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Merge branch 'master' of git://code.opencv.org/opencv

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yao 2012-08-08 17:13:30 +08:00
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8
modules/ocl/CMakeLists.txt
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@ -64,8 +64,8 @@ ocv_add_accuracy_tests(FILES "Include" ${test_hdrs}
################################################################################################################
################################ OpenCL Module Performance ##################################################
################################################################################################################
#file(GLOB perf_srcs "perf/*.cpp")
#file(GLOB perf_hdrs "perf/*.hpp" "perf/*.h")
file(GLOB perf_srcs "perf/*.cpp")
file(GLOB perf_hdrs "perf/*.hpp" "perf/*.h")
#ocv_add_perf_tests(FILES "Include" ${perf_hdrs}
# FILES "Src" ${perf_srcs})
ocv_add_perf_tests(FILES "Include" ${perf_hdrs}
FILES "Src" ${perf_srcs})

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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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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*/
#ifndef __OPENCV_TEST_INTERPOLATION_HPP__
#define __OPENCV_TEST_INTERPOLATION_HPP__
template <typename T> T readVal(const cv::Mat& src, int y, int x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
if (border_type == cv::BORDER_CONSTANT)
return (y >= 0 && y < src.rows && x >= 0 && x < src.cols) ? src.at<T>(y, x * src.channels() + c) : cv::saturate_cast<T>(borderVal.val[c]);
return src.at<T>(cv::borderInterpolate(y, src.rows, border_type), cv::borderInterpolate(x, src.cols, border_type) * src.channels() + c);
}
template <typename T> struct NearestInterpolator
{
static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
return readVal<T>(src, cvFloor(y), cvFloor(x), c, border_type, borderVal);
}
};
template <typename T> struct LinearInterpolator
{
static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
x -= 0.5f;
y -= 0.5f;
int x1 = cvFloor(x);
int y1 = cvFloor(y);
int x2 = x1 + 1;
int y2 = y1 + 1;
float res = 0;
res += readVal<T>(src, y1, x1, c, border_type, borderVal) * ((x2 - x) * (y2 - y));
res += readVal<T>(src, y1, x2, c, border_type, borderVal) * ((x - x1) * (y2 - y));
res += readVal<T>(src, y2, x1, c, border_type, borderVal) * ((x2 - x) * (y - y1));
res += readVal<T>(src, y2, x2, c, border_type, borderVal) * ((x - x1) * (y - y1));
return cv::saturate_cast<T>(res);
}
};
template <typename T> struct CubicInterpolator
{
static float getValue(float p[4], float x)
{
return p[1] + 0.5 * x * (p[2] - p[0] + x*(2.0*p[0] - 5.0*p[1] + 4.0*p[2] - p[3] + x*(3.0*(p[1] - p[2]) + p[3] - p[0])));
}
static float getValue(float p[4][4], float x, float y)
{
float arr[4];
arr[0] = getValue(p[0], x);
arr[1] = getValue(p[1], x);
arr[2] = getValue(p[2], x);
arr[3] = getValue(p[3], x);
return getValue(arr, y);
}
static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
int ix = cvRound(x);
int iy = cvRound(y);
float vals[4][4] =
{
{readVal<T>(src, iy - 2, ix - 2, c, border_type, borderVal), readVal<T>(src, iy - 2, ix - 1, c, border_type, borderVal), readVal<T>(src, iy - 2, ix, c, border_type, borderVal), readVal<T>(src, iy - 2, ix + 1, c, border_type, borderVal)},
{readVal<T>(src, iy - 1, ix - 2, c, border_type, borderVal), readVal<T>(src, iy - 1, ix - 1, c, border_type, borderVal), readVal<T>(src, iy - 1, ix, c, border_type, borderVal), readVal<T>(src, iy - 1, ix + 1, c, border_type, borderVal)},
{readVal<T>(src, iy , ix - 2, c, border_type, borderVal), readVal<T>(src, iy , ix - 1, c, border_type, borderVal), readVal<T>(src, iy , ix, c, border_type, borderVal), readVal<T>(src, iy , ix + 1, c, border_type, borderVal)},
{readVal<T>(src, iy + 1, ix - 2, c, border_type, borderVal), readVal<T>(src, iy + 1, ix - 1, c, border_type, borderVal), readVal<T>(src, iy + 1, ix, c, border_type, borderVal), readVal<T>(src, iy + 1, ix + 1, c, border_type, borderVal)},
};
return cv::saturate_cast<T>(getValue(vals, (x - ix + 2.0) / 4.0, (y - iy + 2.0) / 4.0));
}
};
#endif // __OPENCV_TEST_INTERPOLATION_HPP__

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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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 "precomp.hpp"
#ifdef HAVE_OPENCL
using namespace std;
using namespace cv;
using namespace cv::ocl;
using namespace cvtest;
using namespace testing;
void print_info()
{
printf("\n");
#if defined _WIN32
# if defined _WIN64
puts("OS: Windows 64");
# else
puts("OS: Windows 32");
# endif
#elif defined linux
# if defined _LP64
puts("OS: Linux 64");
# else
puts("OS: Linux 32");
# endif
#elif defined __APPLE__
# if defined _LP64
puts("OS: Apple 64");
# else
puts("OS: Apple 32");
# endif
#endif
}
#if PERF_TEST_OCL
int main(int argc, char** argv)
{
static std::vector<Info> ocl_info;
ocl::getDevice(ocl_info);
run_perf_test();
return 0;
}
#else
int main(int argc, char** argv)
{
TS::ptr()->init("ocl");
InitGoogleTest(&argc, argv);
print_info();
return RUN_ALL_TESTS();
}
#endif // PERF_TEST_OCL
#else // HAVE_OPENC
int main()
{
printf("OpenCV was built without OpenCL support\n");
return 0;
}
#endif // HAVE_OPENCL

