Open Source Computer Vision Library https://opencv.org/
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#include "perf_precomp.hpp"
using namespace std;
using namespace testing;
namespace cv
{
template<> void Ptr<CvBGStatModel>::delete_obj()
{
cvReleaseBGStatModel(&obj);
}
}
namespace {
//////////////////////////////////////////////////////
// BroxOpticalFlow
typedef pair<string, string> pair_string;
DEF_PARAM_TEST_1(ImagePair, pair_string);
PERF_TEST_P(ImagePair, Video_BroxOpticalFlow, Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(10);
cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0);
frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0);
if (runOnGpu)
{
cv::gpu::GpuMat d_frame0(frame0);
cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat d_u;
cv::gpu::GpuMat d_v;
cv::gpu::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
d_flow(d_frame0, d_frame1, d_u, d_v);
TEST_CYCLE()
{
d_flow(d_frame0, d_frame1, d_u, d_v);
}
}
else
{
FAIL();
}
}
//////////////////////////////////////////////////////
// InterpolateFrames
PERF_TEST_P(ImagePair, Video_InterpolateFrames, Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0);
frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0);
if (runOnGpu)
{
cv::gpu::GpuMat d_frame0(frame0);
cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat d_fu, d_fv;
cv::gpu::GpuMat d_bu, d_bv;
cv::gpu::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
d_flow(d_frame0, d_frame1, d_fu, d_fv);
d_flow(d_frame1, d_frame0, d_bu, d_bv);
cv::gpu::GpuMat d_newFrame;
cv::gpu::GpuMat d_buf;
cv::gpu::interpolateFrames(d_frame0, d_frame1, d_fu, d_fv, d_bu, d_bv, 0.5f, d_newFrame, d_buf);
TEST_CYCLE()
{
cv::gpu::interpolateFrames(d_frame0, d_frame1, d_fu, d_fv, d_bu, d_bv, 0.5f, d_newFrame, d_buf);
}
}
else
{
FAIL();
}
}
//////////////////////////////////////////////////////
// CreateOpticalFlowNeedleMap
PERF_TEST_P(ImagePair, Video_CreateOpticalFlowNeedleMap, Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0);
frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0);
if (runOnGpu)
{
cv::gpu::GpuMat d_frame0(frame0);
cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat d_u;
cv::gpu::GpuMat d_v;
cv::gpu::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
d_flow(d_frame0, d_frame1, d_u, d_v);
cv::gpu::GpuMat d_vertex, d_colors;
cv::gpu::createOpticalFlowNeedleMap(d_u, d_v, d_vertex, d_colors);
TEST_CYCLE()
{
cv::gpu::createOpticalFlowNeedleMap(d_u, d_v, d_vertex, d_colors);
}
}
else
{
FAIL();
}
}
//////////////////////////////////////////////////////
// GoodFeaturesToTrack
DEF_PARAM_TEST(Image_MinDistance, string, double);
PERF_TEST_P(Image_MinDistance, Video_GoodFeaturesToTrack, Combine(Values<string>("gpu/perf/aloe.jpg"), Values(0.0, 3.0)))
{
string fileName = GET_PARAM(0);
double minDistance = GET_PARAM(1);
cv::Mat image = readImage(fileName, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(image.empty());
if (runOnGpu)
{
cv::gpu::GoodFeaturesToTrackDetector_GPU d_detector(8000, 0.01, minDistance);
cv::gpu::GpuMat d_image(image);
cv::gpu::GpuMat d_pts;
d_detector(d_image, d_pts);
TEST_CYCLE()
{
d_detector(d_image, d_pts);
}
}
else
{
cv::Mat pts;
cv::goodFeaturesToTrack(image, pts, 8000, 0.01, minDistance);
TEST_CYCLE()
{
cv::goodFeaturesToTrack(image, pts, 8000, 0.01, minDistance);
}
}
}
//////////////////////////////////////////////////////
// PyrLKOpticalFlowSparse
DEF_PARAM_TEST(ImagePair_Gray_NPts_WinSz_Levels_Iters, pair_string, bool, int, int, int, int);
PERF_TEST_P(ImagePair_Gray_NPts_WinSz_Levels_Iters, Video_PyrLKOpticalFlowSparse, Combine(
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")),
Bool(),
