213 lines
6.9 KiB
C++
213 lines
6.9 KiB
C++
#include "perf_precomp.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include "opencv2/core/internal.hpp"
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#include "opencv2/flann/flann.hpp"
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#include "opencv2/opencv_modules.hpp"
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using namespace std;
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using namespace cv;
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using namespace perf;
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using std::tr1::make_tuple;
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using std::tr1::get;
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#define SURF_MATCH_CONFIDENCE 0.65f
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#define ORB_MATCH_CONFIDENCE 0.3f
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#define WORK_MEGAPIX 0.6
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typedef TestBaseWithParam<String> stitch;
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typedef TestBaseWithParam<String> match;
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typedef std::tr1::tuple<String, int> matchVector_t;
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typedef TestBaseWithParam<matchVector_t> matchVector;
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#ifdef HAVE_OPENCV_NONFREE_TODO_FIND_WHY_SURF_IS_NOT_ABLE_TO_STITCH_PANOS
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#define TEST_DETECTORS testing::Values("surf", "orb")
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#else
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#define TEST_DETECTORS testing::Values<String>("orb")
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#endif
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PERF_TEST_P(stitch, a123, TEST_DETECTORS)
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{
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Mat pano;
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vector<Mat> imgs;
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imgs.push_back( imread( getDataPath("stitching/a1.png") ) );
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imgs.push_back( imread( getDataPath("stitching/a2.png") ) );
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imgs.push_back( imread( getDataPath("stitching/a3.png") ) );
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Ptr<detail::FeaturesFinder> featuresFinder = GetParam() == "orb"
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? (detail::FeaturesFinder*)new detail::OrbFeaturesFinder()
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: (detail::FeaturesFinder*)new detail::SurfFeaturesFinder();
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Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
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? new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE)
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: new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
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declare.time(30 * 20).iterations(20);
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while(next())
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{
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Stitcher stitcher = Stitcher::createDefault();
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stitcher.setFeaturesFinder(featuresFinder);
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stitcher.setFeaturesMatcher(featuresMatcher);
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stitcher.setWarper(new SphericalWarper());
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stitcher.setRegistrationResol(WORK_MEGAPIX);
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startTimer();
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stitcher.stitch(imgs, pano);
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stopTimer();
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}
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Mat pano_small;
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if (!pano.empty())
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resize(pano, pano_small, Size(320, 240), 0, 0, INTER_AREA);
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SANITY_CHECK(pano_small, 5);
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}
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PERF_TEST_P(stitch, b12, TEST_DETECTORS)
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{
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Mat pano;
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vector<Mat> imgs;
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imgs.push_back( imread( getDataPath("stitching/b1.png") ) );
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imgs.push_back( imread( getDataPath("stitching/b2.png") ) );
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Ptr<detail::FeaturesFinder> featuresFinder = GetParam() == "orb"
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? (detail::FeaturesFinder*)new detail::OrbFeaturesFinder()
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: (detail::FeaturesFinder*)new detail::SurfFeaturesFinder();
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Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
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? new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE)
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: new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
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declare.time(30 * 20).iterations(20);
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while(next())
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{
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Stitcher stitcher = Stitcher::createDefault();
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stitcher.setFeaturesFinder(featuresFinder);
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stitcher.setFeaturesMatcher(featuresMatcher);
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stitcher.setWarper(new SphericalWarper());
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stitcher.setRegistrationResol(WORK_MEGAPIX);
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startTimer();
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stitcher.stitch(imgs, pano);
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stopTimer();
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}
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Mat pano_small;
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if (!pano.empty())
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resize(pano, pano_small, Size(320, 240), 0, 0, INTER_AREA);
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SANITY_CHECK(pano_small, 5);
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}
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PERF_TEST_P( match, bestOf2Nearest, TEST_DETECTORS)
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{
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Mat img1, img1_full = imread( getDataPath("stitching/b1.png") );
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Mat img2, img2_full = imread( getDataPath("stitching/b2.png") );
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float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
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float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
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resize(img1_full, img1, Size(), scale1, scale1);
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resize(img2_full, img2, Size(), scale2, scale2);
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Ptr<detail::FeaturesFinder> finder;
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Ptr<detail::FeaturesMatcher> matcher;
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if (GetParam() == "surf")
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{
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finder = new detail::SurfFeaturesFinder();
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matcher = new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
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}
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else if (GetParam() == "orb")
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{
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finder = new detail::OrbFeaturesFinder();
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matcher = new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE);
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}
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else
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{
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FAIL() << "Unknown 2D features type: " << GetParam();
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}
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detail::ImageFeatures features1, features2;
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(*finder)(img1, features1);
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(*finder)(img2, features2);
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detail::MatchesInfo pairwise_matches;
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declare.in(features1.descriptors, features2.descriptors);
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while(next())
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{
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cvflann::seed_random(42);//for predictive FlannBasedMatcher
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startTimer();
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(*matcher)(features1, features2, pairwise_matches);
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stopTimer();
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matcher->collectGarbage();
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}
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std::vector<DMatch>& matches = pairwise_matches.matches;
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if (GetParam() == "orb") matches.resize(0);
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for(size_t q = 0; q < matches.size(); ++q)
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if (matches[q].imgIdx < 0) { matches.resize(q); break;}
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SANITY_CHECK_MATCHES(matches);
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}
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PERF_TEST_P( matchVector, bestOf2NearestVectorFeatures, testing::Combine(
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TEST_DETECTORS,
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testing::Values(2, 4, 8))
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)
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{
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Mat img1, img1_full = imread( getDataPath("stitching/b1.png") );
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Mat img2, img2_full = imread( getDataPath("stitching/b2.png") );
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float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
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float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
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resize(img1_full, img1, Size(), scale1, scale1);
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resize(img2_full, img2, Size(), scale2, scale2);
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Ptr<detail::FeaturesFinder> finder;
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Ptr<detail::FeaturesMatcher> matcher;
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String detectorName = get<0>(GetParam());
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int featuresVectorSize = get<1>(GetParam());
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if (detectorName == "surf")
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{
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finder = new detail::SurfFeaturesFinder();
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matcher = new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
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}
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else if (detectorName == "orb")
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{
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finder = new detail::OrbFeaturesFinder();
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matcher = new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE);
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}
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else
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{
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FAIL() << "Unknown 2D features type: " << get<0>(GetParam());
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}
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detail::ImageFeatures features1, features2;
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(*finder)(img1, features1);
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(*finder)(img2, features2);
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vector<detail::ImageFeatures> features;
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vector<detail::MatchesInfo> pairwise_matches;
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for(int i = 0; i < featuresVectorSize/2; i++)
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{
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features.push_back(features1);
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features.push_back(features2);
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}
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declare.time(200);
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while(next())
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{
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cvflann::seed_random(42);//for predictive FlannBasedMatcher
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startTimer();
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(*matcher)(features, pairwise_matches);
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stopTimer();
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matcher->collectGarbage();
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}
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std::vector<DMatch>& matches = pairwise_matches[detectorName == "surf" ? 1 : 0].matches;
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for(size_t q = 0; q < matches.size(); ++q)
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if (matches[q].imgIdx < 0) { matches.resize(q); break;}
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SANITY_CHECK_MATCHES(matches);
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}
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