55.665115  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665120  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665124  5581 caffe.cpp:501] detection_eval = 4.21774
-I0511 11:50:55.665129  5581 caffe.cpp:501] detection_eval = 9.04435
-I0511 11:50:55.665133  5581 caffe.cpp:501] detection_eval = 0.0390687
-I0511 11:50:55.665138  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.665143  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665148  5581 caffe.cpp:501] detection_eval = 4.21774
-I0511 11:50:55.665151  5581 caffe.cpp:501] detection_eval = 9.10685
-I0511 11:50:55.665155  5581 caffe.cpp:501] detection_eval = 0.0397611
-I0511 11:50:55.665160  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665164  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665169  5581 caffe.cpp:501] detection_eval = 4.22177
-I0511 11:50:55.665174  5581 caffe.cpp:501] detection_eval = 9.1371
-I0511 11:50:55.665181  5581 caffe.cpp:501] detection_eval = 0.044734
-I0511 11:50:55.665186  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.665190  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.665195  5581 caffe.cpp:501] detection_eval = 4.22782
-I0511 11:50:55.665199  5581 caffe.cpp:501] detection_eval = 9.06855
-I0511 11:50:55.665205  5581 caffe.cpp:501] detection_eval = 0.0412259
-I0511 11:50:55.665210  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665213  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665218  5581 caffe.cpp:501] detection_eval = 4.22984
-I0511 11:50:55.665222  5581 caffe.cpp:501] detection_eval = 9.15927
-I0511 11:50:55.665226  5581 caffe.cpp:501] detection_eval = 0.0449804
-I0511 11:50:55.665231  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665235  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665241  5581 caffe.cpp:501] detection_eval = 4.23185
-I0511 11:50:55.665244  5581 caffe.cpp:501] detection_eval = 9.21976
-I0511 11:50:55.665248  5581 caffe.cpp:501] detection_eval = 0.0495442
-I0511 11:50:55.665253  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.665257  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665262  5581 caffe.cpp:501] detection_eval = 4.23387
-I0511 11:50:55.665266  5581 caffe.cpp:501] detection_eval = 9.24395
-I0511 11:50:55.665271  5581 caffe.cpp:501] detection_eval = 0.0492313
-I0511 11:50:55.665275  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.665279  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.665283  5581 caffe.cpp:501] detection_eval = 4.23387
-I0511 11:50:55.665288  5581 caffe.cpp:501] detection_eval = 9.30847
-I0511 11:50:55.665292  5581 caffe.cpp:501] detection_eval = 0.045926
-I0511 11:50:55.665297  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.665302  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665307  5581 caffe.cpp:501] detection_eval = 4.23589
-I0511 11:50:55.665310  5581 caffe.cpp:501] detection_eval = 9.39315
-I0511 11:50:55.665314  5581 caffe.cpp:501] detection_eval = 0.0468036
-I0511 11:50:55.665319  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.665323  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665328  5581 caffe.cpp:501] detection_eval = 4.23589
-I0511 11:50:55.665333  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.665338  5581 caffe.cpp:501] detection_eval = 0.0508337
-I0511 11:50:55.665341  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.665345  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.665350  5581 caffe.cpp:501] detection_eval = 4.23589
-I0511 11:50:55.665354  5581 caffe.cpp:501] detection_eval = 9.59476
-I0511 11:50:55.665359  5581 caffe.cpp:501] detection_eval = 0.0415461
-I0511 11:50:55.665364  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665369  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665372  5581 caffe.cpp:501] detection_eval = 4.2379
-I0511 11:50:55.665377  5581 caffe.cpp:501] detection_eval = 9.64516
-I0511 11:50:55.665381  5581 caffe.cpp:501] detection_eval = 0.0447107
-I0511 11:50:55.665386  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.665390  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665395  5581 caffe.cpp:501] detection_eval = 4.2379
-I0511 11:50:55.665400  5581 caffe.cpp:501] detection_eval = 9.69153
-I0511 11:50:55.665403  5581 caffe.cpp:501] detection_eval = 0.0375447
-I0511 11:50:55.665408  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665412  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.665417  5581 caffe.cpp:501] detection_eval = 4.23992
-I0511 11:50:55.665421  5581 caffe.cpp:501] detection_eval = 9.73589
-I0511 11:50:55.665426  5581 caffe.cpp:501] detection_eval = 0.0430661
-I0511 11:50:55.665431  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665434  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665439  5581 caffe.cpp:501] detection_eval = 4.24194
-I0511 11:50:55.665443  5581 caffe.cpp:501] detection_eval = 9.79435
-I0511 11:50:55.665451  5581 caffe.cpp:501] detection_eval = 0.0461263
-I0511 11:50:55.665455  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.665460  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665464  5581 caffe.cpp:501] detection_eval = 4.24395
-I0511 11:50:55.665469  5581 caffe.cpp:501] detection_eval = 9.87298
-I0511 11:50:55.665473  5581 caffe.cpp:501] detection_eval = 0.0567309
-I0511 11:50:55.665478  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.665482  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.665486  5581 caffe.cpp:501] detection_eval = 4.25
-I0511 11:50:55.665491  5581 caffe.cpp:501] detection_eval = 9.82661
-I0511 11:50:55.665495  5581 caffe.cpp:501] detection_eval = 0.0488227
-I0511 11:50:55.665500  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.665504  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.665509  5581 caffe.cpp:501] detection_eval = 4.25
-I0511 11:50:55.665513  5581 caffe.cpp:501] detection_eval = 9.86895
-I0511 11:50:55.665518  5581 caffe.cpp:501] detection_eval = 0.0474801
-I0511 11:50:55.665522  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665527  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665531  5581 caffe.cpp:501] detection_eval = 4.25605
-I0511 11:50:55.665536  5581 caffe.cpp:501] detection_eval = 9.875
-I0511 11:50:55.665540  5581 caffe.cpp:501] detection_eval = 0.0479852
-I0511 11:50:55.665544  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.665549  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665554  5581 caffe.cpp:501] detection_eval = 4.25605
-I0511 11:50:55.665557  5581 caffe.cpp:501] detection_eval = 9.92944
-I0511 11:50:55.665562  5581 caffe.cpp:501] detection_eval = 0.0425905
-I0511 11:50:55.665566  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665571  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.665575  5581 caffe.cpp:501] detection_eval = 4.25806
-I0511 11:50:55.665580  5581 caffe.cpp:501] detection_eval = 9.99798
-I0511 11:50:55.665585  5581 caffe.cpp:501] detection_eval = 0.042935
-I0511 11:50:55.665588  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665593  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665597  5581 caffe.cpp:501] detection_eval = 4.25806
-I0511 11:50:55.665602  5581 caffe.cpp:501] detection_eval = 10.1048
-I0511 11:50:55.665606  5581 caffe.cpp:501] detection_eval = 0.0455724
-I0511 11:50:55.665611  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.665616  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.665621  5581 caffe.cpp:501] detection_eval = 4.25806
-I0511 11:50:55.665624  5581 caffe.cpp:501] detection_eval = 10.2056
-I0511 11:50:55.665629  5581 caffe.cpp:501] detection_eval = 0.0434433
-I0511 11:50:55.665634  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.665638  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665643  5581 caffe.cpp:501] detection_eval = 4.26008
-I0511 11:50:55.665647  5581 caffe.cpp:501] detection_eval = 10.2903
-I0511 11:50:55.665652  5581 caffe.cpp:501] detection_eval = 0.0421711
-I0511 11:50:55.665657  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665661  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.665665  5581 caffe.cpp:501] detection_eval = 4.26815
-I0511 11:50:55.665669  5581 caffe.cpp:501] detection_eval = 10.2964
-I0511 11:50:55.665674  5581 caffe.cpp:501] detection_eval = 0.0435917
-I0511 11:50:55.665679  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665683  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665688  5581 caffe.cpp:501] detection_eval = 4.27016
-I0511 11:50:55.665693  5581 caffe.cpp:501] detection_eval = 10.3609
-I0511 11:50:55.665697  5581 caffe.cpp:501] detection_eval = 0.0449169
-I0511 11:50:55.665701  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.665705  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.665710  5581 caffe.cpp:501] detection_eval = 4.28024
-I0511 11:50:55.665717  5581 caffe.cpp:501] detection_eval = 10.3024
-I0511 11:50:55.665722  5581 caffe.cpp:501] detection_eval = 0.0445046
-I0511 11:50:55.665727  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665731  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665735  5581 caffe.cpp:501] detection_eval = 4.28629
-I0511 11:50:55.665740  5581 caffe.cpp:501] detection_eval = 10.3105
-I0511 11:50:55.665745  5581 caffe.cpp:501] detection_eval = 0.0444123
-I0511 11:50:55.665750  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665753  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.665758  5581 caffe.cpp:501] detection_eval = 4.29032
-I0511 11:50:55.665762  5581 caffe.cpp:501] detection_eval = 10.3145
-I0511 11:50:55.665767  5581 caffe.cpp:501] detection_eval = 0.0398316
-I0511 11:50:55.665771  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665776  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665781  5581 caffe.cpp:501] detection_eval = 4.29435
-I0511 11:50:55.665786  5581 caffe.cpp:501] detection_eval = 10.3387
-I0511 11:50:55.665789  5581 caffe.cpp:501] detection_eval = 0.0463916
-I0511 11:50:55.665794  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665798  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665803  5581 caffe.cpp:501] detection_eval = 4.29839
-I0511 11:50:55.665807  5581 caffe.cpp:501] detection_eval = 10.371
-I0511 11:50:55.665812  5581 caffe.cpp:501] detection_eval = 0.0514975
-I0511 11:50:55.665817  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.665822  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665825  5581 caffe.cpp:501] detection_eval = 4.3004
-I0511 11:50:55.665830  5581 caffe.cpp:501] detection_eval = 10.3851
-I0511 11:50:55.665834  5581 caffe.cpp:501] detection_eval = 0.0445005
-I0511 11:50:55.665839  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665843  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665848  5581 caffe.cpp:501] detection_eval = 4.30444
-I0511 11:50:55.665853  5581 caffe.cpp:501] detection_eval = 10.4173
-I0511 11:50:55.665858  5581 caffe.cpp:501] detection_eval = 0.0444614
-I0511 11:50:55.665861  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665866  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665870  5581 caffe.cpp:501] detection_eval = 4.30645
-I0511 11:50:55.665874  5581 caffe.cpp:501] detection_eval = 10.4556
-I0511 11:50:55.665879  5581 caffe.cpp:501] detection_eval = 0.0405224
-I0511 11:50:55.665884  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665889  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.665894  5581 caffe.cpp:501] detection_eval = 4.3125
-I0511 11:50:55.665897  5581 caffe.cpp:501] detection_eval = 10.4516
-I0511 11:50:55.665902  5581 caffe.cpp:501] detection_eval = 0.0424148
-I0511 11:50:55.665906  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665911  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.665915  5581 caffe.cpp:501] detection_eval = 4.31452
-I0511 11:50:55.665920  5581 caffe.cpp:501] detection_eval = 10.5101
-I0511 11:50:55.665925  5581 caffe.cpp:501] detection_eval = 0.0433033
-I0511 11:50:55.665930  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.665933  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.665938  5581 caffe.cpp:501] detection_eval = 4.31855
-I0511 11:50:55.665942  5581 caffe.cpp:501] detection_eval = 10.5202
-I0511 11:50:55.665946  5581 caffe.cpp:501] detection_eval = 0.0425584
-I0511 11:50:55.665951  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.665956  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.665961  5581 caffe.cpp:501] detection_eval = 4.32258
-I0511 11:50:55.665964  5581 caffe.cpp:501] detection_eval = 10.498
-I0511 11:50:55.665969  5581 caffe.cpp:501] detection_eval = 0.0391324
-I0511 11:50:55.665974  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.665978  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.665983  5581 caffe.cpp:501] detection_eval = 4.32661
-I0511 11:50:55.665990  5581 caffe.cpp:501] detection_eval = 10.5262
-I0511 11:50:55.665995  5581 caffe.cpp:501] detection_eval = 0.0420095
-I0511 11:50:55.665999  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666004  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666008  5581 caffe.cpp:501] detection_eval = 4.33669
-I0511 11:50:55.666013  5581 caffe.cpp:501] detection_eval = 10.4536
-I0511 11:50:55.666018  5581 caffe.cpp:501] detection_eval = 0.0434449
-I0511 11:50:55.666023  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666026  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666031  5581 caffe.cpp:501] detection_eval = 4.33669
-I0511 11:50:55.666035  5581 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:50:55.666040  5581 caffe.cpp:501] detection_eval = 0.0387064
-I0511 11:50:55.666044  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.666049  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.666054  5581 caffe.cpp:501] detection_eval = 4.34274
-I0511 11:50:55.666059  5581 caffe.cpp:501] detection_eval = 10.4819
-I0511 11:50:55.666062  5581 caffe.cpp:501] detection_eval = 0.0370433
-I0511 11:50:55.666067  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.666071  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.666076  5581 caffe.cpp:501] detection_eval = 4.34677
-I0511 11:50:55.666080  5581 caffe.cpp:501] detection_eval = 10.4859
-I0511 11:50:55.666085  5581 caffe.cpp:501] detection_eval = 0.0383295
-I0511 11:50:55.666090  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666093  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.666098  5581 caffe.cpp:501] detection_eval = 4.34879
-I0511 11:50:55.666102  5581 caffe.cpp:501] detection_eval = 10.5645
-I0511 11:50:55.666107  5581 caffe.cpp:501] detection_eval = 0.0456144
-I0511 11:50:55.666112  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666116  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666121  5581 caffe.cpp:501] detection_eval = 4.34879
-I0511 11:50:55.666126  5581 caffe.cpp:501] detection_eval = 10.6391
-I0511 11:50:55.666131  5581 caffe.cpp:501] detection_eval = 0.0450885
-I0511 11:50:55.666134  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666139  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666143  5581 caffe.cpp:501] detection_eval = 4.35081
-I0511 11:50:55.666148  5581 caffe.cpp:501] detection_eval = 10.7097
-I0511 11:50:55.666152  5581 caffe.cpp:501] detection_eval = 0.0424969
-I0511 11:50:55.666157  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666162  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.666167  5581 caffe.cpp:501] detection_eval = 4.35685
-I0511 11:50:55.666170  5581 caffe.cpp:501] detection_eval = 10.752
-I0511 11:50:55.666175  5581 caffe.cpp:501] detection_eval = 0.0436257
-I0511 11:50:55.666179  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666184  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666188  5581 caffe.cpp:501] detection_eval = 4.35887
-I0511 11:50:55.666193  5581 caffe.cpp:501] detection_eval = 10.7903
-I0511 11:50:55.666198  5581 caffe.cpp:501] detection_eval = 0.0431476
-I0511 11:50:55.666203  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666206  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.666211  5581 caffe.cpp:501] detection_eval = 4.3629
-I0511 11:50:55.666215  5581 caffe.cpp:501] detection_eval = 10.7843
-I0511 11:50:55.666220  5581 caffe.cpp:501] detection_eval = 0.0442008
-I0511 11:50:55.666224  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666229  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666232  5581 caffe.cpp:501] detection_eval = 4.36694
-I0511 11:50:55.666237  5581 caffe.cpp:501] detection_eval = 10.7782
-I0511 11:50:55.666241  5581 caffe.cpp:501] detection_eval = 0.0414062
-I0511 11:50:55.666246  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666250  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.666258  5581 caffe.cpp:501] detection_eval = 4.36895
-I0511 11:50:55.666262  5581 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:50:55.666267  5581 caffe.cpp:501] detection_eval = 0.041054
-I0511 11:50:55.666272  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.666276  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666281  5581 caffe.cpp:501] detection_eval = 4.37097
-I0511 11:50:55.666285  5581 caffe.cpp:501] detection_eval = 10.9012
-I0511 11:50:55.666290  5581 caffe.cpp:501] detection_eval = 0.0459491
-I0511 11:50:55.666296  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.666299  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.666303  5581 caffe.cpp:501] detection_eval = 4.37903
-I0511 11:50:55.666308  5581 caffe.cpp:501] detection_eval = 10.875
-I0511 11:50:55.666312  5581 caffe.cpp:501] detection_eval = 0.041678
-I0511 11:50:55.666317  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666321  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666326  5581 caffe.cpp:501] detection_eval = 4.38105
-I0511 11:50:55.666330  5581 caffe.cpp:501] detection_eval = 10.9294
-I0511 11:50:55.666335  5581 caffe.cpp:501] detection_eval = 0.0375598
-I0511 11:50:55.666339  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666344  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.666349  5581 caffe.cpp:501] detection_eval = 4.39113
-I0511 11:50:55.666353  5581 caffe.cpp:501] detection_eval = 10.8387
-I0511 11:50:55.666357  5581 caffe.cpp:501] detection_eval = 0.0412384
-I0511 11:50:55.666362  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666366  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666370  5581 caffe.cpp:501] detection_eval = 4.39919
-I0511 11:50:55.666375  5581 caffe.cpp:501] detection_eval = 10.7964
-I0511 11:50:55.666379  5581 caffe.cpp:501] detection_eval = 0.045887
-I0511 11:50:55.666384  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666388  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666393  5581 caffe.cpp:501] detection_eval = 4.40121
-I0511 11:50:55.666398  5581 caffe.cpp:501] detection_eval = 10.8327
-I0511 11:50:55.666402  5581 caffe.cpp:501] detection_eval = 0.0433971
-I0511 11:50:55.666407  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666411  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666416  5581 caffe.cpp:501] detection_eval = 4.40524
-I0511 11:50:55.666420  5581 caffe.cpp:501] detection_eval = 10.8992
-I0511 11:50:55.666425  5581 caffe.cpp:501] detection_eval = 0.0442976
-I0511 11:50:55.666429  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666435  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666438  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666443  5581 caffe.cpp:501] detection_eval = 10.9032
-I0511 11:50:55.666447  5581 caffe.cpp:501] detection_eval = 0.0453736
-I0511 11:50:55.666452  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.666456  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.666461  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666465  5581 caffe.cpp:501] detection_eval = 10.9698
-I0511 11:50:55.666471  5581 caffe.cpp:501] detection_eval = 0.0438347
-I0511 11:50:55.666474  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.666479  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.666483  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666488  5581 caffe.cpp:501] detection_eval = 11.0282
-I0511 11:50:55.666492  5581 caffe.cpp:501] detection_eval = 0.0439485
-I0511 11:50:55.666497  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666501  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666507  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666510  5581 caffe.cpp:501] detection_eval = 11.0887
-I0511 11:50:55.666515  5581 caffe.cpp:501] detection_eval = 0.0499174
-I0511 11:50:55.666519  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.666527  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.666532  5581 caffe.cpp:501] detection_eval = 4.41129
-I0511 11:50:55.666537  5581 caffe.cpp:501] detection_eval = 11.1593
-I0511 11:50:55.666541  5581 caffe.cpp:501] detection_eval = 0.0429797
-I0511 11:50:55.666545  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666550  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666555  5581 caffe.cpp:501] detection_eval = 4.41331
-I0511 11:50:55.666559  5581 caffe.cpp:501] detection_eval = 11.2016
-I0511 11:50:55.666564  5581 caffe.cpp:501] detection_eval = 0.0434779
-I0511 11:50:55.666568  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666574  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666577  5581 caffe.cpp:501] detection_eval = 4.41734
-I0511 11:50:55.666582  5581 caffe.cpp:501] detection_eval = 11.1935
-I0511 11:50:55.666586  5581 caffe.cpp:501] detection_eval = 0.0429046
-I0511 11:50:55.666591  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666595  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666600  5581 caffe.cpp:501] detection_eval = 4.41935
-I0511 11:50:55.666604  5581 caffe.cpp:501] detection_eval = 11.2137
-I0511 11:50:55.666610  5581 caffe.cpp:501] detection_eval = 0.0456519
-I0511 11:50:55.666613  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666618  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666622  5581 caffe.cpp:501] detection_eval = 4.42137
-I0511 11:50:55.666626  5581 caffe.cpp:501] detection_eval = 11.2782
-I0511 11:50:55.666631  5581 caffe.cpp:501] detection_eval = 0.040348
-I0511 11:50:55.666635  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666640  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666645  5581 caffe.cpp:501] detection_eval = 4.42339
-I0511 11:50:55.666649  5581 caffe.cpp:501] detection_eval = 11.3306
-I0511 11:50:55.666653  5581 caffe.cpp:501] detection_eval = 0.0440193
-I0511 11:50:55.666658  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.666662  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.666667  5581 caffe.cpp:501] detection_eval = 4.42339
-I0511 11:50:55.666671  5581 caffe.cpp:501] detection_eval = 11.4153
-I0511 11:50:55.666676  5581 caffe.cpp:501] detection_eval = 0.0462135
-I0511 11:50:55.666680  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.666685  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.666689  5581 caffe.cpp:501] detection_eval = 4.4254
-I0511 11:50:55.666694  5581 caffe.cpp:501] detection_eval = 11.4274
-I0511 11:50:55.666698  5581 caffe.cpp:501] detection_eval = 0.0443372
-I0511 11:50:55.666703  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.666707  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666712  5581 caffe.cpp:501] detection_eval = 4.43347
-I0511 11:50:55.666716  5581 caffe.cpp:501] detection_eval = 11.3327
-I0511 11:50:55.666721  5581 caffe.cpp:501] detection_eval = 0.0398814
-I0511 11:50:55.666725  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666730  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666734  5581 caffe.cpp:501] detection_eval = 4.43548
-I0511 11:50:55.666739  5581 caffe.cpp:501] detection_eval = 11.3508
-I0511 11:50:55.666743  5581 caffe.cpp:501] detection_eval = 0.0379586
-I0511 11:50:55.666749  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.666752  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666757  5581 caffe.cpp:501] detection_eval = 4.4375
-I0511 11:50:55.666761  5581 caffe.cpp:501] detection_eval = 11.375
-I0511 11:50:55.666766  5581 caffe.cpp:501] detection_eval = 0.0398871
-I0511 11:50:55.666770  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666775  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666779  5581 caffe.cpp:501] detection_eval = 4.44355
-I0511 11:50:55.666785  5581 caffe.cpp:501] detection_eval = 11.3407
-I0511 11:50:55.666788  5581 caffe.cpp:501] detection_eval = 0.0427237
-I0511 11:50:55.666793  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666800  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666805  5581 caffe.cpp:501] detection_eval = 4.44556
-I0511 11:50:55.666810  5581 caffe.cpp:501] detection_eval = 11.371
-I0511 11:50:55.666815  5581 caffe.cpp:501] detection_eval = 0.0427771
-I0511 11:50:55.666820  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.666823  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.666827  5581 caffe.cpp:501] detection_eval = 4.4496
-I0511 11:50:55.666832  5581 caffe.cpp:501] detection_eval = 11.3508
-I0511 11:50:55.666837  5581 caffe.cpp:501] detection_eval = 0.040328
-I0511 11:50:55.666841  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666846  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.666851  5581 caffe.cpp:501] detection_eval = 4.45161
-I0511 11:50:55.666854  5581 caffe.cpp:501] detection_eval = 11.3609
-I0511 11:50:55.666859  5581 caffe.cpp:501] detection_eval = 0.0401247
-I0511 11:50:55.666864  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666868  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.666873  5581 caffe.cpp:501] detection_eval = 4.45565
-I0511 11:50:55.666877  5581 caffe.cpp:501] detection_eval = 11.4052
-I0511 11:50:55.666882  5581 caffe.cpp:501] detection_eval = 0.0399035
-I0511 11:50:55.666887  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.666891  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.666895  5581 caffe.cpp:501] detection_eval = 4.45968
-I0511 11:50:55.666899  5581 caffe.cpp:501] detection_eval = 11.496
-I0511 11:50:55.666904  5581 caffe.cpp:501] detection_eval = 0.0506911
-I0511 11:50:55.666908  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.666913  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.666918  5581 caffe.cpp:501] detection_eval = 4.46371
-I0511 11:50:55.666921  5581 caffe.cpp:501] detection_eval = 11.5222
-I0511 11:50:55.666926  5581 caffe.cpp:501] detection_eval = 0.0458513
-I0511 11:50:55.666931  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.666935  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.666939  5581 caffe.cpp:501] detection_eval = 4.46371
-I0511 11:50:55.666944  5581 caffe.cpp:501] detection_eval = 11.6129
-I0511 11:50:55.666949  5581 caffe.cpp:501] detection_eval = 0.0485337
-I0511 11:50:55.666954  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.666959  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.666962  5581 caffe.cpp:501] detection_eval = 4.46371
-I0511 11:50:55.666966  5581 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:50:55.666971  5581 caffe.cpp:501] detection_eval = 0.0491915
-I0511 11:50:55.666975  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.666980  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.666985  5581 caffe.cpp:501] detection_eval = 4.46774
-I0511 11:50:55.666990  5581 caffe.cpp:501] detection_eval = 11.7298
-I0511 11:50:55.666995  5581 caffe.cpp:501] detection_eval = 0.0518123
-I0511 11:50:55.666998  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.667002  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.667007  5581 caffe.cpp:501] detection_eval = 4.47379
-I0511 11:50:55.667011  5581 caffe.cpp:501] detection_eval = 11.6935
-I0511 11:50:55.667016  5581 caffe.cpp:501] detection_eval = 0.0429515
-I0511 11:50:55.667021  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667026  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667029  5581 caffe.cpp:501] detection_eval = 4.47581
-I0511 11:50:55.667034  5581 caffe.cpp:501] detection_eval = 11.7238
-I0511 11:50:55.667039  5581 caffe.cpp:501] detection_eval = 0.0408649
-I0511 11:50:55.667043  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.667047  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667052  5581 caffe.cpp:501] detection_eval = 4.47984
-I0511 11:50:55.667057  5581 caffe.cpp:501] detection_eval = 11.7419
-I0511 11:50:55.667062  5581 caffe.cpp:501] detection_eval = 0.0378178
-I0511 11:50:55.667068  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667073  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667078  5581 caffe.cpp:501] detection_eval = 4.48185
-I0511 11:50:55.667083  5581 caffe.cpp:501] detection_eval = 11.7722
-I0511 11:50:55.667088  5581 caffe.cpp:501] detection_eval = 0.0400242
-I0511 11:50:55.667093  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667096  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667101  5581 caffe.cpp:501] detection_eval = 4.48589
-I0511 11:50:55.667105  5581 caffe.cpp:501] detection_eval = 11.7903
-I0511 11:50:55.667110  5581 caffe.cpp:501] detection_eval = 0.0403816
-I0511 11:50:55.667115  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667120  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.667124  5581 caffe.cpp:501] detection_eval = 4.49194
-I0511 11:50:55.667129  5581 caffe.cpp:501] detection_eval = 11.7621
-I0511 11:50:55.667134  5581 caffe.cpp:501] detection_eval = 0.0395134
-I0511 11:50:55.667138  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.667142  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667147  5581 caffe.cpp:501] detection_eval = 4.49597
-I0511 11:50:55.667151  5581 caffe.cpp:501] detection_eval = 11.752
-I0511 11:50:55.667156  5581 caffe.cpp:501] detection_eval = 0.0386682
-I0511 11:50:55.667160  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667165  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667170  5581 caffe.cpp:501] detection_eval = 4.49798
-I0511 11:50:55.667174  5581 caffe.cpp:501] detection_eval = 11.8206
-I0511 11:50:55.667178  5581 caffe.cpp:501] detection_eval = 0.0428092
-I0511 11:50:55.667183  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667188  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667192  5581 caffe.cpp:501] detection_eval = 4.5
-I0511 11:50:55.667196  5581 caffe.cpp:501] detection_eval = 11.8327
-I0511 11:50:55.667201  5581 caffe.cpp:501] detection_eval = 0.0396953
-I0511 11:50:55.667207  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667210  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667214  5581 caffe.cpp:501] detection_eval = 4.50202
-I0511 11:50:55.667219  5581 caffe.cpp:501] detection_eval = 11.8629
-I0511 11:50:55.667224  5581 caffe.cpp:501] detection_eval = 0.0432461
-I0511 11:50:55.667228  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667233  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667237  5581 caffe.cpp:501] detection_eval = 4.50605
-I0511 11:50:55.667243  5581 caffe.cpp:501] detection_eval = 11.8851
-I0511 11:50:55.667246  5581 caffe.cpp:501] detection_eval = 0.0406408
-I0511 11:50:55.667251  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667256  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667260  5581 caffe.cpp:501] detection_eval = 4.51008
-I0511 11:50:55.667265  5581 caffe.cpp:501] detection_eval = 11.9234
-I0511 11:50:55.667269  5581 caffe.cpp:501] detection_eval = 0.04964
-I0511 11:50:55.667274  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.667279  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.667284  5581 caffe.cpp:501] detection_eval = 4.51008
-I0511 11:50:55.667287  5581 caffe.cpp:501] detection_eval = 11.9879
-I0511 11:50:55.667292  5581 caffe.cpp:501] detection_eval = 0.0440365
-I0511 11:50:55.667297  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667301  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667304  5581 caffe.cpp:501] detection_eval = 4.51613
-I0511 11:50:55.667306  5581 caffe.cpp:501] detection_eval = 11.9516
-I0511 11:50:55.667309  5581 caffe.cpp:501] detection_eval = 0.0413376
-I0511 11:50:55.667311  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667315  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667316  5581 caffe.cpp:501] detection_eval = 4.51613
-I0511 11:50:55.667318  5581 caffe.cpp:501] detection_eval = 12.0524
-I0511 11:50:55.667323  5581 caffe.cpp:501] detection_eval = 0.0399847
-I0511 11:50:55.667326  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.667328  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.667331  5581 caffe.cpp:501] detection_eval = 4.52016
-I0511 11:50:55.667333  5581 caffe.cpp:501] detection_eval = 12.0645
-I0511 11:50:55.667335  5581 caffe.cpp:501] detection_eval = 0.042322
-I0511 11:50:55.667337  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.667340  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.667342  5581 caffe.cpp:501] detection_eval = 4.52016
-I0511 11:50:55.667345  5581 caffe.cpp:501] detection_eval = 12.125
-I0511 11:50:55.667346  5581 caffe.cpp:501] detection_eval = 0.0411623
-I0511 11:50:55.667349  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667351  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667353  5581 caffe.cpp:501] detection_eval = 4.52419
-I0511 11:50:55.667356  5581 caffe.cpp:501] detection_eval = 12.1653
-I0511 11:50:55.667361  5581 caffe.cpp:501] detection_eval = 0.0385926
-I0511 11:50:55.667364  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667369  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.667374  5581 caffe.cpp:501] detection_eval = 4.52419
-I0511 11:50:55.667378  5581 caffe.cpp:501] detection_eval = 12.2238
-I0511 11:50:55.667383  5581 caffe.cpp:501] detection_eval = 0.0362826
-I0511 11:50:55.667387  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.667392  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.667397  5581 caffe.cpp:501] detection_eval = 4.52823
-I0511 11:50:55.667400  5581 caffe.cpp:501] detection_eval = 12.2278
-I0511 11:50:55.667405  5581 caffe.cpp:501] detection_eval = 0.0397036
-I0511 11:50:55.667410  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667414  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667418  5581 caffe.cpp:501] detection_eval = 4.53226
-I0511 11:50:55.667423  5581 caffe.cpp:501] detection_eval = 12.2359
-I0511 11:50:55.667428  5581 caffe.cpp:501] detection_eval = 0.0423725
-I0511 11:50:55.667433  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667436  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667441  5581 caffe.cpp:501] detection_eval = 4.53226
-I0511 11:50:55.667445  5581 caffe.cpp:501] detection_eval = 12.2823
-I0511 11:50:55.667450  5581 caffe.cpp:501] detection_eval = 0.040986
-I0511 11:50:55.667455  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667459  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667464  5581 caffe.cpp:501] detection_eval = 4.53427
-I0511 11:50:55.667469  5581 caffe.cpp:501] detection_eval = 12.2883
-I0511 11:50:55.667472  5581 caffe.cpp:501] detection_eval = 0.0366525
-I0511 11:50:55.667477  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667481  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.667486  5581 caffe.cpp:501] detection_eval = 4.54032
-I0511 11:50:55.667490  5581 caffe.cpp:501] detection_eval = 12.2601
-I0511 11:50:55.667495  5581 caffe.cpp:501] detection_eval = 0.0393226
-I0511 11:50:55.667500  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667505  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667508  5581 caffe.cpp:501] detection_eval = 4.54839
-I0511 11:50:55.667513  5581 caffe.cpp:501] detection_eval = 12.1754
-I0511 11:50:55.667517  5581 caffe.cpp:501] detection_eval = 0.0431251
-I0511 11:50:55.667522  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667526  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667531  5581 caffe.cpp:501] detection_eval = 4.55444
-I0511 11:50:55.667536  5581 caffe.cpp:501] detection_eval = 12.1371
-I0511 11:50:55.667541  5581 caffe.cpp:501] detection_eval = 0.0422945
-I0511 11:50:55.667544  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.667549  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667553  5581 caffe.cpp:501] detection_eval = 4.56452
-I0511 11:50:55.667557  5581 caffe.cpp:501] detection_eval = 12.127
-I0511 11:50:55.667565  5581 caffe.cpp:501] detection_eval = 0.0491096
-I0511 11:50:55.667570  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.667575  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.667579  5581 caffe.cpp:501] detection_eval = 4.57258
-I0511 11:50:55.667583  5581 caffe.cpp:501] detection_eval = 12.0565
-I0511 11:50:55.667588  5581 caffe.cpp:501] detection_eval = 0.0461282
-I0511 11:50:55.667593  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.667598  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667601  5581 caffe.cpp:501] detection_eval = 4.57258
-I0511 11:50:55.667606  5581 caffe.cpp:501] detection_eval = 12.131
-I0511 11:50:55.667610  5581 caffe.cpp:501] detection_eval = 0.044421
-I0511 11:50:55.667615  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667620  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.667624  5581 caffe.cpp:501] detection_eval = 4.5746
-I0511 11:50:55.667629  5581 caffe.cpp:501] detection_eval = 12.129
-I0511 11:50:55.667634  5581 caffe.cpp:501] detection_eval = 0.0402017
-I0511 11:50:55.667639  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667642  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.667647  5581 caffe.cpp:501] detection_eval = 4.5746
-I0511 11:50:55.667651  5581 caffe.cpp:501] detection_eval = 12.1915
-I0511 11:50:55.667656  5581 caffe.cpp:501] detection_eval = 0.0372778
-I0511 11:50:55.667660  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667665  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667670  5581 caffe.cpp:501] detection_eval = 4.57661
-I0511 11:50:55.667675  5581 caffe.cpp:501] detection_eval = 12.2359
-I0511 11:50:55.667678  5581 caffe.cpp:501] detection_eval = 0.0438748
-I0511 11:50:55.667683  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.667687  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667692  5581 caffe.cpp:501] detection_eval = 4.57661
-I0511 11:50:55.667696  5581 caffe.cpp:501] detection_eval = 12.3044
-I0511 11:50:55.667701  5581 caffe.cpp:501] detection_eval = 0.0404307
-I0511 11:50:55.667706  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.667711  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667716  5581 caffe.cpp:501] detection_eval = 4.57863
-I0511 11:50:55.667719  5581 caffe.cpp:501] detection_eval = 12.3024
-I0511 11:50:55.667724  5581 caffe.cpp:501] detection_eval = 0.0437116
-I0511 11:50:55.667728  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667733  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667737  5581 caffe.cpp:501] detection_eval = 4.58065
-I0511 11:50:55.667742  5581 caffe.cpp:501] detection_eval = 12.3387
-I0511 11:50:55.667747  5581 caffe.cpp:501] detection_eval = 0.0399681
-I0511 11:50:55.667752  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667755  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.667760  5581 caffe.cpp:501] detection_eval = 4.58871
-I0511 11:50:55.667764  5581 caffe.cpp:501] detection_eval = 12.2581
-I0511 11:50:55.667769  5581 caffe.cpp:501] detection_eval = 0.0360596
-I0511 11:50:55.667773  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667778  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667783  5581 caffe.cpp:501] detection_eval = 4.58871
-I0511 11:50:55.667788  5581 caffe.cpp:501] detection_eval = 12.3125
-I0511 11:50:55.667791  5581 caffe.cpp:501] detection_eval = 0.0368753
-I0511 11:50:55.667795  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667798  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667799  5581 caffe.cpp:501] detection_eval = 4.59073
-I0511 11:50:55.667803  5581 caffe.cpp:501] detection_eval = 12.369
-I0511 11:50:55.667804  5581 caffe.cpp:501] detection_eval = 0.0376381
-I0511 11:50:55.667807  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667809  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.667811  5581 caffe.cpp:501] detection_eval = 4.59677
-I0511 11:50:55.667817  5581 caffe.cpp:501] detection_eval = 12.373
-I0511 11:50:55.667820  5581 caffe.cpp:501] detection_eval = 0.0410415
-I0511 11:50:55.667822  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.667824  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.667826  5581 caffe.cpp:501] detection_eval = 4.60081
-I0511 11:50:55.667829  5581 caffe.cpp:501] detection_eval = 12.4234
-I0511 11:50:55.667831  5581 caffe.cpp:501] detection_eval = 0.0435586
-I0511 11:50:55.667834  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.667836  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667838  5581 caffe.cpp:501] detection_eval = 4.60081
-I0511 11:50:55.667840  5581 caffe.cpp:501] detection_eval = 12.4819
-I0511 11:50:55.667842  5581 caffe.cpp:501] detection_eval = 0.0419101
-I0511 11:50:55.667845  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667847  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667850  5581 caffe.cpp:501] detection_eval = 4.60081
-I0511 11:50:55.667851  5581 caffe.cpp:501] detection_eval = 12.5181
-I0511 11:50:55.667855  5581 caffe.cpp:501] detection_eval = 0.0393905
-I0511 11:50:55.667856  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667858  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.667860  5581 caffe.cpp:501] detection_eval = 4.60282
-I0511 11:50:55.667862  5581 caffe.cpp:501] detection_eval = 12.5444
-I0511 11:50:55.667865  5581 caffe.cpp:501] detection_eval = 0.0369975
-I0511 11:50:55.667867  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667870  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667871  5581 caffe.cpp:501] detection_eval = 4.60685
-I0511 11:50:55.667874  5581 caffe.cpp:501] detection_eval = 12.5343
-I0511 11:50:55.667876  5581 caffe.cpp:501] detection_eval = 0.0365329
