opencv/modules/gapi/include/opencv2/gapi/cpu/gcpukernel.hpp
2020-04-03 01:21:51 +03:00

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