generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity
opencv/modules/ocl/test/test_imgproc.cpp
Niko 5df77a841e remove redundant OPENCL_DIR flag 
remove as much warnings as possible
use enum instead of MACRO for ocl.hpp
add command line parser in accuracy test and perf test
some bug fix for arthim functions
2012-10-22 15:14:22 +08:00

1762 lines
54 KiB
C++
Raw Blame History

/*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
// Niko Li, newlife20080214@gmail.com
// Jia Haipeng, jiahaipeng95@gmail.com
// Shengen Yan, yanshengen@gmail.com
// Jiang Liyuan, lyuan001.good@163.com
// Rock Li, Rock.Li@amd.com
// Wu Zailong, bullet@yeah.net
// Xu Pang, pangxu010@163.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;
MatType nulltype = -1;
#define ONE_TYPE(type) testing::ValuesIn(typeVector(type))
#define NULL_TYPE testing::ValuesIn(typeVector(nulltype))
vector<MatType> typeVector(MatType type)
{
vector<MatType> v;
v.push_back(type);
return v;
}
typedef struct
{
short x;
short y;
} COOR;
COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep, cv::Size size, int sp, int sr, int maxIter, float eps, int *tab)
{
int isr2 = sr * sr;
int c0, c1, c2, c3;
int iter;
uchar *ptr = NULL;
uchar *pstart = NULL;
int revx = 0, revy = 0;
c0 = sptr[0];
c1 = sptr[1];
c2 = sptr[2];
c3 = sptr[3];
// iterate meanshift procedure
for(iter = 0; iter < maxIter; iter++ )
{
int count = 0;
int s0 = 0, s1 = 0, s2 = 0, sx = 0, sy = 0;
//mean shift: process pixels in window (p-sigmaSp)x(p+sigmaSp)
int minx = x0 - sp;
int miny = y0 - sp;
int maxx = x0 + sp;
int maxy = y0 + sp;
//deal with the image boundary
if(minx < 0) minx = 0;
if(miny < 0) miny = 0;
if(maxx >= size.width) maxx = size.width - 1;
if(maxy >= size.height) maxy = size.height - 1;
if(iter == 0)
{
pstart = sptr;
}
else
{
pstart = pstart + revy * sstep + (revx << 2); //point to the new position
}
ptr = pstart;
ptr = ptr + (miny - y0) * sstep + ((minx - x0) << 2); //point to the start in the row
for( int y = miny; y <= maxy; y++, ptr += sstep - ((maxx - minx + 1) << 2))
{
int rowCount = 0;
int x = minx;
#if CV_ENABLE_UNROLLED
for( ; x + 4 <= maxx; x += 4, ptr += 16)
{
int t0, t1, t2;
t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
{
s0 += t0;
s1 += t1;
s2 += t2;
sx += x;
rowCount++;
}
t0 = ptr[4], t1 = ptr[5], t2 = ptr[6];
if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
{
s0 += t0;
s1 += t1;
s2 += t2;
sx += x + 1;
rowCount++;
}
t0 = ptr[8], t1 = ptr[9], t2 = ptr[10];
if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
{
s0 += t0;
s1 += t1;
s2 += t2;
sx += x + 2;
rowCount++;
}
t0 = ptr[12], t1 = ptr[13], t2 = ptr[14];
if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
{
s0 += t0;
s1 += t1;
s2 += t2;
sx += x + 3;
rowCount++;
}
}
#endif
for(; x <= maxx; x++, ptr += 4)
{
int t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
{
s0 += t0;
s1 += t1;
s2 += t2;
sx += x;
rowCount++;
}
}
if(rowCount == 0)
continue;
count += rowCount;
sy += y * rowCount;
}
if( count == 0 )
break;
double icount = 1.0 / count;
int x1 = cvFloor(sx * icount);
int y1 = cvFloor(sy * icount);
s0 = cvFloor(s0 * icount);
s1 = cvFloor(s1 * icount);
s2 = cvFloor(s2 * icount);
bool stopFlag = (x0 == x1 && y0 == y1) || (abs(x1 - x0) + abs(y1 - y0) +
tab[s0 - c0 + 255] + tab[s1 - c1 + 255] + tab[s2 - c2 + 255] <= eps);
//revise the pointer corresponding to the new (y0,x0)
revx = x1 - x0;
revy = y1 - y0;
x0 = x1;
y0 = y1;
c0 = s0;
c1 = s1;
c2 = s2;
if( stopFlag )
break;
} //for iter
dptr[0] = (uchar)c0;
dptr[1] = (uchar)c1;
dptr[2] = (uchar)c2;
dptr[3] = (uchar)c3;
COOR coor;
coor.x = x0;
coor.y = y0;
return coor;
}
void meanShiftFiltering_(const Mat &src_roi, Mat &dst_roi, int sp, int sr, cv::TermCriteria crit)
{
if( src_roi.empty() )
CV_Error( CV_StsBadArg, "The input image is empty" );
if( src_roi.depth() != CV_8U || src_roi.channels() != 4 )
CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );
CV_Assert( (src_roi.cols == dst_roi.cols) && (src_roi.rows == dst_roi.rows) );
CV_Assert( !(dst_roi.step & 0x3) );
if( !(crit.type & cv::TermCriteria::MAX_ITER) )
crit.maxCount = 5;
int maxIter = std::min(std::max(crit.maxCount, 1), 100);
float eps;
if( !(crit.type & cv::TermCriteria::EPS) )
eps = 1.f;
eps = (float)std::max(crit.epsilon, 0.0);
int tab[512];
for(int i = 0; i < 512; i++)
tab[i] = (i - 255) * (i - 255);
uchar *sptr = src_roi.data;
uchar *dptr = dst_roi.data;
int sstep = (int)src_roi.step;
int dstep = (int)dst_roi.step;
cv::Size size = src_roi.size();
for(int i = 0; i < size.height; i++, sptr += sstep - (size.width << 2),
dptr += dstep - (size.width << 2))
{
for(int j = 0; j < size.width; j++, sptr += 4, dptr += 4)
{
do_meanShift(j, i, sptr, dptr, sstep, size, sp, sr, maxIter, eps, tab);
}
}
}
void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi, int sp, int sr, cv::TermCriteria crit)
{
if( src_roi.empty() )
CV_Error( CV_StsBadArg, "The input image is empty" );
if( src_roi.depth() != CV_8U || src_roi.channels() != 4 )
CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );
