init - 初始化项目
This commit is contained in:
Lee Nony
491
modules/gapi/test/common/gapi_video_tests_common.hpp
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491
modules/gapi/test/common/gapi_video_tests_common.hpp
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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) 2020 Intel Corporation
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#ifndef OPENCV_GAPI_VIDEO_TESTS_COMMON_HPP
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#define OPENCV_GAPI_VIDEO_TESTS_COMMON_HPP
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#include "gapi_tests_common.hpp"
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#include "../../include/opencv2/gapi/video.hpp"
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#ifdef HAVE_OPENCV_VIDEO
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#include <opencv2/video.hpp>
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#endif // HAVE_OPENCV_VIDEO
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namespace opencv_test
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{
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namespace
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{
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G_TYPED_KERNEL(GMinScalar, <GScalar(GScalar,GScalar)>, "custom.MinScalar") {
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static GScalarDesc outMeta(GScalarDesc,GScalarDesc) { return empty_scalar_desc(); }
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};
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GAPI_OCV_KERNEL(GCPUMinScalar, GMinScalar) {
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static void run(const Scalar &sc1, const Scalar &sc2, Scalar &scOut) {
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scOut = Scalar(std::min(sc1[0], sc2[0]));
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}
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};
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inline void initTrackingPointsArray(std::vector<cv::Point2f>& points, int width, int height,
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int nPointsX, int nPointsY)
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{
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if (nPointsX > width || nPointsY > height)
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{
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FAIL() << "Specified points number is too big";
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}
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int stepX = width / nPointsX;
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int stepY = height / nPointsY;
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points.clear();
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GAPI_Assert((nPointsX >= 0) && (nPointsY) >= 0);
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points.reserve(nPointsX * nPointsY);
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for (int x = stepX / 2; x < width; x += stepX)
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{
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for (int y = stepY / 2; y < height; y += stepY)
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{
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Point2f pt(static_cast<float>(x), static_cast<float>(y));
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points.push_back(pt);
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}
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}
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}
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struct BuildOpticalFlowPyramidTestOutput
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{
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BuildOpticalFlowPyramidTestOutput(std::vector<Mat> &pyr, int maxLvl) :
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pyramid(pyr), maxLevel(maxLvl) { }
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std::vector<Mat> &pyramid;
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int maxLevel = 0;
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};
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template<typename Type>
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struct OptFlowLKTestInput
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{
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Type& prevData;
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Type& nextData;
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std::vector<cv::Point2f>& prevPoints;
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};
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struct OptFlowLKTestOutput
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{
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std::vector<cv::Point2f> &nextPoints;
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std::vector<uchar> &statuses;
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std::vector<float> &errors;
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};
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struct BuildOpticalFlowPyramidTestParams
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{
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BuildOpticalFlowPyramidTestParams() = default;
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BuildOpticalFlowPyramidTestParams(const std::string& name, int winSz, int maxLvl,
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bool withDeriv, int pBorder, int dBorder,
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bool tryReuse, const GCompileArgs& compArgs):
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fileName(name), winSize(winSz), maxLevel(maxLvl),
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withDerivatives(withDeriv), pyrBorder(pBorder),
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derivBorder(dBorder), tryReuseInputImage(tryReuse),
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compileArgs(compArgs) { }
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std::string fileName = "";
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int winSize = -1;
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int maxLevel = -1;
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bool withDerivatives = false;
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int pyrBorder = -1;
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int derivBorder = -1;
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bool tryReuseInputImage = false;
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cv::GCompileArgs compileArgs;