-I0511 11:50:55.667878  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667881  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667883  5581 caffe.cpp:501] detection_eval = 4.61089
-I0511 11:50:55.667886  5581 caffe.cpp:501] detection_eval = 12.5484
-I0511 11:50:55.667887  5581 caffe.cpp:501] detection_eval = 0.0391375
-I0511 11:50:55.667889  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667891  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.667894  5581 caffe.cpp:501] detection_eval = 4.6129
-I0511 11:50:55.667896  5581 caffe.cpp:501] detection_eval = 12.6008
-I0511 11:50:55.667898  5581 caffe.cpp:501] detection_eval = 0.0370847
-I0511 11:50:55.667901  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667903  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667906  5581 caffe.cpp:501] detection_eval = 4.61694
-I0511 11:50:55.667907  5581 caffe.cpp:501] detection_eval = 12.6089
-I0511 11:50:55.667909  5581 caffe.cpp:501] detection_eval = 0.0369866
-I0511 11:50:55.667912  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667914  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667917  5581 caffe.cpp:501] detection_eval = 4.61895
-I0511 11:50:55.667918  5581 caffe.cpp:501] detection_eval = 12.6351
-I0511 11:50:55.667920  5581 caffe.cpp:501] detection_eval = 0.0427287
-I0511 11:50:55.667922  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.667925  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.667927  5581 caffe.cpp:501] detection_eval = 4.625
-I0511 11:50:55.667929  5581 caffe.cpp:501] detection_eval = 12.5988
-I0511 11:50:55.667934  5581 caffe.cpp:501] detection_eval = 0.0338396
-I0511 11:50:55.667937  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.667939  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.667942  5581 caffe.cpp:501] detection_eval = 4.625
-I0511 11:50:55.667943  5581 caffe.cpp:501] detection_eval = 12.6754
-I0511 11:50:55.667945  5581 caffe.cpp:501] detection_eval = 0.0368577
-I0511 11:50:55.667948  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667950  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.667953  5581 caffe.cpp:501] detection_eval = 4.62903
-I0511 11:50:55.667958  5581 caffe.cpp:501] detection_eval = 12.6371
-I0511 11:50:55.667959  5581 caffe.cpp:501] detection_eval = 0.0340815
-I0511 11:50:55.667963  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.667964  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.667966  5581 caffe.cpp:501] detection_eval = 4.63306
-I0511 11:50:55.667968  5581 caffe.cpp:501] detection_eval = 12.6069
-I0511 11:50:55.667970  5581 caffe.cpp:501] detection_eval = 0.0356699
-I0511 11:50:55.667973  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667975  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667978  5581 caffe.cpp:501] detection_eval = 4.63306
-I0511 11:50:55.667979  5581 caffe.cpp:501] detection_eval = 12.6653
-I0511 11:50:55.667981  5581 caffe.cpp:501] detection_eval = 0.0346759
-I0511 11:50:55.667984  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.667986  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.667989  5581 caffe.cpp:501] detection_eval = 4.63508
-I0511 11:50:55.667990  5581 caffe.cpp:501] detection_eval = 12.6915
-I0511 11:50:55.667994  5581 caffe.cpp:501] detection_eval = 0.0398253
-I0511 11:50:55.667995  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.667997  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.667999  5581 caffe.cpp:501] detection_eval = 4.6371
-I0511 11:50:55.668001  5581 caffe.cpp:501] detection_eval = 12.7258
-I0511 11:50:55.668004  5581 caffe.cpp:501] detection_eval = 0.0422131
-I0511 11:50:55.668006  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668009  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668010  5581 caffe.cpp:501] detection_eval = 4.64113
-I0511 11:50:55.668012  5581 caffe.cpp:501] detection_eval = 12.7117
-I0511 11:50:55.668015  5581 caffe.cpp:501] detection_eval = 0.0367614
-I0511 11:50:55.668017  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668020  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.668021  5581 caffe.cpp:501] detection_eval = 4.64113
-I0511 11:50:55.668023  5581 caffe.cpp:501] detection_eval = 12.748
-I0511 11:50:55.668026  5581 caffe.cpp:501] detection_eval = 0.0399707
-I0511 11:50:55.668028  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668030  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668032  5581 caffe.cpp:501] detection_eval = 4.64315
-I0511 11:50:55.668035  5581 caffe.cpp:501] detection_eval = 12.7661
-I0511 11:50:55.668037  5581 caffe.cpp:501] detection_eval = 0.0411466
-I0511 11:50:55.668040  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668041  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668043  5581 caffe.cpp:501] detection_eval = 4.64718
-I0511 11:50:55.668045  5581 caffe.cpp:501] detection_eval = 12.7742
-I0511 11:50:55.668048  5581 caffe.cpp:501] detection_eval = 0.0421279
-I0511 11:50:55.668051  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668052  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668054  5581 caffe.cpp:501] detection_eval = 4.65121
-I0511 11:50:55.668056  5581 caffe.cpp:501] detection_eval = 12.7923
-I0511 11:50:55.668059  5581 caffe.cpp:501] detection_eval = 0.0409486
-I0511 11:50:55.668061  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668063  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668066  5581 caffe.cpp:501] detection_eval = 4.65927
-I0511 11:50:55.668068  5581 caffe.cpp:501] detection_eval = 12.7399
-I0511 11:50:55.668071  5581 caffe.cpp:501] detection_eval = 0.0392662
-I0511 11:50:55.668072  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668076  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668077  5581 caffe.cpp:501] detection_eval = 4.66532
-I0511 11:50:55.668079  5581 caffe.cpp:501] detection_eval = 12.7238
-I0511 11:50:55.668081  5581 caffe.cpp:501] detection_eval = 0.0405585
-I0511 11:50:55.668083  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668087  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668090  5581 caffe.cpp:501] detection_eval = 4.66935
-I0511 11:50:55.668092  5581 caffe.cpp:501] detection_eval = 12.7278
-I0511 11:50:55.668095  5581 caffe.cpp:501] detection_eval = 0.0404869
-I0511 11:50:55.668097  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668099  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668102  5581 caffe.cpp:501] detection_eval = 4.67137
-I0511 11:50:55.668103  5581 caffe.cpp:501] detection_eval = 12.7964
-I0511 11:50:55.668107  5581 caffe.cpp:501] detection_eval = 0.0449684
-I0511 11:50:55.668108  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668110  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668112  5581 caffe.cpp:501] detection_eval = 4.67339
-I0511 11:50:55.668114  5581 caffe.cpp:501] detection_eval = 12.8347
-I0511 11:50:55.668118  5581 caffe.cpp:501] detection_eval = 0.0470513
-I0511 11:50:55.668119  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668121  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668123  5581 caffe.cpp:501] detection_eval = 4.67339
-I0511 11:50:55.668125  5581 caffe.cpp:501] detection_eval = 12.8992
-I0511 11:50:55.668128  5581 caffe.cpp:501] detection_eval = 0.0420022
-I0511 11:50:55.668130  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668133  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668135  5581 caffe.cpp:501] detection_eval = 4.67944
-I0511 11:50:55.668138  5581 caffe.cpp:501] detection_eval = 12.9435
-I0511 11:50:55.668140  5581 caffe.cpp:501] detection_eval = 0.0400056
-I0511 11:50:55.668144  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668148  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668149  5581 caffe.cpp:501] detection_eval = 4.68145
-I0511 11:50:55.668151  5581 caffe.cpp:501] detection_eval = 13
-I0511 11:50:55.668154  5581 caffe.cpp:501] detection_eval = 0.0423659
-I0511 11:50:55.668156  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668159  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668161  5581 caffe.cpp:501] detection_eval = 4.68347
-I0511 11:50:55.668164  5581 caffe.cpp:501] detection_eval = 13.1532
-I0511 11:50:55.668165  5581 caffe.cpp:501] detection_eval = 0.0435836
-I0511 11:50:55.668167  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668169  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668172  5581 caffe.cpp:501] detection_eval = 4.6875
-I0511 11:50:55.668174  5581 caffe.cpp:501] detection_eval = 13.2419
-I0511 11:50:55.668176  5581 caffe.cpp:501] detection_eval = 0.0409402
-I0511 11:50:55.668179  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668181  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668184  5581 caffe.cpp:501] detection_eval = 4.69153
-I0511 11:50:55.668185  5581 caffe.cpp:501] detection_eval = 13.377
-I0511 11:50:55.668187  5581 caffe.cpp:501] detection_eval = 0.0397732
-I0511 11:50:55.668190  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668192  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668195  5581 caffe.cpp:501] detection_eval = 4.69758
-I0511 11:50:55.668197  5581 caffe.cpp:501] detection_eval = 13.6149
-I0511 11:50:55.668200  5581 caffe.cpp:501] detection_eval = 0.0355242
-I0511 11:50:55.668201  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668203  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.668206  5581 caffe.cpp:501] detection_eval = 5.13306
-I0511 11:50:55.668208  5581 caffe.cpp:501] detection_eval = 7.21774
-I0511 11:50:55.668210  5581 caffe.cpp:501] detection_eval = 0.083593
-I0511 11:50:55.668212  5581 caffe.cpp:501] detection_eval = 0.046371
-I0511 11:50:55.668215  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.668216  5581 caffe.cpp:501] detection_eval = 5.13508
-I0511 11:50:55.668220  5581 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:50:55.668221  5581 caffe.cpp:501] detection_eval = 0.0686604
-I0511 11:50:55.668223  5581 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:50:55.668228  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.668231  5581 caffe.cpp:501] detection_eval = 5.13508
-I0511 11:50:55.668232  5581 caffe.cpp:501] detection_eval = 7.62702
-I0511 11:50:55.668236  5581 caffe.cpp:501] detection_eval = 0.0638157
-I0511 11:50:55.668237  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.668239  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668241  5581 caffe.cpp:501] detection_eval = 5.13508
-I0511 11:50:55.668243  5581 caffe.cpp:501] detection_eval = 7.75403
-I0511 11:50:55.668246  5581 caffe.cpp:501] detection_eval = 0.0532077
-I0511 11:50:55.668248  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.668251  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.668253  5581 caffe.cpp:501] detection_eval = 5.14113
-I0511 11:50:55.668256  5581 caffe.cpp:501] detection_eval = 7.79032
-I0511 11:50:55.668257  5581 caffe.cpp:501] detection_eval = 0.0506467
-I0511 11:50:55.668259  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.668262  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668264  5581 caffe.cpp:501] detection_eval = 5.14315
-I0511 11:50:55.668267  5581 caffe.cpp:501] detection_eval = 7.85081
-I0511 11:50:55.668268  5581 caffe.cpp:501] detection_eval = 0.0490163
-I0511 11:50:55.668270  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668272  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668275  5581 caffe.cpp:501] detection_eval = 5.14516
-I0511 11:50:55.668277  5581 caffe.cpp:501] detection_eval = 7.88508
-I0511 11:50:55.668279  5581 caffe.cpp:501] detection_eval = 0.0515722
-I0511 11:50:55.668282  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.668283  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668285  5581 caffe.cpp:501] detection_eval = 5.14718
-I0511 11:50:55.668288  5581 caffe.cpp:501] detection_eval = 7.94355
-I0511 11:50:55.668290  5581 caffe.cpp:501] detection_eval = 0.0459141
-I0511 11:50:55.668292  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668294  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668296  5581 caffe.cpp:501] detection_eval = 5.14919
-I0511 11:50:55.668298  5581 caffe.cpp:501] detection_eval = 7.99194
-I0511 11:50:55.668301  5581 caffe.cpp:501] detection_eval = 0.0476944
-I0511 11:50:55.668303  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.668305  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.668308  5581 caffe.cpp:501] detection_eval = 5.15524
-I0511 11:50:55.668309  5581 caffe.cpp:501] detection_eval = 8.01613
-I0511 11:50:55.668313  5581 caffe.cpp:501] detection_eval = 0.0487789
-I0511 11:50:55.668314  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668316  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668318  5581 caffe.cpp:501] detection_eval = 5.15726
-I0511 11:50:55.668320  5581 caffe.cpp:501] detection_eval = 8.06452
-I0511 11:50:55.668323  5581 caffe.cpp:501] detection_eval = 0.0494443
-I0511 11:50:55.668325  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668328  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668329  5581 caffe.cpp:501] detection_eval = 5.15726
-I0511 11:50:55.668331  5581 caffe.cpp:501] detection_eval = 8.15726
-I0511 11:50:55.668334  5581 caffe.cpp:501] detection_eval = 0.0519537
-I0511 11:50:55.668336  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.668339  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.668340  5581 caffe.cpp:501] detection_eval = 5.15927
-I0511 11:50:55.668342  5581 caffe.cpp:501] detection_eval = 8.17339
-I0511 11:50:55.668345  5581 caffe.cpp:501] detection_eval = 0.0487953
-I0511 11:50:55.668347  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668349  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668351  5581 caffe.cpp:501] detection_eval = 5.16331
-I0511 11:50:55.668354  5581 caffe.cpp:501] detection_eval = 8.18145
-I0511 11:50:55.668355  5581 caffe.cpp:501] detection_eval = 0.0461852
-I0511 11:50:55.668359  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668362  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668365  5581 caffe.cpp:501] detection_eval = 5.16532
-I0511 11:50:55.668367  5581 caffe.cpp:501] detection_eval = 8.23589
-I0511 11:50:55.668370  5581 caffe.cpp:501] detection_eval = 0.0456467
-I0511 11:50:55.668371  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668373  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668376  5581 caffe.cpp:501] detection_eval = 5.16734
-I0511 11:50:55.668378  5581 caffe.cpp:501] detection_eval = 8.28226
-I0511 11:50:55.668380  5581 caffe.cpp:501] detection_eval = 0.0411408
-I0511 11:50:55.668383  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.668385  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.668387  5581 caffe.cpp:501] detection_eval = 5.17137
-I0511 11:50:55.668390  5581 caffe.cpp:501] detection_eval = 8.31855
-I0511 11:50:55.668392  5581 caffe.cpp:501] detection_eval = 0.0467666
-I0511 11:50:55.668395  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668396  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668400  5581 caffe.cpp:501] detection_eval = 5.17137
-I0511 11:50:55.668401  5581 caffe.cpp:501] detection_eval = 8.4254
-I0511 11:50:55.668403  5581 caffe.cpp:501] detection_eval = 0.0439995
-I0511 11:50:55.668406  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668408  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668411  5581 caffe.cpp:501] detection_eval = 5.1754
-I0511 11:50:55.668412  5581 caffe.cpp:501] detection_eval = 8.45161
-I0511 11:50:55.668414  5581 caffe.cpp:501] detection_eval = 0.0518023
-I0511 11:50:55.668417  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668419  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668421  5581 caffe.cpp:501] detection_eval = 5.17742
-I0511 11:50:55.668423  5581 caffe.cpp:501] detection_eval = 8.50605
-I0511 11:50:55.668426  5581 caffe.cpp:501] detection_eval = 0.0514247
-I0511 11:50:55.668427  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668431  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.668432  5581 caffe.cpp:501] detection_eval = 5.18145
-I0511 11:50:55.668434  5581 caffe.cpp:501] detection_eval = 8.47984
-I0511 11:50:55.668437  5581 caffe.cpp:501] detection_eval = 0.0472633
-I0511 11:50:55.668439  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668442  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668443  5581 caffe.cpp:501] detection_eval = 5.18145
-I0511 11:50:55.668445  5581 caffe.cpp:501] detection_eval = 8.53629
-I0511 11:50:55.668447  5581 caffe.cpp:501] detection_eval = 0.0406202
-I0511 11:50:55.668450  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.668452  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.668454  5581 caffe.cpp:501] detection_eval = 5.18347
-I0511 11:50:55.668457  5581 caffe.cpp:501] detection_eval = 8.61895
-I0511 11:50:55.668458  5581 caffe.cpp:501] detection_eval = 0.0442999
-I0511 11:50:55.668460  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668463  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668465  5581 caffe.cpp:501] detection_eval = 5.19758
-I0511 11:50:55.668468  5581 caffe.cpp:501] detection_eval = 8.47581
-I0511 11:50:55.668470  5581 caffe.cpp:501] detection_eval = 0.0477267
-I0511 11:50:55.668473  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668474  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668478  5581 caffe.cpp:501] detection_eval = 5.20363
-I0511 11:50:55.668479  5581 caffe.cpp:501] detection_eval = 8.42944
-I0511 11:50:55.668481  5581 caffe.cpp:501] detection_eval = 0.045115
-I0511 11:50:55.668483  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668485  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668488  5581 caffe.cpp:501] detection_eval = 5.20565
-I0511 11:50:55.668490  5581 caffe.cpp:501] detection_eval = 8.51008
-I0511 11:50:55.668493  5581 caffe.cpp:501] detection_eval = 0.044696
-I0511 11:50:55.668498  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668499  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668501  5581 caffe.cpp:501] detection_eval = 5.21169
-I0511 11:50:55.668503  5581 caffe.cpp:501] detection_eval = 8.48185
-I0511 11:50:55.668506  5581 caffe.cpp:501] detection_eval = 0.0442546
-I0511 11:50:55.668509  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668510  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668512  5581 caffe.cpp:501] detection_eval = 5.21371
-I0511 11:50:55.668514  5581 caffe.cpp:501] detection_eval = 8.52218
-I0511 11:50:55.668516  5581 caffe.cpp:501] detection_eval = 0.0434062
-I0511 11:50:55.668519  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668521  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668529  5581 caffe.cpp:501] detection_eval = 5.21774
-I0511 11:50:55.668531  5581 caffe.cpp:501] detection_eval = 8.5121
-I0511 11:50:55.668534  5581 caffe.cpp:501] detection_eval = 0.0414134
-I0511 11:50:55.668535  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668537  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668540  5581 caffe.cpp:501] detection_eval = 5.22177
-I0511 11:50:55.668542  5581 caffe.cpp:501] detection_eval = 8.50403
-I0511 11:50:55.668545  5581 caffe.cpp:501] detection_eval = 0.0423669
-I0511 11:50:55.668546  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668548  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668551  5581 caffe.cpp:501] detection_eval = 5.22379
-I0511 11:50:55.668553  5581 caffe.cpp:501] detection_eval = 8.53629
-I0511 11:50:55.668555  5581 caffe.cpp:501] detection_eval = 0.0402759
-I0511 11:50:55.668557  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668560  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668562  5581 caffe.cpp:501] detection_eval = 5.22581
-I0511 11:50:55.668565  5581 caffe.cpp:501] detection_eval = 8.56855
-I0511 11:50:55.668566  5581 caffe.cpp:501] detection_eval = 0.0421297
-I0511 11:50:55.668568  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668571  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668573  5581 caffe.cpp:501] detection_eval = 5.22782
-I0511 11:50:55.668576  5581 caffe.cpp:501] detection_eval = 8.60887
-I0511 11:50:55.668577  5581 caffe.cpp:501] detection_eval = 0.0462904
-I0511 11:50:55.668579  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668582  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668584  5581 caffe.cpp:501] detection_eval = 5.22984
-I0511 11:50:55.668586  5581 caffe.cpp:501] detection_eval = 8.65726
-I0511 11:50:55.668588  5581 caffe.cpp:501] detection_eval = 0.0466748
-I0511 11:50:55.668591  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.668593  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.668596  5581 caffe.cpp:501] detection_eval = 5.22984
-I0511 11:50:55.668597  5581 caffe.cpp:501] detection_eval = 8.7379
-I0511 11:50:55.668599  5581 caffe.cpp:501] detection_eval = 0.0410906
-I0511 11:50:55.668601  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668604  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668606  5581 caffe.cpp:501] detection_eval = 5.23185
-I0511 11:50:55.668608  5581 caffe.cpp:501] detection_eval = 8.77218
-I0511 11:50:55.668611  5581 caffe.cpp:501] detection_eval = 0.0426186
-I0511 11:50:55.668612  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668615  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668617  5581 caffe.cpp:501] detection_eval = 5.23387
-I0511 11:50:55.668619  5581 caffe.cpp:501] detection_eval = 8.80645
-I0511 11:50:55.668622  5581 caffe.cpp:501] detection_eval = 0.0417548
-I0511 11:50:55.668624  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668627  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668629  5581 caffe.cpp:501] detection_eval = 5.23387
-I0511 11:50:55.668632  5581 caffe.cpp:501] detection_eval = 8.93145
-I0511 11:50:55.668637  5581 caffe.cpp:501] detection_eval = 0.0471477
-I0511 11:50:55.668639  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668642  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668643  5581 caffe.cpp:501] detection_eval = 5.2379
-I0511 11:50:55.668646  5581 caffe.cpp:501] detection_eval = 9.00806
-I0511 11:50:55.668648  5581 caffe.cpp:501] detection_eval = 0.0530266
-I0511 11:50:55.668650  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668653  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668655  5581 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:50:55.668658  5581 caffe.cpp:501] detection_eval = 8.96976
-I0511 11:50:55.668659  5581 caffe.cpp:501] detection_eval = 0.0465821
-I0511 11:50:55.668661  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668663  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668666  5581 caffe.cpp:501] detection_eval = 5.24395
-I0511 11:50:55.668668  5581 caffe.cpp:501] detection_eval = 9.02621
-I0511 11:50:55.668670  5581 caffe.cpp:501] detection_eval = 0.0416271
-I0511 11:50:55.668673  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668675  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.668678  5581 caffe.cpp:501] detection_eval = 5.24597
-I0511 11:50:55.668679  5581 caffe.cpp:501] detection_eval = 9.10685
-I0511 11:50:55.668682  5581 caffe.cpp:501] detection_eval = 0.0442582
-I0511 11:50:55.668684  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668686  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668689  5581 caffe.cpp:501] detection_eval = 5.25
-I0511 11:50:55.668691  5581 caffe.cpp:501] detection_eval = 9.13306
-I0511 11:50:55.668694  5581 caffe.cpp:501] detection_eval = 0.0430844
-I0511 11:50:55.668695  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668699  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.668700  5581 caffe.cpp:501] detection_eval = 5.25403
-I0511 11:50:55.668702  5581 caffe.cpp:501] detection_eval = 9.17137
-I0511 11:50:55.668704  5581 caffe.cpp:501] detection_eval = 0.0411147
-I0511 11:50:55.668707  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668709  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668711  5581 caffe.cpp:501] detection_eval = 5.25403
-I0511 11:50:55.668714  5581 caffe.cpp:501] detection_eval = 9.22379
-I0511 11:50:55.668716  5581 caffe.cpp:501] detection_eval = 0.0439104
-I0511 11:50:55.668718  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668720  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668722  5581 caffe.cpp:501] detection_eval = 5.25605
-I0511 11:50:55.668725  5581 caffe.cpp:501] detection_eval = 9.33266
-I0511 11:50:55.668727  5581 caffe.cpp:501] detection_eval = 0.0474289
-I0511 11:50:55.668730  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668731  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668733  5581 caffe.cpp:501] detection_eval = 5.25605
-I0511 11:50:55.668736  5581 caffe.cpp:501] detection_eval = 9.41935
-I0511 11:50:55.668738  5581 caffe.cpp:501] detection_eval = 0.0444779
-I0511 11:50:55.668740  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668742  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668745  5581 caffe.cpp:501] detection_eval = 5.26008
-I0511 11:50:55.668747  5581 caffe.cpp:501] detection_eval = 9.44355
-I0511 11:50:55.668750  5581 caffe.cpp:501] detection_eval = 0.0479086
-I0511 11:50:55.668751  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668754  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668756  5581 caffe.cpp:501] detection_eval = 5.26613
-I0511 11:50:55.668758  5581 caffe.cpp:501] detection_eval = 9.38911
-I0511 11:50:55.668761  5581 caffe.cpp:501] detection_eval = 0.0470021
-I0511 11:50:55.668762  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.668766  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668767  5581 caffe.cpp:501] detection_eval = 5.26613
-I0511 11:50:55.668769  5581 caffe.cpp:501] detection_eval = 9.4496
-I0511 11:50:55.668774  5581 caffe.cpp:501] detection_eval = 0.0433997
-I0511 11:50:55.668776  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668778  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668781  5581 caffe.cpp:501] detection_eval = 5.26815
-I0511 11:50:55.668783  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.668786  5581 caffe.cpp:501] detection_eval = 0.0450501
-I0511 11:50:55.668787  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668789  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668792  5581 caffe.cpp:501] detection_eval = 5.27218
-I0511 11:50:55.668794  5581 caffe.cpp:501] detection_eval = 9.58468
-I0511 11:50:55.668797  5581 caffe.cpp:501] detection_eval = 0.0429084
-I0511 11:50:55.668798  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668800  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668803  5581 caffe.cpp:501] detection_eval = 5.27218
-I0511 11:50:55.668805  5581 caffe.cpp:501] detection_eval = 9.64516
-I0511 11:50:55.668807  5581 caffe.cpp:501] detection_eval = 0.0422002
-I0511 11:50:55.668809  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668812  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.668814  5581 caffe.cpp:501] detection_eval = 5.27823
-I0511 11:50:55.668817  5581 caffe.cpp:501] detection_eval = 9.59476
-I0511 11:50:55.668819  5581 caffe.cpp:501] detection_eval = 0.0405412
-I0511 11:50:55.668822  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668823  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668825  5581 caffe.cpp:501] detection_eval = 5.27823
-I0511 11:50:55.668828  5581 caffe.cpp:501] detection_eval = 9.68952
-I0511 11:50:55.668830  5581 caffe.cpp:501] detection_eval = 0.0440439
-I0511 11:50:55.668833  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668834  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.668836  5581 caffe.cpp:501] detection_eval = 5.28024
-I0511 11:50:55.668839  5581 caffe.cpp:501] detection_eval = 9.72177
-I0511 11:50:55.668841  5581 caffe.cpp:501] detection_eval = 0.0416299
-I0511 11:50:55.668843  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668845  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668848  5581 caffe.cpp:501] detection_eval = 5.28226
-I0511 11:50:55.668849  5581 caffe.cpp:501] detection_eval = 9.80847
-I0511 11:50:55.668853  5581 caffe.cpp:501] detection_eval = 0.0423391
-I0511 11:50:55.668854  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.668856  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668859  5581 caffe.cpp:501] detection_eval = 5.28226
-I0511 11:50:55.668861  5581 caffe.cpp:501] detection_eval = 9.87903
-I0511 11:50:55.668864  5581 caffe.cpp:501] detection_eval = 0.0398229
-I0511 11:50:55.668865  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.668867  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.668870  5581 caffe.cpp:501] detection_eval = 5.28427
-I0511 11:50:55.668872  5581 caffe.cpp:501] detection_eval = 9.93952
-I0511 11:50:55.668875  5581 caffe.cpp:501] detection_eval = 0.0441284
-I0511 11:50:55.668877  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668879  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668882  5581 caffe.cpp:501] detection_eval = 5.28629
-I0511 11:50:55.668884  5581 caffe.cpp:501] detection_eval = 9.98992
-I0511 11:50:55.668886  5581 caffe.cpp:501] detection_eval = 0.0474331
-I0511 11:50:55.668889  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668891  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668893  5581 caffe.cpp:501] detection_eval = 5.29234
-I0511 11:50:55.668895  5581 caffe.cpp:501] detection_eval = 10.0081
-I0511 11:50:55.668898  5581 caffe.cpp:501] detection_eval = 0.0480445
-I0511 11:50:55.668900  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.668902  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668905  5581 caffe.cpp:501] detection_eval = 5.29839
-I0511 11:50:55.668910  5581 caffe.cpp:501] detection_eval = 9.98185
-I0511 11:50:55.668912  5581 caffe.cpp:501] detection_eval = 0.048949
-I0511 11:50:55.668915  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668917  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668920  5581 caffe.cpp:501] detection_eval = 5.30242
-I0511 11:50:55.668921  5581 caffe.cpp:501] detection_eval = 9.98185
-I0511 11:50:55.668923  5581 caffe.cpp:501] detection_eval = 0.0434407
-I0511 11:50:55.668926  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.668928  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.668931  5581 caffe.cpp:501] detection_eval = 5.30847
-I0511 11:50:55.668933  5581 caffe.cpp:501] detection_eval = 9.97581
-I0511 11:50:55.668936  5581 caffe.cpp:501] detection_eval = 0.042905
-I0511 11:50:55.668941  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668944  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668947  5581 caffe.cpp:501] detection_eval = 5.31048
-I0511 11:50:55.668951  5581 caffe.cpp:501] detection_eval = 10.0524
-I0511 11:50:55.668952  5581 caffe.cpp:501] detection_eval = 0.0485621
-I0511 11:50:55.668954  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.668956  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.668958  5581 caffe.cpp:501] detection_eval = 5.31452
-I0511 11:50:55.668962  5581 caffe.cpp:501] detection_eval = 10.1008
-I0511 11:50:55.668963  5581 caffe.cpp:501] detection_eval = 0.0470324
-I0511 11:50:55.668965  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668967  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.668970  5581 caffe.cpp:501] detection_eval = 5.31653
-I0511 11:50:55.668972  5581 caffe.cpp:501] detection_eval = 10.1613
-I0511 11:50:55.668974  5581 caffe.cpp:501] detection_eval = 0.043986
-I0511 11:50:55.668977  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.668979  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.668982  5581 caffe.cpp:501] detection_eval = 5.31653
-I0511 11:50:55.668983  5581 caffe.cpp:501] detection_eval = 10.252
-I0511 11:50:55.668985  5581 caffe.cpp:501] detection_eval = 0.047543
-I0511 11:50:55.668988  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.668990  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.668992  5581 caffe.cpp:501] detection_eval = 5.31855
-I0511 11:50:55.668994  5581 caffe.cpp:501] detection_eval = 10.2641
-I0511 11:50:55.668998  5581 caffe.cpp:501] detection_eval = 0.0483524
-I0511 11:50:55.668999  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669001  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669003  5581 caffe.cpp:501] detection_eval = 5.32661
-I0511 11:50:55.669005  5581 caffe.cpp:501] detection_eval = 10.248
-I0511 11:50:55.669008  5581 caffe.cpp:501] detection_eval = 0.0499154
-I0511 11:50:55.669010  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669013  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669014  5581 caffe.cpp:501] detection_eval = 5.33065
-I0511 11:50:55.669016  5581 caffe.cpp:501] detection_eval = 10.2399
-I0511 11:50:55.669019  5581 caffe.cpp:501] detection_eval = 0.0430064
-I0511 11:50:55.669021  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669023  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669025  5581 caffe.cpp:501] detection_eval = 5.34073
-I0511 11:50:55.669028  5581 caffe.cpp:501] detection_eval = 10.1734
-I0511 11:50:55.669030  5581 caffe.cpp:501] detection_eval = 0.0436573
-I0511 11:50:55.669032  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669034  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669037  5581 caffe.cpp:501] detection_eval = 5.34274
-I0511 11:50:55.669039  5581 caffe.cpp:501] detection_eval = 10.246
-I0511 11:50:55.669041  5581 caffe.cpp:501] detection_eval = 0.043249
-I0511 11:50:55.669044  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669046  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669049  5581 caffe.cpp:501] detection_eval = 5.35081
-I0511 11:50:55.669054  5581 caffe.cpp:501] detection_eval = 10.1875
-I0511 11:50:55.669057  5581 caffe.cpp:501] detection_eval = 0.0414232
-I0511 11:50:55.669059  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669061  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669064  5581 caffe.cpp:501] detection_eval = 5.35484
-I0511 11:50:55.669065  5581 caffe.cpp:501] detection_eval = 10.246
-I0511 11:50:55.669068  5581 caffe.cpp:501] detection_eval = 0.0454759
-I0511 11:50:55.669070  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.669073  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.669075  5581 caffe.cpp:501] detection_eval = 5.35887
-I0511 11:50:55.669077  5581 caffe.cpp:501] detection_eval = 10.248
-I0511 11:50:55.669080  5581 caffe.cpp:501] detection_eval = 0.0448357
-I0511 11:50:55.669081  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669085  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669086  5581 caffe.cpp:501] detection_eval = 5.36089
-I0511 11:50:55.669088  5581 caffe.cpp:501] detection_eval = 10.3145
-I0511 11:50:55.669091  5581 caffe.cpp:501] detection_eval = 0.0508685
-I0511 11:50:55.669093  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669095  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669097  5581 caffe.cpp:501] detection_eval = 5.36492
-I0511 11:50:55.669100  5581 caffe.cpp:501] detection_eval = 10.3044
-I0511 11:50:55.669102  5581 caffe.cpp:501] detection_eval = 0.0464236
-I0511 11:50:55.669104  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669106  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.669108  5581 caffe.cpp:501] detection_eval = 5.36895
-I0511 11:50:55.669111  5581 caffe.cpp:501] detection_eval = 10.2964
-I0511 11:50:55.669113  5581 caffe.cpp:501] detection_eval = 0.0446635
-I0511 11:50:55.669116  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669117  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669119  5581 caffe.cpp:501] detection_eval = 5.375
-I0511 11:50:55.669121  5581 caffe.cpp:501] detection_eval = 10.3004
-I0511 11:50:55.669124  5581 caffe.cpp:501] detection_eval = 0.0434711
-I0511 11:50:55.669126  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669128  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669131  5581 caffe.cpp:501] detection_eval = 5.37702
-I0511 11:50:55.669132  5581 caffe.cpp:501] detection_eval = 10.371
-I0511 11:50:55.669136  5581 caffe.cpp:501] detection_eval = 0.0435071
-I0511 11:50:55.669137  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669139  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669142  5581 caffe.cpp:501] detection_eval = 5.37903
-I0511 11:50:55.669144  5581 caffe.cpp:501] detection_eval = 10.4516
-I0511 11:50:55.669147  5581 caffe.cpp:501] detection_eval = 0.0447716
-I0511 11:50:55.669148  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669150  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669152  5581 caffe.cpp:501] detection_eval = 5.38508
-I0511 11:50:55.669155  5581 caffe.cpp:501] detection_eval = 10.4577
-I0511 11:50:55.669157  5581 caffe.cpp:501] detection_eval = 0.045388
-I0511 11:50:55.669159  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669162  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669164  5581 caffe.cpp:501] detection_eval = 5.38911
-I0511 11:50:55.669167  5581 caffe.cpp:501] detection_eval = 10.5242
-I0511 11:50:55.669168  5581 caffe.cpp:501] detection_eval = 0.0461074
-I0511 11:50:55.669172  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669173  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669175  5581 caffe.cpp:501] detection_eval = 5.39718
-I0511 11:50:55.669178  5581 caffe.cpp:501] detection_eval = 10.4859
-I0511 11:50:55.669180  5581 caffe.cpp:501] detection_eval = 0.0467653
-I0511 11:50:55.669183  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669184  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669189  5581 caffe.cpp:501] detection_eval = 5.39718
-I0511 11:50:55.669191  5581 caffe.cpp:501] detection_eval = 10.5927
-I0511 11:50:55.669194  5581 caffe.cpp:501] detection_eval = 0.0469085
-I0511 11:50:55.669196  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669198  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669200  5581 caffe.cpp:501] detection_eval = 5.40323
-I0511 11:50:55.669203  5581 caffe.cpp:501] detection_eval = 10.5927
-I0511 11:50:55.669205  5581 caffe.cpp:501] detection_eval = 0.0469142
-I0511 11:50:55.669208  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669209  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669211  5581 caffe.cpp:501] detection_eval = 5.40726
-I0511 11:50:55.669214  5581 caffe.cpp:501] detection_eval = 10.6169
-I0511 11:50:55.669216  5581 caffe.cpp:501] detection_eval = 0.0497463
-I0511 11:50:55.669219  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669220  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669224  5581 caffe.cpp:501] detection_eval = 5.41129
-I0511 11:50:55.669225  5581 caffe.cpp:501] detection_eval = 10.6391
-I0511 11:50:55.669229  5581 caffe.cpp:501] detection_eval = 0.0516768
-I0511 11:50:55.669230  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669232  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669234  5581 caffe.cpp:501] detection_eval = 5.41129
-I0511 11:50:55.669236  5581 caffe.cpp:501] detection_eval = 10.744
-I0511 11:50:55.669239  5581 caffe.cpp:501] detection_eval = 0.0503277
-I0511 11:50:55.669241  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669243  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669245  5581 caffe.cpp:501] detection_eval = 5.41532
-I0511 11:50:55.669248  5581 caffe.cpp:501] detection_eval = 10.756
-I0511 11:50:55.669250  5581 caffe.cpp:501] detection_eval = 0.0503253
-I0511 11:50:55.669252  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669255  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669256  5581 caffe.cpp:501] detection_eval = 5.41935
-I0511 11:50:55.669260  5581 caffe.cpp:501] detection_eval = 10.7278
-I0511 11:50:55.669261  5581 caffe.cpp:501] detection_eval = 0.0467886
-I0511 11:50:55.669263  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669265  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669268  5581 caffe.cpp:501] detection_eval = 5.42137
-I0511 11:50:55.669270  5581 caffe.cpp:501] detection_eval = 10.7702
-I0511 11:50:55.669272  5581 caffe.cpp:501] detection_eval = 0.0471315
-I0511 11:50:55.669275  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669276  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669279  5581 caffe.cpp:501] detection_eval = 5.4254
-I0511 11:50:55.669281  5581 caffe.cpp:501] detection_eval = 10.752
-I0511 11:50:55.669283  5581 caffe.cpp:501] detection_eval = 0.0403206
-I0511 11:50:55.669286  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.669288  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669291  5581 caffe.cpp:501] detection_eval = 5.43347
-I0511 11:50:55.669292  5581 caffe.cpp:501] detection_eval = 10.6895
-I0511 11:50:55.669296  5581 caffe.cpp:501] detection_eval = 0.0403499
-I0511 11:50:55.669297  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669299  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669302  5581 caffe.cpp:501] detection_eval = 5.43548
-I0511 11:50:55.669304  5581 caffe.cpp:501] detection_eval = 10.7319
-I0511 11:50:55.669306  5581 caffe.cpp:501] detection_eval = 0.0390869
-I0511 11:50:55.669308  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669312  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669313  5581 caffe.cpp:501] detection_eval = 5.4375
-I0511 11:50:55.669315  5581 caffe.cpp:501] detection_eval = 10.8004
-I0511 11:50:55.669318  5581 caffe.cpp:501] detection_eval = 0.0409101
-I0511 11:50:55.669320  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669327  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669330  5581 caffe.cpp:501] detection_eval = 5.44758
-I0511 11:50:55.669332  5581 caffe.cpp:501] detection_eval = 10.7278
-I0511 11:50:55.669334  5581 caffe.cpp:501] detection_eval = 0.0428666
-I0511 11:50:55.669337  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669339  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669342  5581 caffe.cpp:501] detection_eval = 5.45161
-I0511 11:50:55.669343  5581 caffe.cpp:501] detection_eval = 10.754
-I0511 11:50:55.669345  5581 caffe.cpp:501] detection_eval = 0.0514215
