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opencv/modules/cudabgsegm/perf/perf_bgsegm.cpp
Roman Donchenko d58cd9851f Merge remote-tracking branch 'origin/2.4' into merge-2.4 
Conflicts:
	CMakeLists.txt
	cmake/OpenCVDetectCUDA.cmake
	doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.rst
	modules/core/src/cmdparser.cpp
	modules/gpu/CMakeLists.txt
	modules/gpu/doc/introduction.rst
	modules/gpu/perf/perf_video.cpp
	modules/highgui/doc/reading_and_writing_images_and_video.rst
	modules/ocl/src/cl_context.cpp
	modules/video/include/opencv2/video/background_segm.hpp
	samples/cpp/image_sequence.cpp
	samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp
	samples/python/chessboard.py
	samples/python/cvutils.py
	samples/python/demhist.py
	samples/python/dft.py
	samples/python/distrans.py
	samples/python/edge.py
	samples/python/ffilldemo.py
	samples/python/fitellipse.py
	samples/python/houghlines.py
	samples/python/inpaint.py
	samples/python/logpolar.py
	samples/python/morphology.py
	samples/python/numpy_array.py
	samples/python/watershed.py
2013-12-03 17:35:21 +04:00

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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"
#ifdef HAVE_OPENCV_LEGACY
# include "opencv2/legacy.hpp"
#endif
#ifdef HAVE_OPENCV_CUDAIMGPROC
# include "opencv2/cudaimgproc.hpp"
#endif
using namespace std;
using namespace testing;
using namespace perf;
#if defined(HAVE_XINE) || \
defined(HAVE_GSTREAMER) || \
defined(HAVE_QUICKTIME) || \
defined(HAVE_QTKIT) || \
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
//////////////////////////////////////////////////////
// FGDStatModel
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
#ifdef HAVE_OPENCV_LEGACY
namespace cv
{
template<> void DefaultDeleter<CvBGStatModel>::operator ()(CvBGStatModel* obj) const
{
cvReleaseBGStatModel(&obj);
}
}
#endif
DEF_PARAM_TEST_1(Video, string);
PERF_TEST_P(Video, FGDStatModel,
Values(string("gpu/video/768x576.avi")))
{
const int numIters = 10;
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_CUDA())
{
cv::cuda::GpuMat d_frame(frame), foreground;
cv::Ptr<cv::cuda::BackgroundSubtractorFGD> d_fgd = cv::cuda::createBackgroundSubtractorFGD();
d_fgd->apply(d_frame, foreground);
int i = 0;
// collect performance data
for (; i < numIters; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
d_frame.upload(frame);
startTimer();
if(!next())
break;
d_fgd->apply(d_frame, foreground);
stopTimer();
}
// process last frame in sequence to get data for sanity test
for (; i < numIters; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
d_frame.upload(frame);
d_fgd->apply(d_frame, foreground);
}
CUDA_SANITY_CHECK(foreground, 1e-2, ERROR_RELATIVE);
#ifdef HAVE_OPENCV_CUDAIMGPROC
cv::cuda::GpuMat background3, background;
d_fgd->getBackgroundImage(background3);
cv::cuda::cvtColor(background3, background, cv::COLOR_BGR2BGRA);
CUDA_SANITY_CHECK(background, 1e-2, ERROR_RELATIVE);
#endif
}
else
{
#ifdef HAVE_OPENCV_LEGACY
IplImage ipl_frame = frame;
cv::Ptr<CvBGStatModel> model(cvCreateFGDStatModel(&ipl_frame));
int i = 0;
// collect performance data
for (; i < numIters; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
ipl_frame = frame;
startTimer();
if(!next())
break;
cvUpdateBGStatModel(&ipl_frame, model);
stopTimer();
}
// process last frame in sequence to get data for sanity test
for (; i < numIters; ++i)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
ipl_frame = frame;
cvUpdateBGStatModel(&ipl_frame, model);
}
const cv::Mat background = cv::cvarrToMat(model->background);
const cv::Mat foreground = cv::cvarrToMat(model->foreground);
CPU_SANITY_CHECK(background);
CPU_SANITY_CHECK(foreground);
#else
FAIL_NO_CPU();
#endif
}
}
#endif
//////////////////////////////////////////////////////
// MOG
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
DEF_PARAM_TEST(Video_Cn_LearningRate, string, MatCn, double);
PERF_TEST_P(Video_Cn_LearningRate, MOG,
Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
CUDA_CHANNELS_1_3_4,
Values(0.0, 0.01)))
{
const int numIters = 10;
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_CUDA())
{
cv::Ptr<cv::BackgroundSubtractor> d_mog = cv::cuda::createBackgroundSubtractorMOG();
cv::cuda::GpuMat d_frame(frame);
cv::cuda::GpuMat foreground;
d_mog->apply(d_frame, foreground, learningRate);
int i = 0;
// collect performance data
for (; i < numIters; ++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();
if(!next())
break;
d_mog->apply(d_frame, foreground, learningRate);