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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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 "precomp.hpp"

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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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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*/
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
#include <cmath>
#include <cstdio>
#include <iostream>
#include <fstream>
#include <sstream>
#include <string>
#include <limits>
#include <algorithm>
#include <iterator>
#include <string>
#include <cstdarg>
#include "cvconfig.h"
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/video/video.hpp"
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts/ts_perf.hpp"
#include "opencv2/ocl/ocl.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "utility.hpp"
#include "interpolation.hpp"
//#include "add_test_info.h"
//#define PERF_TEST_OCL 1
#endif

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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, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Jia Haipeng, jiahaipeng95@gmail.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
// and/or other oclMaterials 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 "opencv2/objdetect/objdetect.hpp"
#include "precomp.hpp"
#ifdef HAVE_OPENCL
using namespace cvtest;
using namespace testing;
using namespace std;
using namespace cv;
struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
PARAM_TEST_CASE(HaarTestBase, int, int)
{
std::vector<cv::ocl::Info> oclinfo;
cv::ocl::OclCascadeClassifier cascade, nestedCascade;
cv::CascadeClassifier cpucascade, cpunestedCascade;
// Mat img;
double scale;
int index;
virtual void SetUp()
{
scale = 1.1;
#if WIN32
string cascadeName="E:\\opencvbuffer\\trunk\\data\\haarcascades\\haarcascade_frontalface_alt.xml";
#else
string cascadeName="../data/haarcascades/haarcascade_frontalface_alt.xml";
#endif
if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)))
{
cout << "ERROR: Could not load classifier cascade" << endl;
cout << "Usage: facedetect [--cascade=<cascade_path>]\n"
" [--nested-cascade[=nested_cascade_path]]\n"
" [--scale[=<image scale>\n"
" [filename|camera_index]\n" << endl ;
return;
}
int devnums = getDevice(oclinfo);
CV_Assert(devnums>0);
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
cv::ocl::setBinpath("E:\\");
}
};
////////////////////////////////faceDetect/////////////////////////////////////////////////
struct Haar : HaarTestBase {};
TEST_P(Haar, FaceDetect)
{
for(int index = 1;index < 2; index++)
{
Mat img;
char buff[256];
#if WIN32
sprintf(buff,"E:\\myDataBase\\%d.jpg",index);
img = imread( buff, 1 );
#else
sprintf(buff,"%d.jpg",index);
img = imread( buff, 1 );
std::cout << "Now test " << index << ".jpg" <<std::endl;
#endif
if(img.empty())
{
std::cout << "Couldn't read test" << index <<".jpg" << std::endl;
continue;
}
int i = 0;
double t = 0;
vector<Rect> faces;
const static Scalar colors[] = { CV_RGB(0,0,255),
CV_RGB(0,128,255),
CV_RGB(0,255,255),
CV_RGB(0,255,0),
CV_RGB(255,128,0),
CV_RGB(255,255,0),
CV_RGB(255,0,0),
CV_RGB(255,0,255)} ;
Mat gray, smallImg(cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
MemStorage storage(cvCreateMemStorage(0));
cvtColor( img, gray, CV_BGR2GRAY );
resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
equalizeHist( smallImg, smallImg );
CvMat _image = smallImg;
Mat tempimg(&_image, false);
cv::ocl::oclMat image(tempimg);
CvSeq* _objects;
#if 1
for(int k= 0; k<10; k++)
{
t = (double)cvGetTickCount();
_objects = cascade.oclHaarDetectObjects( image, storage, 1.1,
2, 0
|CV_HAAR_SCALE_IMAGE
, Size(30,30), Size(0, 0) );
t = (double)cvGetTickCount() - t ;
printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
}
#else
cpucascade.detectMultiScale( image, faces, 1.1,
2, 0
|CV_HAAR_SCALE_IMAGE
, Size(30,30), Size(0, 0) );
#endif
vector<CvAvgComp> vecAvgComp;
Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
faces.resize(vecAvgComp.size());
std::transform(vecAvgComp.begin(), vecAvgComp.end(), faces.begin(), getRect());
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
{
Mat smallImgROI;
vector<Rect> nestedObjects;
Point center;
Scalar color = colors[i%8];
int radius;
center.x = cvRound((r->x + r->width*0.5)*scale);
center.y = cvRound((r->y + r->height*0.5)*scale);
radius = cvRound((r->width + r->height)*0.25*scale);
circle( img, center, radius, color, 3, 8, 0 );
}
#if WIN32
sprintf(buff,"E:\\result1\\%d.jpg",index);
imwrite(buff,img);
#else
sprintf(buff,"testdet_%d.jpg",index);
imwrite(buff,img);
#endif
}
}
//INSTANTIATE_TEST_CASE_P(HaarTestBase, Haar, Combine(Values(1),
// Values(1)));
#endif // HAVE_OPENCL

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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, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Jia Haipeng, jiahaipeng95@gmail.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
// and/or other oclMaterials 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 "precomp.hpp"
#ifdef HAVE_OPENCL
using namespace cvtest;
using namespace testing;
using namespace std;
using namespace cv::ocl;
////////////////////////////////converto/////////////////////////////////////////////////
PARAM_TEST_CASE(ConvertToTestBase, MatType, MatType)
