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dnn(IE): use HAVE_DNN_IE_NN_BUILDER_2019 for NN Builder API code

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- CMake option: OPENCV_DNN_IE_NN_BUILDER_2019
This commit is contained in:
Alexander Alekhin
2020-03-03 08:01:44 +00:00
parent 4d0f13544d
commit 124bf8339f
32 changed files with 351 additions and 146 deletions
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modules/dnn/src/op_inf_engine.cpp
+42 -29
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@@ -42,8 +42,8 @@ Backend& getInferenceEngineBackendTypeParam()
{
static Backend param = parseInferenceEngineBackendType(
utils::getConfigurationParameterString("OPENCV_DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019_TYPE",
#ifdef HAVE_NGRAPH
CV_DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_API // future: CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH
#ifndef HAVE_DNN_IE_NN_BUILDER_2019
CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH
#else
CV_DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_API
#endif
@@ -69,6 +69,36 @@ cv::String setInferenceEngineBackendType(const cv::String& newBackendType)
CV__DNN_EXPERIMENTAL_NS_END
Mat infEngineBlobToMat(const InferenceEngine::Blob::Ptr& blob)
{
// NOTE: Inference Engine sizes are reversed.
std::vector<size_t> dims = blob->getTensorDesc().getDims();
std::vector<int> size(dims.begin(), dims.end());
auto precision = blob->getTensorDesc().getPrecision();
int type = -1;
switch (precision)
{
case InferenceEngine::Precision::FP32: type = CV_32F; break;
case InferenceEngine::Precision::U8: type = CV_8U; break;
default:
CV_Error(Error::StsNotImplemented, "Unsupported blob precision");
}
return Mat(size, type, (void*)blob->buffer());
}
void infEngineBlobsToMats(const std::vector<InferenceEngine::Blob::Ptr>& blobs,
std::vector<Mat>& mats)
{
mats.resize(blobs.size());
for (int i = 0; i < blobs.size(); ++i)
mats[i] = infEngineBlobToMat(blobs[i]);
}
#ifdef HAVE_DNN_IE_NN_BUILDER_2019
// For networks with input layer which has an empty name, IE generates a name id[some_number].
// OpenCV lets users use an empty input name and to prevent unexpected naming,
// we can use some predefined name.
@@ -556,6 +586,8 @@ void InfEngineBackendWrapper::setHostDirty()
}
#endif // HAVE_DNN_IE_NN_BUILDER_2019
#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2019R1)
static std::map<std::string, InferenceEngine::InferenceEnginePluginPtr>& getSharedPlugins()
{
@@ -686,6 +718,9 @@ static bool detectMyriadX_()
}
#endif // !defined(OPENCV_DNN_IE_VPU_TYPE_DEFAULT)
#ifdef HAVE_DNN_IE_NN_BUILDER_2019
void InfEngineBackendNet::initPlugin(InferenceEngine::CNNNetwork& net)
{
CV_Assert(!isInitialized());
@@ -984,32 +1019,6 @@ void InfEngineBackendNet::forward(const std::vector<Ptr<BackendWrapper> >& outBl
}
}
Mat infEngineBlobToMat(const InferenceEngine::Blob::Ptr& blob)
{
// NOTE: Inference Engine sizes are reversed.
std::vector<size_t> dims = blob->getTensorDesc().getDims();
std::vector<int> size(dims.begin(), dims.end());
auto precision = blob->getTensorDesc().getPrecision();
int type = -1;
switch (precision)
{
case InferenceEngine::Precision::FP32: type = CV_32F; break;
case InferenceEngine::Precision::U8: type = CV_8U; break;
default:
CV_Error(Error::StsNotImplemented, "Unsupported blob precision");
}
return Mat(size, type, (void*)blob->buffer());
}
void infEngineBlobsToMats(const std::vector<InferenceEngine::Blob::Ptr>& blobs,
std::vector<Mat>& mats)
{
mats.resize(blobs.size());
for (int i = 0; i < blobs.size(); ++i)
mats[i] = infEngineBlobToMat(blobs[i]);
}
bool InfEngineBackendLayer::getMemoryShapes(const std::vector<MatShape> &inputs,
const int requiredOutputs,
std::vector<MatShape> &outputs,
@@ -1076,6 +1085,8 @@ void addConstantData(const std::string& name, InferenceEngine::Blob::Ptr data,
#endif
}
#endif // HAVE_DNN_IE_NN_BUILDER_2019
#endif // HAVE_INF_ENGINE
bool haveInfEngine()
@@ -1091,11 +1102,13 @@ void forwardInfEngine(const std::vector<Ptr<BackendWrapper> >& outBlobsWrappers,
Ptr<BackendNode>& node, bool isAsync)
{
CV_Assert(haveInfEngine());
#ifdef HAVE_INF_ENGINE
#ifdef HAVE_DNN_IE_NN_BUILDER_2019
CV_Assert(!node.empty());
Ptr<InfEngineBackendNode> ieNode = node.dynamicCast<InfEngineBackendNode>();
CV_Assert(!ieNode.empty());
ieNode->net->forward(outBlobsWrappers, isAsync);
#else
CV_Error(Error::StsNotImplemented, "This OpenCV version is built without Inference Engine NN Builder API support");
#endif // HAVE_INF_ENGINE
}