Merge tag 'v01.03.02' into develop
authorYuan Zhao <yuanzhao@ti.com>
Mon, 16 Sep 2019 19:53:15 +0000 (14:53 -0500)
committerYuan Zhao <yuanzhao@ti.com>
Mon, 16 Sep 2019 19:53:15 +0000 (14:53 -0500)
TIDL-API 1.3.2 for Processor SDK 6.1

29 files changed:
examples/classification/main.cpp
examples/classification/readme.md
examples/test/testvecs/config/infer/tidl_config_dense_1x1.txt
examples/test/testvecs/config/infer/tidl_config_inceptionNetv1.txt
examples/test/testvecs/config/infer/tidl_config_inceptionNetv1_lg2.txt
examples/test/testvecs/config/infer/tidl_config_j11_bn.txt
examples/test/testvecs/config/infer/tidl_config_j11_cifar.txt
examples/test/testvecs/config/infer/tidl_config_j11_controlLayers.txt
examples/test/testvecs/config/infer/tidl_config_j11_prelu.txt
examples/test/testvecs/config/infer/tidl_config_j11_v2.txt
examples/test/testvecs/config/infer/tidl_config_j11_v2_dense.txt
examples/test/testvecs/config/infer/tidl_config_j11_v2_dense_lg2.txt
examples/test/testvecs/config/infer/tidl_config_j11_v2_lg2.txt
examples/test/testvecs/config/infer/tidl_config_jseg21.txt
examples/test/testvecs/config/infer/tidl_config_jseg21_dense.txt
examples/test/testvecs/config/infer/tidl_config_jseg21_tiscapes.txt
examples/test/testvecs/config/infer/tidl_config_mnist_lenet.txt
examples/test/testvecs/config/infer/tidl_config_mobileNet1.txt
examples/test/testvecs/config/infer/tidl_config_mobileNet1_lg2.txt
examples/test/testvecs/config/infer/tidl_config_mobileNet2.txt [new file with mode: 0755]
examples/test/testvecs/config/infer/tidl_config_mobileNet2_lg2.txt [new file with mode: 0755]
examples/test/testvecs/config/infer/tidl_config_smallRoi.txt
examples/test/testvecs/config/infer/tidl_config_squeeze1_1.txt
examples/test/testvecs/config/tidl_models/tidl_net_inceptionv1_224.bin [moved from examples/test/testvecs/config/tidl_models/tidl_inception_v1_net.bin with 99% similarity]
examples/test/testvecs/config/tidl_models/tidl_net_mobilenet_1_224.bin
examples/test/testvecs/config/tidl_models/tidl_net_mobilenet_2_224.bin [new file with mode: 0755]
examples/test/testvecs/config/tidl_models/tidl_param_inceptionv1_224.bin [moved from examples/test/testvecs/config/tidl_models/tidl_inception_v1_param.bin with 100% similarity]
examples/test/testvecs/config/tidl_models/tidl_param_mobilenet_2_224.bin [new file with mode: 0755]
tidl_api/src/ocl_device.cpp

index 25361f8a210a1de37c37a3030d6d3bfc55adf988..68c5f8009034ea1e9204f58e45a5b38db91ac7f2 100644 (file)
@@ -111,7 +111,8 @@ Rect rectCrop[NUM_ROI];
 // Report average FPS across a sliding window of 16 frames
 AvgFPSWindow fps_window(16);
 
-static int tf_postprocess(uchar *in, int size, int roi_idx, int frame_idx, int f_id);
+static int tf_postprocess(uchar *in, int out_size, int size, int roi_idx,
+                          int frame_idx, int f_id);
 static int ShowRegion(int roi_history[]);
 // from most recent to oldest at top indices
 static int selclass_history[MAX_NUM_ROI][3];
@@ -485,6 +486,7 @@ bool ReadFrame(ExecutionObjectPipeline* eop, const Configuration& c,
                sprintf(tmp_string, "ROI[%02d]", frame_idx % NUM_ROI);
                cv::imshow(tmp_string, r_image);
             }
+            image.copyTo(show_image);
 #endif
             imgutil::PreprocessImage(r_image, eop->GetInputBufferPtr(), c);
             eop->SetFrameIndex(frame_idx);
@@ -495,10 +497,6 @@ bool ReadFrame(ExecutionObjectPipeline* eop, const Configuration& c,
             writer << to_stream;
 #endif
 
