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opencv/modules/gpu/perf/perf_video.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "perf_precomp.hpp"
#include "opencv2/legacy.hpp"
using namespace std;
using namespace testing;
using namespace perf;
#if defined(HAVE_XINE) || \
defined(HAVE_GSTREAMER) || \
defined(HAVE_QUICKTIME) || \
defined(HAVE_AVFOUNDATION) || \
defined(HAVE_FFMPEG) || \
defined(WIN32) /* assume that we have ffmpeg */
# define BUILD_WITH_VIDEO_INPUT_SUPPORT 1
#else
# define BUILD_WITH_VIDEO_INPUT_SUPPORT 0
#endif
namespace cv
{
template<> void Ptr<CvBGStatModel>::delete_obj()
{
cvReleaseBGStatModel(&obj);
}
}
//////////////////////////////////////////////////////
// InterpolateFrames
typedef pair<string, string> pair_string;
DEF_PARAM_TEST_1(ImagePair, pair_string);
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 (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_frame0(frame0);
const 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 newFrame;
cv::gpu::GpuMat d_buf;
TEST_CYCLE() cv::gpu::interpolateFrames(d_frame0, d_frame1, d_fu, d_fv, d_bu, d_bv, 0.5f, newFrame, d_buf);
GPU_SANITY_CHECK(newFrame);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////
// 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 (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_frame0(frame0);
const cv::gpu::GpuMat d_frame1(frame1);
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(d_frame0, d_frame1, u, v);
cv::gpu::GpuMat vertex, colors;
TEST_CYCLE() cv::gpu::createOpticalFlowNeedleMap(u, v, vertex, colors);
GPU_SANITY_CHECK(vertex);
GPU_SANITY_CHECK(colors);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////
// GoodFeaturesToTrack
DEF_PARAM_TEST(Image_MinDistance, string, double);
PERF_TEST_P(Image_MinDistance, Video_GoodFeaturesToTrack,
Combine(Values<string>("gpu/perf/aloe.png"),
Values(0.0, 3.0)))
{
const string fileName = GET_PARAM(0);
const double minDistance = GET_PARAM(1);
const cv::Mat image = readImage(fileName, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(image.empty());
const int maxCorners = 8000;
const double qualityLevel = 0.01;
if (PERF_RUN_GPU())
{
cv::gpu::GoodFeaturesToTrackDetector_GPU d_detector(maxCorners, qualityLevel, minDistance);
const cv::gpu::GpuMat d_image(image);
cv::gpu::GpuMat pts;
TEST_CYCLE() d_detector(d_image, pts);
GPU_SANITY_CHECK(pts);
}
else
{
cv::Mat pts;
TEST_CYCLE() cv::goodFeaturesToTrack(image, pts, maxCorners, qualityLevel, minDistance);
CPU_SANITY_CHECK(pts);
}
}
//////////////////////////////////////////////////////
// BroxOpticalFlow
PERF_TEST_P(ImagePair, Video_BroxOpticalFlow,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(300);
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 (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_frame0(frame0);
const cv::gpu::GpuMat d_frame1(frame1);
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*/);
TEST_CYCLE() d_flow(d_frame0, d_frame1, u, v);
GPU_SANITY_CHECK(u);
GPU_SANITY_CHECK(v);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////
// 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(8000),
Values(21),
Values(1, 3),
Values(1, 30)))
{
declare.time(20.0);
const pair_string imagePair = GET_PARAM(0);
const bool useGray = GET_PARAM(1);
const int points = GET_PARAM(2);
const int winSize = GET_PARAM(3);
const int levels = GET_PARAM(4);
const int iters = GET_PARAM(5);
const cv::Mat frame0 = readImage(imagePair.first, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame0.empty());
const 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 (PERF_RUN_GPU())
{
const 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;
const cv::gpu::GpuMat d_frame0(frame0);
const cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat nextPts;
cv::gpu::GpuMat status;
TEST_CYCLE() d_pyrLK.sparse(d_frame0, d_frame1, d_pts, nextPts, status);
GPU_SANITY_CHECK(nextPts);
GPU_SANITY_CHECK(status);
}
else
{
cv::Mat nextPts;
cv::Mat status;
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));
}
CPU_SANITY_CHECK(nextPts);
CPU_SANITY_CHECK(status);
}
}
//////////////////////////////////////////////////////
// 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, 3),
Values(1, 10)))
{
declare.time(30);
const pair_string imagePair = GET_PARAM(0);
const int winSize = GET_PARAM(1);
const int levels = GET_PARAM(2);
const int iters = GET_PARAM(3);
const cv::Mat frame0 = readImage(imagePair.first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(imagePair.second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_frame0(frame0);
const cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat u;
cv::gpu::GpuMat v;
cv::gpu::PyrLKOpticalFlow d_pyrLK;
d_pyrLK.winSize = cv::Size(winSize, winSize);
d_pyrLK.maxLevel = levels - 1;
d_pyrLK.iters = iters;
TEST_CYCLE() d_pyrLK.dense(d_frame0, d_frame1, u, v);