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};
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struct OptFlowLKTestParams
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{
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OptFlowLKTestParams(): fileNamePattern(""), format(1), channels(0), pointsNum{0, 0},
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winSize(0), maxLevel(3), minEigThreshold(1e-4), flags(0) { }
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OptFlowLKTestParams(const std::string& namePat, int chans,
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const std::tuple<int,int>& ptsNum, int winSz,
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const cv::TermCriteria& crit, const cv::GCompileArgs& compArgs,
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int flgs = 0, int fmt = 1, int maxLvl = 3, double minEigThresh = 1e-4):
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fileNamePattern(namePat), format(fmt), channels(chans),
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pointsNum(ptsNum), winSize(winSz), maxLevel(maxLvl),
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criteria(crit), minEigThreshold(minEigThresh), compileArgs(compArgs),
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flags(flgs) { }
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std::string fileNamePattern = "";
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int format = 1;
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int channels = 0;
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std::tuple<int,int> pointsNum = std::make_tuple(0, 0);
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int winSize = 0;
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int maxLevel = 3;
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cv::TermCriteria criteria;
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double minEigThreshold = 1e-4;
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cv::GCompileArgs compileArgs;
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int flags = 0;
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};
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inline void compareOutputPyramids(const BuildOpticalFlowPyramidTestOutput& outGAPI,
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const BuildOpticalFlowPyramidTestOutput& outOCV)
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{
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GAPI_Assert(outGAPI.maxLevel == outOCV.maxLevel);
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GAPI_Assert(outOCV.maxLevel >= 0);
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const size_t maxLevel = static_cast<size_t>(outOCV.maxLevel);
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for (size_t i = 0; i <= maxLevel; i++)
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{
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EXPECT_TRUE(AbsExact().to_compare_f()(outGAPI.pyramid[i], outOCV.pyramid[i]));
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}
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}
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template <typename Elem>
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inline bool compareVectorsAbsExactForOptFlow(const std::vector<Elem>& outGAPI,
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const std::vector<Elem>& outOCV)
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{
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return AbsExactVector<Elem>().to_compare_f()(outGAPI, outOCV);
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}
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inline void compareOutputsOptFlow(const OptFlowLKTestOutput& outGAPI,
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const OptFlowLKTestOutput& outOCV)
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{
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EXPECT_TRUE(compareVectorsAbsExactForOptFlow(outGAPI.nextPoints, outOCV.nextPoints));
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EXPECT_TRUE(compareVectorsAbsExactForOptFlow(outGAPI.statuses, outOCV.statuses));
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EXPECT_TRUE(compareVectorsAbsExactForOptFlow(outGAPI.errors, outOCV.errors));
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}
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inline std::ostream& operator<<(std::ostream& os, const cv::TermCriteria& criteria)
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{
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os << "{";
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switch (criteria.type) {
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case cv::TermCriteria::COUNT:
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os << "COUNT; ";
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break;
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case cv::TermCriteria::EPS:
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os << "EPS; ";
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break;
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case cv::TermCriteria::COUNT | cv::TermCriteria::EPS:
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os << "COUNT | EPS; ";
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break;
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default:
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os << "TypeUndefined; ";
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break;
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};
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return os << criteria.maxCount << "; " << criteria.epsilon <<"}";
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}
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#ifdef HAVE_OPENCV_VIDEO
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inline GComputation runOCVnGAPIBuildOptFlowPyramid(TestFunctional& testInst,
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const BuildOpticalFlowPyramidTestParams& params,
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BuildOpticalFlowPyramidTestOutput& outOCV,
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BuildOpticalFlowPyramidTestOutput& outGAPI)
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{
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testInst.initMatFromImage(CV_8UC1, params.fileName);
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// OpenCV code /////////////////////////////////////////////////////////////
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{
