Open Source Computer Vision Library https://opencv.org/
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#include "perf_precomp.hpp"
#ifdef HAVE_CUDA
//////////////////////////////////////////////////////
// BroxOpticalFlow
GPU_PERF_TEST_1(BroxOpticalFlow, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
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cv::Mat frame0_host = readImage("gpu/opticalflow/frame0.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0_host.empty());
cv::Mat frame1_host = readImage("gpu/opticalflow/frame1.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1_host.empty());
frame0_host.convertTo(frame0_host, CV_32FC1, 1.0 / 255.0);
frame1_host.convertTo(frame1_host, CV_32FC1, 1.0 / 255.0);
cv::gpu::GpuMat frame0(frame0_host);
cv::gpu::GpuMat frame1(frame1_host);
cv::gpu::GpuMat u;
cv::gpu::GpuMat 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(frame0, frame1, u, v);
declare.time(10);
TEST_CYCLE()
{
d_flow(frame0, frame1, u, v);
}
}
INSTANTIATE_TEST_CASE_P(Video, BroxOpticalFlow, ALL_DEVICES);
//////////////////////////////////////////////////////
// InterpolateFrames
GPU_PERF_TEST_1(InterpolateFrames, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat frame0_host = readImage("gpu/perf/aloe.jpg", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0_host.empty());
cv::Mat frame1_host = readImage("gpu/perf/aloeR.jpg", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1_host.empty());
frame0_host.convertTo(frame0_host, CV_32FC1, 1.0 / 255.0);
frame1_host.convertTo(frame1_host, CV_32FC1, 1.0 / 255.0);
cv::gpu::GpuMat frame0(frame0_host);
cv::gpu::GpuMat frame1(frame1_host);
cv::gpu::GpuMat fu, fv;
cv::gpu::GpuMat bu, 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(frame0, frame1, fu, fv);
d_flow(frame1, frame0, bu, bv);
cv::gpu::GpuMat newFrame;
cv::gpu::GpuMat buf;
cv::gpu::interpolateFrames(frame0, frame1, fu, fv, bu, bv, 0.5f, newFrame, buf);
TEST_CYCLE()
{
cv::gpu::interpolateFrames(frame0, frame1, fu, fv, bu, bv, 0.5f, newFrame, buf);
}
}
INSTANTIATE_TEST_CASE_P(Video, InterpolateFrames, ALL_DEVICES);
//////////////////////////////////////////////////////
// CreateOpticalFlowNeedleMap
GPU_PERF_TEST_1(CreateOpticalFlowNeedleMap, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat frame0_host = readImage("gpu/perf/aloe.jpg", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0_host.empty());
cv::Mat frame1_host = readImage("gpu/perf/aloeR.jpg", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1_host.empty());
frame0_host.convertTo(frame0_host, CV_32FC1, 1.0 / 255.0);
frame1_host.convertTo(frame1_host, CV_32FC1, 1.0 / 255.0);
cv::gpu::GpuMat frame0(frame0_host);
cv::gpu::GpuMat frame1(frame1_host);
cv::gpu::GpuMat u, 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(frame0, frame1, u, v);
cv::gpu::GpuMat vertex, colors;
cv::gpu::createOpticalFlowNeedleMap(u, v, vertex, colors);
TEST_CYCLE()
{
cv::gpu::createOpticalFlowNeedleMap(u, v, vertex, colors);
}
}
INSTANTIATE_TEST_CASE_P(Video, CreateOpticalFlowNeedleMap, ALL_DEVICES);
//////////////////////////////////////////////////////
// GoodFeaturesToTrack
IMPLEMENT_PARAM_CLASS(MinDistance, double)
GPU_PERF_TEST(GoodFeaturesToTrack, cv::gpu::DeviceInfo, MinDistance)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
double minDistance = GET_PARAM(1);
cv::Mat image_host = readImage("gpu/perf/aloe.jpg", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(image_host.empty());
cv::gpu::GoodFeaturesToTrackDetector_GPU detector(8000, 0.01, minDistance);
cv::gpu::GpuMat image(image_host);
cv::gpu::GpuMat pts;
detector(image, pts);
TEST_CYCLE()
{
detector(image, pts);
}
}
INSTANTIATE_TEST_CASE_P(Video, GoodFeaturesToTrack, testing::Combine(
ALL_DEVICES,
testing::Values(MinDistance(0.0), MinDistance(3.0))));
//////////////////////////////////////////////////////
// PyrLKOpticalFlowSparse