{
int type;
int dst_type;
//src mat
cv::Mat mat;
cv::Mat dst;
// set up roi
int roicols;
int roirows;
int srcx;
int srcy;
int dstx;
int dsty;
//src mat with roi
cv::Mat mat_roi;
cv::Mat dst_roi;
std::vector<cv::ocl::Info> oclinfo;
//ocl dst mat for testing
cv::ocl::oclMat gdst_whole;
//ocl mat with roi
cv::ocl::oclMat gmat;
cv::ocl::oclMat gdst;
virtual void SetUp()
{
type = GET_PARAM(0);
dst_type = GET_PARAM(1);
cv::RNG& rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
mat = randomMat(rng, size, type, 5, 16, false);
dst = randomMat(rng, size, type, 5, 16, false);
int devnums = getDevice(oclinfo);
CV_Assert(devnums > 0);
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
setBinpath(CLBINPATH);
}
void Has_roi(int b)
{
//cv::RNG& rng = TS::ptr()->get_rng();
if(b)
{
//randomize ROI
roicols = mat.cols-1; //start
roirows = mat.rows-1;
srcx = 1;
srcy = 1;
dstx = 1;
dsty =1;
}else
{
roicols = mat.cols;
roirows = mat.rows;
srcx = 0;
srcy = 0;
dstx = 0;
dsty = 0;
};
mat_roi = mat(Rect(srcx,srcy,roicols,roirows));
dst_roi = dst(Rect(dstx,dsty,roicols,roirows));
//gdst_whole = dst;
//gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
//gmat = mat_roi;
}
};
struct ConvertTo :ConvertToTestBase {};
TEST_P(ConvertTo, Accuracy)
{
#ifndef PRINT_KERNEL_RUN_TIME
double totalcputick=0;
double totalgputick=0;
double totalgputick_kernel=0;
double t0=0;
double t1=0;
double t2=0;
for(int k=0;k<2;k++){
totalcputick=0;
totalgputick=0;
totalgputick_kernel=0;
for(int j = 0; j < LOOP_TIMES+1; j ++)
{
Has_roi(k);
t0 = (double)cvGetTickCount();//cpu start
mat_roi.convertTo(dst_roi, dst_type);
t0 = (double)cvGetTickCount() - t0;//cpu end
t1 = (double)cvGetTickCount();//gpu start1
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
gmat = mat_roi;
t2=(double)cvGetTickCount();//kernel
gmat.convertTo(gdst, dst_type);
t2 = (double)cvGetTickCount() - t2;//kernel
cv::Mat cpu_dst;
gdst_whole.download (cpu_dst);//download
t1 = (double)cvGetTickCount() - t1;//gpu end1
if(j == 0)
continue;
totalgputick=t1+totalgputick;
totalcputick=t0+totalcputick;
totalgputick_kernel=t2+totalgputick_kernel;
}
if(k==0){cout<<"no roi\n";}else{cout<<"with roi\n";};
cout << "average cpu runtime is " << totalcputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime is " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime without data transfer is " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
}
#else
for(int j = 0; j < 2; j ++)
{
Has_roi(j);
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
gmat = mat_roi;
if(j==0){cout<<"no roi:";}else{cout<<"\nwith roi:";};
gmat.convertTo(gdst, dst_type);
};
#endif
}
///////////////////////////////////////////copyto/////////////////////////////////////////////////////////////
PARAM_TEST_CASE(CopyToTestBase, MatType, bool)
{
int type;
cv::Mat mat;
cv::Mat mask;
cv::Mat dst;
// set up roi
int roicols;
int roirows;
int srcx;
int srcy;
int dstx;
int dsty;
int maskx;
int masky;
//src mat with roi
cv::Mat mat_roi;
cv::Mat mask_roi;
cv::Mat dst_roi;
std::vector<cv::ocl::Info> oclinfo;
//ocl dst mat for testing
cv::ocl::oclMat gdst_whole;
//ocl mat with roi
cv::ocl::oclMat gmat;
cv::ocl::oclMat gdst;
cv::ocl::oclMat gmask;
virtual void SetUp()
{
type = GET_PARAM(0);
cv::RNG& rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
mat = randomMat(rng, size, type, 5, 16, false);
dst = randomMat(rng, size, type, 5, 16, false);
mask = randomMat(rng, size, CV_8UC1, 0, 2, false);
cv::threshold(mask, mask, 0.5, 255., CV_8UC1);
int devnums = getDevice(oclinfo);
CV_Assert(devnums > 0);
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
setBinpath(CLBINPATH);
}
void Has_roi(int b)
{
//cv::RNG& rng = TS::ptr()->get_rng();
if(b)
{
//randomize ROI
roicols = mat.cols-1; //start
roirows = mat.rows-1;
srcx = 1;
srcy = 1;
dstx = 1;
dsty =1;
maskx = 1;
masky = 1;
}else
{
roicols = mat.cols;
roirows = mat.rows;
srcx = 0;
srcy = 0;
dstx = 0;
dsty = 0;
maskx = 0;
masky = 0;
};
mat_roi = mat(Rect(srcx,srcy,roicols,roirows));
mask_roi = mask(Rect(maskx,masky,roicols,roirows));
dst_roi = dst(Rect(dstx,dsty,roicols,roirows));
//gdst_whole = dst;
//gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
//gmat = mat_roi;
//gmask = mask_roi;
}
};
struct CopyTo :CopyToTestBase {};
TEST_P(CopyTo, Without_mask)
{
#ifndef PRINT_KERNEL_RUN_TIME
double totalcputick=0;
double totalgputick=0;
double totalgputick_kernel=0;
double t0=0;
double t1=0;
double t2=0;
for(int k=0;k<2;k++){
totalcputick=0;
totalgputick=0;
totalgputick_kernel=0;
for(int j = 0; j < LOOP_TIMES+1; j ++)
{
Has_roi(k);
t0 = (double)cvGetTickCount();//cpu start
mat_roi.copyTo(dst_roi);
t0 = (double)cvGetTickCount() - t0;//cpu end
t1 = (double)cvGetTickCount();//gpu start1
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
gmat = mat_roi;
t2=(double)cvGetTickCount();//kernel
gmat.copyTo(gdst);
t2 = (double)cvGetTickCount() - t2;//kernel
cv::Mat cpu_dst;
gdst_whole.download (cpu_dst);//download
t1 = (double)cvGetTickCount() - t1;//gpu end1
if(j == 0)
continue;
totalgputick=t1+totalgputick;
totalcputick=t0+totalcputick;
totalgputick_kernel=t2+totalgputick_kernel;
}
if(k==0){cout<<"no roi\n";}else{cout<<"with roi\n";};
cout << "average cpu runtime is " << totalcputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime is " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime without data transfer is " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