stopTimer();
}
// process last frame in sequence to get data for sanity test
for (; i < numIters; ++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_mog->apply(d_frame, foreground, learningRate);
}
CUDA_SANITY_CHECK(foreground);
}
else
{
cv::Ptr<cv::BackgroundSubtractor> mog = cv::createBackgroundSubtractorMOG();
cv::Mat foreground;
mog->apply(frame, foreground, learningRate);
int i = 0;
// collect performance data
for (; i < numIters; ++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();
if(!next())
break;
mog->apply(frame, foreground, learningRate);
stopTimer();
}
// process last frame in sequence to get data for sanity test
for (; i < numIters; ++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);
}
mog->apply(frame, foreground, learningRate);
}
CPU_SANITY_CHECK(foreground);
}
}
#endif
//////////////////////////////////////////////////////
// MOG2
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
DEF_PARAM_TEST(Video_Cn, string, int);
PERF_TEST_P(Video_Cn, DISABLED_MOG2,
Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
CUDA_CHANNELS_1_3_4))
{
const int numIters = 10;
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_CUDA())
{
cv::Ptr<cv::BackgroundSubtractorMOG2> d_mog2 = cv::cuda::createBackgroundSubtractorMOG2();
d_mog2->setDetectShadows(false);
cv::cuda::GpuMat d_frame(frame);
cv::cuda::GpuMat foreground;
d_mog2->apply(d_frame, foreground);
int i = 0;
// collect performance data
for (; i < numIters; ++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();
if(!next())
break;
d_mog2->apply(d_frame, foreground);
stopTimer();
}
// process last frame in sequence to get data for sanity test
for (; i < numIters; ++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->apply(d_frame, foreground);
}
CUDA_SANITY_CHECK(foreground);
}
else
{
cv::Ptr<cv::BackgroundSubtractorMOG2> mog2 = cv::createBackgroundSubtractorMOG2();
mog2->setDetectShadows(false);
cv::Mat foreground;
mog2->apply(frame, foreground);
int i = 0;
// collect performance data
for (; i < numIters; ++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();
if(!next())
break;
mog2->apply(frame, foreground);
stopTimer();
}
// process last frame in sequence to get data for sanity test
for (; i < numIters; ++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);
}
CPU_SANITY_CHECK(foreground);
}
}
#endif
//////////////////////////////////////////////////////
// MOG2GetBackgroundImage
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
PERF_TEST_P(Video_Cn, MOG2GetBackgroundImage,
Combine(Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
CUDA_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_CUDA())
{
cv::Ptr<cv::BackgroundSubtractor> d_mog2 = cv::cuda::createBackgroundSubtractorMOG2();
cv::cuda::GpuMat d_frame;
cv::cuda::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->apply(d_frame, d_foreground);
}
cv::cuda::GpuMat background;
TEST_CYCLE() d_mog2->getBackgroundImage(background);
CUDA_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, GMG,
Combine(Values(string("gpu/video/768x576.avi")),
CUDA_CHANNELS_1_3_4,
Values(20, 40, 60)))
{
const int numIters = 150;
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_CUDA())
{
cv::cuda::GpuMat d_frame(frame);
cv::cuda::GpuMat foreground;
cv::Ptr<cv::BackgroundSubtractorGMG> d_gmg = cv::cuda::createBackgroundSubtractorGMG();
d_gmg->setMaxFeatures(maxFeatures);
d_gmg->apply(d_frame, foreground);
int i = 0;
// collect performance data
for (; i < numIters; ++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();
if(!next())
break;
d_gmg->apply(d_frame, foreground);
stopTimer();
}
// process last frame in sequence to get data for sanity test
for (; i < numIters; ++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);
d_gmg->apply(d_frame, foreground);
}
CUDA_SANITY_CHECK(foreground);
}
else
{
cv::Mat foreground;
cv::Mat zeros(frame.size(), CV_8UC1, cv::Scalar::all(0));
cv::Ptr<cv::BackgroundSubtractorGMG> gmg = cv::createBackgroundSubtractorGMG();
gmg->setMaxFeatures(maxFeatures);
gmg->apply(frame, foreground);
int i = 0;
// collect performance data
for (; i < numIters; ++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();
if(!next())
break;
gmg->apply(frame, foreground);
stopTimer();
}
// process last frame in sequence to get data for sanity test
for (; i < numIters; ++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);
}
gmg->apply(frame, foreground);
}
CPU_SANITY_CHECK(foreground);
}
}
#endif
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