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dnn(test): add extra IR models, more checks in IE testing code
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@ -112,6 +112,25 @@ static const std::map<std::string, OpenVINOModelTestCaseInfo>& getOpenVINOTestMo
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"intel/age-gender-recognition-retail-0013/FP16/age-gender-recognition-retail-0013",
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"intel/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013"
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}},
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#endif
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#if INF_ENGINE_RELEASE >= 2021020000
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// OMZ: 2020.2
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{ "face-detection-0105", {
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"intel/face-detection-0105/FP32/face-detection-0105",
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"intel/face-detection-0105/FP16/face-detection-0105"
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}},
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{ "face-detection-0106", {
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"intel/face-detection-0106/FP32/face-detection-0106",
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"intel/face-detection-0106/FP16/face-detection-0106"
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}},
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#endif
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#if INF_ENGINE_RELEASE >= 2021040000
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// OMZ: 2021.4
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{ "person-vehicle-bike-detection-2004", {
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"intel/person-vehicle-bike-detection-2004/FP32/person-vehicle-bike-detection-2004",
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"intel/person-vehicle-bike-detection-2004/FP16/person-vehicle-bike-detection-2004"
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//"intel/person-vehicle-bike-detection-2004/FP16-INT8/person-vehicle-bike-detection-2004"
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}},
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#endif
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};
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@ -145,10 +164,22 @@ inline static std::string getOpenVINOModel(const std::string &modelName, bool is
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static inline void genData(const InferenceEngine::TensorDesc& desc, Mat& m, Blob::Ptr& dataPtr)
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{
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const std::vector<size_t>& dims = desc.getDims();
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m.create(std::vector<int>(dims.begin(), dims.end()), CV_32F);
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randu(m, -1, 1);
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dataPtr = make_shared_blob<float>(desc, (float*)m.data);
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if (desc.getPrecision() == InferenceEngine::Precision::FP32)
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{
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m.create(std::vector<int>(dims.begin(), dims.end()), CV_32F);
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randu(m, -1, 1);
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dataPtr = make_shared_blob<float>(desc, (float*)m.data);
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}
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else if (desc.getPrecision() == InferenceEngine::Precision::I32)
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{
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m.create(std::vector<int>(dims.begin(), dims.end()), CV_32S);
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randu(m, -100, 100);
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dataPtr = make_shared_blob<int>(desc, (int*)m.data);
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}
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else
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{
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FAIL() << "Unsupported precision: " << desc.getPrecision();
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}
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}
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void runIE(Target target, const std::string& xmlPath, const std::string& binPath,
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@ -254,7 +285,16 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
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BlobMap inputBlobs;
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for (auto& it : net.getInputsInfo())
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{
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genData(it.second->getTensorDesc(), inputsMap[it.first], inputBlobs[it.first]);
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const InferenceEngine::TensorDesc& desc = it.second->getTensorDesc();
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genData(desc, inputsMap[it.first], inputBlobs[it.first]);
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if (cvtest::debugLevel > 0)
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{
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const std::vector<size_t>& dims = desc.getDims();
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std::cout << "Input: '" << it.first << "' precison=" << desc.getPrecision() << " dims=" << dims.size() << " [";
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for (auto d : dims)
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std::cout << " " << d;
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std::cout << "] ocv_mat=" << inputsMap[it.first].size << " of " << typeToString(inputsMap[it.first].type()) << std::endl;
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}
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}
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infRequest.SetInput(inputBlobs);
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@ -263,7 +303,16 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
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BlobMap outputBlobs;
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for (auto& it : net.getOutputsInfo())
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{
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genData(it.second->getTensorDesc(), outputsMap[it.first], outputBlobs[it.first]);
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const InferenceEngine::TensorDesc& desc = it.second->getTensorDesc();
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genData(desc, outputsMap[it.first], outputBlobs[it.first]);
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if (cvtest::debugLevel > 0)
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{
