/*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 // Niko Li, newlife20080214@gmail.com // Jia Haipeng, jiahaipeng95@gmail.com // Zero Lin, Zero.Lin@amd.com // Zhang Ying, zhangying913@gmail.com // Yao Wang, bitwangyaoyao@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(FilterTestBase, MatType, cv::Size, // kernel size cv::Size, // dx,dy int // border type, or iteration ) { //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; 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; } void Init(int mat_type) { cv::Size size(MWIDTH, MHEIGHT); mat1 = randomMat(size, mat_type, 5, 16); dst = randomMat(size, mat_type, 5, 16); } void Near(double threshold) { EXPECT_MAT_NEAR(dst, Mat(gdst_whole), threshold); } }; ///////////////////////////////////////////////////////////////////////////////////////////////// // blur struct Blur : FilterTestBase { int type; cv::Size ksize; int bordertype; virtual void SetUp() { type = GET_PARAM(0); ksize = GET_PARAM(1); bordertype = GET_PARAM(3); Init(type); } }; TEST_P(Blur, Mat) { for(int j = 0; j < LOOP_TIMES; j++) { random_roi(); cv::blur(mat1_roi, dst_roi, ksize, Point(-1, -1), bordertype); cv::ocl::blur(gmat1, gdst, ksize, Point(-1, -1), bordertype); Near(1.0); } } ///////////////////////////////////////////////////////////////////////////////////////////////// //Laplacian struct Laplacian : FilterTestBase { int type; cv::Size ksize; virtual void SetUp() { type = GET_PARAM(0); ksize = GET_PARAM(1); Init(type); } }; TEST_P(Laplacian, Accuracy) { for(int j = 0; j < LOOP_TIMES; j++) { random_roi(); cv::Laplacian(mat1_roi, dst_roi, -1, ksize.width, 1); cv::ocl::Laplacian(gmat1, gdst, -1, ksize.width, 1); Near(1e-5); } } ///////////////////////////////////////////////////////////////////////////////////////////////// // erode & dilate struct ErodeDilate : FilterTestBase { int type; int iterations; //erode or dilate kernel cv::Mat kernel; virtual void SetUp() { type = GET_PARAM(0); iterations = GET_PARAM(3); Init(type); // rng.fill(kernel, cv::RNG::UNIFORM, cv::Scalar::all(0), cv::Scalar::all(3)); kernel = randomMat(Size(3, 3), CV_8UC1, 0, 3); } }; TEST_P(ErodeDilate, Mat) { for(int j = 0; j < LOOP_TIMES; j++) { random_roi(); cv::erode(mat1_roi, dst_roi, kernel, Point(-1, -1), iterations); cv::ocl::erode(gmat1, gdst, kernel, Point(-1, -1), iterations); Near(1e-5); } for(int j = 0; j < LOOP_TIMES; j++) { random_roi(); cv::dilate(mat1_roi, dst_roi, kernel, Point(-1, -1), iterations); cv::ocl::dilate(gmat1, gdst, kernel, Point(-1, -1), iterations); Near(1e-5); } } ///////////////////////////////////////////////////////////////////////////////////////////////// // Sobel struct Sobel : FilterTestBase { int type; int dx, dy, ksize, bordertype; virtual void SetUp() { type = GET_PARAM(0); Size s = GET_PARAM(1); ksize = s.width; s = GET_PARAM(2); dx = s.width; dy = s.height; bordertype = GET_PARAM(3); Init(type); } }; TEST_P(Sobel, Mat) { for(int j = 0; j < LOOP_TIMES; j++) { random_roi(); cv::Sobel(mat1_roi, dst_roi, -1, dx, dy, ksize, /*scale*/0.00001,/*delta*/0, bordertype); cv::ocl::Sobel(gmat1, gdst, -1, dx, dy, ksize,/*scale*/0.00001,/*delta*/0, bordertype); Near(1); } } ///////////////////////////////////////////////////////////////////////////////////////////////// // Scharr struct Scharr : FilterTestBase { int type; int dx, dy, bordertype; virtual void SetUp() { type = GET_PARAM(0); Size s = GET_PARAM(2); dx = s.width; dy = s.height; bordertype = GET_PARAM(3); Init(type); } }; TEST_P(Scharr, Mat) { for(int j = 0; j < LOOP_TIMES; j++) { random_roi(); cv::Scharr(mat1_roi, dst_roi, -1, dx, dy, /*scale*/1,/*delta*/0, bordertype); cv::ocl::Scharr(gmat1, gdst, -1, dx, dy,/*scale*/1,/*delta*/0, bordertype); Near(1); } } ///////////////////////////////////////////////////////////////////////////////////////////////// // GaussianBlur struct GaussianBlur : FilterTestBase { int type; cv::Size ksize; int bordertype; double sigma1, sigma2; virtual void SetUp() { type = GET_PARAM(0); ksize = GET_PARAM(1); bordertype = GET_PARAM(3); Init(type); cv::RNG &rng = TS::ptr()->get_rng(); sigma1 = rng.uniform(0.1, 1.0); sigma2 = rng.uniform(0.1, 1.0); } }; TEST_P(GaussianBlur, Mat) { for(int j = 0; j < LOOP_TIMES; j++) { random_roi(); cv::GaussianBlur(mat1_roi, dst_roi, ksize, sigma1, sigma2, bordertype); cv::ocl::GaussianBlur(gmat1, gdst, ksize, sigma1, sigma2, bordertype); Near(1); } } INSTANTIATE_TEST_CASE_P(Filter, Blur, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4), Values(cv::Size(3, 3), cv::Size(5, 5), cv::Size(7, 7)), Values(Size(0, 0)), //not use Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE, (MatType)cv::BORDER_REFLECT, (MatType)cv::BORDER_REFLECT_101))); INSTANTIATE_TEST_CASE_P(Filters, Laplacian, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4), Values(Size(3, 3)), Values(Size(0, 0)), //not use Values(0))); //not use INSTANTIATE_TEST_CASE_P(Filter, ErodeDilate, Combine( Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4), Values(Size(0, 0)), //not use Values(Size(0, 0)), //not use Values(1))); INSTANTIATE_TEST_CASE_P(Filter, Sobel, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4), Values(Size(3, 3), Size(5, 5)), Values(Size(1, 0), Size(1, 1), Size(2, 0), Size(2, 1)), Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE))); INSTANTIATE_TEST_CASE_P(Filter, Scharr, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4), Values(Size(0, 0)), //not use Values(Size(0, 1), Size(1, 0)), Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE))); INSTANTIATE_TEST_CASE_P(Filter, GaussianBlur, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4), Values(Size(3, 3), Size(5, 5)), Values(Size(0, 0)), //not use Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE))); #endif // HAVE_OPENCL