IMPLEMENT_PARAM_CLASS(GraySource, bool)
IMPLEMENT_PARAM_CLASS(Points, int)
IMPLEMENT_PARAM_CLASS(WinSize, int)
IMPLEMENT_PARAM_CLASS(Levels, int)
IMPLEMENT_PARAM_CLASS(Iters, int)
GPU_PERF_TEST(PyrLKOpticalFlowSparse, cv::gpu::DeviceInfo, GraySource, Points, WinSize, Levels, Iters)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
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_host = readImage("gpu/opticalflow/frame0.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame0_host.empty());
cv::Mat frame1_host = readImage("gpu/opticalflow/frame1.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame1_host.empty());
cv::Mat gray_frame;
if (useGray)
gray_frame = frame0_host;
else
cv::cvtColor(frame0_host, gray_frame, cv::COLOR_BGR2GRAY);
cv::gpu::GpuMat pts;
cv::gpu::GoodFeaturesToTrackDetector_GPU detector(points, 0.01, 0.0);
detector(cv::gpu::GpuMat(gray_frame), pts);
cv::gpu::PyrLKOpticalFlow pyrLK;
pyrLK.winSize = cv::Size(winSize, winSize);
pyrLK.maxLevel = levels - 1;
pyrLK.iters = iters;
cv::gpu::GpuMat frame0(frame0_host);
cv::gpu::GpuMat frame1(frame1_host);
cv::gpu::GpuMat nextPts;
cv::gpu::GpuMat status;
pyrLK.sparse(frame0, frame1, pts, nextPts, status);
TEST_CYCLE()
{
pyrLK.sparse(frame0, frame1, pts, nextPts, status);
}
}
INSTANTIATE_TEST_CASE_P(Video, PyrLKOpticalFlowSparse, testing::Combine(
ALL_DEVICES,
testing::Values(GraySource(true), GraySource(false)),
testing::Values(Points(1000), Points(2000), Points(4000), Points(8000)),
testing::Values(WinSize(9), WinSize(13), WinSize(17), WinSize(21)),
testing::Values(Levels(1), Levels(2), Levels(3)),
testing::Values(Iters(1), Iters(10), Iters(30))));
//////////////////////////////////////////////////////
// PyrLKOpticalFlowDense
GPU_PERF_TEST(PyrLKOpticalFlowDense, cv::gpu::DeviceInfo, WinSize, Levels, Iters)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
int winSize = GET_PARAM(1);
int levels = GET_PARAM(2);
int iters = GET_PARAM(3);
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cv::Mat frame0_host = readImage("gpu/opticalflow/frame0.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0_host.empty());
cv::Mat frame1_host = readImage("gpu/opticalflow/frame1.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1_host.empty());
cv::gpu::GpuMat frame0(frame0_host);
cv::gpu::GpuMat frame1(frame1_host);
cv::gpu::GpuMat u;
cv::gpu::GpuMat v;
cv::gpu::PyrLKOpticalFlow pyrLK;
pyrLK.winSize = cv::Size(winSize, winSize);
pyrLK.maxLevel = levels - 1;
pyrLK.iters = iters;
pyrLK.dense(frame0, frame1, u, v);
declare.time(30);
TEST_CYCLE()
{
pyrLK.dense(frame0, frame1, u, v);
}
}
INSTANTIATE_TEST_CASE_P(Video, PyrLKOpticalFlowDense, testing::Combine(
ALL_DEVICES,
testing::Values(WinSize(3), WinSize(5), WinSize(7), WinSize(9), WinSize(13), WinSize(17), WinSize(21)),
testing::Values(Levels(1), Levels(2), Levels(3)),
testing::Values(Iters(1), Iters(10))));
//////////////////////////////////////////////////////
// FarnebackOpticalFlowTest
GPU_PERF_TEST_1(FarnebackOpticalFlowTest, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat frame0_host = readImage("gpu/opticalflow/frame0.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0_host.empty());
cv::Mat frame1_host = readImage("gpu/opticalflow/frame1.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1_host.empty());
cv::gpu::GpuMat frame0(frame0_host);
cv::gpu::GpuMat frame1(frame1_host);
cv::gpu::GpuMat u;
cv::gpu::GpuMat v;
cv::gpu::FarnebackOpticalFlow farneback;
farneback(frame0, frame1, u, v);
declare.time(10);
TEST_CYCLE()
{
farneback(frame0, frame1, u, v);
}
}
INSTANTIATE_TEST_CASE_P(Video, FarnebackOpticalFlowTest, ALL_DEVICES);
//////////////////////////////////////////////////////
// FGDStatModel
GPU_PERF_TEST(FGDStatModel, cv::gpu::DeviceInfo, std::string)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cap >> frame;
ASSERT_FALSE(frame.empty());
cv::gpu::GpuMat d_frame(frame);
