/*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. // 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" #ifdef HAVE_CUDA using namespace cvtest; namespace { cv::Mat createTransfomMatrix(cv::Size srcSize, double angle) { cv::Mat M(3, 3, CV_64FC1); M.at(0, 0) = std::cos(angle); M.at(0, 1) = -std::sin(angle); M.at(0, 2) = srcSize.width / 2; M.at(1, 0) = std::sin(angle); M.at(1, 1) = std::cos(angle); M.at(1, 2) = 0.0; M.at(2, 0) = 0.0 ; M.at(2, 1) = 0.0 ; M.at(2, 2) = 1.0; return M; } } /////////////////////////////////////////////////////////////////// // Test buildWarpPerspectiveMaps PARAM_TEST_CASE(BuildWarpPerspectiveMaps, cv::gpu::DeviceInfo, cv::Size, Inverse) { cv::gpu::DeviceInfo devInfo; cv::Size size; bool inverse; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); inverse = GET_PARAM(2); cv::gpu::setDevice(devInfo.deviceID()); } }; GPU_TEST_P(BuildWarpPerspectiveMaps, Accuracy) { cv::Mat M = createTransfomMatrix(size, CV_PI / 4); cv::gpu::GpuMat xmap, ymap; cv::gpu::buildWarpPerspectiveMaps(M, inverse, size, xmap, ymap); cv::Mat src = randomMat(randomSize(200, 400), CV_8UC1); int interpolation = cv::INTER_NEAREST; int borderMode = cv::BORDER_CONSTANT; int flags = interpolation; if (inverse) flags |= cv::WARP_INVERSE_MAP; cv::Mat dst; cv::remap(src, dst, cv::Mat(xmap), cv::Mat(ymap), interpolation, borderMode); cv::Mat dst_gold; cv::warpPerspective(src, dst_gold, M, size, flags, borderMode); EXPECT_MAT_NEAR(dst_gold, dst, 0.0); } INSTANTIATE_TEST_CASE_P(GPU_Warping, BuildWarpPerspectiveMaps, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES, DIRECT_INVERSE)); /////////////////////////////////////////////////////////////////// // Gold implementation namespace { template class Interpolator> void warpPerspectiveImpl(const cv::Mat& src, const cv::Mat& M, cv::Size dsize, cv::Mat& dst, int borderType, cv::Scalar borderVal) { const int cn = src.channels(); dst.create(dsize, src.type()); for (int y = 0; y < dsize.height; ++y) { for (int x = 0; x < dsize.width; ++x) { float coeff = static_cast(M.at(2, 0) * x + M.at(2, 1) * y + M.at(2, 2)); float xcoo = static_cast((M.at(0, 0) * x + M.at(0, 1) * y + M.at(0, 2)) / coeff); float ycoo = static_cast((M.at(1, 0) * x + M.at(1, 1) * y + M.at(1, 2)) / coeff); for (int c = 0; c < cn; ++c) dst.at(y, x * cn + c) = Interpolator::getValue(src, ycoo, xcoo, c, borderType, borderVal); } } } void warpPerspectiveGold(const cv::Mat& src, const cv::Mat& M, bool inverse, cv::Size dsize, cv::Mat& dst, int interpolation, int borderType, cv::Scalar borderVal) { typedef void (*func_t)(const cv::Mat& src, const cv::Mat& M, cv::Size dsize, cv::Mat& dst, int borderType, cv::Scalar borderVal); static const func_t nearest_funcs[] = { warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl }; static const func_t linear_funcs[] = { warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl }; static const func_t cubic_funcs[] = { warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl, warpPerspectiveImpl }; static const func_t* funcs[] = {nearest_funcs, linear_funcs, cubic_funcs}; if (inverse) funcs[interpolation][src.depth()](src, M, dsize, dst, borderType, borderVal); else { cv::Mat iM; cv::invert(M, iM); funcs[interpolation][src.depth()](src, iM, dsize, dst, borderType, borderVal); } } } /////////////////////////////////////////////////////////////////// // Test PARAM_TEST_CASE(WarpPerspective, cv::gpu::DeviceInfo, cv::Size, MatType, Inverse, Interpolation, BorderType, UseRoi) { cv::gpu::DeviceInfo devInfo; cv::Size size; int type; bool inverse; int interpolation; int borderType; bool useRoi; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); type = GET_PARAM(2); inverse = GET_PARAM(3); interpolation = GET_PARAM(4); borderType = GET_PARAM(5); useRoi = GET_PARAM(6); cv::gpu::setDevice(devInfo.deviceID()); } }; GPU_TEST_P(WarpPerspective, Accuracy) { cv::Mat src = randomMat(size, type); cv::Mat M = createTransfomMatrix(size, CV_PI / 3); int flags = interpolation; if (inverse) flags |= cv::WARP_INVERSE_MAP; cv::Scalar val = randomScalar(0.0, 255.0); cv::gpu::GpuMat dst = createMat(size, type, useRoi); cv::gpu::warpPerspective(loadMat(src, useRoi), dst, M, size, flags, borderType, val); cv::Mat dst_gold; warpPerspectiveGold(src, M, inverse, size, dst_gold, interpolation, borderType, val); EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-1 : 1.0); } INSTANTIATE_TEST_CASE_P(GPU_Warping, WarpPerspective, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES, testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), DIRECT_INVERSE, testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)), testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_REFLECT), BorderType(cv::BORDER_WRAP)), WHOLE_SUBMAT)); /////////////////////////////////////////////////////////////////// // Test NPP PARAM_TEST_CASE(WarpPerspectiveNPP, cv::gpu::DeviceInfo, MatType, Inverse, Interpolation) { cv::gpu::DeviceInfo devInfo; int type; bool inverse; int interpolation; virtual void SetUp() { devInfo = GET_PARAM(0); type = GET_PARAM(1); inverse = GET_PARAM(2); interpolation = GET_PARAM(3); cv::gpu::setDevice(devInfo.deviceID()); } }; GPU_TEST_P(WarpPerspectiveNPP, Accuracy) { cv::Mat src = readImageType("stereobp/aloe-L.png", type); ASSERT_FALSE(src.empty()); cv::Mat M = createTransfomMatrix(src.size(), CV_PI / 4); int flags = interpolation; if (inverse) flags |= cv::WARP_INVERSE_MAP; cv::gpu::GpuMat dst; cv::gpu::warpPerspective(loadMat(src), dst, M, src.size(), flags); cv::Mat dst_gold; warpPerspectiveGold(src, M, inverse, src.size(), dst_gold, interpolation, cv::BORDER_CONSTANT, cv::Scalar::all(0)); EXPECT_MAT_SIMILAR(dst_gold, dst, 2e-2); } INSTANTIATE_TEST_CASE_P(GPU_Warping, WarpPerspectiveNPP, testing::Combine( ALL_DEVICES, testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), DIRECT_INVERSE, testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)))); #endif // HAVE_CUDA