CV_Assert( (src_roi.cols == dst_roi.cols) && (src_roi.rows == dst_roi.rows) &&
(src_roi.cols == dstCoor_roi.cols) && (src_roi.rows == dstCoor_roi.rows));
CV_Assert( !(dstCoor_roi.step & 0x3) );
if( !(crit.type & cv::TermCriteria::MAX_ITER) )
crit.maxCount = 5;
int maxIter = std::min(std::max(crit.maxCount, 1), 100);
float eps;
if( !(crit.type & cv::TermCriteria::EPS) )
eps = 1.f;
eps = (float)std::max(crit.epsilon, 0.0);
int tab[512];
for(int i = 0; i < 512; i++)
tab[i] = (i - 255) * (i - 255);
uchar *sptr = src_roi.data;
uchar *dptr = dst_roi.data;
short *dCoorptr = (short *)dstCoor_roi.data;
int sstep = (int)src_roi.step;
int dstep = (int)dst_roi.step;
int dCoorstep = (int)dstCoor_roi.step >> 1;
cv::Size size = src_roi.size();
for(int i = 0; i < size.height; i++, sptr += sstep - (size.width << 2),
dptr += dstep - (size.width << 2), dCoorptr += dCoorstep - (size.width << 1))
{
for(int j = 0; j < size.width; j++, sptr += 4, dptr += 4, dCoorptr += 2)
{
*((COOR *)dCoorptr) = do_meanShift(j, i, sptr, dptr, sstep, size, sp, sr, maxIter, eps, tab);
}
}
}
PARAM_TEST_CASE(ImgprocTestBase, MatType, MatType, MatType, MatType, MatType, bool)
{
int type1, type2, type3, type4, type5;
cv::Scalar val;
// set up roi
int roicols;
int roirows;
int src1x;
int src1y;
int src2x;
int src2y;
int dstx;
int dsty;
int dst1x;
int dst1y;
int maskx;
int masky;
//mat
cv::Mat mat1;
cv::Mat mat2;
cv::Mat mask;
cv::Mat dst;
cv::Mat dst1; //bak, for two outputs
//mat with roi
cv::Mat mat1_roi;
cv::Mat mat2_roi;
cv::Mat mask_roi;
cv::Mat dst_roi;
cv::Mat dst1_roi; //bak
//std::vector<cv::ocl::Info> oclinfo;
//ocl mat
cv::ocl::oclMat clmat1;
cv::ocl::oclMat clmat2;
cv::ocl::oclMat clmask;
cv::ocl::oclMat cldst;
cv::ocl::oclMat cldst1; //bak
//ocl mat with roi
cv::ocl::oclMat clmat1_roi;
cv::ocl::oclMat clmat2_roi;
cv::ocl::oclMat clmask_roi;
cv::ocl::oclMat cldst_roi;
cv::ocl::oclMat cldst1_roi;
virtual void SetUp()
{
type1 = GET_PARAM(0);
type2 = GET_PARAM(1);
type3 = GET_PARAM(2);
type4 = GET_PARAM(3);
type5 = GET_PARAM(4);
cv::RNG &rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
double min = 1, max = 20;
//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
//CV_Assert(devnums > 0);
////if you want to use undefault device, set it here
////setDevice(oclinfo[0]);
if(type1 != nulltype)
{
mat1 = randomMat(rng, size, type1, min, max, false);
clmat1 = mat1;
}
if(type2 != nulltype)
{
mat2 = randomMat(rng, size, type2, min, max, false);
clmat2 = mat2;
}
if(type3 != nulltype)
{
dst = randomMat(rng, size, type3, min, max, false);
cldst = dst;
}
if(type4 != nulltype)
{
dst1 = randomMat(rng, size, type4, min, max, false);
cldst1 = dst1;
}
if(type5 != nulltype)
{
mask = randomMat(rng, size, CV_8UC1, 0, 2, false);
cv::threshold(mask, mask, 0.5, 255., type5);
clmask = mask;
}
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));
}
void random_roi()
{
#ifdef RANDOMROI
//randomize ROI
cv::RNG &rng = TS::ptr()->get_rng();
roicols = rng.uniform(1, mat1.cols);
roirows = rng.uniform(1, mat1.rows);
src1x = rng.uniform(0, mat1.cols - roicols);
src1y = rng.uniform(0, mat1.rows - roirows);
src2x = rng.uniform(0, mat2.cols - roicols);
src2y = rng.uniform(0, mat2.rows - roirows);
dstx = rng.uniform(0, dst.cols - roicols);
dsty = rng.uniform(0, dst.rows - roirows);
dst1x = rng.uniform(0, dst1.cols - roicols);
dst1y = rng.uniform(0, dst1.rows - roirows);
maskx = rng.uniform(0, mask.cols - roicols);
masky = rng.uniform(0, mask.rows - roirows);
#else
roicols = mat1.cols;
roirows = mat1.rows;
src1x = 0;
src1y = 0;
src2x = 0;
src2y = 0;
dstx = 0;
dsty = 0;
dst1x = 0;
dst1y = 0;
maskx = 0;
masky = 0;
#endif
if(type1 != nulltype)
{
mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
clmat1_roi = clmat1(Rect(src1x, src1y, roicols, roirows));
}
if(type2 != nulltype)
{
mat2_roi = mat2(Rect(src2x, src2y, roicols, roirows));
clmat2_roi = clmat2(Rect(src2x, src2y, roicols, roirows));
}
if(type3 != nulltype)
{
dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
cldst_roi = cldst(Rect(dstx, dsty, roicols, roirows));
}
if(type4 != nulltype)
{
dst1_roi = dst1(Rect(dst1x, dst1y, roicols, roirows));
cldst1_roi = cldst1(Rect(dst1x, dst1y, roicols, roirows));
}
if(type5 != nulltype)
{
mask_roi = mask(Rect(maskx, masky, roicols, roirows));
clmask_roi = clmask(Rect(maskx, masky, roicols, roirows));
}
}
};
////////////////////////////////equalizeHist//////////////////////////////////////////
struct equalizeHist : ImgprocTestBase {};
TEST_P(equalizeHist, Mat)
{
if (mat1.type() != CV_8UC1 || mat1.type() != dst.type())
{
cout << "Unsupported type" << endl;
EXPECT_DOUBLE_EQ(0.0, 0.0);
}
else
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::equalizeHist(mat1_roi, dst_roi);
cv::ocl::equalizeHist(clmat1_roi, cldst_roi);
cv::Mat cpu_cldst;
cldst.download(cpu_cldst);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);
EXPECT_MAT_NEAR(dst, cpu_cldst, 1.1, sss);
}
}
}
////////////////////////////////bilateralFilter////////////////////////////////////////////
struct bilateralFilter : ImgprocTestBase {};
