/*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, bool) { int src_depth, dst_depth; int cn, dst_type; bool use_roi; // src mat cv::Mat mat; cv::Mat dst; // set up roi int roicols, roirows; int srcx, srcy; int dstx, 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 gsrc; cv::ocl::oclMat gdst; virtual void SetUp() { src_depth = GET_PARAM(0); dst_depth = GET_PARAM(1); cn = GET_PARAM(2); int src_type = CV_MAKE_TYPE(src_depth, cn); dst_type = CV_MAKE_TYPE(dst_depth, cn); use_roi = GET_PARAM(3); cv::RNG &rng = TS::ptr()->get_rng(); mat = randomMat(rng, randomSize(MIN_VALUE, MAX_VALUE), src_type, 5, 136, false); dst = randomMat(rng, use_roi ? randomSize(MIN_VALUE, MAX_VALUE) : mat.size(), dst_type, 5, 136, false); } void random_roi() { if (use_roi) { // randomize ROI cv::RNG &rng = TS::ptr()->get_rng(); roicols = rng.uniform(1, MIN_VALUE); roirows = rng.uniform(1, MIN_VALUE); 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 = srcy = 0; dstx = dsty = 0; } 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)); gsrc = mat_roi; } }; typedef ConvertToTestBase ConvertTo; TEST_P(ConvertTo, Accuracy) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); mat_roi.convertTo(dst_roi, dst_type); gsrc.convertTo(gdst, dst_type); EXPECT_MAT_NEAR(dst, Mat(gdst_whole), src_depth == CV_64F ? 1.0 : 0.0); EXPECT_MAT_NEAR(dst_roi, Mat(gdst), src_depth == CV_64F ? 1.0 : 0.0); } } ///////////////////////////////////////////copyto///////////////////////////////////////////////////////////// PARAM_TEST_CASE(CopyToTestBase, MatType, int, bool) { bool use_roi; cv::Mat src, mask, dst; // set up roi int roicols,roirows; int srcx, srcy; int dstx, dsty; int maskx,masky; // src mat with roi cv::Mat src_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 gsrc, gdst, gmask; virtual void SetUp() { int type = CV_MAKETYPE(GET_PARAM(0), GET_PARAM(1)); use_roi = GET_PARAM(2); cv::RNG &rng = TS::ptr()->get_rng(); src = randomMat(rng, randomSize(MIN_VALUE, MAX_VALUE), type, 5, 16, false); dst = randomMat(rng, use_roi ? randomSize(MIN_VALUE, MAX_VALUE) : src.size(), type, 5, 16, false); mask = randomMat(rng, use_roi ? randomSize(MIN_VALUE, MAX_VALUE) : src.size(), CV_8UC1, 0, 2, false); cv::threshold(mask, mask, 0.5, 255., CV_8UC1); } void random_roi() { if (use_roi) { // randomize ROI cv::RNG &rng = TS::ptr()->get_rng(); roicols = rng.uniform(1, MIN_VALUE); roirows = rng.uniform(1, MIN_VALUE); srcx = rng.uniform(0, src.cols - roicols); srcy = rng.uniform(0, src.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 = src.cols; roirows = src.rows; srcx = srcy = 0; dstx = dsty = 0; maskx = masky = 0; } src_roi = src(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)); gsrc = src_roi; gmask = mask_roi; } }; typedef CopyToTestBase CopyTo; TEST_P(CopyTo, Without_mask) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); src_roi.copyTo(dst_roi); gsrc.