mirror of
https://github.com/opencv/opencv.git
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Merge pull request #19351 from TolyaTalamanov:at/python-backend
This commit is contained in:
Alexander Alekhin
commit
64072e44cc
@ -53,6 +53,7 @@ file(GLOB gapi_ext_hdrs
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"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/streaming/*.hpp"
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"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/plaidml/*.hpp"
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"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/util/*.hpp"
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"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/python/*.hpp"
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)
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set(gapi_srcs
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@ -158,6 +159,7 @@ set(gapi_srcs
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# Python bridge
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src/backends/ie/bindings_ie.cpp
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src/backends/python/gpythonbackend.cpp
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)
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ocv_add_dispatched_file(backends/fluid/gfluidimgproc_func SSE4_1 AVX2)
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@ -645,7 +645,7 @@ Supported matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref
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@param ddepth optional depth of the output matrix.
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@sa sub, addWeighted
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*/
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GAPI_EXPORTS GMat addC(const GMat& src1, const GScalar& c, int ddepth = -1);
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GAPI_EXPORTS_W GMat addC(const GMat& src1, const GScalar& c, int ddepth = -1);
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//! @overload
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GAPI_EXPORTS GMat addC(const GScalar& c, const GMat& src1, int ddepth = -1);
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@ -1945,7 +1945,7 @@ Gets dimensions from rectangle.
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@param r Input rectangle.
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@return Size (rectangle dimensions).
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*/
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GAPI_EXPORTS GOpaque<Size> size(const GOpaque<Rect>& r);
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GAPI_EXPORTS_W GOpaque<Size> size(const GOpaque<Rect>& r);
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/** @brief Gets dimensions from MediaFrame.
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@ -1168,7 +1168,7 @@ Calculates the up-right bounding rectangle of a point set.
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@param src Input 2D point set, stored in std::vector<cv::Point2i>.
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*/
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GAPI_EXPORTS GOpaque<Rect> boundingRect(const GArray<Point2i>& src);
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GAPI_EXPORTS_W GOpaque<Rect> boundingRect(const GArray<Point2i>& src);
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/** @overload
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58
modules/gapi/include/opencv2/gapi/python/python.hpp
Normal file
58
modules/gapi/include/opencv2/gapi/python/python.hpp
Normal file
@ -0,0 +1,58 @@
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// 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) 2021 Intel Corporation
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#ifndef OPENCV_GAPI_PYTHON_API_HPP
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#define OPENCV_GAPI_PYTHON_API_HPP
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#include <opencv2/gapi/gkernel.hpp> // GKernelPackage
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#include <opencv2/gapi/own/exports.hpp> // GAPI_EXPORTS
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namespace cv {
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namespace gapi {
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namespace python {
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GAPI_EXPORTS cv::gapi::GBackend backend();
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struct GPythonContext
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{
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const cv::GArgs &ins;
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const cv::GMetaArgs &in_metas;
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const cv::GTypesInfo &out_info;
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};
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using Impl = std::function<cv::GRunArgs(const GPythonContext&)>;
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class GAPI_EXPORTS GPythonKernel
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{
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public:
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GPythonKernel() = default;
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GPythonKernel(Impl run);
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cv::GRunArgs operator()(const GPythonContext& ctx);
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private:
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Impl m_run;
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};
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class GAPI_EXPORTS GPythonFunctor : public cv::gapi::GFunctor
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{
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public:
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using Meta = cv::GKernel::M;
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GPythonFunctor(const char* id, const Meta &meta, const Impl& impl);
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GKernelImpl impl() const override;
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gapi::GBackend backend() const override;
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private:
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GKernelImpl impl_;
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};
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} // namespace python
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} // namespace gapi
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} // namespace cv
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#endif // OPENCV_GAPI_PYTHON_API_HPP
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@ -3,10 +3,13 @@
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#ifdef HAVE_OPENCV_GAPI
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#include <opencv2/gapi/cpu/gcpukernel.hpp>
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#include <opencv2/gapi/python/python.hpp>
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// NB: Python wrapper replaces :: with _ for classes
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using gapi_GKernelPackage = cv::gapi::GKernelPackage;
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using gapi_GNetPackage = cv::gapi::GNetPackage;
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using gapi_ie_PyParams = cv::gapi::ie::PyParams;
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using gapi_GKernelPackage = cv::gapi::GKernelPackage;
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using gapi_GNetPackage = cv::gapi::GNetPackage;
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using gapi_ie_PyParams = cv::gapi::ie::PyParams;
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using gapi_wip_IStreamSource_Ptr = cv::Ptr<cv::gapi::wip::IStreamSource>;
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using detail_ExtractArgsCallback = cv::detail::ExtractArgsCallback;
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using detail_ExtractMetaCallback = cv::detail::ExtractMetaCallback;
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@ -18,7 +21,7 @@ using GOpaque_int = cv::GOpaque<int>;
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using GOpaque_double = cv::GOpaque<double>;
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using GOpaque_float = cv::GOpaque<double>;
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using GOpaque_string = cv::GOpaque<std::string>;
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using GOpaque_Point = cv::GOpaque<cv::Point>;
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using GOpaque_Point2i = cv::GOpaque<cv::Point>;
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using GOpaque_Point2f = cv::GOpaque<cv::Point2f>;
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using GOpaque_Size = cv::GOpaque<cv::Size>;
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using GOpaque_Rect = cv::GOpaque<cv::Rect>;
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@ -28,7 +31,7 @@ using GArray_int = cv::GArray<int>;
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using GArray_double = cv::GArray<double>;