}
#else
for(int j = 0; j < 2; j ++)
{
Has_roi(j);
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
gmat = mat_roi;
if(j==0){cout<<"no roi:";}else{cout<<"\nwith roi:";};
gmat.copyTo(gdst);
};
#endif
}
TEST_P(CopyTo, With_mask)
{
#ifndef PRINT_KERNEL_RUN_TIME
double totalcputick=0;
double totalgputick=0;
double totalgputick_kernel=0;
double t0=0;
double t1=0;
double t2=0;
for(int k=0;k<2;k++){
totalcputick=0;
totalgputick=0;
totalgputick_kernel=0;
for(int j = 0; j < LOOP_TIMES+1; j ++)
{
Has_roi(k);
t0 = (double)cvGetTickCount();//cpu start
mat_roi.copyTo(dst_roi,mask_roi);
t0 = (double)cvGetTickCount() - t0;//cpu end
t1 = (double)cvGetTickCount();//gpu start1
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
gmat = mat_roi;
gmask = mask_roi;
t2=(double)cvGetTickCount();//kernel
gmat.copyTo(gdst, gmask);
t2 = (double)cvGetTickCount() - t2;//kernel
cv::Mat cpu_dst;
gdst_whole.download (cpu_dst);//download
t1 = (double)cvGetTickCount() - t1;//gpu end1
if(j == 0)
continue;
totalgputick=t1+totalgputick;
totalcputick=t0+totalcputick;
totalgputick_kernel=t2+totalgputick_kernel;
}
if(k==0){cout<<"no roi\n";}else{cout<<"with roi\n";};
cout << "average cpu runtime is " << totalcputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime is " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime without data transfer is " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
}
#else
for(int j = 0; j < 2; j ++)
{
Has_roi(j);
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
gmat = mat_roi;
gmask = mask_roi;
if(j==0){cout<<"no roi:";}else{cout<<"\nwith roi:";};
gmat.copyTo(gdst, gmask);
};
#endif
}
///////////////////////////////////////////copyto/////////////////////////////////////////////////////////////
PARAM_TEST_CASE(SetToTestBase, MatType, bool)
{
int type;
cv::Scalar val;
cv::Mat mat;
cv::Mat mask;
// set up roi
int roicols;
int roirows;
int srcx;
int srcy;
int maskx;
int masky;
//src mat with roi
cv::Mat mat_roi;
cv::Mat mask_roi;
std::vector<cv::ocl::Info> oclinfo;
//ocl dst mat for testing
cv::ocl::oclMat gmat_whole;
//ocl mat with roi
cv::ocl::oclMat gmat;
cv::ocl::oclMat gmask;
virtual void SetUp()
{
type = GET_PARAM(0);
cv::RNG& rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
mat = randomMat(rng, size, type, 5, 16, false);
mask = randomMat(rng, size, CV_8UC1, 0, 2, false);
cv::threshold(mask, mask, 0.5, 255., CV_8UC1);
val = cv::Scalar(rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0));
int devnums = getDevice(oclinfo);
CV_Assert(devnums > 0);
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
setBinpath(CLBINPATH);
}
void Has_roi(int b)
{
//cv::RNG& rng = TS::ptr()->get_rng();
if(b)
{
//randomize ROI
roicols = mat.cols-1; //start
roirows = mat.rows-1;
srcx = 1;
srcy = 1;
maskx = 1;
masky = 1;
}else
{
roicols = mat.cols;
roirows = mat.rows;
srcx = 0;
srcy = 0;
maskx = 0;
masky = 0;
};
mat_roi = mat(Rect(srcx,srcy,roicols,roirows));
mask_roi = mask(Rect(maskx,masky,roicols,roirows));
//gmat_whole = mat;
//gmat = gmat_whole(Rect(srcx,srcy,roicols,roirows));
//gmask = mask_roi;
}
};
struct SetTo :SetToTestBase {};
TEST_P(SetTo, Without_mask)
{
#ifndef PRINT_KERNEL_RUN_TIME
double totalcputick=0;
double totalgputick=0;
double totalgputick_kernel=0;
double t0=0;
double t1=0;
double t2=0;
for(int k=0;k<2;k++){
totalcputick=0;
totalgputick=0;
totalgputick_kernel=0;
for(int j = 0; j < LOOP_TIMES+1; j ++)
{
Has_roi(k);
t0 = (double)cvGetTickCount();//cpu start
mat_roi.setTo(val);
t0 = (double)cvGetTickCount() - t0;//cpu end
t1 = (double)cvGetTickCount();//gpu start1
gmat_whole = mat;
gmat = gmat_whole(Rect(srcx,srcy,roicols,roirows));
t2=(double)cvGetTickCount();//kernel
gmat.setTo(val);
t2 = (double)cvGetTickCount() - t2;//kernel
cv::Mat cpu_dst;
gmat_whole.download(cpu_dst);//download
t1 = (double)cvGetTickCount() - t1;//gpu end1
if(j == 0)
continue;
totalgputick=t1+totalgputick;
totalcputick=t0+totalcputick;
totalgputick_kernel=t2+totalgputick_kernel;
}
if(k==0){cout<<"no roi\n";}else{cout<<"with roi\n";};
cout << "average cpu runtime is " << totalcputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime is " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime without data transfer is " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
}
#else
for(int j = 0; j < 2; j ++)
{
Has_roi(j);
gmat_whole = mat;
gmat = gmat_whole(Rect(srcx,srcy,roicols,roirows));
if(j==0){cout<<"no roi:";}else{cout<<"\nwith roi:";};
gmat.setTo(val);
};
#endif
}
TEST_P(SetTo, With_mask)
{
#ifndef PRINT_KERNEL_RUN_TIME
double totalcputick=0;
double totalgputick=0;
double totalgputick_kernel=0;
double t0=0;
double t1=0;
double t2=0;
for(int k=0;k<2;k++){
totalcputick=0;
totalgputick=0;
totalgputick_kernel=0;
for(int j = 0; j < LOOP_TIMES+1; j ++)
{
Has_roi(k);
t0 = (double)cvGetTickCount();//cpu start
mat_roi.setTo(val, mask_roi);
t0 = (double)cvGetTickCount() - t0;//cpu end
t1 = (double)cvGetTickCount();//gpu start1
gmat_whole = mat;
gmat = gmat_whole(Rect(srcx,srcy,roicols,roirows));
gmask = mask_roi;
t2=(double)cvGetTickCount();//kernel
gmat.setTo(val, gmask);
t2 = (double)cvGetTickCount() - t2;//kernel
cv::Mat cpu_dst;
gmat_whole.download(cpu_dst);//download
