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Merge pull request #21172 from alalek:dnn_test_drop_non_cpu_int8

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Alexander Alekhin 2021-12-02 13:50:04 +00:00
commit d206350738
1 changed files with 11 additions and 191 deletions
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202
modules/dnn/test/test_int8_layers.cpp
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@ -8,6 +8,13 @@
#include <opencv2/dnn/all_layers.hpp> #include <opencv2/dnn/all_layers.hpp>
namespace opencv_test { namespace { namespace opencv_test { namespace {
testing::internal::ParamGenerator< tuple<Backend, Target> > dnnBackendsAndTargetsInt8()
{
std::vector< tuple<Backend, Target> > targets;
targets.push_back(make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU));
return testing::ValuesIn(targets);
}
template<typename TString> template<typename TString>
static std::string _tf(TString filename) static std::string _tf(TString filename)
{ {
@ -341,7 +348,7 @@ TEST_P(Test_Int8_layers, Eltwise)
testLayer("split_max", "ONNX", 0.004, 0.012); 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 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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; float l1 = 4e-5, lInf = 0.0025;
testONNXNet("caffenet", l1, lInf); testONNXNet("caffenet", l1, lInf);
} }
@ -679,11 +681,6 @@ TEST_P(Test_Int8_nets, RCNN_ILSVRC13)
if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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; float l1 = 0.02, lInf = 0.042;
testONNXNet("rcnn_ilsvrc13", l1, lInf); testONNXNet("rcnn_ilsvrc13", l1, lInf);
} }
@ -715,12 +712,6 @@ TEST_P(Test_Int8_nets, Shufflenet)
if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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), Net net = readNetFromTensorflow(findDataFile("dnn/ssd_mobilenet_v1_ppn_coco.pb", false),
findDataFile("dnn/ssd_mobilenet_v1_ppn_coco.pbtxt")); 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(CV_TEST_TAG_DNN_SKIP_OPENCL);
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); 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), Net net = readNetFromTensorflow(findDataFile("dnn/ssd_inception_v2_coco_2017_11_17.pb", false),
findDataFile("dnn/ssd_inception_v2_coco_2017_11_17.pbtxt")); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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) if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_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), Net net = readNetFromTensorflow(findDataFile("dnn/faster_rcnn_resnet50_coco_2018_01_28.pb", false),
findDataFile("dnn/faster_rcnn_resnet50_coco_2018_01_28.pbtxt")); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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) if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_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), 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")); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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"), Net net = readNetFromCaffe(findDataFile("dnn/faster_rcnn_vgg16.prototxt"),
findDataFile("dnn/VGG16_faster_rcnn_final.caffemodel", false)); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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"), Net net = readNetFromCaffe(findDataFile("dnn/faster_rcnn_zf.prototxt"),
findDataFile("dnn/ZF_faster_rcnn_final.caffemodel", false)); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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"), Net net = readNetFromCaffe(findDataFile("dnn/rfcn_pascal_voc_resnet50.prototxt"),
findDataFile("dnn/resnet50_rfcn_final.caffemodel", false)); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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_<float>(6, 7) << 0, 6, 0.750469f, 0.577374f, 0.127391f, 0.902949f, 0.300809f, Mat ref = (Mat_<float>(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, 1, 0.780879f, 0.270762f, 0.264102f, 0.732475f, 0.745412f,
0, 11, 0.901615f, 0.1386f, 0.338509f, 0.421337f, 0.938789f, 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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_<float>(4, 7) << 0, 6, 0.761967f, 0.579042f, 0.159161f, 0.894482f, 0.31994f, Mat ref = (Mat_<float>(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, 0, 11, 0.780595f, 0.129696f, 0.386467f, 0.445275f, 0.920994f,
1, 6, 0.651450f, 0.460526f, 0.458019f, 0.522527f, 0.5341f, 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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 N0 = 3;
const int N1 = 6; const int N1 = 6;
static const float ref_[/* (N0 + N1) * 7 */] = { 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); 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"); SCOPED_TRACE("batch size 2");
testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff, confThreshold); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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 N0 = 3;
const int N1 = 7; const int N1 = 7;
static const float ref_[/* (N0 + N1) * 7 */] = { static const float ref_[/* (N0 + N1) * 7 */] = {
@ -1262,19 +1118,6 @@ TEST_P(Test_Int8_nets, YOLOv4)
{ {
SCOPED_TRACE("batch size 2"); 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); 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()) if (target == DNN_TARGET_OPENCL && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL); 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 float confThreshold = 0.6;
const int N0 = 2; const int N0 = 2;
@ -1314,38 +1152,20 @@ TEST_P(Test_Int8_nets, YOLOv4_tiny)
double scoreDiff = 0.12; double scoreDiff = 0.12;
double iouDiff = target == DNN_TARGET_OPENCL_FP16 ? 0.2 : 0.082; 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<double>::quiet_NaN();
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_OPENCL)
iouDiff = std::numeric_limits<double>::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<double>::quiet_NaN();
#endif
{ {
SCOPED_TRACE("batch size 1"); SCOPED_TRACE("batch size 1");
testDarknetModel(config_file, weights_file, ref.rowRange(0, N0), scoreDiff, iouDiff, confThreshold); 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 /* bad accuracy on second image
{ {
SCOPED_TRACE("batch size 2"); SCOPED_TRACE("batch size 2");
testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff, confThreshold); 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 }} // namespace