mirror of
https://github.com/opencv/opencv.git
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386 lines
12 KiB
C++
386 lines
12 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2018-2019 Intel Corporation
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#ifndef OPENCV_GAPI_GCPUKERNEL_HPP
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#define OPENCV_GAPI_GCPUKERNEL_HPP
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#include <functional>
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#include <unordered_map>
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#include <utility>
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#include <vector>
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#include <opencv2/core/mat.hpp>
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#include <opencv2/gapi/gcommon.hpp>
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#include <opencv2/gapi/gkernel.hpp>
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#include <opencv2/gapi/garg.hpp>
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#include <opencv2/gapi/own/convert.hpp> //to_ocv
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#include <opencv2/gapi/util/compiler_hints.hpp> //suppress_unused_warning
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#include <opencv2/gapi/util/util.hpp>
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// FIXME: namespace scheme for backends?
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namespace cv {
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namespace gimpl
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{
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// Forward-declare an internal class
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class GCPUExecutable;
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namespace render
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{
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namespace ocv
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{
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class GRenderExecutable;
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}
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}
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} // namespace gimpl
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namespace gapi
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{
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namespace cpu
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{
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/**
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* \addtogroup gapi_std_backends
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* @{
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*
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* @brief G-API backends available in this OpenCV version
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*
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* G-API backends play a corner stone role in G-API execution
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* stack. Every backend is hardware-oriented and thus can run its
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* kernels efficiently on the target platform.
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*
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* Backends are usually "black boxes" for G-API users -- on the API
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* side, all backends are represented as different objects of the
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* same class cv::gapi::GBackend.
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* User can manipulate with backends by specifying which kernels to use.
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*
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* @sa @ref gapi_hld
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*/
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/**
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* @brief Get a reference to CPU (OpenCV) backend.
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*
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* This is the default backend in G-API at the moment, providing
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* broader functional coverage but losing some graph model
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* advantages. Provided mostly for reference and prototyping
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* purposes.
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*
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* @sa gapi_std_backends
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*/
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GAPI_EXPORTS cv::gapi::GBackend backend();
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/** @} */
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class GOCVFunctor;
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//! @cond IGNORED
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template<typename K, typename Callable>
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GOCVFunctor ocv_kernel(const Callable& c);
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template<typename K, typename Callable>
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GOCVFunctor ocv_kernel(Callable& c);
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//! @endcond
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} // namespace cpu
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} // namespace gapi
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// Represents arguments which are passed to a wrapped CPU function
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// FIXME: put into detail?
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class GAPI_EXPORTS GCPUContext
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{
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public:
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// Generic accessor API
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template<typename T>
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const T& inArg(int input) { return m_args.at(input).get<T>(); }
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// Syntax sugar
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const cv::gapi::own::Mat& inMat(int input);
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cv::gapi::own::Mat& outMatR(int output); // FIXME: Avoid cv::gapi::own::Mat m = ctx.outMatR()
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const cv::Scalar& inVal(int input);
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cv::Scalar& outValR(int output); // FIXME: Avoid cv::Scalar s = ctx.outValR()
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template<typename T> std::vector<T>& outVecR(int output) // FIXME: the same issue
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{
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return outVecRef(output).wref<T>();
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}
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template<typename T> T& outOpaqueR(int output) // FIXME: the same issue
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{
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return outOpaqueRef(output).wref<T>();
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}
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protected:
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detail::VectorRef& outVecRef(int output);
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detail::OpaqueRef& outOpaqueRef(int output);
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std::vector<GArg> m_args;
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//FIXME: avoid conversion of arguments from internal representation to OpenCV one on each call
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//to OCV kernel. (This can be achieved by a two single time conversions in GCPUExecutable::run,
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//once on enter for input and output arguments, and once before return for output arguments only
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std::unordered_map<std::size_t, GRunArgP> m_results;
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friend class gimpl::GCPUExecutable;
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friend class gimpl::render::ocv::GRenderExecutable;
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};
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class GAPI_EXPORTS GCPUKernel
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{
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public:
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// This function is kernel's execution entry point (does the processing work)
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using F = std::function<void(GCPUContext &)>;
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GCPUKernel();
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explicit GCPUKernel(const F& f);
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void apply(GCPUContext &ctx);
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protected:
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F m_f;