-#ifdef LIVE_DISPLAY
-                //waitKey(2);
-            image.copyTo(show_image);
-#endif
             return true;
         }
     } else {
@@ -519,6 +517,7 @@ void DisplayFrame(const ExecutionObjectPipeline* eop, VideoWriter& writer,
     int f_id = eop->GetFrameIndex();
     int curr_roi = f_id % NUM_ROI;
     int is_object = tf_postprocess((uchar*) eop->GetOutputBufferPtr(),
+                                   eop->GetOutputBufferSizeInBytes(),
                                  IMAGE_CLASSES_NUM, curr_roi, frame_idx, f_id);
     selclass_history[curr_roi][2] = selclass_history[curr_roi][1];
     selclass_history[curr_roi][1] = selclass_history[curr_roi][0];
@@ -691,12 +690,17 @@ bool tf_expected_id(int id)
    return false;
 }
 
-int tf_postprocess(uchar *in, int size, int roi_idx, int frame_idx, int f_id)
+int tf_postprocess(uchar *in, int out_size, int size, int roi_idx,
+                   int frame_idx, int f_id)
 {
   //prob_i = exp(TIDL_Lib_output_i) / sum(exp(TIDL_Lib_output))
   // sort and get k largest values and corresponding indices
   const int k = TOP_CANDIDATES;
   int rpt_id = -1;
+  // Tensorflow trained network outputs 1001 probabilities,
+  // with 0-index being background, thus we need to subtract 1 when
+  // reporting classified object from 1000 categories
+  int background_offset = out_size == 1001 ? 1 : 0;
 
   typedef std::pair<uchar, int> val_index;
   auto cmp = [](val_index &left, val_index &right) { return left.first > right.first; };
@@ -725,13 +729,13 @@ int tf_postprocess(uchar *in, int size, int roi_idx, int frame_idx, int f_id)
 
   for (int i = 0; i < k; i++)
   {
-      int id = sorted[i].second;
+      int id = sorted[i].second - background_offset;
 
