191 lines
7.3 KiB
C++
191 lines
7.3 KiB
C++
/*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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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., 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 the copyright holders 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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using namespace cvtest;
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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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GPU_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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#ifdef OPENCV_TINY_GPU_MODULE
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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)),
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testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT)),
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WHOLE_SUBMAT));
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#else
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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
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#endif // HAVE_CUDA
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