documentation update - added accuracies for regnetx based segmentation models.

[jacinto-ai/pytorch-jacinto-ai-devkit.git] / run_segmentation.sh

diff --git a/run_segmentation.sh b/run_segmentation.sh
index 11616e43e03bad07b5a5198ee3f06423028668a3..e2b6970e3586c9e8af84318f590e1731a148d15c 100755 (executable)
--- a/run_segmentation.sh
+++ b/run_segmentation.sh
@@ -31,6 +31,18 @@
 #--data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \
 #--pretrained https://download.pytorch.org/models/mobilenet_v2-b0353104.pth
 
+#### Cityscapes Semantic Segmentation - Training with MobileNetV2+FPNLite
+#python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name fpnlite_pixel2pixel_aspp_mobilenetv2_tv \
+#--data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \
+#--pretrained https://download.pytorch.org/models/mobilenet_v2-b0353104.pth
+
+#### Cityscapes Semantic Segmentation - Training with MobileNetV2+UNetLite
+#python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name unetlite_pixel2pixel_aspp_mobilenetv2_tv \
+#--data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \
+#--pretrained https://download.pytorch.org/models/mobilenet_v2-b0353104.pth
+
+#Higher Resolution
+#------------------------
 #### Cityscapes Semantic Segmentation - Training with MobileNetV2+DeeplabV3Lite, Higher Resolution
 #python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name deeplabv3lite_mobilenetv2_tv \
 #--data_path ./data/datasets/cityscapes/data --img_resize 768 1536 --rand_crop 512 1024 --output_size 1024 2048 --gpus 0 1 \
@@ -43,6 +55,27 @@
 
 
 
+#RegNetX based Models
+#------------------------
+## Cityscapes Semantic Segmentation - Training with RegNetX800MF+DeeplabV3Lite
+#Note: to use BGR input, set: --input_channel_reverse True, for RGB input ommit this argument or set it to False.
+#python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name deeplabv3lite_regnetx800mf \
+#--data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \
+#--pretrained https://dl.fbaipublicfiles.com/pycls/dds_baselines/160906036/RegNetX-800MF_dds_8gpu.pyth
+
+### Cityscapes Semantic Segmentation - Training with RegNetX800MF+FPNLite
+#Note: to use BGR input, set: --input_channel_reverse True, for RGB input ommit this argument or set it to False.
+#python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name fpnlite_pixel2pixel_aspp_regnetx800mf \
+#--data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \
+#--pretrained https://dl.fbaipublicfiles.com/pycls/dds_baselines/160906036/RegNetX-800MF_dds_8gpu.pyth
+
+### Cityscapes Semantic Segmentation - Training with RegNetX800MF+UNetLite
+#Note: to use BGR input, set: --input_channel_reverse True, for RGB input ommit this argument or set it to False.
+#python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name unetlite_pixel2pixel_aspp_regnetx800mf \
+#--data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \
+#--pretrained https://dl.fbaipublicfiles.com/pycls/dds_baselines/160906036/RegNetX-800MF_dds_8gpu.pyth
+
+
 #ResNet50 based Models
 #------------------------
 #### Cityscapes Semantic Segmentation - Training with ResNet50+DeeplabV3Lite
@@ -61,15 +94,6 @@
 #--pretrained "./data/modelzoo/pretrained/pytorch/imagenet_classification/jacinto_ai/resnet50-0.5_2018-07-23_12-10-23.pth"
 
 
-#RegNetX based Models
-#------------------------
-### Cityscapes Semantic Segmentation - Training with RegNetX800MF+DeeplabV3Lite
-#Note: to use BGR input, set: --input_channel_reverse True, for RGB input ommit this argument or set it to False.
-#python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name fpnlite_pixel2pixel_aspp_regnetx800mf \
-#--data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \
-#--pretrained https://dl.fbaipublicfiles.com/pycls/dds_baselines/160906036/RegNetX-800MF_dds_8gpu.pyth
-
-
 
 
 #-- VOC Segmentation