fast-yolo4/3rdparty/opencv/inc/opencv2/gapi/cpu/gcpukernel.hpp
2024-09-25 09:43:03 +08:00

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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) 2018-2020 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/gmetaarg.hpp>
#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 gimpl
namespace gapi
{
/**
* @brief This namespace contains G-API CPU backend functions,
* structures, and symbols.
*/
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::Mat& inMat(int input);
cv::Mat& outMatR(int output); // FIXME: Avoid cv::Mat m = ctx.outMatR()
const cv::Scalar& inVal(int input);
cv::Scalar& outValR(int output); // FIXME: Avoid cv::Scalar s = ctx.outValR()
cv::MediaFrame& outFrame(int output);
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>();
}
GArg state()
{
return m_state;
}
protected:
detail::VectorRef& outVecRef(int output);
detail::OpaqueRef& outOpaqueRef(int output);
std::vector<GArg> m_args;
GArg m_state;
//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;
};
class GAPI_EXPORTS GCPUKernel
{
public:
// This function is a kernel's execution entry point (does the processing work)
using RunF = std::function<void(GCPUContext &)>;
// This function is a stateful kernel's setup routine (configures state)
using SetupF = std::function<void(const GMetaArgs &, const GArgs &,
GArg &, const GCompileArgs &)>;
GCPUKernel();
GCPUKernel(const RunF& runF, const SetupF& setupF = nullptr);
RunF m_runF = nullptr;
SetupF m_setupF = nullptr;
bool m_isStateful = false;
};
// 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 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::MediaFrame get(GCPUContext &ctx, int idx) { return ctx.inArg<cv::MediaFrame>(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): GArray<vector<U>>/GArray<GArray<U>> conversion should be done more gracefully in the system
template<typename U> struct get_in<cv::GArray<cv::GArray<U>> >: public get_in<cv::GArray<std::vector<U>> >
{
};
//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::Mat& m) : r{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<> struct get_out<cv::GFrame>
{
static cv::MediaFrame& get(GCPUContext &ctx, int idx)
{
return ctx.outFrame(idx);
}
};
template<typename U> struct get_out<cv::GArray<U>>
{
static std::vector<U>& get(GCPUContext &ctx, int idx)
{
return ctx.outVecR<U>(idx);
}
};
//FIXME(dm): GArray<Mat>/GArray<GMat> conversion should be done more gracefully in the system
template<> struct get_out<cv::GArray<cv::GMat> >: public get_out<cv::GArray<cv::Mat> >
{
};
// FIXME(dm): GArray<vector<U>>/GArray<GArray<U>> conversion should be done more gracefully in the system
template<typename U> struct get_out<cv::GArray<cv::GArray<U>> >: public get_out<cv::GArray<std::vector<U>> >
{
};
template<typename U> struct get_out<cv::GOpaque<U>>
{
static U& get(GCPUContext &ctx, int idx)
{
return ctx.outOpaqueR<U>(idx);
}
};
template<typename, typename>
struct OCVSetupHelper;
template<typename Impl, typename... Ins>
struct OCVSetupHelper<Impl, std::tuple<Ins...>>
{
// Using 'auto' return type and 'decltype' specifier in both 'setup_impl' versions
// to check existence of required 'Impl::setup' functions.
// While 'decltype' specifier accepts expression we pass expression with 'comma-operator'
// where first operand of comma-operator is call attempt to desired 'Impl::setup' and
// the second operand is 'void()' expression.
//
// SFINAE for 'Impl::setup' which accepts compile arguments.
template<int... IIs>
static auto setup_impl(const GMetaArgs &metaArgs, const GArgs &args,
GArg &state, const GCompileArgs &compileArgs,
detail::Seq<IIs...>) ->
decltype(Impl::setup(detail::get_in_meta<Ins>(metaArgs, args, IIs)...,
std::declval<typename std::add_lvalue_reference<
std::shared_ptr<typename Impl::State>
>::type
>(),
compileArgs)
, void())
{
// TODO: unique_ptr <-> shared_ptr conversion ?
