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// 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) 2018-2019, 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 "opencv2/core/cvdef.h"
#include "opencv2/core/cvstd.hpp"
#include "opencv2/dnn.hpp"
#include "opencv2/core/async.hpp"
#include "opencv2/core/detail/async_promise.hpp"
#include "opencv2/dnn/utils/inference_engine.hpp"
#ifdef HAVE_INF_ENGINE
#define INF_ENGINE_RELEASE_2018R5 2018050000
#define INF_ENGINE_RELEASE_2019R1 2019010000
#define INF_ENGINE_RELEASE_2019R2 2019020000
#define INF_ENGINE_RELEASE_2019R3 2019030000
#ifndef INF_ENGINE_RELEASE
#warning("IE version have not been provided via command-line. Using 2019R3 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2019R3
#endif
#define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))
#define INF_ENGINE_VER_MAJOR_GE(ver) (((INF_ENGINE_RELEASE) / 10000) >= ((ver) / 10000))
#define INF_ENGINE_VER_MAJOR_LT(ver) (((INF_ENGINE_RELEASE) / 10000) < ((ver) / 10000))
#define INF_ENGINE_VER_MAJOR_LE(ver) (((INF_ENGINE_RELEASE) / 10000) <= ((ver) / 10000))
#define INF_ENGINE_VER_MAJOR_EQ(ver) (((INF_ENGINE_RELEASE) / 10000) == ((ver) / 10000))
#if defined(__GNUC__) && __GNUC__ >= 5
//#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wsuggest-override"
#endif
//#define INFERENCE_ENGINE_DEPRECATED // turn off deprecation warnings from IE
//there is no way to suppress warnings from IE only at this moment, so we are forced to suppress warnings globally
#if defined(__GNUC__)
#pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#endif
#ifdef _MSC_VER
#pragma warning(disable: 4996) // was declared deprecated
#endif
#if defined(__GNUC__)
#pragma GCC visibility push(default)
#endif
#include <inference_engine.hpp>
#include <ie_builders.hpp>
#if defined(__GNUC__)
#pragma GCC visibility pop
#endif
#if defined(__GNUC__) && __GNUC__ >= 5
//#pragma GCC diagnostic pop
#endif
#endif // HAVE_INF_ENGINE
namespace cv { namespace dnn {
#ifdef HAVE_INF_ENGINE
class InfEngineBackendNet
{
public:
InfEngineBackendNet();
InfEngineBackendNet(InferenceEngine::CNNNetwork& net);
void addLayer(InferenceEngine::Builder::Layer& layer);
void addOutput(const std::string& name);
void connect(const std::vector<Ptr<BackendWrapper> >& inputs,
const std::vector<Ptr<BackendWrapper> >& outputs,
const std::string& layerName);
bool isInitialized();
void init(int targetId);
void forward(const std::vector<Ptr<BackendWrapper> >& outBlobsWrappers,
bool isAsync);
void initPlugin(InferenceEngine::CNNNetwork& net);
void addBlobs(const std::vector<cv::Ptr<BackendWrapper> >& ptrs);
private:
InferenceEngine::Builder::Network netBuilder;
InferenceEngine::ExecutableNetwork netExec;
InferenceEngine::BlobMap allBlobs;
std::string device_name;
#if INF_ENGINE_VER_MAJOR_LE(2019010000)
InferenceEngine::InferenceEnginePluginPtr enginePtr;
InferenceEngine::InferencePlugin plugin;
#else
bool isInit = false;
#endif
struct InfEngineReqWrapper
{
InfEngineReqWrapper() : isReady(true) {}
void makePromises(const std::vector<Ptr<BackendWrapper> >& outs);
InferenceEngine::InferRequest req;
std::vector<cv::AsyncPromise> outProms;
std::vector<std::string> outsNames;
bool isReady;
};
std::vector<Ptr<InfEngineReqWrapper> > infRequests;
InferenceEngine::CNNNetwork cnn;
bool hasNetOwner;
std::map<std::string, int> layers;
std::vector<std::string> requestedOutputs;
std::set<int> unconnectedLayersIds;
};
class InfEngineBackendNode : public BackendNode
{
public:
InfEngineBackendNode(const InferenceEngine::Builder::Layer& layer);
InfEngineBackendNode(Ptr<Layer>& layer, std::vector<Mat*>& inputs,
std::vector<Mat>& outputs, std::vector<Mat>& internals);
void connect(std::vector<Ptr<BackendWrapper> >& inputs,
std::vector<Ptr<BackendWrapper> >& outputs);
// Inference Engine network object that allows to obtain the outputs of this layer.