Values(1000, 2000, 4000, 8000),
Values(9, 13, 17, 21),
Values(1, 2, 3),
Values(1, 10, 30)))
{
declare.time(20.0);
pair_string imagePair = GET_PARAM(0);
bool useGray = GET_PARAM(1);
int points = GET_PARAM(2);
int winSize = GET_PARAM(3);
int levels = GET_PARAM(4);
int iters = GET_PARAM(5);
cv::Mat frame0 = readImage(imagePair.first, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage(imagePair.second, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame1.empty());
cv::Mat gray_frame;
if (useGray)
gray_frame = frame0;
else
cv::cvtColor(frame0, gray_frame, cv::COLOR_BGR2GRAY);
cv::Mat pts;
cv::goodFeaturesToTrack(gray_frame, pts, points, 0.01, 0.0);
if (runOnGpu)
{
cv::gpu::GpuMat d_pts(pts.reshape(2, 1));
cv::gpu::PyrLKOpticalFlow d_pyrLK;
d_pyrLK.winSize = cv::Size(winSize, winSize);
d_pyrLK.maxLevel = levels - 1;
d_pyrLK.iters = iters;
cv::gpu::GpuMat d_frame0(frame0);
cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat d_nextPts;
cv::gpu::GpuMat d_status;
d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status);
TEST_CYCLE()
{
d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status);
}
}
else
{
cv::Mat nextPts;
cv::Mat status;
cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(),
cv::Size(winSize, winSize), levels - 1,
cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, iters, 0.01));
TEST_CYCLE()
{
cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(),
cv::Size(winSize, winSize), levels - 1,
cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, iters, 0.01));
}
}
}
//////////////////////////////////////////////////////
// PyrLKOpticalFlowDense
DEF_PARAM_TEST(ImagePair_WinSz_Levels_Iters, pair_string, int, int, int);
PERF_TEST_P(ImagePair_WinSz_Levels_Iters, Video_PyrLKOpticalFlowDense, Combine(
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")),
Values(3, 5, 7, 9, 13, 17, 21),
Values(1, 2, 3),
Values(1, 10)))
{
declare.time(30);
pair_string imagePair = GET_PARAM(0);
int winSize = GET_PARAM(1);
int levels = GET_PARAM(2);
int iters = GET_PARAM(3);
cv::Mat frame0 = readImage(imagePair.first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage(imagePair.second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
if (runOnGpu)
{
cv::gpu::GpuMat d_frame0(frame0);
cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat d_u;
cv::gpu::GpuMat d_v;
cv::gpu::PyrLKOpticalFlow d_pyrLK;
d_pyrLK.winSize = cv::Size(winSize, winSize);
d_pyrLK.maxLevel = levels - 1;
d_pyrLK.iters = iters;
d_pyrLK.dense(d_frame0, d_frame1, d_u, d_v);
TEST_CYCLE()
{
d_pyrLK.dense(d_frame0, d_frame1, d_u, d_v);
}
}
else
{
FAIL();
}
}
//////////////////////////////////////////////////////
// FarnebackOpticalFlow
PERF_TEST_P(ImagePair, Video_FarnebackOpticalFlow, Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(10);
cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
int numLevels = 5;
double pyrScale = 0.5;
int winSize = 13;
int numIters = 10;
int polyN = 5;
double polySigma = 1.1;
int flags = 0;
if (runOnGpu)
{
cv::gpu::GpuMat d_frame0(frame0);
cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat d_u;
cv::gpu::GpuMat d_v;
cv::gpu::FarnebackOpticalFlow d_farneback;
d_farneback.numLevels = numLevels;
d_farneback.pyrScale = pyrScale;
d_farneback.winSize = winSize;
d_farneback.numIters = numIters;
d_farneback.polyN = polyN;
d_farneback.polySigma = polySigma;
d_farneback.flags = flags;
d_farneback(d_frame0, d_frame1, d_u, d_v);
TEST_CYCLE()
{
d_farneback(d_frame0, d_frame1, d_u, d_v);
}
}
else
{
cv::Mat flow;
cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags);
TEST_CYCLE()
{
cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags);
}
}
}
//////////////////////////////////////////////////////
