Features matcher which finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf.
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#include <opencv2/stitching/detail/matchers.hpp>
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static Ptr< BestOf2NearestMatcher > | create (bool try_use_gpu=false, float match_conf=0.3f, int num_matches_thresh1=6, int num_matches_thresh2=6, double matches_confindece_thresh=3.) |
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void | match (const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info) CV_OVERRIDE |
| This method must implement matching logic in order to make the wrappers detail::FeaturesMatcher::operator()_ work.
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| FeaturesMatcher (bool is_thread_safe=false) |
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virtual void | match (const std::vector< ImageFeatures > &features, std::vector< MatchesInfo > &pairwise_matches, const cv::UMat &mask=cv::UMat()) |
| This method implements logic to match features between arbitrary number of features. By default this checks every pair of inputs in the input, but the behaviour can be changed by subclasses.
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Features matcher which finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf.
- See also
- detail::FeaturesMatcher
◆ BestOf2NearestMatcher()
cv::detail::BestOf2NearestMatcher::BestOf2NearestMatcher |
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bool |
try_use_gpu = false , |
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float |
match_conf = 0.3f , |
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int |
num_matches_thresh1 = 6 , |
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int |
num_matches_thresh2 = 6 , |
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double |
matches_confindece_thresh = 3. |
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Python: |
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| cv.detail.BestOf2NearestMatcher( | [, try_use_gpu[, match_conf[, num_matches_thresh1[, num_matches_thresh2[, matches_confindece_thresh]]]]] | ) -> | <detail_BestOf2NearestMatcher object> |
Constructs a "best of 2 nearest" matcher.
- Parameters
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try_use_gpu | Should try to use GPU or not |
match_conf | Match distances ration threshold |
num_matches_thresh1 | Minimum number of matches required for the 2D projective transform estimation used in the inliers classification step |
num_matches_thresh2 | Minimum number of matches required for the 2D projective transform re-estimation on inliers |
matches_confindece_thresh | Matching confidence threshold to take the match into account. The threshold was determined experimentally and set to 3 by default. |
◆ collectGarbage()
void cv::detail::BestOf2NearestMatcher::collectGarbage |
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virtual |
Python: |
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| cv.detail.BestOf2NearestMatcher.collectGarbage( | | ) -> | None |
◆ create()
static Ptr< BestOf2NearestMatcher > cv::detail::BestOf2NearestMatcher::create |
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bool |
try_use_gpu = false , |
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float |
match_conf = 0.3f , |
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int |
num_matches_thresh1 = 6 , |
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int |
num_matches_thresh2 = 6 , |
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double |
matches_confindece_thresh = 3. |
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) |
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Python: |
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| cv.detail.BestOf2NearestMatcher.create( | [, try_use_gpu[, match_conf[, num_matches_thresh1[, num_matches_thresh2[, matches_confindece_thresh]]]]] | ) -> | retval |
| cv.detail.BestOf2NearestMatcher_create( | [, try_use_gpu[, match_conf[, num_matches_thresh1[, num_matches_thresh2[, matches_confindece_thresh]]]]] | ) -> | retval |
◆ match()
◆ impl_
◆ matches_confindece_thresh_
double cv::detail::BestOf2NearestMatcher::matches_confindece_thresh_ |
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◆ num_matches_thresh1_
int cv::detail::BestOf2NearestMatcher::num_matches_thresh1_ |
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◆ num_matches_thresh2_
int cv::detail::BestOf2NearestMatcher::num_matches_thresh2_ |
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The documentation for this class was generated from the following file: