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Added ORB features finder into stitching module
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40ee754e28
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@ -89,6 +89,17 @@ private:
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Ptr<SURF> surf;
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};
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class CV_EXPORTS OrbFeaturesFinder : public FeaturesFinder
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{
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public:
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OrbFeaturesFinder(size_t n_features = 1500, const ORB::CommonParams & detector_params = ORB::CommonParams(1.3, 5));
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private:
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void find(const Mat &image, ImageFeatures &features);
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Ptr<ORB> orb;
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};
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#ifndef ANDROID
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class CV_EXPORTS SurfFeaturesFinderGpu : public FeaturesFinder
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@ -6,11 +6,9 @@ using namespace std;
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using namespace cv;
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using namespace perf;
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typedef TestBaseWithParam<String> stitch;
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/*
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// Stitcher::Status Stitcher::stitch(InputArray imgs, OutputArray pano)
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*/
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PERF_TEST( stitch3, a123 )
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PERF_TEST_P( stitch, a123, testing::Values("surf", "orb"))
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{
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Mat pano;
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@ -20,12 +18,21 @@ PERF_TEST( stitch3, a123 )
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imgs.push_back( imread( getDataPath("stitching/a3.jpg") ) );
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Stitcher::Status status;
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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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declare.time(30 * 20);
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Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
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? new detail::BestOf2NearestMatcher(false, 0.3f)
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: new detail::BestOf2NearestMatcher(false, 0.65f);
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declare.time(30 * 20).iterations(50);
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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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startTimer();
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status = stitcher.stitch(imgs, pano);
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@ -33,7 +40,7 @@ PERF_TEST( stitch3, a123 )
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}
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}
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PERF_TEST( stitch2, b12 )
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PERF_TEST_P( stitch, b12, testing::Values("surf", "orb"))
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{
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Mat pano;
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@ -42,12 +49,21 @@ PERF_TEST( stitch2, b12 )
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imgs.push_back( imread( getDataPath("stitching/b2.jpg") ) );
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Stitcher::Status status;
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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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declare.time(30 * 20);
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Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
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? new detail::BestOf2NearestMatcher(false, 0.3f)
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: new detail::BestOf2NearestMatcher(false, 0.65f);
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declare.time(30 * 20).iterations(50);
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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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startTimer();
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status = stitcher.stitch(imgs, pano);
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@ -148,7 +148,20 @@ private:
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void CpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo& matches_info)
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{
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matches_info.matches.clear();
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FlannBasedMatcher matcher;
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CV_Assert(features1.descriptors.type() == features2.descriptors.type());
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CV_Assert(features2.descriptors.depth() == CV_8U || features2.descriptors.depth() == CV_32F);
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Ptr<flann::IndexParams> indexParams = new flann::KDTreeIndexParams();
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Ptr<flann::SearchParams> searchParams = new flann::SearchParams();
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if (features2.descriptors.depth() == CV_8U)
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{
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indexParams->setAlgorithm(cvflann::FLANN_INDEX_LSH);
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searchParams->setAlgorithm(cvflann::FLANN_INDEX_LSH);
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}
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FlannBasedMatcher matcher(indexParams, searchParams);
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vector< vector<DMatch> > pair_matches;
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MatchesSet matches;
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@ -166,6 +179,7 @@ void CpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &feat
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matches.insert(make_pair(m0.queryIdx, m0.trainIdx));
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}
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}
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LOG("\n1->2 matches: " << matches_info.matches.size() << endl);
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// Find 2->1 matches
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pair_matches.clear();
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@ -180,6 +194,7 @@ void CpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &feat
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if (matches.find(make_pair(m0.trainIdx, m0.queryIdx)) == matches.end())
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matches_info.matches.push_back(DMatch(m0.trainIdx, m0.queryIdx, m0.distance));
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}
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LOG("1->2 & 2->1 matches: " << matches_info.matches.size() << endl);
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}
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#ifndef ANDROID
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@ -304,11 +319,10 @@ SurfFeaturesFinder::SurfFeaturesFinder(double hess_thresh, int num_octaves, int
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}
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}
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void SurfFeaturesFinder::find(const Mat &image, ImageFeatures &features)
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{
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Mat gray_image;
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CV_Assert(image.depth() == CV_8U);
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CV_Assert(image.type() == CV_8UC3);
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cvtColor(image, gray_image, CV_BGR2GRAY);
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if (surf == 0)
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{
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@ -323,6 +337,19 @@ void SurfFeaturesFinder::find(const Mat &image, ImageFeatures &features)
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}
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}
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OrbFeaturesFinder::OrbFeaturesFinder(size_t n_features, const ORB::CommonParams & detector_params)
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{