TEST_P(bilateralFilter, Mat)
{
double sigmacolor = 50.0;
int radius = 9;
int d = 2 * radius + 1;
double sigmaspace = 20.0;
int bordertype[] = {cv::BORDER_CONSTANT, cv::BORDER_REPLICATE, cv::BORDER_REFLECT, cv::BORDER_WRAP, cv::BORDER_REFLECT_101};
const char *borderstr[] = {"BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP", "BORDER_REFLECT_101"};
if (mat1.depth() != CV_8U || mat1.type() != dst.type())
{
cout << "Unsupported type" << endl;
EXPECT_DOUBLE_EQ(0.0, 0.0);
}
else
{
for(int i = 0; i < sizeof(bordertype) / sizeof(int); i++)
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
if(((bordertype[i] != cv::BORDER_CONSTANT) && (bordertype[i] != cv::BORDER_REPLICATE)) && (mat1_roi.cols <= radius) || (mat1_roi.cols <= radius) || (mat1_roi.rows <= radius) || (mat1_roi.rows <= radius))
{
continue;
}
//if((dstx>=radius) && (dsty >= radius) && (dstx+cldst_roi.cols+radius <=cldst_roi.wholecols) && (dsty+cldst_roi.rows+radius <= cldst_roi.wholerows))
//{
// dst_roi.adjustROI(radius, radius, radius, radius);
// cldst_roi.adjustROI(radius, radius, radius, radius);
//}
//else
//{
// continue;
//}
cv::bilateralFilter(mat1_roi, dst_roi, d, sigmacolor, sigmaspace, bordertype[i] | cv::BORDER_ISOLATED);
cv::ocl::bilateralFilter(clmat1_roi, cldst_roi, d, sigmacolor, sigmaspace, bordertype[i] | cv::BORDER_ISOLATED);
cv::Mat cpu_cldst;
cldst.download(cpu_cldst);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,radius=%d,boredertype=%s", roicols, roirows, src1x, src1y, dstx, dsty, radius, borderstr[i]);
//for(int i=0;i<dst.rows;i++)
//{
// for(int j=0;j<dst.cols*dst.channels();j++)
// {
// if(dst.at<uchar>(i,j)!=cpu_cldst.at<uchar>(i,j))
// cout<< i <<" "<< j <<" "<< (int)dst.at<uchar>(i,j)<<" "<< (int)cpu_cldst.at<uchar>(i,j)<<" ";
// }
// cout<<endl;
//}
EXPECT_MAT_NEAR(dst, cpu_cldst, 1.0, sss);
}
}
}
////////////////////////////////copyMakeBorder////////////////////////////////////////////
struct CopyMakeBorder : ImgprocTestBase {};
TEST_P(CopyMakeBorder, Mat)
{
int bordertype[] = {cv::BORDER_CONSTANT, cv::BORDER_REPLICATE, cv::BORDER_REFLECT, cv::BORDER_WRAP, cv::BORDER_REFLECT_101};
const char *borderstr[] = {"BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP", "BORDER_REFLECT_101"};
cv::RNG &rng = TS::ptr()->get_rng();
int top = rng.uniform(0, 10);
int bottom = rng.uniform(0, 10);
int left = rng.uniform(0, 10);
int right = rng.uniform(0, 10);
if (mat1.type() != dst.type())
{
cout << "Unsupported type" << endl;
EXPECT_DOUBLE_EQ(0.0, 0.0);
}
else
{
for(int i = 0; i < sizeof(bordertype) / sizeof(int); i++)
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
#ifdef RANDOMROI
if(((bordertype[i] != cv::BORDER_CONSTANT) && (bordertype[i] != cv::BORDER_REPLICATE)) && (mat1_roi.cols <= left) || (mat1_roi.cols <= right) || (mat1_roi.rows <= top) || (mat1_roi.rows <= bottom))
{
continue;
}
if((dstx >= left) && (dsty >= top) && (dstx + cldst_roi.cols + right <= cldst_roi.wholecols) && (dsty + cldst_roi.rows + bottom <= cldst_roi.wholerows))
{
dst_roi.adjustROI(top, bottom, left, right);
cldst_roi.adjustROI(top, bottom, left, right);
}
else
{
continue;
}
#endif
cv::copyMakeBorder(mat1_roi, dst_roi, top, bottom, left, right, bordertype[i] | cv::BORDER_ISOLATED, cv::Scalar(1.0));
cv::ocl::copyMakeBorder(clmat1_roi, cldst_roi, top, bottom, left, right, bordertype[i] | cv::BORDER_ISOLATED, cv::Scalar(1.0));
cv::Mat cpu_cldst;
#ifndef RANDOMROI
cldst_roi.download(cpu_cldst);
#else
cldst.download(cpu_cldst);
#endif
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,top=%d,bottom=%d,left=%d,right=%d, bordertype=%s", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, top, bottom, left, right, borderstr[i]);
#ifndef RANDOMROI
EXPECT_MAT_NEAR(dst_roi, cpu_cldst, 0.0, sss);
#else
//for(int i=0;i<dst.rows;i++)
//{
//for(int j=0;j<dst.cols;j++)
//{
// cout<< (int)dst.at<uchar>(i,j)<<" ";
//}
//cout<<endl;
//}
EXPECT_MAT_NEAR(dst, cpu_cldst, 0.0, sss);
#endif
}
}
}
////////////////////////////////cornerMinEigenVal//////////////////////////////////////////
struct cornerMinEigenVal : ImgprocTestBase {};
TEST_P(cornerMinEigenVal, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
int blockSize = 3, apertureSize = 3;//1 + 2 * (rand() % 4);
//int borderType = cv::BORDER_CONSTANT;
//int borderType = cv::BORDER_REPLICATE;
int borderType = cv::BORDER_REFLECT;
cv::cornerMinEigenVal(mat1_roi, dst_roi, blockSize, apertureSize, borderType);
cv::ocl::cornerMinEigenVal(clmat1_roi, cldst_roi, blockSize, apertureSize, borderType);
cv::Mat cpu_cldst;
cldst.download(cpu_cldst);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);
EXPECT_MAT_NEAR(dst, cpu_cldst, 1, sss);
}
}
////////////////////////////////cornerHarris//////////////////////////////////////////
struct cornerHarris : ImgprocTestBase {};
TEST_P(cornerHarris, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
int blockSize = 3, apertureSize = 3; //1 + 2 * (rand() % 4);
double k = 2;
//int borderType = cv::BORDER_CONSTANT;
//int borderType = cv::BORDER_REPLICATE;
int borderType = cv::BORDER_REFLECT;
