/*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 // Shengen Yan, yanshengen@gmail.com // Jiang Liyuan, lyuan001.good@163.com // Rock Li, Rock.Li@amd.com // Wu Zailong, bullet@yeah.net // Xu Pang, pangxu010@163.com // Sen Liu, swjtuls1987@126.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 materials 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" #include "opencv2/ts/ocl_test.hpp" #ifdef HAVE_OPENCL namespace cvtest { namespace ocl { enum { noType = -1 }; ///////////////////////////////////////////////////////////////////////////////////////////////// // warpAffine & warpPerspective PARAM_TEST_CASE(WarpTestBase, MatType, Interpolation, bool, bool) { int type, interpolation; Size dsize; bool useRoi, mapInverse; int depth; TEST_DECLARE_INPUT_PARAMETER(src); TEST_DECLARE_OUTPUT_PARAMETER(dst); virtual void SetUp() { type = GET_PARAM(0); interpolation = GET_PARAM(1); mapInverse = GET_PARAM(2); useRoi = GET_PARAM(3); depth = CV_MAT_DEPTH(type); if (mapInverse) interpolation |= WARP_INVERSE_MAP; } void random_roi() { dsize = randomSize(1, MAX_VALUE); Size roiSize = randomSize(1, MAX_VALUE); Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(src, src_roi, roiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(dst, dst_roi, dsize, dstBorder, type, -MAX_VALUE, MAX_VALUE); UMAT_UPLOAD_INPUT_PARAMETER(src); UMAT_UPLOAD_OUTPUT_PARAMETER(dst); } void Near(double threshold = 0.0) { if (depth < CV_32F) EXPECT_MAT_N_DIFF(dst_roi, udst_roi, cvRound(dst_roi.total()*threshold)); else OCL_EXPECT_MATS_NEAR_RELATIVE(dst, threshold); } }; PARAM_TEST_CASE(WarpTest_cols4_Base, MatType, Interpolation, bool, bool) { int type, interpolation; Size dsize; bool useRoi, mapInverse; int depth; TEST_DECLARE_INPUT_PARAMETER(src); TEST_DECLARE_OUTPUT_PARAMETER(dst); virtual void SetUp() { type = GET_PARAM(0); interpolation = GET_PARAM(1); mapInverse = GET_PARAM(2); useRoi = GET_PARAM(3); depth = CV_MAT_DEPTH(type); if (mapInverse) interpolation |= WARP_INVERSE_MAP; } void random_roi() { dsize = randomSize(1, MAX_VALUE); dsize.width = ((dsize.width >> 2) + 1) * 4; Size roiSize = randomSize(1, MAX_VALUE); Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(src, src_roi, roiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(dst, dst_roi, dsize, dstBorder, type, -MAX_VALUE, MAX_VALUE); UMAT_UPLOAD_INPUT_PARAMETER(src); UMAT_UPLOAD_OUTPUT_PARAMETER(dst); } void Near(double threshold = 0.0) { if (depth < CV_32F) EXPECT_MAT_N_DIFF(dst_roi, udst_roi, cvRound(dst_roi.total()*threshold)); else OCL_EXPECT_MATS_NEAR_RELATIVE(dst, threshold); } }; /////warpAffine typedef WarpTestBase WarpAffine; /////warpAffine typedef WarpTestBase WarpAffine; OCL_TEST_P(WarpAffine, Mat) { for (int j = 0; j < test_loop_times; j++) { double eps = depth < CV_32F ? 0.04 : 0.06; random_roi(); Mat M = getRotationMatrix2D(Point2f(src_roi.cols / 2.0f, src_roi.rows / 2.0f), rng.uniform(-180.f, 180.f), rng.uniform(0.4f, 2.0f)); OCL_OFF(cv::warpAffine(src_roi, dst_roi, M, dsize, interpolation)); OCL_ON(cv::warpAffine(usrc_roi, udst_roi, M, dsize, interpolation)); Near(eps); } } typedef WarpTest_cols4_Base WarpAffine_cols4; OCL_TEST_P(WarpAffine_cols4, Mat) { for (int j = 0; j < test_loop_times; j++) { double eps = depth < CV_32F ? 0.04 : 0.06; random_roi(); Mat M = getRotationMatrix2D(Point2f(src_roi.cols / 2.0f, src_roi.rows / 2.0f), rng.uniform(-180.f, 180.f), rng.uniform(0.4f, 2.0f)); OCL_OFF(cv::warpAffine(src_roi, dst_roi, M, dsize, interpolation)); OCL_ON(cv::warpAffine(usrc_roi, udst_roi, M, dsize, interpolation)); Near(eps); } } //// warpPerspective typedef WarpTestBase WarpPerspective; OCL_TEST_P(WarpPerspective, Mat) { for (int j = 0; j < test_loop_times; j++) { double eps = depth < CV_32F ? 