GPU_SANITY_CHECK(u);
GPU_SANITY_CHECK(v);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////
// FarnebackOpticalFlow
PERF_TEST_P(ImagePair, Video_FarnebackOpticalFlow,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(10);
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
const int numLevels = 5;
const double pyrScale = 0.5;
const int winSize = 13;
const int numIters = 10;
const int polyN = 5;
const double polySigma = 1.1;
const int flags = 0;
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_frame0(frame0);
const cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat u;
cv::gpu::GpuMat 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;
TEST_CYCLE() d_farneback(d_frame0, d_frame1, u, v);
GPU_SANITY_CHECK(u, 1e-4);
GPU_SANITY_CHECK(v, 1e-4);
}
else
{
cv::Mat flow;
TEST_CYCLE() cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags);
CPU_SANITY_CHECK(flow);
}
}
//////////////////////////////////////////////////////
// OpticalFlowDual_TVL1
PERF_TEST_P(ImagePair, Video_OpticalFlowDual_TVL1,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(20);
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_frame0(frame0);
const cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat u;
cv::gpu::GpuMat v;
cv::gpu::OpticalFlowDual_TVL1_GPU d_alg;
TEST_CYCLE() d_alg(d_frame0, d_frame1, u, v);
GPU_SANITY_CHECK(u, 1e-2);
GPU_SANITY_CHECK(v, 1e-2);
}
else
{
cv::Mat flow;
cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
alg->set("medianFiltering", 1);
alg->set("innerIterations", 1);
alg->set("outerIterations", 300);
TEST_CYCLE() alg->calc(frame0, frame1, flow);
CPU_SANITY_CHECK(flow);
}
}
//////////////////////////////////////////////////////
// OpticalFlowBM
void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr,
cv::Size bSize, cv::Size shiftSize, cv::Size maxRange, int usePrevious,
cv::Mat& velx, cv::Mat& vely)
{
cv::Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height);
velx.create(sz, CV_32FC1);
vely.create(sz, CV_32FC1);
CvMat cvprev = prev;
CvMat cvcurr = curr;
CvMat cvvelx = velx;
CvMat cvvely = vely;
cvCalcOpticalFlowBM(&cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely);
}
PERF_TEST_P(ImagePair, Video_OpticalFlowBM,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(400);
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
const cv::Size block_size(16, 16);
const cv::Size shift_size(1, 1);
const cv::Size max_range(16, 16);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_frame0(frame0);
const cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat u, v, buf;
TEST_CYCLE() cv::gpu::calcOpticalFlowBM(d_frame0, d_frame1, block_size, shift_size, max_range, false, u, v, buf);
GPU_SANITY_CHECK(u);
GPU_SANITY_CHECK(v);
}
else
{
cv::Mat u, v;
TEST_CYCLE() calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, u, v);
CPU_SANITY_CHECK(u);
CPU_SANITY_CHECK(v);
}
}
PERF_TEST_P(ImagePair, Video_FastOpticalFlowBM,
Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
declare.time(400);
const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
const cv::Size block_size(16, 16);
const cv::Size shift_size(1, 1);
const cv::Size max_range(16, 16);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_frame0(frame0);
const cv::gpu::GpuMat d_frame1(frame1);
cv::gpu::GpuMat u, v;
cv::gpu::FastOpticalFlowBM fastBM;
TEST_CYCLE() fastBM(d_frame0, d_frame1, u, v, max_range.width, block_size.width);
GPU_SANITY_CHECK(u, 2);
GPU_SANITY_CHECK(v, 2);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////
// FGDStatModel
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
DEF_PARAM_TEST_1(Video, string);
PERF_TEST_P(Video, Video_FGDStatModel,
Values(string("gpu/video/768x576.avi")))
{
declare.time(60);
const string inputFile = perf::TestBase::getDataPath(GetParam());
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
cap >> frame;
ASSERT_FALSE(frame.empty());
if (PERF_RUN_GPU())
{
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();
}
const cv::gpu::GpuMat background = d_model.background;
const cv::gpu::GpuMat foreground = d_model.foreground;
GPU_SANITY_CHECK(background, 1e-2, ERROR_RELATIVE);
GPU_SANITY_CHECK(foreground, 1e-2, ERROR_RELATIVE);
}
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();
}
const cv::Mat background = cv::cvarrToMat(model->background);
const cv::Mat foreground = cv::cvarrToMat(model->foreground);
CPU_SANITY_CHECK(background);
CPU_SANITY_CHECK(foreground);
}
}
#endif
//////////////////////////////////////////////////////
// MOG
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
DEF_PARAM_TEST(Video_Cn_LearningRate, string, MatCn, 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)))
{
const string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
const int cn = GET_PARAM(1);
const 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 (PERF_RUN_GPU())
{
