Open Source Computer Vision Library https://opencv.org/
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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) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Fangfang Bai, fangfang@multicorewareinc.com
// Jin Ma, jin@multicorewareinc.com
//
// 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
11 years ago
// 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
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//
//M*/
#include "perf_precomp.hpp"
using namespace perf;
using namespace std;
using namespace cv::ocl;
using namespace cv;
using std::tr1::tuple;
using std::tr1::get;
#if defined(HAVE_XINE) || \
defined(HAVE_GSTREAMER) || \
defined(HAVE_QUICKTIME) || \
defined(HAVE_AVFOUNDATION) || \
defined(HAVE_FFMPEG) || \
defined(WIN32)
# define BUILD_WITH_VIDEO_INPUT_SUPPORT 1
#else
# define BUILD_WITH_VIDEO_INPUT_SUPPORT 0
#endif
#if BUILD_WITH_VIDEO_INPUT_SUPPORT
static void cvtFrameFmt(vector<Mat>& input, vector<Mat>& output)
{
for(int i = 0; i< (int)(input.size()); i++)
{
cvtColor(input[i], output[i], COLOR_RGB2GRAY);
}
}
//prepare data for CPU
static void prepareData(VideoCapture& cap, int cn, vector<Mat>& frame_buffer)
{
cv::Mat frame;
std::vector<Mat> frame_buffer_init;
int nFrame = (int)frame_buffer.size();
for(int i = 0; i < nFrame; i++)
{
cap >> frame;
ASSERT_FALSE(frame.empty());
frame_buffer_init.push_back(frame);
}
if(cn == 1)
cvtFrameFmt(frame_buffer_init, frame_buffer);
else
frame_buffer = frame_buffer_init;
}
//copy CPU data to GPU
static void prepareData(vector<Mat>& frame_buffer, vector<oclMat>& frame_buffer_ocl)
{
for(int i = 0; i < (int)frame_buffer.size(); i++)
frame_buffer_ocl.push_back(cv::ocl::oclMat(frame_buffer[i]));
}
///////////// MOG ////////////////////////
typedef tuple<string, int, double> VideoMOGParamType;
typedef TestBaseWithParam<VideoMOGParamType> VideoMOGFixture;
PERF_TEST_P(VideoMOGFixture, MOG,
::testing::Combine(::testing::Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
::testing::Values(1, 3),
::testing::Values(0.0, 0.01)))
{
VideoMOGParamType params = GetParam();
const string inputFile = perf::TestBase::getDataPath(get<0>(params));
const int cn = get<1>(params);
const float learningRate = static_cast<float>(get<2>(params));
const int nFrame = 5;
Mat foreground_cpu;
std::vector<Mat> frame_buffer(nFrame);
std::vector<oclMat> frame_buffer_ocl;
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
prepareData(cap, cn, frame_buffer);
cv::Mat foreground;
cv::ocl::oclMat foreground_d;
if(RUN_PLAIN_IMPL)
{
TEST_CYCLE()
{
cv::BackgroundSubtractorMOG mog;
foreground.release();
for (int i = 0; i < nFrame; i++)
{
mog(frame_buffer[i], foreground, learningRate);
}
}
SANITY_CHECK(foreground);
}
else if(RUN_OCL_IMPL)
{
prepareData(frame_buffer, frame_buffer_ocl);
CV_Assert((int)(frame_buffer_ocl.size()) == nFrame);
OCL_TEST_CYCLE()
{
cv::ocl::MOG d_mog;
foreground_d.release();
for (int i = 0; i < nFrame; ++i)
{
d_mog(frame_buffer_ocl[i], foreground_d, learningRate);
}
}
foreground_d.download(foreground);
SANITY_CHECK(foreground);
}
else
OCL_PERF_ELSE
}
///////////// MOG2 ////////////////////////
typedef tuple<string, int> VideoMOG2ParamType;
typedef TestBaseWithParam<VideoMOG2ParamType> MOG2_Apply;
OCL_PERF_TEST_P(MOG2_Apply, Mog2,
testing::Combine(testing::Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
testing::Values(1, 3)))
{
VideoMOG2ParamType params = GetParam();
const string inputFile = perf::TestBase::getDataPath(get<0>(params));
const int cn = get<1>(params);
int nFrame = 5;
std::vector<cv::Mat> frame_buffer(nFrame);
std::vector<cv::ocl::oclMat> frame_buffer_ocl;
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
prepareData(cap, cn, frame_buffer);
cv::Mat foreground;
cv::ocl::oclMat foreground_d;
if(RUN_PLAIN_IMPL)
{
TEST_CYCLE()
{
cv::BackgroundSubtractorMOG2 mog2;
mog2.set("detectShadows", false);
foreground.release();
for (int i = 0; i < nFrame; i++)
mog2(frame_buffer[i], foreground);
}
SANITY_CHECK(foreground);
}
else if(RUN_OCL_IMPL)
{
prepareData(frame_buffer, frame_buffer_ocl);
CV_Assert((int)(frame_buffer_ocl.size()) == nFrame);
OCL_TEST_CYCLE()
{
cv::ocl::MOG2 d_mog2;
foreground_d.release();
for (int i = 0; i < nFrame; i++)
d_mog2(frame_buffer_ocl[i], foreground_d);
}
foreground_d.download(foreground);
SANITY_CHECK(foreground);
}
else
OCL_PERF_ELSE
}
///////////// MOG2_GetBackgroundImage //////////////////
typedef TestBaseWithParam<VideoMOG2ParamType> MOG2_GetBackgroundImage;
OCL_PERF_TEST_P(MOG2_GetBackgroundImage, Mog2,
testing::Combine(testing::Values("gpu/video/768x576.avi", "gpu/video/1920x1080.avi"),
testing::Values(3)))
{
VideoMOG2ParamType params = GetParam();
const string inputFile = perf::TestBase::getDataPath(get<0>(params));
const int cn = get<1>(params);
int nFrame = 5;
std::vector<cv::Mat> frame_buffer(nFrame);
std::vector<cv::ocl::oclMat> frame_buffer_ocl;
cv::VideoCapture cap(inputFile);
ASSERT_TRUE(cap.isOpened());
prepareData(cap, cn, frame_buffer);
cv::Mat foreground;
cv::Mat background;
cv::ocl::oclMat foreground_d;
cv::ocl::oclMat background_d;
if (RUN_PLAIN_IMPL)
{
TEST_CYCLE()
{
cv::BackgroundSubtractorMOG2 mog2;
mog2.set("detectShadows", false);
foreground.release();
background.release();
for (int i = 0; i < nFrame; i++)
{
mog2(frame_buffer[i], foreground);
}
mog2.getBackgroundImage(background);
}
SANITY_CHECK(background);
}
else if (RUN_OCL_IMPL)
{
prepareData(frame_buffer, frame_buffer_ocl);
CV_Assert((int)(frame_buffer_ocl.size()) == nFrame);
OCL_TEST_CYCLE()
{
cv::ocl::MOG2 d_mog2;
foreground_d.release();
background_d.release();
for (int i = 0; i < nFrame; i++)
{
d_mog2(frame_buffer_ocl[i], foreground_d);
}
d_mog2.getBackgroundImage(background_d);
}
background_d.download(background);
SANITY_CHECK(background);
}
else
OCL_PERF_ELSE
}
#endif