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(); src_roi.copyTo(dst_roi, mask_roi); gsrc.copyTo(gdst, gmask); EXPECT_MAT_NEAR(dst, Mat(gdst_whole), 0.0); } } /////////////////////////////////////////// setTo ///////////////////////////////////////////////////////////// PARAM_TEST_CASE(SetToTestBase, MatType, int, bool) { int depth, channels; bool use_roi; cv::Scalar val; cv::Mat src; cv::Mat mask; // set up roi int roicols, roirows; int srcx, srcy; int maskx, masky; // src mat with roi cv::Mat src_roi; cv::Mat mask_roi; // ocl dst mat for testing cv::ocl::oclMat gsrc_whole; // ocl mat with roi cv::ocl::oclMat gsrc; cv::ocl::oclMat gmask; virtual void SetUp() { depth = GET_PARAM(0); channels = GET_PARAM(1); use_roi = GET_PARAM(2); cv::RNG &rng = TS::ptr()->get_rng(); int type = CV_MAKE_TYPE(depth, channels); src = randomMat(rng, randomSize(MIN_VALUE, MAX_VALUE), type, 5, 16, false); mask = randomMat(rng, use_roi ? randomSize(MIN_VALUE, MAX_VALUE) : src.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() { if (use_roi) { // randomize ROI cv::RNG &rng = TS::ptr()->get_rng(); roicols = rng.uniform(1, MIN_VALUE); roirows = rng.uniform(1, MIN_VALUE); srcx = rng.uniform(0, src.cols - roicols); srcy = rng.uniform(0, src.rows - roirows); maskx = rng.uniform(0, mask.cols - roicols); masky = rng.uniform(0, mask.rows - roirows); } else { roicols = src.cols; roirows = src.rows; srcx = srcy = 0; maskx = masky = 0; } src_roi = src(Rect(srcx, srcy, roicols, roirows)); mask_roi = mask(Rect(maskx, masky, roicols, roirows)); gsrc_whole = src; gsrc = gsrc_whole(Rect(srcx, srcy, roicols, roirows)); gmask = mask_roi; } }; typedef SetToTestBase SetTo; TEST_P(SetTo, Without_mask) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); src_roi.setTo(val); gsrc.setTo(val); EXPECT_MAT_NEAR(src, Mat(gsrc_whole), 1.); } } TEST_P(SetTo, With_mask) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); src_roi.setTo(val, mask_roi); gsrc.setTo(val, gmask); EXPECT_MAT_NEAR(src, Mat(gsrc_whole), 1.); } } // convertC3C4 PARAM_TEST_CASE(convertC3C4, MatType, bool) { int depth; bool use_roi; //src mat cv::Mat src; // set up roi int roicols, roirows; int srcx, srcy; //src mat with roi cv::Mat src_roi; //ocl mat with roi cv::ocl::oclMat gsrc_roi; virtual void SetUp() { depth = GET_PARAM(0); use_roi = GET_PARAM(1); int type = CV_MAKE_TYPE(depth, 3); cv::RNG &rng = TS::ptr()->get_rng(); src = randomMat(rng, randomSize(MIN_VALUE, MAX_VALUE), type, 0, 40, false); } void random_roi() { if (use_roi) { //randomize ROI cv::RNG &rng = TS::ptr()->get_rng(); roicols = rng.uniform(1, src.cols); roirows = rng.uniform(1, src.rows); srcx = rng.uniform(0, src.cols - roicols); srcy = rng.uniform(0, src.rows - roirows); } else { roicols = src.cols; roirows = src.rows; srcx = srcy = 0; } src_roi = src(Rect(srcx, srcy, roicols, roirows)); } }; TEST_P(convertC3C4, Accuracy) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); gsrc_roi = src_roi; EXPECT_MAT_NEAR(src_roi, Mat(gsrc_roi), 0.0); } } INSTANTIATE_TEST_CASE_P(MatrixOperation, ConvertTo, Combine( Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F), Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F), Range(1, 5), Bool())); INSTANTIATE_TEST_CASE_P(MatrixOperation, CopyTo, Combine( Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F), testing::Range(1, 5), Bool())); INSTANTIATE_TEST_CASE_P(MatrixOperation, SetTo, Combine( Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F), testing::Range(1, 5), Bool())); INSTANTIATE_TEST_CASE_P(MatrixOperation, convertC3C4, Combine( Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F), Bool())); #endif