mirror of
https://github.com/opencv/opencv.git
synced 2024-12-13 16:09:23 +08:00
4a297a2443
- removed tr1 usage (dropped in C++17) - moved includes of vector/map/iostream/limits into ts.hpp - require opencv_test + anonymous namespace (added compile check) - fixed norm() usage (must be from cvtest::norm for checks) and other conflict functions - added missing license headers
134 lines
4.4 KiB
C++
134 lines
4.4 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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namespace opencv_test { namespace {
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//////////////////////////////////////////////////////
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// GoodFeaturesToTrack
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namespace
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{
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IMPLEMENT_PARAM_CLASS(MinDistance, double)
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}
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PARAM_TEST_CASE(GoodFeaturesToTrack, cv::cuda::DeviceInfo, MinDistance)
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{
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cv::cuda::DeviceInfo devInfo;
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double minDistance;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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minDistance = GET_PARAM(1);
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cv::cuda::setDevice(devInfo.deviceID());
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}
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};
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CUDA_TEST_P(GoodFeaturesToTrack, Accuracy)
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{
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cv::Mat image = readImage("opticalflow/frame0.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(image.empty());
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int maxCorners = 1000;
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double qualityLevel = 0.01;
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cv::Ptr<cv::cuda::CornersDetector> detector = cv::cuda::createGoodFeaturesToTrackDetector(image.type(), maxCorners, qualityLevel, minDistance);
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cv::cuda::GpuMat d_pts;
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detector->detect(loadMat(image), d_pts);
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ASSERT_FALSE(d_pts.empty());
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std::vector<cv::Point2f> pts(d_pts.cols);
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cv::Mat pts_mat(1, d_pts.cols, CV_32FC2, (void*) &pts[0]);
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d_pts.download(pts_mat);
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std::vector<cv::Point2f> pts_gold;
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cv::goodFeaturesToTrack(image, pts_gold, maxCorners, qualityLevel, minDistance);
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ASSERT_EQ(pts_gold.size(), pts.size());
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size_t mistmatch = 0;
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for (size_t i = 0; i < pts.size(); ++i)
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{
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cv::Point2i a = pts_gold[i];
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cv::Point2i b = pts[i];
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bool eq = std::abs(a.x - b.x) < 1 && std::abs(a.y - b.y) < 1;
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if (!eq)
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++mistmatch;
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}
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double bad_ratio = static_cast<double>(mistmatch) / pts.size();
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ASSERT_LE(bad_ratio, 0.01);
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}
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CUDA_TEST_P(GoodFeaturesToTrack, EmptyCorners)
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{
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int maxCorners = 1000;
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double qualityLevel = 0.01;
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cv::cuda::GpuMat src(100, 100, CV_8UC1, cv::Scalar::all(0));
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cv::cuda::GpuMat corners(1, maxCorners, CV_32FC2);
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cv::Ptr<cv::cuda::CornersDetector> detector = cv::cuda::createGoodFeaturesToTrackDetector(src.type(), maxCorners, qualityLevel, minDistance);
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detector->detect(src, corners);
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ASSERT_TRUE(corners.empty());
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, GoodFeaturesToTrack, testing::Combine(
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ALL_DEVICES,
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testing::Values(MinDistance(0.0), MinDistance(3.0))));
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}} // namespace
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#endif // HAVE_CUDA
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