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refactored all the tests in ocl/test/test_imgproc.cpp

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Ilya Lavrenov 12 years ago
parent 4cbf0cb31e
commit 4a81be7d0b
3 changed files with 1069 additions and 1403 deletions
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  1. 1695
      modules/ocl/test/test_imgproc.cpp
  2. 408
      modules/ocl/test/test_mean_shift.cpp
  3. 369
      modules/ocl/test/test_warp.cpp

1695
modules/ocl/test/test_imgproc.cpp
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408
modules/ocl/test/test_mean_shift.cpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Copyright (C) 2010-2012, Multicoreware, 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
// Sen Liu, swjtuls1987@126.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 "test_precomp.hpp"
#ifdef HAVE_OPENCL
using namespace testing;
using namespace std;
using namespace cv;
typedef struct
{
short x;
short y;
} COOR;
COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep, 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;
int x1 = sx / count;
int y1 = sy / count;
s0 = s0 / count;
s1 = s1 / count;
s2 = s2 / count;
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 = (short)x0;
coor.y = (short)y0;
return coor;
}
void meanShiftFiltering_(const Mat &src_roi, Mat &dst_roi, int sp, int sr, 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 & TermCriteria::MAX_ITER) )
crit.maxCount = 5;
int maxIter = std::min(std::max(crit.maxCount, 1), 100);
float eps;
if( !(crit.type & 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;
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, 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 & TermCriteria::MAX_ITER) )
crit.maxCount = 5;
int maxIter = std::min(std::max(crit.maxCount, 1), 100);
float eps;
if( !(crit.type & 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;
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);
}
}
}
//////////////////////////////// meanShift //////////////////////////////////////////
PARAM_TEST_CASE(meanShiftTestBase, MatType, MatType, int, int, TermCriteria, bool)
{
int type, typeCoor;
int sp, sr;
TermCriteria crit;
bool useRoi;
// src mat
Mat src, src_roi;
Mat dst, dst_roi;
Mat dstCoor, dstCoor_roi;
// ocl dst mat
ocl::oclMat gsrc, gsrc_roi;
ocl::oclMat gdst, gdst_roi;
ocl::oclMat gdstCoor, 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);
useRoi = GET_PARAM(5);
}
void random_roi()
{
Size roiSize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, type, 5, 256);
generateOclMat(gsrc, gsrc_roi, src, roiSize, srcBorder);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst, dst_roi, roiSize, dstBorder, type, 5, 256);
generateOclMat(gdst, gdst_roi, dst, roiSize, dstBorder);
randomSubMat(dstCoor, dstCoor_roi, roiSize, dstBorder, typeCoor, 5, 256);
generateOclMat(gdstCoor, gdstCoor_roi, dstCoor, roiSize, dstBorder);
}
void Near(double threshold = 0.0)
{
Mat whole, roi;
gdst.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
void Near1(double threshold = 0.0)
{
Mat whole, roi;
gdstCoor.download(whole);
gdstCoor_roi.download(roi);
EXPECT_MAT_NEAR(dstCoor, whole, threshold);
EXPECT_MAT_NEAR(dstCoor_roi, roi, threshold);
}
};
/////////////////////////meanShiftFiltering/////////////////////////////
typedef meanShiftTestBase meanShiftFiltering;
OCL_TEST_P(meanShiftFiltering, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
meanShiftFiltering_(src_roi, dst_roi, sp, sr, crit);
ocl::meanShiftFiltering(gsrc_roi, gdst_roi, sp, sr, crit);
Near();
}
}
///////////////////////////meanShiftProc//////////////////////////////////
typedef meanShiftTestBase meanShiftProc;
OCL_TEST_P(meanShiftProc, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
meanShiftProc_(src_roi, dst_roi, dstCoor_roi, sp, sr, crit);
ocl::meanShiftProc(gsrc_roi, gdst_roi, gdstCoor_roi, sp, sr, crit);
Near();
Near1();
}
}