-I0511 11:50:55.669348  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669350  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669353  5581 caffe.cpp:501] detection_eval = 5.45968
-I0511 11:50:55.669354  5581 caffe.cpp:501] detection_eval = 10.6956
-I0511 11:50:55.669358  5581 caffe.cpp:501] detection_eval = 0.0517602
-I0511 11:50:55.669359  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669361  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669363  5581 caffe.cpp:501] detection_eval = 5.46976
-I0511 11:50:55.669365  5581 caffe.cpp:501] detection_eval = 10.5988
-I0511 11:50:55.669368  5581 caffe.cpp:501] detection_eval = 0.0470854
-I0511 11:50:55.669370  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669373  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669375  5581 caffe.cpp:501] detection_eval = 5.46976
-I0511 11:50:55.669379  5581 caffe.cpp:501] detection_eval = 10.6532
-I0511 11:50:55.669384  5581 caffe.cpp:501] detection_eval = 0.0442673
-I0511 11:50:55.669386  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669390  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669400  5581 caffe.cpp:501] detection_eval = 5.47379
-I0511 11:50:55.669404  5581 caffe.cpp:501] detection_eval = 10.6694
-I0511 11:50:55.669406  5581 caffe.cpp:501] detection_eval = 0.0429766
-I0511 11:50:55.669409  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669411  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669414  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.669415  5581 caffe.cpp:501] detection_eval = 10.6351
-I0511 11:50:55.669417  5581 caffe.cpp:501] detection_eval = 0.0445091
-I0511 11:50:55.669420  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669422  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669425  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.669426  5581 caffe.cpp:501] detection_eval = 10.7056
-I0511 11:50:55.669428  5581 caffe.cpp:501] detection_eval = 0.041474
-I0511 11:50:55.669431  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669433  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669435  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.669437  5581 caffe.cpp:501] detection_eval = 10.7661
-I0511 11:50:55.669440  5581 caffe.cpp:501] detection_eval = 0.0445598
-I0511 11:50:55.669442  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669445  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669446  5581 caffe.cpp:501] detection_eval = 5.47984
-I0511 11:50:55.669448  5581 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:50:55.669451  5581 caffe.cpp:501] detection_eval = 0.046457
-I0511 11:50:55.669453  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669456  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669457  5581 caffe.cpp:501] detection_eval = 5.48387
-I0511 11:50:55.669461  5581 caffe.cpp:501] detection_eval = 10.8589
-I0511 11:50:55.669462  5581 caffe.cpp:501] detection_eval = 0.0519797
-I0511 11:50:55.669464  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.669466  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.669469  5581 caffe.cpp:501] detection_eval = 5.48589
-I0511 11:50:55.669471  5581 caffe.cpp:501] detection_eval = 10.9032
-I0511 11:50:55.669473  5581 caffe.cpp:501] detection_eval = 0.0435595
-I0511 11:50:55.669476  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669481  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669483  5581 caffe.cpp:501] detection_eval = 5.4879
-I0511 11:50:55.669486  5581 caffe.cpp:501] detection_eval = 10.9657
-I0511 11:50:55.669487  5581 caffe.cpp:501] detection_eval = 0.0442254
-I0511 11:50:55.669489  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669492  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669494  5581 caffe.cpp:501] detection_eval = 5.48992
-I0511 11:50:55.669497  5581 caffe.cpp:501] detection_eval = 10.998
-I0511 11:50:55.669498  5581 caffe.cpp:501] detection_eval = 0.0425595
-I0511 11:50:55.669500  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669503  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669505  5581 caffe.cpp:501] detection_eval = 5.49194
-I0511 11:50:55.669507  5581 caffe.cpp:501] detection_eval = 11.0544
-I0511 11:50:55.669509  5581 caffe.cpp:501] detection_eval = 0.0436593
-I0511 11:50:55.669512  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669514  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669517  5581 caffe.cpp:501] detection_eval = 5.49395
-I0511 11:50:55.669518  5581 caffe.cpp:501] detection_eval = 11.0948
-I0511 11:50:55.669520  5581 caffe.cpp:501] detection_eval = 0.0409294
-I0511 11:50:55.669523  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669525  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.669528  5581 caffe.cpp:501] detection_eval = 5.49395
-I0511 11:50:55.669529  5581 caffe.cpp:501] detection_eval = 11.1774
-I0511 11:50:55.669533  5581 caffe.cpp:501] detection_eval = 0.0480408
-I0511 11:50:55.669534  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669536  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669538  5581 caffe.cpp:501] detection_eval = 5.49798
-I0511 11:50:55.669540  5581 caffe.cpp:501] detection_eval = 11.1956
-I0511 11:50:55.669543  5581 caffe.cpp:501] detection_eval = 0.0418039
-I0511 11:50:55.669545  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669548  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669549  5581 caffe.cpp:501] detection_eval = 5.50202
-I0511 11:50:55.669551  5581 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:50:55.669554  5581 caffe.cpp:501] detection_eval = 0.0453119
-I0511 11:50:55.669556  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669559  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669560  5581 caffe.cpp:501] detection_eval = 5.50605
-I0511 11:50:55.669562  5581 caffe.cpp:501] detection_eval = 11.246
-I0511 11:50:55.669565  5581 caffe.cpp:501] detection_eval = 0.0457032
-I0511 11:50:55.669567  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669569  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669571  5581 caffe.cpp:501] detection_eval = 5.51008
-I0511 11:50:55.669574  5581 caffe.cpp:501] detection_eval = 11.2198
-I0511 11:50:55.669576  5581 caffe.cpp:501] detection_eval = 0.0436824
-I0511 11:50:55.669579  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669580  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669584  5581 caffe.cpp:501] detection_eval = 5.51613
-I0511 11:50:55.669585  5581 caffe.cpp:501] detection_eval = 11.1875
-I0511 11:50:55.669589  5581 caffe.cpp:501] detection_eval = 0.04641
-I0511 11:50:55.669590  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669592  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669595  5581 caffe.cpp:501] detection_eval = 5.52016
-I0511 11:50:55.669596  5581 caffe.cpp:501] detection_eval = 11.2137
-I0511 11:50:55.669600  5581 caffe.cpp:501] detection_eval = 0.051417
-I0511 11:50:55.669601  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.669605  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.669606  5581 caffe.cpp:501] detection_eval = 5.52419
-I0511 11:50:55.669608  5581 caffe.cpp:501] detection_eval = 11.2198
-I0511 11:50:55.669610  5581 caffe.cpp:501] detection_eval = 0.0473769
-I0511 11:50:55.669615  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669617  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669620  5581 caffe.cpp:501] detection_eval = 5.52621
-I0511 11:50:55.669622  5581 caffe.cpp:501] detection_eval = 11.2802
-I0511 11:50:55.669625  5581 caffe.cpp:501] detection_eval = 0.0477645
-I0511 11:50:55.669626  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669628  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669631  5581 caffe.cpp:501] detection_eval = 5.53024
-I0511 11:50:55.669633  5581 caffe.cpp:501] detection_eval = 11.3044
-I0511 11:50:55.669636  5581 caffe.cpp:501] detection_eval = 0.0483738
-I0511 11:50:55.669637  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669639  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669641  5581 caffe.cpp:501] detection_eval = 5.53629
-I0511 11:50:55.669644  5581 caffe.cpp:501] detection_eval = 11.2843
-I0511 11:50:55.669646  5581 caffe.cpp:501] detection_eval = 0.0479017
-I0511 11:50:55.669648  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669651  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669652  5581 caffe.cpp:501] detection_eval = 5.54032
-I0511 11:50:55.669656  5581 caffe.cpp:501] detection_eval = 11.2802
-I0511 11:50:55.669657  5581 caffe.cpp:501] detection_eval = 0.0443945
-I0511 11:50:55.669659  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669661  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669663  5581 caffe.cpp:501] detection_eval = 5.54032
-I0511 11:50:55.669667  5581 caffe.cpp:501] detection_eval = 11.3367
-I0511 11:50:55.669668  5581 caffe.cpp:501] detection_eval = 0.0423903
-I0511 11:50:55.669670  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669672  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669675  5581 caffe.cpp:501] detection_eval = 5.54032
-I0511 11:50:55.669677  5581 caffe.cpp:501] detection_eval = 11.4194
-I0511 11:50:55.669679  5581 caffe.cpp:501] detection_eval = 0.0477495
-I0511 11:50:55.669682  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669683  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669687  5581 caffe.cpp:501] detection_eval = 5.54435
-I0511 11:50:55.669688  5581 caffe.cpp:501] detection_eval = 11.4476
-I0511 11:50:55.669690  5581 caffe.cpp:501] detection_eval = 0.0473879
-I0511 11:50:55.669692  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669694  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669697  5581 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:50:55.669699  5581 caffe.cpp:501] detection_eval = 11.4194
-I0511 11:50:55.669701  5581 caffe.cpp:501] detection_eval = 0.0470163
-I0511 11:50:55.669703  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669705  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669708  5581 caffe.cpp:501] detection_eval = 5.55645
-I0511 11:50:55.669710  5581 caffe.cpp:501] detection_eval = 11.4355
-I0511 11:50:55.669713  5581 caffe.cpp:501] detection_eval = 0.0413591
-I0511 11:50:55.669714  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669718  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669720  5581 caffe.cpp:501] detection_eval = 5.56048
-I0511 11:50:55.669724  5581 caffe.cpp:501] detection_eval = 11.4556
-I0511 11:50:55.669728  5581 caffe.cpp:501] detection_eval = 0.0422115
-I0511 11:50:55.669733  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669735  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669737  5581 caffe.cpp:501] detection_eval = 5.56452
-I0511 11:50:55.669739  5581 caffe.cpp:501] detection_eval = 11.4617
-I0511 11:50:55.669742  5581 caffe.cpp:501] detection_eval = 0.0433957
-I0511 11:50:55.669744  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669746  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669749  5581 caffe.cpp:501] detection_eval = 5.57056
-I0511 11:50:55.669750  5581 caffe.cpp:501] detection_eval = 11.4859
-I0511 11:50:55.669754  5581 caffe.cpp:501] detection_eval = 0.0469743
-I0511 11:50:55.669759  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669761  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669764  5581 caffe.cpp:501] detection_eval = 5.57661
-I0511 11:50:55.669765  5581 caffe.cpp:501] detection_eval = 11.4718
-I0511 11:50:55.669769  5581 caffe.cpp:501] detection_eval = 0.0456488
-I0511 11:50:55.669770  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669772  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669775  5581 caffe.cpp:501] detection_eval = 5.58065
-I0511 11:50:55.669776  5581 caffe.cpp:501] detection_eval = 11.4819
-I0511 11:50:55.669780  5581 caffe.cpp:501] detection_eval = 0.0487595
-I0511 11:50:55.669781  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669783  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669785  5581 caffe.cpp:501] detection_eval = 5.58468
-I0511 11:50:55.669787  5581 caffe.cpp:501] detection_eval = 11.4718
-I0511 11:50:55.669790  5581 caffe.cpp:501] detection_eval = 0.0458818
-I0511 11:50:55.669792  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669795  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669796  5581 caffe.cpp:501] detection_eval = 5.58669
-I0511 11:50:55.669798  5581 caffe.cpp:501] detection_eval = 11.4778
-I0511 11:50:55.669801  5581 caffe.cpp:501] detection_eval = 0.0440891
-I0511 11:50:55.669803  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669806  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669807  5581 caffe.cpp:501] detection_eval = 5.58871
-I0511 11:50:55.669809  5581 caffe.cpp:501] detection_eval = 11.5565
-I0511 11:50:55.669812  5581 caffe.cpp:501] detection_eval = 0.0466776
-I0511 11:50:55.669814  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669816  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669818  5581 caffe.cpp:501] detection_eval = 5.59073
-I0511 11:50:55.669821  5581 caffe.cpp:501] detection_eval = 11.623
-I0511 11:50:55.669823  5581 caffe.cpp:501] detection_eval = 0.0433827
-I0511 11:50:55.669826  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669827  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669829  5581 caffe.cpp:501] detection_eval = 5.59274
-I0511 11:50:55.669831  5581 caffe.cpp:501] detection_eval = 11.6552
-I0511 11:50:55.669834  5581 caffe.cpp:501] detection_eval = 0.0483604
-I0511 11:50:55.669836  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669838  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669840  5581 caffe.cpp:501] detection_eval = 5.59274
-I0511 11:50:55.669842  5581 caffe.cpp:501] detection_eval = 11.7319
-I0511 11:50:55.669845  5581 caffe.cpp:501] detection_eval = 0.0416868
-I0511 11:50:55.669847  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.669849  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.669852  5581 caffe.cpp:501] detection_eval = 5.59879
-I0511 11:50:55.669853  5581 caffe.cpp:501] detection_eval = 11.7056
-I0511 11:50:55.669857  5581 caffe.cpp:501] detection_eval = 0.0412591
-I0511 11:50:55.669858  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669860  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669862  5581 caffe.cpp:501] detection_eval = 5.60282
-I0511 11:50:55.669865  5581 caffe.cpp:501] detection_eval = 11.7077
-I0511 11:50:55.669867  5581 caffe.cpp:501] detection_eval = 0.0404898
-I0511 11:50:55.669869  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669872  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669873  5581 caffe.cpp:501] detection_eval = 5.60685
-I0511 11:50:55.669876  5581 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:50:55.669878  5581 caffe.cpp:501] detection_eval = 0.0412444
-I0511 11:50:55.669880  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.669883  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669884  5581 caffe.cpp:501] detection_eval = 5.60685
-I0511 11:50:55.669888  5581 caffe.cpp:501] detection_eval = 11.7802
-I0511 11:50:55.669891  5581 caffe.cpp:501] detection_eval = 0.0403206
-I0511 11:50:55.669894  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669896  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.669898  5581 caffe.cpp:501] detection_eval = 5.60887
-I0511 11:50:55.669900  5581 caffe.cpp:501] detection_eval = 11.8105
-I0511 11:50:55.669903  5581 caffe.cpp:501] detection_eval = 0.0406728
-I0511 11:50:55.669905  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669908  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.669909  5581 caffe.cpp:501] detection_eval = 5.60887
-I0511 11:50:55.669911  5581 caffe.cpp:501] detection_eval = 11.9335
-I0511 11:50:55.669914  5581 caffe.cpp:501] detection_eval = 0.0443882
-I0511 11:50:55.669916  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669919  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669920  5581 caffe.cpp:501] detection_eval = 5.6129
-I0511 11:50:55.669924  5581 caffe.cpp:501] detection_eval = 11.9093
-I0511 11:50:55.669925  5581 caffe.cpp:501] detection_eval = 0.0395095
-I0511 11:50:55.669927  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.669929  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669931  5581 caffe.cpp:501] detection_eval = 5.61694
-I0511 11:50:55.669934  5581 caffe.cpp:501] detection_eval = 11.873
-I0511 11:50:55.669936  5581 caffe.cpp:501] detection_eval = 0.0422343
-I0511 11:50:55.669939  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669940  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669942  5581 caffe.cpp:501] detection_eval = 5.61694
-I0511 11:50:55.669945  5581 caffe.cpp:501] detection_eval = 11.9133
-I0511 11:50:55.669947  5581 caffe.cpp:501] detection_eval = 0.0376908
-I0511 11:50:55.669950  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.669951  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.669955  5581 caffe.cpp:501] detection_eval = 5.62097
-I0511 11:50:55.669956  5581 caffe.cpp:501] detection_eval = 11.9355
-I0511 11:50:55.669958  5581 caffe.cpp:501] detection_eval = 0.0406901
-I0511 11:50:55.669960  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.669962  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.669965  5581 caffe.cpp:501] detection_eval = 5.62702
-I0511 11:50:55.669967  5581 caffe.cpp:501] detection_eval = 11.8952
-I0511 11:50:55.669970  5581 caffe.cpp:501] detection_eval = 0.0444293
-I0511 11:50:55.669971  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.669973  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.669975  5581 caffe.cpp:501] detection_eval = 5.63508
-I0511 11:50:55.669978  5581 caffe.cpp:501] detection_eval = 11.8427
-I0511 11:50:55.669981  5581 caffe.cpp:501] detection_eval = 0.0456376
-I0511 11:50:55.669982  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.669984  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.669987  5581 caffe.cpp:501] detection_eval = 5.64113
-I0511 11:50:55.669989  5581 caffe.cpp:501] detection_eval = 11.8044
-I0511 11:50:55.669991  5581 caffe.cpp:501] detection_eval = 0.0494156
-I0511 11:50:55.669993  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.669996  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.669998  5581 caffe.cpp:501] detection_eval = 5.64919
-I0511 11:50:55.670001  5581 caffe.cpp:501] detection_eval = 11.7399
-I0511 11:50:55.670002  5581 caffe.cpp:501] detection_eval = 0.0463872
-I0511 11:50:55.670004  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670007  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670009  5581 caffe.cpp:501] detection_eval = 5.65927
-I0511 11:50:55.670011  5581 caffe.cpp:501] detection_eval = 11.6855
-I0511 11:50:55.670013  5581 caffe.cpp:501] detection_eval = 0.0443355
-I0511 11:50:55.670015  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670018  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670020  5581 caffe.cpp:501] detection_eval = 5.65927
-I0511 11:50:55.670024  5581 caffe.cpp:501] detection_eval = 11.7137
-I0511 11:50:55.670027  5581 caffe.cpp:501] detection_eval = 0.0426486
-I0511 11:50:55.670029  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670032  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670033  5581 caffe.cpp:501] detection_eval = 5.66129
-I0511 11:50:55.670035  5581 caffe.cpp:501] detection_eval = 11.7339
-I0511 11:50:55.670038  5581 caffe.cpp:501] detection_eval = 0.0423245
-I0511 11:50:55.670040  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670042  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670044  5581 caffe.cpp:501] detection_eval = 5.66129
-I0511 11:50:55.670047  5581 caffe.cpp:501] detection_eval = 11.7984
-I0511 11:50:55.670049  5581 caffe.cpp:501] detection_eval = 0.040463
-I0511 11:50:55.670051  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670053  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670055  5581 caffe.cpp:501] detection_eval = 5.66532
-I0511 11:50:55.670058  5581 caffe.cpp:501] detection_eval = 11.8085
-I0511 11:50:55.670060  5581 caffe.cpp:501] detection_eval = 0.0426931
-I0511 11:50:55.670063  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670064  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670066  5581 caffe.cpp:501] detection_eval = 5.66532
-I0511 11:50:55.670069  5581 caffe.cpp:501] detection_eval = 11.9032
-I0511 11:50:55.670071  5581 caffe.cpp:501] detection_eval = 0.0421257
-I0511 11:50:55.670073  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670075  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670078  5581 caffe.cpp:501] detection_eval = 5.66734
-I0511 11:50:55.670080  5581 caffe.cpp:501] detection_eval = 11.9456
-I0511 11:50:55.670083  5581 caffe.cpp:501] detection_eval = 0.0416543
-I0511 11:50:55.670084  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670086  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670089  5581 caffe.cpp:501] detection_eval = 5.66935
-I0511 11:50:55.670091  5581 caffe.cpp:501] detection_eval = 11.9919
-I0511 11:50:55.670094  5581 caffe.cpp:501] detection_eval = 0.0403842
-I0511 11:50:55.670095  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670097  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670100  5581 caffe.cpp:501] detection_eval = 5.67742
-I0511 11:50:55.670102  5581 caffe.cpp:501] detection_eval = 11.9073
-I0511 11:50:55.670104  5581 caffe.cpp:501] detection_eval = 0.0411806
-I0511 11:50:55.670106  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670109  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670111  5581 caffe.cpp:501] detection_eval = 5.67944
-I0511 11:50:55.670114  5581 caffe.cpp:501] detection_eval = 11.9234
-I0511 11:50:55.670115  5581 caffe.cpp:501] detection_eval = 0.0410597
-I0511 11:50:55.670117  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670120  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670122  5581 caffe.cpp:501] detection_eval = 5.68347
-I0511 11:50:55.670125  5581 caffe.cpp:501] detection_eval = 11.9778
-I0511 11:50:55.670126  5581 caffe.cpp:501] detection_eval = 0.0414674
-I0511 11:50:55.670130  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670131  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670133  5581 caffe.cpp:501] detection_eval = 5.69153
-I0511 11:50:55.670135  5581 caffe.cpp:501] detection_eval = 11.9133
-I0511 11:50:55.670137  5581 caffe.cpp:501] detection_eval = 0.0408694
-I0511 11:50:55.670140  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670142  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670145  5581 caffe.cpp:501] detection_eval = 5.69758
-I0511 11:50:55.670146  5581 caffe.cpp:501] detection_eval = 11.8972
-I0511 11:50:55.670148  5581 caffe.cpp:501] detection_eval = 0.0456838
-I0511 11:50:55.670151  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670153  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670156  5581 caffe.cpp:501] detection_eval = 5.6996
-I0511 11:50:55.670159  5581 caffe.cpp:501] detection_eval = 11.9113
-I0511 11:50:55.670162  5581 caffe.cpp:501] detection_eval = 0.0433706
-I0511 11:50:55.670164  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670166  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670168  5581 caffe.cpp:501] detection_eval = 5.6996
-I0511 11:50:55.670171  5581 caffe.cpp:501] detection_eval = 11.9657
-I0511 11:50:55.670173  5581 caffe.cpp:501] detection_eval = 0.0377889
-I0511 11:50:55.670176  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.670177  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.670181  5581 caffe.cpp:501] detection_eval = 5.70363
-I0511 11:50:55.670182  5581 caffe.cpp:501] detection_eval = 12.0484
-I0511 11:50:55.670184  5581 caffe.cpp:501] detection_eval = 0.0475116
-I0511 11:50:55.670186  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670188  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670192  5581 caffe.cpp:501] detection_eval = 5.70766
-I0511 11:50:55.670193  5581 caffe.cpp:501] detection_eval = 12.0948
-I0511 11:50:55.670195  5581 caffe.cpp:501] detection_eval = 0.0430094
-I0511 11:50:55.670197  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670200  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670202  5581 caffe.cpp:501] detection_eval = 5.71169
-I0511 11:50:55.670204  5581 caffe.cpp:501] detection_eval = 12.0625
-I0511 11:50:55.670207  5581 caffe.cpp:501] detection_eval = 0.0406012
-I0511 11:50:55.670208  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670212  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.670213  5581 caffe.cpp:501] detection_eval = 5.71371
-I0511 11:50:55.670215  5581 caffe.cpp:501] detection_eval = 12.0867
-I0511 11:50:55.670217  5581 caffe.cpp:501] detection_eval = 0.0406962
-I0511 11:50:55.670219  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670222  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670224  5581 caffe.cpp:501] detection_eval = 5.71976
-I0511 11:50:55.670226  5581 caffe.cpp:501] detection_eval = 12.0302
-I0511 11:50:55.670228  5581 caffe.cpp:501] detection_eval = 0.0404774
-I0511 11:50:55.670230  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670233  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670235  5581 caffe.cpp:501] detection_eval = 5.72177
-I0511 11:50:55.670238  5581 caffe.cpp:501] detection_eval = 12.0927
-I0511 11:50:55.670239  5581 caffe.cpp:501] detection_eval = 0.0428298
-I0511 11:50:55.670241  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670244  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670246  5581 caffe.cpp:501] detection_eval = 5.72984
-I0511 11:50:55.670248  5581 caffe.cpp:501] detection_eval = 12.0383
-I0511 11:50:55.670250  5581 caffe.cpp:501] detection_eval = 0.0414953
-I0511 11:50:55.670253  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670255  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670258  5581 caffe.cpp:501] detection_eval = 5.72984
-I0511 11:50:55.670259  5581 caffe.cpp:501] detection_eval = 12.1129
-I0511 11:50:55.670262  5581 caffe.cpp:501] detection_eval = 0.0400972
-I0511 11:50:55.670264  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670266  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670269  5581 caffe.cpp:501] detection_eval = 5.73185
-I0511 11:50:55.670270  5581 caffe.cpp:501] detection_eval = 12.1512
-I0511 11:50:55.670274  5581 caffe.cpp:501] detection_eval = 0.040751
-I0511 11:50:55.670275  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670277  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670279  5581 caffe.cpp:501] detection_eval = 5.73589
-I0511 11:50:55.670281  5581 caffe.cpp:501] detection_eval = 12.1714
-I0511 11:50:55.670284  5581 caffe.cpp:501] detection_eval = 0.0410402
-I0511 11:50:55.670286  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670289  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670294  5581 caffe.cpp:501] detection_eval = 5.73589
-I0511 11:50:55.670295  5581 caffe.cpp:501] detection_eval = 12.2843
-I0511 11:50:55.670297  5581 caffe.cpp:501] detection_eval = 0.0396485
-I0511 11:50:55.670300  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.670302  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.670305  5581 caffe.cpp:501] detection_eval = 5.7379
-I0511 11:50:55.670306  5581 caffe.cpp:501] detection_eval = 12.3528
-I0511 11:50:55.670310  5581 caffe.cpp:501] detection_eval = 0.0383403
-I0511 11:50:55.670311  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670313  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670315  5581 caffe.cpp:501] detection_eval = 5.73992
-I0511 11:50:55.670317  5581 caffe.cpp:501] detection_eval = 12.3629
-I0511 11:50:55.670320  5581 caffe.cpp:501] detection_eval = 0.0364093
-I0511 11:50:55.670322  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.670325  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.670326  5581 caffe.cpp:501] detection_eval = 5.74194
-I0511 11:50:55.670328  5581 caffe.cpp:501] detection_eval = 12.3589
-I0511 11:50:55.670331  5581 caffe.cpp:501] detection_eval = 0.0348181
-I0511 11:50:55.670333  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670336  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670337  5581 caffe.cpp:501] detection_eval = 5.74194
-I0511 11:50:55.670339  5581 caffe.cpp:501] detection_eval = 12.4435
-I0511 11:50:55.670342  5581 caffe.cpp:501] detection_eval = 0.0372052
-I0511 11:50:55.670344  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.670346  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.670348  5581 caffe.cpp:501] detection_eval = 5.74395
-I0511 11:50:55.670351  5581 caffe.cpp:501] detection_eval = 12.4758
-I0511 11:50:55.670353  5581 caffe.cpp:501] detection_eval = 0.0411981
-I0511 11:50:55.670356  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670357  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670359  5581 caffe.cpp:501] detection_eval = 5.74597
-I0511 11:50:55.670361  5581 caffe.cpp:501] detection_eval = 12.5202
-I0511 11:50:55.670364  5581 caffe.cpp:501] detection_eval = 0.0401802
-I0511 11:50:55.670367  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670368  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670370  5581 caffe.cpp:501] detection_eval = 5.75
-I0511 11:50:55.670372  5581 caffe.cpp:501] detection_eval = 12.5685
-I0511 11:50:55.670375  5581 caffe.cpp:501] detection_eval = 0.0423118
-I0511 11:50:55.670377  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670379  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670382  5581 caffe.cpp:501] detection_eval = 5.75806
-I0511 11:50:55.670383  5581 caffe.cpp:501] detection_eval = 12.5544
-I0511 11:50:55.670387  5581 caffe.cpp:501] detection_eval = 0.0422818
-I0511 11:50:55.670388  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670390  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.670393  5581 caffe.cpp:501] detection_eval = 5.76411
-I0511 11:50:55.670395  5581 caffe.cpp:501] detection_eval = 12.5242
-I0511 11:50:55.670397  5581 caffe.cpp:501] detection_eval = 0.0396301
-I0511 11:50:55.670399  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670402  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670404  5581 caffe.cpp:501] detection_eval = 5.77016
-I0511 11:50:55.670406  5581 caffe.cpp:501] detection_eval = 12.502
-I0511 11:50:55.670408  5581 caffe.cpp:501] detection_eval = 0.0395042
-I0511 11:50:55.670410  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670413  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670415  5581 caffe.cpp:501] detection_eval = 5.77218
-I0511 11:50:55.670418  5581 caffe.cpp:501] detection_eval = 12.5625
-I0511 11:50:55.670419  5581 caffe.cpp:501] detection_eval = 0.0449169
-I0511 11:50:55.670421  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.670426  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670428  5581 caffe.cpp:501] detection_eval = 5.77419
-I0511 11:50:55.670430  5581 caffe.cpp:501] detection_eval = 12.6069
-I0511 11:50:55.670433  5581 caffe.cpp:501] detection_eval = 0.0452324
-I0511 11:50:55.670435  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670437  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670439  5581 caffe.cpp:501] detection_eval = 5.77419
-I0511 11:50:55.670441  5581 caffe.cpp:501] detection_eval = 12.6754
-I0511 11:50:55.670444  5581 caffe.cpp:501] detection_eval = 0.0440708
-I0511 11:50:55.670446  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.670449  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670450  5581 caffe.cpp:501] detection_eval = 5.78226
-I0511 11:50:55.670452  5581 caffe.cpp:501] detection_eval = 12.6694
-I0511 11:50:55.670455  5581 caffe.cpp:501] detection_eval = 0.0442899
-I0511 11:50:55.670457  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670459  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670461  5581 caffe.cpp:501] detection_eval = 5.78427
-I0511 11:50:55.670464  5581 caffe.cpp:501] detection_eval = 12.75
-I0511 11:50:55.670466  5581 caffe.cpp:501] detection_eval = 0.0428761
-I0511 11:50:55.670469  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670470  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670472  5581 caffe.cpp:501] detection_eval = 5.78831
-I0511 11:50:55.670475  5581 caffe.cpp:501] detection_eval = 12.7984
-I0511 11:50:55.670477  5581 caffe.cpp:501] detection_eval = 0.0431764
-I0511 11:50:55.670480  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670483  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670487  5581 caffe.cpp:501] detection_eval = 5.79234
-I0511 11:50:55.670491  5581 caffe.cpp:501] detection_eval = 12.9254
-I0511 11:50:55.670495  5581 caffe.cpp:501] detection_eval = 0.0473418
-I0511 11:50:55.670496  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670500  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670501  5581 caffe.cpp:501] detection_eval = 5.79435
-I0511 11:50:55.670503  5581 caffe.cpp:501] detection_eval = 13.1069
-I0511 11:50:55.670506  5581 caffe.cpp:501] detection_eval = 0.0430409
-I0511 11:50:55.670508  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670511  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670512  5581 caffe.cpp:501] detection_eval = 5.79839
-I0511 11:50:55.670514  5581 caffe.cpp:501] detection_eval = 13.2843
-I0511 11:50:55.670516  5581 caffe.cpp:501] detection_eval = 0.041264
-I0511 11:50:55.670519  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670521  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.670523  5581 caffe.cpp:501] detection_eval = 6.1754
-I0511 11:50:55.670526  5581 caffe.cpp:501] detection_eval = 7.66129
-I0511 11:50:55.670527  5581 caffe.cpp:501] detection_eval = 0.076982
-I0511 11:50:55.670529  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.670532  5581 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:50:55.670534  5581 caffe.cpp:501] detection_eval = 6.17742
-I0511 11:50:55.670536  5581 caffe.cpp:501] detection_eval = 7.8004
-I0511 11:50:55.670538  5581 caffe.cpp:501] detection_eval = 0.0611119
-I0511 11:50:55.670541  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.670543  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.670545  5581 caffe.cpp:501] detection_eval = 6.17742
-I0511 11:50:55.670547  5581 caffe.cpp:501] detection_eval = 7.93145
-I0511 11:50:55.670549  5581 caffe.cpp:501] detection_eval = 0.0522914
-I0511 11:50:55.670552  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.670553  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670555  5581 caffe.cpp:501] detection_eval = 6.17742
-I0511 11:50:55.670558  5581 caffe.cpp:501] detection_eval = 8.02419
-I0511 11:50:55.670560  5581 caffe.cpp:501] detection_eval = 0.0472921
-I0511 11:50:55.670562  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670567  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670569  5581 caffe.cpp:501] detection_eval = 6.18347
-I0511 11:50:55.670572  5581 caffe.cpp:501] detection_eval = 8.03629
-I0511 11:50:55.670573  5581 caffe.cpp:501] detection_eval = 0.0516428
-I0511 11:50:55.670575  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.670578  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.670580  5581 caffe.cpp:501] detection_eval = 6.18548
-I0511 11:50:55.670583  5581 caffe.cpp:501] detection_eval = 8.1371
-I0511 11:50:55.670584  5581 caffe.cpp:501] detection_eval = 0.0505285
-I0511 11:50:55.670586  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.670589  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670591  5581 caffe.cpp:501] detection_eval = 6.1875
-I0511 11:50:55.670593  5581 caffe.cpp:501] detection_eval = 8.19355
-I0511 11:50:55.670595  5581 caffe.cpp:501] detection_eval = 0.0476904
-I0511 11:50:55.670598  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.670599  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.670603  5581 caffe.cpp:501] detection_eval = 6.18952
-I0511 11:50:55.670604  5581 caffe.cpp:501] detection_eval = 8.24194
-I0511 11:50:55.670606  5581 caffe.cpp:501] detection_eval = 0.0466943
-I0511 11:50:55.670608  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.670610  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.670612  5581 caffe.cpp:501] detection_eval = 6.19153
-I0511 11:50:55.670615  5581 caffe.cpp:501] detection_eval = 8.26815
-I0511 11:50:55.670617  5581 caffe.cpp:501] detection_eval = 0.0453015
-I0511 11:50:55.670619  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670622  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670624  5581 caffe.cpp:501] detection_eval = 6.19758
-I0511 11:50:55.670626  5581 caffe.cpp:501] detection_eval = 8.23589
-I0511 11:50:55.670629  5581 caffe.cpp:501] detection_eval = 0.0449947
-I0511 11:50:55.670630  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670632  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670634  5581 caffe.cpp:501] detection_eval = 6.1996
-I0511 11:50:55.670637  5581 caffe.cpp:501] detection_eval = 8.31855
-I0511 11:50:55.670639  5581 caffe.cpp:501] detection_eval = 0.0454182
-I0511 11:50:55.670641  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670644  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670645  5581 caffe.cpp:501] detection_eval = 6.1996
-I0511 11:50:55.670647  5581 caffe.cpp:501] detection_eval = 8.37903
-I0511 11:50:55.670650  5581 caffe.cpp:501] detection_eval = 0.0448143
-I0511 11:50:55.670652  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670655  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670656  5581 caffe.cpp:501] detection_eval = 6.20161
-I0511 11:50:55.670658  5581 caffe.cpp:501] detection_eval = 8.39516
-I0511 11:50:55.670661  5581 caffe.cpp:501] detection_eval = 0.0511922
-I0511 11:50:55.670663  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.670665  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670667  5581 caffe.cpp:501] detection_eval = 6.20363
-I0511 11:50:55.670670  5581 caffe.cpp:501] detection_eval = 8.44153
-I0511 11:50:55.670672  5581 caffe.cpp:501] detection_eval = 0.0454235
-I0511 11:50:55.670675  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670676  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670678  5581 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:50:55.670680  5581 caffe.cpp:501] detection_eval = 8.51411
-I0511 11:50:55.670683  5581 caffe.cpp:501] detection_eval = 0.043053
-I0511 11:50:55.670686  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670687  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670689  5581 caffe.cpp:501] detection_eval = 6.20766
-I0511 11:50:55.670691  5581 caffe.cpp:501] detection_eval = 8.57056
-I0511 11:50:55.670693  5581 caffe.cpp:501] detection_eval = 0.0410455
-I0511 11:50:55.670698  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670701  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670703  5581 caffe.cpp:501] detection_eval = 6.20968
-I0511 11:50:55.670706  5581 caffe.cpp:501] detection_eval = 8.62298
-I0511 11:50:55.670707  5581 caffe.cpp:501] detection_eval = 0.0451681
-I0511 11:50:55.670711  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.670712  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.670717  5581 caffe.cpp:501] detection_eval = 6.20968
-I0511 11:50:55.670719  5581 caffe.cpp:501] detection_eval = 8.6875
-I0511 11:50:55.670722  5581 caffe.cpp:501] detection_eval = 0.0372051
-I0511 11:50:55.670728  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.670733  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.670737  5581 caffe.cpp:501] detection_eval = 6.21573
-I0511 11:50:55.670738  5581 caffe.cpp:501] detection_eval = 8.66734
-I0511 11:50:55.670740  5581 caffe.cpp:501] detection_eval = 0.0402002
-I0511 11:50:55.670742  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670745  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670747  5581 caffe.cpp:501] detection_eval = 6.21774
-I0511 11:50:55.670749  5581 caffe.cpp:501] detection_eval = 8.74395
-I0511 11:50:55.670752  5581 caffe.cpp:501] detection_eval = 0.0415073
-I0511 11:50:55.670754  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670756  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670758  5581 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:50:55.670760  5581 caffe.cpp:501] detection_eval = 8.72379
-I0511 11:50:55.670763  5581 caffe.cpp:501] detection_eval = 0.0389802
-I0511 11:50:55.670765  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670768  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670769  5581 caffe.cpp:501] detection_eval = 6.22379
-I0511 11:50:55.670771  5581 caffe.cpp:501] detection_eval = 8.7621
-I0511 11:50:55.670773  5581 caffe.cpp:501] detection_eval = 0.0355101
-I0511 11:50:55.670776  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.670778  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670780  5581 caffe.cpp:501] detection_eval = 6.22581
-I0511 11:50:55.670783  5581 caffe.cpp:501] detection_eval = 8.83266
-I0511 11:50:55.670784  5581 caffe.cpp:501] detection_eval = 0.041855
-I0511 11:50:55.670786  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670789  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670791  5581 caffe.cpp:501] detection_eval = 6.23992
-I0511 11:50:55.670794  5581 caffe.cpp:501] detection_eval = 8.65726
-I0511 11:50:55.670795  5581 caffe.cpp:501] detection_eval = 0.0365189
-I0511 11:50:55.670797  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670800  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670802  5581 caffe.cpp:501] detection_eval = 6.24597
-I0511 11:50:55.670804  5581 caffe.cpp:501] detection_eval = 8.70161
-I0511 11:50:55.670807  5581 caffe.cpp:501] detection_eval = 0.0387272
-I0511 11:50:55.670809  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670811  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670814  5581 caffe.cpp:501] detection_eval = 6.25202
-I0511 11:50:55.670815  5581 caffe.cpp:501] detection_eval = 8.73185
-I0511 11:50:55.670817  5581 caffe.cpp:501] detection_eval = 0.0477054
-I0511 11:50:55.670820  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.670822  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.670825  5581 caffe.cpp:501] detection_eval = 6.2621