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using GArray_float = cv::GArray<double>;
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using GArray_string = cv::GArray<std::string>;
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using GArray_Point = cv::GArray<cv::Point>;
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using GArray_Point2i = cv::GArray<cv::Point>;
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using GArray_Point2f = cv::GArray<cv::Point2f>;
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using GArray_Size = cv::GArray<cv::Size>;
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using GArray_Rect = cv::GArray<cv::Rect>;
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@ -41,19 +44,19 @@ using GArray_GMat = cv::GArray<cv::GMat>;
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// WA: Create using
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using std::string;
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template<>
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template <>
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bool pyopencv_to(PyObject* obj, std::vector<GCompileArg>& value, const ArgInfo& info)
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{
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return pyopencv_to_generic_vec(obj, value, info);
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}
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template<>
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template <>
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PyObject* pyopencv_from(const std::vector<GCompileArg>& value)
|
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{
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return pyopencv_from_generic_vec(value);
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}
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template<>
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template <>
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bool pyopencv_to(PyObject* obj, GRunArgs& value, const ArgInfo& info)
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{
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return pyopencv_to_generic_vec(obj, value, info);
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@ -267,10 +270,9 @@ static cv::detail::OpaqueRef extract_opaque_ref(PyObject* from, cv::detail::Opaq
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UNSUPPORTED(SCALAR);
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UNSUPPORTED(MAT);
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UNSUPPORTED(DRAW_PRIM);
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}
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#undef HANDLE_CASE
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#undef UNSUPPORTED
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|
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}
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util::throw_error(std::logic_error("Unsupported type for GOpaqueT"));
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}
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@ -302,8 +304,7 @@ static cv::detail::VectorRef extract_vector_ref(PyObject* from, cv::detail::Opaq
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#undef HANDLE_CASE
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#undef UNSUPPORTED
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}
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util::throw_error(std::logic_error("Unsupported type for GOpaqueT"));
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util::throw_error(std::logic_error("Unsupported type for GArrayT"));
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}
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static cv::GRunArg extract_run_arg(const cv::GTypeInfo& info, PyObject* item)
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@ -340,6 +341,7 @@ static cv::GRunArg extract_run_arg(const cv::GTypeInfo& info, PyObject* item)
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}
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case cv::GShape::GFRAME:
|
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{
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// NB: Isn't supported yet.
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break;
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}
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}
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@ -391,7 +393,6 @@ static cv::GMetaArg extract_meta_arg(const cv::GTypeInfo& info, PyObject* item)
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break;
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}
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}
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util::throw_error(std::logic_error("Unsupported output shape"));
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}
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@ -409,6 +410,134 @@ static cv::GMetaArgs extract_meta_args(const cv::GTypesInfo& info, PyObject* py_
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return metas;
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}
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inline PyObject* extract_opaque_value(const cv::GArg& value)
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{
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GAPI_Assert(value.kind != cv::detail::ArgKind::GOBJREF);
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#define HANDLE_CASE(T, O) case cv::detail::OpaqueKind::CV_##T: \
|
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{ \
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return pyopencv_from(value.get<O>()); \
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}
|
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|
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#define UNSUPPORTED(T) case cv::detail::OpaqueKind::CV_##T: break
|
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switch (value.opaque_kind)
|
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{
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HANDLE_CASE(BOOL, bool);
|
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HANDLE_CASE(INT, int);
|
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HANDLE_CASE(DOUBLE, double);
|
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HANDLE_CASE(FLOAT, float);
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HANDLE_CASE(STRING, std::string);
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HANDLE_CASE(POINT, cv::Point);
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HANDLE_CASE(POINT2F, cv::Point2f);
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HANDLE_CASE(SIZE, cv::Size);
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HANDLE_CASE(RECT, cv::Rect);
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HANDLE_CASE(SCALAR, cv::Scalar);
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HANDLE_CASE(MAT, cv::Mat);
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UNSUPPORTED(UNKNOWN);
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UNSUPPORTED(UINT64);
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UNSUPPORTED(DRAW_PRIM);
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#undef HANDLE_CASE
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#undef UNSUPPORTED
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}
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util::throw_error(std::logic_error("Unsupported kernel input type"));
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}
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static cv::GRunArgs run_py_kernel(PyObject* kernel,
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const cv::gapi::python::GPythonContext &ctx)
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{
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const auto& ins = ctx.ins;
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const auto& in_metas = ctx.in_metas;
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const auto& out_info = ctx.out_info;
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|
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PyGILState_STATE gstate;
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gstate = PyGILState_Ensure();
|
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|
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cv::GRunArgs outs;
|
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try
|
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{
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int in_idx = 0;
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PyObject* args = PyTuple_New(ins.size());
|
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for (size_t i = 0; i < ins.size(); ++i)
|
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{
|
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// NB: If meta is monostate then object isn't associated with G-TYPE, so in case it
|
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// kind matches with supported types do conversion from c++ to python, if not (CV_UNKNOWN)
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// obtain PyObject* and pass as-is.