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outOCV.maxLevel = cv::buildOpticalFlowPyramid(testInst.in_mat1, outOCV.pyramid,
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Size(params.winSize, params.winSize),
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params.maxLevel, params.withDerivatives,
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params.pyrBorder, params.derivBorder,
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params.tryReuseInputImage);
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}
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// G-API code //////////////////////////////////////////////////////////////
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GMat in;
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GArray<GMat> out;
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GScalar outMaxLevel;
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std::tie(out, outMaxLevel) =
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cv::gapi::buildOpticalFlowPyramid(in, Size(params.winSize, params.winSize),
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params.maxLevel, params.withDerivatives,
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params.pyrBorder, params.derivBorder,
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params.tryReuseInputImage);
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GComputation c(GIn(in), GOut(out, outMaxLevel));
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Scalar outMaxLevelSc;
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c.apply(gin(testInst.in_mat1), gout(outGAPI.pyramid, outMaxLevelSc),
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std::move(const_cast<GCompileArgs&>(params.compileArgs)));
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outGAPI.maxLevel = static_cast<int>(outMaxLevelSc[0]);
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return c;
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}
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template<typename GType, typename Type>
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cv::GComputation runOCVnGAPIOptFlowLK(OptFlowLKTestInput<Type>& in,
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int width, int height,
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const OptFlowLKTestParams& params,
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OptFlowLKTestOutput& ocvOut,
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OptFlowLKTestOutput& gapiOut)
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{
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int nPointsX = 0, nPointsY = 0;
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std::tie(nPointsX, nPointsY) = params.pointsNum;
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initTrackingPointsArray(in.prevPoints, width, height, nPointsX, nPointsY);
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cv::Size winSize(params.winSize, params.winSize);
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// OpenCV code /////////////////////////////////////////////////////////////
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{
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cv::calcOpticalFlowPyrLK(in.prevData, in.nextData, in.prevPoints,
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ocvOut.nextPoints, ocvOut.statuses, ocvOut.errors,
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winSize, params.maxLevel, params.criteria,
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params.flags, params.minEigThreshold);
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}
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// G-API code //////////////////////////////////////////////////////////////
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{
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GType inPrev, inNext;
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GArray<cv::Point2f> prevPts, predPts, nextPts;
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GArray<uchar> statuses;
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GArray<float> errors;
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std::tie(nextPts, statuses, errors) = cv::gapi::calcOpticalFlowPyrLK(
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inPrev, inNext,
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prevPts, predPts, winSize,
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params.maxLevel, params.criteria,
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params.flags, params.minEigThreshold);
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cv::GComputation c(cv::GIn(inPrev, inNext, prevPts, predPts),
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cv::GOut(nextPts, statuses, errors));
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c.apply(cv::gin(in.prevData, in.nextData, in.prevPoints, std::vector<cv::Point2f>{ }),
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cv::gout(gapiOut.nextPoints, gapiOut.statuses, gapiOut.errors),
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std::move(const_cast<cv::GCompileArgs&>(params.compileArgs)));
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return c;
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}
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}
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inline cv::GComputation runOCVnGAPIOptFlowLK(TestFunctional& testInst,
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std::vector<cv::Point2f>& inPts,
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const OptFlowLKTestParams& params,
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OptFlowLKTestOutput& ocvOut,
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OptFlowLKTestOutput& gapiOut)
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{
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testInst.initMatsFromImages(params.channels,
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params.fileNamePattern,
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params.format);
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OptFlowLKTestInput<cv::Mat> in{ testInst.in_mat1, testInst.in_mat2, inPts };
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return runOCVnGAPIOptFlowLK<cv::GMat>(in,
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testInst.in_mat1.cols,
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testInst.in_mat1.rows,
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params,
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ocvOut,
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gapiOut);
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}
