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Merge pull request #20325 from alalek:dnn_openvino_2021.4.0

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pull/20339/head^2
Alexander Alekhin 4 years ago
parent 947e06a860 f2057ce1ab
commit 24983f62e2
6 changed files with 63 additions and 25 deletions
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  1. 4
      cmake/OpenCVDetectInferenceEngine.cmake
  2. 51
      modules/dnn/src/ie_ngraph.cpp
  3. 5
      modules/dnn/src/op_inf_engine.hpp
  4. 10
      modules/dnn/test/test_backends.cpp
  5. 9
      modules/dnn/test/test_ie_models.cpp
  6. 9
      modules/dnn/test/test_torch_importer.cpp

4
cmake/OpenCVDetectInferenceEngine.cmake
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@ -141,9 +141,9 @@ endif()
if(INF_ENGINE_TARGET)
if(NOT INF_ENGINE_RELEASE)
message(WARNING "InferenceEngine version has not been set, 2021.3 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
message(WARNING "InferenceEngine version has not been set, 2021.4 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
endif()
set(INF_ENGINE_RELEASE "2021030000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2020.1.0.2 -> 2020010002)")
set(INF_ENGINE_RELEASE "2021040000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2020.1.0.2 -> 2020010002)")
set_target_properties(${INF_ENGINE_TARGET} PROPERTIES
INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}"
)

51
modules/dnn/src/ie_ngraph.cpp
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@ -654,7 +654,11 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net)
try
{
InferenceEngine::IExtensionPtr extension =
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
std::make_shared<InferenceEngine::Extension>(libName);
#else
InferenceEngine::make_so_pointer<InferenceEngine::IExtension>(libName);
#endif
ie.AddExtension(extension, "CPU");
CV_LOG_INFO(NULL, "DNN-IE: Loaded extension plugin: " << libName);
@ -1002,35 +1006,54 @@ void InfEngineNgraphNet::forward(const std::vector<Ptr<BackendWrapper> >& outBlo
reqWrapper->req.SetInput(inpBlobs);
reqWrapper->req.SetOutput(outBlobs);
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
InferenceEngine::InferRequest infRequest = reqWrapper->req;
NgraphReqWrapper* wrapperPtr = reqWrapper.get();
CV_Assert(wrapperPtr && "Internal error");
#else
InferenceEngine::IInferRequest::Ptr infRequestPtr = reqWrapper->req;
infRequestPtr->SetUserData(reqWrapper.get(), 0);
CV_Assert(infRequestPtr);
InferenceEngine::IInferRequest& infRequest = *infRequestPtr.get();
infRequest.SetUserData(reqWrapper.get(), 0);
#endif
infRequestPtr->SetCompletionCallback(
[](InferenceEngine::IInferRequest::Ptr request, InferenceEngine::StatusCode status)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
// do NOT capture 'reqWrapper' (smart ptr) in the lambda callback
infRequest.SetCompletionCallback<std::function<void(InferenceEngine::InferRequest, InferenceEngine::StatusCode)>>(
[wrapperPtr](InferenceEngine::InferRequest /*request*/, InferenceEngine::StatusCode status)
#else
infRequest.SetCompletionCallback(
[](InferenceEngine::IInferRequest::Ptr requestPtr, InferenceEngine::StatusCode status)
#endif
{
CV_LOG_DEBUG(NULL, "DNN(nGraph): completionCallback(" << (int)status << ")");
#if !INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
CV_Assert(requestPtr);
InferenceEngine::IInferRequest& request = *requestPtr.get();
NgraphReqWrapper* wrapper;
request->GetUserData((void**)&wrapper, 0);
CV_Assert(wrapper && "Internal error");
NgraphReqWrapper* wrapperPtr;
request.GetUserData((void**)&wrapperPtr, 0);
CV_Assert(wrapperPtr && "Internal error");
#endif
NgraphReqWrapper& wrapper = *wrapperPtr;
size_t processedOutputs = 0;
try
{
for (; processedOutputs < wrapper->outProms.size(); ++processedOutputs)
for (; processedOutputs < wrapper.outProms.size(); ++processedOutputs)
{
const std::string& name = wrapper->outsNames[processedOutputs];
Mat m = ngraphBlobToMat(wrapper->req.GetBlob(name));
const std::string& name = wrapper.outsNames[processedOutputs];
Mat m = ngraphBlobToMat(wrapper.req.GetBlob(name));
try
{
CV_Assert(status == InferenceEngine::StatusCode::OK);
wrapper->outProms[processedOutputs].setValue(m.clone());
wrapper.outProms[processedOutputs].setValue(m.clone());
}
catch (...)
{
try {
wrapper->outProms[processedOutputs].setException(std::current_exception());
wrapper.outProms[processedOutputs].setException(std::current_exception());
} catch(...) {
CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
}
@ -1040,16 +1063,16 @@ void InfEngineNgraphNet::forward(const std::vector<Ptr<BackendWrapper> >& outBlo
catch (...)
{
std::exception_ptr e = std::current_exception();
for (; processedOutputs < wrapper->outProms.size(); ++processedOutputs)
for (; processedOutputs < wrapper.outProms.size(); ++processedOutputs)
{
try {
wrapper->outProms[processedOutputs].setException(e);
wrapper.outProms[processedOutputs].setException(e);
} catch(...) {
CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
}
}
}
wrapper->isReady = true;
wrapper.isReady = true;
}
);
}

