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Open Source Computer Vision Library
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195 lines
6.9 KiB
195 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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#include <string> |
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using namespace cv; |
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using namespace cv::gpu; |
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using namespace std; |
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const string FEATURES2D_DIR = "features2d"; |
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const string IMAGE_FILENAME = "aloe.png"; |
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class CV_GPU_SURFTest : public cvtest::BaseTest |
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{ |
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public: |
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CV_GPU_SURFTest() |
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{ |
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} |
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protected: |
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bool isSimilarKeypoints(const KeyPoint& p1, const KeyPoint& p2); |
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int getValidCount(const vector<KeyPoint>& keypoints1, const vector<KeyPoint>& keypoints2, const vector<DMatch>& matches); |
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void compareKeypointSets(const vector<KeyPoint>& validKeypoints, const vector<KeyPoint>& calcKeypoints, |
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const Mat& validDescriptors, const Mat& calcDescriptors); |
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void emptyDataTest(); |
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void accuracyTest(); |
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virtual void run(int); |
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}; |
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void CV_GPU_SURFTest::emptyDataTest() |
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{ |
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SURF_GPU fdetector; |
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GpuMat image; |
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vector<KeyPoint> keypoints; |
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vector<float> descriptors; |
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try |
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{ |
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fdetector(image, GpuMat(), keypoints, descriptors); |
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} |
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catch(...) |
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{ |
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ts->printf( cvtest::TS::LOG, "detect() on empty image must not generate exception (1).\n" ); |
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT ); |
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} |
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if( !keypoints.empty() ) |
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{ |
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ts->printf( cvtest::TS::LOG, "detect() on empty image must return empty keypoints vector (1).\n" ); |
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT ); |
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return; |
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} |
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if( !descriptors.empty() ) |
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{ |
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ts->printf( cvtest::TS::LOG, "detect() on empty image must return empty descriptors vector (1).\n" ); |
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT ); |
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return; |
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} |
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} |
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bool CV_GPU_SURFTest::isSimilarKeypoints(const KeyPoint& p1, const KeyPoint& p2) |
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{ |
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const float maxPtDif = 1.f; |
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const float maxSizeDif = 1.f; |
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const float maxAngleDif = 2.f; |
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const float maxResponseDif = 0.1f; |
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float dist = (float)norm( p1.pt - p2.pt ); |
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return (dist < maxPtDif && |
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fabs(p1.size - p2.size) < maxSizeDif && |
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abs(p1.angle - p2.angle) < maxAngleDif && |
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abs(p1.response - p2.response) < maxResponseDif && |
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p1.octave == p2.octave && |
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p1.class_id == p2.class_id ); |
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} |
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int CV_GPU_SURFTest::getValidCount(const vector<KeyPoint>& keypoints1, const vector<KeyPoint>& keypoints2, |
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const vector<DMatch>& matches) |
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{ |
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int count = 0; |
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for (size_t i = 0; i < matches.size(); ++i) |
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{ |
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const DMatch& m = matches[i]; |
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const KeyPoint& kp1 = keypoints1[m.queryIdx]; |
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const KeyPoint& kp2 = keypoints2[m.trainIdx]; |
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if (isSimilarKeypoints(kp1, kp2)) |
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++count; |
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} |
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return count; |
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} |
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void CV_GPU_SURFTest::compareKeypointSets(const vector<KeyPoint>& validKeypoints, const vector<KeyPoint>& calcKeypoints, |
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const Mat& validDescriptors, const Mat& calcDescriptors) |
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{ |
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BruteForceMatcher< L2<float> > matcher; |
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vector<DMatch> matches; |
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matcher.match(validDescriptors, calcDescriptors, matches); |
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int validCount = getValidCount(validKeypoints, calcKeypoints, matches); |
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float validRatio = (float)validCount / matches.size(); |
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if (validRatio < 0.5f) |
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{ |
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ts->printf(cvtest::TS::LOG, "Bad accuracy - %f.\n", validRatio); |
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY ); |
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return; |
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} |
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} |
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void CV_GPU_SURFTest::accuracyTest() |
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{ |
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string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME; |
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// Read the test image. |
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Mat image = imread(imgFilename, 0); |
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if (image.empty()) |
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{ |
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ts->printf( cvtest::TS::LOG, "Image %s can not be read.\n", imgFilename.c_str() ); |
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA ); |
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return; |
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} |
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Mat mask(image.size(), CV_8UC1, Scalar::all(1)); |
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mask(Range(0, image.rows / 2), Range(0, image.cols / 2)).setTo(Scalar::all(0)); |
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// Compute keypoints. |
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vector<KeyPoint> calcKeypoints; |
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GpuMat calcDescriptors; |
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SURF_GPU fdetector; fdetector.extended = false; |
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fdetector(GpuMat(image), GpuMat(mask), calcKeypoints, calcDescriptors); |
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// Calc validation keypoints set. |
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vector<KeyPoint> validKeypoints; |
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vector<float> validDescriptors; |
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SURF fdetector_gold; fdetector_gold.extended = false; |
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fdetector_gold(image, mask, validKeypoints, validDescriptors); |
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compareKeypointSets(validKeypoints, calcKeypoints, |
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Mat(validKeypoints.size(), fdetector_gold.descriptorSize(), CV_32F, &validDescriptors[0]), calcDescriptors); |
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} |
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void CV_GPU_SURFTest::run( int /*start_from*/ ) |
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{ |
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emptyDataTest(); |
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accuracyTest(); |
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} |
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TEST(SURF, empty_data_and_accuracy) { CV_GPU_SURFTest test; test.safe_run(); }
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