/*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; 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 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 dev_src; dev_src.push_back(mat1_roi); if(channels >= 2) dev_src.push_back(mat2_roi); if(channels >= 3) dev_src.push_back(mat3_roi); if(channels >= 4) dev_src.push_back(mat4_roi); std::vector dev_gsrc; dev_gsrc.push_back(gmat1); if(channels >= 2) dev_gsrc.push_back(gmat2); if(channels >= 3) dev_gsrc.push_back(gmat3); if(channels >= 4) 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 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); if(channels >= 1) EXPECT_MAT_NEAR(dst1, cpu_dst1, 0.0, sss); if(channels >= 2) EXPECT_MAT_NEAR(dst2, cpu_dst2, 0.0, sss); if(channels >= 3) EXPECT_MAT_NEAR(dst3, cpu_dst3, 0.0, sss); if(channels >= 4) 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, 3,4))); INSTANTIATE_TEST_CASE_P(SplitMerge, Split , Combine( Values(CV_8U, CV_32S, CV_32F), Values(1, 3,4))); #endif // HAVE_OPENCL