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198 lines
6.9 KiB
198 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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// 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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// SURF |
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#ifdef HAVE_OPENCV_CUDAARITHM |
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namespace |
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{ |
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IMPLEMENT_PARAM_CLASS(SURF_HessianThreshold, double) |
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IMPLEMENT_PARAM_CLASS(SURF_Octaves, int) |
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IMPLEMENT_PARAM_CLASS(SURF_OctaveLayers, int) |
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IMPLEMENT_PARAM_CLASS(SURF_Extended, bool) |
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IMPLEMENT_PARAM_CLASS(SURF_Upright, bool) |
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} |
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PARAM_TEST_CASE(SURF, SURF_HessianThreshold, SURF_Octaves, SURF_OctaveLayers, SURF_Extended, SURF_Upright) |
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{ |
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double hessianThreshold; |
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int nOctaves; |
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int nOctaveLayers; |
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bool extended; |
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bool upright; |
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virtual void SetUp() |
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{ |
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hessianThreshold = GET_PARAM(0); |
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nOctaves = GET_PARAM(1); |
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nOctaveLayers = GET_PARAM(2); |
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extended = GET_PARAM(3); |
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upright = GET_PARAM(4); |
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} |
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}; |
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CUDA_TEST_P(SURF, Detector) |
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{ |
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cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(image.empty()); |
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cv::cuda::SURF_CUDA surf; |
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surf.hessianThreshold = hessianThreshold; |
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surf.nOctaves = nOctaves; |
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surf.nOctaveLayers = nOctaveLayers; |
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surf.extended = extended; |
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surf.upright = upright; |
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surf.keypointsRatio = 0.05f; |
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std::vector<cv::KeyPoint> keypoints; |
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surf(loadMat(image), cv::cuda::GpuMat(), keypoints); |
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cv::SURF surf_gold; |
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surf_gold.hessianThreshold = hessianThreshold; |
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surf_gold.nOctaves = nOctaves; |
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surf_gold.nOctaveLayers = nOctaveLayers; |
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surf_gold.extended = extended; |
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surf_gold.upright = upright; |
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std::vector<cv::KeyPoint> keypoints_gold; |
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surf_gold(image, cv::noArray(), keypoints_gold); |
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ASSERT_EQ(keypoints_gold.size(), keypoints.size()); |
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int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints); |
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double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size(); |
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EXPECT_GT(matchedRatio, 0.95); |
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} |
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CUDA_TEST_P(SURF, Detector_Masked) |
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{ |
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cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(image.empty()); |
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cv::Mat mask(image.size(), CV_8UC1, cv::Scalar::all(1)); |
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mask(cv::Range(0, image.rows / 2), cv::Range(0, image.cols / 2)).setTo(cv::Scalar::all(0)); |
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cv::cuda::SURF_CUDA surf; |
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surf.hessianThreshold = hessianThreshold; |
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surf.nOctaves = nOctaves; |
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surf.nOctaveLayers = nOctaveLayers; |
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surf.extended = extended; |
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surf.upright = upright; |
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surf.keypointsRatio = 0.05f; |
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std::vector<cv::KeyPoint> keypoints; |
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surf(loadMat(image), loadMat(mask), keypoints); |
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cv::SURF surf_gold; |
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surf_gold.hessianThreshold = hessianThreshold; |
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surf_gold.nOctaves = nOctaves; |
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surf_gold.nOctaveLayers = nOctaveLayers; |
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surf_gold.extended = extended; |
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surf_gold.upright = upright; |
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std::vector<cv::KeyPoint> keypoints_gold; |
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surf_gold(image, mask, keypoints_gold); |
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ASSERT_EQ(keypoints_gold.size(), keypoints.size()); |
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int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints); |
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double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size(); |
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EXPECT_GT(matchedRatio, 0.95); |
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} |
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CUDA_TEST_P(SURF, Descriptor) |
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{ |
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cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(image.empty()); |
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cv::cuda::SURF_CUDA surf; |
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surf.hessianThreshold = hessianThreshold; |
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surf.nOctaves = nOctaves; |
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surf.nOctaveLayers = nOctaveLayers; |
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surf.extended = extended; |
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surf.upright = upright; |
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surf.keypointsRatio = 0.05f; |
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cv::SURF surf_gold; |
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surf_gold.hessianThreshold = hessianThreshold; |
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surf_gold.nOctaves = nOctaves; |
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surf_gold.nOctaveLayers = nOctaveLayers; |
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surf_gold.extended = extended; |
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surf_gold.upright = upright; |
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std::vector<cv::KeyPoint> keypoints; |
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surf_gold(image, cv::noArray(), keypoints); |
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cv::cuda::GpuMat descriptors; |
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surf(loadMat(image), cv::cuda::GpuMat(), keypoints, descriptors, true); |
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cv::Mat descriptors_gold; |
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surf_gold(image, cv::noArray(), keypoints, descriptors_gold, true); |
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cv::BFMatcher matcher(surf.defaultNorm()); |
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std::vector<cv::DMatch> matches; |
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matcher.match(descriptors_gold, cv::Mat(descriptors), matches); |
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int matchedCount = getMatchedPointsCount(keypoints, keypoints, matches); |
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double matchedRatio = static_cast<double>(matchedCount) / keypoints.size(); |
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EXPECT_GT(matchedRatio, 0.6); |
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} |
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INSTANTIATE_TEST_CASE_P(CUDA_Features2D, SURF, testing::Combine( |
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testing::Values(SURF_HessianThreshold(100.0), SURF_HessianThreshold(500.0), SURF_HessianThreshold(1000.0)), |
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testing::Values(SURF_Octaves(3), SURF_Octaves(4)), |
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testing::Values(SURF_OctaveLayers(2), SURF_OctaveLayers(3)), |
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testing::Values(SURF_Extended(false), SURF_Extended(true)), |
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testing::Values(SURF_Upright(false), SURF_Upright(true)))); |
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#endif // HAVE_OPENCV_CUDAARITHM |
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#endif // HAVE_CUDA
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