Trait opencv::prelude::BinaryDescriptorMatcherTrait

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pub trait BinaryDescriptorMatcherTrait: AlgorithmTrait + BinaryDescriptorMatcherTraitConst {
    // Required method
    fn as_raw_mut_BinaryDescriptorMatcher(&mut self) -> *mut c_void;

    // Provided methods
    fn match_query(
        &mut self,
        query_descriptors: &Mat,
        matches: &mut Vector<DMatch>,
        masks: &Vector<Mat>
    ) -> Result<()> { ... }
    fn knn_match_query(
        &mut self,
        query_descriptors: &Mat,
        matches: &mut Vector<Vector<DMatch>>,
        k: i32,
        masks: &Vector<Mat>,
        compact_result: bool
    ) -> Result<()> { ... }
    fn radius_match_1(
        &mut self,
        query_descriptors: &Mat,
        matches: &mut Vector<Vector<DMatch>>,
        max_distance: f32,
        masks: &Vector<Mat>,
        compact_result: bool
    ) -> Result<()> { ... }
    fn add(&mut self, descriptors: &Vector<Mat>) -> Result<()> { ... }
    fn train(&mut self) -> Result<()> { ... }
    fn clear(&mut self) -> Result<()> { ... }
}

Expand description

Mutable methods for crate::line_descriptor::BinaryDescriptorMatcher

Required Methods§

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fn as_raw_mut_BinaryDescriptorMatcher(&mut self) -> *mut c_void

Provided Methods§

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fn match_query( &mut self, query_descriptors: &Mat, matches: &mut Vector<DMatch>, masks: &Vector<Mat> ) -> Result<()>

For every input query descriptor, retrieve the best matching one from a dataset provided from user or from the one internal to class

Parameters

queryDescriptors: query descriptors
trainDescriptors: dataset of descriptors furnished by user
matches: vector to host retrieved matches
mask: mask to select which input descriptors must be matched to one in dataset

Overloaded parameters

queryDescriptors: query descriptors
matches: vector to host retrieved matches
masks: vector of masks to select which input descriptors must be matched to one in dataset (the i-th mask in vector indicates whether each input query can be matched with descriptors in dataset relative to i-th image)

C++ default parameters

masks: std::vector()

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fn knn_match_query( &mut self, query_descriptors: &Mat, matches: &mut Vector<Vector<DMatch>>, k: i32, masks: &Vector<Mat>, compact_result: bool ) -> Result<()>

For every input query descriptor, retrieve the best k matching ones from a dataset provided from user or from the one internal to class

Parameters

queryDescriptors: query descriptors
trainDescriptors: dataset of descriptors furnished by user
matches: vector to host retrieved matches
k: number of the closest descriptors to be returned for every input query
mask: mask to select which input descriptors must be matched to ones in dataset
compactResult: flag to obtain a compact result (if true, a vector that doesn’t contain any matches for a given query is not inserted in final result)

Overloaded parameters

queryDescriptors: query descriptors
matches: vector to host retrieved matches
k: number of the closest descriptors to be returned for every input query
masks: vector of masks to select which input descriptors must be matched to ones in dataset (the i-th mask in vector indicates whether each input query can be matched with descriptors in dataset relative to i-th image)
compactResult: flag to obtain a compact result (if true, a vector that doesn’t contain any matches for a given query is not inserted in final result)

C++ default parameters

masks: std::vector()
compact_result: false

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fn radius_match_1( &mut self, query_descriptors: &Mat, matches: &mut Vector<Vector<DMatch>>, max_distance: f32, masks: &Vector<Mat>, compact_result: bool ) -> Result<()>

For every input query descriptor, retrieve, from a dataset provided from user or from the one internal to class, all the descriptors that are not further than maxDist from input query

Parameters

queryDescriptors: query descriptors
trainDescriptors: dataset of descriptors furnished by user
matches: vector to host retrieved matches
maxDistance: search radius
mask: mask to select which input descriptors must be matched to ones in dataset
compactResult: flag to obtain a compact result (if true, a vector that doesn’t contain any matches for a given query is not inserted in final result)

Overloaded parameters

queryDescriptors: query descriptors
matches: vector to host retrieved matches
maxDistance: search radius
masks: vector of masks to select which input descriptors must be matched to ones in dataset (the i-th mask in vector indicates whether each input query can be matched with descriptors in dataset relative to i-th image)
compactResult: flag to obtain a compact result (if true, a vector that doesn’t contain any matches for a given query is not inserted in final result)

C++ default parameters

masks: std::vector()
compact_result: false

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fn add(&mut self, descriptors: &Vector<Mat>) -> Result<()>

Store locally new descriptors to be inserted in dataset, without updating dataset.

Parameters

descriptors: matrices containing descriptors to be inserted into dataset

Note: Each matrix i in descriptors should contain descriptors relative to lines extracted from i-th image.

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fn train(&mut self) -> Result<()>

Update dataset by inserting into it all descriptors that were stored locally by add function.

Note: Every time this function is invoked, current dataset is deleted and locally stored descriptors are inserted into dataset. The locally stored copy of just inserted descriptors is then removed.

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