|
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if (cv::util::holds_alternative<cv::util::monostate>(in_metas[i]))
|
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{
|
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PyTuple_SetItem(args, i,
|
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ins[i].opaque_kind != cv::detail::OpaqueKind::CV_UNKNOWN ? extract_opaque_value(ins[i])
|
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: ins[i].get<PyObject*>());
|
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continue;
|
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}
|
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|
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switch (in_metas[i].index())
|
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{
|
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case cv::GMetaArg::index_of<cv::GMatDesc>():
|
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PyTuple_SetItem(args, i, pyopencv_from(ins[i].get<cv::Mat>()));
|
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break;
|
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case cv::GMetaArg::index_of<cv::GScalarDesc>():
|
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PyTuple_SetItem(args, i, pyopencv_from(ins[i].get<cv::Scalar>()));
|
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break;
|
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case cv::GMetaArg::index_of<cv::GOpaqueDesc>():
|
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PyTuple_SetItem(args, i, pyopencv_from(ins[i].get<cv::detail::OpaqueRef>()));
|
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break;
|
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case cv::GMetaArg::index_of<cv::GArrayDesc>():
|
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PyTuple_SetItem(args, i, pyopencv_from(ins[i].get<cv::detail::VectorRef>()));
|
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break;
|
||||
case cv::GMetaArg::index_of<cv::GFrameDesc>():
|
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util::throw_error(std::logic_error("GFrame isn't supported for custom operation"));
|
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break;
|
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}
|
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++in_idx;
|
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}
|
||||
|
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PyObject* result = PyObject_CallObject(kernel, args);
|
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|
||||
outs = out_info.size() == 1 ? cv::GRunArgs{extract_run_arg(out_info[0], result)}
|
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: extract_run_args(out_info, result);
|
||||
}
|
||||
catch (...)
|
||||
{
|
||||
PyGILState_Release(gstate);
|
||||
throw;
|
||||
}
|
||||
PyGILState_Release(gstate);
|
||||
|
||||
return outs;
|
||||
}
|
||||
|
||||
// FIXME: Now it's impossible to obtain meta function from operation,
|
||||
// because kernel connects to operation only by id (string).
|
||||
static GMetaArgs empty_meta(const cv::GMetaArgs &, const cv::GArgs &) {
|
||||
return {};
|
||||
}
|
||||
|
||||
static PyObject* pyopencv_cv_gapi_kernels(PyObject* , PyObject* py_args, PyObject*)
|
||||
{
|
||||
using namespace cv;
|
||||
gapi::GKernelPackage pkg;
|
||||
Py_ssize_t size = PyTuple_Size(py_args);
|
||||
for (int i = 0; i < size; ++i)
|
||||
{
|
||||
PyObject* pair = PyTuple_GetItem(py_args, i);
|
||||
PyObject* kernel = PyTuple_GetItem(pair, 0);
|
||||
|
||||
std::string id;
|
||||
if (!pyopencv_to(PyTuple_GetItem(pair, 1), id, ArgInfo("id", false)))
|
||||
{
|
||||
PyErr_SetString(PyExc_TypeError, "Failed to obtain: kernel id must be a string");
|
||||
return NULL;
|
||||
}
|
||||
Py_INCREF(kernel);
|
||||
gapi::python::GPythonFunctor f(id.c_str(),
|
||||
empty_meta,
|
||||
std::bind(run_py_kernel,
|
||||
kernel,
|
||||
std::placeholders::_1));
|
||||
pkg.include(f);
|
||||
}
|
||||
return pyopencv_from(pkg);
|
||||
}
|
||||
|
||||
static PyObject* pyopencv_cv_gin(PyObject*, PyObject* py_args, PyObject*)
|
||||
{
|
||||
Py_INCREF(py_args);
|
||||
|
||||
@ -15,6 +15,59 @@ pkgs = [
|
||||
# ('plaidml', cv.gapi.core.plaidml.kernels())
|
||||
]
|
||||
|
||||
# Test output GMat.
|
||||
def custom_add(img1, img2, dtype):
|
||||
return cv.add(img1, img2)
|
||||
|
||||
# Test output GScalar.
|
||||
def custom_mean(img):
|
||||
return cv.mean(img)
|
||||
|
||||
# Test output tuple of GMat's.
|
||||
def custom_split3(img):
|
||||
# NB: cv.split return list but g-api requires tuple in multiple output case
|
||||
return tuple(cv.split(img))