5
modules/dnn/src/op_inf_engine.hpp
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@ -30,10 +30,11 @@
#define INF_ENGINE_RELEASE_2021_1 2021010000
#define INF_ENGINE_RELEASE_2021_2 2021020000
#define INF_ENGINE_RELEASE_2021_3 2021030000
#define INF_ENGINE_RELEASE_2021_4 2021040000
#ifndef INF_ENGINE_RELEASE
#warning("IE version have not been provided via command-line. Using 2021.3 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2021_3
#warning("IE version have not been provided via command-line. Using 2021.4 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2021_4
#endif
#define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))

10
modules/dnn/test/test_backends.cpp
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@ -196,7 +196,7 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe)
Mat inp = blobFromImage(sample, 1.0f / 127.5, Size(300, 300), Scalar(127.5, 127.5, 127.5), false);
float diffScores = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 1.5e-2 : 0.0;
float diffSquares = (target == DNN_TARGET_MYRIAD) ? 0.063 : 0.0;
float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.252 : FLT_MIN;
float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.262 : FLT_MIN;
processNet("dnn/MobileNetSSD_deploy.caffemodel", "dnn/MobileNetSSD_deploy.prototxt",
inp, "detection_out", "", diffScores, diffSquares, detectionConfThresh);
expectNoFallbacksFromIE(net);
@ -301,8 +301,8 @@ TEST_P(DNNTestNetwork, OpenPose_pose_coco)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.0056 : 0.0;
const float lInf = (target == DNN_TARGET_MYRIAD) ? 0.072 : 0.0;
const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.009 : 0.0;
const float lInf = (target == DNN_TARGET_MYRIAD) ? 0.09 : 0.0;
processNet("dnn/openpose_pose_coco.caffemodel", "dnn/openpose_pose_coco.prototxt",
Size(46, 46), "", "", l1, lInf);
expectNoFallbacksFromIE(net);
@ -321,8 +321,8 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi)
#endif
// output range: [-0.001, 0.97]
const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.012 : 0.0;
const float lInf = (target == DNN_TARGET_MYRIAD || target == DNN_TARGET_OPENCL_FP16) ? 0.16 : 0.0;
const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.02 : 0.0;
const float lInf = (target == DNN_TARGET_MYRIAD || target == DNN_TARGET_OPENCL_FP16) ? 0.2 : 0.0;
processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi.prototxt",
Size(46, 46), "", "", l1, lInf);
expectNoFallbacksFromIE(net);

9
modules/dnn/test/test_ie_models.cpp
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@ -288,6 +288,15 @@ TEST_P(DNNTestOpenVINO, models)
ASSERT_FALSE(backendId != DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && backendId != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) <<
"Inference Engine backend is required";
#if INF_ENGINE_VER_MAJOR_EQ(2021040000)
if (targetId == DNN_TARGET_MYRIAD && (
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
)
)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
#if INF_ENGINE_VER_MAJOR_GE(2020020000)
if (targetId == DNN_TARGET_MYRIAD && backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
{

9
modules/dnn/test/test_torch_importer.cpp
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@ -254,9 +254,14 @@ TEST_P(Test_Torch_layers, net_padding)
TEST_P(Test_Torch_layers, net_non_spatial)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000)
#if defined(INF_ENGINE_RELEASE) && ( \
INF_ENGINE_VER_MAJOR_EQ(2021030000) || \
INF_ENGINE_VER_MAJOR_EQ(2021040000) \
)
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); // crash
// 2021.3: crash
// 2021.4: [ GENERAL_ERROR ] AssertionFailed: !out.networkInputs.empty()
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
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_NGRAPH); // exception
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16)

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