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orb = new ORB(n_features, detector_params);
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}
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void OrbFeaturesFinder::find(const Mat &image, ImageFeatures &features)
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{
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Mat gray_image;
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CV_Assert(image.type() == CV_8UC3);
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cvtColor(image, gray_image, CV_BGR2GRAY);
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(*orb)(gray_image, Mat(), features.keypoints, features.descriptors);
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}
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#ifndef ANDROID
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SurfFeaturesFinderGpu::SurfFeaturesFinderGpu(double hess_thresh, int num_octaves, int num_layers,
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@ -74,8 +74,10 @@ void printUsage()
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"\nMotion Estimation Flags:\n"
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" --work_megapix <float>\n"
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" Resolution for image registration step. The default is 0.6 Mpx.\n"
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" --features (surf|orb)\n"
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" Type of features used for images matching. The default is surf.\n"
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" --match_conf <float>\n"
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" Confidence for feature matching step. The default is 0.65.\n"
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" Confidence for feature matching step. The default is 0.65 for surf and 0.3 for orb.\n"
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" --conf_thresh <float>\n"
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" Threshold for two images are from the same panorama confidence.\n"
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" The default is 1.0.\n"
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@ -123,6 +125,7 @@ double work_megapix = 0.6;
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double seam_megapix = 0.1;
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double compose_megapix = -1;
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float conf_thresh = 1.f;
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string features = "surf";
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string ba_cost_func = "ray";
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string ba_refine_mask = "xxxxx";
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bool do_wave_correct = true;
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@ -188,6 +191,13 @@ int parseCmdArgs(int argc, char** argv)
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result_name = argv[i + 1];
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i++;
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}
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else if (string(argv[i]) == "--features")
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{
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features = argv[i + 1];
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if (features == "orb")
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match_conf = 0.3f;
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i++;
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}
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else if (string(argv[i]) == "--match_conf")
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{
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match_conf = static_cast<float>(atof(argv[i + 1]));
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@ -334,12 +344,24 @@ int main(int argc, char* argv[])
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int64 t = getTickCount();
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Ptr<FeaturesFinder> finder;
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if (features == "surf")
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{
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#ifndef ANDROID
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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finder = new SurfFeaturesFinderGpu();
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else
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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finder = new SurfFeaturesFinderGpu();
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else
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#endif
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finder = new SurfFeaturesFinder();
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finder = new SurfFeaturesFinder();
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}
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else if (features == "orb")
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{
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finder = new OrbFeaturesFinder();
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}
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else
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{
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cout << "Unknown 2D features type: '" << features << "'.\n";
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return -1;
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}
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Mat full_img, img;
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vector<ImageFeatures> features(num_images);
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@ -548,27 +570,27 @@ int main(int argc, char* argv[])
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compensator->feed(corners, images_warped, masks_warped);
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Ptr<SeamFinder> seam_finder;
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if (seam_find_type == "no")
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seam_finder = new detail::NoSeamFinder();
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else if (seam_find_type == "voronoi")
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seam_finder = new detail::VoronoiSeamFinder();
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else if (seam_find_type == "gc_color")
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{
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#ifndef ANDROID
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR);
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else
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#endif
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seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR);
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}
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else if (seam_find_type == "gc_colorgrad")
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{
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#ifndef ANDROID
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR_GRAD);
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else
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#endif
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seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR_GRAD);
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if (seam_find_type == "no")
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seam_finder = new detail::NoSeamFinder();
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else if (seam_find_type == "voronoi")
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seam_finder = new detail::VoronoiSeamFinder();
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else if (seam_find_type == "gc_color")
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{
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#ifndef ANDROID
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR);
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else
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#endif
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seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR);
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}
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else if (seam_find_type == "gc_colorgrad")
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{
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#ifndef ANDROID
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR_GRAD);
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else
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#endif
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seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR_GRAD);
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}
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if (seam_finder.empty())
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{
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