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Merge pull request #14241 from alalek:openvino_2019R1

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Alexander Alekhin
2019-04-03 19:26:46 +00:00
parent 4bb6edf176 cafa010389
commit c300070b8a
13 changed files with 126 additions and 48 deletions
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modules/dnn/src/dnn.cpp
+1 -1
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@@ -1636,7 +1636,7 @@ struct Net::Impl
preferableTarget == DNN_TARGET_MYRIAD ||
preferableTarget == DNN_TARGET_FPGA) && !fused)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
for (const std::string& name : {"weights", "biases"})
{
auto it = ieNode->layer.getParameters().find(name);
modules/dnn/src/layers/normalize_bbox_layer.cpp
+1 -1
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@@ -290,7 +290,7 @@ public:
weights = wrapToInfEngineBlob(blobs[0], {(size_t)numChannels}, InferenceEngine::Layout::C);
l.getParameters()["channel_shared"] = blobs[0].total() == 1;
}
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
l.getParameters()["weights"] = weights;
#else
l.addConstantData("weights", weights);
modules/dnn/src/op_inf_engine.cpp
+4 -4
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@@ -130,7 +130,7 @@ void InfEngineBackendNet::init(int targetId)
for (int id : unconnectedLayersIds)
{
InferenceEngine::Builder::OutputLayer outLayer("myconv1");
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// Inference Engine determines network precision by ports.
InferenceEngine::Precision p = (targetId == DNN_TARGET_MYRIAD ||
targetId == DNN_TARGET_OPENCL_FP16) ?
@@ -188,7 +188,7 @@ void InfEngineBackendNet::init(int targetId)
void InfEngineBackendNet::addLayer(InferenceEngine::Builder::Layer& layer)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// Add weights to network and connect them after input blobs.
std::map<std::string, InferenceEngine::Parameter>& params = layer.getParameters();
std::vector<int> blobsIds;
@@ -229,7 +229,7 @@ void InfEngineBackendNet::addLayer(InferenceEngine::Builder::Layer& layer)
CV_Assert(layers.insert({layerName, id}).second);
unconnectedLayersIds.insert(id);
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// By default, all the weights are connected to last ports ids.
for (int i = 0; i < blobsIds.size(); ++i)
{
@@ -903,7 +903,7 @@ InferenceEngine::Blob::Ptr convertFp16(const InferenceEngine::Blob::Ptr& blob)
void addConstantData(const std::string& name, InferenceEngine::Blob::Ptr data,
InferenceEngine::Builder::Layer& l)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
l.getParameters()[name] = data;
#else
l.addConstantData(name, data);
modules/dnn/src/op_inf_engine.hpp
+3 -2
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@@ -27,10 +27,11 @@
#define INF_ENGINE_RELEASE_2018R3 2018030000
#define INF_ENGINE_RELEASE_2018R4 2018040000
#define INF_ENGINE_RELEASE_2018R5 2018050000
#define INF_ENGINE_RELEASE_2019R1 2019010000
#ifndef INF_ENGINE_RELEASE
#warning("IE version have not been provided via command-line. Using 2018R5 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2018R5
#warning("IE version have not been provided via command-line. Using 2019R1 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2019R1
#endif
#define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))