From 2b6b6f12e286b563c23d85de2aaa144d114919e5 Mon Sep 17 00:00:00 2001 From: Andrey Kamaev Date: Fri, 29 Jun 2012 08:47:38 +0000 Subject: [PATCH] Debug message is turned off --- modules/stitching/src/matchers.cpp | 36 ++++++++++++++++++------------------ 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/modules/stitching/src/matchers.cpp b/modules/stitching/src/matchers.cpp index f0b5d19..6664db0 100644 --- a/modules/stitching/src/matchers.cpp +++ b/modules/stitching/src/matchers.cpp @@ -273,14 +273,14 @@ namespace cv { namespace detail { void FeaturesFinder::operator ()(const Mat &image, ImageFeatures &features) -{ +{ find(image, features); features.img_size = image.size(); } void FeaturesFinder::operator ()(const Mat &image, ImageFeatures &features, const vector &rois) -{ +{ vector roi_features(rois.size()); size_t total_kps_count = 0; int total_descriptors_height = 0; @@ -294,8 +294,8 @@ void FeaturesFinder::operator ()(const Mat &image, ImageFeatures &features, cons features.img_size = image.size(); features.keypoints.resize(total_kps_count); - features.descriptors.create(total_descriptors_height, - roi_features[0].descriptors.cols, + features.descriptors.create(total_descriptors_height, + roi_features[0].descriptors.cols, roi_features[0].descriptors.type()); int kp_idx = 0; @@ -332,14 +332,14 @@ SurfFeaturesFinder::SurfFeaturesFinder(double hess_thresh, int num_octaves, int { detector_ = Algorithm::create("Feature2D.SURF"); extractor_ = Algorithm::create("Feature2D.SURF"); - + if( detector_.empty() || extractor_.empty() ) CV_Error( CV_StsNotImplemented, "OpenCV was built without SURF support" ); - + detector_->set("hessianThreshold", hess_thresh); detector_->set("nOctaves", num_octaves); detector_->set("nOctaveLayers", num_layers); - + extractor_->set("nOctaves", num_octaves_descr); extractor_->set("nOctaveLayers", num_layers_descr); } @@ -403,17 +403,17 @@ void OrbFeaturesFinder::find(const Mat &image, ImageFeatures &features) int xr = (c+1) * gray_image.cols / grid_size.width; int yr = (r+1) * gray_image.rows / grid_size.height; - LOGLN("OrbFeaturesFinder::find: gray_image.empty=" << (gray_image.empty()?"true":"false") << ", " - << " gray_image.size()=(" << gray_image.size().width << "x" << gray_image.size().height << "), " - << " yl=" << yl << ", yr=" << yr << ", " - << " xl=" << xl << ", xr=" << xr << ", gray_image.data=" << ((size_t)gray_image.data) << ", " - << "gray_image.dims=" << gray_image.dims << "\n"); + // LOGLN("OrbFeaturesFinder::find: gray_image.empty=" << (gray_image.empty()?"true":"false") << ", " + // << " gray_image.size()=(" << gray_image.size().width << "x" << gray_image.size().height << "), " + // << " yl=" << yl << ", yr=" << yr << ", " + // << " xl=" << xl << ", xr=" << xr << ", gray_image.data=" << ((size_t)gray_image.data) << ", " + // << "gray_image.dims=" << gray_image.dims << "\n"); Mat gray_image_part=gray_image(Range(yl, yr), Range(xl, xr)); - LOGLN("OrbFeaturesFinder::find: gray_image_part.empty=" << (gray_image_part.empty()?"true":"false") << ", " - << " gray_image_part.size()=(" << gray_image_part.size().width << "x" << gray_image_part.size().height << "), " - << " gray_image_part.dims=" << gray_image_part.dims << ", " - << " gray_image_part.data=" << ((size_t)gray_image_part.data) << "\n"); + // LOGLN("OrbFeaturesFinder::find: gray_image_part.empty=" << (gray_image_part.empty()?"true":"false") << ", " + // << " gray_image_part.size()=(" << gray_image_part.size().width << "x" << gray_image_part.size().height << "), " + // << " gray_image_part.dims=" << gray_image_part.dims << ", " + // << " gray_image_part.data=" << ((size_t)gray_image_part.data) << "\n"); (*orb)(gray_image_part, Mat(), points, descriptors); @@ -583,11 +583,11 @@ void BestOf2NearestMatcher::match(const ImageFeatures &features1, const ImageFea if (matches_info.inliers_mask[i]) matches_info.num_inliers++; - // These coeffs are from paper M. Brown and D. Lowe. "Automatic Panoramic Image Stitching + // These coeffs are from paper M. Brown and D. Lowe. "Automatic Panoramic Image Stitching // using Invariant Features" matches_info.confidence = matches_info.num_inliers / (8 + 0.3 * matches_info.matches.size()); - // Set zero confidence to remove matches between too close images, as they don't provide + // Set zero confidence to remove matches between too close images, as they don't provide // additional information anyway. The threshold was set experimentally. matches_info.confidence = matches_info.confidence > 3. ? 0. : matches_info.confidence; -- 2.7.4