t1 = (double)cvGetTickCount() - t1;//gpu end1
if(j == 0)
continue;
totalgputick=t1+totalgputick;
totalcputick=t0+totalcputick;
totalgputick_kernel=t2+totalgputick_kernel;
}
if(k==0){cout<<"no roi\n";}else{cout<<"with roi\n";};
cout << "average cpu runtime is " << totalcputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime is " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime without data transfer is " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
}
#else
for(int j = 0; j < 2; j ++)
{
Has_roi(j);
gmat_whole = mat;
gmat = gmat_whole(Rect(srcx,srcy,roicols,roirows));
gmask = mask_roi;
if(j==0){cout<<"no roi:";}else{cout<<"\nwith roi:";};
gmat.setTo(val, gmask);
};
#endif
}
//**********test************
INSTANTIATE_TEST_CASE_P(MatrixOperation, ConvertTo, Combine(
Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),
Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4)));
INSTANTIATE_TEST_CASE_P(MatrixOperation, CopyTo, Combine(
Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),
Values(false))); // Values(false) is the reserved parameter
INSTANTIATE_TEST_CASE_P(MatrixOperation, SetTo, Combine(
Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),
Values(false))); // Values(false) is the reserved parameter
#endif

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@ -0,0 +1,455 @@
/*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, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Jia Haipeng, jiahaipeng95@gmail.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
// and/or other oclMaterials 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 "precomp.hpp"
#ifdef HAVE_OPENCL
using namespace cvtest;
using namespace testing;
using namespace std;
using namespace cv::ocl;
PARAM_TEST_CASE(MergeTestBase, MatType, int)
{
int type;
int channels;
//src mat
cv::Mat mat1;
cv::Mat mat2;
cv::Mat mat3;
cv::Mat mat4;
//dst mat
cv::Mat dst;
// set up roi
int roicols;
int roirows;
int src1x;
int src1y;
int src2x;
int src2y;
int src3x;
int src3y;
int src4x;
int src4y;
int dstx;
int dsty;
//src mat with roi
cv::Mat mat1_roi;
cv::Mat mat2_roi;
cv::Mat mat3_roi;
cv::Mat mat4_roi;
//dst mat with roi
cv::Mat dst_roi;
std::vector<cv::ocl::Info> oclinfo;
//ocl dst mat for testing
cv::ocl::oclMat gdst_whole;
//ocl mat with roi
cv::ocl::oclMat gmat1;
cv::ocl::oclMat gmat2;
cv::ocl::oclMat gmat3;
cv::ocl::oclMat gmat4;
cv::ocl::oclMat gdst;
virtual void SetUp()
{
type = GET_PARAM(0);
channels = GET_PARAM(1);
cv::RNG& rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
mat1 = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false);
mat2 = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false);
mat3 = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false);
mat4 = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false);
dst = randomMat(rng, size, CV_MAKETYPE(type, channels), 5, 16, false);
int devnums = getDevice(oclinfo);
CV_Assert(devnums > 0);
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
setBinpath(CLBINPATH);
}
void Has_roi(int b)
{
//cv::RNG& rng = TS::ptr()->get_rng();
if(b)
{
//randomize ROI
roicols = mat1.cols-1; //start
roirows = mat1.rows-1;
src1x = 1;
src1y = 1;
src2x = 1;
src2y = 1;
src3x = 1;
src3y = 1;
src4x = 1;
src4y = 1;
dstx = 1;
dsty =1;
}else
{
roicols = mat1.cols;
roirows = mat1.rows;
src1x = 0;
src1y = 0;
src2x = 0;
src2y = 0;
src3x = 0;
src3y = 0;
src4x = 0;
src4y = 0;
dstx = 0;
dsty = 0;
};
mat1_roi = mat1(Rect(src1x,src1y,roicols,roirows));
mat2_roi = mat2(Rect(src2x,src2y,roicols,roirows));
mat3_roi = mat3(Rect(src3x,src3y,roicols,roirows));
mat4_roi = mat4(Rect(src4x,src4y,roicols,roirows));
dst_roi = dst(Rect(dstx,dsty,roicols,roirows));
}
};
struct Merge : MergeTestBase {};
TEST_P(Merge, Accuracy)
{
#ifndef PRINT_KERNEL_RUN_TIME
double totalcputick=0;
double totalgputick=0;
double totalgputick_kernel=0;
double t0=0;
double t1=0;
double t2=0;
for(int k=0;k<2;k++){
totalcputick=0;
totalgputick=0;
totalgputick_kernel=0;
for(int j = 0; j < LOOP_TIMES+1; j ++)
{
Has_roi(k);
std::vector<cv::Mat> dev_src;
dev_src.push_back(mat1_roi);
dev_src.push_back(mat2_roi);
dev_src.push_back(mat3_roi);
dev_src.push_back(mat4_roi);
t0 = (double)cvGetTickCount();//cpu start
cv::merge(dev_src, dst_roi);
t0 = (double)cvGetTickCount() - t0;//cpu end
t1 = (double)cvGetTickCount();//gpu start1 ]
gmat1 = mat1_roi;
gmat2 = mat2_roi;
gmat3 = mat3_roi;
gmat4 = mat4_roi;
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
std::vector<cv::ocl::oclMat> dev_gsrc;
dev_gsrc.push_back(gmat1);
dev_gsrc.push_back(gmat2);
dev_gsrc.push_back(gmat3);
dev_gsrc.push_back(gmat4);
t2=(double)cvGetTickCount();//kernel
cv::ocl::merge(dev_gsrc, gdst);
t2 = (double)cvGetTickCount() - t2;//kernel
cv::Mat cpu_dst;
gdst_whole.download (cpu_dst);//download
t1 = (double)cvGetTickCount() - t1;//gpu end1
if(j == 0)
continue;
totalgputick=t1+totalgputick;
totalcputick=t0+totalcputick;
totalgputick_kernel=t2+totalgputick_kernel;
}
if(k==0){cout<<"no roi\n";}else{cout<<"with roi\n";};
cout << "average cpu runtime is " << totalcputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime is " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime without data transfer is " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
}
#else
for(int j = 0; j < 2; j ++)
{
Has_roi(j);
gmat1 = mat1_roi;
gmat2 = mat2_roi;
