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dnn(test): add extra IR models, more checks in IE testing code

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This commit is contained in:
Alexander Alekhin 2021-07-10 13:06:33 +00:00
parent bc210b292b
commit 602e7c83e2
1 changed files with 88 additions and 10 deletions
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98
modules/dnn/test/test_ie_models.cpp
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@ -112,6 +112,25 @@ static const std::map<std::string, OpenVINOModelTestCaseInfo>& getOpenVINOTestMo
"intel/age-gender-recognition-retail-0013/FP16/age-gender-recognition-retail-0013", "intel/age-gender-recognition-retail-0013/FP16/age-gender-recognition-retail-0013",
"intel/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013" "intel/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013"
}}, }},
#endif
#if INF_ENGINE_RELEASE >= 2021020000
// OMZ: 2020.2
{ "face-detection-0105", {
"intel/face-detection-0105/FP32/face-detection-0105",
"intel/face-detection-0105/FP16/face-detection-0105"
}},
{ "face-detection-0106", {
"intel/face-detection-0106/FP32/face-detection-0106",
"intel/face-detection-0106/FP16/face-detection-0106"
}},
#endif
#if INF_ENGINE_RELEASE >= 2021040000
// OMZ: 2021.4
{ "person-vehicle-bike-detection-2004", {
"intel/person-vehicle-bike-detection-2004/FP32/person-vehicle-bike-detection-2004",
"intel/person-vehicle-bike-detection-2004/FP16/person-vehicle-bike-detection-2004"
//"intel/person-vehicle-bike-detection-2004/FP16-INT8/person-vehicle-bike-detection-2004"
}},
#endif #endif
}; };
@ -145,10 +164,22 @@ inline static std::string getOpenVINOModel(const std::string &modelName, bool is
static inline void genData(const InferenceEngine::TensorDesc& desc, Mat& m, Blob::Ptr& dataPtr) static inline void genData(const InferenceEngine::TensorDesc& desc, Mat& m, Blob::Ptr& dataPtr)
{ {
const std::vector<size_t>& dims = desc.getDims(); const std::vector<size_t>& dims = desc.getDims();
m.create(std::vector<int>(dims.begin(), dims.end()), CV_32F); if (desc.getPrecision() == InferenceEngine::Precision::FP32)
randu(m, -1, 1); {
m.create(std::vector<int>(dims.begin(), dims.end()), CV_32F);
dataPtr = make_shared_blob<float>(desc, (float*)m.data); randu(m, -1, 1);
dataPtr = make_shared_blob<float>(desc, (float*)m.data);
}
else if (desc.getPrecision() == InferenceEngine::Precision::I32)
{
m.create(std::vector<int>(dims.begin(), dims.end()), CV_32S);
randu(m, -100, 100);
dataPtr = make_shared_blob<int>(desc, (int*)m.data);
}
else
{
FAIL() << "Unsupported precision: " << desc.getPrecision();
}
} }
void runIE(Target target, const std::string& xmlPath, const std::string& binPath, void runIE(Target target, const std::string& xmlPath, const std::string& binPath,
@ -254,7 +285,16 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
BlobMap inputBlobs; BlobMap inputBlobs;
for (auto& it : net.getInputsInfo()) for (auto& it : net.getInputsInfo())
{ {
genData(it.second->getTensorDesc(), inputsMap[it.first], inputBlobs[it.first]); const InferenceEngine::TensorDesc& desc = it.second->getTensorDesc();
genData(desc, inputsMap[it.first], inputBlobs[it.first]);
if (cvtest::debugLevel > 0)
{
const std::vector<size_t>& dims = desc.getDims();
std::cout << "Input: '" << it.first << "' precison=" << desc.getPrecision() << " dims=" << dims.size() << " [";
for (auto d : dims)
std::cout << " " << d;
std::cout << "] ocv_mat=" << inputsMap[it.first].size << " of " << typeToString(inputsMap[it.first].type()) << std::endl;
}
} }
infRequest.SetInput(inputBlobs); infRequest.SetInput(inputBlobs);
@ -263,7 +303,16 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
BlobMap outputBlobs; BlobMap outputBlobs;
for (auto& it : net.getOutputsInfo()) for (auto& it : net.getOutputsInfo())
{ {
genData(it.second->getTensorDesc(), outputsMap[it.first], outputBlobs[it.first]); const InferenceEngine::TensorDesc& desc = it.second->getTensorDesc();
genData(desc, outputsMap[it.first], outputBlobs[it.first]);
if (cvtest::debugLevel > 0)
{
const std::vector<size_t>& dims = desc.getDims();
std::cout << "Output: '" << it.first << "' precison=" << desc.getPrecision() << " dims=" << dims.size() << " [";