// FGDStatModel
DEF_PARAM_TEST_1(Video, string);
PERF_TEST_P(Video, Video_FGDStatModel, Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"))
{
declare.time(60);
string inputFile = perf::TestBase::getDataPath(GetParam());
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cap >> frame;
ASSERT_FALSE(frame.empty());
if (runOnGpu)
{
cv::gpu::GpuMat d_frame(frame);
cv::gpu::FGDStatModel d_model(4);
d_model.create(d_frame);
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
d_frame.upload(frame);
startTimer(); next();
d_model.update(d_frame);
stopTimer();
}
}
else
{
IplImage ipl_frame = frame;
cv::Ptr<CvBGStatModel> model(cvCreateFGDStatModel(&ipl_frame));
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
ipl_frame = frame;
startTimer(); next();
cvUpdateBGStatModel(&ipl_frame, model);
stopTimer();
}
}
}
//////////////////////////////////////////////////////
// MOG
DEF_PARAM_TEST(Video_Cn_LearningRate, string, int, double);
PERF_TEST_P(Video_Cn_LearningRate, Video_MOG, Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"), GPU_CHANNELS_1_3_4, Values(0.0, 0.01)))
{
string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
int cn = GET_PARAM(1);
float learningRate = static_cast<float>(GET_PARAM(2));
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
if (runOnGpu)
{
cv::gpu::GpuMat d_frame(frame);
cv::gpu::MOG_GPU d_mog;
cv::gpu::GpuMat d_foreground;
d_mog(d_frame, d_foreground, learningRate);
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
d_frame.upload(frame);
startTimer(); next();
d_mog(d_frame, d_foreground, learningRate);
stopTimer();
}
}
else
{
cv::BackgroundSubtractorMOG mog;
cv::Mat foreground;
mog(frame, foreground, learningRate);
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
startTimer(); next();
mog(frame, foreground, learningRate);
stopTimer();
}
}
}
//////////////////////////////////////////////////////
// MOG2
DEF_PARAM_TEST(Video_Cn, string, int);
PERF_TEST_P(Video_Cn, Video_MOG2, Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"), GPU_CHANNELS_1_3_4))
{
string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
int cn = GET_PARAM(1);
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
if (runOnGpu)
{
cv::gpu::GpuMat d_frame(frame);
cv::gpu::MOG2_GPU d_mog2;
cv::gpu::GpuMat d_foreground;
d_mog2(d_frame, d_foreground);
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
d_frame.upload(frame);
startTimer(); next();
d_mog2(d_frame, d_foreground);
stopTimer();
}
}
else
{
cv::BackgroundSubtractorMOG2 mog2;
cv::Mat foreground;
mog2(frame, foreground);
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
startTimer(); next();
mog2(frame, foreground);
stopTimer();
}
}
}
//////////////////////////////////////////////////////
// MOG2GetBackgroundImage
PERF_TEST_P(Video_Cn, Video_MOG2GetBackgroundImage, Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"), GPU_CHANNELS_1_3_4))
{
string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
int cn = GET_PARAM(1);
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
if (runOnGpu)
{
cv::gpu::GpuMat d_frame;
cv::gpu::MOG2_GPU d_mog2;
cv::gpu::GpuMat d_foreground;
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
d_frame.upload(frame);
d_mog2(d_frame, d_foreground);
}
cv::gpu::GpuMat d_background;
d_mog2.getBackgroundImage(d_background);
TEST_CYCLE()
{
d_mog2.getBackgroundImage(d_background);
}
}
else
{
cv::BackgroundSubtractorMOG2 mog2;
cv::Mat foreground;
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
mog2(frame, foreground);
}
cv::Mat background;
mog2.getBackgroundImage(background);
TEST_CYCLE()
{
mog2.getBackgroundImage(background);
}
}
}
//////////////////////////////////////////////////////