cv::gpu::GpuMat d_frame(frame);
cv::gpu::MOG_GPU d_mog;
cv::gpu::GpuMat foreground;
d_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();
d_mog(d_frame, foreground, learningRate);
stopTimer();
}
GPU_SANITY_CHECK(foreground);
}
else
{
cv::Ptr<cv::BackgroundSubtractor> mog = cv::createBackgroundSubtractorMOG();
cv::Mat foreground;
mog->apply(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->apply(frame, foreground, learningRate);
stopTimer();
}
CPU_SANITY_CHECK(foreground);
}
}
#endif
//////////////////////////////////////////////////////
// MOG2
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
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))
{
const string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
const 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 (PERF_RUN_GPU())
{
cv::gpu::MOG2_GPU d_mog2;
d_mog2.bShadowDetection = false;
cv::gpu::GpuMat d_frame(frame);
cv::gpu::GpuMat foreground;
d_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();
d_mog2(d_frame, foreground);
stopTimer();
}
GPU_SANITY_CHECK(foreground);
}
else
{
cv::Ptr<cv::BackgroundSubtractor> mog2 = cv::createBackgroundSubtractorMOG2();
mog2->set("detectShadows", false);
cv::Mat foreground;
mog2->apply(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->apply(frame, foreground);
stopTimer();
}
CPU_SANITY_CHECK(foreground);
}
}
#endif
//////////////////////////////////////////////////////
// MOG2GetBackgroundImage
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
PERF_TEST_P(Video_Cn, Video_MOG2GetBackgroundImage,
Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
GPU_CHANNELS_1_3_4))
{
const string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
const int cn = GET_PARAM(1);
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
cv::Mat frame;
if (PERF_RUN_GPU())
{
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 background;
TEST_CYCLE() d_mog2.getBackgroundImage(background);
GPU_SANITY_CHECK(background, 1);
}
else
{
cv::Ptr<cv::BackgroundSubtractor> mog2 = cv::createBackgroundSubtractorMOG2();
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->apply(frame, foreground);
}
cv::Mat background;
TEST_CYCLE() mog2->getBackgroundImage(background);
CPU_SANITY_CHECK(background);
}
}
#endif
//////////////////////////////////////////////////////
// GMG
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
DEF_PARAM_TEST(Video_Cn_MaxFeatures, string, MatCn, int);
PERF_TEST_P(Video_Cn_MaxFeatures, Video_GMG,
Combine(Values(string("gpu/video/768x576.avi")),
GPU_CHANNELS_1_3_4,
Values(20, 40, 60)))
{
const std::string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
const int cn = GET_PARAM(1);
const 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 (PERF_RUN_GPU())
{
cv::gpu::GpuMat d_frame(frame);
cv::gpu::GpuMat foreground;
cv::gpu::GMG_GPU d_gmg;
d_gmg.maxFeatures = maxFeatures;
d_gmg(d_frame, foreground);
for (int i = 0; i < 150; ++i)
{
cap >> frame;
if (frame.empty())
{
cap.release();
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, foreground);
stopTimer();
}
GPU_SANITY_CHECK(foreground);
}
else
{
cv::Mat foreground;
cv::Mat zeros(frame.size(), CV_8UC1, cv::Scalar::all(0));
cv::Ptr<cv::BackgroundSubtractor> gmg = cv::createBackgroundSubtractorGMG();
gmg->set("maxFeatures", maxFeatures);
//gmg.initialize(frame.size(), 0.0, 255.0);
gmg->apply(frame, foreground);
for (int i = 0; i < 150; ++i)
{
cap >> frame;
if (frame.empty())
{
cap.release();
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->apply(frame, foreground);
stopTimer();
}
CPU_SANITY_CHECK(foreground);
}
}
#endif
//////////////////////////////////////////////////////
// VideoReader
#if defined(HAVE_NVCUVID) && BUILD_WITH_VIDEO_INPUT_SUPPORT
PERF_TEST_P(Video, DISABLED_Video_VideoReader, Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"))
{
declare.time(20);
const string inputFile = perf::TestBase::getDataPath(GetParam());
if (PERF_RUN_GPU())
{
cv::gpu::VideoReader_GPU d_reader(inputFile);
ASSERT_TRUE( d_reader.isOpened() );
cv::gpu::GpuMat frame;
TEST_CYCLE_N(10) d_reader.read(frame);
GPU_SANITY_CHECK(frame);
}
else
{
cv::VideoCapture reader(inputFile);
ASSERT_TRUE( reader.isOpened() );
cv::Mat frame;
TEST_CYCLE_N(10) reader >> frame;
CPU_SANITY_CHECK(frame);
}
}
#endif
//////////////////////////////////////////////////////
// VideoWriter
#if defined(HAVE_NVCUVID) && defined(WIN32)
PERF_TEST_P(Video, DISABLED_Video_VideoWriter, Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"))
{
declare.time(30);
const string inputFile = perf::TestBase::getDataPath(GetParam());
const string outputFile = cv::tempfile(".avi");
const double FPS = 25.0;
cv::VideoCapture reader(inputFile);
ASSERT_TRUE( reader.isOpened() );
cv::Mat frame;
if (PERF_RUN_GPU())
{
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();
}
}
SANITY_CHECK(frame);
}
#endif