-I0511 11:50:55.670826  5581 caffe.cpp:501] detection_eval = 8.65323
-I0511 11:50:55.670828  5581 caffe.cpp:501] detection_eval = 0.0480796
-I0511 11:50:55.670830  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670833  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.670835  5581 caffe.cpp:501] detection_eval = 6.26613
-I0511 11:50:55.670837  5581 caffe.cpp:501] detection_eval = 8.63508
-I0511 11:50:55.670840  5581 caffe.cpp:501] detection_eval = 0.0421389
-I0511 11:50:55.670845  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670847  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.670850  5581 caffe.cpp:501] detection_eval = 6.27016
-I0511 11:50:55.670851  5581 caffe.cpp:501] detection_eval = 8.64113
-I0511 11:50:55.670853  5581 caffe.cpp:501] detection_eval = 0.0429365
-I0511 11:50:55.670856  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.670858  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670861  5581 caffe.cpp:501] detection_eval = 6.27419
-I0511 11:50:55.670862  5581 caffe.cpp:501] detection_eval = 8.68548
-I0511 11:50:55.670866  5581 caffe.cpp:501] detection_eval = 0.0376349
-I0511 11:50:55.670867  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670869  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670871  5581 caffe.cpp:501] detection_eval = 6.27823
-I0511 11:50:55.670873  5581 caffe.cpp:501] detection_eval = 8.70565
-I0511 11:50:55.670876  5581 caffe.cpp:501] detection_eval = 0.0425564
-I0511 11:50:55.670878  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670881  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670882  5581 caffe.cpp:501] detection_eval = 6.28024
-I0511 11:50:55.670886  5581 caffe.cpp:501] detection_eval = 8.74395
-I0511 11:50:55.670887  5581 caffe.cpp:501] detection_eval = 0.0418464
-I0511 11:50:55.670889  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670892  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670893  5581 caffe.cpp:501] detection_eval = 6.28226
-I0511 11:50:55.670897  5581 caffe.cpp:501] detection_eval = 8.77621
-I0511 11:50:55.670898  5581 caffe.cpp:501] detection_eval = 0.0413275
-I0511 11:50:55.670900  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.670902  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.670904  5581 caffe.cpp:501] detection_eval = 6.28427
-I0511 11:50:55.670907  5581 caffe.cpp:501] detection_eval = 8.78226
-I0511 11:50:55.670909  5581 caffe.cpp:501] detection_eval = 0.0399679
-I0511 11:50:55.670912  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670913  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670915  5581 caffe.cpp:501] detection_eval = 6.28427
-I0511 11:50:55.670917  5581 caffe.cpp:501] detection_eval = 8.85887
-I0511 11:50:55.670919  5581 caffe.cpp:501] detection_eval = 0.0441443
-I0511 11:50:55.670922  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670924  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670927  5581 caffe.cpp:501] detection_eval = 6.28629
-I0511 11:50:55.670928  5581 caffe.cpp:501] detection_eval = 8.90927
-I0511 11:50:55.670930  5581 caffe.cpp:501] detection_eval = 0.0413302
-I0511 11:50:55.670933  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670935  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670938  5581 caffe.cpp:501] detection_eval = 6.28831
-I0511 11:50:55.670939  5581 caffe.cpp:501] detection_eval = 8.94556
-I0511 11:50:55.670941  5581 caffe.cpp:501] detection_eval = 0.0397936
-I0511 11:50:55.670943  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670946  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670948  5581 caffe.cpp:501] detection_eval = 6.28831
-I0511 11:50:55.670950  5581 caffe.cpp:501] detection_eval = 9.0121
-I0511 11:50:55.670953  5581 caffe.cpp:501] detection_eval = 0.0402532
-I0511 11:50:55.670954  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.670958  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.670959  5581 caffe.cpp:501] detection_eval = 6.29234
-I0511 11:50:55.670961  5581 caffe.cpp:501] detection_eval = 8.99597
-I0511 11:50:55.670964  5581 caffe.cpp:501] detection_eval = 0.040991
-I0511 11:50:55.670965  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.670967  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.670970  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.670972  5581 caffe.cpp:501] detection_eval = 9.01411
-I0511 11:50:55.670977  5581 caffe.cpp:501] detection_eval = 0.0375293
-I0511 11:50:55.670979  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670982  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.670984  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.670986  5581 caffe.cpp:501] detection_eval = 9.0746
-I0511 11:50:55.670989  5581 caffe.cpp:501] detection_eval = 0.0419776
-I0511 11:50:55.670990  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.670994  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.670995  5581 caffe.cpp:501] detection_eval = 6.29839
-I0511 11:50:55.670997  5581 caffe.cpp:501] detection_eval = 9.13306
-I0511 11:50:55.671000  5581 caffe.cpp:501] detection_eval = 0.0421072
-I0511 11:50:55.671001  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671005  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.671006  5581 caffe.cpp:501] detection_eval = 6.30242
-I0511 11:50:55.671008  5581 caffe.cpp:501] detection_eval = 9.12702
-I0511 11:50:55.671010  5581 caffe.cpp:501] detection_eval = 0.0413086
-I0511 11:50:55.671013  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.671015  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.671017  5581 caffe.cpp:501] detection_eval = 6.30645
-I0511 11:50:55.671020  5581 caffe.cpp:501] detection_eval = 9.17742
-I0511 11:50:55.671022  5581 caffe.cpp:501] detection_eval = 0.0431557
-I0511 11:50:55.671025  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671026  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671028  5581 caffe.cpp:501] detection_eval = 6.30645
-I0511 11:50:55.671030  5581 caffe.cpp:501] detection_eval = 9.25605
-I0511 11:50:55.671033  5581 caffe.cpp:501] detection_eval = 0.045073
-I0511 11:50:55.671036  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671037  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.671039  5581 caffe.cpp:501] detection_eval = 6.3125
-I0511 11:50:55.671042  5581 caffe.cpp:501] detection_eval = 9.25806
-I0511 11:50:55.671044  5581 caffe.cpp:501] detection_eval = 0.0464449
-I0511 11:50:55.671046  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671048  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671051  5581 caffe.cpp:501] detection_eval = 6.3125
-I0511 11:50:55.671053  5581 caffe.cpp:501] detection_eval = 9.3629
-I0511 11:50:55.671056  5581 caffe.cpp:501] detection_eval = 0.0388863
-I0511 11:50:55.671057  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.671059  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671061  5581 caffe.cpp:501] detection_eval = 6.31653
-I0511 11:50:55.671064  5581 caffe.cpp:501] detection_eval = 9.39718
-I0511 11:50:55.671066  5581 caffe.cpp:501] detection_eval = 0.0381406
-I0511 11:50:55.671068  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671314  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671329  5581 caffe.cpp:501] detection_eval = 6.32258
-I0511 11:50:55.671330  5581 caffe.cpp:501] detection_eval = 9.37903
-I0511 11:50:55.671332  5581 caffe.cpp:501] detection_eval = 0.0403081
-I0511 11:50:55.671335  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671337  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.671339  5581 caffe.cpp:501] detection_eval = 6.32258
-I0511 11:50:55.671342  5581 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:50:55.671344  5581 caffe.cpp:501] detection_eval = 0.0435655
-I0511 11:50:55.671346  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671349  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671350  5581 caffe.cpp:501] detection_eval = 6.32258
-I0511 11:50:55.671352  5581 caffe.cpp:501] detection_eval = 9.5625
-I0511 11:50:55.671355  5581 caffe.cpp:501] detection_eval = 0.0449686
-I0511 11:50:55.671357  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.671360  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.671361  5581 caffe.cpp:501] detection_eval = 6.32661
-I0511 11:50:55.671368  5581 caffe.cpp:501] detection_eval = 9.54435
-I0511 11:50:55.671371  5581 caffe.cpp:501] detection_eval = 0.0405597
-I0511 11:50:55.671373  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671375  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.671377  5581 caffe.cpp:501] detection_eval = 6.32661
-I0511 11:50:55.671380  5581 caffe.cpp:501] detection_eval = 9.62097
-I0511 11:50:55.671382  5581 caffe.cpp:501] detection_eval = 0.0419663
-I0511 11:50:55.671385  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.671386  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.671388  5581 caffe.cpp:501] detection_eval = 6.33266
-I0511 11:50:55.671391  5581 caffe.cpp:501] detection_eval = 9.62702
-I0511 11:50:55.671393  5581 caffe.cpp:501] detection_eval = 0.0426358
-I0511 11:50:55.671396  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671397  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671399  5581 caffe.cpp:501] detection_eval = 6.33266
-I0511 11:50:55.671401  5581 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:50:55.671403  5581 caffe.cpp:501] detection_eval = 0.041483
-I0511 11:50:55.671406  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.671408  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.671411  5581 caffe.cpp:501] detection_eval = 6.33468
-I0511 11:50:55.671412  5581 caffe.cpp:501] detection_eval = 9.74194
-I0511 11:50:55.671414  5581 caffe.cpp:501] detection_eval = 0.043737
-I0511 11:50:55.671416  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671419  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.671422  5581 caffe.cpp:501] detection_eval = 6.33669
-I0511 11:50:55.671423  5581 caffe.cpp:501] detection_eval = 9.75605
-I0511 11:50:55.671425  5581 caffe.cpp:501] detection_eval = 0.0428811
-I0511 11:50:55.671427  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671429  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671432  5581 caffe.cpp:501] detection_eval = 6.33871
-I0511 11:50:55.671434  5581 caffe.cpp:501] detection_eval = 9.85282
-I0511 11:50:55.671437  5581 caffe.cpp:501] detection_eval = 0.0469635
-I0511 11:50:55.671438  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671440  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.671442  5581 caffe.cpp:501] detection_eval = 6.34073
-I0511 11:50:55.671444  5581 caffe.cpp:501] detection_eval = 9.89718
-I0511 11:50:55.671447  5581 caffe.cpp:501] detection_eval = 0.0461667
-I0511 11:50:55.671449  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671452  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671453  5581 caffe.cpp:501] detection_eval = 6.34274
-I0511 11:50:55.671455  5581 caffe.cpp:501] detection_eval = 9.95363
-I0511 11:50:55.671458  5581 caffe.cpp:501] detection_eval = 0.0466406
-I0511 11:50:55.671460  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671463  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671464  5581 caffe.cpp:501] detection_eval = 6.34879
-I0511 11:50:55.671466  5581 caffe.cpp:501] detection_eval = 9.95161
-I0511 11:50:55.671468  5581 caffe.cpp:501] detection_eval = 0.0466964
-I0511 11:50:55.671471  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.671473  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.671475  5581 caffe.cpp:501] detection_eval = 6.35282
-I0511 11:50:55.671478  5581 caffe.cpp:501] detection_eval = 9.96169
-I0511 11:50:55.671479  5581 caffe.cpp:501] detection_eval = 0.0472965
-I0511 11:50:55.671481  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.671484  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.671486  5581 caffe.cpp:501] detection_eval = 6.35484
-I0511 11:50:55.671489  5581 caffe.cpp:501] detection_eval = 10
-I0511 11:50:55.671490  5581 caffe.cpp:501] detection_eval = 0.0437015
-I0511 11:50:55.671494  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671495  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.671497  5581 caffe.cpp:501] detection_eval = 6.36089
-I0511 11:50:55.671502  5581 caffe.cpp:501] detection_eval = 9.98185
-I0511 11:50:55.671504  5581 caffe.cpp:501] detection_eval = 0.0436494
-I0511 11:50:55.671507  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.671509  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671511  5581 caffe.cpp:501] detection_eval = 6.3629
-I0511 11:50:55.671514  5581 caffe.cpp:501] detection_eval = 10.0222
-I0511 11:50:55.671516  5581 caffe.cpp:501] detection_eval = 0.0393048
-I0511 11:50:55.671519  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.671520  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.671522  5581 caffe.cpp:501] detection_eval = 6.36694
-I0511 11:50:55.671525  5581 caffe.cpp:501] detection_eval = 10.0927
-I0511 11:50:55.671527  5581 caffe.cpp:501] detection_eval = 0.0493265
-I0511 11:50:55.671530  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.671531  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.671533  5581 caffe.cpp:501] detection_eval = 6.37097
-I0511 11:50:55.671535  5581 caffe.cpp:501] detection_eval = 10.1351
-I0511 11:50:55.671538  5581 caffe.cpp:501] detection_eval = 0.0468921
-I0511 11:50:55.671540  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.671542  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.671545  5581 caffe.cpp:501] detection_eval = 6.37097
-I0511 11:50:55.671546  5581 caffe.cpp:501] detection_eval = 10.1976
-I0511 11:50:55.671550  5581 caffe.cpp:501] detection_eval = 0.0425419
-I0511 11:50:55.671551  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.671553  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.671555  5581 caffe.cpp:501] detection_eval = 6.37097
-I0511 11:50:55.671557  5581 caffe.cpp:501] detection_eval = 10.2702
-I0511 11:50:55.671561  5581 caffe.cpp:501] detection_eval = 0.0398125
-I0511 11:50:55.671562  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.671564  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.671566  5581 caffe.cpp:501] detection_eval = 6.38105
-I0511 11:50:55.671568  5581 caffe.cpp:501] detection_eval = 10.2339
-I0511 11:50:55.671571  5581 caffe.cpp:501] detection_eval = 0.0415377
-I0511 11:50:55.671573  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.671576  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.671577  5581 caffe.cpp:501] detection_eval = 6.3871
-I0511 11:50:55.671579  5581 caffe.cpp:501] detection_eval = 10.2077
-I0511 11:50:55.671582  5581 caffe.cpp:501] detection_eval = 0.0431371
-I0511 11:50:55.671584  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.671586  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.671588  5581 caffe.cpp:501] detection_eval = 6.39516
-I0511 11:50:55.671591  5581 caffe.cpp:501] detection_eval = 10.2036
-I0511 11:50:55.672657  5581 caffe.cpp:501] detection_eval = 0.0418587
-I0511 11:50:55.672663  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.672667  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.672672  5581 caffe.cpp:501] detection_eval = 6.39919
-I0511 11:50:55.672675  5581 caffe.cpp:501] detection_eval = 10.2581
-I0511 11:50:55.672679  5581 caffe.cpp:501] detection_eval = 0.0437859
-I0511 11:50:55.672683  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.672686  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672689  5581 caffe.cpp:501] detection_eval = 6.40726
-I0511 11:50:55.672693  5581 caffe.cpp:501] detection_eval = 10.244
-I0511 11:50:55.672696  5581 caffe.cpp:501] detection_eval = 0.0470156
-I0511 11:50:55.672699  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.672703  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.672708  5581 caffe.cpp:501] detection_eval = 6.40927
-I0511 11:50:55.672711  5581 caffe.cpp:501] detection_eval = 10.2843
-I0511 11:50:55.672715  5581 caffe.cpp:501] detection_eval = 0.0422535
-I0511 11:50:55.672719  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.672722  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672731  5581 caffe.cpp:501] detection_eval = 6.41129
-I0511 11:50:55.672735  5581 caffe.cpp:501] detection_eval = 10.3871
-I0511 11:50:55.672739  5581 caffe.cpp:501] detection_eval = 0.0487919
-I0511 11:50:55.672742  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.672746  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.672750  5581 caffe.cpp:501] detection_eval = 6.41734
-I0511 11:50:55.672755  5581 caffe.cpp:501] detection_eval = 10.4133
-I0511 11:50:55.672757  5581 caffe.cpp:501] detection_eval = 0.0452637
-I0511 11:50:55.672761  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.672765  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.672770  5581 caffe.cpp:501] detection_eval = 6.4254
-I0511 11:50:55.672772  5581 caffe.cpp:501] detection_eval = 10.3468
-I0511 11:50:55.672776  5581 caffe.cpp:501] detection_eval = 0.0409249
-I0511 11:50:55.672780  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.672783  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.672786  5581 caffe.cpp:501] detection_eval = 6.42944
-I0511 11:50:55.672789  5581 caffe.cpp:501] detection_eval = 10.3407
-I0511 11:50:55.672794  5581 caffe.cpp:501] detection_eval = 0.0460814
-I0511 11:50:55.672797  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.672801  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.672806  5581 caffe.cpp:501] detection_eval = 6.4375
-I0511 11:50:55.672808  5581 caffe.cpp:501] detection_eval = 10.2782
-I0511 11:50:55.672812  5581 caffe.cpp:501] detection_eval = 0.0408642
-I0511 11:50:55.672816  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672821  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.672823  5581 caffe.cpp:501] detection_eval = 6.43952
-I0511 11:50:55.672827  5581 caffe.cpp:501] detection_eval = 10.3024
-I0511 11:50:55.672832  5581 caffe.cpp:501] detection_eval = 0.0417377
-I0511 11:50:55.672835  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672839  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672842  5581 caffe.cpp:501] detection_eval = 6.43952
-I0511 11:50:55.672847  5581 caffe.cpp:501] detection_eval = 10.3669
-I0511 11:50:55.672850  5581 caffe.cpp:501] detection_eval = 0.0402777
-I0511 11:50:55.672853  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.672857  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672861  5581 caffe.cpp:501] detection_eval = 6.44758
-I0511 11:50:55.672864  5581 caffe.cpp:501] detection_eval = 10.3488
-I0511 11:50:55.672868  5581 caffe.cpp:501] detection_eval = 0.0426006
-I0511 11:50:55.672871  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672874  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.672878  5581 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:50:55.672883  5581 caffe.cpp:501] detection_eval = 10.4113
-I0511 11:50:55.672886  5581 caffe.cpp:501] detection_eval = 0.0435831
-I0511 11:50:55.672890  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672894  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.672897  5581 caffe.cpp:501] detection_eval = 6.45766
-I0511 11:50:55.672901  5581 caffe.cpp:501] detection_eval = 10.3468
-I0511 11:50:55.672905  5581 caffe.cpp:501] detection_eval = 0.0409441
-I0511 11:50:55.672909  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.672912  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.672916  5581 caffe.cpp:501] detection_eval = 6.45968
-I0511 11:50:55.672920  5581 caffe.cpp:501] detection_eval = 10.3629
-I0511 11:50:55.672924  5581 caffe.cpp:501] detection_eval = 0.0370585
-I0511 11:50:55.672927  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.672931  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.672935  5581 caffe.cpp:501] detection_eval = 6.46573
-I0511 11:50:55.672938  5581 caffe.cpp:501] detection_eval = 10.3831
-I0511 11:50:55.672942  5581 caffe.cpp:501] detection_eval = 0.0436748
-I0511 11:50:55.672946  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.672950  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.672956  5581 caffe.cpp:501] detection_eval = 6.46976
-I0511 11:50:55.672960  5581 caffe.cpp:501] detection_eval = 10.4617
-I0511 11:50:55.672965  5581 caffe.cpp:501] detection_eval = 0.0420634
-I0511 11:50:55.672968  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.672972  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.672976  5581 caffe.cpp:501] detection_eval = 6.47177
-I0511 11:50:55.672979  5581 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:50:55.672983  5581 caffe.cpp:501] detection_eval = 0.0396105
-I0511 11:50:55.672987  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.672991  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.672994  5581 caffe.cpp:501] detection_eval = 6.47177
-I0511 11:50:55.672998  5581 caffe.cpp:501] detection_eval = 10.5504
-I0511 11:50:55.673002  5581 caffe.cpp:501] detection_eval = 0.0455037
-I0511 11:50:55.673005  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.673009  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.673013  5581 caffe.cpp:501] detection_eval = 6.47984
-I0511 11:50:55.673017  5581 caffe.cpp:501] detection_eval = 10.5121
-I0511 11:50:55.673020  5581 caffe.cpp:501] detection_eval = 0.0397872
-I0511 11:50:55.673024  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.673028  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.673032  5581 caffe.cpp:501] detection_eval = 6.48387
-I0511 11:50:55.673035  5581 caffe.cpp:501] detection_eval = 10.5625
-I0511 11:50:55.673038  5581 caffe.cpp:501] detection_eval = 0.0478975
-I0511 11:50:55.673041  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.673045  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.673049  5581 caffe.cpp:501] detection_eval = 6.48589
-I0511 11:50:55.673053  5581 caffe.cpp:501] detection_eval = 10.5988
-I0511 11:50:55.673056  5581 caffe.cpp:501] detection_eval = 0.0457368
-I0511 11:50:55.673060  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.673064  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.673068  5581 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:50:55.673071  5581 caffe.cpp:501] detection_eval = 10.6472
-I0511 11:50:55.673075  5581 caffe.cpp:501] detection_eval = 0.0450222
-I0511 11:50:55.673079  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.673082  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.673086  5581 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:50:55.673090  5581 caffe.cpp:501] detection_eval = 10.5645
-I0511 11:50:55.673094  5581 caffe.cpp:501] detection_eval = 0.0388435
-I0511 11:50:55.673097  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.673101  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.676645  5581 caffe.cpp:501] detection_eval = 6.5
-I0511 11:50:55.676661  5581 caffe.cpp:501] detection_eval = 10.6008
-I0511 11:50:55.676666  5581 caffe.cpp:501] detection_eval = 0.0386242
-I0511 11:50:55.676671  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.676674  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.676677  5581 caffe.cpp:501] detection_eval = 6.50403
-I0511 11:50:55.676681  5581 caffe.cpp:501] detection_eval = 10.5887
-I0511 11:50:55.676686  5581 caffe.cpp:501] detection_eval = 0.0385548
-I0511 11:50:55.676689  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.676693  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.676697  5581 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:50:55.676702  5581 caffe.cpp:501] detection_eval = 10.4677
-I0511 11:50:55.676705  5581 caffe.cpp:501] detection_eval = 0.0414124
-I0511 11:50:55.676709  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.676713  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.676717  5581 caffe.cpp:501] detection_eval = 6.52218
-I0511 11:50:55.676722  5581 caffe.cpp:501] detection_eval = 10.5
-I0511 11:50:55.676725  5581 caffe.cpp:501] detection_eval = 0.0490748
-I0511 11:50:55.676730  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.676744  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.676749  5581 caffe.cpp:501] detection_eval = 6.53024
-I0511 11:50:55.676753  5581 caffe.cpp:501] detection_eval = 10.4194
-I0511 11:50:55.676757  5581 caffe.cpp:501] detection_eval = 0.0412619
-I0511 11:50:55.676761  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.676765  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.676769  5581 caffe.cpp:501] detection_eval = 6.54032
-I0511 11:50:55.676774  5581 caffe.cpp:501] detection_eval = 10.3649
-I0511 11:50:55.676777  5581 caffe.cpp:501] detection_eval = 0.0379293
-I0511 11:50:55.676781  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.676786  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676791  5581 caffe.cpp:501] detection_eval = 6.54032
-I0511 11:50:55.676796  5581 caffe.cpp:501] detection_eval = 10.4738
-I0511 11:50:55.676801  5581 caffe.cpp:501] detection_eval = 0.0394541
-I0511 11:50:55.676807  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.676811  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676816  5581 caffe.cpp:501] detection_eval = 6.54234
-I0511 11:50:55.676821  5581 caffe.cpp:501] detection_eval = 10.5605
-I0511 11:50:55.676826  5581 caffe.cpp:501] detection_eval = 0.0442708
-I0511 11:50:55.676831  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.676834  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.676838  5581 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:50:55.676841  5581 caffe.cpp:501] detection_eval = 10.5323
-I0511 11:50:55.676846  5581 caffe.cpp:501] detection_eval = 0.0391731
-I0511 11:50:55.676849  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.676853  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676857  5581 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:50:55.676862  5581 caffe.cpp:501] detection_eval = 10.625
-I0511 11:50:55.676864  5581 caffe.cpp:501] detection_eval = 0.0472549
-I0511 11:50:55.676867  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.676869  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.676872  5581 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:50:55.676873  5581 caffe.cpp:501] detection_eval = 10.7117
-I0511 11:50:55.676875  5581 caffe.cpp:501] detection_eval = 0.0440087
-I0511 11:50:55.676878  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.676880  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.676882  5581 caffe.cpp:501] detection_eval = 6.55444
-I0511 11:50:55.676884  5581 caffe.cpp:501] detection_eval = 10.7863
-I0511 11:50:55.676887  5581 caffe.cpp:501] detection_eval = 0.0437509
-I0511 11:50:55.676889  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.676892  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.676893  5581 caffe.cpp:501] detection_eval = 6.55847
-I0511 11:50:55.676895  5581 caffe.cpp:501] detection_eval = 10.8246
-I0511 11:50:55.676898  5581 caffe.cpp:501] detection_eval = 0.0438239
-I0511 11:50:55.676900  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.676903  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.676904  5581 caffe.cpp:501] detection_eval = 6.56048
-I0511 11:50:55.676906  5581 caffe.cpp:501] detection_eval = 10.9597
-I0511 11:50:55.676909  5581 caffe.cpp:501] detection_eval = 0.0470999
-I0511 11:50:55.676911  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.676913  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.676915  5581 caffe.cpp:501] detection_eval = 6.5625
-I0511 11:50:55.676918  5581 caffe.cpp:501] detection_eval = 10.9778
-I0511 11:50:55.676920  5581 caffe.cpp:501] detection_eval = 0.0391168
-I0511 11:50:55.676923  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.676924  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676926  5581 caffe.cpp:501] detection_eval = 6.5625
-I0511 11:50:55.676928  5581 caffe.cpp:501] detection_eval = 11.0524
-I0511 11:50:55.676931  5581 caffe.cpp:501] detection_eval = 0.0409669
-I0511 11:50:55.676937  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.676940  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.676942  5581 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:50:55.676944  5581 caffe.cpp:501] detection_eval = 11.1149
-I0511 11:50:55.676946  5581 caffe.cpp:501] detection_eval = 0.0414753
-I0511 11:50:55.676949  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.676951  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.676954  5581 caffe.cpp:501] detection_eval = 6.56653
-I0511 11:50:55.676955  5581 caffe.cpp:501] detection_eval = 11.1391
-I0511 11:50:55.676957  5581 caffe.cpp:501] detection_eval = 0.0385771
-I0511 11:50:55.676960  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.676962  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.676964  5581 caffe.cpp:501] detection_eval = 6.56653
-I0511 11:50:55.676966  5581 caffe.cpp:501] detection_eval = 11.2177
-I0511 11:50:55.676968  5581 caffe.cpp:501] detection_eval = 0.0447229
-I0511 11:50:55.676971  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.676973  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.676975  5581 caffe.cpp:501] detection_eval = 6.5746
-I0511 11:50:55.676977  5581 caffe.cpp:501] detection_eval = 11.2177
-I0511 11:50:55.676980  5581 caffe.cpp:501] detection_eval = 0.0430438
-I0511 11:50:55.676982  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.676985  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.676986  5581 caffe.cpp:501] detection_eval = 6.57863
-I0511 11:50:55.676988  5581 caffe.cpp:501] detection_eval = 11.2601
-I0511 11:50:55.676990  5581 caffe.cpp:501] detection_eval = 0.0434762
-I0511 11:50:55.676992  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.676995  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.676997  5581 caffe.cpp:501] detection_eval = 6.58266
-I0511 11:50:55.677000  5581 caffe.cpp:501] detection_eval = 11.2964
-I0511 11:50:55.677001  5581 caffe.cpp:501] detection_eval = 0.0451837
-I0511 11:50:55.677003  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.677006  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.677008  5581 caffe.cpp:501] detection_eval = 6.58669
-I0511 11:50:55.677011  5581 caffe.cpp:501] detection_eval = 11.3528
-I0511 11:50:55.677012  5581 caffe.cpp:501] detection_eval = 0.0427262
-I0511 11:50:55.677014  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.677017  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.677019  5581 caffe.cpp:501] detection_eval = 6.59476
-I0511 11:50:55.677021  5581 caffe.cpp:501] detection_eval = 11.3266
-I0511 11:50:55.677023  5581 caffe.cpp:501] detection_eval = 0.0412815
-I0511 11:50:55.680585  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680595  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680599  5581 caffe.cpp:501] detection_eval = 6.59879
-I0511 11:50:55.680603  5581 caffe.cpp:501] detection_eval = 11.3609
-I0511 11:50:55.680606  5581 caffe.cpp:501] detection_eval = 0.0484833
-I0511 11:50:55.680610  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.680613  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.680616  5581 caffe.cpp:501] detection_eval = 6.60081
-I0511 11:50:55.680620  5581 caffe.cpp:501] detection_eval = 11.371
-I0511 11:50:55.680624  5581 caffe.cpp:501] detection_eval = 0.0438451
-I0511 11:50:55.680627  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.680630  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.680634  5581 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:50:55.680637  5581 caffe.cpp:501] detection_eval = 11.371
-I0511 11:50:55.680640  5581 caffe.cpp:501] detection_eval = 0.0414156
-I0511 11:50:55.680644  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.680647  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.680650  5581 caffe.cpp:501] detection_eval = 6.60685
-I0511 11:50:55.680654  5581 caffe.cpp:501] detection_eval = 11.4194
-I0511 11:50:55.680657  5581 caffe.cpp:501] detection_eval = 0.037859
-I0511 11:50:55.680666  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680670  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680672  5581 caffe.cpp:501] detection_eval = 6.6129
-I0511 11:50:55.680675  5581 caffe.cpp:501] detection_eval = 11.4032
-I0511 11:50:55.680677  5581 caffe.cpp:501] detection_eval = 0.0393683
-I0511 11:50:55.680680  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680685  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680687  5581 caffe.cpp:501] detection_eval = 6.61694
-I0511 11:50:55.680691  5581 caffe.cpp:501] detection_eval = 11.4617
-I0511 11:50:55.680694  5581 caffe.cpp:501] detection_eval = 0.0462445
-I0511 11:50:55.680697  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.680701  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.680703  5581 caffe.cpp:501] detection_eval = 6.61694
-I0511 11:50:55.680706  5581 caffe.cpp:501] detection_eval = 11.5081
-I0511 11:50:55.680711  5581 caffe.cpp:501] detection_eval = 0.0451816
-I0511 11:50:55.680713  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680717  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.680721  5581 caffe.cpp:501] detection_eval = 6.61694
-I0511 11:50:55.680723  5581 caffe.cpp:501] detection_eval = 11.5383
-I0511 11:50:55.680727  5581 caffe.cpp:501] detection_eval = 0.0431461
-I0511 11:50:55.680730  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680734  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680737  5581 caffe.cpp:501] detection_eval = 6.62097
-I0511 11:50:55.680740  5581 caffe.cpp:501] detection_eval = 11.5141
-I0511 11:50:55.680743  5581 caffe.cpp:501] detection_eval = 0.0417651
-I0511 11:50:55.680747  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680750  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680753  5581 caffe.cpp:501] detection_eval = 6.62702
-I0511 11:50:55.680757  5581 caffe.cpp:501] detection_eval = 11.5242
-I0511 11:50:55.680760  5581 caffe.cpp:501] detection_eval = 0.0376938
-I0511 11:50:55.680763  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.680766  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.680770  5581 caffe.cpp:501] detection_eval = 6.63105
-I0511 11:50:55.680773  5581 caffe.cpp:501] detection_eval = 11.5867
-I0511 11:50:55.680778  5581 caffe.cpp:501] detection_eval = 0.0394057
-I0511 11:50:55.680780  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680783  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680786  5581 caffe.cpp:501] detection_eval = 6.63306
-I0511 11:50:55.680789  5581 caffe.cpp:501] detection_eval = 11.6613
-I0511 11:50:55.680794  5581 caffe.cpp:501] detection_eval = 0.0416283
-I0511 11:50:55.680797  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680800  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680804  5581 caffe.cpp:501] detection_eval = 6.63508
-I0511 11:50:55.680807  5581 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:50:55.680810  5581 caffe.cpp:501] detection_eval = 0.0394006
-I0511 11:50:55.680814  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680816  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.680820  5581 caffe.cpp:501] detection_eval = 6.64113
-I0511 11:50:55.680824  5581 caffe.cpp:501] detection_eval = 11.6774
-I0511 11:50:55.680826  5581 caffe.cpp:501] detection_eval = 0.0416138
-I0511 11:50:55.680829  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680830  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.680833  5581 caffe.cpp:501] detection_eval = 6.64718
-I0511 11:50:55.680836  5581 caffe.cpp:501] detection_eval = 11.6512
-I0511 11:50:55.680840  5581 caffe.cpp:501] detection_eval = 0.0441298
-I0511 11:50:55.680843  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.680846  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.680850  5581 caffe.cpp:501] detection_eval = 6.65323
-I0511 11:50:55.680852  5581 caffe.cpp:501] detection_eval = 11.6613
-I0511 11:50:55.680860  5581 caffe.cpp:501] detection_eval = 0.040598
-I0511 11:50:55.680863  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.680867  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.680871  5581 caffe.cpp:501] detection_eval = 6.65726
-I0511 11:50:55.680873  5581 caffe.cpp:501] detection_eval = 11.6653
-I0511 11:50:55.680877  5581 caffe.cpp:501] detection_eval = 0.0421925
-I0511 11:50:55.680881  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.680883  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680886  5581 caffe.cpp:501] detection_eval = 6.66331
-I0511 11:50:55.680889  5581 caffe.cpp:501] detection_eval = 11.6331
-I0511 11:50:55.680893  5581 caffe.cpp:501] detection_eval = 0.0367033
-I0511 11:50:55.680896  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.680900  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680903  5581 caffe.cpp:501] detection_eval = 6.66532
-I0511 11:50:55.680907  5581 caffe.cpp:501] detection_eval = 11.6452
-I0511 11:50:55.680910  5581 caffe.cpp:501] detection_eval = 0.0413331
-I0511 11:50:55.680913  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.680917  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.680920  5581 caffe.cpp:501] detection_eval = 6.66734
-I0511 11:50:55.680923  5581 caffe.cpp:501] detection_eval = 11.6552
-I0511 11:50:55.680927  5581 caffe.cpp:501] detection_eval = 0.0404099
-I0511 11:50:55.680929  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.680933  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.680936  5581 caffe.cpp:501] detection_eval = 6.67137
-I0511 11:50:55.680939  5581 caffe.cpp:501] detection_eval = 11.6371
-I0511 11:50:55.680943  5581 caffe.cpp:501] detection_eval = 0.0405138
-I0511 11:50:55.680946  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.680949  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.680953  5581 caffe.cpp:501] detection_eval = 6.67137
-I0511 11:50:55.680956  5581 caffe.cpp:501] detection_eval = 11.6956
-I0511 11:50:55.680959  5581 caffe.cpp:501] detection_eval = 0.0369072
-I0511 11:50:55.680963  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680966  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.680969  5581 caffe.cpp:501] detection_eval = 6.68145
-I0511 11:50:55.680974  5581 caffe.cpp:501] detection_eval = 11.6149
-I0511 11:50:55.680975  5581 caffe.cpp:501] detection_eval = 0.0393978
-I0511 11:50:55.680977  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.680979  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.680984  5581 caffe.cpp:501] detection_eval = 6.68548
-I0511 11:50:55.680986  5581 caffe.cpp:501] detection_eval = 11.6472
-I0511 11:50:55.680990  5581 caffe.cpp:501] detection_eval = 0.042582
-I0511 11:50:55.680994  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.680996  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681000  5581 caffe.cpp:501] detection_eval = 6.68952
-I0511 11:50:55.681004  5581 caffe.cpp:501] detection_eval = 11.6835
-I0511 11:50:55.681007  5581 caffe.cpp:501] detection_eval = 0.0463598
-I0511 11:50:55.681010  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.681011  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.681013  5581 caffe.cpp:501] detection_eval = 6.68952
-I0511 11:50:55.681017  5581 caffe.cpp:501] detection_eval = 11.744
-I0511 11:50:55.681020  5581 caffe.cpp:501] detection_eval = 0.0451782
-I0511 11:50:55.681022  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.681025  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.681027  5581 caffe.cpp:501] detection_eval = 6.69355
-I0511 11:50:55.681030  5581 caffe.cpp:501] detection_eval = 11.7722
-I0511 11:50:55.681032  5581 caffe.cpp:501] detection_eval = 0.0414692
-I0511 11:50:55.681035  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681036  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681040  5581 caffe.cpp:501] detection_eval = 6.69355
-I0511 11:50:55.681044  5581 caffe.cpp:501] detection_eval = 11.8085
-I0511 11:50:55.681046  5581 caffe.cpp:501] detection_eval = 0.0398301
-I0511 11:50:55.681048  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681051  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681053  5581 caffe.cpp:501] detection_eval = 6.69758
-I0511 11:50:55.681056  5581 caffe.cpp:501] detection_eval = 11.8024
-I0511 11:50:55.681057  5581 caffe.cpp:501] detection_eval = 0.0399019
-I0511 11:50:55.681059  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681061  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.681064  5581 caffe.cpp:501] detection_eval = 6.70363
-I0511 11:50:55.681066  5581 caffe.cpp:501] detection_eval = 11.7863
-I0511 11:50:55.681068  5581 caffe.cpp:501] detection_eval = 0.0409525
-I0511 11:50:55.681071  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681073  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681076  5581 caffe.cpp:501] detection_eval = 6.70363
-I0511 11:50:55.681077  5581 caffe.cpp:501] detection_eval = 11.8508
-I0511 11:50:55.681079  5581 caffe.cpp:501] detection_eval = 0.0380396
-I0511 11:50:55.681082  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681084  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681087  5581 caffe.cpp:501] detection_eval = 6.70968
-I0511 11:50:55.681088  5581 caffe.cpp:501] detection_eval = 11.8165
-I0511 11:50:55.681092  5581 caffe.cpp:501] detection_eval = 0.0388819
-I0511 11:50:55.681093  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681095  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681097  5581 caffe.cpp:501] detection_eval = 6.71371
-I0511 11:50:55.681099  5581 caffe.cpp:501] detection_eval = 11.8508
-I0511 11:50:55.681102  5581 caffe.cpp:501] detection_eval = 0.0387082
-I0511 11:50:55.681104  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681107  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681108  5581 caffe.cpp:501] detection_eval = 6.72177
-I0511 11:50:55.681110  5581 caffe.cpp:501] detection_eval = 11.8367
-I0511 11:50:55.681113  5581 caffe.cpp:501] detection_eval = 0.0440489
