mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
510 lines
14 KiB
510 lines
14 KiB
/*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; |
|
|
|
////////////////////////////////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); |
|
//std::vector<cv::ocl::Info> oclinfo; |
|
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, mat.cols); |
|
roirows = rng.uniform(1, mat.rows); |
|
srcx = rng.uniform(0, mat.cols - roicols); |
|
srcy = rng.uniform(0, mat.rows - roirows); |
|
dstx = rng.uniform(0, dst.cols - roicols); |
|
dsty = rng.uniform(0, dst.rows - roirows); |
|
#else |
|
roicols = mat.cols; |
|
roirows = mat.rows; |
|
srcx = 0; |
|
srcy = 0; |
|
dstx = 0; |
|
dsty = 0; |
|
#endif |
|
|
|
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) |
|
{ |
|
for(int j = 0; j < LOOP_TIMES; j++) |
|
{ |
|
random_roi(); |
|
|
|
mat_roi.convertTo(dst_roi, dst_type); |
|
gmat.convertTo(gdst, dst_type); |
|
|
|
cv::Mat cpu_dst; |
|
gdst_whole.download(cpu_dst); |
|
char sss[1024]; |
|
sprintf(sss, "roicols=%d,roirows=%d,srcx =%d,srcy=%d,dstx=%d,dsty=%d", roicols, roirows, srcx , srcy, dstx, dsty); |
|
|
|
EXPECT_MAT_NEAR(dst, cpu_dst, 0.0, sss); |
|
} |
|
} |
|
|
|
|
|
|
|
|
|
///////////////////////////////////////////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, 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, mat.cols); |
|
roirows = rng.uniform(1, mat.rows); |
|
srcx = rng.uniform(0, mat.cols - roicols); |
|
srcy = rng.uniform(0, mat.rows - roirows); |
|
dstx = rng.uniform(0, dst.cols - roicols); |
|
dsty = rng.uniform(0, dst.rows - roirows); |
|
maskx = rng.uniform(0, mask.cols - roicols); |
|
masky = rng.uniform(0, mask.rows - roirows); |
|
#else |
|
roicols = mat.cols; |
|
roirows = mat.rows; |
|
srcx = 0; |
|
srcy = 0; |
|
dstx = 0; |
|
dsty = 0; |
|
maskx = 0; |
|
masky = 0; |
|
#endif |
|
|
|
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) |
|
{ |
|
for(int j = 0; j < LOOP_TIMES; j++) |
|
{ |
|
random_roi(); |
|
|
|
mat_roi.copyTo(dst_roi); |
|
gmat.copyTo(gdst); |
|
|
|
cv::Mat cpu_dst; |
|
gdst_whole.download(cpu_dst); |
|
char sss[1024]; |
|
sprintf(sss, "roicols=%d,roirows=%d,srcx =%d,srcy=%d,dstx=%d,dsty=%d,maskx=%d,masky=%d", roicols, roirows, srcx , srcy, dstx, dsty, maskx, masky); |
|
|
|
EXPECT_MAT_NEAR(dst, cpu_dst, 0.0, sss); |
|
} |
|
} |
|
|
|
TEST_P(CopyTo, With_mask) |
|
{ |
|
for(int j = 0; j < LOOP_TIMES; j++) |
|
{ |
|
random_roi(); |
|
|
|
mat_roi.copyTo(dst_roi, mask_roi); |
|
gmat.copyTo(gdst, gmask); |
|
|
|
cv::Mat cpu_dst; |
|
gdst_whole.download(cpu_dst); |
|
char sss[1024]; |
|
sprintf(sss, "roicols=%d,roirows=%d,srcx =%d,srcy=%d,dstx=%d,dsty=%d,maskx=%d,masky=%d", roicols, roirows, srcx , srcy, dstx, dsty, maskx, masky); |
|
|
|
EXPECT_MAT_NEAR(dst, cpu_dst, 0.0, sss); |
|
} |
|
} |
|
|
|
|
|
|
|
|
|
///////////////////////////////////////////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, 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, mat.cols); |