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};
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// FIXME: This is an ugly ad-hoc implementation. TODO: refactor
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namespace detail
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{
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template<class T> struct get_in;
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template<> struct get_in<cv::GMat>
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{
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static cv::Mat get(GCPUContext &ctx, int idx) { return to_ocv(ctx.inMat(idx)); }
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};
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template<> struct get_in<cv::GMatP>
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{
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static cv::Mat get(GCPUContext &ctx, int idx) { return get_in<cv::GMat>::get(ctx, idx); }
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};
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template<> struct get_in<cv::GFrame>
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{
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static cv::Mat get(GCPUContext &ctx, int idx) { return get_in<cv::GMat>::get(ctx, idx); }
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};
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template<> struct get_in<cv::GScalar>
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{
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static cv::Scalar get(GCPUContext &ctx, int idx) { return ctx.inVal(idx); }
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};
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template<typename U> struct get_in<cv::GArray<U> >
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{
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static const std::vector<U>& get(GCPUContext &ctx, int idx) { return ctx.inArg<VectorRef>(idx).rref<U>(); }
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};
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template<typename U> struct get_in<cv::GOpaque<U> >
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{
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static const U& get(GCPUContext &ctx, int idx) { return ctx.inArg<OpaqueRef>(idx).rref<U>(); }
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};
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//FIXME(dm): GArray<Mat>/GArray<GMat> conversion should be done more gracefully in the system
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template<> struct get_in<cv::GArray<cv::GMat> >: public get_in<cv::GArray<cv::Mat> >
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{
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};
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//FIXME(dm): GArray<Scalar>/GArray<GScalar> conversion should be done more gracefully in the system
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template<> struct get_in<cv::GArray<cv::GScalar> >: public get_in<cv::GArray<cv::Scalar> >
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{
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};
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//FIXME(dm): GOpaque<Mat>/GOpaque<GMat> conversion should be done more gracefully in the system
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template<> struct get_in<cv::GOpaque<cv::GMat> >: public get_in<cv::GOpaque<cv::Mat> >
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{
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};
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//FIXME(dm): GOpaque<Scalar>/GOpaque<GScalar> conversion should be done more gracefully in the system
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template<> struct get_in<cv::GOpaque<cv::GScalar> >: public get_in<cv::GOpaque<cv::Mat> >
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{
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};
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template<class T> struct get_in
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{
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static T get(GCPUContext &ctx, int idx) { return ctx.inArg<T>(idx); }
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};
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struct tracked_cv_mat{
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tracked_cv_mat(cv::gapi::own::Mat& m) : r{to_ocv(m)}, original_data{m.data} {}
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cv::Mat r;
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uchar* original_data;
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operator cv::Mat& (){ return r;}
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void validate() const{
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if (r.data != original_data)
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{
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util::throw_error
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(std::logic_error
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("OpenCV kernel output parameter was reallocated. \n"
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"Incorrect meta data was provided ?"));
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}
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}
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};
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template<typename... Outputs>
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void postprocess(Outputs&... outs)
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{
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struct
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{
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void operator()(tracked_cv_mat* bm) { bm->validate(); }
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void operator()(...) { }
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} validate;
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//dummy array to unfold parameter pack
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int dummy[] = { 0, (validate(&outs), 0)... };
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cv::util::suppress_unused_warning(dummy);
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}
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template<class T> struct get_out;
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template<> struct get_out<cv::GMat>
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{
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static tracked_cv_mat get(GCPUContext &ctx, int idx)
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{
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auto& r = ctx.outMatR(idx);
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return {r};
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}
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};
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template<> struct get_out<cv::GMatP>
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{
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static tracked_cv_mat get(GCPUContext &ctx, int idx)
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{
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return get_out<cv::GMat>::get(ctx, idx);
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}
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};
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template<> struct get_out<cv::GScalar>
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{
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static cv::Scalar& get(GCPUContext &ctx, int idx)
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{
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return ctx.outValR(idx);
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}
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};
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template<typename U> struct get_out<cv::GArray<U>>
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{
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static std::vector<U>& get(GCPUContext &ctx, int idx)
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{
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return ctx.outVecR<U>(idx);
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}
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};
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template<typename U> struct get_out<cv::GOpaque<U>>
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{
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static U& get(GCPUContext &ctx, int idx)
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{
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return ctx.outOpaqueR<U>(idx);
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}
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};
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template<typename, typename, typename>
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struct OCVCallHelper;
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// FIXME: probably can be simplified with std::apply or analogue.
