From f55c9ed1ba5f40a67014bd030463f80bece351a0 Mon Sep 17 00:00:00 2001 From: Alexander Alekhin Date: Thu, 2 Dec 2021 05:52:12 +0000 Subject: [PATCH] dnn(test): drop non OCV/CPU cases for Int8 - zero code coverage and up to x3-x8 tests slowdown - implementation executes OCV/CPU in all cases - wrong skip conditions --- modules/dnn/test/test_int8_layers.cpp | 202 ++------------------------ 1 file changed, 11 insertions(+), 191 deletions(-) diff --git a/modules/dnn/test/test_int8_layers.cpp b/modules/dnn/test/test_int8_layers.cpp index 85c30a4271..c181dfa5eb 100644 --- a/modules/dnn/test/test_int8_layers.cpp +++ b/modules/dnn/test/test_int8_layers.cpp @@ -8,6 +8,13 @@ #include namespace opencv_test { namespace { +testing::internal::ParamGenerator< tuple > dnnBackendsAndTargetsInt8() +{ + std::vector< tuple > targets; + targets.push_back(make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)); + return testing::ValuesIn(targets); +} + template static std::string _tf(TString filename) { @@ -341,7 +348,7 @@ TEST_P(Test_Int8_layers, Eltwise) testLayer("split_max", "ONNX", 0.004, 0.012); } -INSTANTIATE_TEST_CASE_P(/**/, Test_Int8_layers, dnnBackendsAndTargets()); +INSTANTIATE_TEST_CASE_P(/**/, Test_Int8_layers, dnnBackendsAndTargetsInt8()); class Test_Int8_nets : public DNNTestLayer { @@ -657,11 +664,6 @@ TEST_P(Test_Int8_nets, CaffeNet) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019030000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD - && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif float l1 = 4e-5, lInf = 0.0025; testONNXNet("caffenet", l1, lInf); } @@ -679,11 +681,6 @@ TEST_P(Test_Int8_nets, RCNN_ILSVRC13) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019030000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD - && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif float l1 = 0.02, lInf = 0.042; testONNXNet("rcnn_ilsvrc13", l1, lInf); } @@ -715,12 +712,6 @@ TEST_P(Test_Int8_nets, Shufflenet) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) - { - if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); - if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); - if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER); - } testONNXNet("shufflenet", default_l1, default_lInf); } @@ -767,12 +758,6 @@ TEST_P(Test_Int8_nets, MobileNet_v1_SSD_PPN) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2018050000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) - applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, - CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif - Net net = readNetFromTensorflow(findDataFile("dnn/ssd_mobilenet_v1_ppn_coco.pb", false), findDataFile("dnn/ssd_mobilenet_v1_ppn_coco.pbtxt")); @@ -792,11 +777,6 @@ TEST_P(Test_Int8_nets, Inception_v2_SSD) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2019010000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD && - getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif Net net = readNetFromTensorflow(findDataFile("dnn/ssd_inception_v2_coco_2017_11_17.pb", false), findDataFile("dnn/ssd_inception_v2_coco_2017_11_17.pbtxt")); @@ -875,25 +855,9 @@ TEST_P(Test_Int8_nets, FasterRCNN_resnet50) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#ifdef INF_ENGINE_RELEASE - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && - (INF_ENGINE_VER_MAJOR_LT(2019020000) || target != DNN_TARGET_CPU)) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - - if (INF_ENGINE_VER_MAJOR_GT(2019030000) && - backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); -#endif - - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); - if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16); - if (backend == DNN_BACKEND_CUDA && target == DNN_TARGET_CUDA_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA_FP16); - Net net = readNetFromTensorflow(findDataFile("dnn/faster_rcnn_resnet50_coco_2018_01_28.pb", false), findDataFile("dnn/faster_rcnn_resnet50_coco_2018_01_28.pbtxt")); @@ -918,25 +882,9 @@ TEST_P(Test_Int8_nets, FasterRCNN_inceptionv2) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#ifdef INF_ENGINE_RELEASE - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && - (INF_ENGINE_VER_MAJOR_LT(2019020000) || target != DNN_TARGET_CPU)) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - - if (INF_ENGINE_VER_MAJOR_GT(2019030000) && - backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); -#endif - - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); - if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16); - if (backend == DNN_BACKEND_CUDA && target == DNN_TARGET_CUDA_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA_FP16); - Net net = readNetFromTensorflow(findDataFile("dnn/faster_rcnn_inception_v2_coco_2018_01_28.pb", false), findDataFile("dnn/faster_rcnn_inception_v2_coco_2018_01_28.pbtxt")); @@ -965,17 +913,6 @@ TEST_P(Test_Int8_nets, FasterRCNN_vgg16) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)) - applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16); - - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD); -#endif - Net net = readNetFromCaffe(findDataFile("dnn/faster_rcnn_vgg16.prototxt"), findDataFile("dnn/VGG16_faster_rcnn_final.caffemodel", false)); @@ -1003,17 +940,6 @@ TEST_P(Test_Int8_nets, FasterRCNN_zf) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || - backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16); - - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || - backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_MYRIAD) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD); - - if (target == DNN_TARGET_CUDA_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA_FP16); - Net net = readNetFromCaffe(findDataFile("dnn/faster_rcnn_zf.prototxt"), findDataFile("dnn/ZF_faster_rcnn_final.caffemodel", false)); @@ -1038,14 +964,6 @@ TEST_P(Test_Int8_nets, RFCN) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || - backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16); - - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || - backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_MYRIAD) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD); - Net net = readNetFromCaffe(findDataFile("dnn/rfcn_pascal_voc_resnet50.prototxt"), findDataFile("dnn/resnet50_rfcn_final.caffemodel", false)); @@ -1072,22 +990,6 @@ TEST_P(Test_Int8_nets, YoloVoc) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16); -#endif -#if defined(INF_ENGINE_RELEASE) - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && - target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X); -#endif - Mat ref = (Mat_(6, 7) << 0, 6, 0.750469f, 0.577374f, 0.127391f, 0.902949f, 0.300809f, 0, 1, 0.780879f, 0.270762f, 0.264102f, 0.732475f, 0.745412f, 0, 11, 0.901615f, 0.1386f, 0.338509f, 0.421337f, 0.938789f, @@ -1119,18 +1021,6 @@ TEST_P(Test_Int8_nets, TinyYoloVoc) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif -#if defined(INF_ENGINE_RELEASE) - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && - target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X); -#endif - Mat ref = (Mat_(4, 7) << 0, 6, 0.761967f, 0.579042f, 0.159161f, 0.894482f, 0.31994f, 0, 11, 0.780595f, 0.129696f, 0.386467f, 0.445275f, 0.920994f, 1, 6, 0.651450f, 0.460526f, 0.458019f, 0.522527f, 0.5341f, @@ -1160,16 +1050,6 @@ TEST_P(Test_Int8_nets, YOLOv3) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif - - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH); - const int N0 = 3; const int N1 = 6; static const float ref_[/* (N0 + N1) * 7 */] = { @@ -1195,19 +1075,6 @@ TEST_P(Test_Int8_nets, YOLOv3) testDarknetModel(config_file, weights_file, ref.rowRange(0, N0), scoreDiff, iouDiff, confThreshold); } -#if defined(INF_ENGINE_RELEASE) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) - { - if (target == DNN_TARGET_OPENCL) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - else if (target == DNN_TARGET_OPENCL_FP16 && INF_ENGINE_VER_MAJOR_LE(202010000)) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - else if (target == DNN_TARGET_MYRIAD && - getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X); - } -#endif - { SCOPED_TRACE("batch size 2"); testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff, confThreshold); @@ -1223,17 +1090,6 @@ TEST_P(Test_Int8_nets, YOLOv4) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif -#if defined(INF_ENGINE_RELEASE) - if (target == DNN_TARGET_MYRIAD) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif - const int N0 = 3; const int N1 = 7; static const float ref_[/* (N0 + N1) * 7 */] = { @@ -1262,19 +1118,6 @@ TEST_P(Test_Int8_nets, YOLOv4) { SCOPED_TRACE("batch size 2"); -#if defined(INF_ENGINE_RELEASE) - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) - { - if (target == DNN_TARGET_OPENCL) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - else if (target == DNN_TARGET_OPENCL_FP16 && INF_ENGINE_VER_MAJOR_LE(202010000)) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - else if (target == DNN_TARGET_MYRIAD && - getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X); - } -#endif - testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff); } } @@ -1290,11 +1133,6 @@ TEST_P(Test_Int8_nets, YOLOv4_tiny) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); -#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2021010000) - if (target == DNN_TARGET_MYRIAD) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif - const float confThreshold = 0.6; const int N0 = 2; @@ -1314,38 +1152,20 @@ TEST_P(Test_Int8_nets, YOLOv4_tiny) double scoreDiff = 0.12; double iouDiff = target == DNN_TARGET_OPENCL_FP16 ? 0.2 : 0.082; -#if defined(INF_ENGINE_RELEASE) - if (target == DNN_TARGET_MYRIAD) // bad accuracy - iouDiff = std::numeric_limits::quiet_NaN(); - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_OPENCL) - iouDiff = std::numeric_limits::quiet_NaN(); - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || - backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_OPENCL_FP16) - iouDiff = std::numeric_limits::quiet_NaN(); -#endif - { SCOPED_TRACE("batch size 1"); testDarknetModel(config_file, weights_file, ref.rowRange(0, N0), scoreDiff, iouDiff, confThreshold); } + throw SkipTestException("batch2: bad accuracy on second image"); /* bad accuracy on second image { SCOPED_TRACE("batch size 2"); testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff, confThreshold); } */ - -#if defined(INF_ENGINE_RELEASE) - if (target == DNN_TARGET_MYRIAD) // bad accuracy - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_OPENCL) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION); - if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || - backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_OPENCL_FP16) - applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION); -#endif } -INSTANTIATE_TEST_CASE_P(/**/, Test_Int8_nets, dnnBackendsAndTargets()); +INSTANTIATE_TEST_CASE_P(/**/, Test_Int8_nets, dnnBackendsAndTargetsInt8()); + }} // namespace