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inline cv::GComputation runOCVnGAPIOptFlowLKForPyr(TestFunctional& testInst,
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OptFlowLKTestInput<std::vector<cv::Mat>>& in,
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const OptFlowLKTestParams& params,
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bool withDeriv,
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OptFlowLKTestOutput& ocvOut,
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OptFlowLKTestOutput& gapiOut)
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{
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testInst.initMatsFromImages(params.channels,
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params.fileNamePattern,
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params.format);
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cv::Size winSize(params.winSize, params.winSize);
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OptFlowLKTestParams updatedParams(params);
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updatedParams.maxLevel = cv::buildOpticalFlowPyramid(testInst.in_mat1, in.prevData,
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winSize, params.maxLevel, withDeriv);
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updatedParams.maxLevel = cv::buildOpticalFlowPyramid(testInst.in_mat2, in.nextData,
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winSize, params.maxLevel, withDeriv);
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return runOCVnGAPIOptFlowLK<cv::GArray<cv::GMat>>(in,
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testInst.in_mat1.cols,
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testInst.in_mat1.rows,
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updatedParams,
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ocvOut,
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gapiOut);
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}
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inline GComputation runOCVnGAPIOptFlowPipeline(TestFunctional& testInst,
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const BuildOpticalFlowPyramidTestParams& params,
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OptFlowLKTestOutput& outOCV,
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OptFlowLKTestOutput& outGAPI,
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std::vector<Point2f>& prevPoints)
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{
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testInst.initMatsFromImages(3, params.fileName, 1);
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initTrackingPointsArray(prevPoints, testInst.in_mat1.cols, testInst.in_mat1.rows, 15, 15);
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Size winSize = Size(params.winSize, params.winSize);
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// OpenCV code /////////////////////////////////////////////////////////////
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{
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std::vector<Mat> pyr1, pyr2;
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int maxLevel1 = cv::buildOpticalFlowPyramid(testInst.in_mat1, pyr1, winSize,
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params.maxLevel, params.withDerivatives,
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params.pyrBorder, params.derivBorder,
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params.tryReuseInputImage);
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int maxLevel2 = cv::buildOpticalFlowPyramid(testInst.in_mat2, pyr2, winSize,
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params.maxLevel, params.withDerivatives,
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params.pyrBorder, params.derivBorder,
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params.tryReuseInputImage);
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cv::calcOpticalFlowPyrLK(pyr1, pyr2, prevPoints,
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outOCV.nextPoints, outOCV.statuses, outOCV.errors,
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winSize, std::min(maxLevel1, maxLevel2));
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}
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// G-API code //////////////////////////////////////////////////////////////
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GMat in1, in2;
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GArray<GMat> gpyr1, gpyr2;
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GScalar gmaxLevel1, gmaxLevel2;
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GArray<cv::Point2f> gprevPts, gpredPts, gnextPts;
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GArray<uchar> gstatuses;
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GArray<float> gerrors;
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std::tie(gpyr1, gmaxLevel1) = cv::gapi::buildOpticalFlowPyramid(
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in1, winSize, params.maxLevel,
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params.withDerivatives, params.pyrBorder,
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params.derivBorder, params.tryReuseInputImage);
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std::tie(gpyr2, gmaxLevel2) = cv::gapi::buildOpticalFlowPyramid(
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in2, winSize, params.maxLevel,
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params.withDerivatives, params.pyrBorder,
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params.derivBorder, params.tryReuseInputImage);
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GScalar gmaxLevel = GMinScalar::on(gmaxLevel1, gmaxLevel2);
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std::tie(gnextPts, gstatuses, gerrors) = cv::gapi::calcOpticalFlowPyrLK(
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gpyr1, gpyr2, gprevPts, gpredPts, winSize,
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gmaxLevel);
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cv::GComputation c(GIn(in1, in2, gprevPts, gpredPts), cv::GOut(gnextPts, gstatuses, gerrors));
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c.apply(cv::gin(testInst.in_mat1, testInst.in_mat2, prevPoints, std::vector<cv::Point2f>{ }),
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cv::gout(outGAPI.nextPoints, outGAPI.statuses, outGAPI.errors),
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std::move(const_cast<cv::GCompileArgs&>(params.compileArgs)));
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return c;
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}