// To check: Conversion is possible only if the state which should be passed to
// 'setup' user callback isn't required to have previous value
std::shared_ptr<typename Impl::State> stPtr;
Impl::setup(detail::get_in_meta<Ins>(metaArgs, args, IIs)..., stPtr, compileArgs);
state = GArg(stPtr);
}
// SFINAE for 'Impl::setup' which doesn't accept compile arguments.
template<int... IIs>
static auto setup_impl(const GMetaArgs &metaArgs, const GArgs &args,
GArg &state, const GCompileArgs &/* compileArgs */,
detail::Seq<IIs...>) ->
decltype(Impl::setup(detail::get_in_meta<Ins>(metaArgs, args, IIs)...,
std::declval<typename std::add_lvalue_reference<
std::shared_ptr<typename Impl::State>
>::type
>()
)
, void())
{
// The same comment as in 'setup' above.
std::shared_ptr<typename Impl::State> stPtr;
Impl::setup(detail::get_in_meta<Ins>(metaArgs, args, IIs)..., stPtr);
state = GArg(stPtr);
}
static void setup(const GMetaArgs &metaArgs, const GArgs &args,
GArg& state, const GCompileArgs &compileArgs)
{
setup_impl(metaArgs, args, state, compileArgs,
typename detail::MkSeq<sizeof...(Ins)>::type());
}
};
// OCVCallHelper is a helper class to call stateless OCV kernels and OCV kernel functors.
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
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(get_in<Ins>::get(ctx, IIs))...>
::call(impl, get_in<Ins>::get(ctx, IIs)..., 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());
}
};
// OCVStCallHelper is a helper class to call stateful OCV kernels.
template<typename, typename, typename>
struct OCVStCallHelper;
template<typename Impl, typename... Ins, typename... Outs>
struct OCVStCallHelper<Impl, std::tuple<Ins...>, std::tuple<Outs...>> :
OCVCallHelper<Impl, std::tuple<Ins...>, std::tuple<Outs...>>
{
template<typename... Inputs>
struct call_and_postprocess
{
template<typename... Outputs>
static void call(typename Impl::State& st, Inputs&&... ins, Outputs&&... outs)
{
Impl::run(std::forward<Inputs>(ins)..., outs..., st);
postprocess(outs...);
}
};
template<int... IIs, int... OIs>
static void call_impl(GCPUContext &ctx, detail::Seq<IIs...>, detail::Seq<OIs...>)
{
auto& st = *ctx.state().get<std::shared_ptr<typename Impl::State>>();
call_and_postprocess<decltype(get_in<Ins>::get(ctx, IIs))...>
::call(st, get_in<Ins>::get(ctx, IIs)..., 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());
}
};
} // namespace detail
template<class Impl, class K>
class GCPUKernelImpl: public cv::detail::KernelTag
{
using CallHelper = cv::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(&CallHelper::call); }
};
template<class Impl, class K, class S>
class GCPUStKernelImpl: public cv::detail::KernelTag
{
using StSetupHelper = detail::OCVSetupHelper<Impl, typename K::InArgs>;
using StCallHelper = detail::OCVStCallHelper<Impl, typename K::InArgs, typename K::OutArgs>;
public:
using API = K;
using State = S;
static cv::gapi::GBackend backend() { return cv::gapi::cpu::backend(); }
static cv::GCPUKernel kernel() { return GCPUKernel(&StCallHelper::call,
&StSetupHelper::setup); }
};
#define GAPI_OCV_KERNEL(Name, API) struct Name: public cv::GCPUKernelImpl<Name, API>
// TODO: Reuse Anatoliy's logic for support of types with commas in macro.
// Retrieve the common part from Anatoliy's logic to the separate place.
#define GAPI_OCV_KERNEL_ST(Name, API, State) \
struct Name: public cv::GCPUStKernelImpl<Name, API, State> \
/// @private
class gapi::cpu::GOCVFunctor : public gapi::GFunctor
{
public:
using Impl = std::function<void(GCPUContext &)>;
using Meta = cv::GKernel::M;
GOCVFunctor(const char* id, const Meta &meta, const Impl& impl)
: gapi::GFunctor(id), impl_{GCPUKernel(impl), meta}
{
}
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 = cv::detail::OCVCallHelper<Callable, typename K::InArgs, typename K::OutArgs>;
return GOCVFunctor{ K::id()
, &K::getOutMeta
, 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 = cv::detail::OCVCallHelper<Callable, typename K::InArgs, typename K::OutArgs>;
return GOCVFunctor{ K::id()
, &K::getOutMeta
, std::bind(&P::callFunctor, std::placeholders::_1, c)
};
}
//! @endcond
} // namespace cv
#endif // OPENCV_GAPI_GCPUKERNEL_HPP