gmat3 = mat3_roi;
gmat4 = mat4_roi;
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx,dsty,roicols,roirows));
std::vector<cv::ocl::oclMat> dev_gsrc;
dev_gsrc.push_back(gmat1);
dev_gsrc.push_back(gmat2);
dev_gsrc.push_back(gmat3);
dev_gsrc.push_back(gmat4);
if(j==0){cout<<"no roi:";}else{cout<<"\nwith roi:";};
cv::ocl::merge(dev_gsrc, gdst);
};
#endif
}
PARAM_TEST_CASE(SplitTestBase, MatType, int)
{
int type;
int channels;
//src mat
cv::Mat mat;
//dstmat
cv::Mat dst1;
cv::Mat dst2;
cv::Mat dst3;
cv::Mat dst4;
// set up roi
int roicols;
int roirows;
int srcx;
int srcy;
int dst1x;
int dst1y;
int dst2x;
int dst2y;
int dst3x;
int dst3y;
int dst4x;
int dst4y;
//src mat with roi
cv::Mat mat_roi;
//dst mat with roi
cv::Mat dst1_roi;
cv::Mat dst2_roi;
cv::Mat dst3_roi;
cv::Mat dst4_roi;
std::vector<cv::ocl::Info> oclinfo;
//ocl dst mat for testing
cv::ocl::oclMat gdst1_whole;
cv::ocl::oclMat gdst2_whole;
cv::ocl::oclMat gdst3_whole;
cv::ocl::oclMat gdst4_whole;
//ocl mat with roi
cv::ocl::oclMat gmat;
cv::ocl::oclMat gdst1;
cv::ocl::oclMat gdst2;
cv::ocl::oclMat gdst3;
cv::ocl::oclMat gdst4;
virtual void SetUp()
{
type = GET_PARAM(0);
channels = GET_PARAM(1);
cv::RNG& rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
mat = randomMat(rng, size, CV_MAKETYPE(type, channels), 5, 16, false);
dst1 = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false);
dst2 = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false);
dst3 = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false);
dst4 = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false);
int devnums = getDevice(oclinfo);
CV_Assert(devnums > 0);
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
setBinpath(CLBINPATH);
}
void Has_roi(int b)
{
//cv::RNG& rng = TS::ptr()->get_rng();
if(b)
{
//randomize ROI
roicols = mat.cols-1; //start
roirows = mat.rows-1;
srcx = 1;
srcx = 1;
dst1x = 1;
dst1y =1;
dst2x = 1;
dst2y =1;
dst3x = 1;
dst3y =1;
dst4x = 1;
dst4y =1;
}else
{
roicols = mat.cols;
roirows = mat.rows;
srcx = 0;
srcy = 0;
dst1x = 0;
dst1y = 0;
dst2x = 0;
dst2y =0;
dst3x = 0;
dst3y =0;
dst4x = 0;
dst4y =0;
};
mat_roi = mat(Rect(srcx,srcy,roicols,roirows));
dst1_roi = dst1(Rect(dst1x,dst1y,roicols,roirows));
dst2_roi = dst2(Rect(dst2x,dst2y,roicols,roirows));
dst3_roi = dst3(Rect(dst3x,dst3y,roicols,roirows));
dst4_roi = dst4(Rect(dst4x,dst4y,roicols,roirows));
}
};
struct Split :SplitTestBase {};
TEST_P(Split, Accuracy)
{
#ifndef PRINT_KERNEL_RUN_TIME
double totalcputick=0;
double totalgputick=0;
double totalgputick_kernel=0;
double t0=0;
double t1=0;
double t2=0;
for(int k=0;k<2;k++){
totalcputick=0;
totalgputick=0;
totalgputick_kernel=0;
for(int j = 0; j < LOOP_TIMES+1; j ++)
{
Has_roi(k);
cv::Mat dev_dst[4] = {dst1_roi, dst2_roi, dst3_roi, dst4_roi};
cv::ocl::oclMat dev_gdst[4] = {gdst1, gdst2, gdst3, gdst4};
t0 = (double)cvGetTickCount();//cpu start
cv::split(mat_roi, dev_dst);
t0 = (double)cvGetTickCount() - t0;//cpu end
t1 = (double)cvGetTickCount();//gpu start1
gdst1_whole = dst1;
gdst1 = gdst1_whole(Rect(dst1x,dst1y,roicols,roirows));
gdst2_whole = dst2;
gdst2 = gdst2_whole(Rect(dst2x,dst2y,roicols,roirows));
gdst3_whole = dst3;
gdst3 = gdst3_whole(Rect(dst3x,dst3y,roicols,roirows));
gdst4_whole = dst4;
gdst4 = gdst4_whole(Rect(dst4x,dst4y,roicols,roirows));
gmat = mat_roi;
t2=(double)cvGetTickCount();//kernel
cv::ocl::split(gmat, dev_gdst);
t2 = (double)cvGetTickCount() - t2;//kernel
cv::Mat cpu_dst1;
cv::Mat cpu_dst2;
cv::Mat cpu_dst3;
cv::Mat cpu_dst4;
gdst1_whole.download(cpu_dst1);
gdst2_whole.download(cpu_dst2);
gdst3_whole.download(cpu_dst3);
gdst4_whole.download(cpu_dst4);
t1 = (double)cvGetTickCount() - t1;//gpu end1
if(j == 0)
continue;
totalgputick=t1+totalgputick;
totalcputick=t0+totalcputick;
totalgputick_kernel=t2+totalgputick_kernel;
}
if(k==0){cout<<"no roi\n";}else{cout<<"with roi\n";};
cout << "average cpu runtime is " << totalcputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime is " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
cout << "average gpu runtime without data transfer is " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
}
#else
for(int j = 0; j < 2; j ++)
{
Has_roi(j);
cv::Mat dev_dst[4] = {dst1_roi, dst2_roi, dst3_roi, dst4_roi};
cv::ocl::oclMat dev_gdst[4] = {gdst1, gdst2, gdst3, gdst4};
gdst1_whole = dst1;
gdst1 = gdst1_whole(Rect(dst1x,dst1y,roicols,roirows));
gdst2_whole = dst2;
gdst2 = gdst2_whole(Rect(dst2x,dst2y,roicols,roirows));
gdst3_whole = dst3;
gdst3 = gdst3_whole(Rect(dst3x,dst3y,roicols,roirows));
gdst4_whole = dst4;
gdst4 = gdst4_whole(Rect(dst4x,dst4y,roicols,roirows));
gmat = mat_roi;
if(j==0){cout<<"no roi:";}else{cout<<"\nwith roi:";};
cv::ocl::split(gmat, dev_gdst);
};
#endif
}
//*************test*****************
INSTANTIATE_TEST_CASE_P(SplitMerge, Merge, Combine(
Values(CV_8UC4, CV_32FC4), Values(1, 4)));
INSTANTIATE_TEST_CASE_P(SplitMerge, Split , Combine(
Values(CV_8U, CV_32S, CV_32F), Values(1, 4)));
#endif // HAVE_OPENCL

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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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 "precomp.hpp"
#define VARNAME(A) #A
using namespace std;
using namespace cv;
using namespace cv::gpu;
using namespace cvtest;
//std::string generateVarList(int first,...)
