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