Added fix for removing too similar images into the stitching module
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@ -427,12 +427,6 @@ void BestOf2NearestMatcher::match(const ImageFeatures &features1, const ImageFea
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{
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(*impl_)(features1, features2, matches_info);
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//Mat out;
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//drawMatches(features1.img, features1.keypoints, features2.img, features2.keypoints, matches_info.matches, out);
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//stringstream ss;
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//ss << features1.img_idx << features2.img_idx << ".png";
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//imwrite(ss.str(), out);
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// Check if it makes sense to find homography
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if (matches_info.matches.size() < static_cast<size_t>(num_matches_thresh1_))
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return;
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@ -466,7 +460,13 @@ void BestOf2NearestMatcher::match(const ImageFeatures &features1, const ImageFea
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if (matches_info.inliers_mask[i])
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matches_info.num_inliers++;
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matches_info.confidence = matches_info.num_inliers / (8 + 0.3*matches_info.matches.size());
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// These coeffs are from paper M. Brown and D. Lowe. "Automatic Panoramic Image Stitching
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// using Invariant Features"
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matches_info.confidence = matches_info.num_inliers / (8 + 0.3 * matches_info.matches.size());
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// Set zero confidence to remove matches between too close images, as they don't provide
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// additional information anyway. The threshold was set experimentally.
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matches_info.confidence = matches_info.confidence > 3. ? 0. : matches_info.confidence;
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// Check if we should try to refine motion
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if (matches_info.num_inliers < num_matches_thresh2_)
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@ -748,11 +748,12 @@ vector<int> leaveBiggestComponent(vector<ImageFeatures> &features, vector<Match
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if (static_cast<int>(features_subset.size()) == num_images)
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return indices;
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LOG("Removed some images, because can't match them: (");
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LOG(indices_removed[0]+1);
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LOG("Removed some images, because can't match them or there are too similar images: (");
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LOG(indices_removed[0] + 1);
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for (size_t i = 1; i < indices_removed.size(); ++i)
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LOG(", " << indices_removed[i]+1);
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LOGLN("). Try to decrease --match_conf value.");
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LOGLN(").");
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LOGLN("Try to decrease --match_conf value and/or check if you're stitching duplicates.");
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features = features_subset;
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pairwise_matches = pairwise_matches_subset;
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