opencv/modules/dnn/src/op_inf_engine.hpp
Dmitry Kurtaev 10e1de74d2 Intel Inference Engine deep learning backend (#10608)
* Intel Inference Engine deep learning backend.

* OpenFace network using Inference Engine backend
2018-02-06 11:57:35 +03:00

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3.8 KiB
C++

// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
//
// Copyright (C) 2018, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
#ifndef __OPENCV_DNN_OP_INF_ENGINE_HPP__
#define __OPENCV_DNN_OP_INF_ENGINE_HPP__
#include "precomp.hpp"
#ifdef HAVE_INF_ENGINE
#include <inference_engine.hpp>
#endif // HAVE_INF_ENGINE
namespace cv { namespace dnn {
#ifdef HAVE_INF_ENGINE
class InfEngineBackendNet : public InferenceEngine::ICNNNetwork
{
public:
virtual void Release() noexcept;
virtual InferenceEngine::Precision getPrecision() noexcept;
virtual void getOutputsInfo(InferenceEngine::OutputsDataMap &out) noexcept;
virtual void getInputsInfo(InferenceEngine::InputsDataMap &inputs) noexcept;
virtual InferenceEngine::InputInfo::Ptr getInput(const std::string &inputName) noexcept;
virtual void getName(char *pName, size_t len) noexcept;
virtual size_t layerCount() noexcept;
virtual InferenceEngine::DataPtr& getData(const char *dname) noexcept;
virtual void addLayer(const InferenceEngine::CNNLayerPtr &layer) noexcept;
virtual InferenceEngine::StatusCode addOutput(const std::string &layerName,
size_t outputIndex = 0,
InferenceEngine::ResponseDesc *resp = nullptr) noexcept;
virtual InferenceEngine::StatusCode getLayerByName(const char *layerName,
InferenceEngine::CNNLayerPtr &out,
InferenceEngine::ResponseDesc *resp) noexcept;
virtual void setTargetDevice(InferenceEngine::TargetDevice device) noexcept;
virtual InferenceEngine::TargetDevice getTargetDevice() noexcept;
virtual InferenceEngine::StatusCode setBatchSize(const size_t size) noexcept;
virtual size_t getBatchSize() const noexcept;
void initEngine();
void addBlobs(const std::vector<Ptr<BackendWrapper> >& wrappers);
void forward();
bool isInitialized();
private:
std::vector<InferenceEngine::CNNLayerPtr> layers;
InferenceEngine::InputsDataMap inputs;
InferenceEngine::OutputsDataMap outputs;
InferenceEngine::BlobMap inpBlobs;
InferenceEngine::BlobMap outBlobs;
InferenceEngine::BlobMap allBlobs;
InferenceEngine::InferenceEnginePluginPtr engine;
};
class InfEngineBackendNode : public BackendNode
{
public:
InfEngineBackendNode(const InferenceEngine::CNNLayerPtr& layer);
void connect(std::vector<Ptr<BackendWrapper> >& inputs,
std::vector<Ptr<BackendWrapper> >& outputs);
InferenceEngine::CNNLayerPtr layer;
// Inference Engine network object that allows to obtain the outputs of this layer.
Ptr<InfEngineBackendNet> net;
};
class InfEngineBackendWrapper : public BackendWrapper
{
public:
InfEngineBackendWrapper(int targetId, const Mat& m);
~InfEngineBackendWrapper();
virtual void copyToHost();
virtual void setHostDirty();
InferenceEngine::DataPtr dataPtr;
InferenceEngine::TBlob<float>::Ptr blob;
};
InferenceEngine::TBlob<float>::Ptr wrapToInfEngineBlob(const Mat& m);
InferenceEngine::TBlob<float>::Ptr wrapToInfEngineBlob(const Mat& m, const std::vector<size_t>& shape);
InferenceEngine::DataPtr infEngineDataNode(const Ptr<BackendWrapper>& ptr);
// Fuses convolution weights and biases with channel-wise scales and shifts.
void fuseConvWeights(const std::shared_ptr<InferenceEngine::ConvolutionLayer>& conv,
const Mat& w, const Mat& b = Mat());
#endif // HAVE_INF_ENGINE
bool haveInfEngine();
void forwardInfEngine(Ptr<BackendNode>& node);
}} // namespace dnn, namespace cv
#endif // __OPENCV_DNN_OP_INF_ENGINE_HPP__