//{
// vector<std::string> varname;
//
// va_list argp;
// string s;
// stringstream ss;
// va_start(argp,first);
// int i=first;
// while(i!=-1)
// {
// ss<<i<<",";
// i=va_arg(argp,int);
// };
// s=ss.str();
// va_end(argp);
// return s;
//};
//std::string generateVarList(int& p1,int& p2)
//{
// stringstream ss;
// ss<<VARNAME(p1)<<":"<<src1x<<","<<VARNAME(p2)<<":"<<src1y;
// return ss.str();
//};
int randomInt(int minVal, int maxVal)
{
RNG& rng = TS::ptr()->get_rng();
return rng.uniform(minVal, maxVal);
}
double randomDouble(double minVal, double maxVal)
{
RNG& rng = TS::ptr()->get_rng();
return rng.uniform(minVal, maxVal);
}
Size randomSize(int minVal, int maxVal)
{
return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
}
Scalar randomScalar(double minVal, double maxVal)
{
return Scalar(randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal));
}
Mat randomMat(Size size, int type, double minVal, double maxVal)
{
return randomMat(TS::ptr()->get_rng(), size, type, minVal, maxVal, false);
}
/*
void showDiff(InputArray gold_, InputArray actual_, double eps)
{
Mat gold;
if (gold_.kind() == _InputArray::MAT)
gold = gold_.getMat();
else
gold_.getGpuMat().download(gold);
Mat actual;
if (actual_.kind() == _InputArray::MAT)
actual = actual_.getMat();
else
actual_.getGpuMat().download(actual);
Mat diff;
absdiff(gold, actual, diff);
threshold(diff, diff, eps, 255.0, cv::THRESH_BINARY);
namedWindow("gold", WINDOW_NORMAL);
namedWindow("actual", WINDOW_NORMAL);
namedWindow("diff", WINDOW_NORMAL);
imshow("gold", gold);
imshow("actual", actual);
imshow("diff", diff);
waitKey();
}
*/
/*
bool supportFeature(const DeviceInfo& info, FeatureSet feature)
{
return TargetArchs::builtWith(feature) && info.supports(feature);
}
const vector<DeviceInfo>& devices()
{
static vector<DeviceInfo> devs;
static bool first = true;
if (first)
{
int deviceCount = getCudaEnabledDeviceCount();
devs.reserve(deviceCount);
for (int i = 0; i < deviceCount; ++i)
{
DeviceInfo info(i);
if (info.isCompatible())
devs.push_back(info);
}
first = false;
}
return devs;
}
vector<DeviceInfo> devices(FeatureSet feature)
{
const vector<DeviceInfo>& d = devices();
vector<DeviceInfo> devs_filtered;
if (TargetArchs::builtWith(feature))
{
devs_filtered.reserve(d.size());
for (size_t i = 0, size = d.size(); i < size; ++i)
{
const DeviceInfo& info = d[i];
if (info.supports(feature))
devs_filtered.push_back(info);
}
}
return devs_filtered;
}
*/
vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end)
{
vector<MatType> v;
v.reserve((depth_end - depth_start + 1) * (cn_end - cn_start + 1));
for (int depth = depth_start; depth <= depth_end; ++depth)
{
for (int cn = cn_start; cn <= cn_end; ++cn)
{
v.push_back(CV_MAKETYPE(depth, cn));
}
}
return v;
}
const vector<MatType>& all_types()
{
static vector<MatType> v = types(CV_8U, CV_64F, 1, 4);
return v;
}
Mat readImage(const string& fileName, int flags)
{
return imread(string(cvtest::TS::ptr()->get_data_path()) + fileName, flags);
}
Mat readImageType(const string& fname, int type)
{
Mat src = readImage(fname, CV_MAT_CN(type) == 1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
if (CV_MAT_CN(type) == 4)
{
Mat temp;
cvtColor(src, temp, cv::COLOR_BGR2BGRA);
swap(src, temp);
}
src.convertTo(src, CV_MAT_DEPTH(type));
return src;
}
double checkNorm(const Mat& m)
{
return norm(m, NORM_INF);
}
double checkNorm(const Mat& m1, const Mat& m2)
{
return norm(m1, m2, NORM_INF);
}
double checkSimilarity(const Mat& m1, const Mat& m2)
{
Mat diff;
matchTemplate(m1, m2, diff, CV_TM_CCORR_NORMED);
return std::abs(diff.at<float>(0, 0) - 1.f);
}
/*
void cv::ocl::PrintTo(const DeviceInfo& info, ostream* os)
{
(*os) << info.name();
}
*/
void PrintTo(const Inverse& inverse, std::ostream* os)
{
if (inverse)
(*os) << "inverse";
else
(*os) << "direct";
}

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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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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*/
#ifndef __OPENCV_TEST_UTILITY_HPP__
#define __OPENCV_TEST_UTILITY_HPP__
//#define PRINT_KERNEL_RUN_TIME
#ifdef PRINT_KERNEL_RUN_TIME
#define LOOP_TIMES 1
#else
#define LOOP_TIMES 1
#endif
#define MWIDTH 2557
#define MHEIGHT 2579
#define CLBINPATH ".\\"
int randomInt(int minVal, int maxVal);
double randomDouble(double minVal, double maxVal);
//std::string generateVarList(int first,...);
std::string generateVarList(int& p1,int& p2);
cv::Size randomSize(int minVal, int maxVal);
cv::Scalar randomScalar(double minVal, double maxVal);
cv::Mat randomMat(cv::Size size, int type, double minVal = 0.0, double maxVal = 255.0);
void showDiff(cv::InputArray gold, cv::InputArray actual, double eps);
//! return true if device supports specified feature and gpu module was built with support the feature.
