/*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 // 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 "test_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; //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); } 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); EXPECT_MAT_NEAR(dst, Mat(gdst_whole), 0.0); } } ///////////////////////////////////////////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; //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); } 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); EXPECT_MAT_NEAR(dst, Mat(gdst_whole), 0.0); } } 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); EXPECT_MAT_NEAR(dst, Mat(gdst_whole), 0.0); } } ///////////////////////////////////////////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; //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)); } 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); EXPECT_MAT_NEAR(mat, Mat(gmat_whole), 1.); } } 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); EXPECT_MAT_NEAR(mat, Mat(gmat_whole), 1.); } } //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; //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); } 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; EXPECT_MAT_NEAR(mat1, Mat(gmat1), 0.0); } } INSTANTIATE_TEST_CASE_P(MatrixOperation, ConvertTo, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32SC1, CV_32SC4, CV_32FC1, CV_32FC4), Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32SC1, CV_32SC4, CV_32FC1, CV_32FC4))); INSTANTIATE_TEST_CASE_P(MatrixOperation, CopyTo, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32SC1, CV_32SC3, CV_32SC4, CV_32FC1, CV_32FC3, CV_32FC4), Values(false))); // Values(false) is the reserved parameter INSTANTIATE_TEST_CASE_P(MatrixOperation, SetTo, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32SC1, CV_32SC3, CV_32SC4, CV_32FC1, CV_32FC3, 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