-I0511 11:50:55.681115  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681118  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681119  5581 caffe.cpp:501] detection_eval = 6.72581
-I0511 11:50:55.681121  5581 caffe.cpp:501] detection_eval = 11.8286
-I0511 11:50:55.681124  5581 caffe.cpp:501] detection_eval = 0.0400435
-I0511 11:50:55.681126  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681128  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681130  5581 caffe.cpp:501] detection_eval = 6.73387
-I0511 11:50:55.681133  5581 caffe.cpp:501] detection_eval = 11.8105
-I0511 11:50:55.681135  5581 caffe.cpp:501] detection_eval = 0.0408022
-I0511 11:50:55.681138  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681139  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681141  5581 caffe.cpp:501] detection_eval = 6.74395
-I0511 11:50:55.681143  5581 caffe.cpp:501] detection_eval = 11.7097
-I0511 11:50:55.681146  5581 caffe.cpp:501] detection_eval = 0.0409307
-I0511 11:50:55.681149  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681150  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681152  5581 caffe.cpp:501] detection_eval = 6.74597
-I0511 11:50:55.681154  5581 caffe.cpp:501] detection_eval = 11.7016
-I0511 11:50:55.681157  5581 caffe.cpp:501] detection_eval = 0.0338636
-I0511 11:50:55.681159  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.681161  5581 caffe.cpp:501] detection_eval = 0.997984
-I0511 11:50:55.681164  5581 caffe.cpp:501] detection_eval = 6.75
-I0511 11:50:55.681165  5581 caffe.cpp:501] detection_eval = 11.6895
-I0511 11:50:55.681169  5581 caffe.cpp:501] detection_eval = 0.0394032
-I0511 11:50:55.681170  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681172  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681174  5581 caffe.cpp:501] detection_eval = 6.75
-I0511 11:50:55.681180  5581 caffe.cpp:501] detection_eval = 11.75
-I0511 11:50:55.681181  5581 caffe.cpp:501] detection_eval = 0.0362908
-I0511 11:50:55.681185  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681186  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681188  5581 caffe.cpp:501] detection_eval = 6.75403
-I0511 11:50:55.681190  5581 caffe.cpp:501] detection_eval = 11.754
-I0511 11:50:55.681193  5581 caffe.cpp:501] detection_eval = 0.0392379
-I0511 11:50:55.681195  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681197  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681200  5581 caffe.cpp:501] detection_eval = 6.75403
-I0511 11:50:55.681201  5581 caffe.cpp:501] detection_eval = 11.869
-I0511 11:50:55.681205  5581 caffe.cpp:501] detection_eval = 0.0458373
-I0511 11:50:55.681206  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681208  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681210  5581 caffe.cpp:501] detection_eval = 6.75605
-I0511 11:50:55.681212  5581 caffe.cpp:501] detection_eval = 11.8992
-I0511 11:50:55.681215  5581 caffe.cpp:501] detection_eval = 0.0346768
-I0511 11:50:55.681217  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681219  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681221  5581 caffe.cpp:501] detection_eval = 6.76008
-I0511 11:50:55.681223  5581 caffe.cpp:501] detection_eval = 11.875
-I0511 11:50:55.681226  5581 caffe.cpp:501] detection_eval = 0.0334062
-I0511 11:50:55.681227  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681231  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681232  5581 caffe.cpp:501] detection_eval = 6.77218
-I0511 11:50:55.681234  5581 caffe.cpp:501] detection_eval = 11.8024
-I0511 11:50:55.681236  5581 caffe.cpp:501] detection_eval = 0.0393263
-I0511 11:50:55.681238  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681241  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681243  5581 caffe.cpp:501] detection_eval = 6.77419
-I0511 11:50:55.681246  5581 caffe.cpp:501] detection_eval = 11.8185
-I0511 11:50:55.681247  5581 caffe.cpp:501] detection_eval = 0.0362455
-I0511 11:50:55.681249  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681252  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681253  5581 caffe.cpp:501] detection_eval = 6.77823
-I0511 11:50:55.681257  5581 caffe.cpp:501] detection_eval = 11.7863
-I0511 11:50:55.681258  5581 caffe.cpp:501] detection_eval = 0.0368334
-I0511 11:50:55.681260  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681263  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681265  5581 caffe.cpp:501] detection_eval = 6.79032
-I0511 11:50:55.681267  5581 caffe.cpp:501] detection_eval = 11.6734
-I0511 11:50:55.681269  5581 caffe.cpp:501] detection_eval = 0.0370783
-I0511 11:50:55.681272  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681274  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681277  5581 caffe.cpp:501] detection_eval = 6.79637
-I0511 11:50:55.681278  5581 caffe.cpp:501] detection_eval = 11.6452
-I0511 11:50:55.681280  5581 caffe.cpp:501] detection_eval = 0.0398687
-I0511 11:50:55.681282  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681285  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681288  5581 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:50:55.681289  5581 caffe.cpp:501] detection_eval = 11.6976
-I0511 11:50:55.681291  5581 caffe.cpp:501] detection_eval = 0.0381377
-I0511 11:50:55.681293  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681296  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681298  5581 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:50:55.681301  5581 caffe.cpp:501] detection_eval = 11.7903
-I0511 11:50:55.681305  5581 caffe.cpp:501] detection_eval = 0.0413339
-I0511 11:50:55.681308  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681309  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681319  5581 caffe.cpp:501] detection_eval = 6.80444
-I0511 11:50:55.681321  5581 caffe.cpp:501] detection_eval = 11.7843
-I0511 11:50:55.681324  5581 caffe.cpp:501] detection_eval = 0.0380796
-I0511 11:50:55.681326  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681329  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681330  5581 caffe.cpp:501] detection_eval = 6.8125
-I0511 11:50:55.681332  5581 caffe.cpp:501] detection_eval = 11.7419
-I0511 11:50:55.681334  5581 caffe.cpp:501] detection_eval = 0.0394887
-I0511 11:50:55.681337  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681339  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681341  5581 caffe.cpp:501] detection_eval = 6.81653
-I0511 11:50:55.681344  5581 caffe.cpp:501] detection_eval = 11.7177
-I0511 11:50:55.681346  5581 caffe.cpp:501] detection_eval = 0.0369103
-I0511 11:50:55.681349  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681350  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681352  5581 caffe.cpp:501] detection_eval = 6.82056
-I0511 11:50:55.681354  5581 caffe.cpp:501] detection_eval = 11.7198
-I0511 11:50:55.681357  5581 caffe.cpp:501] detection_eval = 0.0381167
-I0511 11:50:55.681360  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681361  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681363  5581 caffe.cpp:501] detection_eval = 6.82863
-I0511 11:50:55.681365  5581 caffe.cpp:501] detection_eval = 11.6976
-I0511 11:50:55.681368  5581 caffe.cpp:501] detection_eval = 0.0405401
-I0511 11:50:55.681370  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681372  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681375  5581 caffe.cpp:501] detection_eval = 6.83065
-I0511 11:50:55.681377  5581 caffe.cpp:501] detection_eval = 11.7722
-I0511 11:50:55.681380  5581 caffe.cpp:501] detection_eval = 0.0391582
-I0511 11:50:55.681381  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681383  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681385  5581 caffe.cpp:501] detection_eval = 6.83669
-I0511 11:50:55.681387  5581 caffe.cpp:501] detection_eval = 11.752
-I0511 11:50:55.681391  5581 caffe.cpp:501] detection_eval = 0.0412488
-I0511 11:50:55.681392  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681394  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681396  5581 caffe.cpp:501] detection_eval = 6.83871
-I0511 11:50:55.681398  5581 caffe.cpp:501] detection_eval = 11.7944
-I0511 11:50:55.681401  5581 caffe.cpp:501] detection_eval = 0.0354297
-I0511 11:50:55.681403  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681406  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.681407  5581 caffe.cpp:501] detection_eval = 6.83871
-I0511 11:50:55.681411  5581 caffe.cpp:501] detection_eval = 11.8669
-I0511 11:50:55.681412  5581 caffe.cpp:501] detection_eval = 0.0418504
-I0511 11:50:55.681414  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681416  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681418  5581 caffe.cpp:501] detection_eval = 6.84274
-I0511 11:50:55.681421  5581 caffe.cpp:501] detection_eval = 11.8891
-I0511 11:50:55.681423  5581 caffe.cpp:501] detection_eval = 0.0377028
-I0511 11:50:55.681426  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681427  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681429  5581 caffe.cpp:501] detection_eval = 6.84274
-I0511 11:50:55.681432  5581 caffe.cpp:501] detection_eval = 11.9657
-I0511 11:50:55.681434  5581 caffe.cpp:501] detection_eval = 0.037204
-I0511 11:50:55.681437  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681438  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681440  5581 caffe.cpp:501] detection_eval = 6.84677
-I0511 11:50:55.681442  5581 caffe.cpp:501] detection_eval = 12.004
-I0511 11:50:55.681445  5581 caffe.cpp:501] detection_eval = 0.0387492
-I0511 11:50:55.681447  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681452  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681454  5581 caffe.cpp:501] detection_eval = 6.85081
-I0511 11:50:55.681457  5581 caffe.cpp:501] detection_eval = 12.0746
-I0511 11:50:55.681459  5581 caffe.cpp:501] detection_eval = 0.0480775
-I0511 11:50:55.681462  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.681463  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681465  5581 caffe.cpp:501] detection_eval = 6.85685
-I0511 11:50:55.681468  5581 caffe.cpp:501] detection_eval = 12.0867
-I0511 11:50:55.681470  5581 caffe.cpp:501] detection_eval = 0.0445336
-I0511 11:50:55.681473  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681474  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681476  5581 caffe.cpp:501] detection_eval = 6.85887
-I0511 11:50:55.681478  5581 caffe.cpp:501] detection_eval = 12.1391
-I0511 11:50:55.681480  5581 caffe.cpp:501] detection_eval = 0.0436437
-I0511 11:50:55.681483  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681485  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681488  5581 caffe.cpp:501] detection_eval = 6.8629
-I0511 11:50:55.681489  5581 caffe.cpp:501] detection_eval = 12.1754
-I0511 11:50:55.681491  5581 caffe.cpp:501] detection_eval = 0.039225
-I0511 11:50:55.681494  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681496  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681499  5581 caffe.cpp:501] detection_eval = 6.86492
-I0511 11:50:55.681500  5581 caffe.cpp:501] detection_eval = 12.2399
-I0511 11:50:55.681502  5581 caffe.cpp:501] detection_eval = 0.043345
-I0511 11:50:55.681504  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681507  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681509  5581 caffe.cpp:501] detection_eval = 6.85282
-I0511 11:50:55.681511  5581 caffe.cpp:501] detection_eval = 12.2056
-I0511 11:50:55.681514  5581 caffe.cpp:501] detection_eval = 0.0443765
-I0511 11:50:55.681515  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681519  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681520  5581 caffe.cpp:501] detection_eval = 6.86089
-I0511 11:50:55.681522  5581 caffe.cpp:501] detection_eval = 12.1391
-I0511 11:50:55.681524  5581 caffe.cpp:501] detection_eval = 0.0425658
-I0511 11:50:55.681526  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681529  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681531  5581 caffe.cpp:501] detection_eval = 6.86492
-I0511 11:50:55.681533  5581 caffe.cpp:501] detection_eval = 12.1734
-I0511 11:50:55.681535  5581 caffe.cpp:501] detection_eval = 0.0386758
-I0511 11:50:55.681537  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681540  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681542  5581 caffe.cpp:501] detection_eval = 6.87097
-I0511 11:50:55.681545  5581 caffe.cpp:501] detection_eval = 12.2117
-I0511 11:50:55.681546  5581 caffe.cpp:501] detection_eval = 0.0415744
-I0511 11:50:55.681548  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681550  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681553  5581 caffe.cpp:501] detection_eval = 6.875
-I0511 11:50:55.681555  5581 caffe.cpp:501] detection_eval = 12.2843
-I0511 11:50:55.681557  5581 caffe.cpp:501] detection_eval = 0.0469725
-I0511 11:50:55.681560  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681561  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.681565  5581 caffe.cpp:501] detection_eval = 6.87702
-I0511 11:50:55.681566  5581 caffe.cpp:501] detection_eval = 12.373
-I0511 11:50:55.681568  5581 caffe.cpp:501] detection_eval = 0.0490451
-I0511 11:50:55.681571  5581 caffe.cpp:501] detection_eval = 0.0241935
-I0511 11:50:55.681573  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.681576  5581 caffe.cpp:501] detection_eval = 6.88105
-I0511 11:50:55.681577  5581 caffe.cpp:501] detection_eval = 12.4254
-I0511 11:50:55.681579  5581 caffe.cpp:501] detection_eval = 0.0459364
-I0511 11:50:55.681581  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681586  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681588  5581 caffe.cpp:501] detection_eval = 6.88911
-I0511 11:50:55.681591  5581 caffe.cpp:501] detection_eval = 12.4113
-I0511 11:50:55.681593  5581 caffe.cpp:501] detection_eval = 0.0461567
-I0511 11:50:55.681596  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681597  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681599  5581 caffe.cpp:501] detection_eval = 6.89113
-I0511 11:50:55.681602  5581 caffe.cpp:501] detection_eval = 12.4859
-I0511 11:50:55.681604  5581 caffe.cpp:501] detection_eval = 0.0445998
-I0511 11:50:55.681607  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681608  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681610  5581 caffe.cpp:501] detection_eval = 6.89516
-I0511 11:50:55.681612  5581 caffe.cpp:501] detection_eval = 12.5101
-I0511 11:50:55.681615  5581 caffe.cpp:501] detection_eval = 0.0377217
-I0511 11:50:55.681617  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681619  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.681622  5581 caffe.cpp:501] detection_eval = 6.90121
-I0511 11:50:55.681624  5581 caffe.cpp:501] detection_eval = 12.6089
-I0511 11:50:55.681627  5581 caffe.cpp:501] detection_eval = 0.0414381
-I0511 11:50:55.681628  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681630  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681632  5581 caffe.cpp:501] detection_eval = 6.90524
-I0511 11:50:55.681634  5581 caffe.cpp:501] detection_eval = 12.625
-I0511 11:50:55.681638  5581 caffe.cpp:501] detection_eval = 0.0353203
-I0511 11:50:55.681639  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681641  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681643  5581 caffe.cpp:501] detection_eval = 6.90927
-I0511 11:50:55.681645  5581 caffe.cpp:501] detection_eval = 12.7198
-I0511 11:50:55.681648  5581 caffe.cpp:501] detection_eval = 0.0347852
-I0511 11:50:55.681650  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681653  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.681654  5581 caffe.cpp:501] detection_eval = 7.22581
-I0511 11:50:55.681656  5581 caffe.cpp:501] detection_eval = 8.06855
-I0511 11:50:55.681658  5581 caffe.cpp:501] detection_eval = 0.0856414
-I0511 11:50:55.681661  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.681663  5581 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:50:55.681665  5581 caffe.cpp:501] detection_eval = 7.22984
-I0511 11:50:55.681668  5581 caffe.cpp:501] detection_eval = 8.21169
-I0511 11:50:55.681670  5581 caffe.cpp:501] detection_eval = 0.0634881
-I0511 11:50:55.681673  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.681674  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.681676  5581 caffe.cpp:501] detection_eval = 7.22984
-I0511 11:50:55.681679  5581 caffe.cpp:501] detection_eval = 8.29032
-I0511 11:50:55.681680  5581 caffe.cpp:501] detection_eval = 0.0491501
-I0511 11:50:55.681684  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681685  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681689  5581 caffe.cpp:501] detection_eval = 7.23185
-I0511 11:50:55.681692  5581 caffe.cpp:501] detection_eval = 8.37097
-I0511 11:50:55.681694  5581 caffe.cpp:501] detection_eval = 0.0485129
-I0511 11:50:55.681696  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681699  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681700  5581 caffe.cpp:501] detection_eval = 7.23589
-I0511 11:50:55.681704  5581 caffe.cpp:501] detection_eval = 8.44556
-I0511 11:50:55.681705  5581 caffe.cpp:501] detection_eval = 0.0500122
-I0511 11:50:55.681707  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681710  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.681711  5581 caffe.cpp:501] detection_eval = 7.23992
-I0511 11:50:55.681713  5581 caffe.cpp:501] detection_eval = 8.44758
-I0511 11:50:55.681716  5581 caffe.cpp:501] detection_eval = 0.0491981
-I0511 11:50:55.681720  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681723  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681725  5581 caffe.cpp:501] detection_eval = 7.24395
-I0511 11:50:55.681727  5581 caffe.cpp:501] detection_eval = 8.46169
-I0511 11:50:55.681730  5581 caffe.cpp:501] detection_eval = 0.0435018
-I0511 11:50:55.681732  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681735  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681736  5581 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:50:55.681738  5581 caffe.cpp:501] detection_eval = 8.49798
-I0511 11:50:55.681740  5581 caffe.cpp:501] detection_eval = 0.0455176
-I0511 11:50:55.681742  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.681744  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681747  5581 caffe.cpp:501] detection_eval = 7.24597
-I0511 11:50:55.681749  5581 caffe.cpp:501] detection_eval = 8.5746
-I0511 11:50:55.681751  5581 caffe.cpp:501] detection_eval = 0.0454906
-I0511 11:50:55.681753  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.681756  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681758  5581 caffe.cpp:501] detection_eval = 7.25
-I0511 11:50:55.681761  5581 caffe.cpp:501] detection_eval = 8.59274
-I0511 11:50:55.681762  5581 caffe.cpp:501] detection_eval = 0.0388731
-I0511 11:50:55.681764  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681766  5581 caffe.cpp:501] detection_eval = 0.993952
-I0511 11:50:55.681768  5581 caffe.cpp:501] detection_eval = 7.25202
-I0511 11:50:55.681771  5581 caffe.cpp:501] detection_eval = 8.64315
-I0511 11:50:55.681773  5581 caffe.cpp:501] detection_eval = 0.0439831
-I0511 11:50:55.681776  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681777  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681779  5581 caffe.cpp:501] detection_eval = 7.25403
-I0511 11:50:55.681782  5581 caffe.cpp:501] detection_eval = 8.67339
-I0511 11:50:55.681784  5581 caffe.cpp:501] detection_eval = 0.0479034
-I0511 11:50:55.681787  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681788  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.681790  5581 caffe.cpp:501] detection_eval = 7.25605
-I0511 11:50:55.681792  5581 caffe.cpp:501] detection_eval = 8.69556
-I0511 11:50:55.681794  5581 caffe.cpp:501] detection_eval = 0.0442465
-I0511 11:50:55.681797  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681798  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.681802  5581 caffe.cpp:501] detection_eval = 7.26008
-I0511 11:50:55.681803  5581 caffe.cpp:501] detection_eval = 8.73387
-I0511 11:50:55.681805  5581 caffe.cpp:501] detection_eval = 0.0396222
-I0511 11:50:55.681808  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681810  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681813  5581 caffe.cpp:501] detection_eval = 7.2621
-I0511 11:50:55.681814  5581 caffe.cpp:501] detection_eval = 8.78024
-I0511 11:50:55.681816  5581 caffe.cpp:501] detection_eval = 0.0417208
-I0511 11:50:55.681818  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681821  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681823  5581 caffe.cpp:501] detection_eval = 7.26411
-I0511 11:50:55.681825  5581 caffe.cpp:501] detection_eval = 8.81048
-I0511 11:50:55.681828  5581 caffe.cpp:501] detection_eval = 0.0406238
-I0511 11:50:55.681829  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681833  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681834  5581 caffe.cpp:501] detection_eval = 7.26613
-I0511 11:50:55.681836  5581 caffe.cpp:501] detection_eval = 8.83468
-I0511 11:50:55.681838  5581 caffe.cpp:501] detection_eval = 0.0393886
-I0511 11:50:55.681840  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.681843  5581 caffe.cpp:501] detection_eval = 0.991935
-I0511 11:50:55.681844  5581 caffe.cpp:501] detection_eval = 7.26613
-I0511 11:50:55.681848  5581 caffe.cpp:501] detection_eval = 8.91331
-I0511 11:50:55.681849  5581 caffe.cpp:501] detection_eval = 0.0400285
-I0511 11:50:55.681854  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681857  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.681859  5581 caffe.cpp:501] detection_eval = 7.27218
-I0511 11:50:55.681861  5581 caffe.cpp:501] detection_eval = 8.86492
-I0511 11:50:55.681864  5581 caffe.cpp:501] detection_eval = 0.0419766
-I0511 11:50:55.681866  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.681869  5581 caffe.cpp:501] detection_eval = 0.995968
-I0511 11:50:55.681870  5581 caffe.cpp:501] detection_eval = 7.27419
-I0511 11:50:55.681872  5581 caffe.cpp:501] detection_eval = 8.91734
-I0511 11:50:55.681874  5581 caffe.cpp:501] detection_eval = 0.0419344
-I0511 11:50:55.681877  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681879  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.681881  5581 caffe.cpp:501] detection_eval = 7.28024
-I0511 11:50:55.681885  5581 caffe.cpp:501] detection_eval = 8.88306
-I0511 11:50:55.681886  5581 caffe.cpp:501] detection_eval = 0.0417776
-I0511 11:50:55.681888  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681890  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.681892  5581 caffe.cpp:501] detection_eval = 7.28024
-I0511 11:50:55.681895  5581 caffe.cpp:501] detection_eval = 8.96573
-I0511 11:50:55.681897  5581 caffe.cpp:501] detection_eval = 0.0458027
-I0511 11:50:55.681900  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.681901  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.681903  5581 caffe.cpp:501] detection_eval = 7.28226
-I0511 11:50:55.681906  5581 caffe.cpp:501] detection_eval = 9.01411
-I0511 11:50:55.681908  5581 caffe.cpp:501] detection_eval = 0.0483489
-I0511 11:50:55.681910  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681912  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.681915  5581 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:50:55.681917  5581 caffe.cpp:501] detection_eval = 8.90927
-I0511 11:50:55.681919  5581 caffe.cpp:501] detection_eval = 0.0468659
-I0511 11:50:55.681921  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.681923  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681926  5581 caffe.cpp:501] detection_eval = 7.29839
-I0511 11:50:55.681928  5581 caffe.cpp:501] detection_eval = 8.93952
-I0511 11:50:55.681931  5581 caffe.cpp:501] detection_eval = 0.0468604
-I0511 11:50:55.681933  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.681936  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.681938  5581 caffe.cpp:501] detection_eval = 7.30444
-I0511 11:50:55.681941  5581 caffe.cpp:501] detection_eval = 8.94153
-I0511 11:50:55.681943  5581 caffe.cpp:501] detection_eval = 0.0424661
-I0511 11:50:55.681946  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.681947  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.681951  5581 caffe.cpp:501] detection_eval = 7.31048
-I0511 11:50:55.681952  5581 caffe.cpp:501] detection_eval = 8.9375
-I0511 11:50:55.681954  5581 caffe.cpp:501] detection_eval = 0.0467155
-I0511 11:50:55.681957  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.681959  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.681962  5581 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:50:55.681963  5581 caffe.cpp:501] detection_eval = 8.99798
-I0511 11:50:55.681965  5581 caffe.cpp:501] detection_eval = 0.0462472
-I0511 11:50:55.681968  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.681970  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.681973  5581 caffe.cpp:501] detection_eval = 7.29839
-I0511 11:50:55.681975  5581 caffe.cpp:501] detection_eval = 9.03226
-I0511 11:50:55.681977  5581 caffe.cpp:501] detection_eval = 0.0433089
-I0511 11:50:55.681980  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.681982  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.681984  5581 caffe.cpp:501] detection_eval = 7.30242
-I0511 11:50:55.681987  5581 caffe.cpp:501] detection_eval = 9.02016
-I0511 11:50:55.681993  5581 caffe.cpp:501] detection_eval = 0.039932
-I0511 11:50:55.681995  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.681998  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682000  5581 caffe.cpp:501] detection_eval = 7.30645
-I0511 11:50:55.682003  5581 caffe.cpp:501] detection_eval = 9.02621
-I0511 11:50:55.682004  5581 caffe.cpp:501] detection_eval = 0.0462682
-I0511 11:50:55.682008  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682009  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682011  5581 caffe.cpp:501] detection_eval = 7.30847
-I0511 11:50:55.682014  5581 caffe.cpp:501] detection_eval = 9.06653
-I0511 11:50:55.682016  5581 caffe.cpp:501] detection_eval = 0.0449975
-I0511 11:50:55.682018  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682020  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682023  5581 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:50:55.682024  5581 caffe.cpp:501] detection_eval = 9.11089
-I0511 11:50:55.682027  5581 caffe.cpp:501] detection_eval = 0.0458093
-I0511 11:50:55.682029  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682031  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682034  5581 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:50:55.682035  5581 caffe.cpp:501] detection_eval = 9.19556
-I0511 11:50:55.682039  5581 caffe.cpp:501] detection_eval = 0.0452179
-I0511 11:50:55.682040  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682042  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682044  5581 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:50:55.682046  5581 caffe.cpp:501] detection_eval = 9.28427
-I0511 11:50:55.682049  5581 caffe.cpp:501] detection_eval = 0.0439263
-I0511 11:50:55.682050  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682054  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682055  5581 caffe.cpp:501] detection_eval = 7.31653
-I0511 11:50:55.682057  5581 caffe.cpp:501] detection_eval = 9.27016
-I0511 11:50:55.682060  5581 caffe.cpp:501] detection_eval = 0.0388889
-I0511 11:50:55.682061  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682063  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682066  5581 caffe.cpp:501] detection_eval = 7.31855
-I0511 11:50:55.682068  5581 caffe.cpp:501] detection_eval = 9.32056
-I0511 11:50:55.682070  5581 caffe.cpp:501] detection_eval = 0.0438795
-I0511 11:50:55.682271  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682279  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682282  5581 caffe.cpp:501] detection_eval = 7.31855
-I0511 11:50:55.682284  5581 caffe.cpp:501] detection_eval = 9.35282
-I0511 11:50:55.682287  5581 caffe.cpp:501] detection_eval = 0.0378971
-I0511 11:50:55.682289  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.682291  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.682293  5581 caffe.cpp:501] detection_eval = 7.31855
-I0511 11:50:55.682296  5581 caffe.cpp:501] detection_eval = 9.40927
-I0511 11:50:55.682298  5581 caffe.cpp:501] detection_eval = 0.0433352
-I0511 11:50:55.682301  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682302  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682304  5581 caffe.cpp:501] detection_eval = 7.3246
-I0511 11:50:55.682307  5581 caffe.cpp:501] detection_eval = 9.43548
-I0511 11:50:55.682309  5581 caffe.cpp:501] detection_eval = 0.040325
-I0511 11:50:55.682312  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682313  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682315  5581 caffe.cpp:501] detection_eval = 7.3246
-I0511 11:50:55.682318  5581 caffe.cpp:501] detection_eval = 9.49798
-I0511 11:50:55.682320  5581 caffe.cpp:501] detection_eval = 0.0409152
-I0511 11:50:55.682322  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682324  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682327  5581 caffe.cpp:501] detection_eval = 7.32661
-I0511 11:50:55.682334  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.682337  5581 caffe.cpp:501] detection_eval = 0.0402087
-I0511 11:50:55.682339  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682341  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682343  5581 caffe.cpp:501] detection_eval = 7.33266
-I0511 11:50:55.682345  5581 caffe.cpp:501] detection_eval = 9.47581
-I0511 11:50:55.682348  5581 caffe.cpp:501] detection_eval = 0.0378348
-I0511 11:50:55.682349  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682353  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682354  5581 caffe.cpp:501] detection_eval = 7.33468
-I0511 11:50:55.682356  5581 caffe.cpp:501] detection_eval = 9.49395
-I0511 11:50:55.682358  5581 caffe.cpp:501] detection_eval = 0.0387339
-I0511 11:50:55.682360  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682363  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682365  5581 caffe.cpp:501] detection_eval = 7.33669
-I0511 11:50:55.682368  5581 caffe.cpp:501] detection_eval = 9.52823
-I0511 11:50:55.682369  5581 caffe.cpp:501] detection_eval = 0.0410701
-I0511 11:50:55.682371  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682374  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682376  5581 caffe.cpp:501] detection_eval = 7.34073
-I0511 11:50:55.682379  5581 caffe.cpp:501] detection_eval = 9.55645
-I0511 11:50:55.682380  5581 caffe.cpp:501] detection_eval = 0.0420968
-I0511 11:50:55.682382  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682384  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682386  5581 caffe.cpp:501] detection_eval = 7.34073
-I0511 11:50:55.682389  5581 caffe.cpp:501] detection_eval = 9.58065
-I0511 11:50:55.682391  5581 caffe.cpp:501] detection_eval = 0.0384954
-I0511 11:50:55.682394  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.682395  5581 caffe.cpp:501] detection_eval = 0.989919
-I0511 11:50:55.682397  5581 caffe.cpp:501] detection_eval = 7.34476
-I0511 11:50:55.682400  5581 caffe.cpp:501] detection_eval = 9.6129
-I0511 11:50:55.682402  5581 caffe.cpp:501] detection_eval = 0.0406598
-I0511 11:50:55.682404  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682406  5581 caffe.cpp:501] detection_eval = 0.985887
-I0511 11:50:55.682409  5581 caffe.cpp:501] detection_eval = 7.35484
-I0511 11:50:55.682410  5581 caffe.cpp:501] detection_eval = 9.55645
-I0511 11:50:55.682413  5581 caffe.cpp:501] detection_eval = 0.040175
-I0511 11:50:55.682415  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682417  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682420  5581 caffe.cpp:501] detection_eval = 7.35887
-I0511 11:50:55.682421  5581 caffe.cpp:501] detection_eval = 9.57056
-I0511 11:50:55.682425  5581 caffe.cpp:501] detection_eval = 0.0418544
-I0511 11:50:55.682426  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682428  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682430  5581 caffe.cpp:501] detection_eval = 7.35887
-I0511 11:50:55.682432  5581 caffe.cpp:501] detection_eval = 9.64718
-I0511 11:50:55.682435  5581 caffe.cpp:501] detection_eval = 0.0400233
-I0511 11:50:55.682437  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682440  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682441  5581 caffe.cpp:501] detection_eval = 7.3629
-I0511 11:50:55.682443  5581 caffe.cpp:501] detection_eval = 9.63105
-I0511 11:50:55.682446  5581 caffe.cpp:501] detection_eval = 0.0385768
-I0511 11:50:55.682448  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682451  5581 caffe.cpp:501] detection_eval = 0.987903
-I0511 11:50:55.682452  5581 caffe.cpp:501] detection_eval = 7.3629
-I0511 11:50:55.682454  5581 caffe.cpp:501] detection_eval = 9.70565
-I0511 11:50:55.682456  5581 caffe.cpp:501] detection_eval = 0.0420802
-I0511 11:50:55.682459  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682461  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682463  5581 caffe.cpp:501] detection_eval = 7.36492
-I0511 11:50:55.682468  5581 caffe.cpp:501] detection_eval = 9.80242
-I0511 11:50:55.682471  5581 caffe.cpp:501] detection_eval = 0.0501388
-I0511 11:50:55.682472  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.682476  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.682477  5581 caffe.cpp:501] detection_eval = 7.36492
-I0511 11:50:55.682479  5581 caffe.cpp:501] detection_eval = 9.9375
-I0511 11:50:55.682482  5581 caffe.cpp:501] detection_eval = 0.0473965
-I0511 11:50:55.682483  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682485  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.682488  5581 caffe.cpp:501] detection_eval = 7.36492
-I0511 11:50:55.682490  5581 caffe.cpp:501] detection_eval = 10.0161
-I0511 11:50:55.682492  5581 caffe.cpp:501] detection_eval = 0.0437935
-I0511 11:50:55.682495  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682497  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682499  5581 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:50:55.682502  5581 caffe.cpp:501] detection_eval = 9.99597
-I0511 11:50:55.682505  5581 caffe.cpp:501] detection_eval = 0.0449916
-I0511 11:50:55.682509  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682514  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682518  5581 caffe.cpp:501] detection_eval = 7.35484
-I0511 11:50:55.682520  5581 caffe.cpp:501] detection_eval = 10.0403
-I0511 11:50:55.682523  5581 caffe.cpp:501] detection_eval = 0.0470892
-I0511 11:50:55.682524  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.682526  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.682529  5581 caffe.cpp:501] detection_eval = 7.35887
-I0511 11:50:55.682531  5581 caffe.cpp:501] detection_eval = 10.0504
-I0511 11:50:55.682533  5581 caffe.cpp:501] detection_eval = 0.0472107
-I0511 11:50:55.682535  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682538  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.682540  5581 caffe.cpp:501] detection_eval = 7.3629
-I0511 11:50:55.682543  5581 caffe.cpp:501] detection_eval = 10.0726
-I0511 11:50:55.682544  5581 caffe.cpp:501] detection_eval = 0.0453176
-I0511 11:50:55.682546  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682548  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682550  5581 caffe.cpp:501] detection_eval = 7.36694
-I0511 11:50:55.682554  5581 caffe.cpp:501] detection_eval = 10.1048
-I0511 11:50:55.682555  5581 caffe.cpp:501] detection_eval = 0.0473685
-I0511 11:50:55.682557  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682559  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682562  5581 caffe.cpp:501] detection_eval = 7.37298
-I0511 11:50:55.682564  5581 caffe.cpp:501] detection_eval = 10.129
-I0511 11:50:55.682566  5581 caffe.cpp:501] detection_eval = 0.0509039
-I0511 11:50:55.682569  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.682570  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.682574  5581 caffe.cpp:501] detection_eval = 7.37903
-I0511 11:50:55.682575  5581 caffe.cpp:501] detection_eval = 10.1573
-I0511 11:50:55.682577  5581 caffe.cpp:501] detection_eval = 0.0425583
-I0511 11:50:55.682579  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682582  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682585  5581 caffe.cpp:501] detection_eval = 7.38306
-I0511 11:50:55.682586  5581 caffe.cpp:501] detection_eval = 10.1956
-I0511 11:50:55.682588  5581 caffe.cpp:501] detection_eval = 0.0446588
-I0511 11:50:55.682590  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682593  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682595  5581 caffe.cpp:501] detection_eval = 7.38508
-I0511 11:50:55.682597  5581 caffe.cpp:501] detection_eval = 10.2621
-I0511 11:50:55.682600  5581 caffe.cpp:501] detection_eval = 0.0470283
-I0511 11:50:55.682601  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682605  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682610  5581 caffe.cpp:501] detection_eval = 7.38911
-I0511 11:50:55.682611  5581 caffe.cpp:501] detection_eval = 10.2903
-I0511 11:50:55.682613  5581 caffe.cpp:501] detection_eval = 0.040443
-I0511 11:50:55.682616  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.682618  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682621  5581 caffe.cpp:501] detection_eval = 7.39113
-I0511 11:50:55.682622  5581 caffe.cpp:501] detection_eval = 10.3367
-I0511 11:50:55.682624  5581 caffe.cpp:501] detection_eval = 0.042165
-I0511 11:50:55.682627  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682629  5581 caffe.cpp:501] detection_eval = 0.983871
-I0511 11:50:55.682631  5581 caffe.cpp:501] detection_eval = 7.39113
-I0511 11:50:55.682633  5581 caffe.cpp:501] detection_eval = 10.3952
-I0511 11:50:55.682636  5581 caffe.cpp:501] detection_eval = 0.0446252
-I0511 11:50:55.682638  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682641  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682642  5581 caffe.cpp:501] detection_eval = 7.39113
-I0511 11:50:55.682644  5581 caffe.cpp:501] detection_eval = 10.4879
-I0511 11:50:55.682646  5581 caffe.cpp:501] detection_eval = 0.0435957
-I0511 11:50:55.682648  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.682651  5581 caffe.cpp:501] detection_eval = 0.981855
-I0511 11:50:55.682653  5581 caffe.cpp:501] detection_eval = 7.39718
-I0511 11:50:55.682656  5581 caffe.cpp:501] detection_eval = 10.5202
-I0511 11:50:55.682657  5581 caffe.cpp:501] detection_eval = 0.0478907
-I0511 11:50:55.682659  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.682662  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.682664  5581 caffe.cpp:501] detection_eval = 7.40323
-I0511 11:50:55.682667  5581 caffe.cpp:501] detection_eval = 10.498
-I0511 11:50:55.682668  5581 caffe.cpp:501] detection_eval = 0.0469434
-I0511 11:50:55.682670  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682672  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682675  5581 caffe.cpp:501] detection_eval = 7.41532
-I0511 11:50:55.682677  5581 caffe.cpp:501] detection_eval = 10.3851
-I0511 11:50:55.682679  5581 caffe.cpp:501] detection_eval = 0.0478128
-I0511 11:50:55.682682  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.682683  5581 caffe.cpp:501] detection_eval = 0.979839
-I0511 11:50:55.682687  5581 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:50:55.682688  5581 caffe.cpp:501] detection_eval = 10.4698
-I0511 11:50:55.682690  5581 caffe.cpp:501] detection_eval = 0.0479721
-I0511 11:50:55.682693  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682694  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682698  5581 caffe.cpp:501] detection_eval = 7.4254
-I0511 11:50:55.682699  5581 caffe.cpp:501] detection_eval = 10.506
-I0511 11:50:55.682701  5581 caffe.cpp:501] detection_eval = 0.0453031
-I0511 11:50:55.682703  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682705  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682708  5581 caffe.cpp:501] detection_eval = 7.40927
-I0511 11:50:55.682710  5581 caffe.cpp:501] detection_eval = 10.494
-I0511 11:50:55.682713  5581 caffe.cpp:501] detection_eval = 0.0457791
-I0511 11:50:55.682714  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682716  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.682719  5581 caffe.cpp:501] detection_eval = 7.41129
-I0511 11:50:55.682721  5581 caffe.cpp:501] detection_eval = 10.5544
-I0511 11:50:55.682723  5581 caffe.cpp:501] detection_eval = 0.0452257
-I0511 11:50:55.682725  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682727  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.682729  5581 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:50:55.682731  5581 caffe.cpp:501] detection_eval = 10.5706
-I0511 11:50:55.682734  5581 caffe.cpp:501] detection_eval = 0.0516385
-I0511 11:50:55.682736  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.682739  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.682744  5581 caffe.cpp:501] detection_eval = 7.40524
-I0511 11:50:55.682746  5581 caffe.cpp:501] detection_eval = 10.5323
-I0511 11:50:55.682749  5581 caffe.cpp:501] detection_eval = 0.0446368
-I0511 11:50:55.682750  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682754  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.682755  5581 caffe.cpp:501] detection_eval = 7.39718
-I0511 11:50:55.682757  5581 caffe.cpp:501] detection_eval = 10.4778
-I0511 11:50:55.682760  5581 caffe.cpp:501] detection_eval = 0.0507295
-I0511 11:50:55.682761  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.682765  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.682766  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.682768  5581 caffe.cpp:501] detection_eval = 10.4133
