/*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) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Copyright (C) 2013, OpenCV Foundation, all rights reserved. // Third party copyrights are property of their respective owners. // // 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" using namespace cv; using namespace cv::cuda; using namespace cv::cudev; using namespace cvtest; // remap enum { HALF_SIZE=0, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH }; static void generateMap(Mat& mapx, Mat& mapy, int remapMode) { for (int j = 0; j < mapx.rows; ++j) { for (int i = 0; i < mapx.cols; ++i) { switch (remapMode) { case HALF_SIZE: if (i > mapx.cols*0.25 && i < mapx.cols*0.75 && j > mapx.rows*0.25 && j < mapx.rows*0.75) { mapx.at<float>(j,i) = 2.f * (i - mapx.cols * 0.25f) + 0.5f; mapy.at<float>(j,i) = 2.f * (j - mapx.rows * 0.25f) + 0.5f; } else { mapx.at<float>(j,i) = 0.f; mapy.at<float>(j,i) = 0.f; } break; case UPSIDE_DOWN: mapx.at<float>(j,i) = static_cast<float>(i); mapy.at<float>(j,i) = static_cast<float>(mapx.rows - j); break; case REFLECTION_X: mapx.at<float>(j,i) = static_cast<float>(mapx.cols - i); mapy.at<float>(j,i) = static_cast<float>(j); break; case REFLECTION_BOTH: mapx.at<float>(j,i) = static_cast<float>(mapx.cols - i); mapy.at<float>(j,i) = static_cast<float>(mapx.rows - j); break; } // end of switch } } } static void test_remap(int remapMode) { const Size size = randomSize(100, 400); Mat src = randomMat(size, CV_32FC1, 0, 1); Mat mapx(size, CV_32FC1); Mat mapy(size, CV_32FC1); generateMap(mapx, mapy, remapMode); GpuMat_<float> d_src(src); GpuMat_<float> d_mapx(mapx); GpuMat_<float> d_mapy(mapy); GpuMat_<float> dst = remap_(interNearest(brdReplicate(d_src)), d_mapx, d_mapy); Mat dst_gold; cv::remap(src, dst_gold, mapx, mapy, INTER_NEAREST, BORDER_REPLICATE); EXPECT_MAT_NEAR(dst_gold, dst, 0.0); } TEST(Remap, HALF_SIZE) { test_remap(HALF_SIZE); } TEST(Remap, UPSIDE_DOWN) { test_remap(UPSIDE_DOWN); } TEST(Remap, REFLECTION_X) { test_remap(REFLECTION_X); } TEST(Remap, REFLECTION_BOTH) { test_remap(REFLECTION_BOTH); } // resize TEST(Resize, Upscale) { const Size size = randomSize(100, 400); Mat src = randomMat(size, CV_32FC1, 0, 1); GpuMat_<float> d_src(src); Texture<float> tex_src(d_src); GpuMat_<float> dst1 = resize_(interCubic(tex_src), 2, 2); Mat mapx(size.height * 2, size.width * 2, CV_32FC1); Mat mapy(size.height * 2, size.width * 2, CV_32FC1); for (int y = 0; y < mapx.rows; ++y) { for (int x = 0; x < mapx.cols; ++x) { mapx.at<float>(y, x) = static_cast<float>(x / 2); mapy.at<float>(y, x) = static_cast<float>(y / 2); } } GpuMat_<float> d_mapx(mapx); GpuMat_<float> d_mapy(mapy); GpuMat_<float> dst2 = remap_(interCubic(brdReplicate(d_src)), d_mapx, d_mapy); EXPECT_MAT_NEAR(dst1, dst2, 0.0); } TEST(Resize, Downscale) { const Size size = randomSize(100, 400); Mat src = randomMat(size, CV_32FC1, 0, 1); const float fx = 1.0f / 3.0f; const float fy = 1.0f / 3.0f; GpuMat_<float> d_src(src); Texture<float> tex_src(d_src); GpuMat_<float> dst1 = resize_(interArea(tex_src, Size(3, 3)), fx, fy); Mat mapx(cv::saturate_cast<int>(size.height * fy), cv::saturate_cast<int>(size.width * fx), CV_32FC1); Mat mapy(cv::saturate_cast<int>(size.height * fy), cv::saturate_cast<int>(size.width * fx), CV_32FC1); for (int y = 0; y < mapx.rows; ++y) { for (int x = 0; x < mapx.cols; ++x) { mapx.at<float>(y, x) = x / fx; mapy.at<float>(y, x) = y / fy; } } GpuMat_<float> d_mapx(mapx); GpuMat_<float> d_mapy(mapy); GpuMat_<float> dst2 = remap_(interArea(brdReplicate(d_src), Size(3, 3)), d_mapx, d_mapy); EXPECT_MAT_NEAR(dst1, dst2, 0.0); } // warpAffine & warpPerspective Mat createAffineTransfomMatrix(Size srcSize, float angle, bool perspective) { cv::Mat M(perspective ? 3 : 2, 3, CV_32FC1); { M.at<float>(0, 0) = std::cos(angle); M.at<float>(0, 1) = -std::sin(angle); M.at<float>(0, 2) = static_cast<float>(srcSize.width / 2); M.at<float>(1, 0) = std::sin(angle); M.at<float>(1, 1) = std::cos(angle); M.at<float>(1, 2) = 0.0f; } if (perspective) { M.at<float>(2, 0) = 0.0f ; M.at<float>(2, 1) = 0.0f ; M.at<float>(2, 2) = 1.0f; } return M; } TEST(WarpAffine, Rotation) { const Size size = randomSize(100, 400); Mat src = randomMat(size, CV_32FC1, 0, 1); Mat M = createAffineTransfomMatrix(size, static_cast<float>(CV_PI / 4), false); GpuMat_<float> d_src(src); GpuMat_<float> d_M; createContinuous(M.size(), M.type(), d_M); d_M.upload(M); GpuMat_<float> dst = warpAffine_(interNearest(brdConstant(d_src)), size, d_M); Mat dst_gold; cv::warpAffine(src, dst_gold, M, size, INTER_NEAREST | WARP_INVERSE_MAP); EXPECT_MAT_SIMILAR(dst_gold, dst, 1e-3); } TEST(WarpPerspective, Rotation) { const Size size = randomSize(100, 400); Mat src = randomMat(size, CV_32FC1, 0, 1); Mat M = createAffineTransfomMatrix(size, static_cast<float>(CV_PI / 4), true); GpuMat_<float> d_src(src); GpuMat_<float> d_M; createContinuous(M.size(), M.type(), d_M); d_M.upload(M); GpuMat_<float> dst = warpPerspective_(interNearest(brdConstant(d_src)), size, d_M); Mat dst_gold; cv::warpPerspective(src, dst_gold, M, size, INTER_NEAREST | WARP_INVERSE_MAP); EXPECT_MAT_SIMILAR(dst_gold, dst, 1e-3); }