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Open Source Computer Vision Library
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177 lines
6.9 KiB
177 lines
6.9 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// Intel License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000, Intel Corporation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of Intel Corporation may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "test_precomp.hpp" |
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#ifdef HAVE_CUDA |
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/////////////////////////////////////////////////////////////////// |
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// Gold implementation |
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namespace |
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{ |
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template <typename T, template <typename> class Interpolator> void remapImpl(const cv::Mat& src, const cv::Mat& xmap, const cv::Mat& ymap, cv::Mat& dst, int borderType, cv::Scalar borderVal) |
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{ |
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const int cn = src.channels(); |
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cv::Size dsize = xmap.size(); |
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dst.create(dsize, src.type()); |
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for (int y = 0; y < dsize.height; ++y) |
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{ |
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for (int x = 0; x < dsize.width; ++x) |
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{ |
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for (int c = 0; c < cn; ++c) |
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dst.at<T>(y, x * cn + c) = Interpolator<T>::getValue(src, ymap.at<float>(y, x), xmap.at<float>(y, x), c, borderType, borderVal); |
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} |
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} |
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} |
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void remapGold(const cv::Mat& src, const cv::Mat& xmap, const cv::Mat& ymap, cv::Mat& dst, int interpolation, int borderType, cv::Scalar borderVal) |
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{ |
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typedef void (*func_t)(const cv::Mat& src, const cv::Mat& xmap, const cv::Mat& ymap, cv::Mat& dst, int borderType, cv::Scalar borderVal); |
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static const func_t nearest_funcs[] = |
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{ |
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remapImpl<unsigned char, NearestInterpolator>, |
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remapImpl<signed char, NearestInterpolator>, |
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remapImpl<unsigned short, NearestInterpolator>, |
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remapImpl<short, NearestInterpolator>, |
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remapImpl<int, NearestInterpolator>, |
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remapImpl<float, NearestInterpolator> |
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}; |
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static const func_t linear_funcs[] = |
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{ |
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remapImpl<unsigned char, LinearInterpolator>, |
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remapImpl<signed char, LinearInterpolator>, |
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remapImpl<unsigned short, LinearInterpolator>, |
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remapImpl<short, LinearInterpolator>, |
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remapImpl<int, LinearInterpolator>, |
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remapImpl<float, LinearInterpolator> |
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}; |
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static const func_t cubic_funcs[] = |
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{ |
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remapImpl<unsigned char, CubicInterpolator>, |
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remapImpl<signed char, CubicInterpolator>, |
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remapImpl<unsigned short, CubicInterpolator>, |
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remapImpl<short, CubicInterpolator>, |
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remapImpl<int, CubicInterpolator>, |
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remapImpl<float, CubicInterpolator> |
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}; |
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static const func_t* funcs[] = {nearest_funcs, linear_funcs, cubic_funcs}; |
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funcs[interpolation][src.depth()](src, xmap, ymap, dst, borderType, borderVal); |
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} |
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} |
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/////////////////////////////////////////////////////////////////// |
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// Test |
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PARAM_TEST_CASE(Remap, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation, BorderType, UseRoi) |
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{ |
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cv::gpu::DeviceInfo devInfo; |
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cv::Size size; |
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int type; |
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int interpolation; |
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int borderType; |
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bool useRoi; |
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cv::Mat xmap; |
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cv::Mat ymap; |
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virtual void SetUp() |
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{ |
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devInfo = GET_PARAM(0); |
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size = GET_PARAM(1); |
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type = GET_PARAM(2); |
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interpolation = GET_PARAM(3); |
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borderType = GET_PARAM(4); |
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useRoi = GET_PARAM(5); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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// rotation matrix |
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const double aplha = CV_PI / 4; |
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static double M[2][3] = { {std::cos(aplha), -std::sin(aplha), size.width / 2.0}, |
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{std::sin(aplha), std::cos(aplha), 0.0}}; |
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xmap.create(size, CV_32FC1); |
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ymap.create(size, CV_32FC1); |
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for (int y = 0; y < size.height; ++y) |
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{ |
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for (int x = 0; x < size.width; ++x) |
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{ |
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xmap.at<float>(y, x) = static_cast<float>(M[0][0] * x + M[0][1] * y + M[0][2]); |
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ymap.at<float>(y, x) = static_cast<float>(M[1][0] * x + M[1][1] * y + M[1][2]); |
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} |
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} |
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} |
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}; |
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TEST_P(Remap, Accuracy) |
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{ |
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cv::Mat src = randomMat(size, type); |
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cv::Scalar val = randomScalar(0.0, 255.0); |
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cv::gpu::GpuMat dst = createMat(xmap.size(), type, useRoi); |
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cv::gpu::remap(loadMat(src, useRoi), dst, loadMat(xmap, useRoi), loadMat(ymap, useRoi), interpolation, borderType, val); |
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cv::Mat dst_gold; |
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remapGold(src, xmap, ymap, dst_gold, interpolation, borderType, val); |
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EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-3 : 1.0); |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Remap, testing::Combine( |
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ALL_DEVICES, |
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DIFFERENT_SIZES, |
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), |
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testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)), |
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testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT), BorderType(cv::BORDER_WRAP)), |
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WHOLE_SUBMAT)); |
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#endif // HAVE_CUDA
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