-I0511 11:50:55.682770  5581 caffe.cpp:501] detection_eval = 0.053087
-I0511 11:50:55.682772  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.682775  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.682777  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.682780  5581 caffe.cpp:501] detection_eval = 10.5101
-I0511 11:50:55.682781  5581 caffe.cpp:501] detection_eval = 0.047828
-I0511 11:50:55.682783  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.682785  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.682787  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.682790  5581 caffe.cpp:501] detection_eval = 10.5766
-I0511 11:50:55.682792  5581 caffe.cpp:501] detection_eval = 0.0488476
-I0511 11:50:55.682795  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.682796  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.682798  5581 caffe.cpp:501] detection_eval = 7.41532
-I0511 11:50:55.682801  5581 caffe.cpp:501] detection_eval = 10.5544
-I0511 11:50:55.682803  5581 caffe.cpp:501] detection_eval = 0.0478669
-I0511 11:50:55.682806  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.682807  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.682809  5581 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:50:55.682811  5581 caffe.cpp:501] detection_eval = 10.5665
-I0511 11:50:55.682814  5581 caffe.cpp:501] detection_eval = 0.0429634
-I0511 11:50:55.682816  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.683734  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.683744  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.683748  5581 caffe.cpp:501] detection_eval = 10.4798
-I0511 11:50:55.683753  5581 caffe.cpp:501] detection_eval = 0.0412703
-I0511 11:50:55.683758  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.683763  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.683766  5581 caffe.cpp:501] detection_eval = 7.40927
-I0511 11:50:55.683769  5581 caffe.cpp:501] detection_eval = 10.5363
-I0511 11:50:55.683774  5581 caffe.cpp:501] detection_eval = 0.0458134
-I0511 11:50:55.683779  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.683782  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.683786  5581 caffe.cpp:501] detection_eval = 7.41331
-I0511 11:50:55.683790  5581 caffe.cpp:501] detection_eval = 10.5222
-I0511 11:50:55.683794  5581 caffe.cpp:501] detection_eval = 0.0491089
-I0511 11:50:55.683799  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.683802  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.683806  5581 caffe.cpp:501] detection_eval = 7.39718
-I0511 11:50:55.683810  5581 caffe.cpp:501] detection_eval = 10.5343
-I0511 11:50:55.683815  5581 caffe.cpp:501] detection_eval = 0.0419852
-I0511 11:50:55.683818  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.683822  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.683826  5581 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:50:55.683830  5581 caffe.cpp:501] detection_eval = 10.5988
-I0511 11:50:55.683835  5581 caffe.cpp:501] detection_eval = 0.0454163
-I0511 11:50:55.683840  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.683847  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683852  5581 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:50:55.683856  5581 caffe.cpp:501] detection_eval = 10.6855
-I0511 11:50:55.683861  5581 caffe.cpp:501] detection_eval = 0.0427413
-I0511 11:50:55.683864  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.683868  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.683872  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.683876  5581 caffe.cpp:501] detection_eval = 10.6371
-I0511 11:50:55.683881  5581 caffe.cpp:501] detection_eval = 0.0447473
-I0511 11:50:55.683884  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.683888  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.683892  5581 caffe.cpp:501] detection_eval = 7.41129
-I0511 11:50:55.683897  5581 caffe.cpp:501] detection_eval = 10.6351
-I0511 11:50:55.683900  5581 caffe.cpp:501] detection_eval = 0.0411808
-I0511 11:50:55.683902  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.683904  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.683907  5581 caffe.cpp:501] detection_eval = 7.41331
-I0511 11:50:55.683909  5581 caffe.cpp:501] detection_eval = 10.6673
-I0511 11:50:55.683912  5581 caffe.cpp:501] detection_eval = 0.0455204
-I0511 11:50:55.683913  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.683915  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683918  5581 caffe.cpp:501] detection_eval = 7.41734
-I0511 11:50:55.683920  5581 caffe.cpp:501] detection_eval = 10.6915
-I0511 11:50:55.683923  5581 caffe.cpp:501] detection_eval = 0.0404305
-I0511 11:50:55.683924  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.683928  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.683929  5581 caffe.cpp:501] detection_eval = 7.42339
-I0511 11:50:55.683931  5581 caffe.cpp:501] detection_eval = 10.6573
-I0511 11:50:55.683933  5581 caffe.cpp:501] detection_eval = 0.0409796
-I0511 11:50:55.683935  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.683938  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.683940  5581 caffe.cpp:501] detection_eval = 7.4254
-I0511 11:50:55.683943  5581 caffe.cpp:501] detection_eval = 10.6915
-I0511 11:50:55.683944  5581 caffe.cpp:501] detection_eval = 0.0417903
-I0511 11:50:55.683948  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.683949  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683951  5581 caffe.cpp:501] detection_eval = 7.43145
-I0511 11:50:55.683954  5581 caffe.cpp:501] detection_eval = 10.6431
-I0511 11:50:55.683956  5581 caffe.cpp:501] detection_eval = 0.0431551
-I0511 11:50:55.683959  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.683960  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683962  5581 caffe.cpp:501] detection_eval = 7.44355
-I0511 11:50:55.683964  5581 caffe.cpp:501] detection_eval = 10.5484
-I0511 11:50:55.683967  5581 caffe.cpp:501] detection_eval = 0.0394992
-I0511 11:50:55.683969  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.683971  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.683974  5581 caffe.cpp:501] detection_eval = 7.4496
-I0511 11:50:55.683975  5581 caffe.cpp:501] detection_eval = 10.5484
-I0511 11:50:55.683979  5581 caffe.cpp:501] detection_eval = 0.044845
-I0511 11:50:55.683980  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.683982  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.683984  5581 caffe.cpp:501] detection_eval = 7.45565
-I0511 11:50:55.683987  5581 caffe.cpp:501] detection_eval = 10.5706
-I0511 11:50:55.683990  5581 caffe.cpp:501] detection_eval = 0.0456398
-I0511 11:50:55.683991  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.683993  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.683995  5581 caffe.cpp:501] detection_eval = 7.46371
-I0511 11:50:55.683998  5581 caffe.cpp:501] detection_eval = 10.5101
-I0511 11:50:55.684000  5581 caffe.cpp:501] detection_eval = 0.0438768
-I0511 11:50:55.684005  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.684007  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.684010  5581 caffe.cpp:501] detection_eval = 7.46371
-I0511 11:50:55.684012  5581 caffe.cpp:501] detection_eval = 10.5766
-I0511 11:50:55.684015  5581 caffe.cpp:501] detection_eval = 0.0471612
-I0511 11:50:55.684016  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684020  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684021  5581 caffe.cpp:501] detection_eval = 7.46774
-I0511 11:50:55.684023  5581 caffe.cpp:501] detection_eval = 10.6149
-I0511 11:50:55.684026  5581 caffe.cpp:501] detection_eval = 0.0489806
-I0511 11:50:55.684027  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.684029  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684032  5581 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:50:55.684034  5581 caffe.cpp:501] detection_eval = 10.5141
-I0511 11:50:55.684036  5581 caffe.cpp:501] detection_eval = 0.0471047
-I0511 11:50:55.684038  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.684041  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.684043  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.684046  5581 caffe.cpp:501] detection_eval = 10.5444
-I0511 11:50:55.684047  5581 caffe.cpp:501] detection_eval = 0.0454401
-I0511 11:50:55.684051  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.684053  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.684056  5581 caffe.cpp:501] detection_eval = 7.48387
-I0511 11:50:55.684059  5581 caffe.cpp:501] detection_eval = 10.5746
-I0511 11:50:55.684062  5581 caffe.cpp:501] detection_eval = 0.0470474
-I0511 11:50:55.684063  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684065  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684067  5581 caffe.cpp:501] detection_eval = 7.48589
-I0511 11:50:55.684069  5581 caffe.cpp:501] detection_eval = 10.6694
-I0511 11:50:55.684072  5581 caffe.cpp:501] detection_eval = 0.0476696
-I0511 11:50:55.684074  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.684077  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.684078  5581 caffe.cpp:501] detection_eval = 7.4879
-I0511 11:50:55.684080  5581 caffe.cpp:501] detection_eval = 10.6855
-I0511 11:50:55.684659  5581 caffe.cpp:501] detection_eval = 0.0402981
-I0511 11:50:55.684667  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.684670  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.684672  5581 caffe.cpp:501] detection_eval = 7.49194
-I0511 11:50:55.684674  5581 caffe.cpp:501] detection_eval = 10.6492
-I0511 11:50:55.684677  5581 caffe.cpp:501] detection_eval = 0.0420391
-I0511 11:50:55.684679  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.684681  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.684684  5581 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:50:55.684686  5581 caffe.cpp:501] detection_eval = 10.621
-I0511 11:50:55.684689  5581 caffe.cpp:501] detection_eval = 0.0434594
-I0511 11:50:55.684691  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684693  5581 caffe.cpp:501] detection_eval = 0.967742
-I0511 11:50:55.684695  5581 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:50:55.684697  5581 caffe.cpp:501] detection_eval = 10.6935
-I0511 11:50:55.684700  5581 caffe.cpp:501] detection_eval = 0.0417081
-I0511 11:50:55.684702  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.684705  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.684706  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.684710  5581 caffe.cpp:501] detection_eval = 10.7097
-I0511 11:50:55.684711  5581 caffe.cpp:501] detection_eval = 0.0412181
-I0511 11:50:55.684713  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684715  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684718  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684720  5581 caffe.cpp:501] detection_eval = 10.7379
-I0511 11:50:55.684722  5581 caffe.cpp:501] detection_eval = 0.0399339
-I0511 11:50:55.684728  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684731  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684733  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684736  5581 caffe.cpp:501] detection_eval = 10.8105
-I0511 11:50:55.684738  5581 caffe.cpp:501] detection_eval = 0.0444372
-I0511 11:50:55.684741  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.684742  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.684744  5581 caffe.cpp:501] detection_eval = 7.46573
-I0511 11:50:55.684747  5581 caffe.cpp:501] detection_eval = 10.8165
-I0511 11:50:55.684749  5581 caffe.cpp:501] detection_eval = 0.0440735
-I0511 11:50:55.684751  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.684753  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.684756  5581 caffe.cpp:501] detection_eval = 7.46976
-I0511 11:50:55.684758  5581 caffe.cpp:501] detection_eval = 10.8065
-I0511 11:50:55.684761  5581 caffe.cpp:501] detection_eval = 0.0413515
-I0511 11:50:55.684762  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684764  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684767  5581 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:50:55.684769  5581 caffe.cpp:501] detection_eval = 10.8468
-I0511 11:50:55.684772  5581 caffe.cpp:501] detection_eval = 0.0372818
-I0511 11:50:55.684773  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.684775  5581 caffe.cpp:501] detection_eval = 0.977823
-I0511 11:50:55.684778  5581 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:50:55.684780  5581 caffe.cpp:501] detection_eval = 10.9173
-I0511 11:50:55.684782  5581 caffe.cpp:501] detection_eval = 0.0365128
-I0511 11:50:55.684784  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.684787  5581 caffe.cpp:501] detection_eval = 0.971774
-I0511 11:50:55.684789  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.684792  5581 caffe.cpp:501] detection_eval = 10.875
-I0511 11:50:55.684793  5581 caffe.cpp:501] detection_eval = 0.0408489
-I0511 11:50:55.684795  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.684798  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684800  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684803  5581 caffe.cpp:501] detection_eval = 10.9355
-I0511 11:50:55.684805  5581 caffe.cpp:501] detection_eval = 0.0390675
-I0511 11:50:55.684808  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.684809  5581 caffe.cpp:501] detection_eval = 0.97379
-I0511 11:50:55.684811  5581 caffe.cpp:501] detection_eval = 7.48387
-I0511 11:50:55.684814  5581 caffe.cpp:501] detection_eval = 10.9516
-I0511 11:50:55.684816  5581 caffe.cpp:501] detection_eval = 0.0401807
-I0511 11:50:55.684818  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684820  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684823  5581 caffe.cpp:501] detection_eval = 7.4879
-I0511 11:50:55.684825  5581 caffe.cpp:501] detection_eval = 10.9617
-I0511 11:50:55.684828  5581 caffe.cpp:501] detection_eval = 0.0392556
-I0511 11:50:55.684829  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.684831  5581 caffe.cpp:501] detection_eval = 0.969758
-I0511 11:50:55.684834  5581 caffe.cpp:501] detection_eval = 7.48992
-I0511 11:50:55.684836  5581 caffe.cpp:501] detection_eval = 11.0121
-I0511 11:50:55.684839  5581 caffe.cpp:501] detection_eval = 0.0392255
-I0511 11:50:55.684841  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.684844  5581 caffe.cpp:501] detection_eval = 0.975806
-I0511 11:50:55.684845  5581 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:50:55.684847  5581 caffe.cpp:501] detection_eval = 10.9657
-I0511 11:50:55.684850  5581 caffe.cpp:501] detection_eval = 0.0426831
-I0511 11:50:55.684852  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684854  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.684856  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684859  5581 caffe.cpp:501] detection_eval = 10.9718
-I0511 11:50:55.684864  5581 caffe.cpp:501] detection_eval = 0.0473402
-I0511 11:50:55.684866  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.684868  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.684870  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684872  5581 caffe.cpp:501] detection_eval = 11.0645
-I0511 11:50:55.684875  5581 caffe.cpp:501] detection_eval = 0.0464121
-I0511 11:50:55.684877  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.684880  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.684881  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.684883  5581 caffe.cpp:501] detection_eval = 11.127
-I0511 11:50:55.684886  5581 caffe.cpp:501] detection_eval = 0.0424388
-I0511 11:50:55.684888  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684890  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.684892  5581 caffe.cpp:501] detection_eval = 7.48589
-I0511 11:50:55.684895  5581 caffe.cpp:501] detection_eval = 11.1331
-I0511 11:50:55.684897  5581 caffe.cpp:501] detection_eval = 0.0401256
-I0511 11:50:55.684900  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684901  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.684903  5581 caffe.cpp:501] detection_eval = 7.47379
-I0511 11:50:55.684906  5581 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:50:55.684908  5581 caffe.cpp:501] detection_eval = 0.0425275
-I0511 11:50:55.684911  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684912  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.684914  5581 caffe.cpp:501] detection_eval = 7.47782
-I0511 11:50:55.684916  5581 caffe.cpp:501] detection_eval = 11.1351
-I0511 11:50:55.684919  5581 caffe.cpp:501] detection_eval = 0.0435966
-I0511 11:50:55.684921  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.684923  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.684926  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.684928  5581 caffe.cpp:501] detection_eval = 11.1835
-I0511 11:50:55.684931  5581 caffe.cpp:501] detection_eval = 0.0434549
-I0511 11:50:55.684932  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.684934  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685073  5581 caffe.cpp:501] detection_eval = 7.46169
-I0511 11:50:55.685081  5581 caffe.cpp:501] detection_eval = 11.2077
-I0511 11:50:55.685084  5581 caffe.cpp:501] detection_eval = 0.0367104
-I0511 11:50:55.685086  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685089  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685091  5581 caffe.cpp:501] detection_eval = 7.46774
-I0511 11:50:55.685093  5581 caffe.cpp:501] detection_eval = 11.1915
-I0511 11:50:55.685096  5581 caffe.cpp:501] detection_eval = 0.0421262
-I0511 11:50:55.685098  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685101  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.685102  5581 caffe.cpp:501] detection_eval = 7.47581
-I0511 11:50:55.685106  5581 caffe.cpp:501] detection_eval = 11.131
-I0511 11:50:55.685107  5581 caffe.cpp:501] detection_eval = 0.0413167
-I0511 11:50:55.685109  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685111  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.685114  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.685117  5581 caffe.cpp:501] detection_eval = 11.0867
-I0511 11:50:55.685118  5581 caffe.cpp:501] detection_eval = 0.0430667
-I0511 11:50:55.685120  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685123  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685125  5581 caffe.cpp:501] detection_eval = 7.48589
-I0511 11:50:55.685127  5581 caffe.cpp:501] detection_eval = 11.0423
-I0511 11:50:55.685129  5581 caffe.cpp:501] detection_eval = 0.04003
-I0511 11:50:55.685132  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685134  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.685137  5581 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:50:55.685138  5581 caffe.cpp:501] detection_eval = 11
-I0511 11:50:55.685144  5581 caffe.cpp:501] detection_eval = 0.0428109
-I0511 11:50:55.685148  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.685149  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685151  5581 caffe.cpp:501] detection_eval = 7.47581
-I0511 11:50:55.685154  5581 caffe.cpp:501] detection_eval = 10.9758
-I0511 11:50:55.685156  5581 caffe.cpp:501] detection_eval = 0.0399438
-I0511 11:50:55.685158  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685161  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685163  5581 caffe.cpp:501] detection_eval = 7.47984
-I0511 11:50:55.685165  5581 caffe.cpp:501] detection_eval = 10.9798
-I0511 11:50:55.685168  5581 caffe.cpp:501] detection_eval = 0.0389812
-I0511 11:50:55.685170  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685173  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685174  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.685176  5581 caffe.cpp:501] detection_eval = 11.0302
-I0511 11:50:55.685178  5581 caffe.cpp:501] detection_eval = 0.04282
-I0511 11:50:55.685181  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.685184  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.685185  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.685189  5581 caffe.cpp:501] detection_eval = 11.1089
-I0511 11:50:55.685190  5581 caffe.cpp:501] detection_eval = 0.0414344
-I0511 11:50:55.685192  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.685194  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685196  5581 caffe.cpp:501] detection_eval = 7.49395
-I0511 11:50:55.685199  5581 caffe.cpp:501] detection_eval = 11.0444
-I0511 11:50:55.685201  5581 caffe.cpp:501] detection_eval = 0.0440561
-I0511 11:50:55.685204  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685205  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.685207  5581 caffe.cpp:501] detection_eval = 7.49597
-I0511 11:50:55.685210  5581 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:50:55.685212  5581 caffe.cpp:501] detection_eval = 0.0436372
-I0511 11:50:55.685214  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685216  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685220  5581 caffe.cpp:501] detection_eval = 7.5
-I0511 11:50:55.685221  5581 caffe.cpp:501] detection_eval = 11.1008
-I0511 11:50:55.685223  5581 caffe.cpp:501] detection_eval = 0.0405424
-I0511 11:50:55.685225  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685228  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685230  5581 caffe.cpp:501] detection_eval = 7.50403
-I0511 11:50:55.685232  5581 caffe.cpp:501] detection_eval = 11.0867
-I0511 11:50:55.685235  5581 caffe.cpp:501] detection_eval = 0.0439476
-I0511 11:50:55.685236  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685240  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685241  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.685243  5581 caffe.cpp:501] detection_eval = 11.0867
-I0511 11:50:55.685245  5581 caffe.cpp:501] detection_eval = 0.0410073
-I0511 11:50:55.685247  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685250  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685252  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.685254  5581 caffe.cpp:501] detection_eval = 11.1754
-I0511 11:50:55.685256  5581 caffe.cpp:501] detection_eval = 0.0386972
-I0511 11:50:55.685258  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685261  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685263  5581 caffe.cpp:501] detection_eval = 7.5121
-I0511 11:50:55.685266  5581 caffe.cpp:501] detection_eval = 11.1976
-I0511 11:50:55.685267  5581 caffe.cpp:501] detection_eval = 0.0414127
-I0511 11:50:55.685269  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685272  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685274  5581 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:50:55.685278  5581 caffe.cpp:501] detection_eval = 11.1653
-I0511 11:50:55.685281  5581 caffe.cpp:501] detection_eval = 0.0389808
-I0511 11:50:55.685283  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685286  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685288  5581 caffe.cpp:501] detection_eval = 7.5
-I0511 11:50:55.685290  5581 caffe.cpp:501] detection_eval = 11.1976
-I0511 11:50:55.685292  5581 caffe.cpp:501] detection_eval = 0.0401342
-I0511 11:50:55.685294  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.685297  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685299  5581 caffe.cpp:501] detection_eval = 7.50605
-I0511 11:50:55.685302  5581 caffe.cpp:501] detection_eval = 11.2137
-I0511 11:50:55.685303  5581 caffe.cpp:501] detection_eval = 0.0410004
-I0511 11:50:55.685307  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.685308  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.685310  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.685312  5581 caffe.cpp:501] detection_eval = 11.25
-I0511 11:50:55.685314  5581 caffe.cpp:501] detection_eval = 0.0405454
-I0511 11:50:55.685317  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685319  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685322  5581 caffe.cpp:501] detection_eval = 7.51815
-I0511 11:50:55.685323  5581 caffe.cpp:501] detection_eval = 11.1411
-I0511 11:50:55.685326  5581 caffe.cpp:501] detection_eval = 0.0426148
-I0511 11:50:55.685328  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.685330  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.685333  5581 caffe.cpp:501] detection_eval = 7.52218
-I0511 11:50:55.685334  5581 caffe.cpp:501] detection_eval = 11.1714
-I0511 11:50:55.685338  5581 caffe.cpp:501] detection_eval = 0.0390047
-I0511 11:50:55.685339  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685341  5581 caffe.cpp:501] detection_eval = 0.965726
-I0511 11:50:55.685343  5581 caffe.cpp:501] detection_eval = 7.52419
-I0511 11:50:55.685345  5581 caffe.cpp:501] detection_eval = 11.2157
-I0511 11:50:55.685348  5581 caffe.cpp:501] detection_eval = 0.0375133
-I0511 11:50:55.685899  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685906  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685909  5581 caffe.cpp:501] detection_eval = 7.53226
-I0511 11:50:55.685911  5581 caffe.cpp:501] detection_eval = 11.1633
-I0511 11:50:55.685914  5581 caffe.cpp:501] detection_eval = 0.0388819
-I0511 11:50:55.685916  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685919  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.685920  5581 caffe.cpp:501] detection_eval = 7.53831
-I0511 11:50:55.685923  5581 caffe.cpp:501] detection_eval = 11.1411
-I0511 11:50:55.685925  5581 caffe.cpp:501] detection_eval = 0.0386862
-I0511 11:50:55.685927  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.685930  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.685932  5581 caffe.cpp:501] detection_eval = 7.54435
-I0511 11:50:55.685935  5581 caffe.cpp:501] detection_eval = 11.129
-I0511 11:50:55.685936  5581 caffe.cpp:501] detection_eval = 0.0423654
-I0511 11:50:55.685940  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685941  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685943  5581 caffe.cpp:501] detection_eval = 7.54637
-I0511 11:50:55.685945  5581 caffe.cpp:501] detection_eval = 11.1653
-I0511 11:50:55.685948  5581 caffe.cpp:501] detection_eval = 0.0426899
-I0511 11:50:55.685950  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.685952  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.685955  5581 caffe.cpp:501] detection_eval = 7.54839
-I0511 11:50:55.685956  5581 caffe.cpp:501] detection_eval = 11.1875
-I0511 11:50:55.685959  5581 caffe.cpp:501] detection_eval = 0.0403573
-I0511 11:50:55.685961  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.685963  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.685969  5581 caffe.cpp:501] detection_eval = 7.54839
-I0511 11:50:55.685972  5581 caffe.cpp:501] detection_eval = 11.254
-I0511 11:50:55.685974  5581 caffe.cpp:501] detection_eval = 0.0407816
-I0511 11:50:55.685976  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.685979  5581 caffe.cpp:501] detection_eval = 0.961694
-I0511 11:50:55.685981  5581 caffe.cpp:501] detection_eval = 7.55242
-I0511 11:50:55.685983  5581 caffe.cpp:501] detection_eval = 11.2238
-I0511 11:50:55.685986  5581 caffe.cpp:501] detection_eval = 0.0359233
-I0511 11:50:55.685987  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.685991  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.685992  5581 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:50:55.685994  5581 caffe.cpp:501] detection_eval = 11.2399
-I0511 11:50:55.685997  5581 caffe.cpp:501] detection_eval = 0.0348085
-I0511 11:50:55.685999  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.686002  5581 caffe.cpp:501] detection_eval = 0.96371
-I0511 11:50:55.686003  5581 caffe.cpp:501] detection_eval = 7.56653
-I0511 11:50:55.686005  5581 caffe.cpp:501] detection_eval = 11.2137
-I0511 11:50:55.686007  5581 caffe.cpp:501] detection_eval = 0.0421677
-I0511 11:50:55.686010  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.686012  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.686014  5581 caffe.cpp:501] detection_eval = 7.56855
-I0511 11:50:55.686017  5581 caffe.cpp:501] detection_eval = 11.2762
-I0511 11:50:55.686018  5581 caffe.cpp:501] detection_eval = 0.0450314
-I0511 11:50:55.686022  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.686023  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686025  5581 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:50:55.686028  5581 caffe.cpp:501] detection_eval = 11.3044
-I0511 11:50:55.686029  5581 caffe.cpp:501] detection_eval = 0.0410906
-I0511 11:50:55.686033  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.686034  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.686036  5581 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:50:55.686038  5581 caffe.cpp:501] detection_eval = 11.1935
-I0511 11:50:55.686041  5581 caffe.cpp:501] detection_eval = 0.0495097
-I0511 11:50:55.686043  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.686045  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686048  5581 caffe.cpp:501] detection_eval = 7.59073
-I0511 11:50:55.686049  5581 caffe.cpp:501] detection_eval = 11.1552
-I0511 11:50:55.686053  5581 caffe.cpp:501] detection_eval = 0.0434247
-I0511 11:50:55.686054  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.686056  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686058  5581 caffe.cpp:501] detection_eval = 7.59274
-I0511 11:50:55.686060  5581 caffe.cpp:501] detection_eval = 11.1996
-I0511 11:50:55.686064  5581 caffe.cpp:501] detection_eval = 0.0404944
-I0511 11:50:55.686065  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686067  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.686069  5581 caffe.cpp:501] detection_eval = 7.59274
-I0511 11:50:55.686071  5581 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:50:55.686074  5581 caffe.cpp:501] detection_eval = 0.0398476
-I0511 11:50:55.686076  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.686079  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686080  5581 caffe.cpp:501] detection_eval = 7.59879
-I0511 11:50:55.686082  5581 caffe.cpp:501] detection_eval = 11.2641
-I0511 11:50:55.686085  5581 caffe.cpp:501] detection_eval = 0.0413881
-I0511 11:50:55.686087  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686089  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.686091  5581 caffe.cpp:501] detection_eval = 7.60887
-I0511 11:50:55.686094  5581 caffe.cpp:501] detection_eval = 11.2298
-I0511 11:50:55.686096  5581 caffe.cpp:501] detection_eval = 0.0435242
-I0511 11:50:55.686098  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686100  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.686105  5581 caffe.cpp:501] detection_eval = 7.6129
-I0511 11:50:55.686108  5581 caffe.cpp:501] detection_eval = 11.2722
-I0511 11:50:55.686110  5581 caffe.cpp:501] detection_eval = 0.0469073
-I0511 11:50:55.686112  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.686115  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686117  5581 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:50:55.686120  5581 caffe.cpp:501] detection_eval = 11.2782
-I0511 11:50:55.686121  5581 caffe.cpp:501] detection_eval = 0.0396851
-I0511 11:50:55.686123  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686126  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.686128  5581 caffe.cpp:501] detection_eval = 7.62298
-I0511 11:50:55.686131  5581 caffe.cpp:501] detection_eval = 11.25
-I0511 11:50:55.686132  5581 caffe.cpp:501] detection_eval = 0.0402459
-I0511 11:50:55.686134  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686137  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.686139  5581 caffe.cpp:501] detection_eval = 7.625
-I0511 11:50:55.686141  5581 caffe.cpp:501] detection_eval = 11.2681
-I0511 11:50:55.686143  5581 caffe.cpp:501] detection_eval = 0.0385593
-I0511 11:50:55.686146  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.686148  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.686151  5581 caffe.cpp:501] detection_eval = 7.62903
-I0511 11:50:55.686152  5581 caffe.cpp:501] detection_eval = 11.2742
-I0511 11:50:55.686154  5581 caffe.cpp:501] detection_eval = 0.041121
-I0511 11:50:55.686157  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.686159  5581 caffe.cpp:501] detection_eval = 0.957661
-I0511 11:50:55.686161  5581 caffe.cpp:501] detection_eval = 7.61089
-I0511 11:50:55.686164  5581 caffe.cpp:501] detection_eval = 11.3327
-I0511 11:50:55.686168  5581 caffe.cpp:501] detection_eval = 0.0439781
-I0511 11:50:55.686170  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.686172  5581 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:50:55.686175  5581 caffe.cpp:501] detection_eval = 7.6129
-I0511 11:50:55.688241  5581 caffe.cpp:501] detection_eval = 11.3911
-I0511 11:50:55.688256  5581 caffe.cpp:501] detection_eval = 0.0422813
-I0511 11:50:55.688261  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.688266  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688268  5581 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:50:55.688272  5581 caffe.cpp:501] detection_eval = 11.4274
-I0511 11:50:55.688275  5581 caffe.cpp:501] detection_eval = 0.0426222
-I0511 11:50:55.688279  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.688282  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.688287  5581 caffe.cpp:501] detection_eval = 7.61694
-I0511 11:50:55.688289  5581 caffe.cpp:501] detection_eval = 11.5101
-I0511 11:50:55.688292  5581 caffe.cpp:501] detection_eval = 0.0423069
-I0511 11:50:55.688297  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688300  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688304  5581 caffe.cpp:501] detection_eval = 7.62298
-I0511 11:50:55.688308  5581 caffe.cpp:501] detection_eval = 11.4819
-I0511 11:50:55.688311  5581 caffe.cpp:501] detection_eval = 0.0420618
-I0511 11:50:55.688315  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688318  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688321  5581 caffe.cpp:501] detection_eval = 7.62702
-I0511 11:50:55.688325  5581 caffe.cpp:501] detection_eval = 11.5302
-I0511 11:50:55.688329  5581 caffe.cpp:501] detection_eval = 0.043554
-I0511 11:50:55.688333  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688338  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.688340  5581 caffe.cpp:501] detection_eval = 7.63105
-I0511 11:50:55.688344  5581 caffe.cpp:501] detection_eval = 11.5927
-I0511 11:50:55.688347  5581 caffe.cpp:501] detection_eval = 0.0423784
-I0511 11:50:55.688351  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.688361  5581 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:50:55.688365  5581 caffe.cpp:501] detection_eval = 7.63306
-I0511 11:50:55.688369  5581 caffe.cpp:501] detection_eval = 11.6089
-I0511 11:50:55.688372  5581 caffe.cpp:501] detection_eval = 0.0439374
-I0511 11:50:55.688376  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.688380  5581 caffe.cpp:501] detection_eval = 0.947581
-I0511 11:50:55.688385  5581 caffe.cpp:501] detection_eval = 7.61895
-I0511 11:50:55.688388  5581 caffe.cpp:501] detection_eval = 11.5645
-I0511 11:50:55.688391  5581 caffe.cpp:501] detection_eval = 0.0409858
-I0511 11:50:55.688395  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.688400  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688402  5581 caffe.cpp:501] detection_eval = 7.62097
-I0511 11:50:55.688405  5581 caffe.cpp:501] detection_eval = 11.5887
-I0511 11:50:55.688410  5581 caffe.cpp:501] detection_eval = 0.0433036
-I0511 11:50:55.688412  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688416  5581 caffe.cpp:501] detection_eval = 0.955645
-I0511 11:50:55.688421  5581 caffe.cpp:501] detection_eval = 7.62702
-I0511 11:50:55.688423  5581 caffe.cpp:501] detection_eval = 11.5665
-I0511 11:50:55.688427  5581 caffe.cpp:501] detection_eval = 0.0424148
-I0511 11:50:55.688431  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.688434  5581 caffe.cpp:501] detection_eval = 0.951613
-I0511 11:50:55.688438  5581 caffe.cpp:501] detection_eval = 7.59879
-I0511 11:50:55.688441  5581 caffe.cpp:501] detection_eval = 11.4597
-I0511 11:50:55.688446  5581 caffe.cpp:501] detection_eval = 0.0412049
-I0511 11:50:55.688448  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688452  5581 caffe.cpp:501] detection_eval = 0.953629
-I0511 11:50:55.688457  5581 caffe.cpp:501] detection_eval = 7.60282
-I0511 11:50:55.688459  5581 caffe.cpp:501] detection_eval = 11.4899
-I0511 11:50:55.688463  5581 caffe.cpp:501] detection_eval = 0.0375759
-I0511 11:50:55.688467  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.688470  5581 caffe.cpp:501] detection_eval = 0.959677
-I0511 11:50:55.688474  5581 caffe.cpp:501] detection_eval = 7.58669
-I0511 11:50:55.688477  5581 caffe.cpp:501] detection_eval = 11.5081
-I0511 11:50:55.688482  5581 caffe.cpp:501] detection_eval = 0.042409
-I0511 11:50:55.688484  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688488  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.688493  5581 caffe.cpp:501] detection_eval = 7.58871
-I0511 11:50:55.688495  5581 caffe.cpp:501] detection_eval = 11.5484
-I0511 11:50:55.688499  5581 caffe.cpp:501] detection_eval = 0.0379165
-I0511 11:50:55.688503  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688506  5581 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:50:55.688509  5581 caffe.cpp:501] detection_eval = 7.57661
-I0511 11:50:55.688513  5581 caffe.cpp:501] detection_eval = 11.4919
-I0511 11:50:55.688518  5581 caffe.cpp:501] detection_eval = 0.0370752
-I0511 11:50:55.688520  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.688539  5581 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:50:55.688544  5581 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:50:55.688547  5581 caffe.cpp:501] detection_eval = 11.4839
-I0511 11:50:55.688551  5581 caffe.cpp:501] detection_eval = 0.0377361
-I0511 11:50:55.688555  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.688558  5581 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:50:55.688561  5581 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:50:55.688565  5581 caffe.cpp:501] detection_eval = 11.4556
-I0511 11:50:55.688568  5581 caffe.cpp:501] detection_eval = 0.0405849
-I0511 11:50:55.688572  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.688575  5581 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:50:55.688580  5581 caffe.cpp:501] detection_eval = 7.57258
-I0511 11:50:55.688582  5581 caffe.cpp:501] detection_eval = 11.4758
-I0511 11:50:55.688586  5581 caffe.cpp:501] detection_eval = 0.037887
-I0511 11:50:55.688591  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.688601  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.688606  5581 caffe.cpp:501] detection_eval = 7.5746
-I0511 11:50:55.688609  5581 caffe.cpp:501] detection_eval = 11.5605
-I0511 11:50:55.688613  5581 caffe.cpp:501] detection_eval = 0.0378704
-I0511 11:50:55.688617  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.688621  5581 caffe.cpp:501] detection_eval = 0.949597
-I0511 11:50:55.688625  5581 caffe.cpp:501] detection_eval = 7.56048
-I0511 11:50:55.688629  5581 caffe.cpp:501] detection_eval = 11.5847
-I0511 11:50:55.688633  5581 caffe.cpp:501] detection_eval = 0.0387462
-I0511 11:50:55.688637  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.688642  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.688645  5581 caffe.cpp:501] detection_eval = 7.56653
-I0511 11:50:55.688648  5581 caffe.cpp:501] detection_eval = 11.6573
-I0511 11:50:55.688653  5581 caffe.cpp:501] detection_eval = 0.0348863
-I0511 11:50:55.688663  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688666  5581 caffe.cpp:501] detection_eval = 0.943548
-I0511 11:50:55.688670  5581 caffe.cpp:501] detection_eval = 7.57056
-I0511 11:50:55.688674  5581 caffe.cpp:501] detection_eval = 11.8044
-I0511 11:50:55.688678  5581 caffe.cpp:501] detection_eval = 0.0350609
-I0511 11:50:55.688683  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.688686  5581 caffe.cpp:501] detection_eval = 0.945565
-I0511 11:50:55.688690  5581 caffe.cpp:501] detection_eval = 7.83266
-I0511 11:50:55.688694  5581 caffe.cpp:501] detection_eval = 7.9254
-I0511 11:50:55.688699  5581 caffe.cpp:501] detection_eval = 0.0567618
-I0511 11:50:55.688701  5581 caffe.cpp:501] detection_eval = 0.0322581
-I0511 11:50:55.688705  5581 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:50:55.688709  5581 caffe.cpp:501] detection_eval = 7.81653
-I0511 11:50:55.688711  5581 caffe.cpp:501] detection_eval = 7.99597
-I0511 11:50:55.688715  5581 caffe.cpp:501] detection_eval = 0.0480278
-I0511 11:50:55.688719  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688725  5581 caffe.cpp:501] detection_eval = 0.935484
-I0511 11:50:55.688729  5581 caffe.cpp:501] detection_eval = 7.81653
-I0511 11:50:55.688732  5581 caffe.cpp:501] detection_eval = 8.10282
-I0511 11:50:55.688735  5581 caffe.cpp:501] detection_eval = 0.0471522
-I0511 11:50:55.688740  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.688742  5581 caffe.cpp:501] detection_eval = 0.927419
-I0511 11:50:55.688746  5581 caffe.cpp:501] detection_eval = 7.79839
-I0511 11:50:55.688750  5581 caffe.cpp:501] detection_eval = 8.20968
-I0511 11:50:55.688752  5581 caffe.cpp:501] detection_eval = 0.0480241
-I0511 11:50:55.688756  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.688760  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.688765  5581 caffe.cpp:501] detection_eval = 7.8004
-I0511 11:50:55.688767  5581 caffe.cpp:501] detection_eval = 8.27016
-I0511 11:50:55.688771  5581 caffe.cpp:501] detection_eval = 0.0514556
-I0511 11:50:55.688774  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.688778  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.688782  5581 caffe.cpp:501] detection_eval = 7.80444
-I0511 11:50:55.688786  5581 caffe.cpp:501] detection_eval = 8.29637
-I0511 11:50:55.688789  5581 caffe.cpp:501] detection_eval = 0.0425682
