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Enable FastNeuralStyle and OpenFace networks with IE backend

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This commit is contained in:
Dmitry Kurtaev
2018-06-09 15:37:04 +03:00
parent 8221f57c26
commit 2c291bc2fb
8 changed files with 119 additions and 12 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+4 -3
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@@ -81,9 +81,10 @@ public:
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
return backendId == DNN_BACKEND_OPENCV ||
backendId == DNN_BACKEND_HALIDE && haveHalide() ||
backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
return preferableTarget != DNN_TARGET_MYRIAD || type != "Deconvolution" || adjustPad == Size();
else
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
}
void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
modules/dnn/src/layers/elementwise_layers.cpp
+53 -3
View File
@@ -115,9 +115,7 @@ public:
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
return backendId == DNN_BACKEND_OPENCV ||
backendId == DNN_BACKEND_HALIDE && haveHalide() ||
backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
return func.supportBackend(backendId, this->preferableTarget);
}
virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node) CV_OVERRIDE
@@ -238,6 +236,12 @@ struct ReLUFunctor
explicit ReLUFunctor(float slope_=1.f) : slope(slope_) {}
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE ||
backendId == DNN_BACKEND_INFERENCE_ENGINE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
float s = slope;
@@ -353,6 +357,12 @@ struct ReLU6Functor
CV_Assert(minValue <= maxValue);
}
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE ||
backendId == DNN_BACKEND_INFERENCE_ENGINE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
for( int cn = cn0; cn < cn1; cn++, srcptr += planeSize, dstptr += planeSize )
@@ -445,6 +455,12 @@ struct TanHFunctor
{
typedef TanHLayer Layer;
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE ||
backendId == DNN_BACKEND_INFERENCE_ENGINE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
for( int cn = cn0; cn < cn1; cn++, srcptr += planeSize, dstptr += planeSize )
@@ -509,6 +525,12 @@ struct SigmoidFunctor
{
typedef SigmoidLayer Layer;
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE ||
backendId == DNN_BACKEND_INFERENCE_ENGINE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
for( int cn = cn0; cn < cn1; cn++, srcptr += planeSize, dstptr += planeSize )
@@ -575,6 +597,11 @@ struct ELUFunctor
explicit ELUFunctor() {}
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
for( int cn = cn0; cn < cn1; cn++, srcptr += planeSize, dstptr += planeSize )
@@ -638,6 +665,11 @@ struct AbsValFunctor
{
typedef AbsLayer Layer;
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
for( int cn = cn0; cn < cn1; cn++, srcptr += planeSize, dstptr += planeSize )
@@ -701,6 +733,11 @@ struct BNLLFunctor
{
typedef BNLLLayer Layer;
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
for( int cn = cn0; cn < cn1; cn++, srcptr += planeSize, dstptr += planeSize )
@@ -751,6 +788,14 @@ struct PowerFunctor
explicit PowerFunctor(float power_ = 1.f, float scale_ = 1.f, float shift_ = 0.f)
: power(power_), scale(scale_), shift(shift_) {}
bool supportBackend(int backendId, int targetId)
{
if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
return (targetId != DNN_TARGET_OPENCL && targetId != DNN_TARGET_OPENCL_FP16) || power == 1.0;
else
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
float a = scale, b = shift, p = power;
@@ -853,6 +898,11 @@ struct ChannelsPReLUFunctor
scale_umat = scale.getUMat(ACCESS_READ);
}
bool supportBackend(int backendId, int)
{
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
CV_Assert(scale.isContinuous() && scale.type() == CV_32F);
modules/dnn/src/layers/resize_layer.cpp
+4 -2
View File
@@ -53,8 +53,10 @@ public:
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
return backendId == DNN_BACKEND_OPENCV ||
backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine() && interpolation == "nearest";
if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
return interpolation == "nearest" && preferableTarget != DNN_TARGET_MYRIAD;
else
return backendId == DNN_BACKEND_OPENCV;
}
virtual void finalize(const std::vector<Mat*>& inputs, std::vector<Mat> &outputs) CV_OVERRIDE
modules/dnn/src/layers/slice_layer.cpp
+30
View File
@@ -41,6 +41,7 @@
//M*/
#include "../precomp.hpp"
#include "../op_inf_engine.hpp"
#include "layers_common.hpp"
#include <opencv2/dnn/shape_utils.hpp>
@@ -107,6 +108,12 @@ public:
}
}
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
return backendId == DNN_BACKEND_OPENCV ||
backendId == DNN_BACKEND_INFERENCE_ENGINE && sliceRanges.size() == 1;
}
bool getMemoryShapes(const std::vector<MatShape> &inputs,
const int requiredOutputs,
std::vector<MatShape> &outputs,
@@ -247,6 +254,29 @@ public:
inpMat(sliceRanges[i]).copyTo(outputs[i]);
}
}
virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >& inputs) CV_OVERRIDE
{
#ifdef HAVE_INF_ENGINE
InferenceEngine::DataPtr input = infEngineDataNode(inputs[0]);
InferenceEngine::LayerParams lp;
lp.name = name;
lp.type = "Crop";
lp.precision = InferenceEngine::Precision::FP32;
std::shared_ptr<InferenceEngine::CropLayer> ieLayer(new InferenceEngine::CropLayer(lp));
CV_Assert(sliceRanges.size() == 1);
for (int i = sliceRanges[0].size() - 1; i >= 0; --i)
{
ieLayer->axis.push_back(i);
ieLayer->offset.push_back(sliceRanges[0][i].start);
ieLayer->dim.push_back(sliceRanges[0][i].end - sliceRanges[0][i].start);
}
return Ptr<BackendNode>(new InfEngineBackendNode(ieLayer));
#endif // HAVE_INF_ENGINE
return Ptr<BackendNode>();
}
};
Ptr<SliceLayer> SliceLayer::create(const LayerParams& params)