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