|
||||
|
||||
# Test output GOpaque.
|
||||
def custom_size(img):
|
||||
# NB: Take only H, W, because the operation should return cv::Size which is 2D.
|
||||
return img.shape[:2]
|
||||
|
||||
# Test output GArray.
|
||||
def custom_goodFeaturesToTrack(img, max_corners, quality_lvl,
|
||||
min_distance, mask, block_sz,
|
||||
use_harris_detector, k):
|
||||
features = cv.goodFeaturesToTrack(img, max_corners, quality_lvl,
|
||||
min_distance, mask=mask,
|
||||
blockSize=block_sz,
|
||||
useHarrisDetector=use_harris_detector, k=k)
|
||||
# NB: The operation output is cv::GArray<cv::Pointf>, so it should be mapped
|
||||
# to python paramaters like this: [(1.2, 3.4), (5.2, 3.2)], because the cv::Point2f
|
||||
# according to opencv rules mapped to the tuple and cv::GArray<> mapped to the list.
|
||||
# OpenCV returns np.array with shape (n_features, 1, 2), so let's to convert it to list
|
||||
# tuples with size - n_features.
|
||||
features = list(map(tuple, features.reshape(features.shape[0], -1)))
|
||||
return features
|
||||
|
||||
# Test input scalar.
|
||||
def custom_addC(img, sc, dtype):
|
||||
# NB: dtype is just ignored in this implementation.
|
||||
# More over from G-API kernel got scalar as tuples with 4 elements
|
||||
# where the last element is equal to zero, just cut him for broadcasting.
|
||||
return img + np.array(sc, dtype=np.uint8)[:-1]
|
||||
|
||||
|
||||
# Test input opaque.
|
||||
def custom_sizeR(rect):
|
||||
# NB: rect - is tuple (x, y, h, w)
|
||||
return (rect[2], rect[3])
|
||||
|
||||
# Test input array.
|
||||
def custom_boundingRect(array):
|
||||
# NB: OpenCV - numpy array (n_points x 2).
|
||||
# G-API - array of tuples (n_points).
|
||||
return cv.boundingRect(np.array(array))
|
||||
|
||||
|
||||
class gapi_sample_pipelines(NewOpenCVTests):
|
||||
|
||||
@ -40,5 +93,182 @@ class gapi_sample_pipelines(NewOpenCVTests):
|
||||
'Failed on ' + pkg_name + ' backend')
|
||||
|
||||
|
||||
def test_custom_mean(self):
|
||||
img_path = self.find_file('cv/face/david2.jpg', [os.environ.get('OPENCV_TEST_DATA_PATH')])
|
||||
in_mat = cv.imread(img_path)
|
||||
|
||||
# OpenCV
|
||||
expected = cv.mean(in_mat)
|
||||
|
||||
# G-API
|
||||
g_in = cv.GMat()
|
||||
g_out = cv.gapi.mean(g_in)
|
||||
|
||||
comp = cv.GComputation(g_in, g_out)
|
||||
|
||||
pkg = cv.gapi_wip_kernels((custom_mean, 'org.opencv.core.math.mean'))
|
||||
actual = comp.apply(cv.gin(in_mat), args=cv.compile_args(pkg))
|
||||
|
||||
# Comparison
|
||||
self.assertEqual(expected, actual)
|
||||
|
||||
|
||||
def test_custom_add(self):
|
||||
sz = (3, 3)
|
||||
in_mat1 = np.full(sz, 45, dtype=np.uint8)
|
||||
in_mat2 = np.full(sz, 50 , dtype=np.uint8)
|
||||
|
||||
# OpenCV
|
||||
expected = cv.add(in_mat1, in_mat2)
|
||||
|
||||
# G-API
|
||||
g_in1 = cv.GMat()
|
||||
g_in2 = cv.GMat()
|
||||
g_out = cv.gapi.add(g_in1, g_in2)
|
||||
comp = cv.GComputation(cv.GIn(g_in1, g_in2), cv.GOut(g_out))
|
||||
|
||||
pkg = cv.gapi_wip_kernels((custom_add, 'org.opencv.core.math.add'))
|
||||
actual = comp.apply(cv.gin(in_mat1, in_mat2), args=cv.compile_args(pkg))
|
||||
|
||||
self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF))
|
||||
|
||||
|
||||
def test_custom_size(self):
|
||||
sz = (100, 150, 3)
|
||||
in_mat = np.full(sz, 45, dtype=np.uint8)
|
||||
|
||||
# OpenCV
|
||||
expected = (100, 150)
|
||||
|
||||
# G-API
|
||||
g_in = cv.GMat()
|
||||
g_sz = cv.gapi.streaming.size(g_in)
|
||||