cv::gpu::FGDStatModel d_model(4);
d_model.create(d_frame);
declare.time(10);
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();
}
}
INSTANTIATE_TEST_CASE_P(Video, FGDStatModel, testing::Combine(
ALL_DEVICES,
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi"))));
//////////////////////////////////////////////////////
// MOG
IMPLEMENT_PARAM_CLASS(LearningRate, double)
GPU_PERF_TEST(MOG, cv::gpu::DeviceInfo, std::string, Channels, LearningRate)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
int cn = GET_PARAM(2);
double learningRate = GET_PARAM(3);
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cv::gpu::GpuMat d_frame;
cv::gpu::MOG_GPU mog;
cv::gpu::GpuMat foreground;
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);
mog(d_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);
}
d_frame.upload(frame);
startTimer(); next();
mog(d_frame, foreground, learningRate);
stopTimer();
}
}
INSTANTIATE_TEST_CASE_P(Video, MOG, testing::Combine(
ALL_DEVICES,
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi")),
testing::Values(Channels(1), Channels(3), Channels(4)),
testing::Values(LearningRate(0.0), LearningRate(0.01))));
//////////////////////////////////////////////////////
// MOG2
GPU_PERF_TEST(MOG2_update, cv::gpu::DeviceInfo, std::string, Channels)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
int cn = GET_PARAM(2);
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cv::gpu::GpuMat d_frame;
cv::gpu::MOG2_GPU mog2;
cv::gpu::GpuMat foreground;
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);
mog2(d_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);
}
d_frame.upload(frame);
startTimer(); next();
mog2(d_frame, foreground);
stopTimer();
}
}
INSTANTIATE_TEST_CASE_P(Video, MOG2_update, testing::Combine(
ALL_DEVICES,
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi")),
testing::Values(Channels(1), Channels(3), Channels(4))));
GPU_PERF_TEST(MOG2_getBackgroundImage, cv::gpu::DeviceInfo, std::string, Channels)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
int cn = GET_PARAM(2);
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cv::gpu::GpuMat d_frame;
cv::gpu::MOG2_GPU mog2;
cv::gpu::GpuMat 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);
mog2(d_frame, foreground);
}
cv::gpu::GpuMat background;
mog2.getBackgroundImage(background);
TEST_CYCLE()
{
mog2.getBackgroundImage(background);
}
}
INSTANTIATE_TEST_CASE_P(Video, MOG2_getBackgroundImage, testing::Combine(
ALL_DEVICES,
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi")),
testing::Values(Channels(1), Channels(3), Channels(4))));
//////////////////////////////////////////////////////
// VideoWriter
#ifdef WIN32
GPU_PERF_TEST(VideoWriter, cv::gpu::DeviceInfo, std::string)
{
const double FPS = 25.0;
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
std::string outputFile = cv::tempfile(".avi");
cv::VideoCapture reader(inputFile);
ASSERT_TRUE( reader.isOpened() );
cv::gpu::VideoWriter_GPU d_writer;
cv::Mat frame;
cv::gpu::GpuMat d_frame;
declare.time(10);
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();
}
}
INSTANTIATE_TEST_CASE_P(Video, VideoWriter, testing::Combine(
ALL_DEVICES,
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi"))));
#endif // WIN32
//////////////////////////////////////////////////////
// VideoReader
GPU_PERF_TEST(VideoReader, cv::gpu::DeviceInfo, std::string)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
std::string inputFile = perf::TestBase::getDataPath(std::string("gpu/video/") + GET_PARAM(1));
cv::gpu::VideoReader_GPU reader(inputFile);
ASSERT_TRUE( reader.isOpened() );
cv::gpu::GpuMat frame;
reader.read(frame);
declare.time(20);
TEST_CYCLE_N(10)
{
reader.read(frame);
}
}
INSTANTIATE_TEST_CASE_P(Video, VideoReader, testing::Combine(
ALL_DEVICES,
testing::Values(std::string("768x576.avi"), std::string("1920x1080.avi"))));
#endif