/////////////////////////////////////////////////////////////////////////////////////
INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftFiltering, Combine(
Values((MatType)CV_8UC4),
Values((MatType)CV_16SC2),
Values(5),
Values(6),
Values(TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 5, 1)),
Bool()
));
INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftProc, Combine(
Values((MatType)CV_8UC4),
Values((MatType)CV_16SC2),
Values(5),
Values(6),
Values(TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 5, 1)),
Bool()
));
#endif // HAVE_OPENCL

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modules/ocl/test/test_warp.cpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Copyright (C) 2010-2012, Multicoreware, 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
// Sen Liu, swjtuls1987@126.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 "test_precomp.hpp"
#ifdef HAVE_OPENCL
using namespace cv;
using namespace testing;
using namespace std;
static MatType noType = -1;
/////////////////////////////////////////////////////////////////////////////////////////////////
// warpAffine & warpPerspective
PARAM_TEST_CASE(WarpTestBase, MatType, int, bool, bool)
{
int type, interpolation;
Size dsize;
bool useRoi, mapInverse;
Mat src, dst_whole, src_roi, dst_roi;
ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
virtual void SetUp()
{
type = GET_PARAM(0);
interpolation = GET_PARAM(1);
mapInverse = GET_PARAM(2);
useRoi = GET_PARAM(3);
if (mapInverse)
interpolation |= WARP_INVERSE_MAP;
}
void random_roi()
{
Size roiSize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
dsize = randomSize(1, MAX_VALUE);
}
void Near(double threshold = 0.0)
{
Mat whole, roi, diff;
gdst_whole.download(whole);
gdst_roi.download(roi);
imshow("OpenCV", dst_whole);
imshow("OpenCL", whole);
cv::absdiff(whole, dst_whole, diff);
imshow("Diff", diff);
cv::waitKey();
EXPECT_MAT_NEAR(dst_whole, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
/////warpAffine
typedef WarpTestBase WarpAffine;
OCL_TEST_P(WarpAffine, Mat)
{
static const double coeffs[2][3] =
{
{ cos(CV_PI / 6), -sin(CV_PI / 6), 100.0 },
{ sin(CV_PI / 6), cos(CV_PI / 6), -100.0 }
};
static Mat M(2, 3, CV_64FC1, (void *)coeffs);
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
warpAffine(src_roi, dst_roi, M, dsize, interpolation);
ocl::warpAffine(gsrc_roi, gdst_roi, M, dsize, interpolation);
Near(1.0);
}
}
// warpPerspective
typedef WarpTestBase WarpPerspective;
OCL_TEST_P(WarpPerspective, Mat)
{
static const double coeffs[3][3] =
{
{ cos(CV_PI / 6), -sin(CV_PI / 6), 100.0 },
{ sin(CV_PI / 6), cos(CV_PI / 6), -100.0 },
{ 0.0, 0.0, 1.0 }
};
static Mat M(3, 3, CV_64FC1, (void *)coeffs);
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
warpPerspective(src_roi, dst_roi, M, dsize, interpolation);
ocl::warpPerspective(gsrc_roi, gdst_roi, M, dsize, interpolation);
Near(1.0);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// remap
PARAM_TEST_CASE(Remap, int, int, pair<MatType, MatType>, int, bool)
{
int srcType, map1Type, map2Type;
int borderType;
bool useRoi;
Scalar val;
Mat src, src_roi;
Mat dst, dst_roi;
Mat map1, map1_roi;
Mat map2, map2_roi;
// ocl mat with roi
ocl::oclMat gsrc, gsrc_roi;
ocl::oclMat gdst, gdst_roi;
ocl::oclMat gmap1, gmap1_roi;
ocl::oclMat gmap2, gmap2_roi;
virtual void SetUp()
{
srcType = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1));
map1Type = GET_PARAM(2).first;
map2Type = GET_PARAM(2).second;
borderType = GET_PARAM(3);
useRoi = GET_PARAM(4);
}
void random_roi()
{
val = randomScalar(-MAX_VALUE, MAX_VALUE);
Size srcROISize = randomSize(1, MAX_VALUE);
Size dstROISize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, srcROISize, srcBorder, srcType, 5, 256);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst, dst_roi, dstROISize, dstBorder, srcType, -MAX_VALUE, MAX_VALUE << 1);
Border map1Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(map1, map1_roi, dstROISize, map1Border, map1Type, -MAX_VALUE, MAX_VALUE << 1);