comp = cv.GComputation(cv.GIn(g_in), cv.GOut(g_sz))
|
||||
|
||||
pkg = cv.gapi_wip_kernels((custom_size, 'org.opencv.streaming.size'))
|
||||
actual = comp.apply(cv.gin(in_mat), args=cv.compile_args(pkg))
|
||||
|
||||
self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF))
|
||||
|
||||
|
||||
def test_custom_goodFeaturesToTrack(self):
|
||||
# G-API
|
||||
img_path = self.find_file('cv/face/david2.jpg', [os.environ.get('OPENCV_TEST_DATA_PATH')])
|
||||
in_mat = cv.cvtColor(cv.imread(img_path), cv.COLOR_RGB2GRAY)
|
||||
|
||||
# NB: goodFeaturesToTrack configuration
|
||||
max_corners = 50
|
||||
quality_lvl = 0.01
|
||||
min_distance = 10
|
||||
block_sz = 3
|
||||
use_harris_detector = True
|
||||
k = 0.04
|
||||
mask = None
|
||||
|
||||
# OpenCV
|
||||
expected = cv.goodFeaturesToTrack(in_mat, max_corners, quality_lvl,
|
||||
min_distance, mask=mask,
|
||||
blockSize=block_sz, useHarrisDetector=use_harris_detector, k=k)
|
||||
|
||||
# G-API
|
||||
g_in = cv.GMat()
|
||||
g_out = cv.gapi.goodFeaturesToTrack(g_in, max_corners, quality_lvl,
|
||||
min_distance, mask, block_sz, use_harris_detector, k)
|
||||
|
||||
comp = cv.GComputation(cv.GIn(g_in), cv.GOut(g_out))
|
||||
pkg = cv.gapi_wip_kernels((custom_goodFeaturesToTrack, 'org.opencv.imgproc.feature.goodFeaturesToTrack'))
|
||||
actual = comp.apply(cv.gin(in_mat), args=cv.compile_args(pkg))
|
||||
|
||||
# NB: OpenCV & G-API have different output types.
|
||||
# OpenCV - numpy array with shape (num_points, 1, 2)
|
||||
# G-API - list of tuples with size - num_points
|
||||
# Comparison
|
||||
self.assertEqual(0.0, cv.norm(expected.flatten(),
|
||||
np.array(actual, dtype=np.float32).flatten(), cv.NORM_INF))
|
||||
|
||||
|
||||
def test_custom_addC(self):
|
||||
sz = (3, 3, 3)
|
||||
in_mat = np.full(sz, 45, dtype=np.uint8)
|
||||
sc = (50, 10, 20)
|
||||
|
||||
# Numpy reference, make array from sc to keep uint8 dtype.
|
||||
expected = in_mat + np.array(sc, dtype=np.uint8)
|
||||
|
||||
# G-API
|
||||
g_in = cv.GMat()
|
||||
g_sc = cv.GScalar()
|
||||
g_out = cv.gapi.addC(g_in, g_sc)
|
||||
comp = cv.GComputation(cv.GIn(g_in, g_sc), cv.GOut(g_out))
|
||||
|
||||
pkg = cv.gapi_wip_kernels((custom_addC, 'org.opencv.core.math.addC'))
|
||||
actual = comp.apply(cv.gin(in_mat, sc), args=cv.compile_args(pkg))
|
||||
|
||||
self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF))
|
||||
|
||||
|
||||
def test_custom_sizeR(self):
|
||||
# x, y, h, w
|
||||
roi = (10, 15, 100, 150)
|
||||
|
||||
expected = (100, 150)
|
||||
|
||||
# G-API
|
||||
g_r = cv.GOpaqueT(cv.gapi.CV_RECT)
|
||||
g_sz = cv.gapi.streaming.size(g_r)
|
||||
comp = cv.GComputation(cv.GIn(g_r), cv.GOut(g_sz))
|
||||
|
||||
pkg = cv.gapi_wip_kernels((custom_sizeR, 'org.opencv.streaming.sizeR'))
|
||||
actual = comp.apply(cv.gin(roi), args=cv.compile_args(pkg))
|
||||
|
||||
# cv.norm works with tuples ?
|
||||
self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF))
|
||||
|
||||
|
||||
def test_custom_boundingRect(self):
|
||||
points = [(0,0), (0,1), (1,0), (1,1)]
|
||||
|
||||
# OpenCV
|
||||
expected = cv.boundingRect(np.array(points))
|
||||
|
||||
# G-API
|
||||
g_pts = cv.GArrayT(cv.gapi.CV_POINT)
|
||||
g_br = cv.gapi.boundingRect(g_pts)
|
||||
comp = cv.GComputation(cv.GIn(g_pts), cv.GOut(g_br))
|
||||
|
||||
pkg = cv.gapi_wip_kernels((custom_boundingRect, 'org.opencv.imgproc.shape.boundingRectVector32S'))
|
||||
actual = comp.apply(cv.gin(points), args=cv.compile_args(pkg))