-I0511 11:50:55.688793  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.688797  5581 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:50:55.688802  5581 caffe.cpp:501] detection_eval = 7.78831
-I0511 11:50:55.688804  5581 caffe.cpp:501] detection_eval = 8.32056
-I0511 11:50:55.688808  5581 caffe.cpp:501] detection_eval = 0.0429682
-I0511 11:50:55.688812  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.688817  5581 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:50:55.688820  5581 caffe.cpp:501] detection_eval = 7.79032
-I0511 11:50:55.688823  5581 caffe.cpp:501] detection_eval = 8.36694
-I0511 11:50:55.688827  5581 caffe.cpp:501] detection_eval = 0.0469394
-I0511 11:50:55.688838  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688843  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.688846  5581 caffe.cpp:501] detection_eval = 7.79032
-I0511 11:50:55.688850  5581 caffe.cpp:501] detection_eval = 8.40323
-I0511 11:50:55.688854  5581 caffe.cpp:501] detection_eval = 0.0435947
-I0511 11:50:55.688858  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.688863  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.688866  5581 caffe.cpp:501] detection_eval = 7.79435
-I0511 11:50:55.688870  5581 caffe.cpp:501] detection_eval = 8.39113
-I0511 11:50:55.688874  5581 caffe.cpp:501] detection_eval = 0.0455785
-I0511 11:50:55.688879  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688881  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.688885  5581 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:50:55.688889  5581 caffe.cpp:501] detection_eval = 8.40927
-I0511 11:50:55.688894  5581 caffe.cpp:501] detection_eval = 0.0375263
-I0511 11:50:55.688897  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.688901  5581 caffe.cpp:501] detection_eval = 0.9375
-I0511 11:50:55.688905  5581 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:50:55.688908  5581 caffe.cpp:501] detection_eval = 8.49395
-I0511 11:50:55.688912  5581 caffe.cpp:501] detection_eval = 0.0382623
-I0511 11:50:55.688916  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.688920  5581 caffe.cpp:501] detection_eval = 0.939516
-I0511 11:50:55.688925  5581 caffe.cpp:501] detection_eval = 7.75806
-I0511 11:50:55.688930  5581 caffe.cpp:501] detection_eval = 8.49597
-I0511 11:50:55.688933  5581 caffe.cpp:501] detection_eval = 0.0384884
-I0511 11:50:55.688937  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.688941  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.688946  5581 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:50:55.688948  5581 caffe.cpp:501] detection_eval = 8.4879
-I0511 11:50:55.688952  5581 caffe.cpp:501] detection_eval = 0.0394526
-I0511 11:50:55.688956  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.688959  5581 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:50:55.688963  5581 caffe.cpp:501] detection_eval = 7.7621
-I0511 11:50:55.688966  5581 caffe.cpp:501] detection_eval = 8.56653
-I0511 11:50:55.688971  5581 caffe.cpp:501] detection_eval = 0.0439014
-I0511 11:50:55.688973  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.688977  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.688982  5581 caffe.cpp:501] detection_eval = 7.76815
-I0511 11:50:55.688985  5581 caffe.cpp:501] detection_eval = 8.53226
-I0511 11:50:55.688988  5581 caffe.cpp:501] detection_eval = 0.044634
-I0511 11:50:55.688992  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.688997  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.688999  5581 caffe.cpp:501] detection_eval = 7.77016
-I0511 11:50:55.689003  5581 caffe.cpp:501] detection_eval = 8.5625
-I0511 11:50:55.689007  5581 caffe.cpp:501] detection_eval = 0.0422691
-I0511 11:50:55.689011  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.689015  5581 caffe.cpp:501] detection_eval = 0.929435
-I0511 11:50:55.689018  5581 caffe.cpp:501] detection_eval = 7.77016
-I0511 11:50:55.689023  5581 caffe.cpp:501] detection_eval = 8.65323
-I0511 11:50:55.689025  5581 caffe.cpp:501] detection_eval = 0.0407678
-I0511 11:50:55.689029  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.689033  5581 caffe.cpp:501] detection_eval = 0.931452
-I0511 11:50:55.689036  5581 caffe.cpp:501] detection_eval = 7.77621
-I0511 11:50:55.689040  5581 caffe.cpp:501] detection_eval = 8.65323
-I0511 11:50:55.689044  5581 caffe.cpp:501] detection_eval = 0.0451118
-I0511 11:50:55.689054  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.689059  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.689062  5581 caffe.cpp:501] detection_eval = 7.77823
-I0511 11:50:55.689066  5581 caffe.cpp:501] detection_eval = 8.65524
-I0511 11:50:55.689070  5581 caffe.cpp:501] detection_eval = 0.0421557
-I0511 11:50:55.689079  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.689085  5581 caffe.cpp:501] detection_eval = 0.927419
-I0511 11:50:55.689088  5581 caffe.cpp:501] detection_eval = 7.74395
-I0511 11:50:55.689092  5581 caffe.cpp:501] detection_eval = 8.64113
-I0511 11:50:55.689096  5581 caffe.cpp:501] detection_eval = 0.0414038
-I0511 11:50:55.689100  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.689103  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.689107  5581 caffe.cpp:501] detection_eval = 7.74395
-I0511 11:50:55.689111  5581 caffe.cpp:501] detection_eval = 8.72379
-I0511 11:50:55.689116  5581 caffe.cpp:501] detection_eval = 0.0421193
-I0511 11:50:55.689119  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.689123  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.689127  5581 caffe.cpp:501] detection_eval = 7.74597
-I0511 11:50:55.689131  5581 caffe.cpp:501] detection_eval = 8.78024
-I0511 11:50:55.689136  5581 caffe.cpp:501] detection_eval = 0.042194
-I0511 11:50:55.689139  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.689143  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.689147  5581 caffe.cpp:501] detection_eval = 7.7379
-I0511 11:50:55.689152  5581 caffe.cpp:501] detection_eval = 8.70161
-I0511 11:50:55.689155  5581 caffe.cpp:501] detection_eval = 0.0456673
-I0511 11:50:55.689159  5581 caffe.cpp:501] detection_eval = 0.0262097
-I0511 11:50:55.689163  5581 caffe.cpp:501] detection_eval = 0.903226
-I0511 11:50:55.689167  5581 caffe.cpp:501] detection_eval = 7.74194
-I0511 11:50:55.689172  5581 caffe.cpp:501] detection_eval = 8.75202
-I0511 11:50:55.689175  5581 caffe.cpp:501] detection_eval = 0.0475273
-I0511 11:50:55.689179  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.689183  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.689188  5581 caffe.cpp:501] detection_eval = 7.75
-I0511 11:50:55.689191  5581 caffe.cpp:501] detection_eval = 8.72782
-I0511 11:50:55.690340  5581 caffe.cpp:501] detection_eval = 0.044641
-I0511 11:50:55.690354  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.690359  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.690364  5581 caffe.cpp:501] detection_eval = 7.73589
-I0511 11:50:55.690368  5581 caffe.cpp:501] detection_eval = 8.69153
-I0511 11:50:55.690372  5581 caffe.cpp:501] detection_eval = 0.0392837
-I0511 11:50:55.690377  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690381  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.690384  5581 caffe.cpp:501] detection_eval = 7.73992
-I0511 11:50:55.690388  5581 caffe.cpp:501] detection_eval = 8.6996
-I0511 11:50:55.690393  5581 caffe.cpp:501] detection_eval = 0.0397084
-I0511 11:50:55.690397  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690402  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.690405  5581 caffe.cpp:501] detection_eval = 7.74597
-I0511 11:50:55.690409  5581 caffe.cpp:501] detection_eval = 8.69556
-I0511 11:50:55.690413  5581 caffe.cpp:501] detection_eval = 0.0382193
-I0511 11:50:55.690418  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.690421  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.690425  5581 caffe.cpp:501] detection_eval = 7.72782
-I0511 11:50:55.690429  5581 caffe.cpp:501] detection_eval = 8.81855
-I0511 11:50:55.690434  5581 caffe.cpp:501] detection_eval = 0.0478034
-I0511 11:50:55.690438  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.690443  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.690446  5581 caffe.cpp:501] detection_eval = 7.73185
-I0511 11:50:55.690450  5581 caffe.cpp:501] detection_eval = 8.85887
-I0511 11:50:55.690454  5581 caffe.cpp:501] detection_eval = 0.0492688
-I0511 11:50:55.690459  5581 caffe.cpp:501] detection_eval = 0.0282258
-I0511 11:50:55.690462  5581 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:50:55.690466  5581 caffe.cpp:501] detection_eval = 7.73387
-I0511 11:50:55.690470  5581 caffe.cpp:501] detection_eval = 8.92742
-I0511 11:50:55.690481  5581 caffe.cpp:501] detection_eval = 0.0427398
-I0511 11:50:55.690487  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.690491  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690495  5581 caffe.cpp:501] detection_eval = 7.71573
-I0511 11:50:55.690500  5581 caffe.cpp:501] detection_eval = 8.96371
-I0511 11:50:55.690503  5581 caffe.cpp:501] detection_eval = 0.0459545
-I0511 11:50:55.690507  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.690510  5581 caffe.cpp:501] detection_eval = 0.91129
-I0511 11:50:55.690515  5581 caffe.cpp:501] detection_eval = 7.71573
-I0511 11:50:55.690518  5581 caffe.cpp:501] detection_eval = 8.99798
-I0511 11:50:55.690522  5581 caffe.cpp:501] detection_eval = 0.0397742
-I0511 11:50:55.690526  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690531  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.690536  5581 caffe.cpp:501] detection_eval = 7.71774
-I0511 11:50:55.690539  5581 caffe.cpp:501] detection_eval = 9.01815
-I0511 11:50:55.690543  5581 caffe.cpp:501] detection_eval = 0.0382935
-I0511 11:50:55.690547  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690551  5581 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:50:55.690556  5581 caffe.cpp:501] detection_eval = 7.72177
-I0511 11:50:55.690559  5581 caffe.cpp:501] detection_eval = 9.02016
-I0511 11:50:55.690563  5581 caffe.cpp:501] detection_eval = 0.0397945
-I0511 11:50:55.690567  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690572  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690575  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690579  5581 caffe.cpp:501] detection_eval = 9.09274
-I0511 11:50:55.690583  5581 caffe.cpp:501] detection_eval = 0.0408245
-I0511 11:50:55.690587  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690590  5581 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:50:55.690594  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690598  5581 caffe.cpp:501] detection_eval = 9.13508
-I0511 11:50:55.690603  5581 caffe.cpp:501] detection_eval = 0.0388966
-I0511 11:50:55.690606  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690610  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.690615  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690619  5581 caffe.cpp:501] detection_eval = 9.18347
-I0511 11:50:55.690623  5581 caffe.cpp:501] detection_eval = 0.0381993
-I0511 11:50:55.690627  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690630  5581 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:50:55.690635  5581 caffe.cpp:501] detection_eval = 7.72782
-I0511 11:50:55.690639  5581 caffe.cpp:501] detection_eval = 9.19153
-I0511 11:50:55.690642  5581 caffe.cpp:501] detection_eval = 0.0365985
-I0511 11:50:55.690647  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.690651  5581 caffe.cpp:501] detection_eval = 0.923387
-I0511 11:50:55.690655  5581 caffe.cpp:501] detection_eval = 7.72782
-I0511 11:50:55.690659  5581 caffe.cpp:501] detection_eval = 9.28226
-I0511 11:50:55.690663  5581 caffe.cpp:501] detection_eval = 0.0398854
-I0511 11:50:55.690667  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690671  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690675  5581 caffe.cpp:501] detection_eval = 7.72984
-I0511 11:50:55.690680  5581 caffe.cpp:501] detection_eval = 9.31855
-I0511 11:50:55.690683  5581 caffe.cpp:501] detection_eval = 0.0395933
-I0511 11:50:55.690687  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690691  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690696  5581 caffe.cpp:501] detection_eval = 7.73589
-I0511 11:50:55.690699  5581 caffe.cpp:501] detection_eval = 9.29637
-I0511 11:50:55.690702  5581 caffe.cpp:501] detection_eval = 0.0382833
-I0511 11:50:55.690706  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.690711  5581 caffe.cpp:501] detection_eval = 0.923387
-I0511 11:50:55.690714  5581 caffe.cpp:501] detection_eval = 7.7379
-I0511 11:50:55.690727  5581 caffe.cpp:501] detection_eval = 9.34879
-I0511 11:50:55.690732  5581 caffe.cpp:501] detection_eval = 0.0420885
-I0511 11:50:55.690737  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.690742  5581 caffe.cpp:501] detection_eval = 0.925403
-I0511 11:50:55.690745  5581 caffe.cpp:501] detection_eval = 7.73992
-I0511 11:50:55.690749  5581 caffe.cpp:501] detection_eval = 9.4254
-I0511 11:50:55.690753  5581 caffe.cpp:501] detection_eval = 0.0426532
-I0511 11:50:55.690763  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690768  5581 caffe.cpp:501] detection_eval = 0.921371
-I0511 11:50:55.690773  5581 caffe.cpp:501] detection_eval = 7.74194
-I0511 11:50:55.690776  5581 caffe.cpp:501] detection_eval = 9.45968
-I0511 11:50:55.690780  5581 caffe.cpp:501] detection_eval = 0.0398424
-I0511 11:50:55.690784  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690788  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.690793  5581 caffe.cpp:501] detection_eval = 7.74194
-I0511 11:50:55.690796  5581 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:50:55.690800  5581 caffe.cpp:501] detection_eval = 0.0413584
-I0511 11:50:55.690804  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.690809  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.690812  5581 caffe.cpp:501] detection_eval = 7.74597
-I0511 11:50:55.690816  5581 caffe.cpp:501] detection_eval = 9.5746
-I0511 11:50:55.690820  5581 caffe.cpp:501] detection_eval = 0.0429807
-I0511 11:50:55.690824  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690829  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690832  5581 caffe.cpp:501] detection_eval = 7.75605
-I0511 11:50:55.690836  5581 caffe.cpp:501] detection_eval = 9.48589
-I0511 11:50:55.690840  5581 caffe.cpp:501] detection_eval = 0.0447192
-I0511 11:50:55.690845  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690848  5581 caffe.cpp:501] detection_eval = 0.919355
-I0511 11:50:55.690853  5581 caffe.cpp:501] detection_eval = 7.72177
-I0511 11:50:55.690857  5581 caffe.cpp:501] detection_eval = 9.44355
-I0511 11:50:55.690861  5581 caffe.cpp:501] detection_eval = 0.0487921
-I0511 11:50:55.690865  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.690870  5581 caffe.cpp:501] detection_eval = 0.90121
-I0511 11:50:55.690873  5581 caffe.cpp:501] detection_eval = 7.72177
-I0511 11:50:55.690877  5581 caffe.cpp:501] detection_eval = 9.49194
-I0511 11:50:55.690881  5581 caffe.cpp:501] detection_eval = 0.0415697
-I0511 11:50:55.690886  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690888  5581 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:50:55.690892  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690896  5581 caffe.cpp:501] detection_eval = 9.52621
-I0511 11:50:55.690901  5581 caffe.cpp:501] detection_eval = 0.0432465
-I0511 11:50:55.690904  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.690908  5581 caffe.cpp:501] detection_eval = 0.913306
-I0511 11:50:55.690912  5581 caffe.cpp:501] detection_eval = 7.72379
-I0511 11:50:55.690917  5581 caffe.cpp:501] detection_eval = 9.57863
-I0511 11:50:55.690920  5581 caffe.cpp:501] detection_eval = 0.0443304
-I0511 11:50:55.690924  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.690928  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.690932  5581 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:50:55.690937  5581 caffe.cpp:501] detection_eval = 9.59677
-I0511 11:50:55.690940  5581 caffe.cpp:501] detection_eval = 0.0420757
-I0511 11:50:55.690945  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690949  5581 caffe.cpp:501] detection_eval = 0.91129
-I0511 11:50:55.690953  5581 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:50:55.690958  5581 caffe.cpp:501] detection_eval = 9.6754
-I0511 11:50:55.690961  5581 caffe.cpp:501] detection_eval = 0.0387125
-I0511 11:50:55.690965  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.690969  5581 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:50:55.690973  5581 caffe.cpp:501] detection_eval = 7.72581
-I0511 11:50:55.690984  5581 caffe.cpp:501] detection_eval = 9.77016
-I0511 11:50:55.690989  5581 caffe.cpp:501] detection_eval = 0.0390132
-I0511 11:50:55.690992  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.690996  5581 caffe.cpp:501] detection_eval = 0.917339
-I0511 11:50:55.691000  5581 caffe.cpp:501] detection_eval = 7.73387
-I0511 11:50:55.691004  5581 caffe.cpp:501] detection_eval = 9.72782
-I0511 11:50:55.691007  5581 caffe.cpp:501] detection_eval = 0.040033
-I0511 11:50:55.691012  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.691016  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.691020  5581 caffe.cpp:501] detection_eval = 7.73387
-I0511 11:50:55.691023  5581 caffe.cpp:501] detection_eval = 9.85282
-I0511 11:50:55.691027  5581 caffe.cpp:501] detection_eval = 0.0460028
-I0511 11:50:55.691031  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.691035  5581 caffe.cpp:501] detection_eval = 0.907258
-I0511 11:50:55.691040  5581 caffe.cpp:501] detection_eval = 7.70363
-I0511 11:50:55.691043  5581 caffe.cpp:501] detection_eval = 9.79234
-I0511 11:50:55.691047  5581 caffe.cpp:501] detection_eval = 0.0412338
-I0511 11:50:55.691051  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.691056  5581 caffe.cpp:501] detection_eval = 0.915323
-I0511 11:50:55.691059  5581 caffe.cpp:501] detection_eval = 7.70968
-I0511 11:50:55.691063  5581 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:50:55.691067  5581 caffe.cpp:501] detection_eval = 0.0459587
-I0511 11:50:55.691071  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.691076  5581 caffe.cpp:501] detection_eval = 0.909274
-I0511 11:50:55.691079  5581 caffe.cpp:501] detection_eval = 7.69556
-I0511 11:50:55.691083  5581 caffe.cpp:501] detection_eval = 9.79435
-I0511 11:50:55.691087  5581 caffe.cpp:501] detection_eval = 0.0512184
-I0511 11:50:55.691092  5581 caffe.cpp:501] detection_eval = 0.0221774
-I0511 11:50:55.691097  5581 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:50:55.691100  5581 caffe.cpp:501] detection_eval = 7.66129
-I0511 11:50:55.691104  5581 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:50:55.691108  5581 caffe.cpp:501] detection_eval = 0.0434903
-I0511 11:50:55.691112  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.691117  5581 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:50:55.691121  5581 caffe.cpp:501] detection_eval = 7.66532
-I0511 11:50:55.691125  5581 caffe.cpp:501] detection_eval = 9.77621
-I0511 11:50:55.691128  5581 caffe.cpp:501] detection_eval = 0.0410269
-I0511 11:50:55.691133  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.691136  5581 caffe.cpp:501] detection_eval = 0.891129
-I0511 11:50:55.691140  5581 caffe.cpp:501] detection_eval = 7.64919
-I0511 11:50:55.691144  5581 caffe.cpp:501] detection_eval = 9.75403
-I0511 11:50:55.691148  5581 caffe.cpp:501] detection_eval = 0.0438427
-I0511 11:50:55.691154  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.691164  5581 caffe.cpp:501] detection_eval = 0.895161
-I0511 11:50:55.691167  5581 caffe.cpp:501] detection_eval = 7.65524
-I0511 11:50:55.691171  5581 caffe.cpp:501] detection_eval = 9.7379
-I0511 11:50:55.691175  5581 caffe.cpp:501] detection_eval = 0.0444285
-I0511 11:50:55.691179  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.691184  5581 caffe.cpp:501] detection_eval = 0.90121
-I0511 11:50:55.691187  5581 caffe.cpp:501] detection_eval = 7.64315
-I0511 11:50:55.691191  5581 caffe.cpp:501] detection_eval = 9.67742
-I0511 11:50:55.691195  5581 caffe.cpp:501] detection_eval = 0.0408442
-I0511 11:50:55.691200  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.691205  5581 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:50:55.691208  5581 caffe.cpp:501] detection_eval = 7.64516
-I0511 11:50:55.691212  5581 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:50:55.691216  5581 caffe.cpp:501] detection_eval = 0.0416625
-I0511 11:50:55.691220  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.691224  5581 caffe.cpp:501] detection_eval = 0.897177
-I0511 11:50:55.691234  5581 caffe.cpp:501] detection_eval = 7.64516
-I0511 11:50:55.691239  5581 caffe.cpp:501] detection_eval = 9.77419
-I0511 11:50:55.691243  5581 caffe.cpp:501] detection_eval = 0.0445151
-I0511 11:50:55.691247  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.691251  5581 caffe.cpp:501] detection_eval = 0.893145
-I0511 11:50:55.691256  5581 caffe.cpp:501] detection_eval = 7.64516
-I0511 11:50:55.691259  5581 caffe.cpp:501] detection_eval = 9.83065
-I0511 11:50:55.691263  5581 caffe.cpp:501] detection_eval = 0.0417487
-I0511 11:50:55.691268  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.691272  5581 caffe.cpp:501] detection_eval = 0.903226
-I0511 11:50:55.691277  5581 caffe.cpp:501] detection_eval = 7.65121
-I0511 11:50:55.691280  5581 caffe.cpp:501] detection_eval = 9.78226
-I0511 11:50:55.691284  5581 caffe.cpp:501] detection_eval = 0.040829
-I0511 11:50:55.691288  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.691293  5581 caffe.cpp:501] detection_eval = 0.905242
-I0511 11:50:55.691296  5581 caffe.cpp:501] detection_eval = 7.65524
-I0511 11:50:55.691300  5581 caffe.cpp:501] detection_eval = 9.77419
-I0511 11:50:55.691304  5581 caffe.cpp:501] detection_eval = 0.0387782
-I0511 11:50:55.691308  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.691313  5581 caffe.cpp:501] detection_eval = 0.899194
-I0511 11:50:55.691316  5581 caffe.cpp:501] detection_eval = 7.64718
-I0511 11:50:55.691320  5581 caffe.cpp:501] detection_eval = 9.60685
-I0511 11:50:55.691324  5581 caffe.cpp:501] detection_eval = 0.0383928
-I0511 11:50:55.691329  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.691332  5581 caffe.cpp:501] detection_eval = 0.90121
-I0511 11:50:55.691336  5581 caffe.cpp:501] detection_eval = 7.64718
-I0511 11:50:55.691340  5581 caffe.cpp:501] detection_eval = 9.71169
-I0511 11:50:55.691344  5581 caffe.cpp:501] detection_eval = 0.0471161
-I0511 11:50:55.692649  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.692672  5581 caffe.cpp:501] detection_eval = 0.895161
-I0511 11:50:55.692678  5581 caffe.cpp:501] detection_eval = 7.59677
-I0511 11:50:55.692682  5581 caffe.cpp:501] detection_eval = 9.59274
-I0511 11:50:55.692687  5581 caffe.cpp:501] detection_eval = 0.0425218
-I0511 11:50:55.692690  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692694  5581 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:50:55.692698  5581 caffe.cpp:501] detection_eval = 7.60081
-I0511 11:50:55.692703  5581 caffe.cpp:501] detection_eval = 9.56452
-I0511 11:50:55.692706  5581 caffe.cpp:501] detection_eval = 0.0429596
-I0511 11:50:55.692711  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692715  5581 caffe.cpp:501] detection_eval = 0.893145
-I0511 11:50:55.692719  5581 caffe.cpp:501] detection_eval = 7.58266
-I0511 11:50:55.692723  5581 caffe.cpp:501] detection_eval = 9.58065
-I0511 11:50:55.692728  5581 caffe.cpp:501] detection_eval = 0.0402131
-I0511 11:50:55.692731  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.692735  5581 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:50:55.692739  5581 caffe.cpp:501] detection_eval = 7.58871
-I0511 11:50:55.692744  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.692747  5581 caffe.cpp:501] detection_eval = 0.0388201
-I0511 11:50:55.692751  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692755  5581 caffe.cpp:501] detection_eval = 0.889113
-I0511 11:50:55.692759  5581 caffe.cpp:501] detection_eval = 7.55645
-I0511 11:50:55.692764  5581 caffe.cpp:501] detection_eval = 9.46371
-I0511 11:50:55.692767  5581 caffe.cpp:501] detection_eval = 0.0393812
-I0511 11:50:55.692771  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692775  5581 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:50:55.692780  5581 caffe.cpp:501] detection_eval = 7.56452
-I0511 11:50:55.692783  5581 caffe.cpp:501] detection_eval = 9.4375
-I0511 11:50:55.692788  5581 caffe.cpp:501] detection_eval = 0.0398975
-I0511 11:50:55.692792  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692796  5581 caffe.cpp:501] detection_eval = 0.887097
-I0511 11:50:55.692811  5581 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:50:55.692816  5581 caffe.cpp:501] detection_eval = 9.34274
-I0511 11:50:55.692821  5581 caffe.cpp:501] detection_eval = 0.0423303
-I0511 11:50:55.692826  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.692829  5581 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:50:55.692833  5581 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:50:55.692836  5581 caffe.cpp:501] detection_eval = 9.40927
-I0511 11:50:55.692840  5581 caffe.cpp:501] detection_eval = 0.0391865
-I0511 11:50:55.692844  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.692848  5581 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:50:55.692852  5581 caffe.cpp:501] detection_eval = 7.55444
-I0511 11:50:55.692857  5581 caffe.cpp:501] detection_eval = 9.45766
-I0511 11:50:55.692860  5581 caffe.cpp:501] detection_eval = 0.0380152
-I0511 11:50:55.692864  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.692868  5581 caffe.cpp:501] detection_eval = 0.877016
-I0511 11:50:55.692873  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.692876  5581 caffe.cpp:501] detection_eval = 9.3004
-I0511 11:50:55.692880  5581 caffe.cpp:501] detection_eval = 0.0360418
-I0511 11:50:55.692884  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.692888  5581 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:50:55.692893  5581 caffe.cpp:501] detection_eval = 7.50806
-I0511 11:50:55.692896  5581 caffe.cpp:501] detection_eval = 9.39113
-I0511 11:50:55.692900  5581 caffe.cpp:501] detection_eval = 0.0389658
-I0511 11:50:55.692904  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.692909  5581 caffe.cpp:501] detection_eval = 0.875
-I0511 11:50:55.692912  5581 caffe.cpp:501] detection_eval = 7.49194
-I0511 11:50:55.692916  5581 caffe.cpp:501] detection_eval = 9.375
-I0511 11:50:55.692920  5581 caffe.cpp:501] detection_eval = 0.0349493
-I0511 11:50:55.692924  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.692929  5581 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:50:55.692932  5581 caffe.cpp:501] detection_eval = 7.49395
-I0511 11:50:55.692936  5581 caffe.cpp:501] detection_eval = 9.40726
-I0511 11:50:55.692940  5581 caffe.cpp:501] detection_eval = 0.037342
-I0511 11:50:55.692945  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.692948  5581 caffe.cpp:501] detection_eval = 0.879032
-I0511 11:50:55.692952  5581 caffe.cpp:501] detection_eval = 7.49798
-I0511 11:50:55.692956  5581 caffe.cpp:501] detection_eval = 9.4254
-I0511 11:50:55.692960  5581 caffe.cpp:501] detection_eval = 0.0354119
-I0511 11:50:55.692965  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.692970  5581 caffe.cpp:501] detection_eval = 0.881048
-I0511 11:50:55.692973  5581 caffe.cpp:501] detection_eval = 7.5
-I0511 11:50:55.692977  5581 caffe.cpp:501] detection_eval = 9.4496
-I0511 11:50:55.692981  5581 caffe.cpp:501] detection_eval = 0.0395983
-I0511 11:50:55.692984  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.692988  5581 caffe.cpp:501] detection_eval = 0.875
-I0511 11:50:55.692992  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.692996  5581 caffe.cpp:501] detection_eval = 9.46169
-I0511 11:50:55.693001  5581 caffe.cpp:501] detection_eval = 0.0373619
-I0511 11:50:55.693003  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693007  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693011  5581 caffe.cpp:501] detection_eval = 7.48185
-I0511 11:50:55.693015  5581 caffe.cpp:501] detection_eval = 9.50806
-I0511 11:50:55.693019  5581 caffe.cpp:501] detection_eval = 0.0331615
-I0511 11:50:55.693023  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.693027  5581 caffe.cpp:501] detection_eval = 0.883065
-I0511 11:50:55.693032  5581 caffe.cpp:501] detection_eval = 7.46774
-I0511 11:50:55.693035  5581 caffe.cpp:501] detection_eval = 9.49597
-I0511 11:50:55.693039  5581 caffe.cpp:501] detection_eval = 0.0373564
-I0511 11:50:55.693042  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693053  5581 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:50:55.693058  5581 caffe.cpp:501] detection_eval = 7.47177
-I0511 11:50:55.693063  5581 caffe.cpp:501] detection_eval = 9.54435
-I0511 11:50:55.693066  5581 caffe.cpp:501] detection_eval = 0.0372191
-I0511 11:50:55.693070  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693079  5581 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:50:55.693084  5581 caffe.cpp:501] detection_eval = 7.45363
-I0511 11:50:55.693087  5581 caffe.cpp:501] detection_eval = 9.55242
-I0511 11:50:55.693091  5581 caffe.cpp:501] detection_eval = 0.0365413
-I0511 11:50:55.693095  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693099  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693104  5581 caffe.cpp:501] detection_eval = 7.43952
-I0511 11:50:55.693106  5581 caffe.cpp:501] detection_eval = 9.54032
-I0511 11:50:55.693110  5581 caffe.cpp:501] detection_eval = 0.0387857
-I0511 11:50:55.693114  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693119  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693122  5581 caffe.cpp:501] detection_eval = 7.4254
-I0511 11:50:55.693125  5581 caffe.cpp:501] detection_eval = 9.5504
-I0511 11:50:55.693130  5581 caffe.cpp:501] detection_eval = 0.0408134
-I0511 11:50:55.693133  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693137  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693141  5581 caffe.cpp:501] detection_eval = 7.42742
-I0511 11:50:55.693145  5581 caffe.cpp:501] detection_eval = 9.55645
-I0511 11:50:55.693150  5581 caffe.cpp:501] detection_eval = 0.0359556
-I0511 11:50:55.693153  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693157  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693161  5581 caffe.cpp:501] detection_eval = 7.41129
-I0511 11:50:55.693166  5581 caffe.cpp:501] detection_eval = 9.60081
-I0511 11:50:55.693168  5581 caffe.cpp:501] detection_eval = 0.0401762
-I0511 11:50:55.693172  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693176  5581 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:50:55.693181  5581 caffe.cpp:501] detection_eval = 7.39919
-I0511 11:50:55.693184  5581 caffe.cpp:501] detection_eval = 9.52218
-I0511 11:50:55.693188  5581 caffe.cpp:501] detection_eval = 0.036138
-I0511 11:50:55.693192  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693195  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693199  5581 caffe.cpp:501] detection_eval = 7.40121
-I0511 11:50:55.693203  5581 caffe.cpp:501] detection_eval = 9.62298
-I0511 11:50:55.693207  5581 caffe.cpp:501] detection_eval = 0.035102
-I0511 11:50:55.693212  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693215  5581 caffe.cpp:501] detection_eval = 0.866935
-I0511 11:50:55.693219  5581 caffe.cpp:501] detection_eval = 7.40726
-I0511 11:50:55.693223  5581 caffe.cpp:501] detection_eval = 9.5625
-I0511 11:50:55.693226  5581 caffe.cpp:501] detection_eval = 0.0320705
-I0511 11:50:55.693230  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.693234  5581 caffe.cpp:501] detection_eval = 0.868952
-I0511 11:50:55.693238  5581 caffe.cpp:501] detection_eval = 7.33871
-I0511 11:50:55.693243  5581 caffe.cpp:501] detection_eval = 9.41532
-I0511 11:50:55.693246  5581 caffe.cpp:501] detection_eval = 0.0364101
-I0511 11:50:55.693250  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693254  5581 caffe.cpp:501] detection_eval = 0.860887
-I0511 11:50:55.693259  5581 caffe.cpp:501] detection_eval = 7.33871
-I0511 11:50:55.693261  5581 caffe.cpp:501] detection_eval = 9.4496
-I0511 11:50:55.693265  5581 caffe.cpp:501] detection_eval = 0.0353211
-I0511 11:50:55.693270  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693274  5581 caffe.cpp:501] detection_eval = 0.858871
-I0511 11:50:55.693277  5581 caffe.cpp:501] detection_eval = 7.34274
-I0511 11:50:55.693281  5581 caffe.cpp:501] detection_eval = 9.42339
-I0511 11:50:55.693285  5581 caffe.cpp:501] detection_eval = 0.0360995
-I0511 11:50:55.693296  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693301  5581 caffe.cpp:501] detection_eval = 0.856855
-I0511 11:50:55.693305  5581 caffe.cpp:501] detection_eval = 7.33065
-I0511 11:50:55.693310  5581 caffe.cpp:501] detection_eval = 9.35685
-I0511 11:50:55.693313  5581 caffe.cpp:501] detection_eval = 0.0390568
-I0511 11:50:55.693317  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693321  5581 caffe.cpp:501] detection_eval = 0.858871
-I0511 11:50:55.693325  5581 caffe.cpp:501] detection_eval = 7.3125
-I0511 11:50:55.693328  5581 caffe.cpp:501] detection_eval = 9.38911
-I0511 11:50:55.693332  5581 caffe.cpp:501] detection_eval = 0.0385728
-I0511 11:50:55.693336  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693341  5581 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:50:55.693344  5581 caffe.cpp:501] detection_eval = 7.27621
-I0511 11:50:55.693348  5581 caffe.cpp:501] detection_eval = 9.38105
-I0511 11:50:55.693352  5581 caffe.cpp:501] detection_eval = 0.0362222
-I0511 11:50:55.693356  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693359  5581 caffe.cpp:501] detection_eval = 0.84879
-I0511 11:50:55.693363  5581 caffe.cpp:501] detection_eval = 7.27823
-I0511 11:50:55.693367  5581 caffe.cpp:501] detection_eval = 9.45766
-I0511 11:50:55.693372  5581 caffe.cpp:501] detection_eval = 0.0385586
-I0511 11:50:55.693375  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693379  5581 caffe.cpp:501] detection_eval = 0.84879
-I0511 11:50:55.693383  5581 caffe.cpp:501] detection_eval = 7.28024
-I0511 11:50:55.693387  5581 caffe.cpp:501] detection_eval = 9.4879
-I0511 11:50:55.693392  5581 caffe.cpp:501] detection_eval = 0.0389247
-I0511 11:50:55.693395  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.693399  5581 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:50:55.693403  5581 caffe.cpp:501] detection_eval = 7.28427
-I0511 11:50:55.693408  5581 caffe.cpp:501] detection_eval = 9.52016
-I0511 11:50:55.693411  5581 caffe.cpp:501] detection_eval = 0.0399768
-I0511 11:50:55.693415  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693419  5581 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:50:55.693423  5581 caffe.cpp:501] detection_eval = 7.29032
-I0511 11:50:55.693428  5581 caffe.cpp:501] detection_eval = 9.50403
-I0511 11:50:55.693430  5581 caffe.cpp:501] detection_eval = 0.0372568
-I0511 11:50:55.693434  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693437  5581 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:50:55.693441  5581 caffe.cpp:501] detection_eval = 7.29032
-I0511 11:50:55.693445  5581 caffe.cpp:501] detection_eval = 9.58266
-I0511 11:50:55.693449  5581 caffe.cpp:501] detection_eval = 0.0362175
-I0511 11:50:55.693454  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693457  5581 caffe.cpp:501] detection_eval = 0.84879
-I0511 11:50:55.693461  5581 caffe.cpp:501] detection_eval = 7.29032
-I0511 11:50:55.693464  5581 caffe.cpp:501] detection_eval = 9.65726
-I0511 11:50:55.693469  5581 caffe.cpp:501] detection_eval = 0.0396827
-I0511 11:50:55.693472  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693482  5581 caffe.cpp:501] detection_eval = 0.844758
-I0511 11:50:55.693486  5581 caffe.cpp:501] detection_eval = 7.29234
-I0511 11:50:55.693490  5581 caffe.cpp:501] detection_eval = 9.70161
-I0511 11:50:55.693495  5581 caffe.cpp:501] detection_eval = 0.0361591
-I0511 11:50:55.693498  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693502  5581 caffe.cpp:501] detection_eval = 0.850806
-I0511 11:50:55.693506  5581 caffe.cpp:501] detection_eval = 7.29234
-I0511 11:50:55.693511  5581 caffe.cpp:501] detection_eval = 9.75403
-I0511 11:50:55.693514  5581 caffe.cpp:501] detection_eval = 0.0331379
-I0511 11:50:55.693518  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.693522  5581 caffe.cpp:501] detection_eval = 0.854839
-I0511 11:50:55.693526  5581 caffe.cpp:501] detection_eval = 7.29435
-I0511 11:50:55.693531  5581 caffe.cpp:501] detection_eval = 9.77621
-I0511 11:50:55.693534  5581 caffe.cpp:501] detection_eval = 0.033433
-I0511 11:50:55.693547  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693552  5581 caffe.cpp:501] detection_eval = 0.850806
-I0511 11:50:55.693555  5581 caffe.cpp:501] detection_eval = 7.27621
-I0511 11:50:55.693559  5581 caffe.cpp:501] detection_eval = 9.79234
-I0511 11:50:55.693563  5581 caffe.cpp:501] detection_eval = 0.037148
-I0511 11:50:55.693567  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693572  5581 caffe.cpp:501] detection_eval = 0.84879
-I0511 11:50:55.693575  5581 caffe.cpp:501] detection_eval = 7.2621
-I0511 11:50:55.693579  5581 caffe.cpp:501] detection_eval = 9.74798
-I0511 11:50:55.693583  5581 caffe.cpp:501] detection_eval = 0.0373937
-I0511 11:50:55.693588  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693591  5581 caffe.cpp:501] detection_eval = 0.840726
-I0511 11:50:55.693595  5581 caffe.cpp:501] detection_eval = 7.2621
-I0511 11:50:55.693599  5581 caffe.cpp:501] detection_eval = 9.82056
-I0511 11:50:55.693603  5581 caffe.cpp:501] detection_eval = 0.0338502
-I0511 11:50:55.693608  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693612  5581 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:50:55.693616  5581 caffe.cpp:501] detection_eval = 7.27218
-I0511 11:50:55.693619  5581 caffe.cpp:501] detection_eval = 9.70766
-I0511 11:50:55.693624  5581 caffe.cpp:501] detection_eval = 0.0336465
-I0511 11:50:55.693627  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.693631  5581 caffe.cpp:501] detection_eval = 0.846774
-I0511 11:50:55.693635  5581 caffe.cpp:501] detection_eval = 7.27419
-I0511 11:50:55.693639  5581 caffe.cpp:501] detection_eval = 9.73387
-I0511 11:50:55.693644  5581 caffe.cpp:501] detection_eval = 0.032233
-I0511 11:50:55.693647  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.693652  5581 caffe.cpp:501] detection_eval = 0.850806
-I0511 11:50:55.693656  5581 caffe.cpp:501] detection_eval = 7.25605
-I0511 11:50:55.693660  5581 caffe.cpp:501] detection_eval = 9.79839
-I0511 11:50:55.693665  5581 caffe.cpp:501] detection_eval = 0.0418286
-I0511 11:50:55.693668  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.693672  5581 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:50:55.693676  5581 caffe.cpp:501] detection_eval = 7.25806
-I0511 11:50:55.693681  5581 caffe.cpp:501] detection_eval = 9.84476
-I0511 11:50:55.693684  5581 caffe.cpp:501] detection_eval = 0.0355745
-I0511 11:50:55.693688  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693692  5581 caffe.cpp:501] detection_eval = 0.842742
-I0511 11:50:55.693696  5581 caffe.cpp:501] detection_eval = 7.26008
-I0511 11:50:55.693701  5581 caffe.cpp:501] detection_eval = 9.86895
-I0511 11:50:55.693704  5581 caffe.cpp:501] detection_eval = 0.0401162
-I0511 11:50:55.693708  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.693712  5581 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:50:55.693716  5581 caffe.cpp:501] detection_eval = 7.20565
-I0511 11:50:55.693719  5581 caffe.cpp:501] detection_eval = 9.81452
-I0511 11:50:55.693723  5581 caffe.cpp:501] detection_eval = 0.0381054
-I0511 11:50:55.693727  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693732  5581 caffe.cpp:501] detection_eval = 0.836694
-I0511 11:50:55.693735  5581 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:50:55.693739  5581 caffe.cpp:501] detection_eval = 9.78024
-I0511 11:50:55.693742  5581 caffe.cpp:501] detection_eval = 0.0359296
-I0511 11:50:55.693747  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693750  5581 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:50:55.693754  5581 caffe.cpp:501] detection_eval = 7.20968
-I0511 11:50:55.693758  5581 caffe.cpp:501] detection_eval = 9.85081
-I0511 11:50:55.693761  5581 caffe.cpp:501] detection_eval = 0.0400798
-I0511 11:50:55.693765  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693769  5581 caffe.cpp:501] detection_eval = 0.832661
-I0511 11:50:55.693773  5581 caffe.cpp:501] detection_eval = 7.21169
-I0511 11:50:55.693778  5581 caffe.cpp:501] detection_eval = 9.84073
-I0511 11:50:55.693786  5581 caffe.cpp:501] detection_eval = 0.0361626
-I0511 11:50:55.693791  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693795  5581 caffe.cpp:501] detection_eval = 0.83871
-I0511 11:50:55.693799  5581 caffe.cpp:501] detection_eval = 7.21573
-I0511 11:50:55.693804  5581 caffe.cpp:501] detection_eval = 9.8629
-I0511 11:50:55.693807  5581 caffe.cpp:501] detection_eval = 0.0403234
-I0511 11:50:55.693810  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693814  5581 caffe.cpp:501] detection_eval = 0.834677
-I0511 11:50:55.693819  5581 caffe.cpp:501] detection_eval = 7.1996
-I0511 11:50:55.693822  5581 caffe.cpp:501] detection_eval = 9.84476
-I0511 11:50:55.693826  5581 caffe.cpp:501] detection_eval = 0.0365513
-I0511 11:50:55.693830  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.693835  5581 caffe.cpp:501] detection_eval = 0.826613
-I0511 11:50:55.693838  5581 caffe.cpp:501] detection_eval = 7.18145
-I0511 11:50:55.693842  5581 caffe.cpp:501] detection_eval = 9.88306
-I0511 11:50:55.693845  5581 caffe.cpp:501] detection_eval = 0.0335514
-I0511 11:50:55.693850  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.693853  5581 caffe.cpp:501] detection_eval = 0.830645