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const std::vector<size_t>& dims = desc.getDims();
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std::cout << "Output: '" << it.first << "' precison=" << desc.getPrecision() << " dims=" << dims.size() << " [";
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for (auto d : dims)
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std::cout << " " << d;
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std::cout << "] ocv_mat=" << outputsMap[it.first].size << " of " << typeToString(outputsMap[it.first].type()) << std::endl;
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}
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}
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infRequest.SetOutput(outputBlobs);
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@ -284,6 +333,12 @@ void runCV(Backend backendId, Target targetId, const std::string& xmlPath, const
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net.setPreferableTarget(targetId);
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std::vector<String> outNames = net.getUnconnectedOutLayersNames();
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if (cvtest::debugLevel > 0)
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{
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std::cout << "OpenCV output names: " << outNames.size() << std::endl;
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for (auto name : outNames)
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std::cout << "- " << name << std::endl;
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}
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std::vector<Mat> outs;
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net.forward(outs, outNames);
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@ -307,13 +362,26 @@ TEST_P(DNNTestOpenVINO, models)
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ASSERT_FALSE(backendId != DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && backendId != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) <<
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"Inference Engine backend is required";
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#if INF_ENGINE_VER_MAJOR_EQ(2021040000)
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if (targetId == DNN_TARGET_MYRIAD && (
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modelName == "person-detection-retail-0013" || // ncDeviceOpen:1013 Failed to find booted device after boot
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modelName == "age-gender-recognition-retail-0013" // ncDeviceOpen:1013 Failed to find booted device after boot
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#if INF_ENGINE_VER_MAJOR_GE(2021030000)
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if (targetId == DNN_TARGET_MYRIAD && (false
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|| modelName == "person-detection-retail-0013" // ncDeviceOpen:1013 Failed to find booted device after boot
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|| modelName == "age-gender-recognition-retail-0013" // ncDeviceOpen:1013 Failed to find booted device after boot
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|| modelName == "face-detection-0105" // get_element_type() must be called on a node with exactly one output
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|| modelName == "face-detection-0106" // get_element_type() must be called on a node with exactly one output
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|| modelName == "person-vehicle-bike-detection-2004" // 2021.4+: ncDeviceOpen:1013 Failed to find booted device after boot
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)
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)
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applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
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if (targetId == DNN_TARGET_OPENCL && (false
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|| modelName == "face-detection-0106" // Operation: 2278 of type ExperimentalDetectronPriorGridGenerator(op::v6) is not supported
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)
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)
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applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
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if (targetId == DNN_TARGET_OPENCL_FP16 && (false
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|| modelName == "face-detection-0106" // Operation: 2278 of type ExperimentalDetectronPriorGridGenerator(op::v6) is not supported
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)
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)
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applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
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#endif
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#if INF_ENGINE_VER_MAJOR_GE(2020020000)
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@ -350,6 +418,8 @@ TEST_P(DNNTestOpenVINO, models)
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if (targetId == DNN_TARGET_MYRIAD)
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resetMyriadDevice();
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EXPECT_NO_THROW(runIE(targetId, xmlPath, binPath, inputsMap, ieOutputsMap)) << "runIE";
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if (targetId == DNN_TARGET_MYRIAD)
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resetMyriadDevice();
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EXPECT_NO_THROW(runCV(backendId, targetId, xmlPath, binPath, inputsMap, cvOutputsMap)) << "runCV";
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double eps = 0;
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@ -357,6 +427,14 @@ TEST_P(DNNTestOpenVINO, models)
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if (targetId == DNN_TARGET_CPU && checkHardwareSupport(CV_CPU_AVX_512F))
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eps = 1e-5;
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#endif
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#if INF_ENGINE_VER_MAJOR_GE(2021030000)
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if (targetId == DNN_TARGET_CPU && modelName == "face-detection-0105")
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eps = 2e-4;
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#endif
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#if INF_ENGINE_VER_MAJOR_GE(2021040000)
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if (targetId == DNN_TARGET_CPU && modelName == "person-vehicle-bike-detection-2004")
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eps = 1e-6;
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#endif
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EXPECT_EQ(ieOutputsMap.size(), cvOutputsMap.size());
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for (auto& srcIt : ieOutputsMap)
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