|
||||
|
||||
# cv.norm works with tuples ?
|
||||
self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF))
|
||||
|
||||
|
||||
def test_multiple_custom_kernels(self):
|
||||
sz = (3, 3, 3)
|
||||
in_mat1 = np.full(sz, 45, dtype=np.uint8)
|
||||
in_mat2 = np.full(sz, 50 , dtype=np.uint8)
|
||||
|
||||
# OpenCV
|
||||
expected = cv.mean(cv.split(cv.add(in_mat1, in_mat2))[1])
|
||||
|
||||
# G-API
|
||||
g_in1 = cv.GMat()
|
||||
g_in2 = cv.GMat()
|
||||
g_sum = cv.gapi.add(g_in1, g_in2)
|
||||
g_b, g_r, g_g = cv.gapi.split3(g_sum)
|
||||
g_mean = cv.gapi.mean(g_b)
|
||||
|
||||
comp = cv.GComputation(cv.GIn(g_in1, g_in2), cv.GOut(g_mean))
|
||||
|
||||
|
||||
pkg = cv.gapi_wip_kernels((custom_add , 'org.opencv.core.math.add'),
|
||||
(custom_mean , 'org.opencv.core.math.mean'),
|
||||
(custom_split3, 'org.opencv.core.transform.split3'))
|
||||
|
||||
actual = comp.apply(cv.gin(in_mat1, in_mat2), args=cv.compile_args(pkg))
|
||||
|
||||
self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF))
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
NewOpenCVTests.bootstrap()
|
||||
|
||||
@ -199,6 +199,5 @@ class test_gapi_streaming(NewOpenCVTests):
|
||||
if proc_num_frames == max_num_frames:
|
||||
break;
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
NewOpenCVTests.bootstrap()
|
||||
|
||||
261
modules/gapi/src/backends/python/gpythonbackend.cpp
Normal file
261
modules/gapi/src/backends/python/gpythonbackend.cpp
Normal file
@ -0,0 +1,261 @@
|
||||
// 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) 2021 Intel Corporation
|
||||
|
||||
#include <ade/util/zip_range.hpp> // zip_range, indexed
|
||||
|
||||
#include <opencv2/gapi/util/throw.hpp> // throw_error
|
||||
#include <opencv2/gapi/python/python.hpp>
|
||||
|
||||
#include "api/gbackend_priv.hpp"
|
||||
#include "backends/common/gbackend.hpp"
|
||||
|
||||
cv::gapi::python::GPythonKernel::GPythonKernel(cv::gapi::python::Impl run)
|
||||
: m_run(run)
|
||||
{
|
||||
}
|
||||
|
||||
cv::GRunArgs cv::gapi::python::GPythonKernel::operator()(const cv::gapi::python::GPythonContext& ctx)
|
||||
{
|
||||
return m_run(ctx);
|
||||
}
|
||||
|
||||
cv::gapi::python::GPythonFunctor::GPythonFunctor(const char* id,
|
||||
const cv::gapi::python::GPythonFunctor::Meta &meta,
|
||||
const cv::gapi::python::Impl& impl)
|
||||
: gapi::GFunctor(id), impl_{GPythonKernel{impl}, meta}
|
||||
{
|
||||
}
|
||||
|
||||
cv::GKernelImpl cv::gapi::python::GPythonFunctor::impl() const
|
||||
{
|
||||
return impl_;
|
||||
}
|
||||
|
||||
cv::gapi::GBackend cv::gapi::python::GPythonFunctor::backend() const
|
||||
{
|
||||
return cv::gapi::python::backend();
|
||||
}
|
||||
|
||||
namespace {
|
||||
|
||||
struct PythonUnit
|
||||
{
|
||||
static const char *name() { return "PythonUnit"; }
|
||||
cv::gapi::python::GPythonKernel kernel;
|
||||
};
|
||||
|
||||
using PythonModel = ade::TypedGraph
|
||||
< cv::gimpl::Op
|
||||
, PythonUnit
|
||||
>;
|
||||
|
||||
using ConstPythonModel = ade::ConstTypedGraph
|
||||
< cv::gimpl::Op
|
||||
, PythonUnit
|
||||
>;
|
||||
|
||||
class GPythonExecutable final: public cv::gimpl::GIslandExecutable
|
||||
{
|
||||
virtual void run(std::vector<InObj> &&,
|
||||
std::vector<OutObj> &&) override;
|
||||
|
||||
virtual bool allocatesOutputs() const override { return true; }
|
||||
// Return an empty RMat since we will reuse the input.
|
||||
// There is no need to allocate and copy 4k image here.
|
||||
virtual cv::RMat allocate(const cv::GMatDesc&) const override { return {}; }
|
||||
|
||||
virtual bool canReshape() const override { return true; }
|
||||
virtual void reshape(ade::Graph&, const cv::GCompileArgs&) override {
|
||||
// Do nothing here
|
||||
}
|
||||
|
||||
public:
|
||||
GPythonExecutable(const ade::Graph &,
|
||||
const std::vector<ade::NodeHandle> &);
|
||||
|
||||
const ade::Graph& m_g;
|
||||
cv::gimpl::GModel::ConstGraph m_gm;
|
||||
cv::gapi::python::GPythonKernel m_kernel;
|
||||
ade::NodeHandle m_op;
|
||||
|
||||
cv::GTypesInfo m_out_info;
|
||||
cv::GMetaArgs m_in_metas;
|
||||
cv::gimpl::Mag m_res;
|
||||
};
|
||||
|
||||
static cv::GArg packArg(cv::gimpl::Mag& m_res, const cv::GArg &arg)
|
||||
{
|
||||
// No API placeholders allowed at this point
|
||||
// FIXME: this check has to be done somewhere in compilation stage.