//bool supportFeature(const cv::gpu::DeviceInfo& info, cv::gpu::FeatureSet feature);
//! return all devices compatible with current gpu module build.
//const std::vector<cv::ocl::DeviceInfo>& devices();
//! return all devices compatible with current gpu module build which support specified feature.
//std::vector<cv::ocl::DeviceInfo> devices(cv::gpu::FeatureSet feature);
//! read image from testdata folder.
cv::Mat readImage(const std::string& fileName, int flags = cv::IMREAD_COLOR);
cv::Mat readImageType(const std::string& fname, int type);
double checkNorm(const cv::Mat& m);
double checkNorm(const cv::Mat& m1, const cv::Mat& m2);
double checkSimilarity(const cv::Mat& m1, const cv::Mat& m2);
#define EXPECT_MAT_NORM(mat, eps) \
{ \
EXPECT_LE(checkNorm(cv::Mat(mat)), eps) \
}
//#define EXPECT_MAT_NEAR(mat1, mat2, eps) \
//{ \
// ASSERT_EQ(mat1.type(), mat2.type()); \
// ASSERT_EQ(mat1.size(), mat2.size()); \
// EXPECT_LE(checkNorm(cv::Mat(mat1), cv::Mat(mat2)), eps); \
//}
#define EXPECT_MAT_NEAR(mat1, mat2, eps,s) \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(checkNorm(cv::Mat(mat1), cv::Mat(mat2)), eps)<<s; \
}
#define EXPECT_MAT_SIMILAR(mat1, mat2, eps) \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(checkSimilarity(cv::Mat(mat1), cv::Mat(mat2)), eps); \
}
namespace cv
{
namespace ocl
{
// void PrintTo(const DeviceInfo& info, std::ostream* os);
}
}
using perf::MatDepth;
using perf::MatType;
//! return vector with types from specified range.
std::vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end);
//! return vector with all types (depth: CV_8U-CV_64F, channels: 1-4).
const std::vector<MatType>& all_types();
class Inverse
{
public:
inline Inverse(bool val = false) : val_(val) {}
inline operator bool() const { return val_; }
private:
bool val_;
};
void PrintTo(const Inverse& useRoi, std::ostream* os);
CV_ENUM(CmpCode, cv::CMP_EQ, cv::CMP_GT, cv::CMP_GE, cv::CMP_LT, cv::CMP_LE, cv::CMP_NE)
CV_ENUM(NormCode, cv::NORM_INF, cv::NORM_L1, cv::NORM_L2, cv::NORM_TYPE_MASK, cv::NORM_RELATIVE, cv::NORM_MINMAX)
enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1};
CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y)
CV_ENUM(ReduceOp, CV_REDUCE_SUM, CV_REDUCE_AVG, CV_REDUCE_MAX, CV_REDUCE_MIN)
CV_FLAGS(GemmFlags, cv::GEMM_1_T, cv::GEMM_2_T, cv::GEMM_3_T);
CV_ENUM(MorphOp, cv::MORPH_OPEN, cv::MORPH_CLOSE, cv::MORPH_GRADIENT, cv::MORPH_TOPHAT, cv::MORPH_BLACKHAT)
CV_ENUM(ThreshOp, cv::THRESH_BINARY, cv::THRESH_BINARY_INV, cv::THRESH_TRUNC, cv::THRESH_TOZERO, cv::THRESH_TOZERO_INV)
CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC)
CV_ENUM(Border, cv::BORDER_REFLECT101, cv::BORDER_REPLICATE, cv::BORDER_CONSTANT, cv::BORDER_REFLECT, cv::BORDER_WRAP)
CV_FLAGS(WarpFlags, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC, cv::WARP_INVERSE_MAP)
CV_ENUM(TemplateMethod, cv::TM_SQDIFF, cv::TM_SQDIFF_NORMED, cv::TM_CCORR, cv::TM_CCORR_NORMED, cv::TM_CCOEFF, cv::TM_CCOEFF_NORMED)
CV_FLAGS(DftFlags, cv::DFT_INVERSE, cv::DFT_SCALE, cv::DFT_ROWS, cv::DFT_COMPLEX_OUTPUT, cv::DFT_REAL_OUTPUT)
void run_perf_test();
#define PARAM_TEST_CASE(name, ...) struct name : testing::TestWithParam< std::tr1::tuple< __VA_ARGS__ > >
#define GET_PARAM(k) std::tr1::get< k >(GetParam())
#define ALL_DEVICES testing::ValuesIn(devices())
#define DEVICES(feature) testing::ValuesIn(devices(feature))
#define ALL_TYPES testing::ValuesIn(all_types())
#define TYPES(depth_start, depth_end, cn_start, cn_end) testing::ValuesIn(types(depth_start, depth_end, cn_start, cn_end))
#define DIFFERENT_SIZES testing::Values(cv::Size(128, 128), cv::Size(113, 113))
#define DIRECT_INVERSE testing::Values(Inverse(false), Inverse(true))
#endif // __OPENCV_TEST_UTILITY_HPP__