       if (tf_expected_id(id))
       {
         std::cout << "Frame:" << frame_idx << "," << f_id << " ROI[" << roi_idx << "]: rank="
                   << k-i << ", outval=" << (float)sorted[i].first / 255 << ", "
-                  << labels_classes[sorted[i].second] << std::endl;
+                  << labels_classes[id] << std::endl;
         rpt_id = id;
       }
   }
index 565807a0fcf6e7e1dbd7233a75cbadefe0d39e5c..047a92267fc6a74786959f4e22122462859a9460 100644 (file)
@@ -3,8 +3,8 @@
 # 1. Live camera input, using 2xEVE and 2xDSP cores, based on model with single layers group 
 ./tidl_classification -g 1 -d 2 -e 2 -l ./imagenet.txt -s ./classlist.txt -i 1 -c ./stream_config_j11_v2.txt
 # 2. Use video clip as input stream, using 2xEVE and 2xDSP cores, based on model with single layers group 
-./tidl_classification -g 1 -d 2 -e 2 -l ./imagenet.txt -s ./classlist.txt -i ./clips/test50.mp4 -c ./stream_config_j11_v2.txt
+./tidl_classification -g 1 -d 2 -e 2 -l ./imagenet.txt -s ./classlist.txt -i ./clips/test10.mp4 -c ./stream_config_j11_v2.txt
 # 3. Use video clip as input stream, using 2xEVE and 1xDSP cores, based on model with two layers group (1st layers group running on EVE, 2nd layers group on DSP)
-./tidl_classification -g 2 -d 1 -e 2 -l ./imagenet.txt -s ./classlist.txt -i ./clips/test50.mp4 -c ./stream_config_j11_v2.txt
+./tidl_classification -g 2 -d 1 -e 2 -l ./imagenet.txt -s ./classlist.txt -i ./clips/test10.mp4 -c ./stream_config_j11_v2.txt
 # 4. Use video clip as input stream, using no EVEs and 2xDSP cores, based on model with single layers group
-./tidl_classification -g 1 -d 2 -e 0 -l ./imagenet.txt -s ./classlist.txt -i ./clips/test50.mp4 -c ./stream_config_j11_v2.txt
+./tidl_classification -g 1 -d 2 -e 0 -l ./imagenet.txt -s ./classlist.txt -i ./clips/test10.mp4 -c ./stream_config_j11_v2.txt
index 475b89a90e86543f8740708b25288d230b5296ca..b41ceaa9f86b49212595e3f91c035e04e95c3d18 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/000100_1024x512_bgr.y
+inData   = "../test/testvecs/input/000100_1024x512_bgr.y"
 outData   = "./stats_tool_out.bin"
 netBinFile     = ../test/testvecs/config/tidl_models/tidl_net_dense_1x1.bin
 paramsBinFile  = ../test/testvecs/config/tidl_models/tidl_param_dense_1x1.bin
index 934cff6b7125157f123ca78da1dd36149c4aa23b..2f9e152b632187908436ccb64e25c3ce65616120 100755 (executable)
@@ -1,9 +1,9 @@
 numFrames   = 1
 preProcType = 2
-inData   = ../test/testvecs/input/preproc_2_224x224.y
+inData   = "../test/testvecs/input/preproc_2_224x224.y"
 outData   = "stats_tool_out.bin"
-netBinFile      = ../test/testvecs/config/tidl_models/tidl_inception_v1_net.bin
-paramsBinFile   = ../test/testvecs/config/tidl_models/tidl_inception_v1_param.bin
+netBinFile      = ../test/testvecs/config/tidl_models/tidl_net_inceptionv1_224.bin
+paramsBinFile   = ../test/testvecs/config/tidl_models/tidl_param_inceptionv1_224.bin
 inWidth = 224
 inHeight = 224
 inNumChannels = 3
index b41294bd11c3512bb3234e7c1061bcd8ef7813b0..37856bb49fecaa369a6ae7b21d4d81024fe6d627 100755 (executable)
@@ -1,9 +1,9 @@
 numFrames   = 1
 preProcType = 2
-inData   = ../test/testvecs/input/preproc_2_224x224.y
+inData   = "../test/testvecs/input/preproc_2_224x224.y"
 outData   = "stats_tool_out.bin"
-netBinFile      = ../test/testvecs/config/tidl_models/tidl_inception_v1_net.bin
-paramsBinFile   = ../test/testvecs/config/tidl_models/tidl_inception_v1_param.bin
+netBinFile      = ../test/testvecs/config/tidl_models/tidl_net_inceptionv1_224.bin
+paramsBinFile   = ../test/testvecs/config/tidl_models/tidl_param_inceptionv1_224.bin
 inWidth = 224
 inHeight = 224
 inNumChannels = 3
index 787bb2f4e5fbfe654104f6ad0df911f33bad9e5a..0cb37ee61fb235f9b12eedc9e2e0b0374d862fe5 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/preproc_0_224x224.y
+inData   = "../test/testvecs/input/preproc_0_224x224.y"
 outData   = "./stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_imagenet_jacintonet11v2_bn.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_imagenet_jacintonet11v2_bn.bin"
index d6fc85b93103daf78ab9e9652acc482cfb3d7c29..bd354167174803a43ec70c84e191f99aa2884227 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames     = 1
 preProcType   = 0
-inData        = ../test/testvecs/input/preproc_3_32x32.y
+inData        = "../test/testvecs/input/preproc_3_32x32.y"
 outData       = "./stats_tool_out.bin"
 netBinFile    = "../test/testvecs/config/tidl_models/tidl_net_cifar_jacintonet11v2.bin"
 paramsBinFile = "../test/testvecs/config/tidl_models/tidl_param_cifar_jacintonet11v2.bin"