|
||||
GAPI_Assert( arg.kind != cv::detail::ArgKind::GMAT
|
||||
&& arg.kind != cv::detail::ArgKind::GSCALAR
|
||||
&& arg.kind != cv::detail::ArgKind::GARRAY
|
||||
&& arg.kind != cv::detail::ArgKind::GOPAQUE
|
||||
&& arg.kind != cv::detail::ArgKind::GFRAME);
|
||||
|
||||
if (arg.kind != cv::detail::ArgKind::GOBJREF)
|
||||
{
|
||||
// All other cases - pass as-is, with no transformations to GArg contents.
|
||||
return arg;
|
||||
}
|
||||
GAPI_Assert(arg.kind == cv::detail::ArgKind::GOBJREF);
|
||||
|
||||
// Wrap associated CPU object (either host or an internal one)
|
||||
// FIXME: object can be moved out!!! GExecutor faced that.
|
||||
const cv::gimpl::RcDesc &ref = arg.get<cv::gimpl::RcDesc>();
|
||||
switch (ref.shape)
|
||||
{
|
||||
case cv::GShape::GMAT: return cv::GArg(m_res.slot<cv::Mat>() [ref.id]);
|
||||
case cv::GShape::GSCALAR: return cv::GArg(m_res.slot<cv::Scalar>()[ref.id]);
|
||||
// Note: .at() is intentional for GArray and GOpaque as objects MUST be already there
|
||||
// (and constructed by either bindIn/Out or resetInternal)
|
||||
case cv::GShape::GARRAY: return cv::GArg(m_res.slot<cv::detail::VectorRef>().at(ref.id));
|
||||
case cv::GShape::GOPAQUE: return cv::GArg(m_res.slot<cv::detail::OpaqueRef>().at(ref.id));
|
||||
case cv::GShape::GFRAME: return cv::GArg(m_res.slot<cv::MediaFrame>().at(ref.id));
|
||||
default:
|
||||
cv::util::throw_error(std::logic_error("Unsupported GShape type"));
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
static void writeBack(cv::GRunArg& arg, cv::GRunArgP& out)
|
||||
{
|
||||
switch (arg.index())
|
||||
{
|
||||
case cv::GRunArg::index_of<cv::Mat>():
|
||||
{
|
||||
auto& rmat = *cv::util::get<cv::RMat*>(out);
|
||||
rmat = cv::make_rmat<cv::gimpl::RMatAdapter>(cv::util::get<cv::Mat>(arg));
|
||||
break;
|
||||
}
|
||||
case cv::GRunArg::index_of<cv::Scalar>():
|
||||
{
|
||||
*cv::util::get<cv::Scalar*>(out) = cv::util::get<cv::Scalar>(arg);
|
||||
break;
|
||||
}
|
||||
case cv::GRunArg::index_of<cv::detail::OpaqueRef>():
|
||||
{
|
||||
auto& oref = cv::util::get<cv::detail::OpaqueRef>(arg);
|
||||
cv::util::get<cv::detail::OpaqueRef>(out).mov(oref);
|
||||
break;
|
||||
}
|
||||
case cv::GRunArg::index_of<cv::detail::VectorRef>():
|
||||
{
|
||||
auto& vref = cv::util::get<cv::detail::VectorRef>(arg);
|
||||
cv::util::get<cv::detail::VectorRef>(out).mov(vref);
|
||||
break;
|
||||
}
|
||||
default:
|
||||
GAPI_Assert(false && "Unsupported output type");
|
||||
}
|
||||
}
|
||||
|
||||
void GPythonExecutable::run(std::vector<InObj> &&input_objs,
|
||||
std::vector<OutObj> &&output_objs)
|
||||
{
|
||||
const auto &op = m_gm.metadata(m_op).get<cv::gimpl::Op>();
|
||||
for (auto& it : input_objs) cv::gimpl::magazine::bindInArg(m_res, it.first, it.second);
|
||||
|
||||
using namespace std::placeholders;
|
||||
cv::GArgs inputs;
|
||||
ade::util::transform(op.args,
|
||||
std::back_inserter(inputs),
|
||||
std::bind(&packArg, std::ref(m_res), _1));
|
||||
|
||||
|
||||
cv::gapi::python::GPythonContext ctx{inputs, m_in_metas, m_out_info};
|
||||
auto outs = m_kernel(ctx);
|
||||
|
||||
for (auto&& it : ade::util::zip(outs, output_objs))
|
||||
{
|
||||
writeBack(std::get<0>(it), std::get<1>(it).second);
|
||||
}
|
||||
}
|
||||
|
||||
class GPythonBackendImpl final: public cv::gapi::GBackend::Priv
|
||||
{
|
||||
virtual void unpackKernel(ade::Graph &graph,