Border map2Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
if (map2Type != noType)
randomSubMat(map2, map2_roi, dstROISize, map2Border, map2Type, -MAX_VALUE, MAX_VALUE << 1);
generateOclMat(gsrc, gsrc_roi, src, srcROISize, srcBorder);
generateOclMat(gdst, gdst_roi, dst, dstROISize, dstBorder);
generateOclMat(gmap1, gmap1_roi, map1, dstROISize, map1Border);
if (noType != map2Type)
generateOclMat(gmap2, gmap2_roi, map2, dstROISize, map2Border);
}
void Near(double threshold = 0.0)
{
Mat whole, roi;
gdst.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
typedef Remap Remap_INTER_NEAREST;
OCL_TEST_P(Remap_INTER_NEAREST, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
remap(src_roi, dst_roi, map1_roi, map2_roi, INTER_NEAREST, borderType, val);
ocl::remap(gsrc_roi, gdst_roi, gmap1_roi, gmap2_roi, INTER_NEAREST, borderType, val);
Near(1.0);
}
}
typedef Remap Remap_INTER_LINEAR;
OCL_TEST_P(Remap_INTER_LINEAR, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::remap(src_roi, dst_roi, map1_roi, map2_roi, INTER_LINEAR, borderType, val);
ocl::remap(gsrc_roi, gdst_roi, gmap1_roi, gmap2_roi, INTER_LINEAR, borderType, val);
Near(2.0);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// resize
PARAM_TEST_CASE(Resize, MatType, double, double, int, bool)
{
int type, interpolation;
double fx, fy;
bool useRoi;
Mat src, dst_whole, src_roi, dst_roi;
ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
virtual void SetUp()
{
type = GET_PARAM(0);
fx = GET_PARAM(1);
fy = GET_PARAM(2);
interpolation = GET_PARAM(3);
useRoi = GET_PARAM(4);
}
void random_roi()
{
Size srcRoiSize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, srcRoiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE);
Size dstRoiSize;
dstRoiSize.width = cvRound(srcRoiSize.width * fx);
dstRoiSize.height = cvRound(srcRoiSize.height * fy);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst_whole, dst_roi, dstRoiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
generateOclMat(gsrc_whole, gsrc_roi, src, srcRoiSize, srcBorder);
generateOclMat(gdst_whole, gdst_roi, dst_whole, dstRoiSize, dstBorder);
}
void Near(double threshold = 0.0)
{
Mat whole, roi;
gdst_whole.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst_whole, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
OCL_TEST_P(Resize, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
resize(src_roi, dst_roi, Size(), fx, fy, interpolation);
ocl::resize(gsrc_roi, gdst_roi, Size(), fx, fy, interpolation);
Near(1.0);
}
}
/////////////////////////////////////////////////////////////////////////////////////
INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpAffine, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values((int)INTER_NEAREST, (int)INTER_LINEAR, (int)INTER_CUBIC),
Bool(),
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpPerspective, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values((int)INTER_NEAREST, (int)INTER_LINEAR, (int)INTER_CUBIC),
Bool(),
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, Remap_INTER_LINEAR, Combine(
testing::Values(CV_8U, CV_16U, CV_16S, CV_32F, CV_64F),
testing::Range(1, 5),
Values(make_pair<MatType, MatType>(CV_32FC1, CV_32FC1),
make_pair<MatType, MatType>(CV_32FC2, noType)),
Values((int)BORDER_CONSTANT),
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, Remap_INTER_NEAREST, Combine(
testing::Values(CV_8U, CV_16U, CV_16S, CV_32F, CV_64F),
testing::Range(1, 5),
Values(make_pair<MatType, MatType>(CV_32FC1, CV_32FC1),
make_pair<MatType, MatType>(CV_32FC2, noType),
make_pair<MatType, MatType>(CV_16SC2, noType)),
Values((int)BORDER_CONSTANT),
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocWarp, Resize, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values(0.5, 1.5, 2.0),
Values(0.5, 1.5, 2.0),
Values((int)INTER_NEAREST, (int)INTER_LINEAR),
Bool()));
#endif // HAVE_OPENCL
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