0.03 : 0.06; random_roi(); float cols = static_cast(src_roi.cols), rows = static_cast(src_roi.rows); float cols2 = cols / 2.0f, rows2 = rows / 2.0f; Point2f sp[] = { Point2f(0.0f, 0.0f), Point2f(cols, 0.0f), Point2f(0.0f, rows), Point2f(cols, rows) }; Point2f dp[] = { Point2f(rng.uniform(0.0f, cols2), rng.uniform(0.0f, rows2)), Point2f(rng.uniform(cols2, cols), rng.uniform(0.0f, rows2)), Point2f(rng.uniform(0.0f, cols2), rng.uniform(rows2, rows)), Point2f(rng.uniform(cols2, cols), rng.uniform(rows2, rows)) }; Mat M = getPerspectiveTransform(sp, dp); OCL_OFF(cv::warpPerspective(src_roi, dst_roi, M, dsize, interpolation)); OCL_ON(cv::warpPerspective(usrc_roi, udst_roi, M, dsize, interpolation)); Near(eps); } } typedef WarpTest_cols4_Base WarpPerspective_cols4; OCL_TEST_P(WarpPerspective_cols4, Mat) { for (int j = 0; j < test_loop_times; j++) { double eps = depth < CV_32F ? 0.03 : 0.06; random_roi(); float cols = static_cast(src_roi.cols), rows = static_cast(src_roi.rows); float cols2 = cols / 2.0f, rows2 = rows / 2.0f; Point2f sp[] = { Point2f(0.0f, 0.0f), Point2f(cols, 0.0f), Point2f(0.0f, rows), Point2f(cols, rows) }; Point2f dp[] = { Point2f(rng.uniform(0.0f, cols2), rng.uniform(0.0f, rows2)), Point2f(rng.uniform(cols2, cols), rng.uniform(0.0f, rows2)), Point2f(rng.uniform(0.0f, cols2), rng.uniform(rows2, rows)), Point2f(rng.uniform(cols2, cols), rng.uniform(rows2, rows)) }; Mat M = getPerspectiveTransform(sp, dp); OCL_OFF(cv::warpPerspective(src_roi, dst_roi, M, dsize, interpolation)); OCL_ON(cv::warpPerspective(usrc_roi, udst_roi, M, dsize, interpolation)); Near(eps); } } ///////////////////////////////////////////////////////////////////////////////////////////////// //// resize PARAM_TEST_CASE(Resize, MatType, double, double, Interpolation, bool, int) { int type, interpolation; int widthMultiple; double fx, fy; bool useRoi; TEST_DECLARE_INPUT_PARAMETER(src); TEST_DECLARE_OUTPUT_PARAMETER(dst); virtual void SetUp() { type = GET_PARAM(0); fx = GET_PARAM(1); fy = GET_PARAM(2); interpolation = GET_PARAM(3); useRoi = GET_PARAM(4); widthMultiple = GET_PARAM(5); } void random_roi() { CV_Assert(fx > 0 && fy > 0); Size srcRoiSize = randomSize(10, MAX_VALUE), dstRoiSize; // Make sure the width is a multiple of the requested value, and no more srcRoiSize.width += widthMultiple - 1 - (srcRoiSize.width - 1) % widthMultiple; dstRoiSize.width = cvRound(srcRoiSize.width * fx); dstRoiSize.height = cvRound(srcRoiSize.height * fy); if (dstRoiSize.area() == 0) { random_roi(); return; } Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(src, src_roi, srcRoiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(dst, dst_roi, dstRoiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE); UMAT_UPLOAD_INPUT_PARAMETER(src); UMAT_UPLOAD_OUTPUT_PARAMETER(dst); } void Near(double threshold = 0.0) { OCL_EXPECT_MATS_NEAR(dst, threshold); } }; OCL_TEST_P(Resize, Mat) { for (int j = 0; j < test_loop_times; j++) { int depth = CV_MAT_DEPTH(type); double eps = depth <= CV_32S ? 1 : 5e-2; random_roi(); OCL_OFF(cv::resize(src_roi, dst_roi, Size(), fx, fy, interpolation)); OCL_ON(cv::resize(usrc_roi, udst_roi, Size(), fx, fy, interpolation)); Near(eps); } } ///////////////////////////////////////////////////////////////////////////////////////////////// // remap PARAM_TEST_CASE(Remap, MatDepth, Channels, std::pair, BorderType, bool) { int srcType, map1Type, map2Type; int borderType; bool useRoi; Scalar val; TEST_DECLARE_INPUT_PARAMETER(src); TEST_DECLARE_INPUT_PARAMETER(map1); TEST_DECLARE_INPUT_PARAMETER(map2); TEST_DECLARE_OUTPUT_PARAMETER(dst); virtual void SetUp() { srcType = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1)); map1Type = GET_PARAM(2).first; map2Type = GET_PARAM(2).second; borderType = GET_PARAM(3); useRoi = GET_PARAM(4); } void random_roi() { val = randomScalar(-MAX_VALUE, MAX_VALUE); Size srcROISize = randomSize(1, MAX_VALUE); Size dstROISize = randomSize(1, MAX_VALUE); Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(src, src_roi, srcROISize, srcBorder, srcType, 5, 256); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(dst, dst_roi, dstROISize, dstBorder, srcType, -MAX_VALUE, MAX_VALUE); int