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opencv/modules/ocl/test/test_split_merge.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.
// 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
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//M*/
#include "precomp.hpp"
#ifdef HAVE_OPENCL
using namespace cvtest;
using namespace testing;
using namespace std;
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, 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);
src2x = rng.uniform(0, mat2.cols - roicols);
src2y = rng.uniform(0, mat2.rows - roirows);
src3x = rng.uniform(0, mat3.cols - roicols);
src3y = rng.uniform(0, mat3.cols - roirows);
src4x = rng.uniform(0, mat4.rows - roicols);
src4y = rng.uniform(0, mat4.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;
src2x = 0;
src2y = 0;
src3x = 0;
src3y = 0;
src4x = 0;
src4y = 0;
dstx = 0;
dsty = 0;
#endif
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));
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
gmat1 = mat1_roi;
gmat2 = mat2_roi;
gmat3 = mat3_roi;
gmat4 = mat4_roi;
}
};
struct Merge : MergeTestBase {};
TEST_P(Merge, Accuracy)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
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);
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);
cv::merge(dev_src, dst_roi);
cv::ocl::merge(dev_gsrc, gdst);
cv::Mat cpu_dst;
gdst_whole.download(cpu_dst);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,src1x =%d,src1y=%d,src2x =%d,src2y=%d,src3x =%d,src3y=%d,src4x =%d,src4y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x, src1y, src2x , src2y, src3x , src3y, src4x , src4y, dstx, dsty);
EXPECT_MAT_NEAR(dst, cpu_dst, 0.0, sss);
}
}
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, 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);
dst1x = rng.uniform(0, dst1.cols - roicols);
dst1y = rng.uniform(0, dst1.rows - roirows);
dst2x = rng.uniform(0, dst2.cols - roicols);
dst2y = rng.uniform(0, dst2.rows - roirows);
dst3x = rng.uniform(0, dst3.cols - roicols);
dst3y = rng.uniform(0, dst3.rows - roirows);
dst4x = rng.uniform(0, dst4.cols - roicols);
dst4y = rng.uniform(0, dst4.rows - roirows);
#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;
#endif
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));
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;
}
};
struct Split : SplitTestBase {};
TEST_P(Split, Accuracy)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::Mat dev_dst[4] = {dst1_roi, dst2_roi, dst3_roi, dst4_roi};
cv::ocl::oclMat dev_gdst[4] = {gdst1, gdst2, gdst3, gdst4};
cv::split(mat_roi, dev_dst);
cv::ocl::split(gmat, dev_gdst);
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);
char sss[1024];
sprintf(sss, "roicols=%d,roirows=%d,dst1x =%d,dsty=%d,dst2x =%d,dst2y=%d,dst3x =%d,dst3y=%d,dst4x =%d,dst4y=%d,srcx=%d,srcy=%d", roicols, roirows, dst1x , dst1y, dst2x , dst2y, dst3x , dst3y, dst4x , dst4y, srcx, srcy);
EXPECT_MAT_NEAR(dst1, cpu_dst1, 0.0, sss);
EXPECT_MAT_NEAR(dst2, cpu_dst2, 0.0, sss);
EXPECT_MAT_NEAR(dst3, cpu_dst3, 0.0, sss);
EXPECT_MAT_NEAR(dst4, cpu_dst4, 0.0, sss);
}
}
INSTANTIATE_TEST_CASE_P(SplitMerge, Merge, Combine(
Values(CV_8U, CV_32S, CV_32F), 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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