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inline void testBackgroundSubtractorStreaming(cv::GStreamingCompiled& gapiBackSub,
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const cv::Ptr<cv::BackgroundSubtractor>& pOCVBackSub,
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const int diffPercent, const int tolerance,
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const double lRate, const std::size_t testNumFrames)
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{
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cv::Mat frame, gapiForeground, ocvForeground;
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double numDiff = diffPercent / 100.0;
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gapiBackSub.start();
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EXPECT_TRUE(gapiBackSub.running());
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compare_f cmpF = AbsSimilarPoints(tolerance, numDiff).to_compare_f();
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// Comparison of G-API and OpenCV substractors
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std::size_t frames = 0u;
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while (frames <= testNumFrames && gapiBackSub.pull(cv::gout(frame, gapiForeground)))
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{
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pOCVBackSub->apply(frame, ocvForeground, lRate);
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EXPECT_TRUE(cmpF(gapiForeground, ocvForeground));
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frames++;
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}
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if (gapiBackSub.running())
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gapiBackSub.stop();
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EXPECT_LT(0u, frames);
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EXPECT_FALSE(gapiBackSub.running());
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}
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inline void initKalmanParams(const int type, const int dDim, const int mDim, const int cDim,
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cv::gapi::KalmanParams& kp)
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{
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kp.state = Mat::zeros(dDim, 1, type);
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cv::randu(kp.state, Scalar::all(0), Scalar::all(0.1));
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kp.errorCov = Mat::eye(dDim, dDim, type);
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kp.transitionMatrix = Mat::ones(dDim, dDim, type) * 2;
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kp.processNoiseCov = Mat::eye(dDim, dDim, type) * (1e-5);
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kp.measurementMatrix = Mat::eye(mDim, dDim, type) * 2;
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kp.measurementNoiseCov = Mat::eye(mDim, mDim, type) * (1e-5);
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if (cDim > 0)
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kp.controlMatrix = Mat::eye(dDim, cDim, type) * (1e-3);
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}
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inline void initKalmanFilter(const cv::gapi::KalmanParams& kp, const bool control,
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cv::KalmanFilter& ocvKalman)
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{
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kp.state.copyTo(ocvKalman.statePost);
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kp.errorCov.copyTo(ocvKalman.errorCovPost);
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kp.transitionMatrix.copyTo(ocvKalman.transitionMatrix);
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kp.measurementMatrix.copyTo(ocvKalman.measurementMatrix);
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kp.measurementNoiseCov.copyTo(ocvKalman.measurementNoiseCov);
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kp.processNoiseCov.copyTo(ocvKalman.processNoiseCov);
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if (control)
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kp.controlMatrix.copyTo(ocvKalman.controlMatrix);
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}
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||||
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#else // !HAVE_OPENCV_VIDEO
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||||
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inline cv::GComputation runOCVnGAPIBuildOptFlowPyramid(TestFunctional&,
|
||||
const BuildOpticalFlowPyramidTestParams&,
|
||||
BuildOpticalFlowPyramidTestOutput&,
|
||||
BuildOpticalFlowPyramidTestOutput&)
|
||||
{
|
||||
GAPI_Assert(0 && "This function shouldn't be called without opencv_video");
|
||||
}
|
||||
|
||||
inline cv::GComputation runOCVnGAPIOptFlowLK(TestFunctional&,
|
||||
std::vector<cv::Point2f>&,
|
||||
const OptFlowLKTestParams&,
|
||||
OptFlowLKTestOutput&,
|
||||
OptFlowLKTestOutput&)
|
||||
{
|
||||
GAPI_Assert(0 && "This function shouldn't be called without opencv_video");
|
||||
}
|
||||
|
||||
inline cv::GComputation runOCVnGAPIOptFlowLKForPyr(TestFunctional&,
|
||||
OptFlowLKTestInput<std::vector<cv::Mat>>&,
|
||||
const OptFlowLKTestParams&,
|
||||
bool,
|
||||
OptFlowLKTestOutput&,
|
||||
OptFlowLKTestOutput&)
|
||||
{
|
||||
GAPI_Assert(0 && "This function shouldn't be called without opencv_video");
|
||||
}
|
||||
|
||||
inline GComputation runOCVnGAPIOptFlowPipeline(TestFunctional&,
|
||||
const BuildOpticalFlowPyramidTestParams&,
|
||||
OptFlowLKTestOutput&,
|
||||
OptFlowLKTestOutput&,
|
||||
std::vector<Point2f>&)
|
||||
{
|
||||
GAPI_Assert(0 && "This function shouldn't be called without opencv_video");
|
||||
}
|
||||
|
||||
#endif // HAVE_OPENCV_VIDEO
|
||||
|
||||
} // namespace
|
||||
} // namespace opencv_test
|
||||
|
||||
// Note: namespace must match the namespace of the type of the printed object
|
||||
namespace cv { namespace gapi { namespace video
|
||||
{
|
||||
inline std::ostream& operator<<(std::ostream& os, const BackgroundSubtractorType op)
|
||||
{
|
||||
#define CASE(v) case BackgroundSubtractorType::v: os << #v; break
|
||||
switch (op)
|
||||
{
|
||||
CASE(TYPE_BS_MOG2);
|
||||
CASE(TYPE_BS_KNN);
|
||||
default: GAPI_Assert(false && "unknown BackgroundSubtractor type");
|
||||
}
|
||||
#undef CASE
|
||||
return os;
|
||||
}
|
||||
}}} // namespace cv::gapi::video
|
||||
|
||||
#endif // OPENCV_GAPI_VIDEO_TESTS_COMMON_HPP
|
||||
Reference in New Issue
Block a user