index 2bf703c2bc303accee4eea5fdb26a799bdfa1f06..8d266f43397de9333d6814ccf3c0fa28b457432b 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames      = 1
 preProcType    = 0
-inData         = ../test/testvecs/input/preproc_3_32x32.y
+inData         = "../test/testvecs/input/preproc_3_32x32.y"
 outData        = "stats_tool_out.bin"
 netBinFile     = "../test/testvecs/config/tidl_models/tidl_net_jacintonet_cntrllayers.bin"
 paramsBinFile  = "../test/testvecs/config/tidl_models/tidl_param_jacintonet_cntrllayers.bin"
index 0a4c3775bc537d0bf4a3c70c044af0e1bdb7d78f..c03f72436c5eb152aa69e6369e247e58609099cf 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames       = 1
 preProcType     = 0
-inData          = ../test/testvecs/input/preproc_0_224x224.y
+inData          = "../test/testvecs/input/preproc_0_224x224.y"
 outData         = "stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_imagenet_jacintonet11v2_prelu.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_imagenet_jacintonet11v2_prelu.bin"
index 184ba7a80607bccafa92097bcb75b5a46b25eb48..79bdd95324f9f387f4d5456ab348587760bbe673 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/preproc_0_224x224.y
+inData   = "../test/testvecs/input/preproc_0_224x224.y"
 outData   = "stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_imagenet_jacintonet11v2.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_imagenet_jacintonet11v2.bin"
index a449ece9f492b98d00d23a7431697cd89e8e93a0..786879d4bc354190868f37e8c79fbdfa248e0c4b 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/preproc_0_224x224.y
+inData   = "../test/testvecs/input/preproc_0_224x224.y"
 outData   = "stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_imagenet_jacintonet11v2_dense.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_imagenet_jacintonet11v2_dense.bin"
index e4f33a5072aa48fee5c0f1c59228d8831f8f83e3..0e5c8990b1a65c2a9a65a9c62540ed88f8e9ca8a 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/preproc_0_224x224.y
+inData   = "../test/testvecs/input/preproc_0_224x224.y"
 outData   = "stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_imagenet_jacintonet11v2_dense.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_imagenet_jacintonet11v2_dense.bin"
index 25983b33b0f18da513a7e5fbaff2c35f1c69f62d..7e821b9523e9308cef5efedace0f17a163081749 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/preproc_0_224x224.y
+inData   = "../test/testvecs/input/preproc_0_224x224.y"
 outData   = "stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_imagenet_jacintonet11v2.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_imagenet_jacintonet11v2.bin"
index ce762700f196ad6695698345d9db9ff1fcc27c75..97683591f0eb67564f23e5195c5803144c002042 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/000100_1024x512_bgr.y
+inData   = "../test/testvecs/input/000100_1024x512_bgr.y"
 outData   = "./stats_tool_out.bin"
 netBinFile     = ../test/testvecs/config/tidl_models/tidl_net_jsegnet21v2.bin
 paramsBinFile        = ../test/testvecs/config/tidl_models/tidl_param_jsegnet21v2.bin
index 357e1e737a882811b39779d3a1871d5f884a37bb..35e6611fe2b894843c4b9c58bf74e022b4329883 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/000100_1024x512_bgr.y
+inData   = "../test/testvecs/input/000100_1024x512_bgr.y"
 outData   = "./stats_tool_out.bin"
 netBinFile     = ../test/testvecs/config/tidl_models/tidl_net_jseg21_cityscapes_dense.bin
 paramsBinFile  = ../test/testvecs/config/tidl_models/tidl_param_jseg21_cityscapes_dense.bin
index fdf242279ec79bafe239dcaba35ecc48b842acd5..b3053f7ef5368dc1d1ed66f29b41bc888d260062 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 9
 preProcType = 0
-inData   = ../test/testvecs/input/000100_1024x512_bgr.y
+inData   = "../test/testvecs/input/000100_1024x512_bgr.y"
 outData   = "./stats_tool_out.bin"
 netBinFile     = ../test/testvecs/config/tidl_models/jsegnet21/tidl_net_jsegnet21v2.bin
 paramsBinFile        = ../test/testvecs/config/tidl_models/jsegnet21/tidl_param_jsegnet21v2.bin
index f4b0b7fc8e94987dff59cf8a182e6ac1457c5dd7..e05c93399e22a177b57e818d3dcbc5b7d43f1bae 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/digits10_images_28x28.y
+inData   = "../test/testvecs/input/digits10_images_28x28.y"
 outData   = "stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_mnist_lenet.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_mnist_lenet.bin"
index 094b697ea3e845ede44231b6f5e5144a571f3331..17c20bf588650684d5eba129103c33bbdba76e20 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 2
-inData   = ../test/testvecs/input/preproc_2_224x224.y
