#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.) |
| 构造一个“最佳 2 个最近邻”匹配器。
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void | collectGarbage () CV_OVERRIDE |
| 释放之前分配的任何未使用的内存。
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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()) |
| 执行图像匹配。
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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 |
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) |
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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]
此方法实现逻辑以匹配任意数量的特征之间的特征。默认情况下,这检查输入中的每对输入,但行为可以通过子类更改。
- 参数
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features | 图像特征向量 |
pairwise_matches | 找到的匹配项 |
mask | (可选) 指示应匹配哪些图像对的掩码 |
从 cv::detail::FeaturesMatcher 重新实现。
◆ range_width_
int cv::detail::BestOf2NearestRangeMatcher::range_width_ |
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protected |
此类的文档是从以下文件生成的