#include <opencv2/stitching/detail/matchers.hpp>
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| | BestOf2NearestRangeMatcher (int range_width=5, bool try_use_gpu=false, float match_conf=0.3f, int num_matches_thresh1=6, int num_matches_thresh2=6) |
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| | BestOf2NearestMatcher (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.) |
| | 構造一個“best of 2 nearest”匹配器。
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| void | collectGarbage () CV_OVERRIDE |
| | 釋放之前分配的任何未使用的記憶體。
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| virtual | ~FeaturesMatcher () |
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| bool | isThreadSafe () const |
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| void | operator() (const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info) |
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| void | operator() (const std::vector< ImageFeatures > &features, std::vector< MatchesInfo > &pairwise_matches, const cv::UMat &mask=cv::UMat()) |
| | 執行影像匹配。
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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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◆ BestOf2NearestRangeMatcher()
| cv::detail::BestOf2NearestRangeMatcher::BestOf2NearestRangeMatcher |
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int | range_width = 5, |
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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 ) |
| Python |
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| cv.detail.BestOf2NearestRangeMatcher( | [, range_width[, try_use_gpu[, match_conf[, num_matches_thresh1[, num_matches_thresh2]]]]] | ) -> | <detail_BestOf2NearestRangeMatcher object> |
◆ match() [1/2]
◆ match() [2/2]
此方法實現邏輯以匹配任意數量特徵之間的特徵。 預設情況下,這會檢查輸入中的每對輸入,但行為可以透過子類更改。
- 引數
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| features | 影像特徵向量 |
| pairwise_matches | 找到的匹配 |
| mask | (可選)指示哪些影像對應匹配的掩碼 |
從 cv::detail::FeaturesMatcher 重新實現。
◆ range_width_
| int cv::detail::BestOf2NearestRangeMatcher::range_width_ |
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保護 |
此類的文件是從以下檔案生成的