cv::cornerHarris(mat1_roi, dst_roi, blockSize, apertureSize, k, borderType);
cv::ocl::cornerHarris(clmat1_roi, cldst_roi, blockSize, apertureSize, k, borderType);
cv::Mat cpu_cldst;
cldst.download(cpu_cldst);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);
EXPECT_MAT_NEAR(dst, cpu_cldst, 1, sss);
}
}
////////////////////////////////integral/////////////////////////////////////////////////
struct integral : ImgprocTestBase {};
TEST_P(integral, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::ocl::integral(clmat1_roi, cldst_roi, cldst1_roi);
cv::integral(mat1_roi, dst_roi, dst1_roi);
cv::Mat cpu_cldst, cpu_cldst1;
cldst.download(cpu_cldst);
cldst1.download(cpu_cldst1);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);
EXPECT_MAT_NEAR(dst, cpu_cldst, 0.0, sss);
EXPECT_MAT_NEAR(dst1, cpu_cldst1, 0.0, sss);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// warpAffine & warpPerspective
PARAM_TEST_CASE(WarpTestBase, MatType, int)
{
int type;
cv::Size size;
int interpolation;
//src mat
cv::Mat mat1;
cv::Mat dst;
// set up roi
int src_roicols;
int src_roirows;
int dst_roicols;
int dst_roirows;
int src1x;
int src1y;
int dstx;
int dsty;
//src mat with roi
cv::Mat mat1_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 gdst;
virtual void SetUp()
{
type = GET_PARAM(0);
//dsize = GET_PARAM(1);
interpolation = GET_PARAM(1);
cv::RNG &rng = TS::ptr()->get_rng();
size = cv::Size(MWIDTH, MHEIGHT);
mat1 = randomMat(rng, size, type, 5, 16, false);
dst = randomMat(rng, size, type, 5, 16, false);
//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
//CV_Assert(devnums > 0);
////if you want to use undefault device, set it here
////setDevice(oclinfo[0]);
}
void random_roi()
{
#ifdef RANDOMROI
//randomize ROI
cv::RNG &rng = TS::ptr()->get_rng();
src_roicols = rng.uniform(1, mat1.cols);
src_roirows = rng.uniform(1, mat1.rows);
dst_roicols = rng.uniform(1, dst.cols);
dst_roirows = rng.uniform(1, dst.rows);
src1x = rng.uniform(0, mat1.cols - src_roicols);
src1y = rng.uniform(0, mat1.rows - src_roirows);
dstx = rng.uniform(0, dst.cols - dst_roicols);
dsty = rng.uniform(0, dst.rows - dst_roirows);
#else
src_roicols = mat1.cols;
src_roirows = mat1.rows;
dst_roicols = dst.cols;
dst_roirows = dst.rows;
src1x = 0;
src1y = 0;
dstx = 0;
dsty = 0;
#endif
mat1_roi = mat1(Rect(src1x, src1y, src_roicols, src_roirows));
dst_roi = dst(Rect(dstx, dsty, dst_roicols, dst_roirows));
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx, dsty, dst_roicols, dst_roirows));
gmat1 = mat1_roi;
}
};
/////warpAffine
struct WarpAffine : WarpTestBase {};
TEST_P(WarpAffine, Mat)
{
static const double coeffs[2][3] =
{
{cos(3.14 / 6), -sin(3.14 / 6), 100.0},
{sin(3.14 / 6), cos(3.14 / 6), -100.0}
};
Mat M(2, 3, CV_64F, (void *)coeffs);
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::warpAffine(mat1_roi, dst_roi, M, size, interpolation);
cv::ocl::warpAffine(gmat1, gdst, M, size, interpolation);
cv::Mat cpu_dst;
gdst_whole.download(cpu_dst);
char sss[1024];
sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", src_roicols, src_roirows, dst_roicols, dst_roirows, src1x, src1y, dstx, dsty);
EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
}
}
// warpPerspective
struct WarpPerspective : WarpTestBase {};
TEST_P(WarpPerspective, Mat)
{
static const double coeffs[3][3] =
{
{cos(3.14 / 6), -sin(3.14 / 6), 100.0},
{sin(3.14 / 6), cos(3.14 / 6), -100.0},
{0.0, 0.0, 1.0}
};
Mat M(3, 3, CV_64F, (void *)coeffs);
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::warpPerspective(mat1_roi, dst_roi, M, size, interpolation);
cv::ocl::warpPerspective(gmat1, gdst, M, size, interpolation);
cv::Mat cpu_dst;
gdst_whole.download(cpu_dst);
char sss[1024];
sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", src_roicols, src_roirows, dst_roicols, dst_roirows, src1x, src1y, dstx, dsty);
EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// remap
//////////////////////////////////////////////////////////////////////////////////////////////////
PARAM_TEST_CASE(Remap, MatType, MatType, MatType, int, int)
{
int srcType;
int map1Type;
int map2Type;
cv::Scalar val;
int interpolation;
int bordertype;
cv::Mat src;
cv::Mat dst;
cv::Mat map1;
cv::Mat map2;
//std::vector<cv::ocl::Info> oclinfo;
int src_roicols;
int src_roirows;
int dst_roicols;
int dst_roirows;
int map1_roicols;
int map1_roirows;
int map2_roicols;
int map2_roirows;
int srcx;
int srcy;
int dstx;
int dsty;
int map1x;
int map1y;
int map2x;
int map2y;
cv::Mat src_roi;
cv::Mat dst_roi;
cv::Mat map1_roi;
cv::Mat map2_roi;
//ocl mat for testing
cv::ocl::oclMat gdst;
//ocl mat with roi
cv::ocl::oclMat gsrc_roi;
cv::ocl::oclMat gdst_roi;
cv::ocl::oclMat gmap1_roi;
cv::ocl::oclMat gmap2_roi;
virtual void SetUp()
{
srcType = GET_PARAM(0);
map1Type = GET_PARAM(1);
map2Type = GET_PARAM(2);
interpolation = GET_PARAM(3);
bordertype = GET_PARAM(4);
//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
//CV_Assert(devnums > 0);
cv::RNG &rng = TS::ptr()->get_rng();
cv::Size srcSize = cv::Size(MWIDTH, MHEIGHT);