|
||||
const ade::NodeHandle &op_node,
|
||||
const cv::GKernelImpl &impl) override
|
||||
{
|
||||
PythonModel gm(graph);
|
||||
const auto &kernel = cv::util::any_cast<cv::gapi::python::GPythonKernel>(impl.opaque);
|
||||
gm.metadata(op_node).set(PythonUnit{kernel});
|
||||
}
|
||||
|
||||
virtual EPtr compile(const ade::Graph &graph,
|
||||
const cv::GCompileArgs &,
|
||||
const std::vector<ade::NodeHandle> &nodes) const override
|
||||
{
|
||||
return EPtr{new GPythonExecutable(graph, nodes)};
|
||||
}
|
||||
|
||||
virtual bool controlsMerge() const override
|
||||
{
|
||||
return true;
|
||||
}
|
||||
|
||||
virtual bool allowsMerge(const cv::gimpl::GIslandModel::Graph &,
|
||||
const ade::NodeHandle &,
|
||||
const ade::NodeHandle &,
|
||||
const ade::NodeHandle &) const override
|
||||
{
|
||||
return false;
|
||||
}
|
||||
};
|
||||
|
||||
GPythonExecutable::GPythonExecutable(const ade::Graph& g,
|
||||
const std::vector<ade::NodeHandle>& nodes)
|
||||
: m_g(g), m_gm(m_g)
|
||||
{
|
||||
using namespace cv::gimpl;
|
||||
const auto is_op = [this](const ade::NodeHandle &nh)
|
||||
{
|
||||
return m_gm.metadata(nh).get<NodeType>().t == NodeType::OP;
|
||||
};
|
||||
|
||||
auto it = std::find_if(nodes.begin(), nodes.end(), is_op);
|
||||
GAPI_Assert(it != nodes.end() && "No operators found for this island?!");
|
||||
|
||||
ConstPythonModel cag(m_g);
|
||||
|
||||
m_op = *it;
|
||||
m_kernel = cag.metadata(m_op).get<PythonUnit>().kernel;
|
||||
|
||||
// Ensure this the only op in the graph
|
||||
if (std::any_of(it+1, nodes.end(), is_op))
|
||||
{
|
||||
cv::util::throw_error
|
||||
(std::logic_error
|
||||
("Internal error: Python subgraph has multiple operations"));
|
||||
}
|
||||
|
||||
m_out_info.reserve(m_op->outEdges().size());
|
||||
for (const auto &e : m_op->outEdges())
|
||||
{
|
||||
const auto& out_data = m_gm.metadata(e->dstNode()).get<cv::gimpl::Data>();
|
||||
m_out_info.push_back(cv::GTypeInfo{out_data.shape, out_data.kind, out_data.ctor});
|
||||
}
|
||||
|
||||
const auto& op = m_gm.metadata(m_op).get<cv::gimpl::Op>();
|
||||
m_in_metas.resize(op.args.size());
|
||||
GAPI_Assert(m_op->inEdges().size() > 0);
|
||||
for (const auto &in_eh : m_op->inEdges())
|
||||
{
|
||||
const auto& input_port = m_gm.metadata(in_eh).get<Input>().port;
|
||||
const auto& input_nh = in_eh->srcNode();
|
||||
const auto& input_meta = m_gm.metadata(input_nh).get<Data>().meta;
|
||||
m_in_metas.at(input_port) = input_meta;
|
||||
}
|
||||
}
|
||||
|
||||
} // anonymous namespace
|
||||
|
||||
cv::gapi::GBackend cv::gapi::python::backend()
|
||||
{
|
||||
static cv::gapi::GBackend this_backend(std::make_shared<GPythonBackendImpl>());
|
||||
return this_backend;
|
||||
}
|
||||
@ -2199,6 +2199,7 @@ static PyMethodDef special_methods[] = {
|
||||
#endif
|
||||
#ifdef HAVE_OPENCV_GAPI
|
||||
{"GIn", CV_PY_FN_WITH_KW(pyopencv_cv_GIn), "GIn(...) -> GInputProtoArgs"},
|
||||
{"gapi_wip_kernels", CV_PY_FN_WITH_KW(pyopencv_cv_gapi_kernels), "kernels(...) -> GKernelPackage"},
|
||||
{"GOut", CV_PY_FN_WITH_KW(pyopencv_cv_GOut), "GOut(...) -> GOutputProtoArgs"},
|
||||
{"gin", CV_PY_FN_WITH_KW(pyopencv_cv_gin), "gin(...) -> ExtractArgsCallback"},
|
||||
{"descr_of", CV_PY_FN_WITH_KW(pyopencv_cv_descr_of), "descr_of(...) -> ExtractMetaCallback"},
|
||||
|
||||
Loading…
Reference in New Issue
Block a user