InferenceEngine::Builder::Layer layer;
Ptr<InfEngineBackendNet> net;
// CPU fallback in case of unsupported Inference Engine layer.
Ptr<dnn::Layer> cvLayer;
};
class InfEngineBackendWrapper : public BackendWrapper
{
public:
InfEngineBackendWrapper(int targetId, const Mat& m);
InfEngineBackendWrapper(Ptr<BackendWrapper> wrapper);
~InfEngineBackendWrapper();
static Ptr<BackendWrapper> create(Ptr<BackendWrapper> wrapper);
virtual void copyToHost() CV_OVERRIDE;
virtual void setHostDirty() CV_OVERRIDE;
InferenceEngine::DataPtr dataPtr;
InferenceEngine::Blob::Ptr blob;
AsyncArray futureMat;
};
InferenceEngine::Blob::Ptr wrapToInfEngineBlob(const Mat& m, InferenceEngine::Layout layout = InferenceEngine::Layout::ANY);
InferenceEngine::Blob::Ptr wrapToInfEngineBlob(const Mat& m, const std::vector<size_t>& shape, InferenceEngine::Layout layout);
InferenceEngine::DataPtr infEngineDataNode(const Ptr<BackendWrapper>& ptr);
Mat infEngineBlobToMat(const InferenceEngine::Blob::Ptr& blob);
void infEngineBlobsToMats(const std::vector<InferenceEngine::Blob::Ptr>& blobs,
std::vector<Mat>& mats);
// Convert Inference Engine blob with FP32 precision to FP16 precision.
// Allocates memory for a new blob.
InferenceEngine::Blob::Ptr convertFp16(const InferenceEngine::Blob::Ptr& blob);
void addConstantData(const std::string& name, InferenceEngine::Blob::Ptr data, InferenceEngine::Builder::Layer& l);
// This is a fake class to run networks from Model Optimizer. Objects of that
// class simulate responses of layers are imported by OpenCV and supported by
// Inference Engine. The main difference is that they do not perform forward pass.
class InfEngineBackendLayer : public Layer
{
public:
InfEngineBackendLayer(const InferenceEngine::CNNNetwork &t_net_) : t_net(t_net_) {};
virtual bool getMemoryShapes(const std::vector<MatShape> &inputs,
const int requiredOutputs,
std::vector<MatShape> &outputs,
std::vector<MatShape> &internals) const CV_OVERRIDE;
virtual void forward(InputArrayOfArrays inputs, OutputArrayOfArrays outputs,
OutputArrayOfArrays internals) CV_OVERRIDE;
virtual bool supportBackend(int backendId) CV_OVERRIDE;
private:
InferenceEngine::CNNNetwork t_net;
};
CV__DNN_INLINE_NS_BEGIN
bool isMyriadX();
CV__DNN_INLINE_NS_END
#endif // HAVE_INF_ENGINE
bool haveInfEngine();
void forwardInfEngine(const std::vector<Ptr<BackendWrapper> >& outBlobsWrappers,
Ptr<BackendNode>& node, bool isAsync);
}} // namespace dnn, namespace cv
#endif // __OPENCV_DNN_OP_INF_ENGINE_HPP__