cv::Size dstSize = cv::Size(MWIDTH, MHEIGHT);
cv::Size map1Size = cv::Size(MWIDTH, MHEIGHT);
double min = 5, max = 16;
if(srcType != nulltype)
{
src = randomMat(rng, srcSize, srcType, min, max, false);
}
if((map1Type == CV_16SC2 && map2Type == nulltype) || (map1Type == CV_32FC2 && map2Type == nulltype))
{
map1 = randomMat(rng, map1Size, map1Type, min, max, false);
}
else if (map1Type == CV_32FC1 && map2Type == CV_32FC1)
{
map1 = randomMat(rng, map1Size, map1Type, min, max, false);
map2 = randomMat(rng, map1Size, map1Type, min, max, false);
}
else
{
cout << "The wrong input type" << endl;
return;
}
dst = randomMat(rng, map1Size, srcType, min, max, false);
switch (src.channels())
{
case 1:
val = cv::Scalar(rng.uniform(0.0, 10.0), 0, 0, 0);
break;
case 2:
val = cv::Scalar(rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), 0, 0);
break;
case 3:
val = cv::Scalar(rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), 0);
break;
case 4:
val = cv::Scalar(rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0));
break;
}
}
void random_roi()
{
cv::RNG &rng = TS::ptr()->get_rng();
dst_roicols = rng.uniform(1, dst.cols);
dst_roirows = rng.uniform(1, dst.rows);
src_roicols = rng.uniform(1, src.cols);
src_roirows = rng.uniform(1, src.rows);
srcx = rng.uniform(0, src.cols - src_roicols);
srcy = rng.uniform(0, src.rows - src_roirows);
dstx = rng.uniform(0, dst.cols - dst_roicols);
dsty = rng.uniform(0, dst.rows - dst_roirows);
map1_roicols = dst_roicols;
map1_roirows = dst_roirows;
map2_roicols = dst_roicols;
map2_roirows = dst_roirows;
map1x = dstx;
map1y = dsty;
map2x = dstx;
map2y = dsty;
if((map1Type == CV_16SC2 && map2Type == nulltype) || (map1Type == CV_32FC2 && map2Type == nulltype))
{
map1_roi = map1(Rect(map1x, map1y, map1_roicols, map1_roirows));
gmap1_roi = map1_roi;
}
else if (map1Type == CV_32FC1 && map2Type == CV_32FC1)
{
map1_roi = map1(Rect(map1x, map1y, map1_roicols, map1_roirows));
gmap1_roi = map1_roi;
map2_roi = map2(Rect(map2x, map2y, map2_roicols, map2_roirows));
gmap2_roi = map2_roi;
}
src_roi = src(Rect(srcx, srcy, src_roicols, src_roirows));
dst_roi = dst(Rect(dstx, dsty, dst_roicols, dst_roirows));
gsrc_roi = src_roi;
gdst = dst;
gdst_roi = gdst(Rect(dstx, dsty, dst_roicols, dst_roirows));
}
};
TEST_P(Remap, Mat)
{
if((interpolation == 1 && map1Type == CV_16SC2) || (map1Type == CV_32FC1 && map2Type == nulltype) || (map1Type == CV_16SC2 && map2Type == CV_32FC1) || (map1Type == CV_32FC2 && map2Type == CV_32FC1))
{
cout << "Don't support the dataType" << endl;
return;
}
int bordertype[] = {cv::BORDER_CONSTANT, cv::BORDER_REPLICATE/*,BORDER_REFLECT,BORDER_WRAP,BORDER_REFLECT_101*/};
const char *borderstr[] = {"BORDER_CONSTANT", "BORDER_REPLICATE"/*, "BORDER_REFLECT","BORDER_WRAP","BORDER_REFLECT_101"*/};
// for(int i = 0; i < sizeof(bordertype)/sizeof(int); i++)
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::remap(src_roi, dst_roi, map1_roi, map2_roi, interpolation, bordertype[0], val);
cv::ocl::remap(gsrc_roi, gdst_roi, gmap1_roi, gmap2_roi, interpolation, bordertype[0], val);
cv::Mat cpu_dst;
gdst.download(cpu_dst);
char sss[1024];
sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d bordertype=%s", src_roicols, src_roirows, dst_roicols, dst_roirows, srcx, srcy, dstx, dsty, borderstr[0]);
if(interpolation == 0)
EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
EXPECT_MAT_NEAR(dst, cpu_dst, 2.0, sss);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// resize
PARAM_TEST_CASE(Resize, MatType, cv::Size, double, double, int)
{
int type;
cv::Size dsize;
double fx, fy;
int interpolation;
//src mat
cv::Mat mat1;
cv::Mat dst;
// set up roi
int src_roicols;
int src_roirows;
int dst_roicols;
int dst_roirows;
int src1x;
int src1y;
int dstx;
int dsty;
//std::vector<cv::ocl::Info> oclinfo;
//src mat with roi
cv::Mat mat1_roi;
cv::Mat dst_roi;
//ocl dst mat for testing
cv::ocl::oclMat gdst_whole;
//ocl mat with roi
cv::ocl::oclMat gmat1;
cv::ocl::oclMat gdst;
virtual void SetUp()
{
type = GET_PARAM(0);
dsize = GET_PARAM(1);
fx = GET_PARAM(2);
fy = GET_PARAM(3);
interpolation = GET_PARAM(4);
cv::RNG &rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
if(dsize == cv::Size() && !(fx > 0 && fy > 0))
{
cout << "invalid dsize and fx fy" << endl;
return;
}
if(dsize == cv::Size())
{
dsize.width = (int)(size.width * fx);
dsize.height = (int)(size.height * fy);
}
mat1 = randomMat(rng, size, type, 5, 16, false);
dst = randomMat(rng, dsize, type, 5, 16, false);
//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
//CV_Assert(devnums > 0);
////if you want to use undefault device, set it here
////setDevice(oclinfo[0]);
}
void random_roi()
{
#ifdef RANDOMROI
//randomize ROI
cv::RNG &rng = TS::ptr()->get_rng();
src_roicols = rng.uniform(1, mat1.cols);
src_roirows = rng.uniform(1, mat1.rows);
dst_roicols = (int)(src_roicols * fx);
dst_roirows = (int)(src_roirows * fy);
src1x = rng.uniform(0, mat1.cols - src_roicols);
src1y = rng.uniform(0, mat1.rows - src_roirows);
dstx = rng.uniform(0, dst.cols - dst_roicols);