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template<typename Impl, typename... Ins, typename... Outs>
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struct OCVCallHelper<Impl, std::tuple<Ins...>, std::tuple<Outs...> >
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{
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template<typename... Inputs>
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struct call_and_postprocess
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{
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template<typename... Outputs>
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static void call(Inputs&&... ins, Outputs&&... outs)
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{
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//not using a std::forward on outs is deliberate in order to
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//cause compilation error, by trying to bind rvalue references to lvalue references
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Impl::run(std::forward<Inputs>(ins)..., outs...);
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postprocess(outs...);
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}
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template<typename... Outputs>
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static void call(Impl& impl, Inputs&&... ins, Outputs&&... outs)
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{
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impl(std::forward<Inputs>(ins)..., outs...);
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}
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};
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template<int... IIs, int... OIs>
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static void call_impl(GCPUContext &ctx, detail::Seq<IIs...>, detail::Seq<OIs...>)
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{
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//Make sure that OpenCV kernels do not reallocate memory for output parameters
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//by comparing it's state (data ptr) before and after the call.
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//This is done by converting each output Mat into tracked_cv_mat object, and binding
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//them to parameters of ad-hoc function
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//Convert own::Scalar to cv::Scalar before call kernel and run kernel
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//convert cv::Scalar to own::Scalar after call kernel and write back results
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call_and_postprocess<decltype(get_in<Ins>::get(ctx, IIs))...>
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::call(get_in<Ins>::get(ctx, IIs)...,
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get_out<Outs>::get(ctx, OIs)...);
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}
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template<int... IIs, int... OIs>
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static void call_impl(cv::GCPUContext &ctx, Impl& impl, detail::Seq<IIs...>, detail::Seq<OIs...>)
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{
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call_and_postprocess<decltype(cv::detail::get_in<Ins>::get(ctx, IIs))...>
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::call(impl, cv::detail::get_in<Ins>::get(ctx, IIs)...,
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cv::detail::get_out<Outs>::get(ctx, OIs)...);
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}
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static void call(GCPUContext &ctx)
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{
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call_impl(ctx,
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typename detail::MkSeq<sizeof...(Ins)>::type(),
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typename detail::MkSeq<sizeof...(Outs)>::type());
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}
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// NB: Same as call but calling the object
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// This necessary for kernel implementations that have a state
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// and are represented as an object
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static void callFunctor(cv::GCPUContext &ctx, Impl& impl)
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{
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call_impl(ctx, impl,
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typename detail::MkSeq<sizeof...(Ins)>::type(),
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typename detail::MkSeq<sizeof...(Outs)>::type());
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}
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};
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} // namespace detail
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template<class Impl, class K>
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class GCPUKernelImpl: public cv::detail::OCVCallHelper<Impl, typename K::InArgs, typename K::OutArgs>,
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public cv::detail::KernelTag
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{
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using P = detail::OCVCallHelper<Impl, typename K::InArgs, typename K::OutArgs>;
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public:
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using API = K;
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static cv::gapi::GBackend backend() { return cv::gapi::cpu::backend(); }
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static cv::GCPUKernel kernel() { return GCPUKernel(&P::call); }
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};
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#define GAPI_OCV_KERNEL(Name, API) struct Name: public cv::GCPUKernelImpl<Name, API>
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class gapi::cpu::GOCVFunctor : public gapi::GFunctor
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{
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public:
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using Impl = std::function<void(GCPUContext &)>;
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GOCVFunctor(const char* id, const Impl& impl)
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: gapi::GFunctor(id), impl_{GCPUKernel(impl)}
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{
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}
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GKernelImpl impl() const override { return impl_; }
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gapi::GBackend backend() const override { return gapi::cpu::backend(); }
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private:
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GKernelImpl impl_;
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};
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//! @cond IGNORED
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template<typename K, typename Callable>
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gapi::cpu::GOCVFunctor gapi::cpu::ocv_kernel(Callable& c)
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{
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using P = detail::OCVCallHelper<Callable, typename K::InArgs, typename K::OutArgs>;
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return GOCVFunctor(K::id(), std::bind(&P::callFunctor, std::placeholders::_1, std::ref(c)));
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}
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template<typename K, typename Callable>
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gapi::cpu::GOCVFunctor gapi::cpu::ocv_kernel(const Callable& c)
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{
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using P = detail::OCVCallHelper<Callable, typename K::InArgs, typename K::OutArgs>;
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return GOCVFunctor(K::id(), std::bind(&P::callFunctor, std::placeholders::_1, c));
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}
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//! @endcond
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} // namespace cv
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#endif // OPENCV_GAPI_GCPUKERNEL_HPP
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