+inData   = "../test/testvecs/input/preproc_2_224x224.y"
 outData   = "./stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_mobilenet_1_224.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_mobilenet_1_224.bin"
index c532ed19a216179671dd969ac19fa05d4c720c41..0c13965117152297e3915f44d79ed1fb67fef5b0 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 2
-inData   = ../test/testvecs/input/preproc_2_224x224.y
+inData   = "../test/testvecs/input/preproc_2_224x224.y"
 outData   = "./stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_mobilenet_1_224.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_mobilenet_1_224.bin"
diff --git a/examples/test/testvecs/config/infer/tidl_config_mobileNet2.txt b/examples/test/testvecs/config/infer/tidl_config_mobileNet2.txt
new file mode 100755 (executable)
index 0000000..f163716
--- /dev/null
@@ -0,0 +1,9 @@
+numFrames   = 1\r
+preProcType = 2\r
+inData    = "../test/testvecs/input/preproc_2_224x224.y"\r
+outData   = "./stats_tool_out.bin"\r
+netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_mobilenet_2_224.bin"\r
+paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_mobilenet_2_224.bin"\r
+inWidth = 224\r
+inHeight = 224\r
+inNumChannels = 3\r
diff --git a/examples/test/testvecs/config/infer/tidl_config_mobileNet2_lg2.txt b/examples/test/testvecs/config/infer/tidl_config_mobileNet2_lg2.txt
new file mode 100755 (executable)
index 0000000..ed36dfb
--- /dev/null
@@ -0,0 +1,10 @@
+numFrames   = 1\r
+preProcType = 2\r
+inData    = "../test/testvecs/input/preproc_2_224x224.y"\r
+outData   = "./stats_tool_out.bin"\r
+netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_mobilenet_2_224.bin"\r
+paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_mobilenet_2_224.bin"\r
+inWidth = 224\r
+inHeight = 224\r
+inNumChannels = 3\r
+layerIndex2LayerGroupId = { {63, 2}, {64, 2}, {65, 2} }\r
index e6258de00cf70a73df1cc8e69a53669a0aa2faa8..9f8d56ed58404529abf832b1d5bc1cac66b3df4f 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 0
-inData   = ../test/testvecs/input/000100_1024x512_bgr.y
+inData   = "../test/testvecs/input/000100_1024x512_bgr.y"
 outData   = "./stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_dense_varibale_block_size.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_dense_varibale_block_size.bin"
index b599e6999722b1088fb5f5b654bd4092c52cd080..911180e4372eccb3465998d5e3496b7ea381e985 100755 (executable)
@@ -1,6 +1,6 @@
 numFrames   = 1
 preProcType = 1
-inData   = ../test/testvecs/input/preproc_1_227x227.y
+inData   = "../test/testvecs/input/preproc_1_227x227.y"
 outData   = "./stats_tool_out.bin"
 netBinFile      = "../test/testvecs/config/tidl_models/tidl_net_squeezeNet1.1.bin"
 paramsBinFile   = "../test/testvecs/config/tidl_models/tidl_param_squeezeNet1.1.bin"
similarity index 99%
rename from examples/test/testvecs/config/tidl_models/tidl_inception_v1_net.bin
rename to examples/test/testvecs/config/tidl_models/tidl_net_inceptionv1_224.bin
index 38600047dccb32ebd38abfaab4d475e3e6eaa56b..96dc888afff4bb9122c569ac30caa2707f8218df 100644 (file)
Binary files a/examples/test/testvecs/config/tidl_models/tidl_inception_v1_net.bin and b/examples/test/testvecs/config/tidl_models/tidl_net_inceptionv1_224.bin differ
index 44950df26f3bc82b5f8b4cac6e32151c424ea5c1..7933c7ab39d03a8f04d7a58cf89402cedfcb6952 100644 (file)
Binary files a/examples/test/testvecs/config/tidl_models/tidl_net_mobilenet_1_224.bin and b/examples/test/testvecs/config/tidl_models/tidl_net_mobilenet_1_224.bin differ
diff --git a/examples/test/testvecs/config/tidl_models/tidl_net_mobilenet_2_224.bin b/examples/test/testvecs/config/tidl_models/tidl_net_mobilenet_2_224.bin
new file mode 100755 (executable)
index 0000000..9aacebe
Binary files /dev/null and b/examples/test/testvecs/config/tidl_models/tidl_net_mobilenet_2_224.bin differ
diff --git a/examples/test/testvecs/config/tidl_models/tidl_param_mobilenet_2_224.bin b/examples/test/testvecs/config/tidl_models/tidl_param_mobilenet_2_224.bin
new file mode 100755 (executable)
index 0000000..8eab5ee
Binary files /dev/null and b/examples/test/testvecs/config/tidl_models/tidl_param_mobilenet_2_224.bin differ
index 867d7422e553e2a66f24c5a5925422c1e39c1cf9..33671ac9426b6594ef6527c3ac2cef774dff8813 100644 (file)
@@ -452,7 +452,7 @@ Device::Ptr Device::Create(DeviceType core_type, const DeviceIds& ids,
 }
 
 // Minimum version of OpenCL required for this version of TIDL API
-#define MIN_OCL_VERSION "01.01.18.00"
+#define MIN_OCL_VERSION "01.01.19.00"
 static bool CheckOpenCLVersion(cl_platform_id id)
 {
     cl_int err;