dsty = rng.uniform(0, dst.rows - dst_roirows);
#else
src_roicols = mat1.cols;
src_roirows = mat1.rows;
dst_roicols = dst.cols;
dst_roirows = dst.rows;
src1x = 0;
src1y = 0;
dstx = 0;
dsty = 0;
#endif
dsize.width = dst_roicols;
dsize.height = dst_roirows;
mat1_roi = mat1(Rect(src1x, src1y, src_roicols, src_roirows));
dst_roi = dst(Rect(dstx, dsty, dst_roicols, dst_roirows));
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx, dsty, dst_roicols, dst_roirows));
dsize.width = (int)(mat1_roi.size().width * fx);
dsize.height = (int)(mat1_roi.size().height * fy);
gmat1 = mat1_roi;
}
};
TEST_P(Resize, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
// cv::resize(mat1_roi, dst_roi, dsize, fx, fy, interpolation);
// cv::ocl::resize(gmat1, gdst, dsize, fx, fy, interpolation);
if(dst_roicols < 1 || dst_roirows < 1) continue;
cv::resize(mat1_roi, dst_roi, dsize, fx, fy, interpolation);
cv::ocl::resize(gmat1, gdst, dsize, fx, fy, interpolation);
cv::Mat cpu_dst;
gdst_whole.download(cpu_dst);
char sss[1024];
sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", src_roicols, src_roirows, dst_roicols, dst_roirows, src1x, src1y, dstx, dsty);
EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
//threshold
PARAM_TEST_CASE(Threshold, MatType, ThreshOp)
{
int type;
int threshOp;
//src mat
cv::Mat mat1;
cv::Mat dst;
// set up roi
int roicols;
int roirows;
int src1x;
int src1y;
int dstx;
int dsty;
//src mat with roi
cv::Mat mat1_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 gdst;
virtual void SetUp()
{
type = GET_PARAM(0);
threshOp = GET_PARAM(1);
cv::RNG &rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
mat1 = randomMat(rng, size, type, 5, 16, false);
dst = randomMat(rng, size, type, 5, 16, false);
//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
//CV_Assert(devnums > 0);
////if you want to use undefault device, set it here
////setDevice(oclinfo[0]);
}
void random_roi()
{
#ifdef RANDOMROI
//randomize ROI
cv::RNG &rng = TS::ptr()->get_rng();
roicols = rng.uniform(1, mat1.cols);
roirows = rng.uniform(1, mat1.rows);
src1x = rng.uniform(0, mat1.cols - roicols);
src1y = rng.uniform(0, mat1.rows - roirows);
dstx = rng.uniform(0, dst.cols - roicols);
dsty = rng.uniform(0, dst.rows - roirows);
#else
roicols = mat1.cols;
roirows = mat1.rows;
src1x = 0;
src1y = 0;
dstx = 0;
dsty = 0;
#endif
mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
gmat1 = mat1_roi;
}
};
TEST_P(Threshold, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
double maxVal = randomDouble(20.0, 127.0);
double thresh = randomDouble(0.0, maxVal);
cv::threshold(mat1_roi, dst_roi, thresh, maxVal, threshOp);
cv::ocl::threshold(gmat1, gdst, thresh, maxVal, threshOp);
cv::Mat cpu_dst;
gdst_whole.download(cpu_dst);
//EXPECT_MAT_NEAR(dst, cpu_dst, 1e-5)
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x , src1y, dstx, dsty);
EXPECT_MAT_NEAR(dst, cpu_dst, 1, sss);
}
}
PARAM_TEST_CASE(meanShiftTestBase, MatType, MatType, int, int, cv::TermCriteria)
{
int type, typeCoor;
int sp, sr;
cv::TermCriteria crit;
//src mat
cv::Mat src;
cv::Mat dst;
cv::Mat dstCoor;
//set up roi
int roicols;
int roirows;
int srcx;
int srcy;
int dstx;
int dsty;
//src mat with roi
cv::Mat src_roi;
cv::Mat dst_roi;
cv::Mat dstCoor_roi;
//ocl dst mat
cv::ocl::oclMat gdst;
cv::ocl::oclMat gdstCoor;
//std::vector<cv::ocl::Info> oclinfo;
//ocl mat with roi
cv::ocl::oclMat gsrc_roi;
cv::ocl::oclMat gdst_roi;
cv::ocl::oclMat gdstCoor_roi;
virtual void SetUp()
{
type = GET_PARAM(0);
typeCoor = GET_PARAM(1);
sp = GET_PARAM(2);
sr = GET_PARAM(3);
crit = GET_PARAM(4);
cv::RNG &rng = TS::ptr()->get_rng();
// MWIDTH=256, MHEIGHT=256. defined in utility.hpp
cv::Size size = cv::Size(MWIDTH, MHEIGHT);
src = randomMat(rng, size, type, 5, 16, false);
dst = randomMat(rng, size, type, 5, 16, false);
dstCoor = randomMat(rng, size, typeCoor, 5, 16, false);
//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
//CV_Assert(devnums > 0);
////if you want to use undefault device, set it here
////setDevice(oclinfo[0]);
}
void random_roi()
{
#ifdef RANDOMROI
cv::RNG &rng = TS::ptr()->get_rng();
//randomize ROI
roicols = rng.uniform(1, src.cols);
roirows = rng.uniform(1, src.rows);
srcx = rng.uniform(0, src.cols - roicols);
srcy = rng.uniform(0, src.rows - roirows);
dstx = rng.uniform(0, dst.cols - roicols);
dsty = rng.uniform(0, dst.rows - roirows);
#else
roicols = src.cols;
roirows = src.rows;
srcx = 0;
srcy = 0;
dstx = 0;
dsty = 0;
#endif
src_roi = src(Rect(srcx, srcy, roicols, roirows));
dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
dstCoor_roi = dstCoor(Rect(dstx, dsty, roicols, roirows));
gdst = dst;
gdstCoor = dstCoor;
gsrc_roi = src_roi;
gdst_roi = gdst(Rect(dstx, dsty, roicols, roirows)); //gdst_roi
gdstCoor_roi = gdstCoor(Rect(dstx, dsty, roicols, roirows));
}
};
/////////////////////////meanShiftFiltering/////////////////////////////
struct meanShiftFiltering : meanShiftTestBase {};
TEST_P(meanShiftFiltering, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::Mat cpu_gdst;