-I0511 11:50:55.693856  5581 caffe.cpp:501] detection_eval = 7.18347
-I0511 11:50:55.693861  5581 caffe.cpp:501] detection_eval = 9.91129
-I0511 11:50:55.693864  5581 caffe.cpp:501] detection_eval = 0.036504
-I0511 11:50:55.693873  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693877  5581 caffe.cpp:501] detection_eval = 0.828629
-I0511 11:50:55.693881  5581 caffe.cpp:501] detection_eval = 7.18347
-I0511 11:50:55.693884  5581 caffe.cpp:501] detection_eval = 9.98589
-I0511 11:50:55.693888  5581 caffe.cpp:501] detection_eval = 0.040345
-I0511 11:50:55.693892  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.693897  5581 caffe.cpp:501] detection_eval = 0.828629
-I0511 11:50:55.693902  5581 caffe.cpp:501] detection_eval = 7.14919
-I0511 11:50:55.693904  5581 caffe.cpp:501] detection_eval = 9.94153
-I0511 11:50:55.693908  5581 caffe.cpp:501] detection_eval = 0.0330725
-I0511 11:50:55.693912  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693917  5581 caffe.cpp:501] detection_eval = 0.830645
-I0511 11:50:55.693922  5581 caffe.cpp:501] detection_eval = 7.13508
-I0511 11:50:55.693925  5581 caffe.cpp:501] detection_eval = 9.88306
-I0511 11:50:55.693929  5581 caffe.cpp:501] detection_eval = 0.0348621
-I0511 11:50:55.693933  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.693938  5581 caffe.cpp:501] detection_eval = 0.822581
-I0511 11:50:55.693941  5581 caffe.cpp:501] detection_eval = 7.11694
-I0511 11:50:55.693945  5581 caffe.cpp:501] detection_eval = 9.88911
-I0511 11:50:55.693949  5581 caffe.cpp:501] detection_eval = 0.0353318
-I0511 11:50:55.693953  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.693956  5581 caffe.cpp:501] detection_eval = 0.820565
-I0511 11:50:55.693960  5581 caffe.cpp:501] detection_eval = 7.10081
-I0511 11:50:55.693964  5581 caffe.cpp:501] detection_eval = 9.90927
-I0511 11:50:55.693967  5581 caffe.cpp:501] detection_eval = 0.0390245
-I0511 11:50:55.693971  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.693975  5581 caffe.cpp:501] detection_eval = 0.814516
-I0511 11:50:55.693979  5581 caffe.cpp:501] detection_eval = 7.08468
-I0511 11:50:55.693982  5581 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:50:55.693986  5581 caffe.cpp:501] detection_eval = 0.0376094
-I0511 11:50:55.693990  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.693994  5581 caffe.cpp:501] detection_eval = 0.818548
-I0511 11:50:55.693997  5581 caffe.cpp:501] detection_eval = 7.08871
-I0511 11:50:55.694001  5581 caffe.cpp:501] detection_eval = 9.87097
-I0511 11:50:55.694005  5581 caffe.cpp:501] detection_eval = 0.03494
-I0511 11:50:55.694010  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.694013  5581 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:50:55.694017  5581 caffe.cpp:501] detection_eval = 7.07258
-I0511 11:50:55.694021  5581 caffe.cpp:501] detection_eval = 9.85282
-I0511 11:50:55.694031  5581 caffe.cpp:501] detection_eval = 0.032036
-I0511 11:50:55.694036  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694041  5581 caffe.cpp:501] detection_eval = 0.820565
-I0511 11:50:55.694044  5581 caffe.cpp:501] detection_eval = 7.07258
-I0511 11:50:55.694048  5581 caffe.cpp:501] detection_eval = 9.91532
-I0511 11:50:55.694053  5581 caffe.cpp:501] detection_eval = 0.0344601
-I0511 11:50:55.694057  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.694061  5581 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:50:55.694066  5581 caffe.cpp:501] detection_eval = 7.07258
-I0511 11:50:55.694070  5581 caffe.cpp:501] detection_eval = 9.99194
-I0511 11:50:55.694074  5581 caffe.cpp:501] detection_eval = 0.0352947
-I0511 11:50:55.694078  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.694082  5581 caffe.cpp:501] detection_eval = 0.810484
-I0511 11:50:55.694087  5581 caffe.cpp:501] detection_eval = 7.04234
-I0511 11:50:55.694090  5581 caffe.cpp:501] detection_eval = 9.87702
-I0511 11:50:55.694094  5581 caffe.cpp:501] detection_eval = 0.0319296
-I0511 11:50:55.694098  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694103  5581 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:50:55.694106  5581 caffe.cpp:501] detection_eval = 7.04435
-I0511 11:50:55.694110  5581 caffe.cpp:501] detection_eval = 9.92944
-I0511 11:50:55.694115  5581 caffe.cpp:501] detection_eval = 0.0294298
-I0511 11:50:55.694118  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.694123  5581 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:50:55.694128  5581 caffe.cpp:501] detection_eval = 7.03024
-I0511 11:50:55.694131  5581 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:50:55.694747  5581 caffe.cpp:501] detection_eval = 0.032493
-I0511 11:50:55.694761  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.694766  5581 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:50:55.694772  5581 caffe.cpp:501] detection_eval = 7.03226
-I0511 11:50:55.694775  5581 caffe.cpp:501] detection_eval = 9.90121
-I0511 11:50:55.694779  5581 caffe.cpp:501] detection_eval = 0.0373495
-I0511 11:50:55.694783  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.694787  5581 caffe.cpp:501] detection_eval = 0.806452
-I0511 11:50:55.694792  5581 caffe.cpp:501] detection_eval = 7.03427
-I0511 11:50:55.694797  5581 caffe.cpp:501] detection_eval = 9.91532
-I0511 11:50:55.694800  5581 caffe.cpp:501] detection_eval = 0.0287897
-I0511 11:50:55.694804  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.694808  5581 caffe.cpp:501] detection_eval = 0.816532
-I0511 11:50:55.694813  5581 caffe.cpp:501] detection_eval = 7.01613
-I0511 11:50:55.694816  5581 caffe.cpp:501] detection_eval = 9.95968
-I0511 11:50:55.694820  5581 caffe.cpp:501] detection_eval = 0.0300179
-I0511 11:50:55.694825  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.694829  5581 caffe.cpp:501] detection_eval = 0.814516
-I0511 11:50:55.694833  5581 caffe.cpp:501] detection_eval = 7
-I0511 11:50:55.694836  5581 caffe.cpp:501] detection_eval = 9.99194
-I0511 11:50:55.694840  5581 caffe.cpp:501] detection_eval = 0.0333731
-I0511 11:50:55.694844  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694847  5581 caffe.cpp:501] detection_eval = 0.808468
-I0511 11:50:55.694850  5581 caffe.cpp:501] detection_eval = 6.98589
-I0511 11:50:55.694854  5581 caffe.cpp:501] detection_eval = 9.97379
-I0511 11:50:55.694857  5581 caffe.cpp:501] detection_eval = 0.0307876
-I0511 11:50:55.694861  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.694865  5581 caffe.cpp:501] detection_eval = 0.8125
-I0511 11:50:55.694869  5581 caffe.cpp:501] detection_eval = 6.96976
-I0511 11:50:55.694874  5581 caffe.cpp:501] detection_eval = 9.95161
-I0511 11:50:55.694877  5581 caffe.cpp:501] detection_eval = 0.0308016
-I0511 11:50:55.694881  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.694885  5581 caffe.cpp:501] detection_eval = 0.810484
-I0511 11:50:55.694888  5581 caffe.cpp:501] detection_eval = 6.9375
-I0511 11:50:55.694900  5581 caffe.cpp:501] detection_eval = 9.86694
-I0511 11:50:55.694905  5581 caffe.cpp:501] detection_eval = 0.0327063
-I0511 11:50:55.694908  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694912  5581 caffe.cpp:501] detection_eval = 0.802419
-I0511 11:50:55.694916  5581 caffe.cpp:501] detection_eval = 6.93952
-I0511 11:50:55.694919  5581 caffe.cpp:501] detection_eval = 9.92339
-I0511 11:50:55.694923  5581 caffe.cpp:501] detection_eval = 0.0311476
-I0511 11:50:55.694926  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.694931  5581 caffe.cpp:501] detection_eval = 0.806452
-I0511 11:50:55.694933  5581 caffe.cpp:501] detection_eval = 6.92944
-I0511 11:50:55.694937  5581 caffe.cpp:501] detection_eval = 9.83468
-I0511 11:50:55.694941  5581 caffe.cpp:501] detection_eval = 0.0329777
-I0511 11:50:55.694945  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.694949  5581 caffe.cpp:501] detection_eval = 0.802419
-I0511 11:50:55.694953  5581 caffe.cpp:501] detection_eval = 6.93145
-I0511 11:50:55.694957  5581 caffe.cpp:501] detection_eval = 9.86895
-I0511 11:50:55.694960  5581 caffe.cpp:501] detection_eval = 0.0373738
-I0511 11:50:55.694964  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.694968  5581 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:50:55.694972  5581 caffe.cpp:501] detection_eval = 6.93548
-I0511 11:50:55.694977  5581 caffe.cpp:501] detection_eval = 9.87097
-I0511 11:50:55.694980  5581 caffe.cpp:501] detection_eval = 0.0336773
-I0511 11:50:55.694984  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.694988  5581 caffe.cpp:501] detection_eval = 0.796371
-I0511 11:50:55.694993  5581 caffe.cpp:501] detection_eval = 6.88508
-I0511 11:50:55.694996  5581 caffe.cpp:501] detection_eval = 9.73992
-I0511 11:50:55.695000  5581 caffe.cpp:501] detection_eval = 0.0320276
-I0511 11:50:55.695004  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.695008  5581 caffe.cpp:501] detection_eval = 0.792339
-I0511 11:50:55.695013  5581 caffe.cpp:501] detection_eval = 6.87097
-I0511 11:50:55.695016  5581 caffe.cpp:501] detection_eval = 9.70766
-I0511 11:50:55.695020  5581 caffe.cpp:501] detection_eval = 0.0358409
-I0511 11:50:55.695024  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695029  5581 caffe.cpp:501] detection_eval = 0.788306
-I0511 11:50:55.695032  5581 caffe.cpp:501] detection_eval = 6.85484
-I0511 11:50:55.695036  5581 caffe.cpp:501] detection_eval = 9.71169
-I0511 11:50:55.695040  5581 caffe.cpp:501] detection_eval = 0.0296722
-I0511 11:50:55.695044  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.695049  5581 caffe.cpp:501] detection_eval = 0.794355
-I0511 11:50:55.695052  5581 caffe.cpp:501] detection_eval = 6.85685
-I0511 11:50:55.695056  5581 caffe.cpp:501] detection_eval = 9.73387
-I0511 11:50:55.695060  5581 caffe.cpp:501] detection_eval = 0.0357246
-I0511 11:50:55.695065  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.695070  5581 caffe.cpp:501] detection_eval = 0.78629
-I0511 11:50:55.695073  5581 caffe.cpp:501] detection_eval = 6.85685
-I0511 11:50:55.695077  5581 caffe.cpp:501] detection_eval = 9.8125
-I0511 11:50:55.695081  5581 caffe.cpp:501] detection_eval = 0.0306283
-I0511 11:50:55.695086  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695089  5581 caffe.cpp:501] detection_eval = 0.790323
-I0511 11:50:55.695093  5581 caffe.cpp:501] detection_eval = 6.85685
-I0511 11:50:55.695097  5581 caffe.cpp:501] detection_eval = 9.88306
-I0511 11:50:55.695101  5581 caffe.cpp:501] detection_eval = 0.0358557
-I0511 11:50:55.695106  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.695109  5581 caffe.cpp:501] detection_eval = 0.782258
-I0511 11:50:55.695113  5581 caffe.cpp:501] detection_eval = 6.82258
-I0511 11:50:55.695117  5581 caffe.cpp:501] detection_eval = 9.80847
-I0511 11:50:55.695122  5581 caffe.cpp:501] detection_eval = 0.0287403
-I0511 11:50:55.695125  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695129  5581 caffe.cpp:501] detection_eval = 0.790323
-I0511 11:50:55.695139  5581 caffe.cpp:501] detection_eval = 6.82661
-I0511 11:50:55.695144  5581 caffe.cpp:501] detection_eval = 9.84073
-I0511 11:50:55.695149  5581 caffe.cpp:501] detection_eval = 0.0328806
-I0511 11:50:55.695153  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695158  5581 caffe.cpp:501] detection_eval = 0.78629
-I0511 11:50:55.695166  5581 caffe.cpp:501] detection_eval = 6.81653
-I0511 11:50:55.695171  5581 caffe.cpp:501] detection_eval = 9.77621
-I0511 11:50:55.695176  5581 caffe.cpp:501] detection_eval = 0.0351629
-I0511 11:50:55.695180  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695184  5581 caffe.cpp:501] detection_eval = 0.780242
-I0511 11:50:55.695188  5581 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:50:55.695192  5581 caffe.cpp:501] detection_eval = 9.81653
-I0511 11:50:55.695196  5581 caffe.cpp:501] detection_eval = 0.0323754
-I0511 11:50:55.695200  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695204  5581 caffe.cpp:501] detection_eval = 0.782258
-I0511 11:50:55.695209  5581 caffe.cpp:501] detection_eval = 6.79839
-I0511 11:50:55.695214  5581 caffe.cpp:501] detection_eval = 9.88508
-I0511 11:50:55.695217  5581 caffe.cpp:501] detection_eval = 0.0343071
-I0511 11:50:55.695221  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.695225  5581 caffe.cpp:501] detection_eval = 0.77621
-I0511 11:50:55.695230  5581 caffe.cpp:501] detection_eval = 6.75
-I0511 11:50:55.695235  5581 caffe.cpp:501] detection_eval = 9.76411
-I0511 11:50:55.695238  5581 caffe.cpp:501] detection_eval = 0.0384378
-I0511 11:50:55.695242  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.695245  5581 caffe.cpp:501] detection_eval = 0.768145
-I0511 11:50:55.695250  5581 caffe.cpp:501] detection_eval = 6.7379
-I0511 11:50:55.695255  5581 caffe.cpp:501] detection_eval = 9.67339
-I0511 11:50:55.695258  5581 caffe.cpp:501] detection_eval = 0.0361436
-I0511 11:50:55.695262  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695266  5581 caffe.cpp:501] detection_eval = 0.770161
-I0511 11:50:55.695271  5581 caffe.cpp:501] detection_eval = 6.73992
-I0511 11:50:55.695276  5581 caffe.cpp:501] detection_eval = 9.71573
-I0511 11:50:55.695279  5581 caffe.cpp:501] detection_eval = 0.0330777
-I0511 11:50:55.695283  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695287  5581 caffe.cpp:501] detection_eval = 0.768145
-I0511 11:50:55.695291  5581 caffe.cpp:501] detection_eval = 6.70363
-I0511 11:50:55.695296  5581 caffe.cpp:501] detection_eval = 9.71371
-I0511 11:50:55.695298  5581 caffe.cpp:501] detection_eval = 0.0299119
-I0511 11:50:55.695302  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695307  5581 caffe.cpp:501] detection_eval = 0.770161
-I0511 11:50:55.695310  5581 caffe.cpp:501] detection_eval = 6.70565
-I0511 11:50:55.695314  5581 caffe.cpp:501] detection_eval = 9.73992
-I0511 11:50:55.695317  5581 caffe.cpp:501] detection_eval = 0.0322463
-I0511 11:50:55.695322  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.695325  5581 caffe.cpp:501] detection_eval = 0.762097
-I0511 11:50:55.695329  5581 caffe.cpp:501] detection_eval = 6.67339
-I0511 11:50:55.695333  5581 caffe.cpp:501] detection_eval = 9.64516
-I0511 11:50:55.695336  5581 caffe.cpp:501] detection_eval = 0.0345244
-I0511 11:50:55.695340  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.695344  5581 caffe.cpp:501] detection_eval = 0.764113
-I0511 11:50:55.695348  5581 caffe.cpp:501] detection_eval = 6.67742
-I0511 11:50:55.695353  5581 caffe.cpp:501] detection_eval = 9.64919
-I0511 11:50:55.695355  5581 caffe.cpp:501] detection_eval = 0.0360615
-I0511 11:50:55.695359  5581 caffe.cpp:501] detection_eval = 0.0201613
-I0511 11:50:55.695363  5581 caffe.cpp:501] detection_eval = 0.752016
-I0511 11:50:55.695367  5581 caffe.cpp:501] detection_eval = 6.66129
-I0511 11:50:55.695371  5581 caffe.cpp:501] detection_eval = 9.60282
-I0511 11:50:55.695374  5581 caffe.cpp:501] detection_eval = 0.0283827
-I0511 11:50:55.695379  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695382  5581 caffe.cpp:501] detection_eval = 0.764113
-I0511 11:50:55.695392  5581 caffe.cpp:501] detection_eval = 6.64718
-I0511 11:50:55.695396  5581 caffe.cpp:501] detection_eval = 9.58266
-I0511 11:50:55.695400  5581 caffe.cpp:501] detection_eval = 0.0298543
-I0511 11:50:55.695405  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695407  5581 caffe.cpp:501] detection_eval = 0.764113
-I0511 11:50:55.695411  5581 caffe.cpp:501] detection_eval = 6.62903
-I0511 11:50:55.695415  5581 caffe.cpp:501] detection_eval = 9.65323
-I0511 11:50:55.695420  5581 caffe.cpp:501] detection_eval = 0.0314333
-I0511 11:50:55.695423  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.695426  5581 caffe.cpp:501] detection_eval = 0.758065
-I0511 11:50:55.695430  5581 caffe.cpp:501] detection_eval = 6.61492
-I0511 11:50:55.695435  5581 caffe.cpp:501] detection_eval = 9.63306
-I0511 11:50:55.695438  5581 caffe.cpp:501] detection_eval = 0.0416447
-I0511 11:50:55.695442  5581 caffe.cpp:501] detection_eval = 0.016129
-I0511 11:50:55.695446  5581 caffe.cpp:501] detection_eval = 0.745968
-I0511 11:50:55.695451  5581 caffe.cpp:501] detection_eval = 6.61492
-I0511 11:50:55.695453  5581 caffe.cpp:501] detection_eval = 9.6754
-I0511 11:50:55.695457  5581 caffe.cpp:501] detection_eval = 0.0339225
-I0511 11:50:55.695461  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695466  5581 caffe.cpp:501] detection_eval = 0.760081
-I0511 11:50:55.695469  5581 caffe.cpp:501] detection_eval = 6.59677
-I0511 11:50:55.695472  5581 caffe.cpp:501] detection_eval = 9.6875
-I0511 11:50:55.695477  5581 caffe.cpp:501] detection_eval = 0.0324571
-I0511 11:50:55.695480  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.695484  5581 caffe.cpp:501] detection_eval = 0.75
-I0511 11:50:55.695488  5581 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:50:55.695492  5581 caffe.cpp:501] detection_eval = 9.65121
-I0511 11:50:55.695497  5581 caffe.cpp:501] detection_eval = 0.0349557
-I0511 11:50:55.695500  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.695503  5581 caffe.cpp:501] detection_eval = 0.745968
-I0511 11:50:55.695508  5581 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:50:55.695511  5581 caffe.cpp:501] detection_eval = 9.69556
-I0511 11:50:55.695515  5581 caffe.cpp:501] detection_eval = 0.0303059
-I0511 11:50:55.695519  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.695523  5581 caffe.cpp:501] detection_eval = 0.747984
-I0511 11:50:55.695526  5581 caffe.cpp:501] detection_eval = 6.53226
-I0511 11:50:55.695530  5581 caffe.cpp:501] detection_eval = 9.60484
-I0511 11:50:55.695534  5581 caffe.cpp:501] detection_eval = 0.0280135
-I0511 11:50:55.695538  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695542  5581 caffe.cpp:501] detection_eval = 0.75
-I0511 11:50:55.695545  5581 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:50:55.695549  5581 caffe.cpp:501] detection_eval = 9.56048
-I0511 11:50:55.695554  5581 caffe.cpp:501] detection_eval = 0.02689
-I0511 11:50:55.695556  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.695560  5581 caffe.cpp:501] detection_eval = 0.752016
-I0511 11:50:55.695564  5581 caffe.cpp:501] detection_eval = 6.50202
-I0511 11:50:55.695567  5581 caffe.cpp:501] detection_eval = 9.54234
-I0511 11:50:55.695571  5581 caffe.cpp:501] detection_eval = 0.0274713
-I0511 11:50:55.695580  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695583  5581 caffe.cpp:501] detection_eval = 0.747984
-I0511 11:50:55.695587  5581 caffe.cpp:501] detection_eval = 6.48387
-I0511 11:50:55.695591  5581 caffe.cpp:501] detection_eval = 9.56048
-I0511 11:50:55.695595  5581 caffe.cpp:501] detection_eval = 0.0282462
-I0511 11:50:55.695598  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695602  5581 caffe.cpp:501] detection_eval = 0.739919
-I0511 11:50:55.695606  5581 caffe.cpp:501] detection_eval = 6.44758
-I0511 11:50:55.695611  5581 caffe.cpp:501] detection_eval = 9.5504
-I0511 11:50:55.695614  5581 caffe.cpp:501] detection_eval = 0.0280578
-I0511 11:50:55.695617  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.695626  5581 caffe.cpp:501] detection_eval = 0.739919
-I0511 11:50:55.695631  5581 caffe.cpp:501] detection_eval = 6.4496
-I0511 11:50:55.695634  5581 caffe.cpp:501] detection_eval = 9.59677
-I0511 11:50:55.695637  5581 caffe.cpp:501] detection_eval = 0.0256961
-I0511 11:50:55.695641  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.695646  5581 caffe.cpp:501] detection_eval = 0.743952
-I0511 11:50:55.695649  5581 caffe.cpp:501] detection_eval = 6.43548
-I0511 11:50:55.695653  5581 caffe.cpp:501] detection_eval = 9.53427
-I0511 11:50:55.695657  5581 caffe.cpp:501] detection_eval = 0.0273331
-I0511 11:50:55.695660  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.695664  5581 caffe.cpp:501] detection_eval = 0.735887
-I0511 11:50:55.695668  5581 caffe.cpp:501] detection_eval = 6.42339
-I0511 11:50:55.695672  5581 caffe.cpp:501] detection_eval = 9.42742
-I0511 11:50:55.695675  5581 caffe.cpp:501] detection_eval = 0.0274096
-I0511 11:50:55.695679  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.695683  5581 caffe.cpp:501] detection_eval = 0.735887
-I0511 11:50:55.695686  5581 caffe.cpp:501] detection_eval = 6.40726
-I0511 11:50:55.695690  5581 caffe.cpp:501] detection_eval = 9.45161
-I0511 11:50:55.695694  5581 caffe.cpp:501] detection_eval = 0.03626
-I0511 11:50:55.695698  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.695703  5581 caffe.cpp:501] detection_eval = 0.721774
-I0511 11:50:55.695706  5581 caffe.cpp:501] detection_eval = 6.40927
-I0511 11:50:55.695710  5581 caffe.cpp:501] detection_eval = 9.47984
-I0511 11:50:55.695714  5581 caffe.cpp:501] detection_eval = 0.0327975
-I0511 11:50:55.703299  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703320  5581 caffe.cpp:501] detection_eval = 0.727823
-I0511 11:50:55.703325  5581 caffe.cpp:501] detection_eval = 6.37298
-I0511 11:50:55.703328  5581 caffe.cpp:501] detection_eval = 9.47782
-I0511 11:50:55.703332  5581 caffe.cpp:501] detection_eval = 0.0288063
-I0511 11:50:55.703336  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703341  5581 caffe.cpp:501] detection_eval = 0.729839
-I0511 11:50:55.703343  5581 caffe.cpp:501] detection_eval = 6.33871
-I0511 11:50:55.703347  5581 caffe.cpp:501] detection_eval = 9.46371
-I0511 11:50:55.703351  5581 caffe.cpp:501] detection_eval = 0.0283002
-I0511 11:50:55.703356  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703358  5581 caffe.cpp:501] detection_eval = 0.72379
-I0511 11:50:55.703362  5581 caffe.cpp:501] detection_eval = 6.30645
-I0511 11:50:55.703366  5581 caffe.cpp:501] detection_eval = 9.40524
-I0511 11:50:55.703371  5581 caffe.cpp:501] detection_eval = 0.0271487
-I0511 11:50:55.703374  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.703377  5581 caffe.cpp:501] detection_eval = 0.725806
-I0511 11:50:55.703382  5581 caffe.cpp:501] detection_eval = 6.28831
-I0511 11:50:55.703385  5581 caffe.cpp:501] detection_eval = 9.45363
-I0511 11:50:55.703389  5581 caffe.cpp:501] detection_eval = 0.0316955
-I0511 11:50:55.703392  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703397  5581 caffe.cpp:501] detection_eval = 0.715726
-I0511 11:50:55.703400  5581 caffe.cpp:501] detection_eval = 6.29032
-I0511 11:50:55.703404  5581 caffe.cpp:501] detection_eval = 9.50202
-I0511 11:50:55.703408  5581 caffe.cpp:501] detection_eval = 0.0298387
-I0511 11:50:55.703411  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703415  5581 caffe.cpp:501] detection_eval = 0.719758
-I0511 11:50:55.703418  5581 caffe.cpp:501] detection_eval = 6.27218
-I0511 11:50:55.703423  5581 caffe.cpp:501] detection_eval = 9.5625
-I0511 11:50:55.703426  5581 caffe.cpp:501] detection_eval = 0.0321499
-I0511 11:50:55.703430  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703433  5581 caffe.cpp:501] detection_eval = 0.711694
-I0511 11:50:55.703438  5581 caffe.cpp:501] detection_eval = 6.25605
-I0511 11:50:55.703441  5581 caffe.cpp:501] detection_eval = 9.59677
-I0511 11:50:55.703444  5581 caffe.cpp:501] detection_eval = 0.0277891
-I0511 11:50:55.703447  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.703461  5581 caffe.cpp:501] detection_eval = 0.717742
-I0511 11:50:55.703465  5581 caffe.cpp:501] detection_eval = 6.21976
-I0511 11:50:55.703469  5581 caffe.cpp:501] detection_eval = 9.60887
-I0511 11:50:55.703472  5581 caffe.cpp:501] detection_eval = 0.0291475
-I0511 11:50:55.703475  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703480  5581 caffe.cpp:501] detection_eval = 0.709677
-I0511 11:50:55.703482  5581 caffe.cpp:501] detection_eval = 6.20363
-I0511 11:50:55.703486  5581 caffe.cpp:501] detection_eval = 9.71371
-I0511 11:50:55.703490  5581 caffe.cpp:501] detection_eval = 0.0273094
-I0511 11:50:55.703492  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703496  5581 caffe.cpp:501] detection_eval = 0.703629
-I0511 11:50:55.703500  5581 caffe.cpp:501] detection_eval = 6.44153
-I0511 11:50:55.703503  5581 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:50:55.703506  5581 caffe.cpp:501] detection_eval = 0.0651437
-I0511 11:50:55.703510  5581 caffe.cpp:501] detection_eval = 0.0504032
-I0511 11:50:55.703513  5581 caffe.cpp:501] detection_eval = 0.663306
-I0511 11:50:55.703516  5581 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:50:55.703521  5581 caffe.cpp:501] detection_eval = 6.24798
-I0511 11:50:55.703523  5581 caffe.cpp:501] detection_eval = 0.0436009
-I0511 11:50:55.703526  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.703531  5581 caffe.cpp:501] detection_eval = 0.693548
-I0511 11:50:55.703533  5581 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:50:55.703537  5581 caffe.cpp:501] detection_eval = 6.35282
-I0511 11:50:55.703541  5581 caffe.cpp:501] detection_eval = 0.0431912
-I0511 11:50:55.703544  5581 caffe.cpp:501] detection_eval = 0.0181452
-I0511 11:50:55.703547  5581 caffe.cpp:501] detection_eval = 0.693548
-I0511 11:50:55.703552  5581 caffe.cpp:501] detection_eval = 6.40524
-I0511 11:50:55.703555  5581 caffe.cpp:501] detection_eval = 6.44556
-I0511 11:50:55.703558  5581 caffe.cpp:501] detection_eval = 0.0368396
-I0511 11:50:55.703562  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703567  5581 caffe.cpp:501] detection_eval = 0.699597
-I0511 11:50:55.703569  5581 caffe.cpp:501] detection_eval = 6.3871
-I0511 11:50:55.703573  5581 caffe.cpp:501] detection_eval = 6.45161
-I0511 11:50:55.703577  5581 caffe.cpp:501] detection_eval = 0.0359233
-I0511 11:50:55.703580  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703584  5581 caffe.cpp:501] detection_eval = 0.695565
-I0511 11:50:55.703588  5581 caffe.cpp:501] detection_eval = 6.35081
-I0511 11:50:55.703593  5581 caffe.cpp:501] detection_eval = 6.4375
-I0511 11:50:55.703595  5581 caffe.cpp:501] detection_eval = 0.0357209
-I0511 11:50:55.703599  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703603  5581 caffe.cpp:501] detection_eval = 0.695565
-I0511 11:50:55.703606  5581 caffe.cpp:501] detection_eval = 6.33266
-I0511 11:50:55.703610  5581 caffe.cpp:501] detection_eval = 6.44758
-I0511 11:50:55.703614  5581 caffe.cpp:501] detection_eval = 0.0291685
-I0511 11:50:55.703619  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703621  5581 caffe.cpp:501] detection_eval = 0.693548
-I0511 11:50:55.703625  5581 caffe.cpp:501] detection_eval = 6.31452
-I0511 11:50:55.703629  5581 caffe.cpp:501] detection_eval = 6.47581
-I0511 11:50:55.703632  5581 caffe.cpp:501] detection_eval = 0.0314611
-I0511 11:50:55.703636  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703640  5581 caffe.cpp:501] detection_eval = 0.691532
-I0511 11:50:55.703644  5581 caffe.cpp:501] detection_eval = 6.31452
-I0511 11:50:55.703647  5581 caffe.cpp:501] detection_eval = 6.52419
-I0511 11:50:55.703651  5581 caffe.cpp:501] detection_eval = 0.0320833
-I0511 11:50:55.703655  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703658  5581 caffe.cpp:501] detection_eval = 0.6875
-I0511 11:50:55.703662  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.703666  5581 caffe.cpp:501] detection_eval = 6.56452
-I0511 11:50:55.703670  5581 caffe.cpp:501] detection_eval = 0.0324025
-I0511 11:50:55.703677  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.703682  5581 caffe.cpp:501] detection_eval = 0.689516
-I0511 11:50:55.703685  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.703689  5581 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:50:55.703693  5581 caffe.cpp:501] detection_eval = 0.0294135
-I0511 11:50:55.703697  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703701  5581 caffe.cpp:501] detection_eval = 0.695565
-I0511 11:50:55.703704  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.703708  5581 caffe.cpp:501] detection_eval = 6.6754
-I0511 11:50:55.703712  5581 caffe.cpp:501] detection_eval = 0.0316228
-I0511 11:50:55.703716  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.703719  5581 caffe.cpp:501] detection_eval = 0.689516
-I0511 11:50:55.703723  5581 caffe.cpp:501] detection_eval = 6.29637
-I0511 11:50:55.703727  5581 caffe.cpp:501] detection_eval = 6.72984
-I0511 11:50:55.703730  5581 caffe.cpp:501] detection_eval = 0.0291904
-I0511 11:50:55.703734  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703738  5581 caffe.cpp:501] detection_eval = 0.695565
-I0511 11:50:55.703742  5581 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:50:55.703745  5581 caffe.cpp:501] detection_eval = 6.70565
-I0511 11:50:55.703749  5581 caffe.cpp:501] detection_eval = 0.0282254
-I0511 11:50:55.703753  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703758  5581 caffe.cpp:501] detection_eval = 0.689516
-I0511 11:50:55.703760  5581 caffe.cpp:501] detection_eval = 6.26008
-I0511 11:50:55.703764  5581 caffe.cpp:501] detection_eval = 6.75403
-I0511 11:50:55.703768  5581 caffe.cpp:501] detection_eval = 0.0292542
-I0511 11:50:55.703771  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703775  5581 caffe.cpp:501] detection_eval = 0.6875
-I0511 11:50:55.703779  5581 caffe.cpp:501] detection_eval = 6.20565
-I0511 11:50:55.703783  5581 caffe.cpp:501] detection_eval = 6.69556
-I0511 11:50:55.703788  5581 caffe.cpp:501] detection_eval = 0.0290907
-I0511 11:50:55.703790  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703794  5581 caffe.cpp:501] detection_eval = 0.685484
-I0511 11:50:55.703799  5581 caffe.cpp:501] detection_eval = 6.1875
-I0511 11:50:55.703802  5581 caffe.cpp:501] detection_eval = 6.69758
-I0511 11:50:55.703805  5581 caffe.cpp:501] detection_eval = 0.0313242
-I0511 11:50:55.703809  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.703814  5581 caffe.cpp:501] detection_eval = 0.675403
-I0511 11:50:55.703816  5581 caffe.cpp:501] detection_eval = 6.16935
-I0511 11:50:55.703820  5581 caffe.cpp:501] detection_eval = 6.71169
-I0511 11:50:55.703824  5581 caffe.cpp:501] detection_eval = 0.031514
-I0511 11:50:55.703829  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703831  5581 caffe.cpp:501] detection_eval = 0.673387
-I0511 11:50:55.703835  5581 caffe.cpp:501] detection_eval = 6.09677
-I0511 11:50:55.703840  5581 caffe.cpp:501] detection_eval = 6.62702
-I0511 11:50:55.703842  5581 caffe.cpp:501] detection_eval = 0.0292035
-I0511 11:50:55.703846  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703850  5581 caffe.cpp:501] detection_eval = 0.671371
-I0511 11:50:55.703855  5581 caffe.cpp:501] detection_eval = 6.07863
-I0511 11:50:55.703857  5581 caffe.cpp:501] detection_eval = 6.64113
-I0511 11:50:55.703861  5581 caffe.cpp:501] detection_eval = 0.0294854
-I0511 11:50:55.703866  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.703868  5581 caffe.cpp:501] detection_eval = 0.669355
-I0511 11:50:55.703872  5581 caffe.cpp:501] detection_eval = 6.06048
-I0511 11:50:55.703876  5581 caffe.cpp:501] detection_eval = 6.62702
-I0511 11:50:55.703879  5581 caffe.cpp:501] detection_eval = 0.0281852
-I0511 11:50:55.703883  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703887  5581 caffe.cpp:501] detection_eval = 0.66129
-I0511 11:50:55.703891  5581 caffe.cpp:501] detection_eval = 6.06048
-I0511 11:50:55.703894  5581 caffe.cpp:501] detection_eval = 6.68548
-I0511 11:50:55.703902  5581 caffe.cpp:501] detection_eval = 0.0296146
-I0511 11:50:55.703907  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703910  5581 caffe.cpp:501] detection_eval = 0.669355
-I0511 11:50:55.703914  5581 caffe.cpp:501] detection_eval = 6.04234
-I0511 11:50:55.703917  5581 caffe.cpp:501] detection_eval = 6.70363
-I0511 11:50:55.703922  5581 caffe.cpp:501] detection_eval = 0.0323881
-I0511 11:50:55.703925  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.703928  5581 caffe.cpp:501] detection_eval = 0.655242
-I0511 11:50:55.703933  5581 caffe.cpp:501] detection_eval = 5.9879
-I0511 11:50:55.703936  5581 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:50:55.703940  5581 caffe.cpp:501] detection_eval = 0.026478
-I0511 11:50:55.703943  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.703948  5581 caffe.cpp:501] detection_eval = 0.66129
-I0511 11:50:55.703951  5581 caffe.cpp:501] detection_eval = 5.95161
-I0511 11:50:55.703954  5581 caffe.cpp:501] detection_eval = 6.60484
-I0511 11:50:55.703958  5581 caffe.cpp:501] detection_eval = 0.0298143
-I0511 11:50:55.703963  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.703966  5581 caffe.cpp:501] detection_eval = 0.653226
-I0511 11:50:55.703969  5581 caffe.cpp:501] detection_eval = 5.87903
-I0511 11:50:55.703974  5581 caffe.cpp:501] detection_eval = 6.50806
-I0511 11:50:55.703977  5581 caffe.cpp:501] detection_eval = 0.0292611
-I0511 11:50:55.703980  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.703984  5581 caffe.cpp:501] detection_eval = 0.641129
-I0511 11:50:55.703987  5581 caffe.cpp:501] detection_eval = 5.84274
-I0511 11:50:55.703990  5581 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:50:55.703994  5581 caffe.cpp:501] detection_eval = 0.0265516
-I0511 11:50:55.703999  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.704002  5581 caffe.cpp:501] detection_eval = 0.641129
-I0511 11:50:55.704007  5581 caffe.cpp:501] detection_eval = 5.80645
-I0511 11:50:55.704011  5581 caffe.cpp:501] detection_eval = 6.49597
-I0511 11:50:55.704015  5581 caffe.cpp:501] detection_eval = 0.0337191
-I0511 11:50:55.704020  5581 caffe.cpp:501] detection_eval = 0.0120968
-I0511 11:50:55.704023  5581 caffe.cpp:501] detection_eval = 0.631048
-I0511 11:50:55.704026  5581 caffe.cpp:501] detection_eval = 5.77016
-I0511 11:50:55.704030  5581 caffe.cpp:501] detection_eval = 6.46573
-I0511 11:50:55.704035  5581 caffe.cpp:501] detection_eval = 0.0312134
-I0511 11:50:55.704037  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704041  5581 caffe.cpp:501] detection_eval = 0.637097
-I0511 11:50:55.704046  5581 caffe.cpp:501] detection_eval = 5.77016
-I0511 11:50:55.704048  5581 caffe.cpp:501] detection_eval = 6.51008
-I0511 11:50:55.704052  5581 caffe.cpp:501] detection_eval = 0.0271473
-I0511 11:50:55.704056  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.704061  5581 caffe.cpp:501] detection_eval = 0.629032
-I0511 11:50:55.704064  5581 caffe.cpp:501] detection_eval = 5.73387
-I0511 11:50:55.704067  5581 caffe.cpp:501] detection_eval = 6.48185
-I0511 11:50:55.704071  5581 caffe.cpp:501] detection_eval = 0.0296419
-I0511 11:50:55.704074  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.704078  5581 caffe.cpp:501] detection_eval = 0.627016
-I0511 11:50:55.704082  5581 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:50:55.704087  5581 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:50:55.704089  5581 caffe.cpp:501] detection_eval = 0.0287038
-I0511 11:50:55.704093  5581 caffe.cpp:501] detection_eval = 0.0141129
-I0511 11:50:55.704097  5581 caffe.cpp:501] detection_eval = 0.618952
-I0511 11:50:55.704102  5581 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:50:55.704104  5581 caffe.cpp:501] detection_eval = 6.5121
-I0511 11:50:55.704108  5581 caffe.cpp:501] detection_eval = 0.0241407
-I0511 11:50:55.704113  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.704115  5581 caffe.cpp:501] detection_eval = 0.625
-I0511 11:50:55.704119  5581 caffe.cpp:501] detection_eval = 5.71573
-I0511 11:50:55.704123  5581 caffe.cpp:501] detection_eval = 6.55242
-I0511 11:50:55.704133  5581 caffe.cpp:501] detection_eval = 0.0278125
-I0511 11:50:55.704136  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704140  5581 caffe.cpp:501] detection_eval = 0.629032
-I0511 11:50:55.704144  5581 caffe.cpp:501] detection_eval = 5.69758
-I0511 11:50:55.704147  5581 caffe.cpp:501] detection_eval = 6.56048
-I0511 11:50:55.704151  5581 caffe.cpp:501] detection_eval = 0.0239643
-I0511 11:50:55.704155  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.704159  5581 caffe.cpp:501] detection_eval = 0.631048
-I0511 11:50:55.704162  5581 caffe.cpp:501] detection_eval = 5.64315
-I0511 11:50:55.704166  5581 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:50:55.704170  5581 caffe.cpp:501] detection_eval = 0.0249106
-I0511 11:50:55.704174  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704177  5581 caffe.cpp:501] detection_eval = 0.620968
-I0511 11:50:55.704180  5581 caffe.cpp:501] detection_eval = 5.58871
-I0511 11:50:55.704185  5581 caffe.cpp:501] detection_eval = 6.43548
-I0511 11:50:55.704187  5581 caffe.cpp:501] detection_eval = 0.0239349
-I0511 11:50:55.704191  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704195  5581 caffe.cpp:501] detection_eval = 0.616935
-I0511 11:50:55.704198  5581 caffe.cpp:501] detection_eval = 5.58871
-I0511 11:50:55.704201  5581 caffe.cpp:501] detection_eval = 6.47782
-I0511 11:50:55.704205  5581 caffe.cpp:501] detection_eval = 0.0220331
-I0511 11:50:55.704208  5581 caffe.cpp:501] detection_eval = 0
-I0511 11:50:55.704212  5581 caffe.cpp:501] detection_eval = 0.620968
-I0511 11:50:55.704216  5581 caffe.cpp:501] detection_eval = 5.58871
-I0511 11:50:55.704219  5581 caffe.cpp:501] detection_eval = 6.50605
-I0511 11:50:55.704222  5581 caffe.cpp:501] detection_eval = 0.0235767
-I0511 11:50:55.704226  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.704229  5581 caffe.cpp:501] detection_eval = 0.614919
-I0511 11:50:55.704232  5581 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:50:55.704236  5581 caffe.cpp:501] detection_eval = 6.44758
-I0511 11:50:55.704239  5581 caffe.cpp:501] detection_eval = 0.0242647
-I0511 11:50:55.704246  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.704249  5581 caffe.cpp:501] detection_eval = 0.606855
-I0511 11:50:55.704252  5581 caffe.cpp:501] detection_eval = 5.55242
-I0511 11:50:55.704257  5581 caffe.cpp:501] detection_eval = 6.50202
-I0511 11:50:55.704259  5581 caffe.cpp:501] detection_eval = 0.0235616
-I0511 11:50:55.704263  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.704267  5581 caffe.cpp:501] detection_eval = 0.610887
-I0511 11:50:55.704270  5581 caffe.cpp:501] detection_eval = 5.53427
-I0511 11:50:55.704274  5581 caffe.cpp:501] detection_eval = 6.5121
-I0511 11:50:55.704277  5581 caffe.cpp:501] detection_eval = 0.0258441
-I0511 11:50:55.704282  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.704285  5581 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:50:55.704289  5581 caffe.cpp:501] detection_eval = 5.51613
-I0511 11:50:55.704293  5581 caffe.cpp:501] detection_eval = 6.48387
-I0511 11:50:55.704296  5581 caffe.cpp:501] detection_eval = 0.0236597
-I0511 11:50:55.704300  5581 caffe.cpp:501] detection_eval = 0.0100806
-I0511 11:50:55.704304  5581 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:50:55.704308  5581 caffe.cpp:501] detection_eval = 5.49798
-I0511 11:50:55.704311  5581 caffe.cpp:501] detection_eval = 6.51815
-I0511 11:50:55.704315  5581 caffe.cpp:501] detection_eval = 0.0250569
-I0511 11:50:55.704319  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.704324  5581 caffe.cpp:501] detection_eval = 0.604839
-I0511 11:50:55.704327  5581 caffe.cpp:501] detection_eval = 5.46169
-I0511 11:50:55.704330  5581 caffe.cpp:501] detection_eval = 6.48992
-I0511 11:50:55.704334  5581 caffe.cpp:501] detection_eval = 0.0238263
-I0511 11:50:55.704339  5581 caffe.cpp:501] detection_eval = 0.00403226
-I0511 11:50:55.704342  5581 caffe.cpp:501] detection_eval = 0.602823
-I0511 11:50:55.704346  5581 caffe.cpp:501] detection_eval = 5.44355
-I0511 11:50:55.704355  5581 caffe.cpp:501] detection_eval = 6.49194
-I0511 11:50:55.704358  5581 caffe.cpp:501] detection_eval = 0.0250854
-I0511 11:50:55.704362  5581 caffe.cpp:501] detection_eval = 0.00806452
-I0511 11:50:55.704366  5581 caffe.cpp:501] detection_eval = 0.594758
-I0511 11:50:55.704370  5581 caffe.cpp:501] detection_eval = 5.44355
-I0511 11:50:55.704375  5581 caffe.cpp:501] detection_eval = 6.52419
-I0511 11:50:55.704378  5581 caffe.cpp:501] detection_eval = 0.0222069
-I0511 11:50:55.704381  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.704385  5581 caffe.cpp:501] detection_eval = 0.600806
-I0511 11:50:55.704390  5581 caffe.cpp:501] detection_eval = 5.40726
-I0511 11:50:55.704393  5581 caffe.cpp:501] detection_eval = 6.49798
-I0511 11:50:55.704396  5581 caffe.cpp:501] detection_eval = 0.0222845
-I0511 11:50:55.704401  5581 caffe.cpp:501] detection_eval = 0.00201613
-I0511 11:50:55.704404  5581 caffe.cpp:501] detection_eval = 0.59879
-I0511 11:50:55.704408  5581 caffe.cpp:501] detection_eval = 5.29839
-I0511 11:50:55.704411  5581 caffe.cpp:501] detection_eval = 6.34879
-I0511 11:50:55.704416  5581 caffe.cpp:501] detection_eval = 0.0229918
-I0511 11:50:55.704419  5581 caffe.cpp:501] detection_eval = 0.00604839
-I0511 11:50:55.704423  5581 caffe.cpp:501] detection_eval = 0.578629
-I0511 11:50:55.705934  5581 caffe.cpp:546] class AP 1: 0.649931
-I0511 11:50:55.706599  5581 caffe.cpp:546] class AP 2: 0.730188
-I0511 11:50:55.720845  5581 caffe.cpp:546] class AP 3: 0.553319
-I0511 11:50:55.725518  5581 caffe.cpp:546] class AP 4: 0.506074
-I0511 11:50:55.752445  5581 caffe.cpp:546] class AP 5: 0.339543
-I0511 11:50:55.752918  5581 caffe.cpp:546] class AP 6: 0.730379
-I0511 11:50:55.764034  5581 caffe.cpp:546] class AP 7: 0.701396
-I0511 11:50:55.764760  5581 caffe.cpp:546] class AP 8: 0.815084
-I0511 11:50:55.789405  5581 caffe.cpp:546] class AP 9: 0.431345
-I0511 11:50:55.790325  5581 caffe.cpp:546] class AP 10: 0.624216
-I0511 11:50:55.791142  5581 caffe.cpp:546] class AP 11: 0.593459
-I0511 11:50:55.792280  5581 caffe.cpp:546] class AP 12: 0.721829
-I0511 11:50:55.792790  5581 caffe.cpp:546] class AP 13: 0.790938
-I0511 11:50:55.793241  5581 caffe.cpp:546] class AP 14: 0.743532
-I0511 11:50:55.880975  5581 caffe.cpp:546] class AP 15: 0.724583
-I0511 11:50:55.887090  5581 caffe.cpp:546] class AP 16: 0.363203
-I0511 11:50:55.889358  5581 caffe.cpp:546] class AP 17: 0.598904
-I0511 11:50:55.889951  5581 caffe.cpp:546] class AP 18: 0.609708
-I0511 11:50:55.890596  5581 caffe.cpp:546] class AP 19: 0.754557
-I0511 11:50:55.891871  5581 caffe.cpp:546] class AP 20: 0.610099
-I0511 11:50:55.891880  5581 caffe.cpp:552] Test net output mAP #0: detection_eval = 0.629614