|
roirows = rng.uniform(1, mat.rows); |
|
srcx = rng.uniform(0, mat.cols - roicols); |
|
srcy = rng.uniform(0, mat.rows - roirows); |
|
maskx = rng.uniform(0, mask.cols - roicols); |
|
masky = rng.uniform(0, mask.rows - roirows); |
|
#else |
|
roicols = mat.cols; |
|
roirows = mat.rows; |
|
srcx = 0; |
|
srcy = 0; |
|
maskx = 0; |
|
masky = 0; |
|
#endif |
|
|
|
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) |
|
{ |
|
for(int j = 0; j < LOOP_TIMES; j++) |
|
{ |
|
random_roi(); |
|
|
|
mat_roi.setTo(val); |
|
gmat.setTo(val); |
|
|
|
cv::Mat cpu_dst; |
|
gmat_whole.download(cpu_dst); |
|
char sss[1024]; |
|
sprintf(sss, "roicols=%d,roirows=%d,srcx =%d,srcy=%d,maskx=%d,masky=%d", roicols, roirows, srcx , srcy, maskx, masky); |
|
|
|
EXPECT_MAT_NEAR(mat, cpu_dst, 1., sss); |
|
} |
|
} |
|
|
|
TEST_P(SetTo, With_mask) |
|
{ |
|
for(int j = 0; j < LOOP_TIMES; j++) |
|
{ |
|
random_roi(); |
|
|
|
mat_roi.setTo(val, mask_roi); |
|
gmat.setTo(val, gmask); |
|
|
|
cv::Mat cpu_dst; |
|
gmat_whole.download(cpu_dst); |
|
char sss[1024]; |
|
sprintf(sss, "roicols=%d,roirows=%d,srcx =%d,srcy=%d,maskx=%d,masky=%d", roicols, roirows, srcx , srcy, maskx, masky); |
|
|
|
EXPECT_MAT_NEAR(mat, cpu_dst, 1., sss); |
|
} |
|
} |
|
|
|
//convertC3C4 |
|
PARAM_TEST_CASE(convertC3C4, MatType, cv::Size) |
|
{ |
|
int type; |
|
cv::Size ksize; |
|
|
|
//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); |
|
ksize = GET_PARAM(1); |
|
|
|
|
|
|
|
//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[1]); |
|
} |
|
|
|
void random_roi() |
|
{ |
|
#ifdef RANDOMROI |
|
//randomize ROI |
|
cv::RNG &rng = TS::ptr()->get_rng(); |
|
roicols = rng.uniform(2, mat1.cols); |
|
roirows = rng.uniform(2, 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(convertC3C4, Accuracy) |
|
{ |
|
cv::RNG &rng = TS::ptr()->get_rng(); |
|
for(int j = 0; j < LOOP_TIMES; j++) |
|
{ |
|
//random_roi(); |
|
int width = rng.uniform(2, MWIDTH); |
|
int height = rng.uniform(2, MHEIGHT); |
|
cv::Size size(width, height); |
|
|
|
mat1 = randomMat(rng, size, type, 0, 40, false); |
|
gmat1 = mat1; |
|
cv::Mat cpu_dst; |
|
gmat1.download(cpu_dst); |
|
char sss[1024]; |
|
sprintf(sss, "cols=%d,rows=%d", mat1.cols, mat1.rows); |
|
EXPECT_MAT_NEAR(mat1, cpu_dst, 0.0, sss); |
|
} |
|
|
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(MatrixOperation, ConvertTo, Combine( |
|
Values(CV_8UC1, CV_8UC4, CV_32SC1, CV_32SC4, CV_32FC1, CV_32FC4), |
|
Values(CV_8UC1, CV_8UC4, CV_32SC1, CV_32SC4, CV_32FC1, CV_32FC4))); |
|
|
|
INSTANTIATE_TEST_CASE_P(MatrixOperation, CopyTo, Combine( |
|
Values(CV_8UC1, CV_8UC4, CV_32SC1, CV_32SC4, 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_32SC1, CV_32SC4, CV_32FC1, CV_32FC4), |
|
Values(false))); // Values(false) is the reserved parameter |
|
|
|
INSTANTIATE_TEST_CASE_P(MatrixOperation, convertC3C4, Combine( |
|
Values(CV_8UC3, CV_32SC3, CV_32FC3), |
|
Values(cv::Size()))); |
|
#endif
|
|
|