gdst.download(cpu_gdst);
meanShiftFiltering_(src_roi, dst_roi, sp, sr, crit);
cv::ocl::meanShiftFiltering(gsrc_roi, gdst_roi, sp, sr, crit);
gdst.download(cpu_gdst);
char sss[1024];
char warning[300] = "Warning: If the selected device doesn't support double, a deviation will exist.\nIf the accuracy is acceptable, please ignore it.\n";
sprintf(sss, "roicols=%d,roirows=%d,srcx=%d,srcy=%d,dstx=%d,dsty=%d\n", roicols, roirows, srcx, srcy, dstx, dsty);
strcat(sss, warning);
EXPECT_MAT_NEAR(dst, cpu_gdst, 0.0, sss);
}
}
///////////////////////////meanShiftProc//////////////////////////////////
struct meanShiftProc : meanShiftTestBase {};
TEST_P(meanShiftProc, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::Mat cpu_gdst;
cv::Mat cpu_gdstCoor;
meanShiftProc_(src_roi, dst_roi, dstCoor_roi, sp, sr, crit);
cv::ocl::meanShiftProc(gsrc_roi, gdst_roi, gdstCoor_roi, sp, sr, crit);
gdst.download(cpu_gdst);
gdstCoor.download(cpu_gdstCoor);
char sss[1024];
char warning[300] = "Warning: If the selected device doesn't support double, a deviation will exist.\nIf the accuracy is acceptable, please ignore it.\n";
sprintf(sss, "roicols=%d,roirows=%d,srcx=%d,srcy=%d,dstx=%d,dsty=%d\n", roicols, roirows, srcx, srcy, dstx, dsty);
strcat(sss, warning);
EXPECT_MAT_NEAR(dst, cpu_gdst, 0.0, sss);
EXPECT_MAT_NEAR(dstCoor, cpu_gdstCoor, 0.0, sss);
}
}
///////////////////////////////////////////////////////////////////////////////////////
//hist
void calcHistGold(const cv::Mat &src, cv::Mat &hist)
{
hist.create(1, 256, CV_32SC1);
hist.setTo(cv::Scalar::all(0));
int *hist_row = hist.ptr<int>();
for (int y = 0; y < src.rows; ++y)
{
const uchar *src_row = src.ptr(y);
for (int x = 0; x < src.cols; ++x)
++hist_row[src_row[x]];
}
}
PARAM_TEST_CASE(histTestBase, MatType, MatType)
{
int type_src;
//src mat
cv::Mat src;
cv::Mat dst_hist;
//set up roi
int roicols;
int roirows;
int srcx;
int srcy;
//src mat with roi
cv::Mat src_roi;
//ocl dst mat, dst_hist and gdst_hist don't have roi
cv::ocl::oclMat gdst_hist;
//ocl mat with roi
cv::ocl::oclMat gsrc_roi;
// std::vector<cv::ocl::Info> oclinfo;
virtual void SetUp()
{
type_src = GET_PARAM(0);
cv::RNG &rng = TS::ptr()->get_rng();
cv::Size size = cv::Size(MWIDTH, MHEIGHT);
src = randomMat(rng, size, type_src, 0, 256, false);
// int devnums = getDevice(oclinfo);
// CV_Assert(devnums > 0);
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
}
void random_roi()
{
#ifdef RANDOMROI
cv::RNG &rng = TS::ptr()->get_rng();
//randomize ROI
roicols = rng.uniform(1, src.cols);
roirows = rng.uniform(1, src.rows);
srcx = rng.uniform(0, src.cols - roicols);
srcy = rng.uniform(0, src.rows - roirows);
#else
roicols = src.cols;
roirows = src.rows;
srcx = 0;
srcy = 0;
#endif
src_roi = src(Rect(srcx, srcy, roicols, roirows));
gsrc_roi = src_roi;
}
};
///////////////////////////calcHist///////////////////////////////////////
struct calcHist : histTestBase {};
TEST_P(calcHist, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::Mat cpu_hist;
calcHistGold(src_roi, dst_hist);
cv::ocl::calcHist(gsrc_roi, gdst_hist);
gdst_hist.download(cpu_hist);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,srcx=%d,srcy=%d\n", roicols, roirows, srcx, srcy);
EXPECT_MAT_NEAR(dst_hist, cpu_hist, 0.0, sss);
}
}
///////////////////////////Convolve//////////////////////////////////
PARAM_TEST_CASE(ConvolveTestBase, MatType, bool)
{
int type;
//src mat
cv::Mat mat1;
cv::Mat mat2;
cv::Mat dst;
cv::Mat dst1; //bak, for two outputs
// set up roi
int roicols;
int roirows;
int src1x;
int src1y;
int src2x;
int src2y;
int dstx;
int dsty;
//src mat with roi
cv::Mat mat1_roi;
cv::Mat mat2_roi;
cv::Mat dst_roi;
cv::Mat dst1_roi; //bak
//ocl dst mat for testing
cv::ocl::oclMat gdst_whole;
cv::ocl::oclMat gdst1_whole; //bak
//ocl mat with roi
cv::ocl::oclMat gmat1;
cv::ocl::oclMat gmat2;
cv::ocl::oclMat gdst;
cv::ocl::oclMat gdst1; //bak
virtual void SetUp()
{
type = GET_PARAM(0);
cv::RNG &rng = TS::ptr()->get_rng();
cv::Size size(MWIDTH, MHEIGHT);
mat1 = randomMat(rng, size, type, 5, 16, false);
mat2 = randomMat(rng, size, type, 5, 16, false);
dst = randomMat(rng, size, type, 5, 16, false);
dst1 = randomMat(rng, size, type, 5, 16, false);
}
void random_roi()
{
cv::RNG &rng = TS::ptr()->get_rng();
#ifdef RANDOMROI
//randomize ROI
roicols = rng.uniform(1, mat1.cols);
roirows = rng.uniform(1, mat1.rows);
src1x = rng.uniform(0, mat1.cols - roicols);
src1y = rng.uniform(0, mat1.rows - roirows);
dstx = rng.uniform(0, dst.cols - roicols);
dsty = rng.uniform(0, dst.rows - roirows);
#else
roicols = mat1.cols;
roirows = mat1.rows;
src1x = 0;
src1y = 0;
dstx = 0;
dsty = 0;
#endif
src2x = rng.uniform(0, mat2.cols - roicols);
src2y = rng.uniform(0, mat2.rows - roirows);
mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
mat2_roi = mat2(Rect(src2x, src2y, roicols, roirows));
dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
dst1_roi = dst1(Rect(dstx, dsty, roicols, roirows));
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
gdst1_whole = dst1;
gdst1 = gdst1_whole(Rect(dstx, dsty, roicols, roirows));