// VIBE
PERF_TEST_P(Video_Cn, Video_VIBE, Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"), GPU_CHANNELS_1_3_4))
{
string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
int cn = GET_PARAM(1);
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
if (runOnGpu)
{
cv::gpu::GpuMat d_frame(frame);
cv::gpu::VIBE_GPU d_vibe;
cv::gpu::GpuMat d_foreground;
d_vibe(d_frame, d_foreground);
for (int i = 0; i < 10; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
d_frame.upload(frame);
startTimer(); next();
d_vibe(d_frame, d_foreground);
stopTimer();
}
}
else
{
FAIL();
}
}
//////////////////////////////////////////////////////
// GMG
DEF_PARAM_TEST(Video_Cn_MaxFeatures, string, int, int);
PERF_TEST_P(Video_Cn_MaxFeatures, Video_GMG, Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"), GPU_CHANNELS_1_3_4, Values(20, 40, 60)))
{
std::string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
int cn = GET_PARAM(1);
int maxFeatures = GET_PARAM(2);
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cap >> frame;
ASSERT_FALSE(frame.empty());
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
if (runOnGpu)
{
cv::gpu::GpuMat d_frame(frame);
cv::gpu::GpuMat d_fgmask;
cv::gpu::GMG_GPU d_gmg;
d_gmg.maxFeatures = maxFeatures;
d_gmg(d_frame, d_fgmask);
for (int i = 0; i < 150; ++i)
{
cap >> frame;
if (frame.empty())
{
cap.open(inputFile);
cap >> frame;
}
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
d_frame.upload(frame);
startTimer(); next();
d_gmg(d_frame, d_fgmask);
stopTimer();
}
}
else
{
cv::Mat fgmask;
cv::Mat zeros(frame.size(), CV_8UC1, cv::Scalar::all(0));
cv::BackgroundSubtractorGMG gmg;
gmg.set("maxFeatures", maxFeatures);
gmg.initialize(frame.size(), 0.0, 255.0);
gmg(frame, fgmask);
for (int i = 0; i < 150; ++i)
{
cap >> frame;
if (frame.empty())
{
cap.open(inputFile);
cap >> frame;
}
if (cn != 3)
{
cv::Mat temp;
if (cn == 1)
cv::cvtColor(frame, temp, cv::COLOR_BGR2GRAY);
else
cv::cvtColor(frame, temp, cv::COLOR_BGR2BGRA);
cv::swap(temp, frame);
}
startTimer(); next();
gmg(frame, fgmask);
stopTimer();
}
}
}
//////////////////////////////////////////////////////
// VideoWriter
PERF_TEST_P(Video, Video_VideoWriter, Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"))
{
declare.time(30);
string inputFile = perf::TestBase::getDataPath(GetParam());
string outputFile = cv::tempfile(".avi");
const double FPS = 25.0;
cv::VideoCapture reader(inputFile);
ASSERT_TRUE( reader.isOpened() );
cv::Mat frame;
if (runOnGpu)
{
cv::gpu::VideoWriter_GPU d_writer;
cv::gpu::GpuMat d_frame;
for (int i = 0; i < 10; ++i)
{
reader >> frame;
ASSERT_FALSE(frame.empty());
d_frame.upload(frame);
if (!d_writer.isOpened())
d_writer.open(outputFile, frame.size(), FPS);
startTimer(); next();
d_writer.write(d_frame);
stopTimer();
}
}
else
{
cv::VideoWriter writer;
for (int i = 0; i < 10; ++i)
{
reader >> frame;
ASSERT_FALSE(frame.empty());
if (!writer.isOpened())
writer.open(outputFile, CV_FOURCC('X', 'V', 'I', 'D'), FPS, frame.size());
startTimer(); next();
writer.write(frame);
stopTimer();
}
}
}
//////////////////////////////////////////////////////
// VideoReader
PERF_TEST_P(Video, Video_VideoReader, Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"))
{
declare.time(20);
string inputFile = perf::TestBase::getDataPath(GetParam());
if (runOnGpu)
{
cv::gpu::VideoReader_GPU d_reader(inputFile);
ASSERT_TRUE( d_reader.isOpened() );
cv::gpu::GpuMat d_frame;
d_reader.read(d_frame);
TEST_CYCLE_N(10)
{
d_reader.read(d_frame);
}
}
else
{
cv::VideoCapture reader(inputFile);
ASSERT_TRUE( reader.isOpened() );
cv::Mat frame;
reader >> frame;
TEST_CYCLE_N(10)
{
reader >> frame;
}
}
}
} // namespace