for (auto d : dims)
std::cout << " " << d;
std::cout << "] ocv_mat=" << outputsMap[it.first].size << " of " << typeToString(outputsMap[it.first].type()) << std::endl;
}
} }
infRequest.SetOutput(outputBlobs); infRequest.SetOutput(outputBlobs);
@ -284,6 +333,12 @@ void runCV(Backend backendId, Target targetId, const std::string& xmlPath, const
net.setPreferableTarget(targetId); net.setPreferableTarget(targetId);
std::vector<String> outNames = net.getUnconnectedOutLayersNames(); std::vector<String> outNames = net.getUnconnectedOutLayersNames();
if (cvtest::debugLevel > 0)
{
std::cout << "OpenCV output names: " << outNames.size() << std::endl;
for (auto name : outNames)
std::cout << "- " << name << std::endl;
}
std::vector<Mat> outs; std::vector<Mat> outs;
net.forward(outs, outNames); net.forward(outs, outNames);
@ -307,13 +362,26 @@ TEST_P(DNNTestOpenVINO, models)
ASSERT_FALSE(backendId != DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && backendId != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) << ASSERT_FALSE(backendId != DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && backendId != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) <<
"Inference Engine backend is required"; "Inference Engine backend is required";
#if INF_ENGINE_VER_MAJOR_EQ(2021040000) #if INF_ENGINE_VER_MAJOR_GE(2021030000)
if (targetId == DNN_TARGET_MYRIAD && ( if (targetId == DNN_TARGET_MYRIAD && (false
modelName == "person-detection-retail-0013" || // ncDeviceOpen:1013 Failed to find booted device after boot || modelName == "person-detection-retail-0013" // ncDeviceOpen:1013 Failed to find booted device after boot
modelName == "age-gender-recognition-retail-0013" // ncDeviceOpen:1013 Failed to find booted device after boot || modelName == "age-gender-recognition-retail-0013" // ncDeviceOpen:1013 Failed to find booted device after boot
|| modelName == "face-detection-0105" // get_element_type() must be called on a node with exactly one output
|| modelName == "face-detection-0106" // get_element_type() must be called on a node with exactly one output
|| modelName == "person-vehicle-bike-detection-2004" // 2021.4+: ncDeviceOpen:1013 Failed to find booted device after boot
) )
) )
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION); applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if (targetId == DNN_TARGET_OPENCL && (false
|| modelName == "face-detection-0106" // Operation: 2278 of type ExperimentalDetectronPriorGridGenerator(op::v6) is not supported
)
)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if (targetId == DNN_TARGET_OPENCL_FP16 && (false
|| modelName == "face-detection-0106" // Operation: 2278 of type ExperimentalDetectronPriorGridGenerator(op::v6) is not supported
)
)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif #endif
#if INF_ENGINE_VER_MAJOR_GE(2020020000) #if INF_ENGINE_VER_MAJOR_GE(2020020000)
@ -350,6 +418,8 @@ TEST_P(DNNTestOpenVINO, models)
if (targetId == DNN_TARGET_MYRIAD) if (targetId == DNN_TARGET_MYRIAD)
resetMyriadDevice(); resetMyriadDevice();
EXPECT_NO_THROW(runIE(targetId, xmlPath, binPath, inputsMap, ieOutputsMap)) << "runIE"; EXPECT_NO_THROW(runIE(targetId, xmlPath, binPath, inputsMap, ieOutputsMap)) << "runIE";
if (targetId == DNN_TARGET_MYRIAD)
resetMyriadDevice();
EXPECT_NO_THROW(runCV(backendId, targetId, xmlPath, binPath, inputsMap, cvOutputsMap)) << "runCV"; EXPECT_NO_THROW(runCV(backendId, targetId, xmlPath, binPath, inputsMap, cvOutputsMap)) << "runCV";
double eps = 0; double eps = 0;
@ -357,6 +427,14 @@ TEST_P(DNNTestOpenVINO, models)
if (targetId == DNN_TARGET_CPU && checkHardwareSupport(CV_CPU_AVX_512F)) if (targetId == DNN_TARGET_CPU && checkHardwareSupport(CV_CPU_AVX_512F))
eps = 1e-5; eps = 1e-5;
#endif #endif
#if INF_ENGINE_VER_MAJOR_GE(2021030000)
if (targetId == DNN_TARGET_CPU && modelName == "face-detection-0105")
eps = 2e-4;
#endif
#if INF_ENGINE_VER_MAJOR_GE(2021040000)
if (targetId == DNN_TARGET_CPU && modelName == "person-vehicle-bike-detection-2004")
eps = 1e-6;
#endif
EXPECT_EQ(ieOutputsMap.size(), cvOutputsMap.size()); EXPECT_EQ(ieOutputsMap.size(), cvOutputsMap.size());
for (auto& srcIt : ieOutputsMap) for (auto& srcIt : ieOutputsMap)