gmat1 = mat1_roi;
gmat2 = mat2_roi;
//end
}
};
struct Convolve : ConvolveTestBase {};
void conv2( cv::Mat x, cv::Mat y, cv::Mat z)
{
int N1 = x.rows;
int M1 = x.cols;
int N2 = y.rows;
int M2 = y.cols;
int i, j;
int m, n;
float *kerneldata = (float *)(x.data);
float *srcdata = (float *)(y.data);
float *dstdata = (float *)(z.data);
for(i = 0; i < N2; i++)
for(j = 0; j < M2; j++)
{
float temp = 0;
for(m = 0; m < N1; m++)
for(n = 0; n < M1; n++)
{
int r, c;
r = min(max((i - N1 / 2 + m), 0), N2 - 1);
c = min(max((j - M1 / 2 + n), 0), M2 - 1);
temp += kerneldata[m * (x.step >> 2) + n] * srcdata[r * (y.step >> 2) + c];
}
dstdata[i * (z.step >> 2) + j] = temp;
}
}
TEST_P(Convolve, Mat)
{
if(mat1.type() != CV_32FC1)
{
cout << "\tUnsupported type\t\n";
}
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::ocl::oclMat temp1;
cv::Mat kernel_cpu = mat2(Rect(0, 0, 7, 7));
temp1 = kernel_cpu;
conv2(kernel_cpu, mat1_roi, dst_roi);
cv::ocl::convolve(gmat1, temp1, gdst);
cv::Mat cpu_dst;
gdst_whole.download(cpu_dst);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, src2x, src2y);
EXPECT_MAT_NEAR(dst, cpu_dst, 1e-1, sss);
}
}
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, equalizeHist, Combine(
ONE_TYPE(CV_8UC1),
NULL_TYPE,
ONE_TYPE(CV_8UC1),
NULL_TYPE,
NULL_TYPE,
Values(false))); // Values(false) is the reserved parameter
//INSTANTIATE_TEST_CASE_P(ImgprocTestBase, bilateralFilter, Combine(
// ONE_TYPE(CV_8UC1),
// NULL_TYPE,
// ONE_TYPE(CV_8UC1),
// NULL_TYPE,
// NULL_TYPE,
// Values(false))); // Values(false) is the reserved parameter
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, bilateralFilter, Combine(
Values(CV_8UC1, CV_8UC3),
NULL_TYPE,
Values(CV_8UC1, CV_8UC3),
NULL_TYPE,
NULL_TYPE,
Values(false))); // Values(false) is the reserved parameter
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, CopyMakeBorder, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32SC1, CV_32SC3, CV_32SC4, CV_32FC1, CV_32FC3, CV_32FC4),
NULL_TYPE,
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32SC1, CV_32SC3, CV_32SC4, CV_32FC1, CV_32FC3, CV_32FC4),
NULL_TYPE,
NULL_TYPE,
Values(false))); // Values(false) is the reserved parameter
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, cornerMinEigenVal, Combine(
Values(CV_8UC1, CV_32FC1),
NULL_TYPE,
ONE_TYPE(CV_32FC1),
NULL_TYPE,
NULL_TYPE,
Values(false))); // Values(false) is the reserved parameter
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, cornerHarris, Combine(
Values(CV_8UC1, CV_32FC1),
NULL_TYPE,
ONE_TYPE(CV_32FC1),
NULL_TYPE,
NULL_TYPE,
Values(false))); // Values(false) is the reserved parameter
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, integral, Combine(
ONE_TYPE(CV_8UC1),
NULL_TYPE,
ONE_TYPE(CV_32SC1),
ONE_TYPE(CV_32FC1),
NULL_TYPE,
Values(false))); // Values(false) is the reserved parameter
INSTANTIATE_TEST_CASE_P(Imgproc, WarpAffine, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values((MatType)cv::INTER_NEAREST, (MatType)cv::INTER_LINEAR,
(MatType)cv::INTER_CUBIC, (MatType)(cv::INTER_NEAREST | cv::WARP_INVERSE_MAP),
(MatType)(cv::INTER_LINEAR | cv::WARP_INVERSE_MAP), (MatType)(cv::INTER_CUBIC | cv::WARP_INVERSE_MAP))));
INSTANTIATE_TEST_CASE_P(Imgproc, WarpPerspective, Combine
(Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values((MatType)cv::INTER_NEAREST, (MatType)cv::INTER_LINEAR,
(MatType)cv::INTER_CUBIC, (MatType)(cv::INTER_NEAREST | cv::WARP_INVERSE_MAP),
(MatType)(cv::INTER_LINEAR | cv::WARP_INVERSE_MAP), (MatType)(cv::INTER_CUBIC | cv::WARP_INVERSE_MAP))));
INSTANTIATE_TEST_CASE_P(Imgproc, Resize, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4), Values(cv::Size()),
Values(0.5, 1.5, 2), Values(0.5, 1.5, 2), Values((MatType)cv::INTER_NEAREST, (MatType)cv::INTER_LINEAR)));
INSTANTIATE_TEST_CASE_P(Imgproc, Threshold, Combine(
Values(CV_8UC1, CV_32FC1), Values(ThreshOp(cv::THRESH_BINARY),
ThreshOp(cv::THRESH_BINARY_INV), ThreshOp(cv::THRESH_TRUNC),
ThreshOp(cv::THRESH_TOZERO), ThreshOp(cv::THRESH_TOZERO_INV))));
INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftFiltering, Combine(
ONE_TYPE(CV_8UC4),
ONE_TYPE(CV_16SC2),
Values(5),
Values(6),
Values(cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 5, 1))
));
INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftProc, Combine(
ONE_TYPE(CV_8UC4),
ONE_TYPE(CV_16SC2),
Values(5),
Values(6),
Values(cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 5, 1))
));
INSTANTIATE_TEST_CASE_P(Imgproc, Remap, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values(CV_32FC1, CV_16SC2, CV_32FC2), Values(-1, CV_32FC1),
Values((int)cv::INTER_NEAREST, (int)cv::INTER_LINEAR),
Values((int)cv::BORDER_CONSTANT)));
INSTANTIATE_TEST_CASE_P(histTestBase, calcHist, Combine(
ONE_TYPE(CV_8UC1),
ONE_TYPE(CV_32SC1) //no use
));
//INSTANTIATE_TEST_CASE_P(ConvolveTestBase, Convolve, Combine(
// Values(CV_32FC1, CV_32FC1),
// Values(false))); // Values(false) is the reserved parameter
#endif // HAVE_OPENCL
Reference in New Issue View Git Blame Copy Permalink