mapMaxValue = MAX_VALUE << 2; Border map1Border = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(map1, map1_roi, dstROISize, map1Border, map1Type, -mapMaxValue, mapMaxValue); Border map2Border = randomBorder(0, useRoi ? MAX_VALUE + 1 : 0); if (map2Type != noType) { int mapMinValue = -mapMaxValue; if (map2Type == CV_16UC1 || map2Type == CV_16SC1) mapMinValue = 0, mapMaxValue = INTER_TAB_SIZE2; randomSubMat(map2, map2_roi, dstROISize, map2Border, map2Type, mapMinValue, mapMaxValue); } UMAT_UPLOAD_INPUT_PARAMETER(src); UMAT_UPLOAD_INPUT_PARAMETER(map1); UMAT_UPLOAD_OUTPUT_PARAMETER(dst); if (noType != map2Type) UMAT_UPLOAD_INPUT_PARAMETER(map2); } void Near(double threshold = 0.0) { OCL_EXPECT_MATS_NEAR(dst, threshold); } }; typedef Remap Remap_INTER_NEAREST; OCL_TEST_P(Remap_INTER_NEAREST, Mat) { for (int j = 0; j < test_loop_times; j++) { random_roi(); OCL_OFF(cv::remap(src_roi, dst_roi, map1_roi, map2_roi, INTER_NEAREST, borderType, val)); OCL_ON(cv::remap(usrc_roi, udst_roi, umap1_roi, umap2_roi, INTER_NEAREST, borderType, val)); Near(1.0); } } typedef Remap Remap_INTER_LINEAR; OCL_TEST_P(Remap_INTER_LINEAR, Mat) { for (int j = 0; j < test_loop_times; j++) { random_roi(); double eps = 2.0; #ifdef ANDROID // TODO investigate accuracy if (cv::ocl::Device::getDefault().isNVidia()) eps = 8.0; #endif OCL_OFF(cv::remap(src_roi, dst_roi, map1_roi, map2_roi, INTER_LINEAR, borderType, val)); OCL_ON(cv::remap(usrc_roi, udst_roi, umap1_roi, umap2_roi, INTER_LINEAR, borderType, val)); Near(eps); } } ///////////////////////////////////////////////////////////////////////////////////// OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpAffine, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4), Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR, (Interpolation)INTER_CUBIC), Bool(), Bool())); OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpAffine_cols4, Combine( Values((MatType)CV_8UC1), Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR), Bool(), Bool())); OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpPerspective, Combine( Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4), Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR, (Interpolation)INTER_CUBIC), Bool(), Bool())); OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpPerspective_cols4, Combine( Values((MatType)CV_8UC1), Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR), Bool(), Bool())); OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, Resize, Combine( Values(CV_8UC1, CV_8UC4, CV_16UC2, CV_32FC1, CV_32FC4), Values(0.5, 1.5, 2.0, 0.2), Values(0.5, 1.5, 2.0, 0.2), Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR), Bool(), Values(1, 16))); OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarpResizeArea, Resize, Combine( Values((MatType)CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4), Values(0.7, 0.4, 0.5), Values(0.3, 0.6, 0.5), Values((Interpolation)INTER_AREA), Bool(), Values(1, 16))); OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, Remap_INTER_LINEAR, Combine( Values(CV_8U, CV_16U, CV_32F), Values(1, 3, 4), Values(std::pair((MatType)CV_32FC1, (MatType)CV_32FC1), std::pair((MatType)CV_16SC2, (MatType)CV_16UC1), std::pair((MatType)CV_32FC2, noType)), Values((BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE, (BorderType)BORDER_WRAP, (BorderType)BORDER_REFLECT, (BorderType)BORDER_REFLECT_101), Bool())); OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, Remap_INTER_NEAREST, Combine( Values(CV_8U, CV_16U, CV_32F), Values(1, 3, 4), Values(std::pair((MatType)CV_32FC1, (MatType)CV_32FC1), std::pair((MatType)CV_32FC2, noType), std::pair((MatType)CV_16SC2, (MatType)CV_16UC1), std::pair((MatType)CV_16SC2, noType)), Values((BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE, (BorderType)BORDER_WRAP, (BorderType)BORDER_REFLECT, (BorderType)BORDER_REFLECT_101), Bool())); } } // namespace cvtest::ocl #endif // HAVE_OPENCL